“MOLECULAR AND AGRO-MORPHOLOGICAL … · 2018-12-07 · short and 24 long grains length) rice germplasm accessions 88 4.3 Mean and Variability parameters for 33 yield and quality

“MOLECULAR AND AGRO-MORPHOLOGICAL

CHARACTERIZATION OF SELECTED RICE (Oryza sativa L.)

GERMPLASM ACCESSION BASED ON GRAIN LENGTH”

M. Sc. (Ag.) Thesis

by

SUMAN RAWTE

DEPARTMENT OF GENETICS AND PLANT BREEDING

COLLEGE OF AGRICULTURE

INDIRA GANDHI KRISHI VISHWAVIDYALAYA

RAIPUR (CHHATTISGARH)

2016

“MOLECULAR AND AGRO-MORPHOLOGICAL

CHARACTERIZATION OF SELECTED RICE (Oryza sativa L.)

GERMPLASM ACCESSION BASED ON GRAIN LENGTH”

Thesis

Submitted to the

Indira Gandhi Krishi Vishwavidyalaya, Raipur

By

SUMAN RAWTE

IN PARTIAL FULFILMENT OF THE REQUIREMENTS

FOR THE DEGREE OF

Master of Science

in

Agriculture

(Genetics and Plant Breeding)

Roll No. 120114118 ID No. 2014520336

JULY, 2016

iii

ACKNOWLEDGEMENT

I would like to take this opportunity to first and foremost thank God for being my

strength and guide in the writing of this thesis. Without Him, I would not have had the

wisdom or the physical ability to do so.

I take immense pleasure to express my sincere and deep sense of gratitude to my major

advisor Dr. Ritu R. Saxena, Associate Professor, Department of Genetics and Plant Breeding,

Indira Gandhi Krishi Vishwavidyalaya, Raipur (C.G.), for her sustained enthusiasm, creative

suggestions, motivation and exemplary guidance throughout the course of my master research.

She has gone beyond the call of a thesis advisor to assume the role of an academic mother, apart

from the subject of my research, I learnt a lot from her, which I am sure will be useful in

different stages of my life. I solemnly submit my honest and humble thanks to her for bringing

my dreams into reality.

I emphatically and gratefully acknowledge extend my loyal and venerable thanks to

members of my Advisory Committee, Dr. A.K. Sarawgi, Professor and Head, Department of

Genetics and Plant Breeding, Dr. N. Mehta, Principal Scientist (Linseed), Department of

Genetics and Plant Breeding, Dr. S.B. Verulkar, Professor and Head, Department of Plant

Molecular Biology and Biotechnology, Dr. R.R. Saxena, Professor (ADR), Department of

Agriculture Statistics and Social Science, College of Agriculture, IGKV, Raipur. They were

always ready to provide valuable guidance, regular encouragement and timely advice whenever

required for enriching with productive scientific discussion, during the most trying times in the

tenure of this research work.

I wish to record my grateful thanks to Dr. S. K. Patil, Hon’ble Vice Chancellor, Shri

K. C. Paikra, Registrar, Dr. J.S. Urkurkar, Director Research Services, Dr. S. S. Shaw,

Director of Instructions and Dr. S.S. Rao, Dean, College of Agriculture, IGKV, Raipur for

providing necessary facilities technical and administrative supports for conductance of this

research work.

I am immensely thankful to Dr. P. K. Chandrakar, Dr. N.K. Motiramani, Dr. R. N.

Sharma, Dr. H. C. Nanda, Dr. Nandan Mehta, Dr. P. K. Joshi, Dr. N. K. Rastogi, Dr. Rajeev

Shrivastava , Dr. Sandeep Bhandarkar, Dr. S. K. Nair, Shri P. L. Johnson, Dr. G. R. Sahu,

Dr. Ravindra K. Verma, Dr.(Smt.) Alice Tirkey, Shri Sunil K. Nag, Smt. Mangla Parikh, Dr.

iv

Bhawana Sharma, Dr. Mayuri Sahu, Dr.(Smt) Prabha R. Chowdhri, Ku. Krishna Tandekar,

for their co-operation and support during my work period for their encouragement and constant

help throughout course of my studies. I extend my thanks to other non-teaching staff of

Department of Genetics and Plant Breeding for their timely cooperation. I would like to

specially thanks to Smt. Pratibha Mohan, RA, Department of Plant Molecular Biology and

Biotechnology, COA, IGKV Raipur, for her kind help and valuable suggestions during the

course of investigation.

I would like to express my sincere gratitude to Dr. Madhav Pandey (Librarian, Nehru

Library, IGKV, Raipur) and all other members of the Nehru Library for giving me their kind

help during the study. My sincere thanks are extended to non- teaching staffs, Lime Dai, and

Radha didi of the Department of Genetics and Plant Breeding, Manish Bhaiya and Moti

Bhaiya, Department of Plant Molecular Biology and Biotechnology.

I sincerely acknowledge my seniors Mr. Hemant Sahu, Miss Namrata Dirhi, Miss

Pooja Yadav, Miss Nirmala Bharti Patel, Mr. Umesh Deshmukh, Mr. Vikas Kumar for their

support and encouragement in my studies and research work. It is with immense pleasure I

express my thankfulness to my batch mates Pratima, Anjali, Neelima, Meenu and many others

who helped me in several ways.

I am speechless! I can barely find words to express all the wisdom, love and support

given me for that I am eternally grateful to my beloved parents Mr. D. L. Rawte and Mrs.

Nirmala Rawte for their unconditional love, fidelity, endurance and encouragement. They have

been selfless in giving me the best of everything and I express my deep gratitude for their love

without which this work would not have been completed. My most cordial thanks goes to my

brothers, Dr. Deepesh Rawte, Lokesh, Saurabh and my family who have been the vital source

of inspiration that helped me to set higher for their blessings and inspiring thoughts throughout

my work. This thesis would not have been possible without the filial affection, obstinate

sacrifice, pampered support, sincere prayers and blessings of the biggest asset of my life.

Last but not least, I would like to convey my cordial thanks to all the teachers and

well wishers from my schooling days onwards who have directly and indirectly helped me to

reach upto this level in my life.

Raipur (SUMAN RAWTE) Dated : Department of Genetics and Plant Breeding College of Agriculture, I.G.K.V. Raipur (C.G.)

v

TABLE OF CONTENTS

Chapter Title Page

ACKNOWLEDGEMENT iii-iv

TABLE OF CONTENTS v-vi

LIST OF TABLES vii-viii

LIST OF FIGURES ix-x

LIST OF NOTATIONS xi

LIST OF ABBREVIATIONS xii

ABSTRACT xiii-xviii

I INTRODUCTION 1-5

II REVIEW OF LITERATURE 6-36

2.1 Agro-morphological characterization 7-9

2.2 Genetic variability 10-13

2.3 Association analysis 13-19

2.3.1 Correlation coefficient analysis

2.3.2 Path coefficient analysis

13-17

17-19

2.4 Principal component and cluster analysis 19-26

2.5 Quality parameter 26-29

2.6 Molecular characterization

29-36

III MATERIALS AND METHODS 37-67

3.1 Experimental site 37

3.2 Climate and weather 37

3.3 Experimental materials and methods 38

3.4 Observations recorded 38-54

3.5 Molecular Study 54-62

3.6 Statistical analysis 62-67

IV RESULTS AND DISCUSSION 68-165

4.1 Agro-morphological and quality characterization 69-86

4.2 Estimation of genetic variance 87-104

4.2.1 Analysis of variance

4.2.2 Mean performance and variability

87-88

vi

Chapter Title Page

parameters of different characters

4.2.3 Phenotypic and Genotypic coefficient of

variation

4.2.4 Heritability and genetic advance as percent

of mean

89-100

100-101

102-104

4.3 Association analysis 104-137

4.3.1 Correlation coefficient

4.3.2 Path coefficient analysis based on grain

yield

4.3.3 Path coefficient analysis based on HRR

104-114

128-137

4.4 Principal Component Analysis 138-145

4.5 Cluster Analysis 146-153

4.6 Molecular characterization 154-166

4.6.1 Development of genotypic data based on

SSR and ISSR Markers

155

4.6.1.1 SSR marker analysis

4.6.1.1a Similarity coefficient analysis and

Clustering

4.6.1.1b Polymorphism Information

Content of SSR markers

4.6.1.2 ISSR marker analysis

4.6.1.2a Similarity coefficient analysis and

Clustering

4.6.1.2b Polymorphism Information

Content of ISSR markers

155-161

157-158

159

162-166

162-164

165

V SUMMARY AND CONCLUSIONS 167-170

REFERENCES 171-189

APPENDICES 190-223

RESUME 224

vii

LIST OF TABLES

Table Title Page

3.1 Landraces and their origin 39

3.2 Scale for Amylose test 50

3.3 Alkali spreading value classification along with GT 50

3.4 Numerical scale for scoring Alkali spreading value 51

3.5 PCR mix for one reaction 55

3.6 Temperature profile used for PCR amplification using micro-

satellite Markers

56

3.7 Temperature profile used for PCR amplification using Inter-

simple sequence repeats Markers

56

3.8 Skeleton of analysis of variance 63

4.1 Frequency distribution of agro-morphological traits based on

DUS

74-76

4.2 Analysis of variance of 33 yield and quality traits of 48 (24

short and 24 long grains length) rice germplasm accessions

88

4.3 Mean and Variability parameters for 33 yield and quality

traits

90

4.3a List of germplasm categorized into early, medium and late

days to flowering

91

4.3b List of germplasm categorized into very short, short, medium

and long panicle length

92

4.3c List of germplasm categorized into very short, short, medium

and long grain length

94

4.3d List of germplasm categorized into very short, short, medium

and long grain length

98

4.3e List of germplasm categorized into soft, medium and hard

gel consistency

99

4.4 Genetic parameters of 33 yield and quality traits of 48 (24

short and 24 long grain length) rice germplasm accessions

101-102

4.5 Association analysis (phenotypic and genotypic) of 33 yield

and quality traits of 48 (24 short and 24 long grains length)

rice germplasm accessions

107-112

4.6 Direct and indirect effects of 33 yield and quality traits of 48

rice germplasm accessions based on grain yield

118-123

viii

Table Title Page

4.7 Direct and indirect effects of 33 yield and quality traits of 48

(24 short and 24 long grains length) rice germplasm

accessions based on HRR

130-135

4.8 Summarized data representing the direct effects of different

traits on grain yield and HRR along with correlation at

genotypic level

136

4.9 Eigen values of 33 yield and quality traits of 48 (24 short and

24 long grains length) rice germplasm accessions

139

4.10 Factor loading (Eigen vectors) of 48 (24 short and 24 long

grains length) rice germplasm accessions for yield and

quality characters

140

4.11 List of selected accession in each principal component on the

basis of top 10PC score

144

4.12 Principal component score of different accessions of grain

length in rice

145

4.13 Clustering patterns of 48 rice genotypes 146

4.14 Estimates of intra (diagonal and bold) and inter cluster

distances among ten clusters

147

4.15 Cluster mean for quantitative characters in 48 aromatic

landraces of C.G.

150-151

4.16 Percent contribution of each character 153

4.17 List of 59 microsatellite markers with their chromosome

locations, number of alleles, Allele size and PIC value found

among 48 rice accessions

156-157

4.18 List of 10 ISSR markers with their PIC value, No. of alleles

and percentage polymorphism found among 48 rice

accessions

163

ix

LIST OF FIGURES

Figure Title Page

3.1 Meteorological data recorded during crop growth season (26

June to 28 November, 2015)

137

3.2 Sowing of rice germplasm accession 40

3.3 Nurseries view 40

3.4 Field view of experiment 40

4.1 Frequency distribution of 28 polymorphic DUS traits 77-81

4.2 Coleoptile Colour 82

4.3 Basal of Sheath Colour 82

4.4 Leaf Auricle 82

4.5 Ligule 82

4.6 Width of blade 82

4.7 Flag leaf attitude of blade 82

4.8 Lemma Anthocyanin Colouration of keel 83

4.9 Lemma : Anthocyanin colouration below apex 83

4.10 Spkikelet : Colour of stigma 83

4.11 Stem : Anthocyanine colouration of node 83

4.12 Panicle curvature 83

4.13 Lemma and palea colour 83-84

4.14 Panicle Awn 84

4.15 Length of Awn 84

4.16 Panicle distribution of awn 84

4.17 Panicle : Secondary branching 84

4.18 Panicle exertion 84

4.19 Grain length 85

4.20 Decorticated grain length 85

4.21 Decorticated grain shape 85

4.22 Decorticated grain colour 85

4.23 Kernel length after cooking 85

4.24 Grain phenol reaction 85

4.25 Amylose test 86

x

4.26 Chalkiness 86

4.27 Alkali spreading value test 86

4.28 Gel consistency 86

4.29 Graph representing significant correlation between grain

yield as well as HRR with other traits

114-115

4.30 Screen plot showing eigen value and percentage of

cumulative

Variability

141

4.31 Distribution of genotypes among two different principal

component

141

4.32 Dendogram of 48 long and short grain accessions derived by

UPGMA from 33 yield and quality traits

148

4.33 An UPGMA cluster dendogram showing the genetic

relationships Among 48 long and short grain accessions of

rice based on the alleles detected by 59 SSR marker

159

4.34 Gel picture of PCR amplification of 48 rice accessions with

SSR primer RM22565 and RM520

160

4.35 Graphical representation of PIC value of SSR marker 161

4.36 An UPGMA cluster dendogram showing the genetic

relationships Among 48 long and short grain accessions of

rice based on the alleles detected by 10 ISSR marker

164

4.37 Gel picture of PCR amplification of 48 rice accessions with

ISSR primer UBC834 and UBC842

165-166

4.38 Graphical representation of PIC value of ISSR marker 166

xi

LIST OF NOTATIONS/SYMBOLS

% Per Cent

°C Degree Celsius

μl Micro Litre

bp Base Pairs

cm Centimeter

d.f. Degree of Freedom

et al. and others

g Gram

H2O Water

ha Hectare

HCl Hydrochloric Acid

i.e. that is

KCl Potassium Chloride

m Meter

M Molar

MgCl2 Magnesium Chloride

min Minutes

ml Milliliter

NaCl Sodium Chloride

ng Nanogram

rpm Rotations per Minute

U Units

xii

LIST OF ABBREVIATIONS

BYPP Biological Yield Per Plant

DTF Days To 50 % Flowering

dATP deoxy adenosine 5’ triphosphate

dCTP deoxy cytidine 5’ triphosphate

dGTP deoxy guanosine 5’ triphosphate

DNA Deoxyribo Nucleic Acid

dNTPs deoxynucleotide triphosphates

dTTP deoxy thymidine 5’ triphosphate

EDTA Ethylene Diamine Tetra Acetic Acid

EtOH Ethanol

EtBr Ethidium Bromide

EI Elongation Index

ET Effective Tillers Per Plant

FLL Flag Leaf Length

FLW Flag Leaf Width

GB Grain Breadth

GL Grain Length

GYPP Grain Yield Per Plant

HI Harvest Index

H % Hulling Per Cent

HRR % Head Rice Recovery Per Cent

KB Kernel Breadth

KBAC Kernel Breadth After Cooking

KER Kernel Elongation Ratio

KL Kernel Length

KLBR Kernel Length Breadth Ratio

KLAC Kernel Length After Cooking

LBRAC Length Breadth Ratio After Cooking

M % Milling Per Cent

NOS Number of Spikelet Per Panicle

PCV Phenotypic Coefficient of Variation

GCV Genotypic Coefficient of Variation

PCA Principal Component Analysis

PC Principal Component

PCR Polymerase Chain Reaction

PH Plant Height

PL Panicle Length

SSR Single Sequence Repeats

ISSR Inter Simple Sequence Repeat

TBE Tris Boric Acid EDTA Buffer

xiv

crop development and improvement programs. Grain length, width and thickness

are important factors relating to not only grain yield but also grain quality in rice.

So keeping these points in view, the present study was conducted with the

objective of characterization of accessions based on DUS descriptors and DNA

profiling using SSR and ISSR markers at Research cum Instructional farm, College

of Agriculture, IGKV, Raipur (C.G.), Department of Genetics and Plant Breeding

and R. H. Richhariya research laboratory, College of Agriculture, IGKV, Raipur

(C.G.) with 24 short and 24 long grain rice accessions in randomized block design

(RBD) during Kharif 2015. The data was statistically analyzed to calculate various

descriptive statistics and to perform Correlation analysis, Path coefficient, principal

component analysis (PCA) and the unweighted variable pair group method of the

average linkage cluster analysis (UPGMA) between 33 yield and other yield

attributing traits.

All considered morphological and quality descriptors showed remarkable

differences in their distribution and amount of variations within them. The analysis

of variance indicated existence of considerable amount of variability for all

observed characters. The high amount of genotypic and phenotypic coefficient of

variation with high heritability and genetic advance as percentage of mean was

observed for thousand grain weight followed by grain length, decorticated grain

length, length of milled grain, length of cooked kernel and elongation index.

Nagbel is the prominent germplasm accession which is having good quality

character namely grain length, thousand grain weight, decorticated grain length,

length of milled grain along with grain yield and harvest index. Thus, this

accession can be taken as a donor parent in crossing program to improve/enhance

these traits.

The result of correlation and path analysis revealed that the traits such as

biological yield, stem thickness, plant height, panicle per plant, time of maturity

and decorticated grain length had significant positive correlation with grain yield

as well as positive direct effect on grain yield per plant. Positive direct effect on

grain yield as well as significant positive correlation with grain yield indicates true

xv

relationship between them and direct selection for these traits will be rewarding for

yield improvement. PCA showed the contribution of each character to the

classification of the rice accessions. The first four principal components explained

about 63.74% of the total variation among the 33 characters. The results of PCA

suggested that characters such as plant height, thousand grain weight, grain length,

decorticated grain length, length of milled grain and length of cooked kernel were

the principal discriminatory characteristics of short and long grain accessions of

rice. On the basis of PC score it is cleared that Nagbel is the best accession for both

quality and yield traits followed by Khatriya Pati , Anjania and Banreg. Ten cluster

groups were obtained from the 33 yield and quality characters using multivariate

analysis. The pattern of constellation proved the existence of significant amount of

variability. Cluster VII constituted of 16 accessions, forming the largest cluster.

Since, the inter cluster distance between cluster IX (Safri) and cluster X (Nagbel)

is quite large therefore, they can be use to obtain higher variability and heterotic

effects.

A total of 59 SSR and 10 ISSR markers (primers) were used covering all

the 12 chromosomes of rice. A total of 199 and 46 alleles with an average of 3.37

and 2.9 alleles per locus were detected by SSR and ISSR markers, respectively.

Out of which 53 SSR and 8 ISSR markers showed polymorphism. Genetic

similarity coefficient ranged from 0.21-0.93 and 0.52-1.00 as revealed by UPGMA

cluster analysis of SSR and ISSR marker, respectively. Forty-eight accessions were

grouped into three major clusters having 22, 20 and 6 genotypes in SSR analysis

while two major clusters were formed in ISSR marker having 24 genotypes in each

cluster.

1

CHAPTER- I

INTRODUCTION

Rice (Oryza sativa L.) (2n = 24) belonging to the family, Poaceae and

subfamily, Oryzoidea is the staple food for half of the world‟s population and

occupies almost one-fifth of the total land area covered under cereals. It is one of

the very few crop species endowed with rich genetic diversity which account over

100,000 landraces and improved cultivars. Agro-morphological characterization of

germplasm variety is fundamental in order to provide information for plant

breeding programs (Lin, 1991).

Rice occupies a pivotal place in Indian agriculture and it contributes to 17

percent of annual GDP and provides 43 per cent calorie requirement for more than

70 per cent of the Indians. In India, it is cultivated on an area of 42.41 million

hectares which is maximum among all rice growing countries, annual production

of about 105.31 mt with productivity of 2393 kg/ha (Anon, 2013). The slogan

“Rice is life” is most appropriate for India as this crop plays a vital role in our

national food security and is a means of livelihood for millions of rural household.

Chhattisgarh state is eminent by the name “Rice Bowl of India” because

maximum area is covered under rice cultivation. The rich biodiversity of rice in

Chhattisgarh is the evidence of this fact. During Kharif, Chhattisgarh state covers

maximum area under rice crop and contributes major share in national rice

production. The state is completely dependent on monsoon, with an annual rainfall

of 1200-1600 mm. It has geographical area of 13.51 mha of which 5.9 mha area is

under cultivation. Rice occupies an area of 3.77 mha with the production of 6608.8

t and productivity of 1746 kg/ha of milled rice during 2012-13 (Anon, 2014).

Chhattisgarh state has received “Krishi Karman Award” (KKA) for

achieving higher rice production during the crop year 2013-14 with an average

production of 67.16 lakh tonnes and 1766 kg/ha productivity.

2

Grain size and weight contribute for crop yield in cereals, whereas in rice,

grain size and shape are major criteria to assess market value and to classify rice

genotypes. Grain size with its dimensions for length and width has become a target

trait for rice breeding in recent years (Xing and Zhang, 2010). Rice yield is

dependent on several factors, including number of plants per unit area, number of

grains per panicle and grain weight, which is largely determined by grain size

(Ikeda et al., 2013 and Xing et al., 2002). Grain size directly affects to rice yield

and is an important determinant of rice quality (Tan et al., 2000). Elucidating the

genetic mechanisms affecting grain shape has great significance to breed high-

yielding rice varieties. In recent years, much research has been devoted to the study

of identification, localization, cloning and functional analysis of genes involved

grain shape and great progress has been made (Miura et al., 2011). Enhancing

grain yield and quality are the two major objectives for many breeding programs.

Grain quality characteristics (grain length (GL), grain breadth (GB), cooked grain

length (CGL), cooked grain breadth (CGB) and gelatinization temperature (GT)) of

rice are related to a complexity of physicochemical properties viz., dimension,

shape and weight, fragmentation, hardness, milling properties, chemical

composition of the endosperm, aroma and nutritional factors. In breeding

programs, the major grain quality considerations are evaluated as (i) milling

efficiency; (ii) grain shape and appearance; (iii) cooking and edibility

characteristics and (iv) nutritional quality (Li et al., 2003).

The yield of rice increases due to breeding efforts but quality part of rice

still have to be improved, this is because the standard of living of the people are

also increased with the change of time. The poor people do not give much priority

to the quality of rice but rich people give more consideration to rice quality. In

cereals, rice has to be cooked and consumed as a whole grain therefore, quality

consideration is more important for any other food crop (Hossain et al., 2009).

Preferences for grain shape vary across different consumers. Long and

slender grain varieties are preferred in most Asian countries including China, USA,

Pakistan and Thailand, and also in the India, while short grain cultivars are

preferred in Japan and Sri Lanka. In addition, grain dimension is an important

indicator of the evolution of cereal crops because humans tended to select large

3

seeds during the early domestication, as evidenced by the fact that most cultivated

species have larger seeds than their wild relatives (Harlan 1992). However, small

seed is usually favoured by natural selection because it is frequently associated

with more seeds per plant, early maturity, and wider geographic distribution.

Therefore, from the standpoints of both biological development and breeding, it is

necessary to understand the genetic basis and formation mechanism of rice grain

shape (Wan et al., 2006).

Enormous variations in size and shape of grain exist among the rice

varieties available in the world. As grain quality is endospermic traits, its

inheritance become more complicated because genetic expression of endospermic

trait in cereals seed is not only conditioned by triploid endosperm genotype, but

also diploid maternal genotype and any additional by cytoplasmic difference

(Pooni et al., 1992; Zhu 1994). The size of a grain measured by weight of grain but

the grain length is more adequate character for analyzing the inheritance of grain

size because of high heritability of trait.

Since, rice grain length is quantitatively inherited (McKenzie and Rutger

1983), it is difficult for breeders to efficiently improve grain appearance using

conventional selection methods. Thus, it should be particularly helpful for

enhancing breeding efficiency to use markers closely linked to genes or major

quantitative trait loci (QTLs) for grain length in order to screen target genotypes

directly in early generations. In rice, numerous studies have been conducted to

genetically map QTLs for grain yield traits, and thousands of QTLs have been

detected. Grain size and shape are important determinants of grain yield and grain

quality, which are usually controlled by QTLs. More than 400 QTLs that control

grain size and shape have been detected by using various mapping populations

(Hao et al., 2010; Huang et al., 2013 and Yu et al., 2013).

Many QTLs for rice grain size traits have been reported in the last decade

(Gao et al, 2011; Huang et al, 2013). Among them, qGL3 (Zhang et al, 2012),

GW8 (Wang et al, 2012), GS5 (Li et al, 2011), GS3 (Fan et al, 2006; Mao et al,

2010), GW2 (Song et al, 2007), GW5 (Weng et al, 2008) and qSW5 (Shomura et

al, 2008) have been cloned, and gw3.1 (Li et al, 2004), qGL7 (Bai et al, 2010),

4

GS7 (Shao et al, 2012), Lk-4(t) (Zhou et al, 2006), gw8.1 (Xie et al, 2006) and

gw9.1 (Xie et al, 2008) have been fine mapped. Thus, understanding the genetic

and molecular basis of grain size is extremely important for rice improvement

programs. Utilization of molecular markers has greatly facilitated the investigation

of the genetic basis of complex quantitative traits. Molecular marker technique has

proved valuable in identification of loci involved in quantitative traits related to

grain quality characters and has provided insight into its complex relationship with

associated factors and their underlying genes are now far more accessible.

Agromorphological characterization gives the mark of identification which

distinguishes one genotype from other. Many studies on genetic diversity using

agro-morphological characterization have been conducted and it led to

identification of phenotypic variability in rice (Ogunbayo et al., 2005; Bajracharya

et al., 2006 and Barry et al., 2007). Traditionally, morphological traits are used to

determine genetic diversity and classify germplasm. However, this technique is a

low-level but powerful taxonomic tool which can be utilized for the preliminary

grouping of cultivars prior to their characterization using more robust marker

technologies. Moreover, this technique is cost effective, less time consuming, easy

to score and it does not need any technical knowledge. According to Din et al.,

(2010) scientific classification of the plant still relies on morphological traits.

Characterization and evaluation of diversity among traditional varieties will

provide plant breeders the information necessary to identify initial materials for

hybridization to produce varieties with improved productivity and quality (Thilang

et al., 2014). So, collection and characterization of this germplasm is not only

important for utilizing the appropriate attribute based donors in breeding

programmes, but is also essential in the present era for protecting the unique rice.

Several researches reported the use of agro-morphological markers in the study of

characterization of rice germplasm diversity.

Keeping in view the above facts, the present investigation entitled

“Molecular and agro-morphological characterization of selected rice (Oryza

sativa L.) germplasm accession based on grain length” has been planned and

was carried out at the Research cum Instructional farm, College of Agriculture,

IGKV, Raipur (C.G), Department of Genetics and Plant Breeding and R. H.

5

Richhariya research laboratory, College of Agriculture, IGKV, Raipur (C.G.)

during Kharif, 2015 with the following objectives:

1. DUS (Distinctiveness, Uniformity, and Stability) based characterization for

yield and yield parameters.

2. DNA profiling for long and short grain length using SSR markers.

3. DNA profiling for long and short grain length using ISSR markers.

6

CHAPTER- II

REVIEW OF LITERATURE

Genetic variability, nature and magnitude of genetic diversity, present in

the available breeding materials are the key resource of a breeding program. Those

criteria create the opportunities for a successful breeding program by the

association of different traits both at physio-morphological and molecular levels.

People in different areas of the world prefer different types of rice for general

consumption. Grain quality characteristics of rice are related to a complexity of

physicochemical properties viz., dimension, shape and weight, fragmentation,

hardness, milling properties, chemical composition of the endosperm, aroma and

nutritional factors. Grain length and shape determine appearance in rice, and affect

milling, cooking and eating quality and are therefore, important traits in rice

breeding. On that point of view, this study was conducted for characterization of

forty eight landraces of rice of Chhattisgarh using agro-morphological and

molecular parameters to provide useful information to facilitate the choice of

breeders for rice plant breeding programme.

In this chapter, an attempt has been taken to review the relevant literatures,

which focuses the basic features of rice plant and associated genetic variability,

nature and magnitude of genetic divergence, association among different traits,

evaluation of field performance and diversity analysis through SSR and ISSR

markers in rice under the following subheads:

2.1 Agro-morphological characterization

2.2 Genetic variability

2.3 Association analysis



2.4 Principal component and cluster analysis

2.5 Quality parameter


7

2.1 Agro-morphological characterization

Subba Rao et al. (2001) reported that genetic diversity probably serves as

an insurance against crop failure.

Ogunbayo et al. (2005) characterized forty rice accessions using fourteen

agro-botanical traits. Number of effective tillers and total number of tillers as well

as heading and maturity dates were observed to greatly influence grain yield.

Significant block effects were observed for flowering date, maturity day and plant

height whereas block effects were non-significant for the other traits meaning that

blocking was not important for the eleven traits that showed non-significant block

effects.

Hien et al. (2007) studied Genetic diversity of morphological responses and

the relationships among Asia aromatic rice (Oryza sativa L.) cultivars.

Characterization for 22 morphological characters with 101 morphometric

descriptors was carried out. Most traits were polymorphic except to ligule color.

Grain size, grain shape, culm strength, plant height and secondary branching

contributed the highest mean diversity indices (H, = 0.91, 0.88, 0.87, 0.82 and

0.83, respectively). For trait groups, highest diversity was found in grain and culm

traits (H, = 1.00 and 0.96, respectively). Populations from Vietnam were more

diverse than others (H, = 0.92) whereas populations from India and Thailand

displayed lower diversity indices (H, = 0.46 and 0.49, respectively). No clear

association was detected between phenotypic diversity and countries of origin.

Five clusters of 36 genotypes based on Euclidean distance were observed with 1 to

22 cultivars per group.

Vanisree et al. (2011) worked in Sugandha Samba (RNR2465), first-ever

highyielding, aromatic, short-grained rice. Sugandha Samba (RNR2465) was the

first aromatic, high-yielding, semi-dwarf, medium-duration (130–135 d), medium-

slender rice variety released in Andhra Pradesh by the State Variety Release

Committee in April 2010. Developed using the pedigree method, this variety has

two quality rice varieties, early samba (RNR-M7) and RNR19994, as the female

and male parent, respectively. This variety recorded a grain yield of 6–7 t ha–1

under good management, comparable with that of Samba Mahsuri (BPT5204), the

8

most popular mega-variety released by ANGRAU. It registered 70% head rice

recovery and had excellent cooking quality and strong aroma.

Subudhi et al. (2012) studied Collection and agro-morphological

characterization of aromatic short grain rice in eastern India. The good yielders are

Chhotbasmati, Pimpudibas, Lajkuri, Jaigundi, Kanika, Bishnubhog. These

landraces can be popularized among the farmers and can be used as donor in

varietal development programme.

Parikh et al. (2012) evaluated physio-chemical characters and cooking

quality of 36 rice genotypes and reported that the fine grain genotypes like Rajim-

12, Kalimuchh, and Munibhog were good for moderate kernel length and L:B

ratio; Rajabhog, Jhulari, and Baghmuchha for kernel length after cooking and L:B

ratio of cooked rice Kalajira and Bikoni for head rice recovery %; Barang,

Bantaphool, Gangabalu, and Bikoni for elongation ratio; Barang, Rajabhog,

Gangabalu, Bikoni, and Chirainikhi for elongation index; Sonth, Rajim-12, Jhulari,

Gangabalu, Jhilli Safri, and Bikoni for intermediate alkali values. These genotypes

may be utilized as donors for improvement of quality traits.

Sarawgi et al. (2012) characterized 46 aromatic rice accessions of Dubraj

group from Chhattisgarh and Madhya Pradesh for twenty morphological, six

agronomical and eight quality characters. The specific accessions D: 1137, D: 812,

D: 950, D: 959, D: 925, D: 1008, D: 939, D: 666I and D: 1090 were identified for

quality and agronomical characteristics. These may be used in hybridization

programme to achieve desired segregants for good grain quality with higher yield.

Subba Rao et al. (2013) characterized 65 landraces of rice using 43

agromorphological traits following Distinctiveness, Uniformity and Stability test

(DUS). Out of 65 varieties studied, 32 were found to be distinctive on the basis of

22 essential and 24 additional characters. This study will be useful for breeders,

researchers and farmers to identify and choose the restoration and conservation of

beneficial genes for crop improvement and also to seek protection under Protection

of Plant Varieties and Farmer‟s Rights Act.

Mondal et al. (2014) reported the descriptors offering the most

discrimination were time to 50% heading, decorticated grain shape, and the color

9

of lemma and palea, Eight of the 21 qualitative and 8 of the 14 quantitative traits

exhibited uniformity as determined by UPOV-recommended levels. Twelve of the

quantitative traits were relatively stable as judged by seasonal variation in

Phenotypic Coefficient of Variation (PCV) and Genotypic Coefficient of Variation

(GCV) values.

Sarawgi et al. (2014) on the basis of frequency distribution for eighteen

qualitative traits of 408 rice germplasm accessions reported that majority of

genotypes possessed green basal leaf sheath colour (87.25 %), green leaf blade

colour (89.70 %), pubescent leaf (48.03 %), well panicle exsertion (57.10 %),

white stigma colour (65.93 %), straw apiculus colour (78.18 %), compact panicle

type (55.63 %), awnless (88.48 %), white seed coat (82.84 %), straw hull colour

(70.34 %), intermediate threshability (47.30 %), erect flag leaf angle (57.59 %),

medium leaf senescence (67.15 %) and straw sterile lemma (97.05 %).

Sajid et al. (2015) has characterized thirty indigenous rice germplasm on

the basis of 32 different agro-morphological traits (15 qualitative and 17

quantitative). Highly significant differences (p<0.01) were observed for the traits

of flag leaf length, flag leaf breadth, culm length, days to 50% flowering, panicle

length, length of primary branches panicle-1

, secondary branches panicle-1, grain

length, grain width, awn length and percent leaf lession while significant

differences (p<0.05) were observed for peduncle length and primary branches. The

rice germplasm exhibited sufficient genetic variation for most of the qualitative

and quantitative traits.

Sinha et al. (2015) has studied fifty five traditional rice varieties of West

Bengal, and investigated for grain morphological characters. A wide variation of

grain characters, like grain size and shape, anthocyanin colouration of lemma-palea

and kernel, presence or absence of aroma, awning characteristics, were found

among the studied varieties. Wide variation among the grain morphological

characters indicated wide genetic variation present among these varieties, which

may be utilized for the selection of the parents for the plant breeding and

production of new improved variety.

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2.2 Genetic Variability

Choudhary et al. (2004) studied genetic variability and genetic advance for

plant traits viz., kernel length, panicle length, effective tiller per plant, fertile

spikelets per panicle, spikelet density, biological yield per plant, harvest index and

grain yield per plant. All these traits exhibited high heritability coupled with high

genetic advance and genetic variability.

Veni and Rani (2006) studied variability and heritability for seven

important physico-chemical traits viz., kernel length, kernel breadth,

length/breadth ratio, kernel length after cooking, elongation ratio, alkali spreading

value and amylose content. Low to moderate estimates of variability (both at

genotypic and phenotypic level), moderate to high heritability and low expected

genetic advance for all the characters indicated the preponderance of both additive

and non-additive gene effects in conditioning these traits.

Sarkar et al, (2007) evaluated 41 genotypes of rice for ten different quality

parameters of grains to asses the genetic variability and revealed that genotypic

and phenotypic coefficient of variations were maximum for cooked kernel L/B

ratio and 1000-grain weight.

Bajpai and Singh (2010) studied the grain quality of some short and

medium grain aromatic rice and compared with premium Dehradun basmati 3020.

The quality characteristics studied from consumer's point of view revealed that

paddy length ranged from 6.8 mm to 7.4 mm. Kernel length ranged from 9.3 mm

to 11.0 mm, elongation ratio ranged from 1.86 to 2.34, amylose content recorded

was from 20.6 % to 25.5 %. The gelatinizing temperature was low in all lines

except 3047 (intermediate) while aroma was strong in all lines except 3047, which

revealed moderate aroma. The parameters studied from farmers/traders point of

view revealed that hulling percentage ranged from 78.6 % to 81.6, milling

percentage ranged from 72 % to 75 % while panicle length recorded ranged from

24.2 cm to 31.0 cm. From consumers point of view expect paddy length and kernel

elongation all quality parameters of these line were near to premium Dehradun

basmati 3020.

11

Das and Ghosh (2011) characterize thirty one qualitative traits of four

hundred thirty one traditional rice cultivars from germplasm collection of Rice

Research Station, Chinsurch. Among the qualitative traits considerable variability

was recorded for basal leaf sheath color, awning and auricle color. Maximum

variability was observed for grains per panicle followed by spikelet per panicle.

Parikh et al. (2011) evaluated seventy one rice accession and studied

diversity pattern among genotype. The genotypes were grouped into eight clusters.

The genotypes in these clusters i.e. Tulsi Mala (cluster II), Kali Kamod (cluster

VI), Shankar Jeera and Bhata Dubraj (cluster VII) and Lohandi and TilKasturi

(cluster VIII) can be used as potential donors for future hybridization programs to

develop genotype with high grain yield.

Chakravorty et al. (2013) studied fifty-one landraces of rice to characterize,

evaluate and work out the interrelationship among the 18 agro-morphological traits

with a view to exploiting them directly in the field and forming a base for using

these landraces in breeding program. The analysis of variance found significant

variability in eighteen quantitative traits. Leaf length had mean value of 47.47 cm

with a wide variation from 34.0 cm to 61.0 cm. Most of the lines (58.8 %) were in

the range of 44.0-53.0 cm. The highest leaf breadth value (2.20 cm) was observed

in Rupsal and Sitasal. Maximum plant height (43.0 cm) was observed in variety

Sarkele aman, while minimum (24.0 cm) in Tolsibhog.

Kumari et al. (2013) evaluated twelve accessions of rice for physical and

biochemical traits and observed highest kernel length in NDR 6265 (7.07 mm) and

kernel breadth in NDR 625 (1.81 mm). Maximum elongation ratio was observed in

Kankjeer and Banta Phool A (1.88 mm) and kernel length after cooking was

maximum in NDR 6265(11.4 mm). Maximum amylose content was found in

variety Kalanamak Berdpur (19.8 %). On the basis of above parameters variety

Kalanamak Berdpur, Badshah pasonda, NDR 6265 and NDR 625 were rated

superior among the all varieties/accessions tested in the present investigation.

Phenotyping of the 41 rice genotypes was done by Pachauri et al. (2013)

for grain quality characters viz., grain length, grain breadth, length breadth ratio,

elongation ratio, alkali spreading value and aroma. The longest grain length

12

(unmilled and milled) was recorded as 11.67±0.4 mm and 8.2±0.38 mm

respectively for SS20, while Sulendas had shortest grain length of 6.93±0.37 mm

and 5.07±0.15 mm respectively. Diverse L: B ratio (unmilled grain) was observed,

ranging from 2.29±0.24 mm (Suranit) to 5.66±0.22 mm (SS20). Highest kernel

elongation ratio was observed in Kakeria-2 (1.608±0.19), while SHPP-20 showed

the lowest elongation ratio of 1.078±0.06. Most of the rice varieties had an ASV of

2 and 1. Sensory analysis of grain aroma revealed the range of sensory scores

between 0 and 3. Highly aromatic varieties such as Tilakchandan and Basmati-334

having a sensory aroma score of 3 as well as moderately aromatic varieties with a

sensory score of 2 had been identified along with some non-aromatic and less

aromatic varieties.

Vanisree et al. (2013) investigated fifty genotypes comprising both basmati

and aromatic short grain types and revealed significant differences among

genotypes for yield, its components and grain quality traits. The high variability

was observed for productive tillers per plant and filled grain per panicle whereas,

the estimates for panicle length, days to 50 % flowering, kernel breadth and kernel

elongation ratio were low.

A population panel of 192 rice genotypes comprising traditional landraces

and exotic genotypes was evaluated for twelve agro - morphological traits by

Nachimuthu et al. (2014) to determine the pattern of genetic diversity and

relationship among individuals. The largest variation was observed for number of

productive tillers with coefficient of variation (CV) of 28.03 % followed by

number of filled grains per panicle, single plant yield, leaf length , grain length

width ratio. Days to maturity has shown the least variation with the CV of 9.74 %.

Tuhina-Khatun et al. (2015) evaluated forty-three genotypes all genotypes

exhibited a wide and significant variation for 22 traits. The highest phenotypic and

genotypic coefficient of variation was recorded for the number of filled

grains/panicle and yields/plant (g). The highest heritability was found for

photosynthetic rate, transpiration rate, stomatal conductance, intercellular CO2, and

number of filled grains/panicle and yields/plant (g). Cluster analysis based on 22

traits grouped the 43 rice genotypes into five clusters. Cluster II was the largest and

13

consisted of 20 genotypes mostly originating from the Philippines. The first four

principle components of 22 traits accounted for about 72% of the total variation

and indicated a wide variation among the genotypes.

Lingaiah et al. (2015) conducted experiment to estimate the genetic

variability parameters for the quantitative characters in mid early group genotypes

of rice cultivars. The analysis of variance revealed significant difference among the

genotypes for the traits studied indicating that a large amount of variability was

present in the material. The magnitude of phenotypic co-efficient of variation was

higher to genotypic co-efficient of variation for all the traits.

Rahman et al. (2016) have studied the response to selection and estimate

the heritability for grain yield and yield components in F2 segregating populations

of rice. Among F2 populations, high heritability and genetic advance values were

observed for spikelet panicle‑1 (0.99 and 67.9), grain length (0.78% and 1.42),

100‑grain weight (0.73% and 0.83), biological yield plant‑1 (0.93% and 33.8),

grain yield plant‑1 (0.94% and 19.0) and harvest index (0.94% and 25.2). The

genetic potential of Dilrosh, TN‑1 and Kangni‑27 for yield and yield associated

traits could be exploited in future rice breeding program.



Grain yield of plant is influenced by a number of components, either

directly or indirectly. Contribution of each character towards increase in grain

yield varies from crop to crop. Correlation coefficient is therefore used to measure

the mutual relationship between various plant characters and to determine the

component characters on which selection can be based for genetic improvement in

the yield.

Madhavilatha et al. (2005) reported positive and significant association of

grain yield per plant with days to 50 % flowering, plant height, number of effective

tillers per plant, panicle length, number of grains per panicle, harvest index and

1000 grain weight.

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Satyanarayana et al. (2005) observed positive association of grain yield per

plant with spikelet fertility, panicle length, number of grains per panicle and

number of effective tillers per plant.

Muthuswamy and Ananda Kumar (2006) reported significant positive

correlation of grain yield per plant with the characters viz., plant height, number of

effective tillers per plant, panicle length, number of grains per panicle, spikelet

fertility and 1000 grain weight.

Girish et al. (2006) reported positive and significant association of grain

yield per plant with plant height, panicle length, number of spikelets per panicle,

number of tillers per plant, biological yield, harvest index and grain breadth.

Agahi et al. (2007) estimated correlations among the traits to find out

association and showed that the grain yield was significantly correlated with days

to heading, total tillers, number of productive tillers, days to maturity, number of

grains per panicle and plant height.

Gnanasekaran et al. (2008) reported positive correlation between grain

yield and length-breadth ratio. Kernel length and Kernel breadth, respectively had

positive and negative correlations with length breadth ratio was reported by

Mahala et al. (2008).

Khan et al. (2009) reported significant and positive correlation of grain

yield per plant with plant height, panicle length, flag leaf width, number of grains

per panicle.

Chakraborty et al. (2010) revealed significant positive correlation of grain

yield per plant with plant height, number of panicles per plant, panicle length,

number of filled grains per panicle and harvest index.

Nandan et al. (2010) revealed strong positive association of yield with days

to 50 % flowering, plant height, number of grains per panicle, number of spikelets

per panicle and spikelet fertility.

Mia et al. (2010) observed highly significant negative correlation between

grain aroma and gelatinization temperature. However, positive correlation was

observed between grain aroma and kernel elongation by Golam et al. (2010).

15

Sanni et al. (2010) reported positive associations between the grain weight

and grain width, and grain length indicate that the wider and/or longer the grain,

the heavier it is. The highly positive correlation between total number of tillers and

fertile tillers showed that the fertile tillers tend to increase along with the total

number of tillers. However, grain length had been found highly significant and

positive association with grain length width ratio.

Ekka et al. (2011) on the basis of association analysis reported that grain

yield per plant had positive significant correlation with leaf width, days to 50 %

flowering, plant height, panicle length, number of filled grains per panicle, 100

seed weight and paddy (grain) length. A positive and significant correlation of

head rice recovery percentage was also observed with leaf length, leaf width, days

to 50 % flowering, number of filled grains per panicle, spikelet sterility % and

milling %.

Ambili and Radhakrishnan (2011) reported significant and positive

correlation of grain yield per plant with plant height, total number of tillers per

plant, number of productive tillers per plant, panicle length, straw yield and harvest

index. At genotypic level yield was positively and significantly correlated with

days to flowering and number of spikelets per panicle

Chakravorty and Ghosh (2012) reported positive and significant association

of plant height with panicle length and grain weight. At genotypic level, kernel

weight was correlated positively and significantly with maturity, grain weight,

grain length, grain breadth and flag leaf angle.

Chakravorty et al. (2013) studied fifty-one landraces of rice to work out the

interrelationship among the 18 agro-morphological traits and found all the traits

except ligule length, culm length, number of grains per panicle and number of

primary branches per panicle exhibited positive and significant correlation

coefficients with kernel weight. Leaf length was positively and significantly

correlated with leaf breadth, plant height and culm length.

Seraj et al. (2013) revealed significant and positive association of grain

aroma with grain length width ratio; significant and negative association with grain

width, gelatinization temperature, and with grain length. Gelatinization

16

temperature had significant and negative correlation with grain length, grain length

width ratio, significant and positive association with grain width. Grain length had

significant and negative correlation with grain width; significant and positive

correlation with length width ratio.

Sinha and Mishra (2013) reported that days to 50 % flowering was highly

correlated with maturity time and also correlated with stem length. Panicle length

was negatively correlated with 100 grain weight. Panicle number shows maximum

correlation with grain length. 100 grain weight shows maximum of correlation

with grain length, grain width, kernel width and kernel length. Grain length and

grain weight possesses maximum correlation with kernel length and kernel weight

respectively. Stem length was highly correlated with length of blade, showing the

morphogenetic compatibility in the architectural configuration of rice plant.

Vanisree et al. (2013) studied association analysis of fifty genotypes

comprising both basmati and aromatic short grain types and revealed that grain

yield was significantly associated with harvest index, plant height, days to 50 %

flowering, panicle length, number of grains per panicle and filled grain per panicle.

Rashid et al. (2014) reported highly significant and positive association of

the traits days to heading, days to maturity, number of productive tillers, 1000-

grain weight with grain yield per plant whereas flag leaf area, plant height and

panicle length showed highly significant negative correlation with grain yield per

plant. Number of grains per panicle was non significant positively correlated with

grain yield per plant.

Sohgaura et al. (2014) reported positive and significant association of grain

yield per plant with number of spikelets per panicle, panicle weight per plant,

kernel elongation ratio, head rice recovery % and number of leaves per plant,

indicated that these are primary yield contributing traits and selection for above

traits might be utilized as inbred for production of hybrids in rice.

Islam et al. (2015) evaluated twenty three rice genotypes including three

check varieties Grain yield was found to be positively and significantly correlated

with filled grain per panicle, plant height, days to 50% flowering and days to

17

maturity both at genotypic and phenotypic levels, indicating the importance of

these traits for yield improvement in rice.

Naseer et al. (2015) studied twenty four Asian accessions of rice Plant yield

was positively and significantly correlated with filled grains weight per panicle,

number of grains per panicle, 1000-grain weight and spikelet fertility percentage at

genotypic and phenotypic levels. Thus, these traits could play pivotal role in the

development of high yielding rice genotypes.

Al-Salim et al. (2016) evaluate the performance of different ten genotypes

of bread rice under irrigated field conditions. The results indicated the existence of

genetic variability, in a significant manner (at the level 5%). The study showed the

importance of the Panicle Length due to its positive and high significant

correlation with the grain yield, so it can be used as indicator of suitable selection

for the development of high-yielding genotypes. Results also showed that

correlation between grain yield and plant height was negative and significant.


Path coefficient analysis measures the direct and indirect contributions of

independent variables on dependent variable. Though, the correlation coefficients

depict the nature of association among the characters, it is the path analysis that

splits the correlation coefficients into direct and indirect effects thus specifying the

relative contribution of each character. It further reveals the different ways in

which character influence the dependent variable.

Bhagat (2007) reported positive direct effect of number of tillers per plant,

number of productive tillers per plant, panicle length, panicle weight per plant,

panicle index, number of spikelets per panicle, number of filled grains per panicle,

1000 grain weight, biological yield per plant and harvest index on grain yield per

plant.

The highest positive direct effect of number of productive tillers on grain

yield was reported by Agahi et al. (2007) however, the greatest direct effect of

filled grains per panicle on the grain yield was reported by Gnanasekran et al.

(2008).

18

Nandan et al. (2010) reported that the number of grains per panicle had

maximum direct effect on grain yield per plant followed by kernel length after

cooking (KLAC), days to 50 % flowering, hulling percentage, plant height, harvest

index and kernel breadth after cooking (KBAC).

Wattoo et al. (2010) reported that the days to maturity had highest direct

effect on grain yield per plant. In addition, the yield components had positive direct

effect on grain yield except the days to heading.

Ambili and Radhakrishnan (2011) reported highest positive direct effect of

plant height on grain yield. This was followed by number of productive tillers per

plant, straw yield, harvest index and total number of tillers per plant. The highest

negative direct effect on yield was obtained for days to flowering. So it can be

concluded that yield of rice can be improved by selecting medium tall genotypes

having more number of productive tillers per plant, higher straw yield and an

optimum duration.

Selvaraj et al. (2011) reported that the test weight exhibited maximum

positive direct effect on grain yield per plant followed by filled grains per panicle,

plant height, panicle length, number of tillers per plant and days to 50 % flowering

and they contributed primarily to yield and could be relied upon for selection of

genotypes to improve genetic yield potential of rice.

Ravindra Babu et al. (2012) reported that panicle length had the highest

positive direct effect on grain yield. Grain yield linearly correlated with panicle

length, the number of panicle per plant, and the number of filled grains per panicle.

Therefore, these traits may be used in the selection for grain yield in rice.

Naseem et al. (2014) reported that the number of productive tillers per

plant, number of spikelets per panicle, number of grains per panicle and days to

maturity had positive direct effect on grain yield per plant.

Sarawgi et al. (2015) reported that the leaf length, leaf width, days to 50%

flowering, effective tiller, plant height, panicle length and days to maturity had

positive direct effect on grain yield per plant. These characters could be used as

direct selection criterion for higher grain yield.

19

Hossain et al. (2015) evaluated Thirty five local aman rice varieties for

their variability with regards to yield and yield components. Yield was observed to

be positively associated with panicle bearing tillers and number of filled grains per

panicle and these characters were noticed to exert high direct effects on grain yield

per plant. High indirect effects of most of the traits were noticed mostly through

panicle bearing tillers per hill indicating importance of the trait as selection criteria

in crop yield improvement programs.

Ratna et al. (2015) studied Correlation and path coefficients analyses

among fourteen morphological Characters in six advanced lines of Basmati rice

and one commercial check. Path coefficient analysis revealed highest positive

direct effect of number of filled spikelets/panicle on grain yield but plant height

and number of unfilled spikelets/panicle had negative direct effect on grain.

Islam et al. (2015) evaluated twenty three rice genotypes including three

check varieties the path coefficient analysis, revealed that days to maturity, days to

50% flowering, plant height, number of filled grain per panicle and grain length

had direct positive effect on yield, indicating these are the main contributors to

yield. Eventually, it was recommended that, for obtaining increased rice yield, a

genotype should possess more number of filled grains per panicle.

Singh et al. (2016) The phenotypic path-coefficient analysis in fourteen

quantitative traits of upland rice (Oryza sativa L.) showed that the total number of

grains per panicle had maximum direct effect on the grain yield per plant followed

by spikelet fertility percentage. The filled grains per panicle and total number of

grains per panicle exhibited high positive and significant association with grain

yield per plant, due to high direct and indirect effect of total number of grains per

panicle on grain yield per plant.

2.4 Principal component and cluster analysis

Multivariate statistical tools have found extensive use in summarizing and

describing the inherent variation among crop genotypes. One of the tools includes

Principal Component Analysis (PCA). This technique identifies plant traits that

20

characterize the distinctness among selected genotypes. These are often extended

to the classification of a population into groups of distinct orders based on

similarities in one or more characters, and thus guide in the choice of parents for

hybridization (Nair et al., 1998). Cluster analysis is also a multivariate method

which aims to classify a sample of subjects (or objects) on the basis of a set of

measured variables into a number of different groups such that similar subjects are

placed in the same group.

Zhang et al. (2004) studied principal component and correlation analyses to

test the quality characteristics of 89 japonica rice varieties. Principal component

analysis showed that brown rice rate, milled rice rate, length: width, chalkiness,

gelatinisation temperature and gel consistency should be taken as the principal

properties for estimating rice quality.

Rashid et al. (2008) in order to identify the major characters which account

for variation among Basmati rice mutants used Single Linkage Cluster Analysis

(SLCA) and Principal Component Analysis (PCA). The first three PCs with

eigenvalues > 1 contributed 78.7 % of the variability among the genotypes. Four

characters were positive to PC3 than PC2 and PC1. Productive tillers per plant and

panicle fertility contributed maximum in PC3.

Yang et al. (2009) classified ten agronomic traits of 98 accessions of

upland rice using PCA and showed that there was remarkable variance among

traits of the accessions. Ten agronomic traits of the accessions could be classified

into four principal components with cumulative proportion of 77.03 %. The first

principal component was determined by spikelets per panicle, total grains per

panicle. The second was determined by effective tillers per plant, 1000-grain

weight and panicle length. The third mainly represented yield per plant, and the

fourth reflected grain and growth period of the accessions.

Li et al. (2010) carried out principal component analysis and clustering of

46 introduced black pericarp rice cultivars based on 8 agronomic traits. On the

basis of principal components, these 46 black rice varieties were divided into three

groups for 4.19 Euclidean distances. The characters of the first group were late

maturity, high stalk, moderate spikes and many grains; and the second group had

21

the characteristics of early maturity, medium stalk, long spike, and weighty grains;

the third group was type of late maturity, high stalk, many spikes, many and light

grains.

Anandan et al. (2011) assessed diversity of 44 rice genotypes from

different geographic regions using Mahalanobis D2 and Principal Component

Analysis (PCA). The PCA revealed that axes 1 and 2 accounted for 82.88 % and

11.14 % of the variance, respectively. The highest contributing variable was the

number of grains per panicle in PC1 and the plant height in PC2. Both D2 and

PCA revealed that the morphometric diversity was based on the pedigree and

independent of geographical origin.

Ashfaq et al. (2012) performed PCA for twelve morphological traits and

reported four principal components out of twelve which exhibited more than one

Eigen value and showed about 67.7 % variability. The PC1 was more related to

plant height, panicle length, primary branches per panicle, number of spikelets per

panicle, number of seed per panicle, seed weight per panicle, plant yield, heading

days and maturity days so, it must be considered. In PC2 the primary branches,

seeds per panicle, seed weight per panicle, 1000 grain weight and plant yield were

more related traits. The PC3 exhibited positive effect for plant height, panicle

length, flag leaf area, primary branches per panicle and 1000 grain weight. The

PC4 was more related to number of spikelets per panicle, 1000 grain weight,

heading days and maturity days. Based on first our PCs it was cleared that the 1000

grain weight, number of spikelets per panicle, primary branches per panicle,

number of seeds per panicle and seed weight per panicle had high weightage value

and number of tillers had lowest value.

Chanbeni et al. (2012) reported nine clusters using by considering 13

quantitative characters in 70 rice genotypes. Cluster I and cluster III constituted

maximum number of genotypes (12 each). The genotypes falling in cluster VII had

the maximum divergence, which was closely followed by cluster V and cluster I.

The inter cluster distance was maximum between cluster VI and VII followed by

cluster III and IX, suggesting that the genotypes constituted in these clusters may

be used as parents for future hybridization programme. Traits like spikelets per

22

panicle; plant height and biological yield were the major contributors to genetic

divergence.

Chakravorty et al. (2013) studied 51 landraces of rice to determine the

nature and magnitude of the variability among the genetic materials, and the

intensity of relationships among the traits using multivariate tools. They identified

six principal components with Eigen value greater than 1.0 and that explained 75.9

% of the total cumulative variance within the axes could effectively be used for

selection among them. In PC1, the traits that accounted for most of the 23.47 %

observed variability among 51 genotypes included leaf length, plant height, culm

diameter, culm number and panicle length. PC2 is related to leaf width, ligule

length, number of primary branches per panicle and number of grains per panicle.

PC3 was more related to grain breadth and grain length: breadth ratio. PC4 was

related to flag leaf angle, maturity and sterile lemma length. PC5 included grain

length while PC6 was related to culm length. Thus, principal component analysis

revealed that six quantitative characters viz., leaf length, culm number, culm

diameter, number of grains per panicle, grain length: breadth ratio and grain length

significantly influenced the variation in these cultivars. Clustering pattern using the

first two principal components permitted the separation 51 landraces of rice into

ten major clusters from diverse geographical location, suggesting environmental

adaptation of the landraces.

Kumar et al. (2013) reported five Principal Components (PCs) exhibited

more than 1.8 Eigen value and showed about 68.34 % variability on the basis of

principal component analysis. The PC1 showed 25.81 %, while PC2, PC3, PC4

and PC5 exhibited 17.22 %, 9.56 %, 8.58 % and 7.16 % variability respectively,

among the RILs for the traits under study. Rotated component matrix revealed that

each principal component separately loaded with various yield and quality

attributing traits. The PC1, PC2, PC3 and PC5 mostly related to yield attributing

traits whereas PC4 related to quality traits. As PC1 was constituted by most of the

yield attributing traits, an intensive selection procedures can be designed to bring

about rapid improvement of dependent traits i.e., grain yield by selecting the lines

from PC1. Similarly, for quality aspect a good breeding programme can be

initiated by selecting the lines from PC4. PC scores of RILs in these five PCs

23

suggested that RIL 2-36 is the best for yield attributing traits whereas RIL 2-52 for

quality traits. These selected RILs may be used as inbred in production of hybrid in

rice. However, RIL 2-50 is the best for both yield and quality traits, which can be

used directly for cultivation.

Meti et al. (2013) studied the cluster pattern by using UPGMA algorithm of

48 aromatic rice germplasm, and grouped into two Clusters (I and II) at 49 %

similarity coefficient. 11 aromatic rice genotypes were represented in Cluster I

whereas 37 varieties were placed in Cluster II. Cluster I was divided into two

subclusters „IA‟ and „IB‟ at 56 % similarity coefficient. The sub-cluster „IA‟

included seven aromatic rice varieties in which „Kaminibhog-1‟ and „Kalikati-1‟

were most similar genotypes within sub-cluster. On the other hand the sub-cluster

„IB‟ was represented by the following four aromatic rice varieties „Basumati dhan‟

„Basumati Bhog‟, „Chatianak‟ and „Pumpudibasa‟. Among them „Basumati dhan‟

was the most diverged one in this sub-cluster. The cluster II was further classified

into two sub-clusters „IIA‟ and „IIB‟. There were 35 aromatic rice varieties

included in the sub-cluster „IIA‟ whereas only two aromatic rice varieties „Dubraj‟

and „Sujata‟ were placed in Cluster „IIB‟.

Sinha and Mishra (2013) characterized 34 landraces of rice based on 12

quantitative agro-morphological characters using Multivariate statistical analysis

and enabled pattern of variation of the germplasm of landraces of rice and

identification of the major traits contributing to the diversity of landraces. Five

cluster groups were obtained from the 12 agro-morphological characters. PCA

showed the contribution of each character to the classification of the rice landraces

into different cluster groups. The first three principal components explained about

86.9 % of the total variation among the 12 characters. The results of PCA

suggested that characters such as leaf length, leaf width, panicle length and grain

size (100 grain weight, length and width of grain and kernel were the principal

discriminatory characteristics of landraces of rice.

Shiva Prasad et al. (2013) reported significant differences among the 470

genotypes for all the nineteen characters studied. The quantum of genetic

divergence was assessed by cluster analysis using Mahalanobis‟s Euclidean

24

squared distances which grouped the entire material into eight clusters and

estimates the average distance between them. It was interesting to observe that

most of the genotypes of one cluster were adapted to only one region. The

clustering pattern reflects the closeness between the clusters and the geographical

adaptation of the genotypes. Also, traits contributing maximum to genetic

divergence are fertile grains/ panicle and panicle length may be utilized in

selecting genetically diverse parents. It was also reported that genotypes within the

cluster with high degree of divergence would produce more desirable breeding

materials for achieving maximum genetic advance.

Nachimuthu et al. (2014) used principal component analysis to examine the

variation and to estimate the relative contribution of various traits in a population

panel of 192 rice genotypes for 12 agro-morphological traits. Component 1 had the

contribution from the traits such as days to 50 % flowering, leaf length, plant

height, panicle length, days to maturity and number of filled grains which

accounted 28.46 % of the total variability. Grain width and grain length width ratio

has contributed 16.8 % of total variability in component 2. The remaining

variability of 14.4 %, 11.7 % and 9.3 % was consolidated in component 3,

component 4 and component 5 by various traits such as spikelet fertility, single

plant yield, grain length and number of productive tillers. The cumulative variance

of 80.56 % of total variation among 12 characters was explained by the first five

axes.

Kumar et al. (2014) reported five clusters based on D2 analysis for 23

genotypes of rice. Among the five clusters, cluster III consists of 7 genotypes

forming the largest cluster followed by cluster I and IV with 5 genotypes each.

Cluster II with 4 genotypes and cluster V with 2 genotypes. Inter cluster distances

were found to be higher than intra cluster distances which depicted wide genetic

diversity among the rice genotypes. The contribution of various characters towards

the expression of total genetic diversity indicated that 1000 grain weight

contributed maximum (54.55 %) followed by plant height (13.44 %) and kernel

breadth (11.86 %). Clustering of the cultivars did not show any pattern of

association between the morphological characters and the origin of the cultivars.

25

Cluster analysis performed by Rashid et al. (2014) on twenty diverse

cultivars of rice revealed that maximum genetic diversity was present between

Cluster I and Cluster VI. Minimum genetic diversity was found between Cluster III

and Cluster IV. It was concluded that traits like number of productive tillers,

number of grains per panicle and 1000-grain weight was useful for direct selection

criteria for higher grain yield.

Apsath Beevi and Venkatesan (2015) grouped 60 rice genotypes from

different eco- geographical regions of India into six clusters. Cluster I was found to

be the largest comprising of 50 genotypes followed by cluster II had four

genotypes. The clusters IV and V had two genotypes each while cluster III and VI

are monogenotypic in nature. The pattern of distribution of genotypes from

different eco-geographical regions into various clusters was at random indicating

that geographical diversity and genetic diversity were not related. The characters

grain yield plant-1, number of grains panicle-1 and plant height contributed

maximum towards genetic divergence among the genotypes. Cluster III recorded

highest mean value for grain yield plant -1 and lowest mean value for days to first

flower. The highest inter-cluster distance (D2 =7925.46) was recorded between

clusters III and VI.

Ayesha et al. (2015) genetic variability among the Oryza sativa germplasm

using agromorphological characters. The data were analyzed by cluster analysis

and principal component analyses. A significant level of variability was noticed for

a number of agro-morphological traits. The largest variation was observed in seed

yield per plant, (588.32), sterile culms per plant (341.25) and flag leaf length

(291.09). The 116 accessions in this study were grouped into seven clusters based

on hierarchical clustering method. PCI which is most important explained 28.41%,

PC II contributed 13.38%, and PC III accounted for 11.69% of total morphological

variability.

Rathore et al. (2016) studied the functional traits of 76 weedy rice

populations and commonly grown rice cultivars from different agro-climatic zones

for nine morphological and five physiological parameters in a field experiment.

The results of principal component analysis revealed the first three principal

26

components to represent 47.3% of the total variation, which indicates an important

role of transpiration, conductance, leaf-air temperature difference, days to panicle

emergence, days to heading, flag leaf length, grain weight, plant height, and

panicle length to the diversity in weedy rice populations.

2.5 Quality parameter

Babu et al. (2006) studied genetic divergence for different grain quality

traits in 70 rice genotypes from different eco-geographical regions of India. The

genotypes were grouped into nine clusters. Water uptake, gel consistency and head

rice recovery contributed the maximum towards genetic divergence. Geographical

diversity was not related with genetic diversity.

Roy et al. (2007) evaluated genetic divergence in twenty eight rice

genotypes using D2 statistics. These genotypes were grouped into four clusters.

Seed yield per plant contributed the maximum towards genetic divergence

followed by amylose content cooked kernel length and thousand seed weight.

Shrivastava et al. (2007) studied genetic diversity using Mahalanobis D2 statistics

in 20 genotypes of rice. These genotypes were grouped into six clusters. There was

lack of relationship between genetic and geographical diversity.

Singh and Singh (2007) analyzed various cooking and physical qualities of

rice. The hulling varied from 68.9 to 82.9%, milling from 56.1 to 74.2%, head rice

recovery from 19.7 to 49.4%, kernel length (KL, uncooked) from 5.1 to 7.1 mm,

kernel breadth (KB, uncooked) from 1.7 to 2.4 mm, kernel length breadth ratio

from 2.31 to 3.94, KL (cooked) from 9.5 to 12.7 mm, KB (cooked) from 2.5 to 3.6

mm, kernel elongation ratio from 1.39 to 1.98, alkali score from 2.6 to 6.6, volume

expansion from 2.78 to 3.12, water uptake number from 390 to 500, amylase

content from 15.15 to 41.62, gel consistency from 30 to 100, and aroma absent to

strong.

Pkania et al. (2007) predicted genotypic values for quality traits were

calculated using the Mahalanobis distance method and used to measure the genetic

similarities among rice varieties.

27

Sharma et al. (2008) studied under irrigated situation using D2

statistics in a

set of 100 aromatic rice genotypes. The genotypes were grouped into nine clusters

and it was observed that there was no association between the geographical

distribution and genetic diversity.

Lang et al. (2009) studied a collection of 200 salt tolerance rice landraces

was assessed for genetic diversity using quantitative agro-morphological

characters. The diversity indices (H‟) for quantitative descriptors were high

ranging from 0.68 to 0.95. Overall the mean diversity index for all traits was 0.88).

Cluster analysis generated by UPGMA grouped the 200 rice landraces into six

clusters with similarity coefficient of 20.61. The six clusters were distinct in terms

of culm length, number of filled grains, panicle length, panicles per plant, grain

length, grain width, yield and biomass.

Shahidullah et al. (2009) studied 40 genotypes composed of 32 local

aromatic, five exotic aromatic and three non-aromatic rice varieties. Univariate and

multivariate analyses were done. Enormous variations were observed in majority

of characters viz. grain length, grain breadth, kernel weight, milling yield, kernel

length, Length/Breadth ratio of kernel, volume expansion ratio (VER), protein

content, amylose content, elongation ratio (ER) and cooking time.

Pandey and Anurag (2010) observed among 22 genotypes of indigenous

rice for yield and quality contributing traits viz., volume expansion ratio, head rice

recovery, kernel length and length breadth ratio, indicating that there is presence of

sufficient amount of variability in the study material. On the basis of mean

performance of yield and yield contributing traits they found that “Indrani” was the

best performer for both yield and quality over Jhumeri. For quality parameters

Narendra-359 and Indrani were good, milling percentage of Lohandi was best

followed by Bayalu and Dudagi general types.

Shilpa et al. (2010) studied 22 traditionally cultivated rice varieties from

Goa for physicochemical characteristics such as physical (hulling, head rice

recovery, broken rice, grain classification, chalkiness), chemical (alkali spreading

value, amylose content, gel consistency, aroma) and cooking characteristics

(volume 29 expansion, elongation ratio, water uptake). The hulling percentage

28

ranged from 63-81% and head rice recovery from 45-74%. Among the varieties

Length/Breath ratio ranged from 1.5-3.5 and the amylose content ranged from 14-

25%. The kernel elongation ratio ranged from 4.78-1.83 mm and water uptake ratio

ranged from 160-390.

Garg et al. (2011) studied forty eight genotypes of rice to study the nature

and magnitude of genetic divergence using D2 statistics. Seventeen yield and

quality traits were recorded on the genotypes. The forty eight genotypes were

grouped into five clusters based on Euclidean cluster analysis. Days to maturity,

gel consistency and days to 50 per cent flowering contributed 74.55 per cent of

total divergence.

Danbaba et al. (2011) studied on the cooking and eating quality of Ofada

rice. The result showed that Ofada rice had high cooked rice volume with length

and breadth increase of 152.54% and 87.85% respectively. Grain elongation ratio

ranged from 1.24-1.75 and highest length/breadth ratio of cooked rice (3.68) and

lowest (2.49) was recorded. Water uptake ratio, cooking time, solids in cooking

gruel and amylase content of Ofada rice samples ranged from 174.0-211.0, 17-24

min, 0.8- 2.1%, and 19.77-24.13% respectively.

Satheeshkumar and Saravanan (2012) studied genetic diversity among fifty

three genotypes of rice genotypes from various states of south Eastern region of

India was evaluated using Mahalanobis D2 statistic. Based on 15 morphological

and quality characters, these genotypes were grouped into six Clusters.

Geographical origin was not found to be a good parameter of genetic divergence.

Grain yield per plant (38.52%) followed by filled grains per panicle (13.46%) and

total number of grain per panicle (12.65%) contributed maximum to total

divergence.

Subudhi et al. (2012) evaluated forty-one rice varieties of different

ecologies at CRRI, Cuttack and found that hulling percentage in all the genotypes

ranged from 71.0 to 81.0, milling recovery varied from 62.0 to 76.0 and head rice

recovery % varied from 43.5 to 68.0. The kernel length was highest (7.54) and

lowest (3.88), kernel length after cooking varied from 7.9 to 12.5, elongation ratio

was highest (2.07) and (2.0) and lowest (1.44). Volume expansion ratio was

29

highest (5.25), and lowest (3.25). Amylose content was intermediate in all the

tested genotypes and it ranged from 22.1 to 26.1.

Gnanamalar and Vivekanandan (2013) analysis of generation mean was

carried out in six crosses of rice for hulling percentage, milling percentage, head

rice recovery, kernel length, kernel breadth, kernel Length/Breadth ratio, kernel

length after cooking, linear elongation ratio and alkali spreading value. The scaling

test showed the presence of epistatic interactions for all the nine grain quality traits

studied. Milling percentage was governed by additive, dominance and epistatic

interactions of additive x additive, dominance x dominance and duplicate epistasis.

Hulling percentage was governed by additive, dominance and duplicate type. Head

rice recovery was under the control of additive, dominance, dominance x

dominance and duplicate epistasis.

Gangadharaiah et al. (2015) studied the physicochemical and cooking

quality of traditioal rice cultivars grown in the farmer‟s field. Among the cultivars,

Kichadi Sona and Salem Sanna recorded higher milling yield (66.0% and 65.0%)

and head rice recovery (58.5% and 58.30%), respectively. Therefore, these

cultivars could be utilized in the breeding programme is the need of the today

towards the „hidden hunger‟ free world.

Hosen et al. (2016) studied 17 Aus rice cultivars including 10 local

cultivars. The highest milling outturn 72.22% was found in the traditional variety

Chakilla and lowest in Kasalath (65.43%). The highest milled rice length (6.5 mm)

was BRRI dhan42 and the highest length-breadth ratio (3.8) was found in both

BR24 and BR26. The lowest grain length was found in BR20 (5.0 mm) and lowest

length-breadth ratio was found in Phul Dumra (2.0). In addition, Surjamukhi has

aroma. These local Aus variety could be a useful germplasm in breeding program

to get improve HYV especially for Aus season.


Molecular characterization of the genotypes gives precise information

about the extent of genetic diversity which helps in the development of an

appropriate breeding program. It is also very important for germplasm

30

management, varietal identification and DNA fingerprinting. A brief reviews has

been summarized below:

Tan et al. (2000) conducted a molecular marker-based genetic analysis of

the traits that are determinants of the appearance quality of rice grains, including

traits specifying grain shape and endosperm opacity and reported the QTL located

in the interval of RG393-C1087 on chromosome 3 is the major locus for grain

length, and the one in the interval RG360-C734a on chromosome 5 plays a major

role in determining grain width.

Hossain et al. (2007) used a total of thirty microsatellite molecular markers

across 21 rice genotypes for their characterization and discrimination. The number

of alleles per locus ranged from three (RM165, RM219, RM248, RM463, RM470

and RM517) to nine (RM223), with an average of 4.53 alleles across the 30 loci

obtained in the study. The polymorphism information content (PIC) values ranged

from 0.30 (RM219) to 0.84 (RM223) in all 30 loci. RM223 was found the best

marker for the identification of 21 genotypes as revealed by PIC values. The

frequency of the most common allele at each locus ranged from 24% (RM223 and

RM334) to 81% (RM219).

Nipon et al. (2007) assessed genetic variability among 24 rice genotypes

from Assam employing ISSR-PCR using ten primers. A total of 201, ISSR markers

were generated with 98 per cent polymorphism. The average polymorphism

information content (PIC) for ISSR markers was 0.88. Cluster analysis and

cophenetic correlation value based on the ISSR data discretely separated the

accessions, according to farmer‟s classification.

Mia et al. (2010) used three SSR primers viz. RM223, RM515 and RM342

for identification of fgr gene locus in 22 rice genotypes and reported that all the

three markers identified fifteen rice genotypes having fgr gene locus. From

phenotypic and genotypic evaluation, it was found that, six genotypes (Basmati

370, Indian Ndingo, Nam Sagui19, IR77542-127-1-1-1-1-2, Si- Feng 43 and

Kalizira) having strong aroma with slender grain. Four genotypes (M6-9-28 UL,

PSB RC 70, PR 26768-PJ (T) 4C 18-8-2-1 and Chinisagor) having moderate aroma

with slender to medium grain. Finally, five genotypes (Indian Ndingo,

31

NamSagui19, IR77542-127-1-1-1-1- 2, Basmati 370 and Si- Feng 43) were

selected having strong aroma with good agronomic performances. These genotypes

could be used in breeding programme to develop new varieties.

Bai et al. (2010) performed QTL analysis for grain shape using an RIL

population derived from two varieties with contrasts in grain shape. Twenty-eight

QTLs were identified. Seven of them were detected for the first time. These results

demonstrated that the mapping population derived from parents with contrasting

phenotypes can be used for detecting more QTLs. In their study, a minor QTL

of qGL7 was validated with pleiotropic effects on GL, GW, TGW, SPP, and GT in

an NIL-F2 population. It is suggested that minor QTL of a highly heritable trait

could be isolated following the strategy of map-based cloning in a large NIL-

F2population.

Girma et al. (2010) studied genetic diversity of three wild rice populations

of Ethiopia along with three cultivated rice populations using Inter simple

sequence repeats (ISSRs) as a molecular marker. Both UPGMA and neighbor

joining trees were constructed for each individual and population using Jaccard‟s

similarity coefficient. The trees and PCO clearly indicated six distinct groups

which are based on populations of origin. Oryza glaberrima, Oryza sativa and

NERICA-3 clustered as a major group while Oryza barthii and Oryza

longistaminata were clustered as the second major group. The overall gene

diversity and percent polymorphisms were found to be higher in wild rice (0.14;

38.3 respectively) than in cultivars (0.11; 28.3 respectively).

The SSR markers have been increasingly applied by many scientists in rice

germplasm. Priti et al. (2011) studied genetic diversity of popular of 29 rice

varieties in India using 12 SSR markers and identified genotype specific alleles in

14 popular rice varieties which can be employed in true identification germplasm

in their country. Herrera et al. (2008) assessed genetic diversity in Venezuelan rice

cultivars using simple sequence repeat markers to broaden the genetic bases of rice

germplasm in the country. The genetic diversity reported was very low, but this

work proved SSR to be an efficient tool in assessing the genetic diversity of rice

genotypes.

32

Shukla et al. (2011) characterized forty four indigenous local strains of

Kalanamak rice (Oryza sativa L.) with 60 morphological DUS descriptors, RAPD

and ISSR markers. The UPGMA cluster analysis revealed that the ISSR loci

enabled identification of 42 strains (95%). Two ISSR primers, viz LC 61 and LC

67 produced genotype specific loci in Kalanamak strains 3131-1P and 3119-SN

which were able to discriminate them from rest of the strains. Higher number of

average bands (8.2), number of average polymorphic bands (6.6), percentage of

polymorphic bands (78.9%), average polymorphic information content (0.33),

average resolving power (10.85), average effective multiplex ratio (5.6) and

marker index (2.08) for ISSR marker as compared to RAPD reflected that ISSR

marker is more efficient tool to establish distinctiveness amongst the present set of

experimental material.

Das et al. (2012) reported the diversity among 26 indigenous non-basmati

aromatic rice genotypes, six basmati and 9 HYV; both morphologically using 12

grain and kernel traits and genetically using 23 previously mapped SSR markers.

High genetic diversity was observed for the grain and kernel dimension and quality

traits, in the indigenous non-basmati aromatic rice genotypes through D2 analysis.

The polymerase chain reaction (PCR) profile obtained from 23 SSR markers

generated 172 alleles including 28 rare alleles and 9 null alleles. The ensuing

dendrogram obtained from the SSR profiles clustered the basmati rice and the

indigenous non-basmati aromatic rice genotypes separately.

Rahman et al. (2012) studied thirty-four microsatellite markers across 21

types of rice to characterize and discriminate among different varieties. The

number of alleles per locus ranged from 2 to 11, with an average of 4.18 alleles

across 34 loci. A total of 57 rare alleles were detected at 24 loci, whereas 42

unique alleles were detected at 20 loci. The results revealed that 14 rice varieties

produced unique alleles that could be used for identification, molecular

characterization, and DNA fingerprinting of these varieties. Polymorphic

Information Content (PIC) values ranged from 0.157 to 0.838, with an average of

0.488, which revealed that much variation was present among the studied varieties.

The PIC values revealed that RM401 might be the best marker for identification

and diversity estimation of rice varieties, followed by RM566, RM3428, RM463,

33

and RM8094 markers. In this study, eight SSR markers (RM10713, RM279,

RM424, RM6266, RM1155, RM289, RM20224, and RM5371) were identified that

produced specific alleles only in the aromatic rice varieties and were useful for

varietal identification and DNA fingerprinting of these varieties. The findings of

this study should be useful for varietal identification and could help in background

selection in backcross breeding programs.

Sajib et al. (2012) used a total of 24 SSR markers across 12 elite aromatic

rice genotypes for their characterization and discrimination. Among these 24

markers 9 microsatellite markers were showed polymorphism. The number of

alleles per locus ranged from 2 alleles (RM510, RM244, and RM277) to 6 alleles

(RM163), with an average of 3.33 alleles across 9 loci obtained in the study. The

polymorphic information content values ranged from 0.14 (RM510) to 0.71

(RM163) in all 9 loci with an average of 0.48. RM163 was found the best marker

for the identification of 12 genotypes as revealed by PIC values. The frequency of

most common allele at each locus ranged from 41 % (RM163, RM590, and

RM413) to 91 % (RM510). The microsatellite marker based molecular

fingerprinting could serve as a sound basis in the identification of genetically

distant accessions as well as in the duplicate sorting of the morphologically close

accessions.

Meti et al. (2013) reported the allelic diversity and relationship among 48

traditional indigenous aromatic rice germplasm grown under Eastern part of India

using SSR markers. Out of 30 primers, 12 primers showed DNA amplification and

polymorphism among 48 aromatic rice genotypes. The number of alleles per locus

ranged from 1 to 5 with an average 2.08. Out of 28 bands, 25 bands were

polymorphic and three were monomorphic bands. The results reveal that all the

tested primers showed distinct polymorphism among the landraces/varieties

indicating the robust nature of SSR markers. The cluster analysis indicates that the

48 traditional indigenous aromatic rice genotypes were grouped into two major

clusters. The information obtained from the SSR profile helps to identify the

variety diagnostic markers in 48 traditional indigenous aromatic rice genotypes.

34

Vohra et al. (2013) reported the genetic diversity among twenty aromatic

and non-aromatic rice genotypes using twenty five microsatellite markers (SSR).

They used fifteen markers for analysis of aromatic and non-aromatic rice

genotypes. These markers generated higher level of polymorphism because they

generated 356 polymorphic reproducible bands with 164 loci. The remaining ten

markers were used for the study of quality traits which shown 222 polymorphic

bands with 101 alleles. The cluster analysis using SSR markers could distinguish

the different genotypes. The dendogram generated on the principle of Unweighted

Pair Wise Method using Arithmetic Average (UPGMA) was constructed by

Jaccard‟s Coefficient and the genotypes were grouped in to clusters. The

dendogram developed for aroma and quality traits showed that the genotypes with

common phylogeny and geographical orientation tend to cluster together.

Kumbhar et al. (2013) used ISSR fingerprinting to assess the genetic

diversity among fifty rice accessions. Out of 25 ISSR primers screened 13 primers

produced polymorphic amplicons and were selected for genetic diversity analysis.

It produced a total of 103 reproducible amplification products with an average of

7.92 amplicons per primer. All the markers displayed polymorphic amplicons. Of

the total amplicons, 100 (97.08 %) were polymorphic for more than one variety.

The UPGMA based clustering analysis using Dice similarity coefficient grouped

these genotypes into three major and eleven sub-clusters. Cluster I had highest

number of genotypes (38) followed by Cluster II (11) and cluster III (I). The

grouping resembled the ancestry of the genotypes under study.

Kumar et al. (2014) characterized a set of 72 rice genotypes collected from

different villages of Chhattisgarh state, using molecular (SSR) marker. SSR

analysis with 15 polymorphic SSR primers produced 44 different alleles on 2.5 %

agarose gel with an average of 2.93, ranging from 1 to 4 alleles per locus.

Aslam and Arif (2014) studied 48 rice accessions and there are a lot of

gene/QTLs were identified by different groups on chromosome 3 and 7 controlling

grain length. Clustering based on grain length divided the 48 accessions into two

major clusters with some contradiction. Genetic relationships among the 48 rice

accessions were determined based on allelic diversity using Power Marker tree,

35

structure analyses and PCA using 51 SSR markers located on chromosome 3 and

chromosome 7. Two-dimensional PCA scaling and power marker tree analysis

showed high-level of differentiation between Basmati and indica rice accessions

and divide these rice accessions in two distinct clusters.

Rout et al. (2014) assess the genetic diversity on the basis of molecular

characterization among 48 traditional aromatic rice varieties of India. Twenty four

ISSR markers were studied in 48 traditional aromatic rice to characterize and

discriminate it. A total of 151 polymorphic alleles were detected whereas 37

monomorphic alleles were detected. Polymorphic information content (PIC) was

found to be the highest in primer (AM-8) and lowest in primer UBC-840. Result

revealed that the primer AM-8 might be the best marker for identification and

diversity estimation of aromatic rice varieties, followed by AM-4, AM-1, UBC-

818 and UBC-850 primers. The UPGMA cluster dendrogram created in this study

identified two clusters with a similarity coefficient of 53%. The genotype pair

(„Dangerbasumati‟ and „Gangaballi‟) showed the maximum similarity (0.93)

among the 48 aromatic genotypes.

Kunusoth et al. (2015) has reported the genetic diversity assessment of 24

elite Indian rice varieties was based on 24 agro-morphological traits and 86 SSR

markers. The morphological and grain traits exhibiting significant variation are

useful for discrimination of the rice varieties and were confirmed by Principal

Component Analysis. Genetic diversity assessment based on SSR markers

displayed genetic similarity coefficients and grouped the varieties into five major

clusters. The genetic population structure obtained was predominantly associated

with UPGMA clustering and the structure bar plot. Cluster analysis based on both

phenotype and SSR marker data did not show perfect congruence between the two

measures of genetic diversity.

Becerra et al. (2015) analyzed 16 commercial varieties using 54

microsatellites. The 54 microsatellite loci allowed the discrimination among the 16

varieties. The number of alleles ranged between 2 and 8 with a mean of 3.54 alleles

per locus, while the polymorphism information content (PIC) presented a mean of

0.44. The highest PIC was positively associated with the highest number of alleles

36

detected by SSRs. Given this situation, it is important to continuously introduce

germplasm from other regions to increase the Rice Breeding Program's genetic

base.

37

CHAPTER- III

METHODS AND MATERIALS

The present investigation entitled, “Molecular and agro-morphological

characterization of selected rice (Oryza sativa L.) germplasm accession based on

grain length” was carried out during Kharif, 2015. The techniques followed and

materials used during the course of investigation are presented below:

3.1 Experimental site

The present research work was conducted at Research cum Instructional

farm, Department of Genetics and Plant Breeding, College of Agriculture, Indira

Gandhi Krishi Vishwavidyalaya, Raipur, Chhattisgarh, during the Kharif season of

2015.

3.2 Climate and weather

Chhattisgarh is located between 17°14‟N and 24°45‟N latitudes and 79°16‟

E and 84°15‟ E longitudes. Raipur is the capital of the Chhattisgarh state and lies at

21°16‟N latitude and 81°36‟ E longitude with an altitude of 289.60 meters above

mean sea level. The maximum temperature was 31.9°C and minimum 18.8°C

during the crop growth period. The total rainfall received during crop growth stage

was 692.6 mm. The maximum rainfall received during month of August was 224.5

mm. The data pertaining to weekly rainfall, minimum and maximum temperatures,

relative humidity, evaporation and bright sunshine hours of entire crop growing

period have been presented in Appendix A and Fig. 3.1, 3.2, 3.3 and 3.4.

Fig 3.1: Meteorological data recorded during crop growth season (26 June to

31 December, 2015)

0

200

26 28 30 32 34 36 38 40 42 44 46 48 50 52Te

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, R

ain

fell

, R

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um

idit

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loci

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Ev

ap

ora

tio

n &

Su

nsh

ine

Meteorological Weeks

Max. Temp. (0C) Min. Temp. (0C)Rainfall (mm) Rainy days

38

3.3 Experimental Materials and Methods

Forty-eight land races of rice belonging to Chhattisgarh were selected for

this study (Table 3.1). Nurseries were raised and twenty-one days old seedlings

were subsequently transplanted in the field, in Randomized Block Design (RBD)

with two replications. Net plot size was 3 m x 1.5 m with both row to row & plant

to plant distance of 25 cm X 25 cm. The crop was maintained under rainfed

condition. Fertilizer dose @ of 50 N: 40 P: 30 K kg/ha was applied. The entire

dose of phosphorus and potassium along with half the dose of nitrogen was applied

as basal dose before transplanting. The remaining dose of nitrogen was applied in

two splits, first at the time of beginning of tillering and second one week after it.

Agronomical practices adopted were similar for all the treatments. Five random

plants from each of the plot were taken for recording data on agro-morphological

and yield characters. To assess distinctness, uniformity and stability (DUS), the

characteristics and their statuswas done as given by PPV & FR Authority, GOI,

2007.

3.4 Observations recorded

In research work, observations on various agro-morphological and quality

traits were recorded to fulfill the objectives of the study. Five random plants from

each of the progeny rows were taken for recording data of various characters at

optimum plant growth stage. Averages of the data from the sampled plants with

respect to different characters were used for various statistical analyses.

3.4.1 Agro-morphological Characters

The observations on various morphological traits including qualitative and

quantitative characters as diagnostic descriptors were recorded. The classification

of DUS is given in appendix B.

3.4.1.1 Seedling Character

Coleoptile color:

The coleoptiles color was recorded at first leaf stage by visual observation

of individual plants. The categories observed were colorless, green color and the

purple color of the coleoptile.

39

Table 3.1: Landraces and their origin

S.

No. CGR no. IC No. Accession Name

Grain

length (mm) Source (Village/Block/Distt.)

Short grain

1 10031 116093 Lokti Machhi 6.0 Bade Rajpur/Bade Rajpur/Bastar

2 10036 116098 Atma Sital 6.0 Antagarh/Antagarh/Bastar

3 10029 116091 Lokti Machhi 6.0 Narayanpur/Narayanpur/Bastar

4 1686 132619 ADT:27 6.0 Rajim/Fingeshwar/Raipur

5 1829 132767 Anjania 6.0 Pandarbhattha/Bemetara/Durg

6 2845 NA Kanak Jira 6.0 Dadesara/Durg/Durg

7 2890 134280 Jhumera 6.0 Martara/Bemetara/Durg

8 2947 134337 Kakeda (I) 6.0 Kuamalji/Pandariya/Bilaspur

9 6475 125708 Dubraj II 6.0 Chandkhuri/Arang/Raipur

10 2300 133269 Bhulau 5.9 Gidhpuri/Palari/Raipur

11 2929 134319 Rani kajar 5.9 Garra/Palari/Raipur

12 3870 135260 Sundar mani 5.9 Kodohatha/Deobhog/Raipur

13 5856 NA Bhado kanker 5.9 Turanga/Pusaur/Raigarh

14 2888 134278 Jhumarwa 5.8 Charbhatha/Fingeshwar/Raipur

15 6062 114188 Bishnu 5.8 Bishnupur/Baikundpur/Sarguja

16 512 123552 Basa Bhog 5.7 Pratappur/Pratappur/Sarguja

17 5375 124958 Krishna Bhog 5.7 Mohgaon/Mandla/Mandla

18 7087 NA Hira Nakhi 5.7 Khekha/Bichhiya/Mandla

19 10032 116094 Lokti Maudi 5.6 Abujhmad/Abujhmad/Bastar

20 6069 NA Kariya bodela bija 5.6 Kodo/Abujhmad/Bastar

21 6688 125922 Ganja Kali 5.6 Kudum Kala/Ghar Ghoda/Raigarh

22 5528 125109 Banas KupiII 5.5 Jhilwada/Waraseoni/Balaghat

23 6444 125677 Dhangari Khusha 5.5 Darrabhatha/Saraipali/Raipur

24 6446 125679 Bhaniya 5.5 Fashakar/Durgkondal/Bastar

Long grain

25 6637 125871 Farsa phool 12.6 Koyalibeda/Koyalibeda/Bastar

26 7125 114272 Jay Bajrang 11.8 Fingeshwar/Fingeshwar/Raipur

27 6726 125960 Gilas 11.8 Enhoor/Durgkondal/Bastar

28 7615 NA Khatia pati 11.5 Odan/Palari/Raipur

29 8421 114979 Mani 11.4 Rajim/Rajim/Raipur

30 7539 NA Khatriya pati 11.4 Odan/Palari/Raipur

31 6729 NA Girmit 11.4 Kokodi/Kirnapur/Balaghat

32 7960 NA Lanji 11.3 Deverda/Baldevgarh/Tikamgarh

33 5772 114018 Banreg 11.3 Khutgaon/Deobhog/Raipur

34 9209 NA Ruchi 11.2 Kusumi/Kusumi/Sarguja

35 8187 NA Safed luchai 11.2 Nagajhare/Barghat/Seoni

36 3090 134480 Kanthi deshi 11.2 Vijaipali/Barghat/Seoni

37 9068 NA Piso III 11.1 Barghat/Barghat/Seoni

38 7301 114358 Kakdi 11.1 Kukanar/Darma/Bastar

39 6656 125890 Gajpati 11.1 Kosamghat/Ghar Ghoda/Bastar

40 6650 125884 Gadur sela 11.1 NA/Mohala/Rajnandgaon

41 5103 124686 Aadan chilpa 11.1 Kesherpal/Bastar/Bastar

42 5078 214553 Unknown 11.1 NA/NA/NA(CG)

43 9420 115695 Saja chhilau 11.0 Kanker/Kanker/Bastar

44 9395 NA Parmal Safri 11.0 Tilda/Tilda/Raipur

45 9254 115573 Safri 11.0 Varasioni/Waraseoni/Balaghat

46 8711 NA Narved 11.0 Muraina/NA/Muraina

47 8673 NA Nagbel 11 Dev Bhog/Dev Bhog/Raipur

48 8558 115101 Mudariya 11 Abhanpur/Abhanpur/Raipur

40

Fig3.2: Sowing of rice germplasm accessions

Fig3.3: Nursery view

Fig 3.4: Field view of experiment

41

3.4.1.2 Leaf characters

Basal leaf sheath color:

The color of the leaf sheath, which is wrapped around the culms above the

basal node, was visually recorded at early boot stage on individual plants. The

categories observed were green, light purple, purple lines and purple color at basal

leaf sheath.

Intensity of green color in leaf:

The intensity of green color of leaves was visually recorded at early boot

stage by observation of a group of plants. The major categories recorded were

light, medium and dark green color.

Anthocyanin coloration on leaf:

The presence or absence of anthocyanin coloration on leaf was recorded at

early boot stage by visual assessment in a group of plants.

Distribution of anthocyanin coloration on leaf blade:

The distribution of anthocyanin coloration on leaf was recorded at early

boot stage by visual assessment of group of plants. The major categories are on

leaf tips only, on leaf margins only, in blotches only and uniform presence of

anthocyanin color on leaf lemma.

Anthocyanin coloration on leaf sheath:

The presence or absence of leaf sheath anthocyanin coloration was

recorded at early boot stage by visual assessment of group of plants.

Intensity of anthocyanin coloration on leaf sheath:

The intensity of anthocyanin coloration on leaf sheath was visually

recorded at early boot stage of a group of plants. The major groups recorded were

very weak, weak, medium and strong based on anthocyanin coloration.

42

Presence of pubescence on leaf blade surface:

The intensity of leaf pubescence was recorded at early boot stage by visual

assessment of individual plants of every land race. The categories observed under

this character were absence, weak, medium, strong and very strong presence of

pubescence on blade surface.

Presence of auricles on leaf:

Most of the leaves possess small paired hairy appendages on either side of

the base of the blade. These appendages are called auricles. The presence or

absence of auricles was visually assessed at early boot stage by observation of

individual plant.

Anthocyanin coloration of auricles:

The anthocyanin coloration of auricles i.e. colorless, light purple and purple

color in auricles was recorded at early boot stage with visual assessment by

observation of individual plants.

Presence of collar on leaves:

The presence or absence of leaf collar that is the juncture between leaf

blade and leaf sheath was recorded at early boot stage by visual assessment of

individual plants.

Anthocyanin coloration of collar:

The presence or absence of anthocyanin coloration at collar was recorded at

early boot stage by visual assessment of individual plants.

Presence of ligule on leaf:

Presence or absence of papery membrane at the inside juncture between the

leaf sheath and blade called ligule was recorded at early boot stage by observation

of individual plants or parts of plants.

Shape of ligule:

The shapes of ligule i.e. truncate, acute and split shapes was recorded at

early boot stage by visual assessment of individual plants.

43

Color of ligule:

The colors of ligule i.e. green, light purple or purple was recorded at early

boot stage by visual assessment of individual plants or parts of plants.

Length of leaf blade:

The length of the leaf blade was measured in centimeter and categorized in

to short, medium and long leaves.

Width of leaf blade:

The width of the leaf blade was measured in centimeter and categorized in

to narrow, medium and broad leaves.

Attitude of flag leaf (early observation):

The flag leaf attitude was recorded at beginning of anthesis through visual

assessment and categorized in to erect, semi-erect, open and spreading types by

observation of group of plants.

Attitude of flag leaf (Late observation):

The attitude of flag leaf was recorded at ripening stage through visual

observation and grouped in to erect, semi-erect, horizontal and deflexed classes

according to the features of majority of plants of the landraces.

Leaf senescence:

The leaf senescence was visually recorded at stage when caryopsis became

hard on a group of plants. Senescence is categorized in to early, medium and late

classes.

3.4.1.3 Characters of culm:

Culm: attitude:

The Culm attitude was recorded at early boot stage by visual assessment

and grouped in to erect, semi-erect, open or spreading culm attitude by observation

of individual plants.

44

Stem thickness:

The stem thickness was recorded at milk development stage. Thickness was

measured in centimeter and categorized into thin, medium and thick stem classes.

Anthocyanin coloration of nodes:

The presence or absence of anthocyanin coloration of nodes was recorded

at milk filling stage through visual assessment of individual plants nodes.

Intensity of anthocyanin coloration of nodes:

The intensity of anthocyanin coloration on nodes was recorded at milk

filling stage of each landrace and through visual assessment the plants are

categorized in to weak, medium and strong intensity of anthocyanin coloration at

node.

Anthocyanin coloration of internodes:

The presence or absence of anthocyanin coloration on internodes was

recorded at milk development stage through visual assessment of each landrace.

3.4.1.4 Flower characters

Days to 50 percent flowering:

Number of days was recorded from date of sowing to the days when

primary panicles in 50 percent plants were emerged.

Color of stigma:

The color of stigma was recorded at stage of half-way anthesis and grouped

in to white and purple stigma through visual assessment by observation of

individual plants.

3.4.1.5 Characters of panicle

Panicle length (cm):

Panicle length was measured at the time of maturity from the base of

panicle to the tip of last spikelet prior to harvesting. The categories under this class

are very short (<16 cm), short (16-20 cm), medium (21-25 cm), long (26-30 cm)

and very long (>30 cm).

45

Curvature of main axis of panicle:

The curvature of main axis of panicle was recorded at ripening stage and

grouped into straight, semi-straight, drooping and deflexed classes through visual

assessment by observation of a group of plants.

Number of effective tillers per plant:

The numbers of panicle bearing tillers of the plants were counted in five

random plants.

Density of pubescence of lemma:

The density of pubescence of lemma was recorded at beginning of anthesis

to dough development stage through visual assessment and grouped in to absent,

medium and strong categories by visual observation of individual plants.

Anthocyanin coloration on apex of lemma:

The anthocyanin coloration on apex of lemma was recorded at half way of

anthesis by visual observation and grouped into absent, very weak, weak, strong

and very strong.

Anthocyanin coloration below apex of lemma:

The anthocyanin coloration below apex of lemma was recorded at half way

of anthesis by visual observation and grouped into absent, weak, medium and very

strong.

Presence of secondary branching on panicles:

The presence or absence of secondary branching was recorded at ripening

stage through visual observation of a group of plants.

Density of secondary branching on panicles:

The panicles which possess secondary branching were classified in to

weak, strong and clustered branching categories. Observations were visual

observed on a group of plants.

46

Exertion of panicle:

The panicle exertion was recorded at ripening stage and classified into

partly exerted, exerted and well exerted classes. The classes were recorded through

visual assessment of a group of plants.

3.4.1.6 Spikelet characters

Color of lemma and palea:

The lemma and palea color was recorded at dough development to ripening

stage through visual assessment of group of plants of landraces and classified into

straw, gold and gold furrows on straw background, brown spots on straw, brown

furrows on straw, brown (tawny), reddish to light purple, purple spots on straw,

purple furrows on straw and purple black.

Presence of awns on panicles:

The individual landraces were classified on the basis of presence or absence

of awns at ripening stage and assessed through visual observation of a group of

plants.

Color of awns:

The color of awns was recorded at ripening stage through visual assessment

of individual plants and grouped into classes yellowish white, yellowish brown,

brown, reddish brown, light red, red, light purple, purple and black on the basis of

awn color.

Length of longest awn:

Length of longest awn was recorded at ripening stage through centimeter

measurement of individual panicle and grouped into very short, short, medium and

long awn length.

Distribution of awns:

The distribution of awns was recorded at ripening stage through visual

assessment by observation of individual plants and grouped in to presence of awns

at tip only, upper half only and whole length.

47

Days to maturity:

This was recorded in days from sowing to maturity. This character is

categorized into very early, early, medium, late and very late duration.

Color of sterile lemma:

The color of sterile lemma was recorded at maturity stage when caryopsis

get hard by visual assessment by observation of individual panicle and grouped

into straw color, purple and gold sterile lemma color.

3.4.1.7 Grain characters

Grain length (mm):

The average length of randomly selected ten hulled spikelets was measured

in terms of millimeters. This is grouped into very short, short, medium, long and

very long grain.

Grain width (mm):

The average breadth of randomly selected ten hulled spikelets was

measured in terms of millimeters. This was grouped into narrow, medium, and

broad grain.

Thousand grain weight (g):

Thousand seeds of each of the entry were taken randomly and weighed in

gram.

Grain yield per plant (g):

The grain (filled) yield of each of the five plants was recorded in grams

after sun drying for 5-8 days after harvesting and averaged.

Biological yields per plant (g):

Weight of each of the five plant excluding root was recorded in grams after

sun drying for 5-8 days after harvesting and averaged.

48

Harvest index (%):

The ratio of grain yield to the biological yield was calculated and expressed

as percentage. Harvest index was calculated as follows:

Grain yield

Harvest index (%) = ---------------------------- × 100

Biological yield

3.4.1.8 Grain quality characters:

Following grain quality characters were recorded:

Hulling (%):

100 g of paddy sample was used; it was properly cleaned, before starting

the dehulling. The dehusking of rice was done by dehusker and hulled rice weight

was recorded.

Weight of the dehusked kernel

Hulling percentage = ------------------------------------------ X 100

Weight of paddy

Milling (%):

Brown rice was put into standard miller or polisher and later milled rice

weight was recorded.

Weight of polished kernel

Milling percentage = ----------------------------------------- X 100

Weight of paddy

Head rice recovery (%):

From milled rice the ¾ kernel was taken as whole grain. The sorting out of

full and broken rice was done and its weight was recorded.

Weight of whole polished kernel

Head Rice Recovery = --------------------------------------------- X 100

Weight of paddy

Amylose content:

49

Amylose content was determined by the method developed at International

Rice Research Institute, Philippines (Jenning et al., 1979). The basic procedure is

to prepare a standard curve using solutions of purified potato amylose employing

the standard method. In this curve, the light transmission value of the colored

solution is plotted against amylose concentration. Next, standard rice samples with

a range of known low, intermediate and high amylose content are treated using the

standard method, and the light transmission values are determined. The already

plotted curve is then used to determine the amylose content of the samples. Their

percentage of amylose is plotted against light transmission values to form a second

curve. Finally, the unknown samples are treated with the use of the simplified

method and the light transmission values are determined. By referring to the

second standard curve, the percentage of amylose of the unknown samples is

determined. The second curve is made to account for the effect of the amylose that

is present in rice but not in purified potato amylose.

Procedure for determining Amylose content:

Weighing of 0.10 g of fine powdered rice grain in 100ml volumetric flask.

Add 4 ml methanol was added and kept for 2.30 hr.

After that methanol was extracted.

Add 9 ml of 1N NaOH and 1ml of 9.5% ethanol.

Then it was heated for 10 minutes in pre-heated water-bath.

Cool it and make up 100 ml volume with distilled water.

From this, 5 ml sample in volumetric flask was taken and 1ml of acetic acid

and 2ml of potassium iodide (KI) reagent was added.

Again the volume was made up with 100 ml distilled water and kept for 20

minutes.

Finally the reading of the sample at 620 nm on spectrophotometer was

recorded.

Amylose (percent) = R X 76.92SS

R = Reading at 620nm on spectrophotometer.

50

Table 3.2: Scale for Amylose test

Very low <10%

Low 11-19%

Medium 20-25%

High 26-30%

Very high >30%

Alkali spreading value and Gelatinization temperature:

Alkali spreading values were determined as per procedure described by

Jennings et al. (1979) and is as follows

(i) Six milled rice kernels without cracks were selected of each variety from each

replication and placed in Petri dishes.

(ii) 10 ml of 1.7 % KOH was added to each Petri dish.

(iii) These were evenly placed in Petri dishes to allow enough space for spreading.

(iv) Petri dishes were covered and placed for 23 hours at constant temperature of

30°C.

(v) Disintegration of endosperm was visually rated as per following scale (Little

et al. 1958).

Table 3.3: Alkali spreading value classification along with Gelatinization

Temperature

Classification Alkali spreading

value(ASV)

Gelatinization

temperature(GT)

1-2 Low High >74 0C

3 Low, intermediate High, intermediate

4-5 Intermediate Intermediate (70 0C – 74

0C)

6-7 High Low (55 0C – 69

0C)

51

Table 3.4: Numerical scale for scoring Alkali spreading value

Score Spreading Clearing

1. Kernel not affected Kernel chalky

2. Kernel swollen Kernel chalky collar powdery

3. Kernel swollen, collar complete and

narrow

Kernel chalky collar cottony or

cloudy

4. Kernel swollen, collar complete and

wide

Center cottony, collar cloudy

5. Kernel split or segregated, collar

complete and wide

Center cottony, collar clearing

6. Kernel dispersed merging with

collar

Center cloudy collar clear

7. Kernel completely dispersed and

intermingled

Center and collar clear

Aroma:

Aroma was determined at post harvest stage using the technique developed

at International Rice Research Institute, Philippines (Jennings et al., 1979).

According to this 20 to 30 freshly harvested milled grains were taken in a test tube

with 20 ml of distilled water. Stoppers were put on the mouth of test tubes and

placed in boiling water bath for 10-20 minutes. Test tubes were removed and

cooled. Aroma was then detected by smelling and categorized into:

SS: Strongly scented; MS = Mild scented; NS = Non - scented.

Gel consistency:

Method of determining gel consistency was given as follow:

1. Take 100 mg of flour quadruplicates in culture tubes.

2. Add 0.2 ml of ethanol containing 0.25% thymol blue.

3. Add 2 ml of 0.2 N Potassium Hydroxide (KOH).

52

4. Mix the solution on a cyclone mixer.

5. Keep the test tube in water bath at 90-100 0C for 8 minutes after putting one

glass tube marble on each test tube.

6. After removing the culture tubes from water bath cool them for 5 minutes.

7. Mix the solution on cyclone mixer.

8. Keep the culture tube in low temperature bath at 0-2o C for 20 minutes.

9. The culture tubes are removed from ice bath and laid horizontally for one hour

over graph paper.

10. Length of blue colored gel from the inside bottom of the test tube to the gel

front was then measured as gel consistency of the sample.

11. 26-40mm Hard gel consistency

12. 41-60mm Medium gel consistency

13. 61-100mm Soft gel consistency

Chalkiness:

The degree of chalkiness describes the milled sample rice‟s with respect to

(a) White belly (b) White center (c) White back.

Notation Kernel area (Extent)

A Absent None

VOC Very occasionally present Small (less than 10%) kernel

OC Occasionally present Medium (11% to 20%)

P Present Long (more than 20%)

Kernel length (mm):

Ten milled grains were taken randomly and average length was recorded in

millimeters. These were classified in to very short, short, medium, long and very

long classes.

Kernel breadth (mm):

Breadth of the above ten milled grains was recorded and average breadth

was recorded in millimeters. These were classified in to very narrow, narrow,

medium, broad and very broad classes.

53

L/B Ratio:

The length/breadth ratio of randomly selected ten milled spikelets was

calculated by dividing respective length with breadth.

Length of milled grains

Kernel L/B ratio= -----------------------------------

Breadth of milled grains

Grain Shape

Based on length and L/B ratio the grain type is classified as per the

guidlines of DUS, PPV & FR 2007.

State Kernel length (mm) Length/breadth ratio

Short Slender < 6.0 > 3.0

Short Bold < 6.0 < 2.5

Medium Slender < 6.0 2.5-3.0

Long Slender > 6.0 > 3.0

Long Bold > 6.0 < 3.0

Basmati type > 6.61 > 3.0

Extra Long

Slender > 7.5 > 3.0

Kernal length after cooking (mm):

The length of randomly selected ten cooked spikelets was measured in

terms of millimeters.

Kernel breadth after cooking:

The breadth of randomly selected ten cooked grains were measured in

terms of millimeters

Length breadth ratio after cooking:

The length/breadth ratio of randomly selected ten cooked grains was

calculated by dividing respective length with breadth. It was computed by formula:

Kernel length after cooking

Length breadth ratio after cooking = ----------------------------------------

Kernel breadth after cooking

54

Kernel Elongation Ratio:

This was calculated by the following formula:

Kernel length after cooking (mm)

Elongation ratio = -----------------------------------------------

Kernel length before cooking (mm)

Elongation Index:

Elongation index was calculated as the ratio of L/B (after cooking) and L/B

(before cooking).

Ratio of L/B (after cooking)

Elongation index = ---------------------------------------

Ratio of L/B (before cooking)

3.5 Molecular Study

Twenty four long grain and twenty four short grain accessions were used

for molecular characterization. For assessing the genetic diversity of rice

germplasm molecular study was performed, which included DNA isolation,

quantification, dilution of DNA, PCR amplification using SSR primers,

electrophoresis using polyacrylamide gel, scoring and analysis of data.

3.5.1 Genomic DNA isolation

Whole genomic DNA was extracted out from rice seedlings of each of the

landraces of rice. The protocol CTAB method (Zheng et al. 1995) of DNA

isolation from rice seedling leaves was as follows.

Procedure

Young plant leaves were collected at seedling stage, about one gram of

leaves bits were cut by scissors and put in 2 ml of eppendrof tube.

Add 700µl of CTAB extraction buffer.

Grind the leaves with the help of tissuelyzer. After grinding add 300 µl of

CTAB extraction buffer.

Keep it in water bath at 650C for 20 minutes.

Add 700 µl of Chloroform: Isoamyl alcohol (24:1).

55

Vertex the sample.

Centrifuge it for 10 min at 14000 rpmin centrifuge machine.

Transfer the supernatant in 1.5 ml of fresh eppendorf tube,

(Repeat the protocol twice from step 5-8)

Add 70 µl of Sodium acetate and about 400 µl of pre-chilled isopropanol

(equal volume of the supernatant transferred) in this and kept it for incubation

at 40C for 2 hr. or -20

0C for overnight.

Centrifuge it for 3 min @ 14000 rpm.

Decant the solution and add 50 µl of 70 % ethanol for washing and

centrifuged at 14000 rpm for 5 minutes.

Decant the solution and dry the pellet for 2 hours or overnight until the smell

of ethanol was evaporated.

Finally dissolved the pellets in 50 μl of TE buffer.

Stored at -200C until use.

3.5.2 Nanodrop spectrophotometer based quantification of DNA

For quantification, DNA samples isolated from each line were quantified

on Nano Drop Spectroscopy (NANODROP, 2000c). After quantification, the DNA

was diluted with TE buffer such that the final concentration of DNA was 50 ηg / μl

for PCR analysis.

3.5.3 PCR amplification using SSR and ISSR primers:

About, 2 μl of diluted template DNA (50 ηg/μl) of each line was dispensed

in the bottom of 96 well PCR plates (AXYGEN-MAKE). Separately cocktail was

prepared in an Eppendorf tube as described in Table 3.5. About 18 μl of the

cocktail was added to each tube to make final volume 20 μl. Then, the PCR was set

as per the temperature profile given is Table 3.6 and 3.7.

Table 3.5: PCR mix for one reaction (Volume 20 μl)

Reagent Stock Concentration Volume (l)

Nanopure H2O - 13.5

PCR buffer A 10 X 2.0

dNTPs (Mix) 1.0 mM 1.0

Primer (forward) 5 ρmol 0.5

56

Primer (reverse) 5 ρmol 0.5

Taq polymerase 1 U/ μl 0.5

DNA template 50 ηg/ μl 2.0

Total 20

Table 3.6: Temperature profile used for PCR amplification using micro-

satellite Markers

Steps Temperature (C) Duration

(min.)

Cycles Activity

1

2

3

4

5

6

94

94

55

72

72

4

5

0.5

0.5

1

7

∞

1

35

1

Denaturation

Denaturation

Annealing

Extension

Final Extension

Storage

Table 3.7: Temperature profile used for PCR amplification using Inter-simple

sequence repeats Markers

Steps Temperature (C) Duration

(min.)

Cycles Activity

1

2

3

4

5

6

94

93

48-54

72

72

4

2

0.45

1

1

8

∞

1

35

1

Denaturation

Denaturation

Annealing

Extension

Final Extension

Storage

3.5.4 Visualization of amplified products in Polyacrylamide gel electrophoresis

Five percent polyacrylamide gels (vertical) were used for better separation

and visualization of PCR amplified microsatellite products, since polyacrylamide

gels have better resolution for amplified products. Gels were casted in

electrophoresis unit. Glass plates were prepared before making the gel solution.

Both glass plates (outer and inner notched glass plates) were cleaned thoroughly

with warm water, detergent and then with deionized water.

57

3.5.5 Assembling and pouring the gel

Gasket was fixed to the three sides of the outer plate (without notches).

Spacers of 1.5mm thickness were placed along the sides by just attaching the

gasket of outer plate.

Later, notch plate was kept on the outer plate so that spacers were between

the two plates. Clamps were put on the three sides of plates leaving notch side of

unit. It was checked with water to found any leakages.

For casting each gel, 65 ml of acrylamide gel (5%) solution was prepared

just prior to pouring. For each 65 ml of solution, 70 μl of TEMED (N-N-N-N-

Tetramethylethylene diamine) and 700 μl of (freshly prepared) ammonium per

sulphate (APS, 10%) were added to initiate the polymerization process.

The contents were mixed gently by swirling, but bubbles were avoided.

Before pouring, assembly was kept on the bench top so that it made 45 degree

angle with bench top.

Then gel solution was poured from notch side with maximum care to avoid

air bubbles. Comb of 1.5 mm thickness (63 wells) was inserted with tooth side in

the gel. Later, the assembly was kept for polymerization for 20-30 min.

3.5.6 Electrophoresis

After polymerization process, gasket was removed and assembly was kept

in the electrophoresis unit with electrophoresis unit clamps so that notch

side facing inner side of the unit and facing other plate without notch to

outer side.

TBE (1x) was poured in upper tank in the unit and the rest was poured in

bottom chamber.

Comb was removed with care so that it does not disturb the wells formed in

the gel.

At last, 4 μl loading dye (10x) was added to PCR products.

58

Finally, 5 μl of each sample were loaded into the wells for facilitating the

sizing of the various alleles. Ladder (50bp, Bangalore GeNei, Mereck Bio

Science) was loaded in the first well.

Gel was run at 180 volts till the dye reached bottom of the gel.

After electrophoresis, gels were stained with Ethidium bromide (10μl/

100ml) and visualized in BIORAD Gel Doc XR+.

3.5.7 Visualization of bands

After electrophoresis, clamps were removed and glass plates were

separated without damaging the gel.

a) Gel was taken out from plate into staining box with care by flipping the gel with

help of spatula and by pouring little amount of water for easy removal.

b) Ethidium bromide solution (prepared by adding 10 μl to 100 ml double distilled

water) was poured into the staining box to stain the gel.

c) It was agitated for about five minutes to stain the gel.

d) Gel stained with Ethidium Bromide was washed two times with double distilled

water to have clear images.

e) The gels were scanned with the help of BIO-RAD gel doc XR+.

f) Care was taken while using TEMED and staining with Ethidium bromide

solution as they are carcinogenic and mutagenic agents, respectively.

3.5.8 Detection of varietal polymorphism using simple sequence repeats (SSR)

primers and ISSR primers

The varietal polymorphism was detected by using 59 SSR primers and 10

ISSR primers.

59

3.5.9 Scoring and analysis of data:

The banding pattern of population developed by each set of primer was

scored separately. The size of amplified fragments was determined by comparing

the migration distance of amplified fragments relative to the molecular weight of

known size markers, 50 base pairs (bp) DNA ladder. Particular base pair position

was scored as “1” and absence of band for that particular base pair position was

scored as “0” (zero). For analysis NTSYS-pc software was used to construct a

UPGMA (unweighted pair group method with arithmetic averages) dendrogram

showing the distance-based interrelationship among the genotypes.

3.5.10 Reagents and solutions

a) Primers: Highly variable rice microsatellite markers from Imperial life sciences

(ILS), USA or Sigma Aldrich were used in the study.

b) dNTPs (dATP/dCTP/dGTP/dTTP):10 mM stock of dNTPs (Bangalore

GeNei, Mereck Bio Science) was used.

c) PCR buffer (10X): 10X GeNei buffer was used.

d) Taq polymerase: 1 unit/μl, Taq polymerase (GeNei) was used for PCR.

3.5.11 Stock solutions:

a) Stock preparation for dNTPs – 10μl of each dNTPs (i.e.

dATP/dCTP/dGTP/dTTPs) was taken in 1.5 ml of Eppendorf tube, mix well by

vortexing, final volume is made to 40μl having 100 mM dNTPs stock

concentration. For dilution 10 μl dNTPs of stock solution was taken in 1.5 ml

Eppendorf tube and add 990 μl SIGMA water to the tube, so the total volume

became 1000 μl. This makes 1mM dNTPs is ready to use for PCR.

b) DNA extraction buffer:

Tris HCl (1M; pH-8) 5 ml

EDTA (0.5M; pH-8) 5 ml

NaCl (4M) 7.5 ml

SDS (20% W/V) 5 ml

60

Final volume was adjusted to 100 ml with distilled water and the pH was

maintained to 8.0.

c) TE buffer:

1M Tris-HCl (pH-8) 10 ml

0.5M EDTA (pH-8) 2 ml

Final volume was adjusted to 100 ml and autoclaved and the pH was

maintained to 8.0.

d) EDTA (0.5M; pH-8):

186.12 g of EDTA was dissolved in 700 ml of distilled water. The pH was

set to 8 using NaOH. Final volume was adjusted to 1000 ml with distilled water

and sterilized by autoclaving.

e) 4M NaCl:

23.36 g of NaCl was dissolved in 80 ml of distilled water. Final volume

was adjusted to 100 ml and sterilized by autoclaving.

f) 1M Tris HCl (pH 8.0 at 25°C):

30.28 g of Trizma base was dissolved in 200 ml of distilled water. The pH

was set to 8.0 using concentrated HCl. The final volume was adjusted to 250 ml

with distilled water and sterilized by autoclaving.

3.5.11 Solutions for electrophoresis

a) 10X TBE buffer:

Tris base 104 g

EDTA (0.5M) 40 ml

Boric Acid 55 g

Distilled water - 500 ml Final volume was adjusted to 1 liter with distilled water.

b) 1X TBE buffer:

100 ml of 10 X TBE + 900 ml of distilled water were taken to make 1 liter

of 1X TBE.

61

c) 10X loading dye

Sucrose 667 mg

Bromophenol Blue 4.2 mg

Water 1.0 ml

d) 50 bp DNA ladder:

GeNei Mereck Biosciences, Bangalore Company was used as known

marker. This is prepared by taking 0.1ml of 50bp with 0.2 ml of 6X loading buffer

and making the volume with 0.4 ml sigma water.

3.5.12 Stocks and solutions for PAGE

a) Five percent PAGE solution (1000ml)

Acrylamide when dissolved in water, slow spontaneous auto

polymerization takes place joining molecules together by head and tail fashion to

form long single chain polymers. A solution of these polymer chains become

viscous but simple slide over one another.

Acrylamide 47.5g

Bis-Acrylamide 2.5g

10X TBE 100 ml

Acrylamide and bis-acrylamide were weighed and dissolved in (to make up

volume to 1000 ml) 500 ml distilled water and then added to the beaker containing

100 ml of 10X TBE and the volume was made upto 1000 ml by adding autoclaved

double distilled water. The solution was sterilized by passing through 0.22 micron

filter and stored in amber colour bottle at 4 0C.

b) 10% Ammonium persulphate (APS) solution was prepared by mixing

following components

Most frequent used linking agent for polyacrylamide gel.

Ammonium persulphate 1.0g

Distilled water 10ml

62

c) TEMED

Stabilizers free radicals and improve polymerization.

3.5.13 Instruments used in the laboratory

Veriti 96 well thermal cycler (Applied Biosystems)

Refrigerated centrifuge

Microwave oven

C.B.S. PAGE unit with power pack

Transilluminator and Gel documentation system( BIORAD Gel Doc XR+)

Micropipettes

Eppendorf tubes

Electronic balance

3.6 Statistical analysis

The data recorded in respect to different morphological and quantitative

characters on the forty eight short and long grain accessions were subjected to the

statistical analysis:


Firstly, mean values were worked out for all traits for each genotype. These

mean data were utilized to calculate variability parameters viz. range, standard

deviation, and coefficient of variation. ANOVA is calculated by using O.P.STAT

software.

63

Table 3.8 Skeleton of analysis of variance

Source of

Variation

Degree of

Freedom

Sum of

Square

Mean Sum of

Square

F

calculated

Replication (r-1) SSR MSR MSR /

MSE

Genotypes (g-1) SSG MSG MSG /

MSE

Error (r-1)(g-1) SSE MSE

Total (rg-1) SS total

3.6.2 Assessment of variability:

3.6.2.1 Range:

The lower and higher value of a character determines its range, which is

expressed as follows:

Range = Highest value – Lowest value.

3.6.2.2 Mean (� )

The mean is calculated by the following formula:

� =ΣXi

N

Where,

ΣXi = Summation of all the observation

N = Total number of observation

3.6.2.3 Standard deviation (SD)

Standard deviation is the root of sum of squares of deviation divided by

their number, calculated by the formula:

Standard deviation =√ Σd2 / n

Where,

d2

= Sum of squares of deviations

n = Total number of observations

64

3.6.2.4 Standard error (SE)

Standard error = S/ √�

Where,

S = Standard deviation

√n = Total number of observation

3.6.2.5 Estimation of coefficients of variation:

The coefficient of variation for different characters was estimated by

formula as suggested by Burton and De Vane (1953).

GCV (%) = (√� 2g/X) 100

PCV (%) = (√�2p/X) 100

where,

PCV = Phenotypic coefficient of variation

GCV = Genotypic coefficient of variation � = Mean of character √�g2= Genotypic variance √�p

2= Phenotypic variance

The magnitude of coefficient of variation was categorized as high (> 20%),

moderate (20% - 10%) and low (< 10%).

3.6.2.6 Heritability (broad sense)

It is the ratio of genotypic variance to the phenotypic variance (total

variance). Heritability for the present study was calculated in a broad sense by

adopting the formula as suggested by Hanson et al., (1956).

h2 (bs) % = (�g

2/� p

2) X 100

Where,

h2 (bs) = heritability in broad sense, �g2 = Genotypic variance,

65

�g2 = Phenotypic variance

As suggested by Johnson et al (1955) heritability values are categorized as

low (<30%), moderate (30 - 60%), and high (>60%).

3.6.2.7 Genetic advance

Improvement in the mean genotypic value of selected plants over the

parental population is known as genetic advance. Expected genetic advance (GA)

was calculated by the method suggested by Johnson et al., (1955)

G A = K .h2. �p

Where,

GA= Genetic advance

K = Constant (Standardized selection differential) having the value of 2.06

at 5 per cent level of selection intensity.

h2 = Heritability of the character �p= Phenotypic standard deviation

3.6.2.8 Genetic advance as percentage of mean

It was calculated by the following formula �� % �� = ��/� ×

Where,

GA = genetic advance � = mean of the character

The range of genetic advance as percent of mean is classified as suggested

by Johnson et al., (1955)

GA > 20 per cent High

GA = 10 – 20 per cent Moderate

GA < 10 per cent Low

3.6.3 Association analysis:

Correlation coefficients analysis measures the mutual relationship between

various characters at genotypic (g), phenotypic (p) and environmental levels with

the help of following formula suggested by Miller et al. (1958).

66

3.6.3.1 Path analysis

Path analysis was originally developed by Wright (1921) and first used for

plant selection by Dewey and Lu (1959). It measures the direct and indirect

contribution of independent variables on dependent variable.

The results of path coefficient analysis are interpreted as per the following

scale suggested by Lenka and Mishra (1973).

Value of direct and indirect effects Rate/ Scale

0.00 to 0.09 Negligible

0.10 to 0.19 Low

0.20 to 0.29 Moderate

0.30 to 0.99 High

> 1.00 Very high

3.6.4 Principal Components Analysis

It is a multivariate statistical analysis to reduce the data with large number

of correlated variables into a substantially smaller set of new variables through

linear combination of the variables that accounts most of the variation present in

the original variables. Principal components are generally estimated either from

correlation matrix or covariance matrix. When the variables are measured in

different units, scale effects can influence the composition of derived components.

In such situations it becomes desirable to standardize the variables. In the

present investigation correlation matrix was used to extract the principal

components.

PCA is a well-known method of dimension reduction (Massy, 1965;

Jolliffe, 1986), which seeks linear combinations of the columns of X with maximal

variance, or equivalently, high information. The analysis was performed using

XLSTAT 2014 sofware.

3.6.6 Cluster analysis

Cluster analysis is a multivariate method which aims to classify a sample of

subjects (or objects) on the basis of a set of measured variables into a number of

67

different groups such that similar subjects are placed in the same group. Cluster

analysis has no mechanism for differentiating between relevant and irrelevant

variables. Therefore, the choice of variables included in a cluster analysis must be

underpinned by conceptual considerations. This is very important because the

clusters formed can be very dependent on the variables included.

In the present study, Euclidian distance between genotypes was calculated

from the standardized data matrix by Unweighted Pair Group Method using

Arithmetic Averages (UPGMA) method and clustering was done by

Agglomerative Hierarchical method using XLSTAT 2014 software.

68

CHAPTER- IV

RESULTS AND DISCUSSION

Rice is the principal cereal food crop grown most extensively in the tropical

and sub-tropical regions of the world. Though, cultivated on large area, rice crop is

characterized by low productivity due to lack of high yielding varieties adapted to

different seasons and agronomic conditions. Now most of the plant breeders

recognize the importance of utilizing genetic diversity in breeding programmes to

meet the continuously expanding needs of varietal improvement.

Grain quality characteristics of rice are related to a complexity of physic-

chemical properties viz., dimension, shape and weight, fragmentation, hardness,

milling properties, chemical composition of the endosperm, aroma. Nearly all

possible combinations of the above component traits can be found in existing

cultivars, signifying the enormous diversity that exists in rice germplasm.

Among the various grain quality characters, grain length (GL), grain breath

(GB), cooked grain length (CGL), cooked grain breath (CGB) and gelatinization

temperature (GT) are considered as prime characters in deciding the overall grain

quality in rice.

The experimental results obtained from present investigation have been

described in following heads:

4.1 Agro-morphological and quality characterization

4.2 Estimation of Genetic Variance


4.2.2 Mean performance of and variability parameters different characters

4.2.3 Genotypic and phenotypic component of variation

4.2.4 Heritability and genetic advance as percent of mean


4.3.1 Correlation Coefficient

4.3.2 Path Analysis

4.4 Principal component analysis

69

4.5 Cluster analysis


4.6.1 Development of genotypic data based on SSR and ISSR markers

4.6.1.1 SSR Primers

4.6.1.1a Similarity coefficient analysis and Clustering

4.6.1.1b Polymorphism Information Content

4.6.1.2 ISSR Primers


4.6.1.2b Polymorphism Information Content

4.1 Agro-morphological and quality characterization

These observations were recorded on 48 germplasm accessions all

descriptors showed makeable differences in their distribution and amount of

variations within them. The data of agro-morphological and quality

characterization as observed in 48 accessions are presented in Appendix C.

Frequency distribution and percentage value of agro-morphological and quality

characters of forty eight long and short grain accessions of rice are presented in

Table 4.1., Table 4.2 and Fig 4.1).

4.1.1 Coleoptile colour

All forty eight landraces under study were classified into three different

classes of coleoptiles colour (DRR, DUS discriptors), colourless, green and purple,

out of which coleoptiles colour was observed under two categories; green (38) and

purple (10) (Fig: 4.1a and 4.2).

4.1.2 Basal leaf sheath colour

Basal leaf sheath colour was observed under two categories, green (32) and

purple line (16) (Fig: 4.1b and 4.3).

4.1.3 Leaf intensity of green colour

This trait was observed under two categories; Dark green (5) and medium

(43) (Fig: 4.1c).

70

4.1.4 Leaf: Pubescence of blade surface

This trait was observed under four categories; Weak (12), Strong (5),

Medium (30) and Hard (1) (Fig: 4.1d).

4.1.5 Leaf: Auricles

Leaf auricle was present in all forty eight germplasm accessions (Fig: 4.4)

4.1.6 Leaf: Anthocyanin colouration of auricles

This trait was observed under two categories; colourless (46) and light

purple (2).

4.1.7 Leaf: Collar

Leaf collar was present in all forty eight long and short grain landraces.

4.1.8 Leaf: Ligule

This trait was found in all the forty eight landraces (Fig: 4.5)

4.1.9 Leaf: Shape of ligule

This trait was observed under two categories; split (45) and acute (3).

4.1.10 Colour of ligules

Colour of ligule was found white in all the germplasm accessions.

4.1.11 Culm: Attitude

This trait was observed under three categories; Erect (30), Semi-erect (15)

and Spreading (3) (Fig: 4.1f).

4.1.12 Attitude of flag leaf (Early)

This trait was observed under two categories; Erect (40) and Semi-erect (8)

(Fig: 4.1g and 4.7).

4.1.13 Spilelet: Density of pubescence of lemma

This trait was observed under four categories; weak (5), medium (22),

strong (15) and very strong (6) (Fig: 4.1h).

4.1.14 Male Sterility

Male sterility was found absent in all the forty eight germplasm accession.

71

4.1.15 Lemma: Anthocyanine colouration of keel

Anthocyanine colouration of keel of lemma was found under4 five

categories; Weak (6), Medium (1), Strong (10), Very Strong (8) and absent (23)

(Fig: 4.1i and 4.8).

4.1.16 Lemma: Anthocyanine colouration of area below apex

This trait was found under five categories; absent (27), Weak (5), Medium

(2), Strong (6) and Very Strong (8) (Fig: 4.1j and 4.9).

4.1.17 Lemma: Anthocyanine colouration of apex

This trait was found under five categories; absent (26), weak (5), medium

(3), Strong (6) and Very Strong (8) (Fig: 4.1k).

4.1.18 Spilelet: Colour of Stigma

The colour of stigma of different forty eight accessions were found under

two categories; White (34) and Purple (14) (Fig: 4.1l and 4.10).

4.1.19 Stem: Anthocyanine colouration of nodes

This trait was found under two categories; present (25) and absent (23)

(Fig: 4.12).

4.1.20 Stem: Intensity of anthocyanine colouration of nodes

This trait was found under four categories; Absent (23), Weak (1), Medium

(23) and Strong (1).

4.1.21 Stem: Anthocyanine colouration of internode

This trait was found under two categories; Present (26) and absent (22).

4.1.22 Flag leaf: Attitude of blade (late observation)

This trait was found under four categories; Desceading (1), Erect (28),

Semi-erect (1) and Horizontal (18).

4.1.23 Panicle: Curvature of main axis

Curvature of panicle was found under three categories; Deflexed (13),

Semi-straight (25) and Straight (10) (Fig: 4.1p and 4.11).

4.1.24 Spikelet: Colour of tip of lemma

This trait was found under five categories; Black (15), Purple (3), Red (4),

White (5) and Yellow (21) (Fig: 4.1q).

72

4.1.25 Lemma and palea colour

Lemma and palea colour was observed under eight categories; Brown (1),

brown furrows on straw (6), Brown spot on straw (1), Gold and gold furrows on

straw (3), Purple furrows on straw (3), Red (8), Reddish to light purple (2) and

Straw (24) (Fig: 4.1r and 4.13).

4.1.26 Panicle: Awns

This trait was observed under two categories; Present (20) and Absent (28)

(Fig: 4.1s and 4.14).

4.1.27 Panicle: Colour of awns (late observation)

This trait was found under four categories; Absent (28), Brown (1), Red (5)

and Yellowish (14) (Fig: 4.1t).

4.1.28 Panicle: Distribution of awns

This trait was found in two categories; Tiponly (20) and rest of the

accessions does not have awns on them i.e. Absent (28) (Fig: 4.1v and 4.16).

4.1.29 Panicle: Presence of secondary branching

Secondary branching in panicle was present in all forty eight germplasm

accessions (Fig: 4.1w and 4.16).

4.1.30 Panicle: Secondary branching

Secondary branching of panicle was found under three categories; Cluster

(11), Strong (16) and Weak (21).

4.1.31 Panicle : Attitude of branches

This trait was found under five categories; Erect (5), Erect to Semi-erect

(11), Semi-erect (13), Semi-erect to spreading (4) and Spreading (15) (Fig: 4.1x).

4.1.32 Panicle: Exertion

The exertion of panicle was found under three categories; Mostly exerted

(23), Partly exerted (2) and Well exerted (23) (Fig: 4.1y and 4.18).

4.1.33 Leaf: Senescence

This trait was observed under two categories; Early (9) and Medium (39)

(Fig: 4.1aa).

73

4.1.34 Sterile lemma: Colour

The colour of sterile lemma of forty eight accession were found under five

categories; Gold (15), Purple (4), Red (1), Straw (27) and Yellow (1) (Fig: 4.1ab).

4.1.35 Grain: Phenol reaction of lemma

Out of 48 rice accessions phenol reaction of lemma exhibited in 6

genotypes and in 42 accessions phenol reaction is absent (Fig 4.24).

4.1.36 Decorticated grain shape

This trait was found under 5 category Basmati type (4), extra long slender

(18), long bold (1), long slender (1), short bold(24) (Fig:4.21).

4.1.37 Decorticated grain: Colour

Out of 48 rice accessions brown colour is observed in only one accession

and rest of the 47 had white colour.

4.1.38 Alkali spreading value

Out of 48 accessions, high alkali spreading value found in one accession,

intermediate in 13 accessions and low in 34 accessions (Fig. 27).

4.1.39 Aroma

Out of forty eight genotypes, 3 showed strong aroma, 17 genotypes were

having mild aroma and 38 genptypes were non - scented.

74

Table 4.1: Frequency distribution of agro-morphological and quality traits

based on DUS S.

No.

Traits Category Number Frequency

(%)

1 Coleoptile colour Green

Purple

38

10

79.17

20.83

2 Basal leaf: Sheath colour Green

Purple line

32

16

66.67

33.33

3 Leaf: Intesity of green

colour

Dark Green

Medium

5

43

10.42

89.58

4 Leaf:Anthocyanin

colouration

Absent 48 100.00

5 Leaf: Pubescence of blade

surface

Hard

Medium

Strong

Weak

1

30

5

12

2.08

62.50

10.42

25.00

6 Leaf: Auricles Present 48 100.00

7 Leaf: Anthocyanin

colouration of auricles

Colourless

Light Purple

46

2

95.83

4.17

8 Leaf: Collar Present 48 100.00

9 Leaf: Ligule Present 48 100.00

10 Leaf: Shape of Ligule Split

Acute

45

3

93.75

6.25

11 Leaf: Colour of ligule White 48 100.00

12 Leaf: Length of blade Short

Medium

Long

4

41

3

8.33

84.38

7.29

13 Leaf: Width of blade Narrow 48 100.00

14 Culm: Attitude Erect

Semi erect

spreading

30

15

3

62.50

31.25

6.25

15 Flag leaf: Attitude of

blade(Early observation)

Erect

Semi erect

40

8

83.33

16.67

16 Spikelet: Density of

pubescence of lemma

Medium

Strong

Very strong

Weak

22

15

6

5

45.83

31.25

12.50

10.42

17 Male sterility Absent 48 100.00

18 Lemma: Anthocyanin

colouration of keel

Medium

Strong

Very Strong

Weak

Absent

1

10

8

6

23

2.08

20.83

16.67

12.50

47.92

19 Lemma:

Anthocyanincolouration of

area below apex

Medium

Strong

Very Strong

Weak

Absent

2

6

8

5

27

4.17

12.50

16.67

10.42

56.25

75

20 Lemma: Anthocyanin

colouration of apex

Absent

Weak

Medium

Strong

Very Strong

26

5

3

6

8

54.17

10.42

6.25

12.50

16.67

21 Spikelet: colour of stigma Purple

White

14

34

29.17

70.83

22 Stem: Thickness Thin

Thick

Medium

2

9

37

4.17

18.75

77.08

23 Stem: Length(excluding

panicle)

Very Short

Short

Medium

Long

19.5

1

11

16.5

40.63

2.08

22.92

34.38

24 Stem: Anthocyanin

colouration of nodes

Present

Absent

25

23

52.08

47.92

25 Stem: Intensity of

anthocyanin colouration of

nodes

Strong

Medium

Weak

Absent

1

23

1

23

2.08

47.92

2.08

47.92

26 Stem: Anthocyanin

colouration of internode

Present

Absent

26

22

54.17

45.83

27 Flag leaf: Attitude of

blade(Late observation)

Descending

Erect

Semi erect

Horizontal

1

28

1

18

2.08

58.33

2.08

37.50

28 Panicle: Curvature of main

axis

Deflexed

Semi straight

Straight

13

25

10

27.08

52.08

20.83

29 Spikelet: Colour of tip of

lemma

Black

Purple

Red

White

Yellow

15

3

4

5

21

31.25

6.25

8.33

10.42

43.75

30 Lemma and Palea colour Brown

Brown furrows on straw

Brown spot on straw

Gold and gold furrows on

straw background

Purple furrows on straw

Red

Reddish to light purple

Straw

1

6

1

3

3

8

2

24

2.08

12.50

2.08

6.25

6.25

16.67

4.17

50.00

31 Panicle:Awns Present

Absent

20

28

41.67

58.33

32 Panicle: Colour of awns(late

observation)

Absent

Brown

Red

Yellowish white

28

1

5

14

58.33

2.08

10.42

29.17

76

33 Panicle: Length of longest

awn

Absent

Long

Medium

Short

28

1

6.5

12.5

58.33

2.08

13.54

26.04

34 Panicle: Distribution of awns Absent

Tip only

28

20

58.33

41.67

35 Panicle: Presence of

secondery branching

Present 48 100.00

36 Panicle: Secondery

branching

Cluster

Strong

Weak

11

16

21

22.92

33.33

43.75

37 Panicle: Attitude of branches Erect

Erect to semi erect

Semi erect

Semi erect to spreading

Spreading

5

11

13

4

15

10.42

22.92

27.08

8.33

31.25

38 Panicle: Exertion Mostly exerted

Partly exerted

Well exerted

23

2

23

47.92

4.17

47.92

39 Time Maturity(Days) Early

Medium

Late

1

16

31

2.08

33.33

64.58

40 Leaf: senescence Early

Medium

9

39

18.75

81.25

41 Sterile lemma: Colour Gold Purple Red Straw Yellow

15 4 1

27 1

31.25 8.33 2.08

56.25 2.08

42 Grain: Phenol reaction of

lemma

Present

Absent

6

42

12.50

87.50

43 Decorticated grain shape Basmati type

Extra long slender,

Long Bold

Long Slender

Short Bold

4

18

1

1

24

7.29

37.50

3.13

2.08

50.00

44 Decorticated grain: Colour Brown

White

1

47

2.08

97.92

45 Expression of White core Small

Very small

Medium

Large

7

1

20

20

14.58

2.08

41.67

41.67

46 Alkali spreading value High

Intermediate

Low

1

13

34

2.08

27.08

70.83

47 Decorticate grain: Aroma Mild Scented

Strongly Scented

Non Scented

17

3

38

35.42

6.25

79.17

77

Figure 4.1 (a-ab): Frequency distribution of 28 polymorphic DUS trait

0

10

20

30

40

green purple

38

10

No

. o

f en

trie

s

Coleoptile colour

Fig. 4.1(a): Frequency distribution

pattern of Coleoptile colour

0

10

20

30

40

Green Purple line

32

16

No

. o

f en

trie

s

Basal leaf: Sheath colour

Fig. 4.1(b): Frequency distribution

pattern of Basal leaf: Sheath colour

0

10

20

30

40

50

Dark Green Medium

5

43

No

. o

f en

trie

s

Leaf: Intesity of green colour

Fig. 4.1(c): Frequency distribution

pattern of Leaf: Intesity of green

colour

05

1015202530

1

30

5

12

No

. o

f en

trie

s

Leaf: Pubescence of blade surface

Fig. 4.1(d): Frequency distribution

pattern of Leaf: Pubescence of blade

surface

0

10

20

30

40

50

Short Medium Long

4

40.5

3.5

No

. o

f en

trie

s

Leaf: Length of blade

Fig. 4.1(e): Frequency distribution

pattern of Leaf: Length of blade

05

1015202530

30

15

3

No

. o

f en

trie

s

Culm: Attitude

Fig. 4.1(f): Frequency distribution

pattern of Culm: Attitude

78

0

10

20

30

40

Erect Semi erect

40

8

No

. o

f en

trie

s

Flag leaf: Attitude of blade

Fig. 4.1(g): Frequency distribution

pattern of Flag leaf: Attitude of

blade(Early)

05

10152025

2215

6 5

No

. o

f en

trie

s

Spikelet: Density of pubescence of

lemma

Fig. 4.1(h): Frequency distribution

pattern of Spikelet: Density of

pubescence of lemma

05

10152025

110 8 6

23

No

. o

f en

trie

s

Anthocyanin colouration of keel of

lemma

Fig. 4.1(i): Frequency distribution

pattern of Anthocyanin colouration

of keel of lemma

0102030 27

52 6 8

No

. o

f en

trie

s

Lemma: Anthocyanincolouration of

area below apex

Fig. 4.1(j): Frequency distribution

pattern of Lemma:

Anthocyanincolouration of area

below apex

05

1015202530 26

5 3 6 8

No

. o

f en

trie

s

Lemma: Anthocyanin colouration of

apex

Fig. 4.1(k): Frequency distribution

pattern of Lemma: Anthocyanin

colouration of apex

0

5

10

15

20

25

30

35

Purple White

14

34

No

. o

f en

trie

s

Spikelet: colour of stigma

Fig. 4.1(l): Frequency distribution

pattern of Spikelet: colour of stigma

79

05

10152025303540

Thin Thick Medium

2

9

37

No

. o

f en

trie

s

Stem: Thickness

Fig. 4.1(m): Frequency distribution

pattern of Stem: Thickness

0

5

10

15

2019.5

1

11

16.5

No

. o

f en

trie

s

Stem: Length(excluding panicle)

Fig. 4.1(n): Frequency distribution

pattern of Stem: Length(excluding

panicle)

05

1015202530

1

28

1

18

No

. o

f en

trie

s

Flag leaf: Attitude of blade(Late)

Fig. 4.1(o): Frequency distribution

pattern of Flag leaf: Attitude of

blade(Late)

0

5

10

15

20

25

Deflexed Semi

straight

Straight

13

25

10

No

. o

f en

trie

s

Panicle: Curvature of main axis

Fig. 4.1(p): Frequency distribution

pattern of Panicle: Curvature of main

axis

0

5

10

15

20

2515

34 5

21

No

. o

f en

trie

s

Spikelet: Colour of tip of lemma

Fig. 4.1(q): Frequency distribution

pattern of Spikelet: Colour of tip of

lemma

05

10152025

Bro

wn

Bro

wn

…B

row

n s

pot …

Gold

an

d g

old

…P

urp

le …

Red

Red

dis

h to …

Str

aw

16

1 3 38

2

24

No

. o

f en

trie

s

Lemma and Palea colour

Fig. 4.1(r): Frequency distribution

pattern of Lemma and Palea colour

80

0

5

10

15

20

25

30

Present Absent

20

28

No

. o

f en

trie

s

Panicle:Awns

Fig. 4.1(s): Frequency distribution

pattern of Panicle:Awns

05

1015202530

28

1 5

14

No

. o

f en

trie

s

Panicle: Colour of awns(late)

Fig. 4.1(t): Frequency distribution

pattern of Panicle: Colour of

awns(late)

05

1015202530

28

16.5

12.5

No

. o

f en

trie

s

Panicle: Length of longest awn

Fig. 4.1(u): Frequency distribution

pattern of Panicle: Length of longest

awn

0

5

10

15

20

25

30

Absent Tip only

28

20

No

. o

f en

trie

s

Panicle: Distribution of awns

Fig. 4.1(v): Frequency distribution

pattern of Panicle: Distribution of

awns

0

5

10

15

20

25

Cluster Strong Weak

1116

21N

o. o

f en

trie

s

Panicle: Secondary branching

Fig. 4.1(w): Frequency distribution

pattern of Panicle: Secondary

branching

0

5

10

15

Erect Semi erect to

spreading

5

11 13

4

15

No

. o

f en

trie

s

Panicle: Attitude of branches

Fig. 4.1(x): Frequency

distribution pattern of Panicle:

Attitude of branches

81

0

5

10

15

20

25

Mostly

exerted

Partly

exerted

Well

exerted

23

2

23N

o. o

f en

trie

s

Panicle: Exertion

Fig. 4.1(y): Frequency

distribution pattern of Panicle:

Exertion

0

10

20

30

40

Early Medium Late

1

16

31

No

. o

f en

trie

s

Time Maturity

Fig. 4.1(z): Frequency

distribution pattern of Time

Maturity

0

10

20

30

40

Early Medium

9

39

No

. o

f en

trie

s

Leaf: senescence

Fig. 4.1(aa): Frequency

distribution pattern of Leaf:

senescence

0

5

10

15

20

25

30

15

41

27

1

No

. o

f en

trie

s

Sterile lemma: Colour

Fig. 4.1(ab): Frequency

distribution pattern of Sterile

lemma: Colour

82

Fig 4.2: Coleoptile colour Fig 4.3: Basal leaf sheath colour Fig 4.4: Auricle

Fig 4.5: Ligule Fig 4.6: Width of leaf blade Fig 4.7: Flag leaf attitude of blade

Green

(Farsaphool)

Purple

(Jaybjarang)

Auricle

Narrow

(Mani)

83

Lemma Anthocyanin

Colouration of Keel

Lemma Anthocyanin

colour below Apex

Stigma Colour

Fig 4.8: Lemma Anthocyanini

colouration of keel

Fig 4.9: Lemma anthocyanin

colour below apex Fig 4.10: Stigma colour

Fig 4.11: Curvature of Panicle Fig 4.12: Anthocyanin colour

of Node

Fig 4.13a: Lemma and Palea

Colour

84

Fig 4.13b: Lemma and Palea Colour Fig 4.14: Panicle Awn Fig 4.15: Panicle length of Awn

Fig 4.16: Panicle distribution of awn Fig 4.17: Panicle secondary branching Fig 4.18: Panicle exertion

85

Fig 4.19: Grain length Fig 4.20: Decorticated grain length Fig 4.21: Decorticated grain shape

Fig 4.22: Decorticated grain colour Fig 4.23: Grain length after cooking Fig 4.24: Grain phenol reaction

86

Fig 4.25: Amylose Fig 4.26: Chalkiness Fig 4.27: Alkali spreading value test

Fig 4.28: Gel consistency (Soft/Medium/Hard)

87

4.2 Estimation of genetic variance


The analysis of variance of 33 yield and quality traits of 48 (24 short and 24

long grains) rice germplasm accessions presented in Table 4.2. The statistical

procedure which separates or splits the total variation into different components is

known as analysis of variation. It is useful in estimating the different components

of variance. Such analysis divides the total variation into two main viz, variation

between varieties and variation within varieties i.e, environmental variation into

genotypic and environmental components.

The results of the analysis of variance indicated that the mean sum of

squares due to accession for replication were significant for most of the characters

except leaf: width of blade, panicle: length of main axis; panicle: length of longest

awn; grain: weight of 1000 fully developed grains; grain length, decorticated grain:

width, L/B ratio of decorticated grain, milling percent, length of milled grain,

width and L/B ratio of milled grain.

The mean sum of squares due to genotype/ treatments was found to be

highly significant for all the traits. This clearly indicates that variability does exist

in all the genotypes for all the traits. The significant and relatively large percentage

of the total variation attributable to GxE interaction suggests that genotypes

responded differentlly to envioronment of rice.

Under study, presence of high variability for plant height is in agreement

with Hein et al. (2007), Sarawgi et al. (2012), Chakravorty et al. (2013).

Significant variability for days to 50% flowering was estimated in present

study supports the findings of Subba Rao et al. (2013), Sarawgi (2014), Sajid et al.

(2015).

Significant variability for grain yield observed in this study is supported by

the findings of Ogunbayo et al. (2005), Vanisree et al. (2011), Sarawgi et al.

(2012) and Tuhia-Khatun et al. (2015).

88

Table 4.2: Analysis of variance of 33 yield and quality traits of 48 (24 short and 24 long grains length) rice germplasm accessions

SV

DF

Mean sum of squares

1 2 3 4 5 6 7 8 9 10

Rep 1 4.99* 0.004 1254.26** 0.05** 89.12* 0.87 107.65* 11.38** 0.003 1218.37**

Treat 47 56.5** 0.019** 130.64** 0.011** 982.68** 23.98** 1228.61** 2.01** 1.391** 138.57**

Error 47 1.2 0.005 1.94 0.003 15.77 1.4 19.22 0.24 0.008 2.35

SV

DF

Mean sum of squares

11 12 13 14 15 16 17 18 19 20

Rep 1 0.07 0.003 0.15** 37** 0.13** 0.001 0.001 2274888.37** 101465.01** 2,198.83**

Treat 47 144.58** 12.82** 0.26** 58.65** 5.96** 0.271** 0.04** 88992.88** 8,927.39** 2,166.74**

Error 47 0.05 0.028 0.01 0.68 0.01 0.016 0.001 39,864.35 6,130.45 2,016.39

SV

DF

Mean sum of squares

21 22 23 24 25 26 27 28 29 30 31 32 33

Rep 1 1.69* 0.21 0.22** 0.013 0.06 0.01 0.28** 0.1* 0.01 0.03** 0.023 4.08* 6*

Treat 47 68.73** 80.63** 125.83** 4.494** 0.2** 1.17** 7.25** 0.28** 0.58** 0.12** 0.152** 34.42** 424.74**

Error 47 0.29 10.47 0.01 0.012 0.01 0.02 0.01 0.01 0.01 0.003 0.008 0.67 0.78

1 = Leaf: Length of blade ; 2 = Leaf: Width of blade ; 3 = Time of heading(50% plants with panicle) ; 4 = Stem: Thickness ; 5 = Stem: Length(excluding panicle) ; 6

= Panicle: Length of main axis ; 7 = plant height ; 8 = Panicle: Number per plant (number of tillers) ; 9 = Panicle: Length of longest awn ; 10 = Time Maturity(Days) ;

11 = Grain: Weight of 1000 fully develop grain ; 12 = Grain: Length ; 13 = Grain: Width ; 14 = L/B ratio ; 15 = Decorticated grain: Length ; 16 = Decorticated grain:

Width ; 17 = L/B Ratio of decorticated grain ; 18 = Biological Yield(gm) ; 19 = Grain Yield(gm) ; 20= Harvest Index ; 21 = Hulling Percent ; 22 = Milling Percent ;

23 = Head Rice Recovery ; 24 = Length of milled grain ; 25 = Width of milled grain ; 26 = L/B ratio of milled grain ; 27 = Length of cooked kernel ; 28 = Width of

cooked kernel ; 29 = L/B ratio of cooked kernel ; 30 = Elongation Ratio ; 31 = Elongation index ; 32 = Endosperm content of Amylose ; 33 = Gel Consistency.

* and ** Significant at 5% and 1% probability level

89

4.2.2 Mean and variability parameters for 33 yield and quality traits of 48 (24

short and 24 long grains) rice germplasm accessions

Execution of the breeding programmes depends largely on the presence of

significant genetic variability to permit effective selection. Relative magnitude of

variability presence in a crop species helps the breeder to handle the breeding

population created by hybridizing the selected donors with high yielding base

varieties. Results revealed that high degree of variability was present in the

breeding lines for all the characters under study.

The mean and variability parameters for 33 yield and quality traits of 48

(24 short and 24 long grains) rice germplasm accessions are presented in table 4.3

and mean performance for different quantitative and quality characters under

present study is presented in Appendix D.

4.2.2.1 Leaf: Length of blade:

The mean of leaf length of blade was found 36.17 cm with minimum length

of blade of 27.00 cm (Krishna Bhog) and maximum of 48.70 cm (Banreg). The

maximum leaf length of blade was recorded is 48.70 cm in Banreg followed by

47.90 cm (Ruchi) and 47.00 cm (Kakeda (I)). The coefficient of variation observed

for this trait was 14.70%.

4.2.2.2 Leaf: Width of blade:

The mean of width of leaf blade was found 0.71 cm with minimum leaf

width of blade of 0.50 cm (Atma Sital) and maximum of 0.90 cm (Lanji). The

maximum leaf : width of blade was recorded is 0.90 cm in Lanji followed by 0.85

cm (Rani Kajar), Basabhog, Hira Nakhi, Banas Kup (II), Khatiya pati, Girmit,

Banreg and Narved. The coefficient of variation recorded for this trait was 13.70%

(Fig: 4.6)

4.2.2.3 Time of heading (50% plant with panicle) days:

The range for days to 50% flowering varied from 88.00 days (Basa Bhog)

to 126.00 days (Lokti Machhi CGR No. 10029) with the overall mean of 112.11

days. Four categories for days to 50% flowering were reported i.e. early (91-

90

Table 4.3: Mean and Variability parameters for 33 yield and quality traits of

48 (24 short and 24 long grains length) rice germplasm accessions

S.

No.

Characters Mean Standard

Error

Standard

Deviation

Coefficient of

Variation (%)

1 Leaf: Length of blade(cm) 36.17 0.77 5.32 14.70

2 Leaf: Width of blade(cm) 0.71 0.01 0.10 13.70

3 Time of heading(50% plants

with panicle) 112.11 1.17 8.08 7.21

4 Stem: Thickness(cm) 0.47 0.01 0.07 15.67

5 Stem: Length(excluding

panicle)(cm) 141.91 3.20 22.17 15.62

6 Panicle: Length of main axis 22.71 0.50 3.46 15.25

7 Plant height(cm) 164.62 3.58 24.79 15.06

8 Panicle: Number per plant

(number of tillers) 7.44 0.15 1.00 13.50

9 Panicle: Length of longest awn 0.57 0.12 0.83 16.38

10 Time Maturity(Days) 141.21 1.20 8.32 5.89

11 Grain: Weight of 1000 fully

develop grain(g) 22.03 1.23 8.50 18.60

12 Grain: Length(mm) 8.21 0.37 2.53 25.84

13 Grain: Width(mm) 2.51 0.05 0.36 14.47

14 L/B ratio 18.8 0.78 5.42 23.81

15 Decorticated grain:

Length(mm) 5.8 0.25 1.73 24.77

16 Decorticated grain:

Width(mm) 2.34 0.05 0.37 15.73

17 L/B Ratio of decorticated grain 0.47 0.02 0.14 25.24

18 Biological Yield(g) 844.688 30.45 210.94 24.97

19 Grain Yield(g) 181.09 9.64 66.81 31.89

20 Harvest Index 22.30 4.75 5.08 22.82

21 Hulling Percent 72.14 0.85 5.86 8.13

22 Milling Percent 61.99 0.92 6.35 10.24

23 Head Rice Recovery (%) 49.44 1.14 7.93 16.04

24 Length of milled grain(mm) 5.23 0.22 1.50 23.66

25 Width of milled grain(mm) 2.26 0.05 0.32 14.01

26 L/B ratio of milled grain 2.36 0.11 0.77 27.44

27 Length of cooked kernel(mm) 8.3 0.27 1.90 22.95

28 Width of cooked kernel(mm) 3.21 0.05 0.37 11.66

29 L/B ratio of cooked kernel 2.58 0.08 0.54 20.98

30 Elongation Ratio 1.63 0.04 0.25 15.25

31 Elongation index 1.16 0.04 0.28 23.77

32 Endosperm content of

Amylose 22.46 0.60 4.15 18.47

33 Gel Consistency 90.46 2.10 14.57 16.11

91

90days), medium (91-110days), late (111-130days) and very late (> 131days). The

C.V. recorded for this trait was 7.21%.

Table 4.3 a: List of germplasm categorized into early, medium and late days

to flowering

Category Short grain rice germplasm

Early ADT:27 (85 days)

Medium Kanak Jira (99); Jhumera(106); Kakeda (I)(96); Bhulau(108); Rani

kajar(100); Sundar mani(107); Bhado kanker(102); Jhumarwa(108);

Bishnu(107); Basa Bhog(94);Krishna Bhog(103); Lokti

Maudi(109); Ganja Kali(102); Dhangari Khusha(102);

Bhaniya(102)

Late

Lokti Machhi(117); Atma Sital(121); Lokti Machhi(121);

Anjania(119); Dubraj II(123); Hira Nakhi(114); Kariya bodela

bija(113); Banas KupiII(114)

Category Long grain rice germplasm

Late Farsa phool(112); Jay Bajrang(113); Gilas(112); Khatia pati(115);

Mani(123); Khatriya pati(113); Girmit(119); Lanji(114);

Banreg(123); Ruchi(120); Safed luchai(113); Kanthi deshi(119);

Piso III(111); Kakdi(122); Gajpati(113); Gadur sela(121); Aadan

chilpa(114); Unknown(122); Saja chhilau(113); Parmal Safri(119);

Safri(114); Narved(121); Nagbel(114); Mudariya(118)

4.2.2.4 Stem: Thickness (cm):

The range of stem thickness varied from 0.30 cm (Sunder Mani) to 0.65 cm

(Anjania) with the grand mean of 0.47 cm. The maximum stem thickness was

recorded was 0.65 cm in Anjania followed by 60 cm (Kariya Bodela Bija, Girmit

and Piso III). The C.V. was 15.67% for stem thickness.

4.2.2.5 Stem Length (cm):

The mean of stem length was found 141.90 cm with minimum stem length

of 82.20 cm (ADT: 27) and maximum of 179.60 cm (Khatia Pati). The maximum

stem length was recorded is 179.60 cm in Khatia Pati followed by 179.20 cm Lanji

and 177.60 Nagbel. The C.V. was recorded for this trait was 15.62%.

92

4.2.2.6 Panicle: Length of main axis (cm):

Four category of panicle length was found i.e. Very short (< 16 cm), Short

(16-20 cm), Medium (21-25 cm) and Long (26-30 cm). The maximum and

minimum panicle length were found 28.00 cm (Khatia Pati) and 14.05 cm (Rank

Kajar), respectively,with the overall mean of 22.71 cm. Highest panicle length was

found 28.00 cm in Khatia pati followed by 27.35 cm in Adan Chilpa and 27.20 cm

in Kanthi deshi. The C.V. was recorded for this trait was 15.25%.

Table 4.3b: List of germplasm categorized into very short, short, medium and

long panicle length

Category Name of accession

Short grain rice germplasm

Very short Bhulau; Rani kajar;

Short Anjania; Jhumera; Kakeda (I); Dubraj II; Sundar mani; Jhumarwa;

Kariya bodela bija; Banas KupiII; Dhangari Khusha; Bhaniya

Medium Lokti Machhi; Atma Sital; Lokti Machhi; ADT:27; Kanak Jira; Bhado

kanker; Bishnu; Basa Bhog; Krishna Bhog; Hira Nakhi;Lokti Maudi;

Long Ganja Kali

Long grain rice germplasm

Short Mani

Medium Farsa phool; Jay Bajrang; Gilas; Khatriya pati; Girmit; Lanji; Banreg;

Kakdi; Gajpati; Gadur sela; Saja chhilau; Parmal Safri; Narved;

Mudariya

Long Khatia pati; Ruchi; Safed luchai; Kanthi deshi; Piso III; Aadan chilpa;

Unknown; Safri; Nagbel

4.2.2.7 Plant height (cm):

The height of plant accession ranged from 103.00 - 207.60 cm with the

mean plant height of 164.62 cm. The maximum plant height was recorded in

Khatia Pati (207.60 cm) followed by Nagbel (204.75 cm) and Lanji (204.65 cm)

and the minimum plant height was recorded in ADT: 27 (103.00cm). The C.V. was

observed 15.06% for this trait.

4.2.2.8 Number of panicle per plant:

The range of number of panicle per plant varied from 5.85 to 9.83 with an

overall mean of 7.44. The highest number of panicles per plant was recorded in

Kakdi (9.83) followed by Nagbel (8.99) and Anjania (8.93). The minimum number

93

of panicle per plant was recorded in Dubraj II (5.85). The C.V. was recorded

13.50% for this trait.

4.2.2.9 Panicle: Length of longest awn (cm):

The length of longest awn ranged from 0.00-3.40 cm with a overall mean of

0.57 cm. The longest awn in recorded in Khatia Pati (3.40 cm) followed by Kanthi

deshi (2.55) and Lanji (2.15 cm) and all the short grain germplasm accessions were

awnless. The C.V. was observed 16.38% for this trait (Fig: 4.15).

4.2.2.10 Time Maturity (Days):

Days to maturity ranged between 116 to 155.50 days with an average of

141.21 days. Atma Sital (155.50 days) took maximum duration to reach maturity

followed by Lokti Machhi CGR no. 10029 (154.00 days), Lokti Machhi CGR no.

10031 (149.50 days) and Banreg (149.00 days). The minimum period for maturity

was recorded in Basa Bhog (116.00 days). The C.V. was recorded 5.89 % for this

trait.

4.2.2.11 1000-seed weight (g):

1000-seed weight ranged from 10.35 gm to 38.65 gm with an average

weight of 22.033 cm. The maximum 1000-seed weight recorded in Jay Bajrang

(38.65 gm) followed by Khatia Pati (38.55 gm) and Nagbel (37.50 gm). The

minimum 1000-seed weight recorded in Krishna Bhog (10.35 gm). The C.V. was

18.60 % for this trait.

4.2.2.12 Grain length (mm):

Grain length ranged from 5.15 to 11.80 mm with the mean performance of

8.21 mm. Jay Bajrang (11.80 mm) recorded maximum grain length, followed by

Nagbel (11.45 mm), Khatiya Pati (11.40 mm), Banreg (11.10 mm) and Mudaria

(11.05 mm). The minimum length of grain was recorded for Jhunarwa (5.15 mm),

Rani Kajar (5.15 mm), Lokti Machhi CGR No. 10029 (5.25), Basa Bhog (5.25),

Krishna Bhog (5.25). The C.V. observed for this trait was 25.84 % (Fig: 4.19).

94

Table 4.3c: List of germplasm categorized into very short, short, medium and

long grain length


Short grain rice germplasm Very short Lokti Machhi; Atma Sital; Lokti Machhi; Anjania; Jhumera; Kakeda (I);

Dubraj II; Bhulau; Rani kajar; Bhado kanker; Jhumarwa; Bishnu; Basa

Bhog; Krishna Bhog; Hira Nakhi; Lokti Maudi; Gganja Kali; Dhangari

Khusha;

Short ADT:27; Kanak Jira; Sundar mani; Kariya bodela bija; Banas KupiII;

Bhaniya


Medium Gilas; Khatia pati; Mani; Girmit; Lanji; Safed luchai; Gajpati; Saja

chhilau; Safri; Narved

Long Farsa phool; Jay Bajrang; Khatriya pati; Banreg; Ruchi; Kanthi deshi;

Piso III; Kakdi; Gadur sela; Aadan chilpa; Unknown; Parmal Safri;

Nagbel; Mudariya

4.2.2.13 Grain width (mm):

The range for grain width in mm varied from 1.85 to 3.55 mm with an

overall mean of 2.51 mm. The highest grain width (mm) was recorded in Saja

Chhilau (3.55 mm) followed by Unknown (CGR no. 5078) (3.25 mm), Nagbel and

Farsa Phool (3.15 mm). The minimum grain width was recorded in Parmal Safri

(1.85 mm). The C.V. recorded for this trait was 14.47 %.

4.2.2.14 Grain L/B ratios:

The range for grain L/B ratio varied from 12.37 to 29.44 with an average

performance of 18.80. The maximum grain L/B ratio was recorded in Lokti

Machhi CGR no. 10029 (29.45) followed by Atma Sital (27.28) and Lokti Machhi

CGR no. 10031 (26.46). The minimum grain L/B ratio was recorded in Jay

Bajrang (12.37). The C.V. was recorded 23.81% for this trait.

4.2.2.15 Decorticated grain length (mm):

The decorticated grain length ranged from 3.70 mm to 8.35 mm with an

overall mean of 5.8 mm. The maximum decorticated grain length was recorded in

Jay Bajrang (8.35 mm) followed by Nagbel (8.30 mm) and Khatriya Pati (8.05

95

mm). The minimum kernel length was recorded in Jhumarva (3.70 mm). The C.V.

observed for this trait was 24.77 % (Fig: 4.20).

4.2.2.16 Decorticated grain width (mm):

The decorticated grain width ranges from 1.65 to 3.05 mm with an overall

mean of 2.34 mm. The maximum decorticated grain width was recdorded in Saja

Chhilau (3.05 mm) followed by Anjania (2.95) and Jhumera (2.85 mm). The

minimum decorticated grain width recorded was in Parmal Safri (1.65 mm). The

C.V. was recorded 15.73 % for this trait.

4.2.2.17 L/B ratio of decorticated grain:

The L/B ratio of decorticated grain ranges from 0.24 to 0.70 with an

average of 0.47. The highest L/B ratio was recorded in Dubraj II (0.70) followed

by Hira Nakhi (0.68) and Bhulau (0.67) and the minimum L/B ratio of decorticated

grain was recorded in Parmal Safri (0.24). The C.V. recorded for this trait was

25.24 %.

4.2.2.18 Biological yield (g):

The mean performance of biological yield was 844.69. It showed variation

from 414.00 to 1439.50 gm. The maximum biological yield was recorded in Safri

(1439.50 gm) followed by Bishnu (1281.50 gm) and Ganja Kali and the minimum

were recorded in Basa bhog (414.00 gm). The C.V. recorded for this trait was

24.97%.

4.2.2.19 Grain yield (g):

The range for grain yield (g) varied from 61.00 g to 498.50 g with a mean

value of 181.09 g. The highest grain yield (g) was recorded in Anjania (498.50 g)

followed by Safri (285.50 g) and Nagbel (259.00 g). The minimum grain yield (g)

was recorded in Lokti Machhi CGR no. 10029 (61.00 g). The C.V. was 31.89%

recorded for this trait.

4.2.2.20 Harvest index (%):

Harvest index was found to vary from 12.50% to 65.51% with an overall

mean of 22.30%. The maximum harvest index was recorded in Anjania (65.51%

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followed by Nagbel (60.23%) and Mudariya (26.98%). The minimum harvest

index was recorded in Kakeda (I) (12.50%). The C.V. recorded for this trait was

22.82 %.

4.2.2.21 Hulling percent (%):

Hulling percentage ranged from 56.44% to 78.95% with an overall mean

performance of 72.14%. The maximum hulling percent was recorded in Lokti

Machhi CGR no. 10031 (78.95%), followed by Bhaniya (78.83%) and Piso III

(78.43%) and the minimum hulling per cent was recorded in Gilas (56.44%). The

C.V. recorded 8.13% for this trait.

4.2.2.22 Milling percent (%):

Milling percentage ranged from 44.88% to 78.91% with an overall mean

performance of 61.99%. The maximum milling percent was recorded in Kanthi

Deshi (78.91%) followed by Lokti Machhi (71.38%) and Kakeda I (69.81%). The

minimum milling percent was recorded in Lanji (44.88%). The C.V. observed for

this trait was 10.24%.

4.2.2.23 Head Rice Recovery (%):

The head rice recovery was found in the ranged from 27.41% to 62.14%

with an overall average of 49.44%. The highest head rice recovery was recorded in

Piso III (62.14%) followed by Mudariya (60.20%) and Safed Luchai (59.88%).

The minimum head rice recovery was recorded in Bhado Kanker (27.41%). The

C.V. recorded for this trait was 16.04%.

4.2.2.24 Length of milled grain (mm):

The length of milled grain ranged from 3.25 to 7.25 mm with an overall

mean of 5.23 mm. The maximum milled grain length was recorded in Safed Luchai

(7.25 mm) followed by Jay Bajrang (7.20 mm) and Khatriya Pati, Nagbel,

Mudariya (7.10 mm) and minimum milled grain length was recorded in Jhumarwa

(3.25 mm). The C.V. recorded from this trait was 23.66%.

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4.2.2.25 Width of milled grain (mm):

The width of milled grain ranges from 1.55 mm to 3.00 mm with an overall

mean of 2.3 mm. The maximum milled grain width was recorded in Saja Chhilau

and Parmal Safri (3.00 mm) followed by Nagbel (2.95 mm) and Anjania (2.75

mm) and the lowest width of milled grain was recorded in Lokti Machhi CGR no.

10029 (1.55 mm). The C.V. was 14.01% recorded for this trait.

4.2.2.26 L/B ratio of milled grain:

The L/B ratio of milled grain ranges from 1.35 to 4.07 with an average

performance of 2.36. The maximum L/B ratio of milled grain was recorded in

Mani (4.07) followed by Safed luchai (4.04) and Khatriya pati (3.39). The

minimum L/B ratio of milled grain was recorded in Jhumarwa (1.35). The C.V.

observed for this trait was 27.44%.

4.2.2.27 Length of cooked kernel (mm):

The kernel length after cooking in genotypes ranged from 5.50 mm to

13.15 mm with an overall average 8.30 mm. The maximum length of cooked

kernel was recorded in Piso III (13.15 mm) followed by Mudariya (11.45 mm) and

Banreg (11.30 mm). The minimum length of cooked kernel was recorded in ADT:

27 (5.50 mm). The C.V. was 22.95% for this trait (Fig: 4.23).

4.2.2.28 Width of cooked kernel (mm):

The kernel width after cooking ranged from 2.50mm to 4.25 mm with an

average of 3.21 mm. The maximum width of cooked kernel was recorded in Kanthi

Deshi (4.25 mm) followed by Godur Sela (3.85 mm), Piso III (3.85 mm) and the

minimum width of cooked kernel was recorded in Banas Kupi II (2.50 mm). The

C.V. observed for this trait was 11.66%.

4.2.2.29 L/B ratio of cooked kernel:

The L/B ratio of cooked kernel ranged from 1.75 to 3.65 with an average of

2.59. The maximum L/B ratio of cooked kernel was recorded in Ruchi (3.65)

followed by Banreg (3.54) and Parmal Safri (3.45). The minimum L/B ratio of

cooked kernel was recorded in Dhangari Khusha (1.75). The C.V. observed was

20.98% for this trait.

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4.2.2.30 Elongation ratio:

The variation in elongation ratio ranged from 1.13 to 2.30 with the overall

mean of 1.63. The highest elongation ratio was recorded in Kariya Bodela Bija

(2.30) followed by Dubraj II (2.26) and Piso III (2.04). The minimum elongation

ratio was recorded in Jay Bajrang (1.13). The C.V. observed for trait was 15.25%.

4.2.2.31 Elongation index:

The elongation index ranges from 0.69 to 1.86 with an overall mean of

1.164. The highest elongation index was recorded in Bhaniya (1.86) followed by

Ganja Kali (1.62) and Dubraj II (1.60) and the minimum elongation index were

recorded in Safed Luchai (0.69). The C.V. was 23.77% for this trait.

4.2.2.32 Amylose content (%):

The amylose content in genotypes ranged from 15.42% to 29.33% with an

overall mean of 22.46%. The highest amylase content was recorded in Sunder

Mani (29.33%) followed by Basa Bhog (28.82%) and Jhumarwa (28.39%) and the

minimum were recorded in Lokti Machhi CGR no. 10031 (14.92%). The C.V.

observed for this trait was 18.47% (Fig: 4.25).

Table 4.3d: List of germplasm categorized into very short, short, medium and

long grain length



Low Lokti Machhi; ADT:27; Jhumera; Krishna Bhog; Hira Nakhi; Lokti Maudi;

Kariya bodela bija; Gganja Kali; Bhaniya

Medium Atma Sital; Lokti Machhi; Anjania; Kanak Jira; Dubraj II; Bhulau; Bhado

kanker; Bishnu; Banas KupiII; Dhangari Khusha

High Kakeda (I); Rani kajar; Sundar mani; Jhumarwa; Basa Bhog


Low Mani; Khatriya pati; Banreg; Ruchi

Medium Jay Bajrang; Gilas; Khatia pati; Girmit; Lanji; Safed luchai; Kanthi deshi;

Piso III; Kakdi; Gajpati; Aadan chilpa; Saja chhilau; Parmal Safri;

Mudariya

High Farsa phool; Gadur sela; Unknown; Safri; Narved; Nagbel

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4.2.2.33 Gel consistency (%)

The gel consistency in genotypes ranges from 32.50% to 100% with an

overall mean of 90.46%. The highest gel consistency was observed in many

genotypes like Atma Sital (100%), ADT : 27 (100%), Anjania (100%), Jhumera

(100%), Kakeda I (100%), Dubraj II and the minimum was recorded in Bhania

(32.50%). The C.V. recorded for this trait was 16.11% (Fig: 4.28).

Table 4.3e: List of germplasm categorized into soft, medium and hard gel

consistency

Category Name of accessions


Soft Lokti Machhi; Atma Sital; ADT:27; Anjania; Kanak Jira; Jhumera;

Kakeda (I); Dubraj II; Bhulau; Sundar mani; Bhado kanker;

Jhumarwa; Bishnu; Basa Bhog; Krishna Bhog; Hira Nakhi; Lokti

Maudi; Kariya bodela bija; Gganja Kali; Banas KupiII; Dhangari

Khusha

Medium Lokti Machhi; Rani kajar

Hard Bhaniya


Soft Farsa phool; Jay Bajrang; Gilas; Khatia pati; Mani; Khatriya pati;

Girmit; Lanji; Banreg; Ruchi; Safed luchai; Kanthi deshi; Piso III;

Kakdi; Gajpati; Gadur sela; Aadan chilpa; Unknown; Saja chhilau;

Parmal Safri; Safri; Narved; Nagbel; Mudariya

The genetic variability in any breeding material is a prerequisite as it does

not only provide a basis for selection but also provide some valuable information

regarding selection of diverse parents for use in hybridization programme.

Coefficient of variation was evolved by Karl Pearson. It is very useful for

the study of variation. It indicates that when the C.V. is high the sample is less

consistent or more variable.

Coefficient of variation truly provides a relative measure of variability

among different traits. In the present investigation wide range of variability was

observed for most of the quantitative traits. High magnitude of coefficient of

variation (more than 20%) in the entire accessions was observed for grain yield

(31.89), L/B ratio of milled grain (27.44), grain length (25.84), L/B ratio of

decorticated grain (25.24), biological yield (24.97), decorticated grain length

100

(24.77), grain L/B ratio (23.81), elongation index (23.77), length of milled grain

(23.66), length of cooked kernel (22.95) and harvest index (22.82). High

magnitude of coefficient of variation for grain yield was observed by Nachimuthu

et al. (2014) and Sarawgi et al. (2014).

Moderate magnitude of coefficient of variation (10-20%) was observed for

1000 grain weight (18.60), endosperm content of amylose (18.47), length of

longest awn (16.38), gel consistency (16.11), head rice recovery (16.04),

decorticated grain width (15.73), stem length (15.62), plant height (15.25),

elongation ratio (15.25), grain width (14.47), no. of panicle per plant (13.50).

Similar findings were also reported by the earlier workers (Chakravorty et al.,

2013; Nachimuthu et al., 2014 and Sarawgi et al., 2014 and Lingaiah et al. 2015).

4.2.3 Phenotypic and Genotypic coefficient of variation

Coefficient of variation was calculated at genotypic and phenotypic levels

as analysis of variance permits estimation of phenotypic, genotypic and

environmental coefficient of variation (Burton, 1952). As usual, phenotypic

coefficient of variation was higher in magnitude than genotypic coefficient of

variation. The PCV and GCV are classified as follows as suggested by Siva

Subramanian and Madhavamenon (1973) (low <10%; moderate 10-20% and

high>20%). The estimates of phenotypic and genotypic coefficient of variation for

different quantitative characters and quality characters are present in Table 4.4.

The highest value of PCV coupled with GCV was recorded in harvest index

(98.63-32.34) followed by grain yield (47.91-20.65), length of longest awn (46.79-

45.98), 1000 grain weight (38.59-38.58), L/B ratio of milled grain (32.75-32.08),

grain length (30.88-30.82), L/B ratio of decorticated grain (30.56-29.94), L/B ratio

(28.97-28.63), decorticated grain: length (29.81-29.73), length of milled grain

(28.68-28.60), length of cooked kernel (22.96-22.92), L/B ratio of cooked kernel

(21.09-20.73) and elongation index (24.28-23.09).

The values of PCV are higher than GCV, indicating the apparent variation

is not only due to genotypes but also due to the influence of environment. The high

magnitude of genotypic coefficient of variation reveals the high genetic variability

present in the material studied. In the present investigation phenotypic coefficient

101

of variation was recorded higher than genotypic coefficient of variation and was in

accordance with the Sarkar et al. (2007) and Lingaiah et al. (2015). The high

magnitude of genotypic coefficient of variation for grain yield was also obtained

by Tuhina-Khatun et al. (2015). High PCV and GCV for cooked kernel L/B ratio

and 1000-grain weight were also obtained by Sarkar et al. (2007). The rest of the

traits recorded moderate to low PCV in association with GCV.

Table 4.4: Genetic parameters of 33 yield and quality traits of 48 (24 short

and 24 long grain length) rice germplasm accessions

Characters Grand

Mean

Range PCV

(%)

GCV

(%)

Heritability

(h2bs) (%)

GA

(%)

1. Leaf: Length of blade(cm) 36.17 27.0-48.7 14.85 14.54 95.82 29.31

2. Leaf: Width of blade(cm) 0.71 0.50-0.90 15.54 11.55 55.27 17.69

3. Time of heading(50% plants with

panicle)

125.11 88.0- 126.0 7.26 7.15 97.07 14.52

4. Stem: Thickness 0.47 0.3-0.65 17.88 13.50 56.99 21.00

5. Stem: Length(excluding panicle) 141.91 82.2-179.6 15.75 15.49 96.84 31.41

6. Panicle: Length of main axis 22.71 14.05-28.0 15.69 14.79 88.91 28.74

7. Plant height(cm) 164.62 103.0-207.6 15.17 14.94 96.91 30.29

8. Panicle: Number per plant (number

of tillers)

7.44 5.845-9.830 14.29 12.67 78.58 23.13

9 .Panicle: Length of longest

awn(cm)

0.57 0.000-3.40 46.79 45.98 98.50 29.05

10. Time Maturity(Days) 149.21 116.0-155.5 5.94 5.84 96.66 11.84

11. Grain: Weight of 1000 fully

develop grain(g)

22.03 10.35-38065 38.59 38.58 99.93 79.45

12. Garin: Length(mm) 8.21 5.15-11.80 30.88 30.82 99.57 63.36

13. Grain: Width(mm) 2.51 1.85-3.55 14.91 14.01 88.35 27.14

14. L/B ratio 18.80 12.37-29.44 28.97 28.63 97.71 58.30

15. Decorticated grain: Length(mm) 5.8 3.70-8.35 29.81 29.73 99.46 61.07

16. Decorticated grain: Width(mm) 2.34 1.65-3.05 16.16 15.25 89.10 29.66

17. L/B Ratio of decorticated grain 0.47 0.24-0.70 30.56 29.94 96.00 60.43

18. Biological Yield(g) 844.688 414-1439.50 30.05 18.55 38.13 23.60

19. Grain Yield(g) 181.09 61.0-498.5 47.91 20.65 42.61 18.33

20. Harvest Index 26.80 12.50-65.51 98.63 32.34 32.79 12.63

21. Hulling Percent 72.14 56.44-78.83 8.14 8.10 99.14 16.63

22. Milling Percent 61.99 44.87-78.90 10.89 9.55 76.99 17.27

23. Head Rice Recovery 49.44 27.41-62.14 16.04 16.04 99.98 33.04

24. Length of milled grain(mm) 5.23 3.25-7.25 28.68 28.6 99.46 58.76

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25. Width of milled grain(mm) 2.26 1.55-3.00 14.54 13.40 85.07 25.47

26. L/B ratio of milled grain 2.36 1.35-4.07 32.75 32.08 95.97 64.74

27. Length of cooked kernel(mm) 8.30 5.50-13.15 22.96 22.92 99.61 47.12

28. Width of cooked kernel(mm) 3.21 2.50-4.25 11.93 11.33 90.12 22.15

29. L/B ratio of cooked kernel 2.58 1.75-3.65 21.09 20.73 96.61 41.97

30. Elongation Ratio 1.63 1.12-2.30 15.41 15.08 95.72 30.39

31. Elongation index 1.16 0.69-1.86 24.28 23.09 90.48 45.25

32. Endosperm content of Amylose 22.46 15.42-29.33 18.65 18.29 96.16 36.95

33. Gel Consistency 90.46 32.50-100.0 16.13 16.09 99.63 33.09

4.2.4 Heritability and Genetic advance as percentage of mean:

Heritability estimates provide the information regarding the amount of

transmissible genetic variation to total variation and determine genetic

improvement and response to selection. Thus, heritability is the heritable portion of

the phenotypic variance. It is a good index of the transformation of characters from

parent to their offsprings. Heritability and genetic advance are important selection

parameters. Heritability estimates alongwith genetic advance are normally more

helpful in predicting the gain under selection than heritability estimates alone.

Improvement in the mean genotypic value of selected plants over the parental

population is known as genetic advance. It is the measure of genetic gain under

selection. The success of genetic advance under selection depends on genetic

variability, heritability and selection intensity. In the present investigation

heritability in broad sense and genetic advance were calculated for 33 yield and

quality characters under study and are presented in Table-4.4.

High estimate of heritability was found for all characters except for harvest

index (32.79%), biological yield (g) (38.13%), grain yield (g) (42.61%), leaf width

of blade (cm) (55.27%) and stem thickness (57.00%). The highest heritability was

estimated for head rice recovery (99.98%) followed by 1000-grain weight

(99.93%), Gel consistency (99.63%), length of cooked kernel (99.62%) and Grain

length (99.57%). This finding is in agreement with Choudhary et al. (2004) and

Tuhina Khatun et al. (2015). Highest heritability for head rice recovery, length of

decorticated grain, gel consistency is similar with the findings of Shrivastava et al.

(2012).

103

Genetic advance is a measure of genetic gain under selection. The success

of genetic advance under selection depends on heritability of the character under

consideration. This indicates that though the character is less influenced by

environmental effects, the selection for improvement of such trait may not be

useful because, heritability is based on total genetic variance which includes

fixable (additive) and non fixable (dominance and epistatic) varience.

The magnitude of genetic advance as percent of mean was recorded high

for all the traits. Only some traits observed moderate genetic advance namely, time

of maturity (11.84%), harvest index (12.63%), time of heading (14.52%), hulling

percent (16.63%), milling percent (17.27%), and leaf: width of blade (17.69%) and

grain yield (18.33%). All the traits possessing high values of genetic advance

indicate that the characters are governed by additive genes and selection will be

rewarding for improvement of such trait.

Out of 33 yield and quality traits, twenty four characters namely, leaf:

length of blade (95.82-29.31), stem length (96.84-31.41), panicle: length of main

axis (88.91-28.74), plant height (96.91-30.29), panicle: number per plant (78.58-

23.13), length of longest awn (98.50-29.05), 1000 grain weight (99.93-79.45),

grain length (99.57-63.36), grain width (88.35-27.14), grain L/B ratio (97.71-

58.30), decorticated grain length (99.46-61.07), decorticated grain width (89.10-

29.66), L/B ratio of decorticated grain (96.00-60.43), head rice recovery (99.98-

33.04), length of milled grain (99.46-58.76), width of milled grain (85.07-25.47),

L/B ratio of milled grain (95.97-64.74), length of cooked kernel (99.61-47.12),

width of cooked kernel (90.12-22.15), L/B ratio of cooked kernel (96.61-41.97),

elongation ratio (95.72-30.39), elongation index (90.48-45.25), amylose content

(96.16-36.95), gel consistency (99.63-33.09) exhibited high heritability coupled

with high genetic advance. It clearly indicates that most likely the heritability is

due to additive gene effects and selection may be effective.

High heritability with low genetic advance as percentage of mean was

observed for Time of heading (97.07, 14.52). Time maturity (days) (96.66, 11.83)

and Hulling percent (99.13, 16.63). This indicates non-additive (dominance and

104

epistasis) gene action. These findings are in agreement with findings of Veni and

Rani (2006) and Rahman et al. (2016).

4.3 Association analysis:

4.3.1 Correlation analysis

Association analysis is an important approach in a breeding programme. It

gives an idea about relationship among the various characters and determines the

component characters, on which selection can be based for genetic improvement in

the grain yield. Degree of association also affects the effectiveness of selection

process. The degree of association between independent and dependent variables

was suggested by Galton 1888, its theory was developed by Pearson (1904) and

their mathematical utilization at phenotypic, genotypic and environmental levels

was described by Searle (1961). The association between any two variables is

termed as simple correlation or total correlation or zero order correlation

coefficient. It is of three types viz, phenotypic, genotypic and environmental

correlations.

The correlation coefficient analysis is the index of association between two

variables. These have been dealt in all possible combination for important

characters at phenotypic and genotypic level and are presented in Table-4.5a and

4.5b.

In table 4.5b, grain yield showed positive and significant correlation with

time of heading (0.40) followed by stem thickness (0.62), stem length (0.38),

panicle length (0.43), plant height (0.40), panicle per plant (0.48), length of longest

awn (0.33), time maturity (0.37), 1000-grain weight (0.56), grain length (0.54),

decorticated grain length (0.54) and biological yield (0.98). However, it showed

negative and significant association with L/B ratio (-0.54).

Time of maturity showed positive and significant correlation with Leaf:

length of blade (0.40, 0.41) followed by Time of heading (0.98, 0.99), Stem length

(0.68, 0.69), Panicle length (0.46, 0.49), Plant height (0.67, 0.69) and Length of

longest awn (0.40, 0.41) both phenotypically and genotypically. 1000-fully

developed grain weight showed positive and significant association with Leaf:

length of blade (0.53) followed by Time of heading (0.44), Stem length (0.70),

105

Panicle length (0.72), Plant height (0.73), Length of longest awn (0.58), Time of

maturity (0.47).

Grain length possessed positive and significant association with Leaf:

length of blade (0.63), followed by Time of heading (0.56), Stem length (0.77),

Panicle length (0.74), Plant height (0.79), Length of longest awn (0.65), Time of

maturity (0.59) and 1000-grain weight (0.93).

Decorticated grain length showed positive and significant association with

Leaf: length of blade (0.60), Time of heading (0.56), Stem length (0.78), Panicle

length (0.74), Plant height (0.80), Length of longest awn (0.63), Time of maturity

(0.58) and 1000-grain weight (0.93) and Grain length (0.99).

Biological yield showed positive and significant association with Time of

maturity (0.44), Stem length (0.46), Panicle length (0.57), Plant height (0.49) and

Time of maturity (0.48).

Harvest index possessed positive and significant association with Time of

heading (0.34), Stem length (0.51), Panicle length (0.42), Plant height (0.51),

Panicle per plant (0.96), 1000-grain weight (0.96), Grain length (0.61), Grain width

(0.88), Decorticated grain length (0.67), Decorticated grain width (0.70) and Grain

yield (0.62).

Hulling percent showed positive and significant association with L/B ratio

(0.44), L/B ratio of decorticated grain (0.29) and Biological yield (0.28). However

it showed negative but significant association with grain length (-0.42) and Harvest

index (-0.81).

Head rice recovery showed positive and significant association with Leaf :

length of blade (0.28) followed by Time of heading (0.34), Stem thickness (0.31),

Stem length (0.39), Panicle length (0.46), Plant height (0.42), Length of longest

awn (0.32), Time of maturity (0.37), 1000-grain weight (0.29), Grain length (0.34),

Decorticated grain length (0.37), Biological yield (0.41), Grain yield (0.34) and

Milling percent (0.37). However, it showed negative but significant association

with L/B ratio of decorticated grain (-0.45).

106

Length of milled grain possessed positive and significant association with

Leaf : length of blade (0.60) followed by Time of heading (0.60), Stem length

(0.77), Panicle length (0.73), Plant height (0.79), Length of longest awn (0.65),

Time of maturity (0.62), 1000-grain weight (0.92), Grain length (0.98),

Decorticated grain length (0.98), Grain yield (0.52), Harvest index (0.61) and Head

rice recovery (0.39).

Width of milled grain showed positive and significant association with

grain width (0.39), Decorticated grain width (0.63), Grain yield (0.40) and Harvest

index (0.97).

L/B ratio of milled grain showed positive and significant association with

Leaf : length of blade (0.59), Time of heading (0.61), Stem length (0.66), Panicle

length (0.65), Plant height (0.68), Length of longest awn (0.63), Time of maturity

(0.61), 1000-grain weight (0.74), Grain length (0.85), Decorticated grain length

(0.85), Biological yield (0.26), Grain yield (0.32), Head rice recovery (0.43) and

Length of milled grain (0.89). However, it showed negative but significant

association with Width of milled grain.

Length of cooked kernel possessed positive and significant association with

Leaf : length of blade (0.50), Time of heading (0.56), Stem thickness (0.27), Stem

length (0.71), Panicle length (0.66), Plant height (0.73), Length of longest awn

(0.64), Time of maturity (0.58), 1000-grain weight (0.76), Grain length (0.85),

decorticated grain length (0.86), Biological yield (0.32), Grain yield (0.62),

Harvest index (0.54), Head rice recovery (0.45), Length of milled grain (0.84) and

L/B ratio of milled grain (0.73). However, it showed negative but significant

association with Grain L/B ratio (-0.82).

Width of cooked kernel possessed positive and significant association with

Time of heading (0.24), Stem thickness (0.34), Stem length (0.25), Panicle length

(0.24), Plant height (0.26), Length of longest awn (0.42), Time of maturity (0.27),

1000-grain weight (0.36), Grain length (0.35), Decorticated grain length (0.35),

Grain yield (0.39), Harvest index (0.35), Head rice recovery (0.33), Length of

milled grain (0.33), L/B ratio of milled grain (0.33) and Length of cooked kernel

(0.44).

107

Table 4.5a: Association analysis (phenotypic and genotypic) of 33 yield and quality traits of 48 (24 short and 24 long grains length)


Traits 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

1 P 1 0.30 0.38 0.09 0.54 0.53 0.56 -0.05 0.56 0.40 0.52 0.61 0.04 -0.59 0.59 -0.41

G 0.35 0.39 0.10 0.55 0.57 0.57 -0.06 0.57 0.41 0.53 0.63 0.03 -0.61 0.60 -0.43

2 P 1 -0.03 -0.01 0.09 0.11 0.09 -0.01 0.18 -0.02 0.12 0.12 -0.001 -0.14 0.13 -0.08

G -0.07 -0.002 0.10 0.07 0.10 0.08 0.26 -0.04 0.16 0.17 -0.01 -0.22 0.18 -0.13

3 P 1 0.1 0.67 0.46 0.67 -0.16 0.39 0.98 0.44 0.55 -0.007 -0.35 0.55 -0.45

G 0.07 0.68 0.47 0.68 -0.18 0.40 0.99 0.44 0.56 -0.02 -0.38 0.56 -0.48

4 P 1 0.11 0.24 0.14 0.23 0.14 0.10 0.19 0.19 0.05 -0.19 0.20 -0.05

G 0.12 0.30 0.15 0.29 0.17 0.08 0.25 0.26 0.01 -0.28 0.25 -0.06

5 P 1 0.70 0.99 -0.01 0.57 0.68 0.69 0.76 0.08 -0.66 0.77 -0.39

G 0.74 0.99 -0.03 0.58 0.69 0.70 0.77 0.08 -0.68 0.78 -0.41

6 P 1 0.77 0.13 0.49 0.46 0.68 0.69 0.15 -0.65 0.70 -0.35

G 0.80 0.16 0.52 0.49 0.72 0.74 0.19 -0.71 0.74 -0.38

7 P 1 0.01 0.58 0.67 0.71 0.78 0.09 -0.68 0.79 -0.40

G -0.01 0.59 0.69 0.73 0.79 0.09 -0.71 0.80 -0.42

8 P 1 -0.09 -0.15 -0.01 0.009 -0.03 -0.04 0.03 0.009

G -0.10 -0.18 -0.01 0.006 -0.05 -0.04 0.03 0.02

9 P 1 0.40 0.57 0.65 -0.05 -0.63 0.63 -0.47

G 0.41 0.58 0.65 -0.05 -0.64 0.63 -0.50

10 P 1 0.46 0.57 -0.01 -0.37 0.57 -0.44

G 0.47 0.59 -0.02 -0.40 0.58 -0.47

11 P 1 0.93 0.26 -0.90 0.93 -0.35

G 0.93 0.28 -0.91 0.93 -0.38

12 P 1 0.16 -0.96 0.98 -0.48

G 0.18 -0.97 0.99 -0.51

13 P 1 -0.18 0.16 0.37

G -0.20 0.17 0.39

14 P 1 -0.94 0.42

G -0.95 0.45

108

15 P 1 -0.48

G -0.52

16 P 1

G

17 P

G

18 P

G

19 P

G

20 P

G

21 P

G

22 P

G

23 P

G

24 P

G

25 P

G

26 P

G

27 P

G

28 P

G

29 P

G

30 P

109

G

31 P

G

32 P

G

33 P

G 1 = Leaf: Length of blade ; 2 = Leaf: Width of blade ; 3 = Time of heading(50% plants with panicle) ; 4 = Stem: Thickness ; 5 = Stem: Length(excluding panicle) ; 6



Width ; 17 = L/B Ratio of decorticated grain ; 18 = Biological Yield(gm) ; 19 = Grain Yield(gm) ; = 20 Harvest Index ; 21 = Hulling Percent ; 22 = Milling Percent ;



Figures in italics and bold are significant at 5% and 1% probability level, respectively.

110

Table 4.5b: Association analysis (phenotypic and genotypic) of 33 yield and quality traits of 48 (24 short and 24 long grains length)


Traits 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33

1 P -0.55 0.04 0.01 -0.01 -0.22 -0.01 0.27 0.59 -0.10 0.56 0.49 0.13 0.47 -0.37 -0.33 -0.03 0.22

G -0.58 0.05 -0.02 -0.05 -0.23 -0.01 0.28 0.60 -0.10 0.59 0.50 0.14 0.49 -0.39 -0.03 -0.04 0.23

2 P -0.09 -0.20 0.03 0.11 -0.05 -0.05 0.03 0.12 0.01 0.11 0.06 0.16 -0.01 -0.16 -0.15 0.02 0.10

G -0.13 -0.2 -0.10 -0.01 -0.07 -0.06 0.052 0.17 0.01 0.15 0.08 0.21 -0.00 -0.24 -0.21 0.03 0.14

3 P -0.56 0.25 0.23 0.07 -0.15 -0.01 0.33 0.58 -0.16 0.58 0.55 0.22 0.49 -0.27 -0.38 -0.05 0.08

G -0.59 0.44 0.40 0.34 -0.15 -0.001 0.34 0.60 -0.19 0.61 0.56 0.24 0.50 -0.29 -0.42 -0.05 0.08

4 P -0.17 0.15 0.31 0.01 0.03 -0.04 0.23 0.17 0.02 0.14 0.20 0.23 0.08 -0.05 -0.15 -0.12 0.09

G -0.27 0.20 0.62 0.19 0.04 -0.04 0.31 0.22 0.08 0.17 0.27 0.34 0.12 -0.04 -0.16 -0.14 0.11

5 P -0.71 0.28 0.20 0.10 -0.22 -0.11 0.39 0.75 0.01 0.64 0.70 0.22 0.64 -0.36 -0.32 0.11 0.18

G -0.75 0.46 0.38 0.51 -0.23 -0.14 0.39 0.77 0.02 0.66 0.71 0.25 0.65 -0.38 -0.35 0.12 0.18

6 P -0.62 0.27 0.20 0.1 -0.15 0.01 0.44 0.69 -0.01 0.58 0.63 0.22 0.56 -0.39 -0.35 -0.02 0.30

G -0.66 0.57 0.43 0.42 -0.17 0.01 0.46 0.73 -0.02 0.65 0.66 0.24 0.61 -0.43 -0.4 -0.02 0.32

7 P -0.72 0.29 0.21 0.10 -0.22 -0.10 0.41 0.77 0.01 0.66 0.72 0.23 0.65 -0.38 -0.34 0.10 0.20

G -0.76 0.49 0.40 0.51 -0.23 -0.12 0.42 0.79 0.01 0.68 0.73 0.26 0.67 -0.40 -0.37 0.10 0.20

8 P -0.01 0.10 0.19 0.20 -0.04 0.05 -0.05 -0.03 -0.01 -0.02 -0.01 0.03 -0.04 0.02 -0.03 0.11 0.32

G -0.01 0.14 0.48 0.96 -0.05 0.04 -0.06 -0.03 -0.05 0.01 -0.01 0.04 -0.04 0.02 -0.07 0.16 0.37

9 P -0.64 0.11 0.14 0.02 -0.26 -0.04 0.32 0.65 -0.10 0.62 0.63 0.40 0.45 -0.30 -0.43 0.09 0.16

G -0.65 0.19 0.33 0.21 -0.26 -0.05 0.32 0.65 -0.1 0.63 0.64 0.42 0.47 -0.31 -0.45 0.09 0.16

10 P -0.57 0.28 0.23 0.05 -0.14 -0.02 0.36 0.60 -0.15 0.59 0.57 0.24 0.50 -0.26 -0.38 -0.03 0.09

G -0.61 0.48 0.37 0.22 -0.14 -0.00 0.37 0.62 -0.16 0.61 0.58 0.27 0.51 -0.29 -0.41 -0.02 0.10

11 P -0.78 0.08 0.24 0.17 -0.35 -0.23 0.29 0.92 0.16 0.73 0.76 0.35 0.64 -0.57 -0.42 0.28 0.27

G -0.79 0.13 0.56 0.96 -0.35 -0.27 0.29 0.92 0.17 0.74 0.76 0.36 0.65 -0.59 -0.44 0.28 0.27

12 P -0.88 0.13 0.21 0.12 -0.42 -0.21 0.34 0.97 0.06 0.83 0.85 0.34 0.74 -0.56 -0.47 0.18 0.26

G -0.90 0.20 0.54 0.61 -0.42 -0.24 0.34 0.98 0.07 0.85 0.85 0.35 0.75 -0.58 -0.49 0.19 0.26

13 P 0.27 -0.15 0.03 0.17 -0.22 -0.34 -0.17 0.10 0.32 -0.09 0.10 0.01 0.11 -0.01 0.12 0.17 0.31

G 0.23 -0.34 -0.03 0.88 -0.24 -0.42 -0.18 0.11 0.39 -0.11 0.11 0.04 0.11 -0.01 0.41 0.21 0.32

14 P 0.83 -0.09 -0.17 -0.1 0.43 0.24 -0.30 -0.93 -0.10 -0.77 -0.81 -0.30 -0.72 0.53 0.40 -0.19 -0.26

111

G 0.86 -0.13 -0.54 -0.55 0.44 0.28 -0.30 -0.94 -0.12 -0.79 -0.82 -0.31 -0.74 0.55 0.42 -0.19 -0.27

15 P -0.89 0.15 0.23 0.13 -0.37 -0.18 0.37 0.97 0.06 0.83 0.86 0.33 0.75 -0.55 -0.46 0.22 0.25

G -0.90 0.23 0.54 0.67 -0.37 -0.20 0.37 0.98 0.06 0.85 0.86 0.35 0.76 -0.56 -0.48 0.23 0.25

16 P 0.59 -0.14 0.01 0.14 0.2 -0.05 -0.36 -0.52 0.61 -0.74 -0.43 -0.16 -0.35 0.36 0.66 0.05 -0.11

G 0.64 -0.27 0.13 0.7 0.21 -0.09 -0.38 -0.56 0.63 -0.77 -0.45 -0.16 -0.39 0.40 0.69 0.07 -0.11

17 P 1 -0.23 -0.21 -0.05 0.28 0.053 -0.44 -0.90 0.05 -0.83 -0.78 -0.28 -0.69 0.54 0.47 -0.13 0.04

G -0.40 -0.58 -0.29 0.29 0.052 -0.45 -0.92 0.07 -0.87 -0.80 -0.29 -0.72 0.56 0.51 -0.13 -0.05

18 P 1 0.16 -0.33 0.17 0.25 0.25 0.15 -0.12 0.18 0.18 -0.03 0.26 -0.04 -0.08 0.06 0.07

G 0.92 -0.26 0.28 0.38 0.41 0.25 -0.14 0.26 0.32 -0.01 0.36 -0.02 -0.10 0.07 0.11

19 P 1 0.48 -0.05 -0.06 0.14 0.22 0.18 0.13 0.27 0.17 0.23 -0.01 -0.00 0.07 0.10

G 0.62 -0.14 0.01 0.34 0.52 0.40 0.32 0.62 0.39 0.52 -0.07 -0.03 0.23 0.26

20 P 1 -0.1 -0.14 -0.03 0.10 0.30 -0.03 0.10 0.08 0.07 -0.04 0.08 0.11 0.07

G -0.81 -0.79 -0.2 0.61 0.97 -0.04 0.54 0.35 0.44 -0.29 0.31 0.73 0.43

21 P 1 0.70 0.11 -0.42 -0.05 -0.36 -0.25 -0.08 -0.22 0.39 0.26 -0.16 -0.25

G 0.81 0.11 -0.42 -0.06 -0.37 -0.25 -0.09 -0.23 0.40 0.28 -0.17 -0.25

22 P 1 0.33 -0.21 -0.16 -0.11 -0.07 0.01 -0.07 0.25 0.08 -0.12 -0.16

G 0.37 -0.25 -0.24 -0.12 -0.08 0.02 -0.09 0.31 0.07 -0.13 -0.18

23 P 1 0.39 -0.15 0.42 0.45 0.31 0.32 -0.10 -0.32 -0.03 0.09

G 0.39 -0.16 0.43 0.45 0.33 0.32 -0.10 -0.34 -0.03 0.09

24 P 1 0.01 0.87 0.84 0.31 0.74 -0.61 -0.51 0.16 0.23

G 0.02 0.89 0.84 0.33 0.76 -0.62 -0.53 0.16 0.24

25 P 1 -0.44 0.05 -0.06 0.11 0.03 0.62 0.28 -0.01

G -0.41 0.06 -0.06 0.21 0.04 0.61 0.32 -0.03

26 P 1 0.72 0.31 0.60 -0.56 -0.74 0.011 0.20

G 0.73 0.33 0.63 -0.58 -0.75 0.01 0.20

27 P 1 0.42 0.84 -0.11 -0.24 0.12 0.17

G 0.44 0.86 -0.12 -0.25 0.13 0.17

28 P 1 -0.11 0.03 -0.49 0.04 0.15

G -0.06 0.02 -0.50 0.03 0.16

29 P 1 -0.15 0.03 0.09 0.09

G -0.16 0.00 0.10 0.09

112

30 P 1 0.61 -0.13 -0.16

G 0.64 -0.1 -0.16

31 P 1 0.041 -0.22

G 0.05 -0.24

32 P 1 0.19

G 0.20

33 P 1

G

1 = Leaf: Length of blade ; 2 = Leaf: Width of blade ; 3 = Time of heading(50% plants with panicle) ; 4 = Stem: Thickness ; 5 = Stem: Length(excluding panicle) ; 6 = Panicle: Length

of main axis ; 7 = plant height ; 8 = Panicle: Number per plant (number of tillers) ; 9 = Panicle: Length of longest awn ; 10 = Time Maturity(Days) ; 11 = Grain: Weight of 1000 fully

develop grain ; 12 = Grain: Length ; 13 = Grain: Width ; 14 = L/B ratio ; 15 = Decorticated grain: Length ; 16 = Decorticated grain: Width ; 17 = L/B Ratio of decorticated grain ; 18 =

Biological Yield(gm) ; 19 = Grain Yield(gm) ; = 20 Harvest Index ; 21 = Hulling Percent ; 22 = Milling Percent ; 23 = Head Rice Recovery ; 24 = Length of milled grain ; 25 = Width of

milled grain ; 26 = L/B ratio of milled grain ; 27 = Length of cooked kernel ; 28 = Width of cooked kernel ; 29 = L/B ratio of cooked kernel ; 30 = Elongation Ratio ; 31 = Elongation

index ; 32 = Endosperm content of Amylose ; 33 = Gel Consistency.

Figures in italics and bold are significant at 5% and 1% probability level, respectively.

113

L/B ratio of cooked kernel showed positive and significant association with

Leaf : length of blade, Time of heading (0.50), Stem length (0.65), Panicle length

(0.61), Plant height (0.67), Length of longest awn (0.47), Time of maturity (0.51),

1000-grain weight (0.65), Grain length (0.75), Decorticated grain length (0.76),

Biological yield (0.36), Grain yield (0.52), Harvest index (0.44), Head rice

recovery (0.32), Length of milled grain (0.76), L/B ratio of milled grain (0.63) and

Length of cooked kernel (0.86).

Elongation ratio showed positive and significant association with Grain L/B

ratio (0.42), decorticated grain width (0.69), L/B ratio of decorticated grain (0.51),

Harvest index (0.31), Hulling percent (0.28), Width of milled grain (0.61) and

Elongation ratio (0.64). Endosperm content of amylose showed positive and

significant association with 1000-grain weight (0.28) followed by Harvest index

(0.73) and Width of milled grain (0.32).

Gel consistency possessed positive and significant association with Panicle

length (0.32), Panicle per plant (0.37), 1000-grain weight (0.27), Grain length

(0.26), Grain width (0.32), Grain yield (0.26), Harvest index (0.43) and

Decorticated grain length (0.25). However it showed negative but significant

association with Grain L/B ratio (0.27).

Grain yield observed high positive and significant correlation with

thousand grain weight. This result is in confirmation with the findings of

Madhvilatha et al. (2005); Muthuswamy and Anadakumar (2006) and Rashid et al.

(2014). However, high positive and significant correlation between grain yield and

biological yield is in agreement with the findings of Girish et al. (2006).

A highly significant and positive correlation of number of panicle per plant

with grain yield is in confirmation with the findings advocated by Madhavilatha et

al. (2005); Muthuswamy and Ananda kumar (2006); Ambili and Radhakrishnan

(2011) and Rashid et al. (2014). Grain length showing significant and positive

correlation with grain yield is in agreement with the findings of Gananasekaran et

al. (2008) while, the same result for correlation between grain yield and grain

breath is in confirmation of the finding of Girish et al. (2006).

114

A significant positive correlation of grain length with grain breath and L/B

ratio are in agreement with the findings of Seraj et al. (2013). Head rice recovery

had significant and positive correlation with milling percent is in confirmation with

the findings of Ekka et al. (2011).

The association between two variables which can be directly observed is

termed as phenotypic correlation and it includes Genotypic and E nvironmental

effects therefore, it differs under environmental conditions.

The inherent or heritable association between two variables is known as

genotypic or genetic correlation. This may be either due to pleotropic action of

genes or due to linkage or both. The main genetic cause of such association is

pleotropy, which refers to manifold effects of a gene (Falconer, 1960). This type of

correlation is more stable and is of paramount importance to bring about genetic

improvement in one character by selecting the other character of a pair that is

genetically correlated.

In the present investigation biological yield, 1000-grain weight, flag leaf

width, grain length, stem length, panicle length, plant height, panicle per plant,

decorticated grain length and time of heading had positive and highly significant

correlation with grain yield per plant. It indicates strong correlation of these traits

with grain yield and selection of these traits will be useful in improving grain yield.

Fig 4.29a: Graph representing signicficant correlation between grain yield

and other traits

0.4

0.62

0.380.43 0.4

0.48

0.37

0.56 0.54

-0.54

0.54

0.92

0.34

0.52

0.40.32

0.62

0.39

0.52

0.26

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

Tim

e o

f h

ea

din

g(5

0%

pla

nts

wit

h p

an

icle

)

Ste

m:

Th

ick

ne

ss

Ste

m:

Len

gth

(exc

lud

ing

pa

nic

le)

Pa

nic

le:

Len

gth

of

ma

in a

xis

Pla

nt

he

igh

t

Pa

nic

le:

Nu

mb

er

pe

r p

lan

t

(nu

mb

er

of

tille

rs)

Tim

e M

atu

rity

(D

ay

s)

Gra

in:

We

igh

t o

f 1

00

0 f

ully

de

ve

lop

gra

in

Ga

rin

: Le

ng

th

L/B

ra

tio

De

cort

ica

ted

gra

in:

Len

gth

Bio

log

ica

l Y

ield

(gm

)

He

ad

Ric

e R

eco

ve

ry

Len

gth

of

mill

ed

gra

in

Wid

th o

f m

ille

d g

rain

L/B

ra

tio

of

mill

ed

gra

in

Len

gth

of

coo

ke

d k

ern

el

Wid

th o

f co

ok

ed

ke

rne

l

L/B

ra

tio

of

coo

ke

d k

ern

el

Ge

l Co

nsi

ste

ncy

Genotypic correlation between Grain yield and other traits

115

Fig 4.29b: Graph representing signicficant genotypic correlation between

Head Rice Recovery and other traits

4.3.2 Path coefficient analysis:

The genetic architecture of economic yield must be resolved with the

genetic contribution of all other characters, influencing it directly or indirectly.

Path coefficient analysis is helpful in partitioning the correlation into the measures

of direct and indirect effects. It measures the direct and indirect contribution of

independent variables on depended variable.

The concept of path analysis was originally developed by Wright in 1921,

but was firstly used for plant selection by Dewey and Lu, 1959. Path coefficient

analysis is simply a standardized partial regression coefficient, which splits the

correlation coefficient into direct and indirect effects. The path coefficient analysis

was carried out by using the correlation coefficient between different quantitative

characters to obtain direct and indirect effects of different characters on grain yield

per plant.

Correlation coefficients along with path coefficients together provide more

reliable information, which can be effectively predicted in crop improvement

programme. If the correlation between causal factor and direct effects is more or

less of equal magnitude, it explains the true and perfect relationship between the

0.28

0.34

0.39

0.460.42

0.32

0.37

0.29

0.340.37

-0.38

-0.45

0.370.39

0.430.45

0.33 0.32

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

Lea

f: L

en

gth

of

bla

de

Tim

e o

f h

ea

din

g(5

0%

pla

nts

wit

h

pa

nic

le)

Ste

m:

Len

gth

(exc

lud

ing

pa

nic

le)

Pa

nic

le:

Len

gth

of

ma

in a

xis

Pla

nt

he

igh

t

Pa

nic

le:

Len

gth

of

lon

ge

st a

wn

Tim

e M

atu

rity

(D

ay

s)

Gra

in:

We

igh

t o

f 1

00

0 f

ully

de

ve

lop

gra

in

Ga

rin

: Le

ng

th

De

cort

ica

ted

gra

in:

Len

gth

De

cort

ica

ted

gra

in:

Wid

th

L/B

Ra

tio

of

de

cort

ica

ted

gra

in

Mill

ing

Pe

rce

nt

Len

gth

of

mill

ed

gra

in

L/B

ra

tio

of

mill

ed

gra

in

Len

gth

of

coo

ke

d k

ern

el

Wid

th o

f co

ok

ed

ke

rne

l

L/B

ra

tio

of

coo

ke

d k

ern

el

Genotypic correlation between Head Rice Recovery and

other traits

116

traits and hence, direct selection through these traits will be rewarding. However, if

the correlation coefficient is positive and the direct effects are negative or

negligible the indirect causal factors are to be considered in simultaneous selection.

To measure the direct and indirect effects, Lenka and Mishra (1973) used

the following scale in rice. The same scale given below is used in the present

investigation also.

Value of direct and indirect effect Rate of scale

0.00 to 0.09 Negligible

0.10 to 0.19 Low

0.20 to 0.29 Moderate

0.30 to 0.99 High

> 1.00 Very high

Direct effect of components on grain yield:

The correlation coefficients between grain yield and other yield attributing

characters were partitioned into direct and indirect effects and are presented in

Table 4.6a and 4.6b. Path coefficient study was carried out by considering the

grain yield as the dependent variable and rest of the characters as the independent

variables.

Based on direct and indirect effect recorded for the traits under present

investigation, it was observed that the high positive direct effect on grain yield was

exhibited by L/B ratio of cooked kernel (42.61) followed by Width of cooked

kernel (34.41), Time of maturity (29.13), Length of milled grain (21.79),

Elongation index (18.91), Plant height (11.05), L/B ratio of decorticated grain

(4.21), Milling percent (3.34), Panicle : number per plant (3.32), Stem thickness

(1.77), gel consistency (1.56), Decorticated grain length (1.47), Endosperm content

of amylase (1.20) and Grain width (0.88). The moderate magnitude of direct effect

on grain yield was recorded by biological yield (gm) (0.21).

As far as indirect effects in concerned, Leaf : length of blade recorded very

high positive indirect effect via Plant height (6.36), Time of maturity (12.17), L/B

ratio of grain (16.53), Decorticated grain width (1.77), Length of milled grain

(13.21), Width of cooked kernel (4.90), L/B ratio of cooked kernel (21.12),

117

Elongation ratio (11.13), Time of heading had high positive indirect effect via

Plant height (7.53), Time of maturity (28.89), L/B ratio of grain (10.13),

Decorticated grain width (2.00), Width of milled grain (3.69), Length of milled

grain (13.12), Width of cooked kernel (8.35), L/B ratio of cooked kernel (21.57)

and Elongation ratio (8.34).

Panicle length had high positive indirect effect via Plant height (8.87),

Time of maturity (14.33), L/B ratio of grain ( 19.16), Decorticated grain length

(1.10), Decorticated grain width (1.56), Length of milled grain (15.99), Width of

cooked kernel (8.40), L/B ratio of cooked kernel (26.02) and Elongation ratio

(12.18).

Plant height had high positive indirect effect via Endosperm content of

amylase (0.32) and had very high positive indirect effect via Time of maturity

(20.11) followed by L/B ratio of grain (18.99), Decorticated grain length (1.18),

Decorticated grain width (1.75), Length of milled grain (17.26), Width of cooked

kernel (9.09), L/B ratio of cooked kernel (28.53) and Elongation ratio (11.45).

Number of panicle per plant (number of tillers) had high positive indirect

effect via Stem thickness (0.52) and Gel consistency (0.58) and had very high

positive indirect effect via Time of heading (4.35), L/B ratio of grain (1.17), Width

of milled grain (1.07) and Width of cooked kernel (1.52).

118

Table 4.6a: Direct and indirect effects of 33 yield and quality traits of 48 (24 short and 24 long grains length) rice germplasm

accessions

Traits 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

1 P -0.17 0.00 0.02 0.02 -0.40 -0.05 0.44 0.00 0.04 -0.09 -0.02 0.50 0.01 -0.44 -0.39 0.07

G -0.95 -1.84 -9.31 0.18 -1.39 -2.00 6.36 -0.21 0.12 12.17 -0.73 -37.50 0.03 16.53 0.89 1.77

2 P -0.05 0.03 0.00 0.00 -0.07 -0.01 0.08 0.00 0.01 0.00 0.00 0.10 0.00 -0.11 -0.09 0.01

G -0.34 -5.19 1.66 0.00 -0.27 -0.27 1.19 0.27 0.06 -1.40 -0.22 -10.59 -0.01 6.04 0.26 0.54

3 P -0.07 0.00 0.06 0.02 -0.50 -0.05 0.53 -0.01 0.03 -0.23 -0.01 0.45 0.00 -0.27 -0.36 0.08

G -0.37 0.36 -23.70 0.13 -1.72 -1.65 7.53 -0.61 0.09 28.89 -0.60 -33.60 -0.02 10.13 0.83 2.00

4 P -0.02 0.00 0.01 0.24 -0.09 -0.02 0.11 0.01 0.01 -0.02 -0.01 0.16 0.01 -0.14 -0.13 0.01

G -0.10 0.01 -1.72 1.77 -0.31 -1.04 1.67 0.97 0.04 2.48 -0.35 -15.34 0.01 7.55 0.38 0.27

5 P -0.09 0.00 0.04 0.03 -0.74 -0.07 0.78 0.00 0.05 -0.16 -0.02 0.61 0.02 -0.50 -0.51 0.07

G -0.53 -0.56 -16.33 0.22 -2.50 -2.57 11.01 -0.10 0.12 20.30 -0.95 -45.75 0.07 18.31 1.15 1.71

6 P -0.09 0.00 0.03 0.06 -0.52 -0.10 0.61 0.01 0.04 -0.11 -0.02 0.56 0.03 -0.49 -0.46 0.06

G -0.55 -0.41 -11.28 0.53 -1.86 -3.46 8.87 0.53 0.11 14.33 -0.98 -44.06 0.17 19.16 1.10 1.56

7 P -0.10 0.00 0.04 0.03 -0.74 -0.08 0.79 0.00 0.05 -0.16 -0.02 0.63 0.02 -0.52 -0.52 0.07

G -0.55 -0.56 -16.14 0.27 -2.49 -2.77 11.05 -0.02 0.13 20.11 -0.99 -46.92 0.09 18.99 1.18 1.75

8 P 0.01 0.00 -0.01 0.06 0.01 -0.01 0.00 0.04 -0.01 0.04 0.00 0.01 -0.01 -0.03 -0.02 0.00

G 0.06 -0.42 4.35 0.52 0.08 -0.55 -0.06 3.32 -0.02 -5.47 0.02 -0.37 -0.05 1.17 0.05 -0.11

9 P -0.10 0.01 0.02 0.04 -0.43 -0.05 0.46 0.00 0.08 -0.09 -0.02 0.52 -0.01 -0.47 -0.41 0.08

G -0.55 -1.38 -9.64 0.31 -1.47 -1.82 6.60 -0.34 0.21 12.10 -0.79 -38.65 -0.05 17.14 0.94 2.06

10 P -0.07 0.00 0.06 0.02 -0.50 -0.05 0.53 -0.01 0.03 -0.23 -0.02 0.46 0.00 -0.28 -0.38 0.08

G -0.40 0.25 -23.51 0.15 -1.74 -1.70 7.63 -0.62 0.09 29.13 -0.64 -34.84 -0.02 10.75 0.86 1.95

11 P -0.09 0.00 0.03 0.05 -0.51 -0.07 0.56 0.00 0.05 -0.11 -0.03 0.75 0.06 -0.68 -0.61 0.06

G -0.51 -0.86 -10.59 0.46 -1.76 -2.50 8.06 -0.05 0.12 13.75 -1.35 -55.17 0.25 24.45 1.37 1.57

12 P -0.11 0.00 0.03 0.05 -0.56 -0.07 0.61 0.00 0.05 -0.13 -0.03 0.81 0.03 -0.73 -0.65 0.08

G -0.60 -0.93 -13.50 0.46 -1.94 -2.58 8.79 0.02 0.14 17.19 -1.26 -59.01 0.16 25.94 1.45 2.13

13 P -0.01 0.00 0.00 0.01 -0.06 -0.02 0.08 0.00 0.00 0.00 -0.01 0.14 0.21 -0.14 -0.11 -0.06

G -0.03 0.07 0.47 0.02 -0.20 -0.67 1.08 -0.17 -0.01 -0.71 -0.38 -10.65 0.88 5.44 0.25 -1.62

14 P 0.10 0.00 -0.02 -0.05 0.49 0.07 -0.54 0.00 -0.05 0.09 0.03 -0.78 -0.04 0.75 0.62 -0.07

119

G 0.59 1.17 8.99 -0.50 1.71 2.48 -7.86 -0.15 -0.14 -11.73 1.24 57.34 -0.18 -26.70 -1.41 -1.87

15 P -0.10 0.00 0.03 0.05 -0.57 -0.07 0.62 0.00 0.02 -0.13 -0.03 0.79 0.03 -0.71 -0.65 0.08

G -0.57 -0.93 -13.45 0.46 -1.96 -2.59 8.90 0.12 0.13 17.07 -1.27 -58.48 0.15 25.59 1.47 2.14

16 P 0.07 0.00 -0.03 -0.01 0.29 0.04 -0.32 0.00 -0.04 0.10 0.01 -0.39 0.08 0.32 0.32 -0.17

G 0.41 0.68 11.51 -0.12 1.04 1.31 -4.68 0.09 -0.11 -13.80 0.51 30.52 0.35 -12.15 -0.76 -4.12

17 P 0.10 0.00 -0.03 -0.04 0.53 0.06 -0.57 0.00 -0.05 0.13 0.03 -0.71 0.06 0.63 0.58 -0.10

G 0.55 0.68 13.97 -0.48 1.87 2.31 -8.43 -0.04 -0.14 -17.76 1.08 53.21 0.21 -22.99 -1.33 -2.64

18 P -0.01 -0.01 0.02 0.04 -0.21 -0.03 0.23 0.00 0.01 -0.07 0.00 0.11 -0.03 -0.07 -0.10 0.03

G -0.05 1.04 -10.52 0.37 -1.15 -1.97 5.42 0.49 0.04 14.17 -0.18 -12.10 -0.31 3.02 0.34 1.15

20 P 0.00 0.00 0.00 0.00 -0.08 -0.01 0.08 0.01 0.00 -0.01 -0.01 0.09 0.04 -0.07 -0.09 -0.03

G 0.05 0.08 -8.21 0.34 -1.29 -1.45 5.74 3.21 0.04 6.68 -1.31 -36.26 0.78 14.74 0.98 -3.25

21 P 0.04 0.00 -0.01 0.01 0.17 0.02 -0.18 0.00 -0.02 0.03 0.01 -0.34 -0.05 0.33 0.25 -0.03

G 0.22 0.40 3.66 0.07 0.59 0.60 -2.60 -0.17 -0.06 -4.35 0.48 24.97 -0.22 -11.89 -0.55 -0.88

22 P 0.00 0.00 0.00 -0.01 0.09 0.00 -0.08 0.00 0.00 0.00 0.01 -0.17 -0.07 0.18 0.12 0.01

G 0.01 0.33 0.03 -0.07 0.36 -0.06 -1.38 0.13 -0.01 -0.19 0.37 14.67 -0.76 -7.66 -0.30 0.37

23 P -0.05 0.00 0.02 0.06 -0.29 -0.04 0.33 0.00 0.03 -0.08 -0.01 0.28 -0.04 -0.23 -0.25 0.06

G -0.27 -0.27 -8.17 0.56 -1.00 -1.62 4.65 -0.21 0.07 10.81 -0.40 -20.60 -0.16 8.20 0.55 1.58

24 P -0.10 0.00 0.04 0.04 -0.56 -0.07 0.61 0.00 0.05 -0.14 -0.03 0.79 0.02 -0.70 -0.64 0.09

G -0.58 -0.90 -14.27 0.40 -1.93 -2.54 8.76 -0.12 0.14 18.05 -1.25 -58.06 0.10 25.26 1.44 2.33

25 P 0.02 0.00 -0.01 0.01 -0.01 0.00 0.01 0.00 -0.01 0.04 -0.01 0.05 0.07 -0.08 -0.04 -0.11

G 0.10 -0.05 4.53 0.15 -0.06 0.09 0.20 -0.18 -0.02 -4.83 -0.24 -4.13 0.34 3.29 0.10 -2.61

26 P -0.10 0.00 0.04 0.03 -0.48 -0.06 0.52 0.00 0.05 -0.14 -0.02 0.67 -0.02 -0.58 -0.54 0.13

G -0.56 -0.80 -14.56 0.31 -1.67 -2.26 7.60 0.01 0.13 17.99 -1.01 -50.20 -0.10 21.32 1.25 3.20

27 P -0.09 0.00 0.03 0.05 -0.52 -0.06 0.57 0.00 0.05 -0.13 -0.03 0.69 0.02 -0.61 -0.56 0.07

G -0.48 -0.46 -13.31 0.49 -1.79 -2.31 8.11 -0.03 0.14 17.10 -1.04 -50.57 0.10 22.06 1.27 1.88

28 P -0.02 0.01 0.01 0.06 -0.17 -0.02 0.19 0.00 0.03 -0.06 -0.01 0.27 0.00 -0.23 -0.22 0.03

G -0.14 -1.09 -5.75 0.62 -0.64 -0.84 2.92 0.15 0.09 7.87 -0.50 -21.10 0.04 8.51 0.52 0.69

29 P -0.08 0.00 0.03 0.02 -0.47 -0.06 0.51 0.00 0.04 -0.12 -0.02 0.60 0.02 -0.54 -0.49 0.06

G -0.47 0.01 -12.00 0.21 -1.64 -2.11 7.40 -0.16 0.10 15.10 -0.88 -44.72 0.10 19.85 1.12 1.61

30 P 0.06 -0.01 -0.02 -0.01 0.27 0.04 -0.30 0.00 -0.02 0.06 0.02 -0.46 0.00 0.40 0.36 -0.06

G 0.37 1.26 7.01 -0.07 0.97 1.49 -4.49 0.08 -0.07 -8.45 0.80 34.29 0.00 -14.83 -0.83 -1.66

120

31 P 0.06 0.00 -0.02 -0.04 0.24 0.04 -0.27 0.00 -0.03 0.09 0.01 -0.38 0.03 0.30 0.30 -0.11

G 0.34 1.10 10.03 -0.28 0.90 1.38 -4.15 -0.23 0.09535 -12.12 0.61 29.17 0.12 -11.37 -0.71 -2.87

32 P 0.01 0.00 0.00 -0.03 -0.09 0.00 0.08 0.00 0.01 0.01 -0.01 0.15 0.04 -0.15 -0.15 -0.01

G 0.04 -0.18 1.20 -0.27 -0.30 0.09 1.14 0.53 0.02 -7.20 -0.39 -11.28 0.19 5.31 0.34 -0.29

33 P -0.04 0.00 0.01 0.02 -0.13 -0.03 0.16 0.01 0.03 -0.02 -0.01 0.21 0.06 -0.20 -0.17 0.02

G -0.22 -0.77 -2.05 0.21 -0.46 -1.12 2.30 1.23 0.04 2.95 -0.38 -15.77 0.29 7.24 0.38 0.46







121

Table 4.6b: Direct and indirect effects of 33 yield and quality traits of 48 (24 short and 24 long grains length) rice germplasm

accessions

Traits 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32

1 P 0.29 0.01 -0.01 -0.04 0.00 -0.02 -0.86 -0.09 0.78 -1.64 0.25 1.69 -0.04 0.11 0.00 0.03

G -2.46 -0.30 0.01 -0.02 -0.04 -0.09 13.21 0.02 -14.27 -12.23 4.90 21.12 11.13 -6.69 -0.05 0.36

2 P 0.05 -0.05 0.05 -0.01 0.01 0.00 -0.18 0.01 0.15 -0.21 0.30 -0.03 -0.02 0.05 0.00 0.01

G -0.56 1.05 0.00 -0.01 -0.21 -0.02 3.79 -0.17 -3.72 -2.15 7.24 -0.05 6.85 -4.02 0.04 0.23

3 P 0.30 0.06 0.03 -0.03 0.00 -0.02 -0.86 -0.15 0.81 -1.84 0.41 1.74 -0.03 0.13 0.00 0.01

G -2.48 -2.34 -0.07 -0.01 0.00 -1.05 13.12 3.69 -14.83 -13.63 8.35 21.57 8.34 -8.00 -0.06 0.13

4 P 0.09 0.04 0.01 0.01 0.01 -0.01 -0.26 0.03 0.19 -0.68 0.44 0.29 -0.01 0.05 -0.01 0.01

G -1.15 -1.10 -0.04 0.00 -0.14 -0.97 4.94 -1.61 -4.20 -6.71 12.02 5.10 1.19 -3.03 -0.18 0.18

5 P 0.38 0.07 0.05 -0.04 0.02 -0.02 -1.10 0.02 0.89 -2.36 0.42 2.27 -0.04 0.11 0.01 0.02

G -3.16 -2.43 -0.10 -0.02 -0.48 -1.22 16.86 -0.48 -16.16 -17.44 8.88 27.94 10.94 -6.78 0.14 0.29

6 P 0.33 0.07 0.05 -0.03 0.00 -0.03 -1.01 -0.01 0.81 -2.10 0.42 1.99 -0.04 0.12 0.00 0.03

G -2.82 -3.00 -0.08 -0.02 0.06 -1.43 15.99 0.49 -15.79 -16.24 8.40 26.02 12.18 -7.57 -0.03 0.51

7 P 0.39 0.07 0.05 -0.04 0.02 -0.02 -1.13 0.01 0.91 -2.41 0.44 2.31 -0.04 0.12 0.01 0.02

G -3.21 -2.58 -0.10 -0.02 -0.42 -1.28 17.26 -0.36 -16.61 -17.81 9.09 28.53 11.45 -7.09 0.12 0.32

8 P 0.00 0.03 0.10 -0.01 -0.01 0.00 0.05 -0.01 -0.04 0.03 0.07 -0.14 0.00 0.01 0.01 0.04

G -0.05 -0.78 -0.19 0.00 0.13 0.20 -0.80 1.07 -0.05 0.22 1.52 -2.09 -0.66 -1.32 0.19 0.58

9 P 0.34 0.03 0.01 -0.05 0.01 -0.02 -0.95 -0.09 0.86 -2.14 0.75 1.62 -0.03 0.15 0.01 0.02

G -2.77 -1.03 -0.04 -0.02 -0.20 -0.99 14.24 2.04 -15.33 -15.65 14.77 20.01 8.82 -8.56 0.12 0.26

10 P 0.31 0.07 0.02 -0.03 0.00 -0.02 -0.88 -0.14 0.82 -1.93 0.45 1.79 -0.03 0.13 0.00 0.01

G -2.57 -2.56 -0.05 -0.01 -0.02 -1.13 13.51 3.21 -14.92 -14.25 9.29 22.10 8.18 -7.87 -0.03 0.16

11 P 0.42 0.02 0.08 -0.06 0.04 -0.02 -1.34 0.15 1.01 -2.55 0.65 2.26 -0.06 0.14 0.02 0.03

G -3.37 -0.69 -0.19 -0.03 -0.90 -0.90 20.11 -3.44 -18.05 -18.59 12.66 27.80 16.64 -8.48 0.35 0.44

12 P 0.47 0.03 0.05 -0.08 0.04 -0.02 -1.43 0.05 1.15 -2.85 0.63 2.62 -0.06 0.16 0.01 0.03

G -3.80 -1.08 -0.12 -0.04 -0.83 -1.06 21.44 -1.35 -20.55 -20.80 12.30 32.29 16.39 -9.35 0.23 0.42

13 P -0.14 -0.04 0.08 -0.04 0.06 0.01 -0.15 0.29 -0.13 -0.35 0.04 0.39 0.00 -0.04 0.01 0.03

G 0.98 1.84 -0.18 -0.02 -1.42 0.56 2.45 -7.53 2.65 -2.78 1.43 4.69 0.11 2.67 0.25 0.51

122

14 P -0.44 -0.02 -0.05 0.08 -0.04 0.02 1.36 -0.09 -1.07 2.73 -0.56 -2.55 0.05 -0.14 -0.02 -0.03

G 3.63 0.60 0.11 0.04 0.96 0.94 -20.62 2.38 19.29 20.06 -10.97 -31.68 -15.67 8.06 -0.24 -0.42

15 P 0.47 0.04 0.06 -0.07 0.03 -0.02 -1.43 0.06 1.14 -2.88 0.62 2.65 -0.06 0.16 0.02 0.03

G -3.83 -1.23 -0.13 -0.03 -0.69 -1.15 21.42 -1.32 -20.52 -21.02 12.17 32.66 15.94 -9.17 0.28 0.40

16 P -0.32 -0.04 0.07 0.04 0.01 0.02 0.77 0.54 -1.02 1.44 -0.30 -1.27 0.04 -0.22 0.00 -0.01

G 2.70 1.47 -0.16 0.02 -0.30 1.17 -12.32 -12.23 18.77 11.05 -5.80 -16.66 -11.35 13.16 0.08 -0.17

17 P -0.53 -0.06 -0.02 0.05 -0.01 0.03 1.32 0.05 -1.15 2.62 -0.52 -2.46 0.05 -0.16 -0.01 -0.01

G 4.21 2.13 0.06 0.03 0.17 1.38 -20.09 -1.40 21.09 19.43 -10.08 -31.04 -16.04 9.68 -0.16 -0.08

18 P 0.13 0.24 -0.16 0.03 -0.04 -0.02 -0.22 -1.11 0.25 -0.61 -0.07 0.80 0.00 0.03 0.01 0.01

G -1.70 -5.26 0.05 0.03 1.30 -1.27 5.45 2.88 -6.42 -7.80 -0.15 15.45 0.64 -2.00 0.09 0.17

20 P 0.03 -0.08 0.47 -0.03 0.03 0.00 -0.16 0.27 -0.05 -0.36 0.16 0.27 0.00 -0.03 0.01 0.01

G -1.26 1.41 -0.20 -0.08 -2.65 0.61 13.48 -26.48 1.11 -13.21 12.14 19.13 8.27 5.93 0.89 0.68

21 P -0.52 0.04 -0.07 0.18 -0.12 -0.01 0.62 -0.05 -0.50 0.84 -0.16 -0.81 0.04 -0.09 -0.01 -0.03

G 1.23 -1.52 0.16 0.09 2.72 -0.34 -9.30 1.25 8.96 6.13 -3.25 -9.85 -11.46 5.37 -0.22 -0.40

22 P -0.03 0.06 -0.07 0.13 -0.17 -0.02 0.31 -0.15 -0.16 0.25 0.01 -0.27 0.03 -0.03 -0.01 -0.02

G 0.22 -2.04 0.16 0.08 3.34 -1.15 -5.47 4.67 2.99 2.09 0.90 -4.19 -8.84 1.50 -0.16 -0.29

23 P 0.24 0.06 -0.02 0.02 -0.06 -0.06 -0.57 -0.14 0.58 -1.52 0.58 1.14 -0.01 0.11 0.00 0.01

G -1.91 -2.19 0.04 0.01 1.27 -1.15 8.58 3.19 -10.38 -11.06 11.48 13.92 3.05 -6.45 -0.04 0.15

24 P 0.48 0.04 0.05 -0.08 0.04 -0.02 -1.46 0.02 1.21 -2.82 0.51 2.64 -0.06 0.17 0.01 0.03

G -3.88 -1.32 -0.12 -0.04 -0.84 -1.20 21.79 -0.38 -21.59 -20.62 11.35 32.60 17.49 -10.11 0.20 0.37

25 P -0.03 -0.03 0.14 -0.01 0.03 0.01 -0.03 0.89 -0.61 -0.18 -0.11 0.39 0.00 -0.21 0.02 0.00

G 0.30 0.78 -0.27 -0.01 -0.81 0.50 0.43 -19.32 10.11 -1.56 -2.18 5.14 -1.34 11.55 0.39 0.00

26 P 0.44 0.04 -0.02 -0.07 0.02 -0.03 -1.28 -0.40 1.38 -2.40 0.59 2.12 -0.06 0.25 0.00 0.02

G -3.68 -1.40 0.01 -0.03 -0.41 -1.31 19.48 8.09 -24.15 -17.84 11.51 26.86 16.48 -14.24 0.01 0.32

27 P 0.42 0.04 0.05 -0.05 0.01 -0.03 -1.23 0.05 0.99 -3.34 0.78 2.99 -0.01 0.08 0.01 0.02

G -3.37 -1.69 -0.11 -0.02 -0.29 -1.39 18.51 -1.24 -17.75 -24.28 15.18 36.67 3.64 -4.83 0.16 0.28

28 P 0.15 -0.01 0.04 -0.02 0.00 -0.02 -0.46 -0.05 0.44 -1.41 1.85 -0.41 0.00 0.17 0.00 0.02

G -1.23 0.02 -0.07 -0.01 0.09 -1.02 7.19 1.22 -8.08 -10.71 34.41 -2.93 -0.65 -9.49 0.05 0.26

29 P 0.37 0.05 0.04 -0.04 0.01 -0.02 -1.09 0.10 0.83 -2.83 -0.21 3.53 -0.02 -0.01 0.01 0.01

G -3.07 -1.91 -0.09 -0.02 -0.33 -0.99 16.67 -2.33 -15.22 -20.90 -2.36 42.61 4.67 0.01 0.12 0.15

30 P -0.29 -0.01 -0.02 0.07 -0.04 0.01 0.90 0.03 -0.78 0.39 0.06 -0.54 0.10 -0.21 -0.01 -0.02

123







Residual value: P= 0.436, G= 0.354

G 2.40 0.12 0.06 0.04 1.05 0.33 -13.51 -0.92 14.11 3.13 0.79 -7.05 -28.20 12.16 -0.16 -0.26

31 P -0.25 -0.02 0.04 0.05 -0.02 0.02 0.75 0.55 -1.03 0.81 -0.92 0.11 0.06 -0.34 0.00 -0.03

G 2.16 0.56 -0.06 0.03 0.27 1.04 -11.65 -11.80 18.19 6.19 -17.26 0.03 -18.13 18.91 0.06 -0.37

32 P 0.07 0.02 0.06 -0.03 0.02 0.00 -0.24 0.25 0.02 -0.42 0.08 0.32 -0.01 -0.01 0.08 0.02

G -0.57 -0.38 -0.15 -0.02 -0.46 0.10 3.69 -6.20 -0.13 -3.15 1.31 4.34 3.87 0.99 1.20 0.32

33 P 0.02 0.02 0.04 -0.05 0.03 -0.01 -0.35 -0.01 0.28 -0.59 0.29 0.33 -0.02 0.08 0.02 0.11

G -0.21 -0.58 -0.09 -0.02 -0.63 -0.29 5.24 0.06 -4.96 -4.30 5.71 3.98 4.75 -4.53 0.24 1.56

124

Time of maturity had high positive indirect effect via Decorticated grain

length (0.86) and had very high positive indirect effect via Plant height (7.63), L/B

ratio of grain (10.75), Decorticated grain width (1.95), Width of milled grain

(3.21), Length of milled grain (13.51), Width of cooked kernel (9.23), L/B ratio of

cooked kernel (22.10) and Elongation ratio (8.18).

1000-grain weight had moderate positive indirect effect via Grain width

(0.25) and had high positive indirect effect via Stem thickness (0.46), Amylose

content (0.35) and Gel consistency (0.44) and it had very high positive indirect

effect via Plant height (8.06), Time of maturity (13.75), Grain L/B ratio (24.45),

Decorticated grain length (1.37), Decorticated grain width (1.57), Length of milled

grain (20.11), Width of cooked kernel (12.66), L/B ratio of cooked kernel (27.80)


Grain length had moderate positive indirect effect via Amylose content

(0.23), it had high positive indirect effect via Gel consistency (0.42), Stem

thickness (0.46), it also had very high positive indirect effect via Plant height 8.79),

Time of maturity (17.19), Grain L/B ratio (25.94), Decorticated grain length (1.45),

Decorticated grain width (2.13), Length of milled grain (21.44), Width of cooked


Grain width has moderate positive indirect effect via Content of amylose

(0.25), it had high positive indirect effect via Time of heading (0.47), L/B ratio of

decorticated grain (0.98), Head rice recovery (0.56) and Gel consistency (0.51). It

also had very high positive indirect effect via Plant height (1.08), L/B ratio of grain

(5.44), Biological yield (1.84), Length of milled grain (2.45), L/B ratio of milled

grain (2.65), L/B ratio of cooked kernel (4.69) and Elongation index (2.67).

Grain L/B ratio had high positive indirect effect via Leaf : length of blade

(0.59), Biological yield (0.60), Head rice recovery (0.94), Milling per cent (0.96),

it had very high positive indirect effect via Width of Lead blade (1.17), Time of

heading (8.99), Panicle length (2.48), 1000-grain weight (1.24), Grain length

(57.34), L/B ratio of decorticated grain (8.63), Width of milled grain (2.38), L/B

125

ratio of milled grain (19.28), Length of cooked kernel (20.06) and Elongation

index (8.06).

Decorticated grain length had moderate positive indirect effect via Amylose

content of Endosperm (0.28) and had very high positive indirect effect via Plant

height (8.90), Time of maturity (17.07), Grain L/B ratio (25.59), Decorticated grain

width (2.14), Length of milled grain (21.42), Width of cooked kernel (12.17), L/B

ratio of cooked kernel (32.66) and Elongation ratio (15.94).

Decorticated grain width had high positive indirect effect via Leaf : length

of blade ( (0.41), Leaf : Width of blade (0.68), 1000-grain weight (0.51), Grain

width (0.35) and it had very high positive indirect effect via Time of heading

(11.57), Stem length (0.04), Panicle length (1.31), Grain length (30.52), L/B ratio

of decorticated grain (2.70), Biological yield (1.47), Head rice recovery (1.17), L/B

ratio of milled grain (18.77), Length of cooked kernel (11.05) and Elongation

index (13.16).

L/B ratio of decorticated grain had moderate positive indirect effect via

Grain width (0.21), had high positive indirect effect via Leaf : length of blade

(0.55), Leaf width of blade (0.68), it also had very high positive indirect effect via

Time of heading (13.97), Stem length (1.87), Panicle length (2.31), 1000-grain

weight (1.08), Grain length (53.21), Biological yield (2.13), Head rice recovery

(1.38), L/B ratio of milled grain (21.09), Length of cooked kernel (19.43) and

Elongation index (9.68).

Biological yield had high positive indirect effect via Stem thickness (0.37),

Number of panicle per plant (0.49), Decorticated grain length (0.34), Elongation

ratio (0.64), it also had very high positive indirect effect via Width of leaf blade

(1.04), Plant height (5.42), Time of maturity (14.17), Grain L/B ratio (3.02),

Decorticated grain width (1.15), Milling percent (1.30), Length of milled grain

(5.45), Width of milled grain (2.88) and L/B ratio of cooked kernel (15.45).

Harvest index had high positive indirect effect via Stem thickness (0.34),

Decorticated grain length, Head rice recovery (0.61), Amylose content of

Endosperm (0.89) and Gel consistency (0.68).

126

Head rice recovery had high positive indirect effect via Stem thickness

(0.56), also had very high positive indirect effect via Plant height (4.65), Time of

maturity (10.81), Grain L/B ratio (8.20), Decorticated grain width (1.58), Milling

percent (1.27), Length of milled grain (8.58), Width of milled grain (3.19), Width

of cooked kernel (11.48), L/B ratio of cooked kernel (13.92) and Elongation ratio

(3.05).

Length of milled grain had high positive indirect effect via Stem thickness

(0.40), Gel consistency (0.37), it had very high positive indirect effect via Plant

height (8.76), Time of maturity (18.05), Grain L/B ratio (25.26), Decorticated grain

length (1.44), Decorticated grain width (2.33), Length of milled grain (21.79),

Width of cooked kernel (11.35), L/B ratio of cooked kernel (32.60) and Elongation

ratio (17.49).

Width of milled grain had high positive indirect effect via Grain width

(0.34), L/B ratio of Decorticated grain (0.30), Biological yield (0.78), Head rice

recovery (0.50) and Length of milled grain (0.43), it also had very high positive

indirect effect via Time of heading (4.53), L/B ratio of milled grain (10.11), L/B


L/B ratio of milled grain had high positive indirect effect via Stem

thickness (0.31), Gel consistency (0.32), it had very high positive indirect effect

via Plant height (7.60), Time of maturity (17.99), Grain L/B ratio (2.32),

Decorticated grain length (1.25), Decorticated grain width (3.20), Length of milled

grain (19.48), Width of milled grain (8.09), Width of cooked kernel (11.51), L/B


Length of cooked kernel had moderate positive indirect effect via Gel

consistency (0.28), it had very high positive indirect effect via Plant height (8.11),

Time of maturity (17.10), Grain L/B ratio (22.06), Decorticated grain length (1.27),

Decorticated grain width (1.88), Length of milled grain (18.51), Width cooked


Width of cooked kernel had very high positive indirect effect via Plant

height (2.92), Time of maturity (7.87), Grain L/B ratio (8.51), Length of milled

grain (7.19), Width of milled grain (1.22).

127

L/B ratio of cooked kernel had very high positive indirect effect via Plant

height (7.40), Time of maturity (15.10), Decorticated grain length (1.12), Grain

L/B ratio (19.85), Decorticated grain width (1.61), Length of milled grain (16.67)


Elongation ratio had high positive indirect effect via Leaf : length of blade

(0.37), Stem length (0.97), it also had very high positive indirect effect via Leaf :

width of blade (1.26), Time of heading (7.01), Panicle length (1.49), Grain length

(34.29), L/B ratio of decorticated grain (2.40), Milling percent (1.05), L/B ratio of

milled grain (14.11), Length of cooked kernel (3.13) and Elongation index (12.16).

Elongation index had very high positive indirect effect via Leaf : width of

blade (1.10), Time of heading (10.03), Panicle length (1.38), Grain length (29.17),

L/B ratio of decorticated grain (2.16), Head rice recovery (1.04), L/B ratio milled

grain (18.19) and Length of cooked kernel (6.19).

Endosperm content of amylose had very high positive indirect effect via

Time of heading (1.20), Plant height (1.14), Grain L/B ratio (5.31), Length of

milled grain (3.69), Width cooked kernel (1.31), L/B ratio of cooked kernel (4.34)


Gel consistency had moderate positive indirect effect via Stem thickness

(0.21), Grain width (0.29), Amylose content (0.24), it had high positive indirect

effect via Decorticated grain length (0.38) and Decorticated grain width (0.46), it

also had very high positive indirect effect via Plant height (2.30), Panicle per plant

(1.23), Time of maturity (2.95), Grain L/B ratio (7.24), Length of milled grain

(5.24), Width of cooked kernel (5.71), L/B ratio of cooked kernel (3.98) and

Elongation ratio (4.75).

Low residual value (P= 0.436, G= 0.354) was observed, it indicates that the

characters taken for study is sufficient to explain the variability.

From the above result, it is clear that L/B ratio of cooked kernel, Time of

maturity, Length of milled grain, Elongation index, Plant height, L/B ratio of

decorticated grain, Milling percent, Stem thickness, Gel consistency, Grain width,

Amylose content had high positive direct effect on Grain yield. The high positive

128

direct effect of plant height on grain yield was in accordance with Ambili and

Radhakrishnan et al. (2011), Selvraj et al. (2011). Time of maturity had direct

positive effect with grain yield was in accordance with Watto et al. (2010), Selvraj

et al. (2011), Naseem et al. (2014), Sarawgi et al. (2015). Islam et al. (2015) found

length of milled grain had direct positive on grain yield which is contradictory with

the present study.

Path coefficient analysis based on HRR:

The correlation coefficients between head rice recovery and other yield

attributing characters were partitioned into direct and indirect effects and are

presented in Table 4.7. Path coefficient study was carried out by considering the

HRR as the dependent variable and rest of the characters as the independent

variable

The high positive direct effect on Head rice recovery was exhibited by Gel

consistency (0.97) followed by Leaf: width of blade (0.63) and Elongation ratio

(0.30). Very high positive direct effect exhibited by Stem length (7.61) followed by

L/B ratio of milled grain (5.96), Grain width (5.70), Length of cooked kernel

(5.54), Time of maturity (3.91), Grain L/B ratio (3.90), Width of milled grain

(3.74), Milling percent (2.33) and 1000-grain weight (1.68).

Time of heading had high positive indirect effect via 1000-grain weight

(0.75), Decorticated grain width (0.52), Elongation index (0.61).

Grain length had high positive indirect effect via Decorticated grain width

(0.55), Hulling percent (0.58) and Elongation index (0.71).

L/B ratio of grain had high positive indirect effect via Leaf: length of blade,

Panicle length (0.43), Grain length (0.54), Milling percent (0.67) and Width of

cooked kernel (0.87).

Decorticated grain length had high positive indirect effect via Grain width

(0.98), Decorticated grain width (0.56), Hulling percent (0.52) and Elongation

index (0.70).

129

L/B ratio of decorticated grain show high positive indirect effect via

Panicle length (0.40), Grain length (0.50 and Width of cooked kernel (0.80).

Biological yield had high positive indirect effect via Decorticated grain

width (0.30) and milling percent (0.90).

Grain yield had high positive indirect effect via 1000-grain weight (0.94)

and had moderate positive indirect effect via Gel consistency (0.25) and Hulling

percent (0.20).

Length of milled grain had high positive indirect effect via Grain width


index (0.77).

L/B ratio of milled grain had high positive indirect effect via Decorticated

grain width and Hulling per cent (0.51).

Length of cooked kernel had high positive indirect effect via Grain width


index (0.37).

L/B ratio of cooked kernel had high positive indirect effect via Grain width

(0.63), Decorticated grain width (0.42), Hulling percent (0.32) and Width of milled

grain (0.45).

Elongation ratio had high positive indirect effect via Grain length (0.32),

Milling percent (0.73) and L/B ratio of cooked kernel (0.63).

Elongation index had high positive indirect effect via Grain width (0.80)

and had moderate positive indirect effect via Panicle length (0.24) and Grain length

(0.27).

Amylose content of Endosperm had high positive indirect effect via Stem

length (0.91), 1000-grain weight (0.48) and Length of cooked kernel (0.72).

Gel consistency had high positive indirect effect via Time of maturity

(0.40), 1000-grain weight (0.47), L/B ratio of decorticated grain (0.59), Hulling

percent (0.35), Length of cooked kernel (0.98) and Elongation index (0.34).

130

Table 4.7a: Direct and indirect effects of 33 yield and quality traits of 48 (24 short and 24 long grains length) rice germplasm


Charact

ers

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

1 P -0.04 -0.03 -0.07 0.02 0.41 0.08 -0.19 0.01 -0.12 0.74 -0.11 -1.85 0.02 0.63 0.05 0.12

G -0.44 0.22 -2.13 0.00 4.22 -0.34 -4.04 0.00 -0.21 1.63 0.90 -0.35 0.20 -2.42 -5.02 0.46

2 P -0.01 -0.09 0.05 0.00 0.08 0.02 -0.03 0.00 -0.04 -0.04 -0.02 -0.37 0.00 0.15 0.01 0.02

G -0.15 0.63 0.38 0.00 0.83 -0.05 -0.76 0.01 -0.10 -0.19 0.28 -0.10 -0.07 -0.88 -1.49 0.14

3 P -0.01 0.00 -1.77 0.02 0.51 0.07 -0.22 0.04 -0.08 1.79 -0.09 -1.67 0.00 0.37 0.05 0.13

G -0.17 -0.04 -5.42 0.00 5.24 -0.28 -4.79 -0.01 -0.15 3.88 0.75 -0.31 -0.11 -1.48 -4.72 0.52

4 P -0.03 0.00 -0.18 0.18 0.09 0.04 -0.05 -0.06 -0.03 0.19 -0.04 -0.59 0.03 0.20 0.02 0.01

G -0.04 0.00 -0.39 0.00 0.94 -0.18 -1.06 0.02 -0.06 0.33 0.43 -0.14 0.06 -1.10 -2.14 0.07

5 P -0.02 -0.01 -1.20 0.02 0.75 0.10 -0.33 0.00 -0.12 1.23 -0.14 -2.28 0.04 0.70 0.06 0.14

G -0.24 0.07 -3.74 0.00 7.61 -0.44 -7.00 0.00 -0.22 2.72 1.18 -0.43 0.46 -2.68 -6.53 0.44

6 P -0.02 -0.01 -0.81 0.04 0.53 0.15 -0.26 -0.03 -0.10 0.84 -0.14 -2.09 0.08 0.70 0.06 0.10

G -0.25 0.05 -2.58 0.00 5.66 -0.60 -5.64 0.01 -0.19 1.92 1.21 -0.41 1.10 -2.80 -6.22 0.41

7 P -0.02 -0.01 -1.19 0.03 0.75 0.11 -0.33 0.00 -0.12 1.22 -0.15 -2.34 0.05 0.73 0.07 0.12

G -0.25 0.07 -3.69 0.00 7.58 -0.48 -7.03 0.00 -0.22 2.70 1.22 -0.44 0.56 -2.78 -6.69 0.45

8 P 0.00 0.00 0.29 0.04 -0.01 0.02 0.00 -0.24 0.02 -0.29 0.00 -0.03 -0.02 0.05 0.00 0.00

G 0.03 0.05 1.00 0.00 -0.23 -0.10 0.04 0.07 0.04 -0.73 -0.03 0.00 -0.29 -0.17 -0.29 -0.03

9 P -0.02 -0.02 -0.70 0.03 0.43 0.07 -0.19 0.02 -0.21 0.73 -0.12 -1.95 -0.03 0.67 0.05 0.14

G -0.25 0.17 -2.21 0.00 4.47 -0.31 -4.20 -0.01 -0.37 1.62 0.97 -0.36 -0.33 -2.51 -5.30 0.54

10 P -0.01 0.00 -1.75 0.02 0.51 0.07 -0.22 0.04 -0.08 1.81 -0.10 -1.72 -0.01 0.40 0.05 0.13

G -0.18 -0.03 -5.38 0.00 5.30 -0.29 -4.85 -0.01 -0.15 3.91 0.79 -0.33 -0.14 -1.57 -4.87 0.51

11 P -0.02 -0.01 -0.78 0.04 0.52 0.10 -0.24 0.00 -0.12 0.84 -0.21 -2.80 0.13 0.96 0.08 0.10

G -0.23 0.10 -2.42 0.00 5.37 -0.43 -5.13 0.00 -0.21 1.84 1.68 -0.52 1.61 -3.58 -7.79 0.41

12 P -0.02 -0.01 -0.98 0.04 0.57 0.10 -0.26 0.00 -0.14 1.04 -0.19 -3.00 0.08 1.03 0.08 0.14

G -0.28 0.11 -3.09 0.00 5.90 -0.45 -5.59 0.00 -0.24 2.31 1.57 -0.55 1.03 -3.79 -8.24 0.55

13 P 0.00 0.00 0.01 0.01 0.06 0.02 -0.03 0.01 0.01 -0.02 -0.05 -0.50 0.48 0.20 0.01 -0.11

G -0.02 -0.01 0.11 0.00 0.61 -0.12 -0.69 0.00 0.02 -0.10 0.47 -0.10 5.70 -0.80 -1.42 -0.42

131

14 P 0.02 0.01 0.62 -0.03 -0.50 -0.10 0.23 0.01 0.13 -0.68 0.19 2.90 -0.09 -1.06 -0.08 -0.12

G 0.27 -0.14 2.06 0.00 -5.22 0.43 5.00 0.00 0.24 -1.57 -1.54 0.54 -1.16 3.90 7.97 -0.49

15 P -0.02 -0.01 -0.98 0.04 0.58 0.10 -0.26 -0.01 -0.13 1.04 -0.19 -2.96 0.08 1.00 0.08 0.14

G -0.26 0.11 -3.08 0.00 5.98 -0.45 -5.66 0.00 -0.24 2.29 1.57 -0.55 0.98 -3.74 -8.31 0.56

16 P 0.01 0.01 0.80 -0.01 -0.29 -0.05 0.13 0.00 0.10 -0.81 0.07 1.46 0.18 -0.45 -0.04 -0.29

G 0.19 -0.08 2.63 0.00 -3.16 0.23 2.98 0.00 0.19 -1.85 -0.64 0.29 2.24 1.78 4.33 -1.07

17 P 0.02 0.01 0.99 -0.03 -0.54 -0.09 0.24 0.00 0.13 -1.05 0.16 2.64 0.13 -0.88 -0.07 -0.17

G 0.25 -0.08 3.20 0.00 -5.71 0.40 5.36 0.00 0.24 -2.38 -1.34 0.50 1.33 3.36 7.54 -0.69

18 P 0.00 0.02 -0.45 0.03 0.21 0.04 -0.10 -0.02 -0.02 0.52 -0.02 -0.41 -0.08 0.10 0.01 0.04

G -0.02 -0.13 -2.41 0.00 3.51 -0.34 -3.45 0.01 -0.07 1.90 0.22 -0.11 -1.99 -0.44 -1.94 0.30

19 P 0.00 0.00 -0.42 0.06 0.15 0.03 -0.07 -0.05 -0.03 0.43 -0.05 -0.65 0.02 0.19 0.02 -0.01

G 0.01 -0.07 -2.19 0.00 2.96 -0.26 -2.87 0.04 -0.12 1.47 0.94 -0.30 -0.19 -2.13 -4.53 -0.14

20 P 0.00 -0.01 -0.12 0.00 0.08 0.01 -0.04 -0.05 -0.01 0.09 -0.04 -0.34 0.08 0.11 0.01 -0.04

G 0.02 -0.01 -1.88 0.00 3.93 -0.25 -3.65 0.07 -0.08 0.90 1.62 -0.34 5.07 -2.16 -5.57 -0.84

21 P 0.01 0.01 0.27 0.01 -0.17 -0.02 0.08 0.01 0.05 -0.26 0.07 1.26 -0.11 -0.47 -0.03 -0.06

G 0.10 -0.05 0.84 0.00 -1.80 0.10 1.66 0.00 0.10 -0.58 -0.59 0.23 -1.40 1.74 3.14 -0.23

22 P 0.00 0.00 0.03 -0.01 -0.09 0.00 0.03 -0.01 0.01 -0.04 0.05 0.64 -0.16 -0.26 -0.02 0.02

G 0.01 -0.04 0.01 0.00 -1.08 -0.01 0.88 0.00 0.02 -0.03 -0.45 0.14 -2.43 1.12 1.71 0.10

24 P -0.02 -0.01 -1.04 0.03 0.57 0.10 -0.26 0.01 -0.14 1.09 -0.19 -2.93 0.05 0.99 0.08 0.15

G -0.26 0.11 -3.27 0.00 5.89 -0.44 -5.57 0.00 -0.24 2.42 1.55 -0.54 0.64 -3.69 -8.17 0.60

25 P 0.00 0.00 0.30 0.01 0.01 0.00 0.00 0.00 0.02 -0.28 -0.03 -0.18 0.16 0.11 0.01 -0.18

G 0.05 0.01 1.04 0.00 0.19 0.02 -0.13 0.00 0.04 -0.65 0.30 -0.04 2.22 -0.48 -0.57 -0.68

26 P -0.02 -0.01 -1.04 0.03 0.48 0.09 -0.22 0.01 -0.13 1.07 -0.15 -2.50 -0.05 0.83 0.07 0.22

G -0.26 0.10 -3.33 0.00 5.09 -0.39 -4.83 0.00 -0.23 2.41 1.25 -0.47 -0.63 -3.12 -7.06 0.83

27 P -0.02 -0.01 -0.97 0.04 0.53 0.09 -0.24 0.00 -0.13 1.04 -0.16 -2.56 0.05 0.87 0.07 0.13

G -0.22 0.06 -3.05 0.00 5.47 -0.40 -5.16 0.00 -0.24 2.29 1.28 -0.47 0.65 -3.23 -7.20 0.49

28 P 0.00 -0.01 -0.39 0.04 0.17 0.03 -0.08 -0.01 -0.08 0.44 -0.07 -1.02 0.01 0.32 0.03 0.05

G -0.06 0.13 -1.32 0.00 1.96 -0.15 -1.86 0.00 -0.16 1.06 0.62 -0.20 0.24 -1.24 -2.94 0.18

29 P -0.02 0.00 -0.87 0.02 0.48 0.08 -0.22 0.01 -0.10 0.91 -0.13 -2.23 0.05 0.77 0.06 0.10

G -0.22 0.00 -2.75 0.00 4.99 -0.36 -4.71 0.00 -0.17 2.03 1.09 -0.42 0.63 -2.90 -6.37 0.42

30 P 0.01 0.02 0.49 -0.01 -0.28 -0.06 0.13 -0.01 0.06 -0.49 0.12 1.70 0.00 -0.57 -0.05 -0.11

132

G 0.17 -0.15 1.60 0.00 -2.95 0.26 2.85 0.00 0.12 -1.13 -0.99 0.32 -0.02 2.17 4.70 -0.43

31 P 0.01 0.01 0.69 -0.03 -0.25 -0.05 0.11 0.01 0.09 -0.69 0.09 1.41 0.06 -0.43 -0.04 -0.19

G 0.15 -0.13 2.30 0.00 -2.73 0.24 2.64 -0.01 0.17 -1.63 -0.75 0.27 0.80 1.66 4.03 -0.74

32 P 0.00 0.00 0.10 -0.02 0.09 0.00 -0.03 -0.03 -0.02 -0.06 -0.06 -0.57 0.08 0.21 0.02 -0.02

G 0.02 0.02 0.28 0.00 0.91 0.02 -0.73 0.01 -0.04 -0.09 0.48 -0.11 1.21 -0.78 -1.94 -0.07

33 P -0.01 -0.01 -0.15 0.02 0.14 0.04 -0.07 -0.08 -0.03 0.18 -0.06 -0.80 0.15 0.28 0.02 0.03

G -0.10 0.09 -0.47 0.00 1.40 -0.19 -1.46 0.03 -0.06 0.40 0.47 -0.15 1.87 -1.06 -2.15 0.12







133

Table 4.7b: Direct and indirect effects of 33 yield and quality traits of 48 (24 short and 24 long grains length) rice germplasm


Charact

ers

17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32

1 P 0.65 -0.01 0.00 0.00 0.01 -0.01 -1.28 -0.12 0.52 -0.35 0.12 1.08 0.12 0.44 0.00 0.05

G 6.86 0.01 0.00 0.00 0.32 -0.03 -3.87 -0.39 3.52 2.79 -0.39 -1.88 -0.12 0.51 0.05 0.22

2 P 0.11 0.03 0.00 0.00 0.00 -0.02 -0.27 0.01 0.10 -0.05 0.15 -0.02 0.05 0.20 0.00 0.02

G 1.55 -0.02 0.00 0.00 0.11 -0.15 -1.11 0.03 0.92 0.49 -0.58 0.00 -0.07 0.31 -0.04 0.14

3 P 0.66 -0.04 -0.01 0.00 0.00 -0.01 -1.27 -0.20 0.54 -0.39 0.20 1.11 0.09 0.51 0.00 0.02

G 6.94 0.05 -0.01 -0.02 0.21 0.00 -3.84 -0.72 3.66 3.11 -0.67 -1.91 -0.09 0.61 0.06 0.08

4 P 0.20 -0.03 -0.01 0.00 0.00 -0.02 -0.38 0.03 0.13 -0.14 0.21 0.19 0.02 0.20 0.00 0.02

G 3.21 0.02 -0.01 -0.01 -0.06 -0.09 -1.45 0.31 1.03 1.53 -0.96 -0.45 -0.01 0.23 0.17 0.11

5 P 0.84 -0.05 -0.01 0.00 0.01 -0.05 -1.64 0.02 0.59 -0.50 0.21 1.45 0.11 0.43 0.00 0.04

G 8.83 0.05 -0.01 -0.03 0.32 -0.33 -4.94 0.09 3.99 3.98 -0.71 -2.48 -0.12 0.51 -0.14 0.18

6 P 0.73 -0.04 -0.10 0.00 0.00 0.00 -1.49 -0.01 0.54 -0.45 0.20 1.28 1.23 0.47 0.00 0.07

G 7.87 0.06 -0.01 -0.02 0.24 0.04 -4.68 -0.10 3.89 3.71 -0.67 -2.31 -0.13 0.57 0.03 0.31

7 P 0.85 -0.05 -0.01 0.00 0.01 -0.04 -1.68 0.02 0.60 -0.52 0.21 1.48 0.12 0.45 0.00 0.05

G 8.97 0.05 -0.01 -0.03 0.32 -0.29 -5.06 0.07 4.10 4.07 -0.72 -2.53 -0.12 0.54 -0.12 0.20

8 P 0.01 -0.02 -0.01 0.00 0.00 0.02 0.08 -0.01 -0.03 0.01 0.03 -0.09 -0.01 0.05 0.00 0.07

G 0.13 0.02 -0.01 -0.05 0.07 0.09 0.23 -0.21 0.01 -0.05 -0.12 0.19 0.01 0.10 -0.19 0.36

9 P 0.75 -0.02 -0.01 0.00 0.01 -0.02 -1.41 -0.12 0.57 -0.46 0.37 1.04 0.10 0.57 0.00 0.04

G 7.74 0.02 -0.01 -0.01 0.36 -0.14 -4.17 -0.40 3.78 3.57 -1.18 -1.78 -0.09 0.65 -0.12 0.16

10 P 0.68 -0.05 -0.01 0.00 0.00 -0.01 -1.30 -0.18 0.52 -0.41 0.02 1.15 0.08 0.50 0.00 0.02

G 7.18 0.05 -0.01 -0.01 0.20 -0.02 -3.96 -0.62 3.68 3.25 -0.74 -1.96 -0.09 0.60 0.03 0.10

11 P 0.91 -0.01 -0.01 0.00 0.01 -0.10 -1.99 0.19 0.67 -0.55 0.32 1.45 0.18 0.56 0.00 0.06

G 9.41 0.01 -0.01 -0.05 0.48 -0.63 -5.89 0.67 4.45 4.24 -1.01 -2.47 -0.18 0.64 -0.34 0.27

12 P 1.03 -0.02 -0.01 0.00 0.01 -0.09 -2.12 0.07 0.76 -0.61 0.31 1.68 0.18 0.62 0.00 0.06

G 10.62 0.02 -0.01 -0.03 0.58 -0.58 -6.28 0.26 5.07 4.75 -0.98 -2.87 -0.17 0.71 -0.22 0.26

13 P -0.32 0.03 0.00 0.00 0.01 -0.14 -0.22 0.38 -0.09 -0.08 0.02 0.25 0.00 -0.17 0.00 0.07

G -2.74 -0.04 0.00 -0.05 0.33 -0.99 -0.72 1.46 -0.65 0.63 -0.11 -0.42 0.00 -0.20 -0.25 0.32

134

14 P -0.97 0.02 0.01 0.00 -0.01 0.10 2.02 -0.12 -0.71 0.58 -0.27 -1.64 -0.17 -0.53 0.00 -0.06

G -10.14 -0.01 0.01 0.03 -0.61 0.67 6.04 -0.46 -4.76 -4.58 0.87 2.81 0.17 -0.61 0.23 -0.26

15 P 1.04 -0.03 -0.01 0.00 0.01 -0.08 -2.12 0.07 0.76 -0.62 0.30 1.70 0.17 0.61 0.00 0.06

G 10.69 0.02 -0.01 -0.03 0.52 -0.48 -6.27 0.26 5.06 4.80 -0.97 -2.90 -0.17 0.70 -0.27 0.25

16 P -0.69 0.02 0.00 0.00 0.00 -0.02 1.14 0.70 -0.68 0.31 -0.15 -0.81 -0.11 -0.87 0.00 -0.02

G -7.56 -0.03 0.00 -0.04 -0.29 -0.21 3.61 2.37 -4.63 -2.52 0.46 1.48 0.12 -1.00 -0.08 -0.11

17 P -1.17 0.04 0.01 0.00 -0.01 0.02 1.95 0.07 -0.76 0.56 -0.26 -1.58 -0.17 -0.63 0.00 -0.01

G -11.77 -0.04 0.01 0.02 -0.40 0.12 5.89 0.27 -5.20 -4.44 0.80 2.76 0.17 -0.74 0.16 -0.05

18 P 0.28 -0.16 -0.01 -0.01 0.00 0.11 -0.33 -0.15 0.17 -0.13 -0.03 0.51 0.01 0.11 0.00 0.02

G 4.76 0.10 -0.02 0.01 -0.39 0.90 -1.60 -0.56 1.58 1.78 0.01 -1.37 -0.01 0.15 -0.08 0.11

19 P 0.26 -0.03 -0.05 0.01 0.00 -0.03 -0.48 0.22 0.12 -0.19 0.16 0.52 0.01 0.00 0.00 0.02

G 6.93 0.13 -0.02 -0.03 0.20 0.04 -3.38 1.50 1.96 3.44 -1.07 -1.97 -0.02 0.04 -0.28 0.25

20 P 0.06 0.05 -0.02 0.02 0.00 -0.06 -0.23 0.35 -0.03 -0.08 0.08 0.17 0.01 -0.12 0.00 0.02

G 3.52 -0.03 -0.01 -0.05 1.11 -1.85 -3.95 5.13 -0.27 3.02 -0.97 -1.70 -0.09 -0.45 -0.86 0.42

21 P -0.33 -0.03 0.00 0.00 -0.02 0.29 0.92 -0.07 -0.33 0.18 -0.08 -0.52 -0.12 -0.35 0.00 -0.06

G -3.43 0.03 0.00 0.04 -1.36 1.90 2.72 -0.24 -2.21 -1.40 0.26 0.87 0.12 -0.41 0.21 -0.25

22 P -0.06 -0.04 0.00 0.00 -0.02 0.41 0.46 -0.19 -0.10 0.05 0.00 -0.17 -0.08 -0.11 0.00 -0.04

G -0.61 0.04 0.00 0.04 -1.11 2.33 1.60 -0.91 -0.74 -0.48 -0.07 0.37 0.09 -0.11 0.16 -0.18

24 P 1.06 -0.02 -0.01 0.00 0.01 -0.09 -2.16 0.02 0.80 -0.60 0.28 1.69 0.19 0.68 0.00 0.05

G 10.85 0.03 -0.01 -0.03 0.58 -0.59 -6.38 0.07 5.32 4.71 -0.90 -2.89 -0.19 0.77 -0.20 0.23

25 P -0.07 0.02 -0.01 0.01 0.00 -0.07 -0.04 1.15 -0.41 -0.04 -0.05 0.25 -0.01 -0.82 0.00 0.00

G -0.85 -0.02 -0.01 -0.07 0.09 -0.56 -0.13 3.74 -2.49 0.36 0.17 -0.46 0.01 -0.88 -0.38 0.00

26 P 0.98 -0.03 -0.01 0.00 0.01 -0.05 -1.90 -0.51 0.91 -0.51 0.29 1.36 0.18 0.99 0.00 0.04

G 10.28 0.03 -0.01 0.00 0.51 -0.29 -5.71 -1.57 5.96 4.07 -0.92 -2.38 -0.17 1.08 -0.01 0.20

27 P 0.92 -0.03 -0.01 0.00 0.01 -0.03 -1.83 0.06 0.66 -0.72 0.38 1.92 0.04 0.32 0.00 0.04

G 9.43 0.03 -0.01 -0.03 0.34 -0.20 -5.42 0.24 4.38 5.54 -1.21 -3.26 -0.04 0.37 -0.15 0.17

28 P 0.33 0.01 -0.01 0.00 0.00 0.00 -0.68 -0.07 0.29 -0.30 0.91 -0.26 -0.01 0.65 0.00 0.03

G 3.45 0.00 -0.01 -0.02 0.13 0.06 -2.11 -0.24 1.99 2.44 -2.74 0.26 0.01 0.72 -0.04 0.16

29 P 0.82 -0.04 -0.01 0.00 0.01 -0.03 -1.61 0.13 0.55 -0.61 -0.10 2.26 0.05 -0.04 0.00 0.02

G 8.58 0.04 -0.01 -0.02 0.32 -0.23 -4.88 0.45 3.75 4.77 0.19 -3.78 -0.05 0.00 -0.12 0.09

30 P -0.64 0.01 0.00 0.00 -0.01 0.11 1.34 0.04 -0.52 0.08 0.03 -0.35 -0.31 -0.81 0.00 -0.04

135

G -6.69 0.00 0.00 0.01 -0.55 0.73 3.96 0.18 -3.48 -0.71 -0.06 0.63 0.30 -0.92 0.16 -0.16

31 P -0.56 0.01 0.00 0.00 -0.01 0.03 1.12 0.72 -0.69 0.17 -0.45 0.07 -0.19 -1.32 0.00 -0.05

G -6.03 -0.01 0.00 -0.02 -0.39 0.19 3.41 2.29 -4.49 -1.41 1.38 0.00 0.19 -1.44 -0.06 -0.23

32 P 0.16 -0.01 0.00 0.00 0.00 -0.05 -0.36 0.33 0.01 -0.09 0.04 0.21 0.04 -0.05 0.00 0.04

G 1.60 0.01 0.00 -0.04 0.24 -0.32 -1.08 1.20 0.03 0.72 -0.10 -0.39 -0.04 -0.08 -1.17 0.20

33 P 0.05 -0.01 0.00 0.00 0.01 -0.07 -0.52 -0.01 0.19 -0.13 0.14 0.21 0.05 0.30 0.00 0.22

G 0.59 0.01 0.00 -0.02 0.35 -0.44 -1.53 -0.01 1.22 0.98 -0.45 -0.35 -0.05 0.34 -0.24 0.97

1 = Leaf: Length of blade ; 2 = Leaf: Width of blade ; 3 = Time of heading(50% plants with panicle) ; 4 = Stem: Thickness ; 5 = Stem: Length(excluding panicle) ; 6 =

Panicle: Length of main axis ; 7 = plant height ; 8 = Panicle: Number per plant (number of tillers) ; 9 = Panicle: Length of longest awn ; 10 = Time Maturity(Days) ; 11 = Grain: Weight

of 1000 fully develop grain ; 12 = Grain: Length ; 13 = Grain: Width ; 14 = L/B ratio ; 15 = Decorticated grain: Length ; 16 = Decorticated grain: Width ; 17 = L/B Ratio of decorticated

grain ; 18 = Biological Yield(gm) ; 19 = Grain Yield(gm) ; = 20 Harvest Index ; 21 = Hulling Percent ; 22 = Milling Percent ; 23 = Head Rice Recovery ; 24 = Length of milled grain ;

25 = Width of milled grain ; 26 = L/B ratio of milled grain ; 27 = Length of cooked kernel ; 28 = Width of cooked kernel ; 29 = L/B ratio of cooked kernel ; 30 = Elongation Ratio ; 31 =

Elongation index ; 32 = Endosperm content of Amylose ; 33 = Gel Consistency.

Residual effect: P=0.339; G=0.011.

136

Low residual value was observed (P= 0.339, G= 0.011), it indicates the

characters taken for study is sufficient to explain the variability.

The high positive direct effect on head rice recovery was exhibited by

Milling percent is in similar finding with Kumar et al. (2010), Ekka et al., (2011).

Table 4.8: Summarized data representing the direct effects of different traits

on grain yield and head rice recovery along with its correlations at

genotypic level

Traits Direct

effects

Correlation Direct

effects

Correlation

Grain yield HRR

Leaf: Length of blade(cm) - - -0.44 0.28

Time of heading(50% plants with

panicle)

-23.7 0.4 -5.42 0.34

Stem: Thickness(cm) 1.77 0.62 - -

Stem: Length(excluding panicle) -2.5 0.38 7.61 0.39

Panicle: Length of main axis(cm) -3.46 0.43 -0.6 0.46

Plant height(cm) 11.05 0.4 -7.03 0.42

Panicle: Number per plant (number

of tillers)

3.32 0.48 - -

Panicle: Length of longest awn(cm) - - -0.37 0.32

Time Maturity (Days) 29.13 0.37 3.91 0.37

Grain: Weight of 1000 fully develop

grain(g)

-1.35 0.56 1.68 0.29

Garin: Length(mm) -59.01 0.54 -0.55 0.34

L/B ratio -26.7 -0.54 - -

Decorticated grain: Length(mm) 1.47 0.54 -8.31 0.37

Decorticated grain: Width(mm) - - -1.07 -0.38

L/B Ratio of decorticated grain - - -11.77 -0.45

Biological Yield(g) -5.26 0.92 - -

Milling Percent - - 2.33 0.37

Head Rice Recovery (%) -1.15 0.34 - -

Length of milled grain(mm) 21.79 0.52 -6.38 0.39

Width of milled grain(mm) -19.32 0.4 - -

L/B ratio of milled grain -24.15 0.32 5.96 0.43

Length of cooked kernel(mm) -24.28 0.62 5.54 0.45

Width of cooked kernel(mm) 34.41 0.39 -2.74 0.33

L/B ratio of cooked kernel 42.61 0.52 -3.78 0.32

Gel Consistency 1.56 0.26 - -

137

Association and path coefficient analysis was performed between 33 yield

and quality characters among 48 rice germplasm accessions. The summarized data

representing the direct effect on grain yield and on head rice recovery along with

its correlation values at genotypic level is presented in Table 4.8. The results

revealed that the correlation between grain yield and 20 other traits is due to direct

effects as depicted in the aforesaid table clearly indicates a true relationship

between them and direct selection of these traits will be rewarding for yield

improvement. Higest correlation value of (0.92) was recorded by biological yield

followed by stem: thickness (0.62), length of cooked kernel (0.62), 1000 grain

weight (-0.56), grain: length (0.54), length of milled grain (0.52) and L/B ratio of

cooked kernel (0.52). Path analysis has been widely applied to several crop species

crested wheat grass (Dewey and Lu, 1959), cereals and legumes (Dixit and Singh,

1975, Singh and Singh, 1976; Mayo, 1984). The information obtained by this

technique helps in indirect selection for genetic improvement of grain yield and

head rice recovery. Selection for a component trait with a view to improve yield is

called indirect selection while selection for yield per se. is called as direct

selection. A greater yield response is obtained when the character for which

indirect selection is practiced has a high heritability and high correlation with

yield.

Path analysis provides information about the cause and effect situation and

helps in understanding the cause of association between two variables. It is quite

possible that a trait showing positive direct effect on yield may have negative

indirect effect via other component traits. Path analysis permits the examination of

direct effects of various characters on yield as well as their indirect effects via

other component traits. It provides the basis for selection of superior genotypes

from the diverse breeding population.

138

4.4 Principal component analysis

Principal component analysis (PCA) is a powerful tool in modern data

analysis because it is a simple, non-parametric method for extracting relevant

information from confusing data sets. With minimal effort, PCA provides a

roadmap for how to reduce a complex data set to a lower dimension to reveal

sometimes hidden, simplified structures that often underlie it. It reduces the

dimensionality of the data while retaining most of the variation in the data set.

PCA accomplishes this reduction by identifying directions, called Principal

Components (PCs), along which the variation in the data is maximal. By using a

few components, each sample can be represented by relatively few numbers

instead of by values for thousands of variables. Thus, the primary benefit of PCA

arise from quantifying the importance of each dimension for describing the

variability of a data set in more interpretable and more visualized dimensions

through linear combinations of variables that accounts for most of the variation

present in the original set of variables. Therefore, principal component analysis is a

variable reduction procedure.

In the present investigation, PCA was performed for thirty-three grain yield

and quality contributing traits in 48 germplasm accessions of rice presented in

Table 4.9 and table 4.10. As per the criteria set by Brejda et al. (2000), the PC with

Eigen value > 1 and which explained at least 5% of the variations in the data were

considered in the present study. The PC with higher Eigen values and variables

which had high factor loading was considered as best representative of system

attributes. Out of 33, only four principal components (PCs) exhibited more than

1.33 Eigen value, and showed about 63.74% cumulative variability among the

traits studied. So, these 4 PCs were given due importance for further explanation.

The PC-1 showed 39.98% while, PC-2, PC-3 and PC-4 exhibited 10.30%, 7.64 and

5.82% variability, respectively among the accessions for the traits under study. The

first PC accounts for as much of the variability in the data as possible, and each

succeeding component accounts for as much of the remaining variability as

possible.

139

Table 4.9: Eigen values of 33 yield and quality traits of 48 (24 short and 24 long grains length) rice germplasm accessions

PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9 PC10 PC11 PC12 PC13 PC14 PC15 PC16

Eigenvalue 13.19 3.40 2.52 1.92 1.45 1.37 1.24 1.11 1.06 0.96 0.79 0.62 0.58 0.53 0.51 0.44

Variability

(%)

39.98 10.30 7.64 5.82 4.40 4.16 3.75 3.36 3.22 2.91 2.39 1.89 1.75 1.59 1.54 1.32

Cumulative

%

39.98 50.28 57.91 63.74 68.13 72.29 76.04 79.41 82.62 85.53 87.92 89.81 91.56 93.15 94.70 96.02

PC17 PC18 PC19 PC20 PC21 PC22 PC23 PC24 PC25 PC26 PC27 PC28 PC29 PC30 PC31 PC32

Eigenvalue 0.34 0.26 0.21 0.15 0.12 0.10 0.05 0.04 0.02 0.01 0.00 0.00 0.00 0.00 0.00 0.00

Variability

%)

1.04 0.78 0.62 0.46 0.37 0.32 0.16 0.11 0.05 0.04 0.01 0.01 0.01 0.01 0.00 0.00

Cumulative

%

97.06 97.84 98.46 98.92 99.29 99.61 99.76 99.87 99.92 99.96 99.97 99.98 99.99 99.99 100.00 100.00

140

Table 4.10: Factor loading (Eigen vectors) of 48 (24 short and 24 long grains

length) rice germplasm accessions for yield and quality characters

Traits Components

PC 1 PC 2 PC 3 PC 4

Leaf: Length of blade(cm) 0.66 -0.07 -0.15 -0.10

Leaf: Width of blade(cm) 0.16 0.08 -0.29 0.21

Time of heading(50% plants with

panicle) 0.68 -0.25 0.18 -0.22

Stem: Thickness(cm) 0.24 0.01 0.26 0.52

Stem: Length(excluding panicle) 0.84 0.01 0.19 -0.16

Panicle: Length of main axis(cm) 0.78 0.00 0.19 0.10

plant height(cm) 0.86 0.01 0.19 -0.13

Panicle: Number per plant (number of

tillers) 0.01 0.16 0.12 0.67

Panicle: Length of longest awn(cm) 0.72 -0.08 -0.08 0.05

Time Maturity(Days) 0.69 -0.25 0.19 -0.22

Grain: Weight of 1000 fully develop

grain(g) 0.89 0.29 -0.03 0.01

Grain: Length(g) 0.96 0.16 -0.05 -0.04

Grain: Width(g) 0.07 0.66 -0.02 -0.07

L/B ratio -0.90 -0.25 0.09 0.00

Decorticated grain: Length(mm) 0.96 0.16 0.00 -0.02

Decorticated grain: Width(mm) -0.60 0.55 0.31 -0.03

L/B Ratio of decorticated grain -0.91 0.12 -0.03 0.05

Biological Yield(g) 0.27 -0.37 0.53 0.07

Grain Yield(g) 0.32 0.24 0.51 0.39

Harvest Index 0.14 0.58 0.16 0.23

Hulling Percent -0.38 -0.44 0.52 0.04

Milling Percent -0.16 -0.59 0.47 0.11

Head Rice Recovery (%) 0.47 -0.38 0.30 0.19

Length of milled grain(mm) 0.97 0.10 -0.07 -0.06

Width of milled grain(mm) -0.07 0.76 0.38 -0.15

L/B ratio of milled grain 0.90 -0.25 -0.24 0.03

Length of cooked kernel(mm) 0.86 0.08 0.25 -0.06

width of cooked kernel(mm) 0.37 -0.06 -0.02 0.50

L/B ratio of cooked kernel 0.74 0.12 0.31 -0.35

Elongation Ratio -0.55 -0.06 0.48 -0.01

Elongation index -0.57 0.40 0.52 -0.36

Endosperm content of Amylose 0.14 0.41 0.03 0.05

Gel Consistency 0.27 0.25 -0.12 0.43

Values in bold represent highly weighted factors in respective PC

141

Scree plot explained the percentage of variation associated with each

principal component obtained by drawing a graph between eigen values and

principal component numbers. First 9 components explains the 82.62% variation

and eign value >1. The PC-1 showed 39.98% variability with eigen value 13.19

which then declined gradually. Elbow type line is obtained which after 4th

PC

tended to straight with little variance observed in each PC. From the graph, it is

clear that the maximum variation was observed in PC-1 (Fig.4.30).

Fig. 4.30: Scree plot showing eigen value and percentage of cumulative variability

Fig. 4.31: Distribution of genotypes among two different Principal Components

0

20

40

60

80

100

0

5

10

15

F1 F3 F5 F7 F9 F11 F13 F15 F17 F19 F21 F23 F25 F27 F29 F31

Cu

mu

lati

ve

va

ria

bil

ity

(%

)

Eig

en

va

lue

axis

Scree plot

Lokti Machhi

Atma Sital

Lokti Machhi

ADT:27

Anjania

Kanak Jira

Jhumera

Kakeda (I)Dubraj II

BhulauRani kajarSundar mani

Bhado kankerJhumarwa

Bishnu

Basa Bhog

Krishna Bhog

Hira Nakhi

Lokti Maudi

Kariya bodela bijaGganja Kali

Banas KupiII

Dhangari Khusha

Bhaniya

Farsa phool

Jay Bajrang

Gilas

Khatia pati

Mani

Khatriya patiGirmit

Lanji

Banreg

Ruchi

Safed luchaiKanthi deshiPiso III

KakdiGajpati

Gadur sela

Aadan chilpaUnknown

Saja chhilau

Parmal Safri

SafriNarved

Nagbel

Mudariya

-6

-4

-2

0

2

4

6

8

-10 -8 -6 -4 -2 0 2 4 6 8 10

F2

(1

0.3

0 %

)

F1 (39.98 %)

Observations (axes F1 and F2: 50.28 %)

142

The results of the PCA explained the genetic diversity of the long and short

grain accessions of rice. „Proper values‟ measure the importance and contribution

of each component to total variance, whereas each co-efficient of proper factors

indicates the degree of contribution of every original variable with which each

principal component is associated. The higher the coefficients, regardless of the

direction (positive or negative), the more effective they will be in discriminating

between accessions (Sanni et al., 2010).

Within each PC, only highly loaded factors or traits (having absolute values

within 10% of the highest factor loading) were retained for further explanation.

Component matrix revealed that the PC-1 which accounted for the highest

variability (39.98%) was mostly related with traits such as length of milled grain

(0.97) followed by decorticated grain length (0.96), grain length (0.96), L/B ratio

of milled grain (0.90), 1000-grain weight (0.89), plant height (0.86), length of

cooked kernel (0.86), stem length (0.84), panicle length (0.78), L/B ratio of cooked

kernel (0.74), panicle : length of longest awn (0.72), time of maturity (0.69), time

of heading (0.68), leaf : length of blade (0.66), head rice recovery (0.47) and width

of cooked kernel (0.37) (Table-4.10). As a result, the first component differentiated

those accessions that have high length of milled grain, decorticated grain length,

grain length, L/B ratio of milled grain, 1000-grain weight, plant height, length of

cooked kernel, stem length, panicle length, L/B ratio of cooked kernel, time of

maturity, time of heading, leaf: length of blade, head rice recovery and width of

cooked kernel. The second principal component accounted for 10.30% of total

variance. Variables highly and positively correlated were width of milled grain,

grain width, harvest - index, width of decorticated grain, amylase content and L/B

ratio of decorticated grain. The second component thus identified good cooking

quality variables presenting positive contributions and the main characters

responsible for quality characterization. The third principal component accounted

for 7.64% of the variability and was highly loaded with four cooking quality

characters viz., elongation index, elongation ratio, hulling and milling percent as

well as two yield attributing characters i.e. Biological yield and grain yield.

The PC-4 was positively and more related with number of panicle per plant

followed by stem thickness, leaf width of blade and gel consistency. Thus, the

143

prominent characters coming together in different principal components and

contributing towards explaining the variability have the tendency to remain

together which may be kept into consideration during utilization of these characters

in breeding program. From the first four PCs, it was cleared that the PC-1, PC-2

are mostly related to quality characters while PC-3 and Pc-4 are associated with

yield related traits. So, for quality aspect a good breeding programme can be

initiated by selecting the accessions from PC-1 and PC-2. These results are in

agreement with the findings of earlier workers (Ashfaq et al., 2012; Chakraborty et

al., 2013; Sinha and Mishra, 2013 and Nachimuthu et al., 2014).

Top 10 principal component scores (PC scores) for all the accessions were

estimated in four principal components and presented in Table-4.12. These scores

can be utilized to propose precise selection indices whose intensity can be decided

by variability explained by each of the principal component. High PC score for a

particular accession in a particular component denotes high values for the variables

in that particular accession. Perusal of results revealed that the Khatria Pati had

highest PC score followed by Banreg, Khatia Pati, Piso III, Jay Bajrang, Nagbel,

Safed Luchai, Mudariya, Safri and Kanthi Deshi in PC-1 indicated that they had

high quality characters. In PC-2, Nagbel had the highest score followed by Saja

Chhilau, Anjania, Farsa Phool, Basa Bhog, Aadan Chilpa, Jhumarwa, Unknown,

Bhado Kanker and Mudariay for the highly loaded traits of cooking quality. The

highest PC score of PC-3 recorded by Ganja Kali followed by Unknown, Kariya

Bodela Bija, Piso III, Anjania, Safri, Bishnu, Ruchi, Lokti Maudi and Dhangari

Khusha it indicates that they had high yielding characters. In PC-4 Anjania had

highest score followed by Kanthi deshi, Kanak Jira, ADT: 27, Piso III, Bishnu,

Safed luchai, Basa Bhog, Krishna Bhog and Bhulau for yield related trait. On the

basis of top 10 PC scores in each principal component, accessions are selected and

presented in summarized form in Table-4.11.

Thus, it is cleared that the principal component analysis highlights the

characters with maximum variability. So, intensive selection procedures can be

designed to bring about rapid improvement of yield and quality traits. PCA also

help in ranking of genotypes on the basis of PC scores in corresponding

component. From the above results, it is cleared that Nagbel is the best accession

144

for both quality and yield attributing traits followed by Khatria pati, Anjania,

Banreg, Khatia pati, Piso III, Jay Bajrang, Safed luchai and Mudariya. This result

corroborates with the finding of Kumar et al. (2013). Above discussion revealed

that identified accessions may be used as donor to improve the yield and quality

traits in varietal development programme.

Table 4.11: List of selected accession in each principal component on the basis

of top 10 PC score

PC1 PC2 PC3 PC4

Khatriya pati Nagbel Gganja Kali Anjania

Banreg Saja chhilau Unknown Kanthi deshi

Khatia pati Anjania Kariya bodela bija Kanak Jira

Piso III Farsa phool Piso III ADT:27

Jay Bajrang Basa Bhog Anjania Piso III

Nagbel Aadan chilpa Safri Bishnu

Safed luchai Jhumarwa Bishnu Safed luchai

Mudariya Unknown Ruchi Basa Bhog

Safri Bhado kanker Lokti Maudi Krishna Bhog

Kanthi deshi Mudariya Dhangari Khusha Bhulau

145

Table 4.12: Principal component score of different accessions of 48 short and

long grain rice

Accessions Name Score

PC1 PC2 PC3 PC4

Lokti Machhi -2.66 -2.64 -0.74 -1.35

Atma Sital -2.03 -1.73 1.05 -2.16

Lokti Machhi -2.20 -4.45 -1.69 -0.88

ADT:27 -4.92 1.11 -3.95 1.44

Anjania -3.11 2.77 2.33 4.66

Kanak Jira -2.98 -1.07 -1.27 2.07

Jhumera -4.10 1.21 -0.15 0.80

Kakeda (I) -3.34 -0.25 -0.37 0.47

Dubraj II -3.45 0.00 0.50 -2.42

Bhulau -4.56 1.04 -0.66 0.89

Rani kajar -5.13 0.39 -0.96 -0.72

Sundar mani -3.94 0.63 0.53 -1.54

Bhado kanker -3.96 1.64 0.38 0.07

Jhumarwa -4.83 1.90 -0.92 0.40

Bishnu -2.23 -1.52 2.07 1.22

Basa Bhog -5.20 2.17 -2.69 1.07

Krishna Bhog -3.53 -1.94 0.54 1.00

Hira Nakhi -3.26 -0.21 -0.23 0.40

Lokti Maudi -2.57 -1.92 1.54 0.34

Kariya bodela bija -2.43 -0.27 2.52 0.36

Gganja Kali -2.99 -0.65 3.04 -0.59

Banas KupiII -3.63 -0.30 -0.33 -0.96

Dhangari Khusha -3.15 -2.03 1.47 0.59

Bhaniya -4.41 0.22 0.74 -3.62

Farsa phool 1.74 2.22 0.88 -1.12

Jay Bajrang 4.19 -0.68 -1.45 0.23

Gilas 3.22 0.50 -2.98 -1.24

Khatia pati 4.46 -0.87 0.47 -0.29

Mani 3.38 -1.79 -2.13 -1.54

Khatriya pati 4.71 -0.90 -1.67 0.40

Girmit 3.09 -0.63 -0.54 0.81

Lanji 4.02 1.04 -1.94 0.06

Banreg 4.57 -0.83 0.56 0.62

Ruchi 3.85 0.15 1.57 -1.02

Safed luchai 4.10 -2.38 -1.04 1.12

Kanthi deshi 4.03 -2.63 0.04 2.25

Piso III 4.35 -1.90 2.45 1.37

Kakdi 2.66 -0.05 -1.60 0.85

Gajpati 2.78 0.46 -0.55 -0.80

Gadur sela 3.08 0.02 -0.63 -0.09

Aadan chilpa 3.35 1.98 -2.30 -0.53

Unknown 2.46 1.74 2.80 -0.80

Saja chhilau 1.86 3.65 0.81 -2.25

Parmal Safri 3.38 0.48 1.30 -1.75

Safri 4.04 -1.04 2.30 0.68

Narved 3.09 -0.55 -0.23 0.18

Nagbel 4.12 6.44 0.79 0.48

Mudariya 4.09 1.48 0.35 0.84

Figures in bold represent top 10 scores in each principal component

146

4.5 Cluster analysis:

Cluster analysis among 48 rice germplasm accessions/genotypes was

studied. The clustering pattern of all the genotypes has been presented in Table-

4.13 and Fig 4.30. The 48 entries were grouped into 10 clusters. The highest

number of genotypes appeared in Cluster VII, which contain 16 genotypes

followed by Cluster VI (10 accessions), Cluster I (8 accessions), Cluster II, III and

VIII (3 accessions), Cluster IV (2 accessions) and Cluster V, IX and X (only one

accession). The pattern of group constellation proved the existence of significant

amount of variability. The inter- and intra cluster distances among ten clusters

were computed and are given in Table 4.14.

Table-4.13: Clustering patterns of 48 rice genotypes

Cluster

No.

No. of

germplasm Name of rice germplasm

I 8 Lokti Machhi, Kanak Jira, Jhumera, Kakeda (I), Dubraj II,

Rani kajar, Khatriya pati, Mudariya

II 3 Atma Sital, Krishna Bhog, Narved

III 3 Lokti Machhi, Bhulau, Bhaniya

IV 2 ADT:27, Basa Bhog

V 1 Anjania

VI 10

Sundar mani, Jhumarwa, Hira Nakhi, Kariya bodela bija, Jay

Bajrang, Mani, Safed luchai, Gajpati, Aadan chilpa, Saja

chhilau

VII 16

Bhado kanker, Lokti Maudi, Banas KupiII, Farsa phool,

Gilas, Khatia pati, Girmit, Lanji, Banreg, Ruchi, Kanthi

deshi, Piso III, Kakdi, Gadur sela, Unknown, Parmal Safri

VIII 3 Bishnu, Gganja Kali, Dhangari Khusha

IX 1 Safri

X 1 Nagbel

147

The intra cluster distance ranged from 0.00 (cluster V, IX and X) to 7.95

(Cluster I). The maximum intra cluster distance 7.95 was shown by Cluster I

having eight genotypes.

Table 4.14: Estimates of intra (diagonal and bold) and inter cluster distances

among ten clusters

1 2 3 4 5 6 7 8 9 10

1 7.95 20.18 9.41 14.49 19.64 11.80 16.89 24.28 28.09 18.72

2

6.76 22.15 24.65 21.24 16.92 11.36 13.60 19.65 26.12

3

7.27 11.57 20.24 14.77 19.22 25.94 29.53 17.22

4

5.86 22.63 18.56 22.13 28.08 31.49 17.75

5

0.00 18.68 19.69 23.94 26.92 20.98

6

6.27 12.63 21.59 25.70 20.60

7

7.39 17.55 22.47 23.79

8

5.67 14.52 29.18

9

0.00 32.12

10

0.00

The highest inter cluster distance was found between cluster IX and X

(32.12) followed by Cluster IV and IX (31.49). Cluster III and IX (29.53), Cluster

VIII and X (29.18), Cluster I and IX (28.09), Cluster IV and VIII (28.08), Cluster

V and IX (26.92), Cluster II and X (26.12), Cluster III and VIII (25.94), Cluster VI

and IX (25.7), Vluster I and VIII (24.28), Cluster II and IV (24.65), Cluster I and

VIII (24.28), Cluster V and VIII (23.94), Cluster VII and X (23.79), Cluster IV and

V (22.63), Cluster VII and IX (22.47), Cluster II and III (22.15), Cluster IV and

VII (22.13), Cluster VI and VIII (21.59), Cluster II and V (21.24), Cluster V and X

(20.98), Cluster VI andX (20.6), Cluster III and V (20.24), Cluster I and II (20.18),

Cluster V and VII (19.69), Cluster II and IX (19.65), Cluster I and V (19.64),

Cluster III and VII (19.22). Cluster I and X (18.72), Cluster V and VI (18.68),

Cluster IV and VI (18.56), Cluster IV and X (17.75), Cluster VII and VIII (17.55),

Cluster III and X (17.22), Cluster II and VI (16.92), Cluster I and VII (16.89),

Cluster III and VI (14.77), Cluster VIII and IX (14.52), Cluster I and IV (14.49),

Cluster II and VIII (13.60), Cluster VI and VII (12.63), Cluster I and VI (11.80),

Cluster III and IV (11.57) and Cluster II and VII (11.36).

The lowest inter-cluster distance was found between cluster I and III (9.41).

The inter-cluster distances in present study were higher than the Intra cluster

distance in all cases reflecting wider diversity among the breeding lines of the

distant group.

148

Fig. 4.32: Dendogram of 48 short and long grain accessions derived by

UPGMA from 33 yield and quality traits.

The cluster mean values showed a wide range of variations for all the

characters undertaken in the study (Table 4.15.). Cluster X exhibited highest mean

value for Time of heading (116.5), Stem length (177.6), Panicle length (27.15),

Plant height (204.8), Panicle number per plant (8.99), 1000-grain weight (37.5),

Grain length (11.45), Grain width (3.15), Decorticated grain length (8.3), Harvest

index (229.7), Length of milled grain (7.1), Width of milled grain (2.95), L/B ratio

of cooked kernel (3.19), Elongation index (1.33), Amylase content (28.33) and Gel

consistency (100). While cluster IX contained genotypes with highest mean value

for Time of heading (116.5), Time of maturity (146.5), Biological yield (144.0),

Hulling percent (77.52), Milling percent (68.18), Head rice recovery (56.43), L/B

ratio of milled grain (3.27) and Length of cooked kernel (10.4). Cluster V recorded

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149

highest value for Stem thickness (0.65, Decorticated grain width (2.95), Grain

yield (498.5) and Gel consistency (100) while highest mean value for Leaf width

of blade (0.78), L/B ratio of decorticated grain (0.66) and Gel consistency (100)

was recorded by cluster IV. Cluster I had highest value for Width of cooked kernel

(3.34) and Elongation ratio (1.77) while Cluster II had highest mean value for

Time of maturity (116.5) and Gel consistency (100). Cluster VII had highest mean

value for Leaf length of blade (39.63) and Length of longest awn (1.10) while

highest mean value for Grain L/B ratio (24.65) was recorded for Cluster VIII. This

result are in confirmation with the findings of Chanbeni et al. (2012); Shiva Prasad

et al. (2013); Kumar et al. (2014) Apsath Beevi and Venkatesan (2015) and

Rathore et al. (2016).

The selection and choice of parents mainly depends upon contribution of

characters towards divergence. It is well known that crosses between divergent

parents usually produce greater heterotic effect than between closely related ones.

Considering the importance of genetic distance and relative contribution of

characters towards total divergence, the present study indicated that parental lines

selected from cluster X (Nagbel) for Time of heading, Stem length, Panicle length,

Plant height, Panicle per plant, 1000-grain weight, Grain length, Grain width,

Decorticated grain length, Harvest index, Length of milled grain, L/B ratio of

cooked kernel, Elongation index, Amylose content and Gel consistency could be

used in crossing programmes to achieve desired segregants.

150

Table 4.15a: Cluster mean for quantitative characters in 48 aromatic landraces of C.G.

Cluster 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

1 36.37 0.74 109.94 0.43 134.71 21.14 155.85 7.36 0.33 139.25 19.53 7.09 2.55 21.30 5.05 2.41

2 32.40 0.68 116.50 0.42 139.87 23.78 163.65 7.62 0.00 145.83 16.45 7.02 2.28 22.52 5.25 2.22

3 34.05 0.72 109.83 0.43 126.37 18.62 144.98 7.04 0.00 137.83 13.18 5.77 2.28 24.31 4.22 2.43

4 33.38 0.78 89.50 0.48 84.10 20.45 104.55 7.83 0.00 117.50 16.85 5.75 2.75 20.62 4.18 2.48

5 29.30 0.75 113.00 0.65 100.70 19.60 120.30 8.93 0.00 141.00 16.45 5.85 2.40 24.11 4.15 2.95

6 34.56 0.66 113.05 0.45 148.75 22.07 170.82 6.99 0.55 141.85 24.27 8.78 2.58 17.47 6.13 2.41

7 39.63 0.74 115.28 0.50 152.53 24.42 176.94 7.43 1.10 144.78 25.18 9.69 2.52 15.69 6.70 2.18

8 31.48 0.58 107.67 0.48 131.90 22.95 154.85 7.76 0.00 137.00 16.70 5.57 2.27 24.65 4.15 2.57

9 37.80 0.75 116.50 0.45 165.00 25.85 190.85 8.57 0.75 146.50 29.30 10.45 2.40 14.02 7.90 2.15

10 38.10 0.75 116.50 0.40 177.60 27.15 204.75 8.99 0.95 144.50 37.50 11.45 3.15 12.62 8.30 2.65







151

Table: 4.15b Cluster mean for quantitative characters in 48 aromatic landraces of C.G.

Cluster 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33

1 0.55 690.81 140.56 20.37 74.05 62.55 49.43 4.54 2.20 2.10 7.81 3.34 2.32 1.77 1.18 21.65 92.00

2 0.47 1079.00 174.50 16.99 74.35 63.21 48.36 4.75 2.05 2.30 7.50 2.88 2.60 1.64 1.17 21.08 100.00

3 0.55 571.33 114.17 22.16 77.28 64.84 44.36 3.80 2.17 1.84 6.53 3.02 2.23 1.72 1.30 20.60 60.00

4 0.66 445.25 75.50 16.30 68.69 57.88 42.82 3.78 2.23 1.71 5.88 2.90 2.02 1.56 1.20 22.67 100.00

5 0.58 760.00 498.50 111.98 70.55 58.87 48.51 3.90 2.75 1.42 6.80 3.70 1.84 1.74 1.30 22.21 100.00

6 0.46 797.20 181.35 23.08 69.79 59.05 49.26 5.58 2.27 2.57 8.32 3.29 2.55 1.57 1.09 22.02 91.65

7 0.40 927.09 190.91 20.50 71.00 62.47 50.28 6.02 2.29 2.67 9.45 3.27 2.90 1.59 1.13 23.21 92.50

8 0.54 1247.33 213.67 17.46 77.30 67.83 55.26 3.98 2.28 1.75 6.82 3.03 2.28 1.71 1.30 21.38 77.17

9 0.30 1439.50 284.50 20.71 77.52 68.18 56.43 6.70 2.05 3.27 10.40 3.05 3.41 1.55 1.05 28.23 98.00

10 0.38 430.00 259.00 229.71 64.34 54.58 46.27 7.10 2.95 2.41 10.35 3.25 3.19 1.46 1.33 28.33 100.00







152

Cluster analysis is one of the useful tools for selection and efficient use of

parents in hybridization program to develop high yielding potential

cultivars/hybrids. The better genotypes can be selected for most of the

characters on the basis of mean performance of the genotypes in the cluster.

The value of percentage contribution of 33 characters (Table: 4.16), included in

cluster analysis, towards divergence ranged from time of maturity (0.67) to

length of longest awn (cm) (16.74). Highest percentage contribution towards

divergence was recorded by trait, length of longest awn (16.74) followed by

harvest index (%) (14.04), 1000-grain weight (4.41), grain yield (g) (4.22), L/B

ratio of milled grain (3.71), grain length (3.53), L/B ratio of decorticated grain

(3.46), decorticated grain length (3.40), grain L/B ratio (3.29), length of milled

grain (3.27), biological yield (2.85), elongation index (2.71), length of cooked

kernel (2.62), L/B ratio of cooked kernel(2.39), amylase content (2.11),

decorticated grain width (1.80), stem length (1.79), leaf : length of blade (1.68),

grain width (1.65), width of milled grain (1.60), leaf width of blade (1.57),

number of panicle per plant (1.54), width of cooked kernel (1.33), milling

percent (1.17), hulling percent (0.93), time of heading (0.82) and time of the

maturity (0.67). The result is in agreement with Rashid et al. (2014) and

Ayesha et al. (2015).

153

Table: 4.16 Percent contribution of each character

S. No. Variable % contribution of each

character

1 Leaf: Length of blade(cm) 1.68

2 Leaf: Width of blade(cm) 1.57

3 Time of heading(50% plants with

panicle) 0.82

4 Stem: Thickness(cm) 1.81

5 Stem: Length(excluding panicle)(cm) 1.79

6 Panicle: Length of main axis(cm) 1.74

7 plant height(cm) 1.72

8 Panicle: Number per plant (number of

tillers) 1.54

9 Panicle: Length of longest awn(cm) 16.74

10 Time Maturity(Days) 0.67

11 Grain: Weight of 1000 fully develop

grain(g) 4.41

12 Grain: Length(mm) 3.53

13 Grain: Width(mm) 1.65

14 L/B ratio 3.29

15 Decorticated grain: Length(mm) 3.40

16 Decorticated grain: Width(mm) 1.80

17 L/B Ratio of decorticated grain 3.46

18 Biological Yield(g) 2.85

19 Grain Yield(g) 4.22

20 Harvest Index 14.04

21 Hulling Percent 0.93

22 Milling Percent 1.17

23 Head Rice Recovery (%) 1.83

24 Length of milled grain(mm) 3.27

25 Width of milled grain(mm) 1.60

26 L/B ratio of milled grain 3.71

27 Length of cooked kernel(mm) 2.62

28 width of cooked kernel(mm) 1.33

29 L/B ratio of cooked kernel 2.39

30 Elongation Ratio 1.74

31 elongation index 2.71

32 Endosperm content of Amylose 2.11

33 Gel Consistency 1.84

154

4.6 Molecular Characterization:

Grain size and weight contribute for crop yield in cereals, whereas in rice, grain

size and shape are major criteria to assess market value and to classify rice genotypes.

Grain size with its dimensions for length and width has become a target trait for rice

breeding in recent years (Xing & Zhang, 2010). Preferences for grain size and grain

shape varies widely between countries; some like long and cylindrical grains (USA and

Europe) and others go for short and round grains including China, Japan, and Korea

(Bai et al., 2010). Rice varieties show huge amount of variation in grain size (Juliano

&Villareal, 1993).

Many individual quantitative trait loci (QTLs) studies for grain size have been

carried out. These individual studies reported hundreds of QTLs, out of which very few

were reported by dozens of studies with different genetic background (Lin et at., 1995;

Tan et al., 2000; Thomson et al., 2003: Li et al., 2004; Lei et al., 2006; Bai et al., 2010;

Shao et al., 2010). Out of many independent studies for identification of QTLs for grain

length in rice, located on chromosome 3 and chromosome 7 has been reported number

of times in different genetic background. Tsunematsu et al. (1996) mapped two QTLs

for grain length on chromosomes 3 and 7, by using F7 population derived from a cross

between Asominari and IR64. Redona & Mackill (1998) also found seven QTLs for

grain length and grain shape were mostly controlled by loci on chromosomes 3 and

chromosomes 7. Tan et al., (2000) identified the QTLs for appearance characteristics of

rice, and suggested that grain length and grain width were individually controlled by

one or two major QTLs and minor QTLs. Numbers of grain length genes was reported

by Wan et al., (2006) on chromosome 2, 3, 5, 7 & 9 with varying phenotypic variation

5.8 to 35.6 in three different environments using SSR and EST markers. Dong & Zheng

(2002) studied steamed-rice shape and detected three QTLs for length on chromosomes

2, 3 and 10.

The outcome of several studies resulted in identification of QTL for grain length

or grain size on chromosome 3 by using different genetic background with biparental

populations originating from indica/ indica and indica/japonica crosses (Li et al., 1997;

Yu et al., 1997; Xiao et al., 1996; Redona & Mackill 1998; Kubo et al., 2001; Xing et

155

al., 2002; Moncada et al., 2001). Bai et al., (2010) reported QTL for grain length on

chromosome 7. Shao et al., (2010) also reported QTL on chromosome 7 placed about

13.2 cM away from the QTL qGL7. The genetic separation between these two loci

implies that they are distinct from each other. Xu et al., (2002) also identified a QTL

associated with variation for grain length (13.9% phenotypic variance) near to the

location of qGL7-2. A QTL was found associated with grain length between the interval

of SSR markers RM505 and RM248 on chromosome 7 by Zheng et al., (2007). The

main aim of this study was to evaluate the correlation between phenotypic diversity

analysis and genetic phylogenetic analysis of chromosomes 3 and 7 based on grain

length variations.

4.6.1 Development of genotypic data based on SSR and ISSR Markers

Total genomic DNA was extracted from 48 lines viz., 24 long grain lengths and

24 short grain length of rice using CTAB method (Zheng et al., 1995). Fresh and

healthy leaves were used for extraction of DNA. The DNA samples were quantified by

using Nano Drop Spectroscopy (NANODROP 2000c). The quantity of the samples was

found in the range from 500-2000 ηg/μl. DNA samples were then diluted with sterilized

water such that the final concentration of DNA became 50 ηg/μl.

Grain length variation: Phenotypic analysis of 48 rice accessions, showed statistically

significant difference in grain length. Grain length variation ranged from 5.2 mm to 11.8

mm. The average grain length was 8.2 mm was found among these accessions.

Maximum grain length was found in Jay Bajrang (11.8 mm) followed by Nagbel (11.5

mm) and Khatriya Pati (11.4 mm). The minimum grain length was found in Rani Kajar

and Jhumarwa (5.2 mm).

4.6.1.1 SSR marker analysis

Genetic associations among 48 accessions were analyzed, based on phenotypic

variation of grain length with the help of 59 SSR markers covering all the

chromosomes. Out of 59 SSR markers, six primers were found monomorphic across all

accessions. A total of 199 alleles were amplified and the number of alleles per locus

156

generated by each marker ranged from 1 to 11 alleles with an average number of 3.37

alleles per locus. Maximum number of alleles (11) was amplified by marker RM 1

marker. The PIC value across markers ranged from 0 to 0.87 with an average of 0.47.

Maximum PIC on chromosome 1 was 0.87 at marker RM 1 followed by RM 19 (0.85)

and RM 135 (0.81).

Table 4.17: List of 59 microsatellite markers with their chromosome locations,

number of alleles, allele size and PIC value found among 48 rice

accessions

S. No. Marker Amplicon

Size

No. of

Alleles

Chromosome

No. #

PIC Value

1 RM 1 67-119 11 1 0.87

2 RM 5 94-138 6 1 0.74

3 RM11 118-151 3 7 0.49

4 RM 19 192-250 10 12 0.85

5 RM 25 121-159 6 8 0.79

6 RM 30 100-140 1 6 0

7 RM 104 222-238 1 1 0

8 RM 105 100-141 4 9 0.59

9 RM 125 105-147 3 7 0.12

10 RM 130 73-81 2 3 0.22

11 RM 132 70-85 2 3 0.5

12 RM 134 92-94 2 7 0.04

13 RM 135 100-150 7 3 0.81

14 RM 148 190-210 4 3 0.65

15 RM 152 133-157 3 8 0.64

16 RM 154 148-230 3 2 0.55

17 RM 161 154-187 3 5 0.28

18 RM 168 96-116 2 3 0.64

19 RM 171 307-347 5 10 0.77

20 RM 172 159-165 2 7 0.49

21 RM 175 80-95 2 3 0.15

22 RM 186 115-132 3 3 0.51

23 RM 201 155-350 2 9 0.48

24 RM 215 126-161 3 9 0.38

25 RM 218 100-120 4 3 0.64

26 RM 231 157-182 3 3 0.55

27 RM 234 133-163 3 7 0.26

157

28 RM 242 200-290 4 9 0.32

29 RM 248 75-100 4 7 0.53

30 RM 287 82-118 3 11 0.46

31 RM 316 194-216 3 9 0.55

32 RM 338 178-184 2 3 0.35

33 RM 408 112-128 2 8 0.50

34 RM 422 385-450 5 3 0.76

35 RM 431 233-261 2 1 0.25

36 RM 432 150-187 5 7 0.76

37 RM 433 216-248 2 8 0.49

38 RM 436 83-134 4 7 0.66

39 RM 447 95-146 4 8 0.72

40 RM 455 127-144 6 7 0.79

41 RM 468 260-350 4 3 0.72

42 RM 481 95-200 6 7 0.79

43 RM 489 248-314 3 3 0.29

44 RM 501 130-179 3 7 0.53

45 RM 517 260-287 3 3 0.57

46 RM 520 200-290 4 3 0.69

47 RM 523 130-150 3 3 0.55

48 RM 527 200-233 2 6 0.33

49 RM 545 150-230 3 3 0.53

50 RM 546 115-150 1 3 0

51 RM 560 237-368 3 7 0.52

52 RM 569 170-185 2 3 0.15

53 RM 22565 200-280 5 8 0.55

54 RM 22710 150-180 1 8 0.44

55 RM 3825 147-200 3 1 0.7

56 OSR-13 85-122 2 8 0

57 Xa- 5 S 300 1 5 0

58 Xa-13 Pro 290-610 1 8 0

59 Xa-21 800-1200 3 11 0.23

4.6.1.1a Similarity coefficient analysis and Clustering:

Many studies have also reported significantly greater allelic diversity of

microsatellite markers than other molecular markers (McCouch et. al., 2001).

Microsatellite markers (SSR) are also used to detect the genetic similarity of long and

158

short grain accessions of rice under study. The genetic similarity coefficient ranged

from 0.21-0.93 as revealed by UPGMA cluster analysis using the 59 SSR markers. Rice

similarity index revealed that high degree of similarity to the extent of 93% exists

between Anjania, Kanak Jira and Jhumera. Similar studies were made by different

authors using SSR markers (Pal et al., 2003; Chakravarthi and Naravaneni, 2006). Three

major clusters were formed 1st cluster consist of 22 genotypes whereas 2

nd cluster

consisted of 20 and 3rd

cluster consist of 6 genotypes (Fig. 4.32).

The accessions that are derivatives of genetically similar dropped in one group.

In UPGMA tree, the accessions within group 1, 2 and 3 clustered into smaller sub

groups based on short and long grains. Group I had twenty-two accessions at 47%

similarity and is further subdivided into 3 sub-clusters. Sub-cluster I consisted of eight

genotypes which fall into category of long grains, it consisted of Farsa Phool, Jay

Bajarang, Khatriya Pati, Khatiya Pati, Gilas, Mani, Lanji and Girmit. Sub-cluster II

consists of nine short grains genotypes which are ADT: 27, Anjania, Kanak Jira,

Jhumera, Sundar Mani, Kakeda I, Bhulau, Rani Kajar, Dubraj II. Sub-cluster III consists

of five genotypes in which Atma Sital is short grain genotype whereas Banreg, Safed

luchai, Ruchi and Kanthi deshi are long grain genotypes.

Group II consists of twenty genotypes at 39% similarity and is further sub-

divided into three sub-clusters. Sub-cluster I had seven long grain accessions which are,

Kakdi, Piso III, Gjpati, Gadursela, Aadan chilpa, Unknown, Saja Chhilau. Sub-cluster II

had eight genotypes among them Parmal Safri, Safri, Narved, Nagbel and Mudariya are

long grain genotypes whereas Bhado Kanker, Jhumarwa, and Bishnu are short grain

genotypes. Sub-cluster III consists of five short grain genotypes which are Hira Nakhi,

Ganja Kali, Dhangri Khusha, Banas Kupi II and Basa Bhog.

Group III consists of six short grain genotypes at 27% similarity and is

comprised of Lokti Machhi, Lokti Machhi (CGR No. 10029), Krishna Bhog, Lokti

Maudi, Kariya Bodela Bija and Bhaniya. Similar kind of findings has been reported by

Kashif and Arif (2014), Singh and Singh (2012).

159

Fig: 4.33: UPGMA-based molecular dendogram of SSR marker showing 48 rice

germplasm

4.6.1.1b Polymorphism Information Content of SSR markers:

Polymorphism Information Content provides an estimate of determining power

of a marker based on the number of alleles at a locus and relative frequencies of these

alleles. PIC value represents the relative informativeness of each marker and in the

present study, PIC value ranged between 0 for RM 30, RM 104, RM 546, OSR-13, Xa-

5S, Xa-13 Pro to 0.87 for RM 1 followed by 0.85 for RM 19 and 0.81 for RM 135 with

an average PIC value of 0.47 (Fig: 4.34).

160

Fig4.34: PCR amplification of 48 short (24) and long (24) grain accessions of rice

with SSR primer RM 22565 and RM 520.

161

Fig 4.35: Graphical representation of PIC value of SSR markers

162

4.6.1.2 ISSR marker analysis:

A total of 10 ISSR primers were taken for this study. The 10 primers

yielded a total of 46 amplified fragments from 48 rice genotypes and out of these,

29 alleles were polymorphic (Table 4.18). The number of scorable bands produced

per primer ranged from 2 to 6 with an average of 4.6, and the average number of

polymorphic fragments per primer was 2.9. The banding profile and polymorphism

generated using one of the primers (UBC 834 and UBC 842) is shown in Fig 4.35.

The highest number of alleles (6) was detected on each of locus UBC 809, UBC

834, UBC 841, UBC 842, UBC 873 and the lowest number of alleles (2) was

detected on locus UBC 824. Out of 10 ISSR markers, two makers UBC 818, UBC

885 exhibited monomorphic reaction for all the accessions whereas rest 8 showed

polymorphic reaction. The polymorphism percentage ranged from 33.33% (primer

UBC 834) to 100% (primer UBC 824, UBC 841, UBC 856) with an average

polymorphism of 60% across all the 48 long and short grain length rice genotypes.

Similar to our study, Ben El Maati et al. (2004) and Fatehi et al. (2011) have found

moderate level of average polymorphism (45%) in their studies. High level of

polymorphism has been reported by Sofalian et al. (2008), Zhu et al. (2011) and

Sadigova et al. (2014). The suitability of the ISSR technique for genetic diversity

studies and germplasm evaluations has been shown in many studies (Shukla et al.,

2011, Tiwari et al., 2013, Kumbhar et al., 2013, Samal et al., 2014 and Singh et

al., 2015).


The relationships among rice genotypes were estimated by a UPGMA

cluster analysis of genetic similarity matrices. ISSR similarity coefficient between

different genotypes ranged from 0.52 to 1.00. Two major clusters were formed and

are sub-divided into three sub-clusters. 1st cluster consists of 24 genotypes whereas

2nd

cluster also consisted of 24 rice genotypes (Fig4.35).

163

Table 4.18: List of 10 ISSR markers with their PIC value, No. of alleles

percentage polymorphism found among 48 rice accessions

Marker No. Of

Alleles

PIC

VALUE

Total No.

of bands

No. of polymorphic

bands

Percentage

Polymorphism

UBC 808 3 0.25 3 2 66.67

UBC 809 6 0.29 6 5 83.33

UBC 818 3 0.00 3 0 0.00

UBC 824 2 0.50 2 2 100.00

UBC 834 6 0.07 6 2 33.33

UBC 841 6 0.50 6 6 100.00

UBC 842 6 0.07 6 3 50.00

UBC 856 5 0.46 5 5 100.00

UBC 873 6 0.15 6 4 66.67

UBC 885 3 0.08 3 0 0.00

The accessions that are derivatives of genetically similar dropped in one

group. Group I exhibited 76.5% similarity coefficient among all the accessions of

the group which include 24 genotypes. It is further subdivided into three sub-

clusters, sub-cluster I consists of 12 long grain genotypes which are Farasaphool,

Jay Bajarang, Khatia Pati, Khatriya Pati, Ruchi, Kanthi deshi, Mani, Banreg, Gilas,

Lanji, Girmit, Safed luchai. Sub- cluster II consists of 10 short grain genotypes

which are Atma Sital, Dubraj II, Anjania, Kanak Jira, Jhumera, Kakeda (I),

Bhulau, Rani Kajar, Sundar Mani and ADT: 27. Sub-cluster III comprised of two

short grain genotypes that are Lokti Machhi and Lokti Machhi (CGR No. 10029).

Group II consists of 24 genotypes at 84% similarity and sub-divided into

three sub-clusters. Sub-cluster I consists of six short grain genotypes which are

Kakdi, Basa Bhog, Krishna Bhog, Lokti Maudi, Kariya Bodela Bija and Bhaniya.

Sub-cluster II consists of 16 genotypes which are Piso III, Gajan Kali, Banas Kupi

III, Dhangri Khusha, Gajpati, Gadursela, Aadan Chilpa, Unknown, Saja Chhilau,

Nagbel, Mudariya, Bhado Kanker, Jhumarwa, Bishnu, Narved and Hira Nakhi.

Sub-cluster III comprised of two long grain genotypes that are Parmal Safri and

164

Safri. This result is in accordance with the findings of Nagraj et al., 2001 and

Singh et al., 2015.

Rice similarity index reveals that high degree of similarity to the extent of

100% exists in many genotypes, in sub-group I under group I Farsa Phool, Jay

Bajrang, Khatia Pati, Khatriya Pati, and Ruchi shows 100% similarity. Again in

same sub-group Mani and Banreg also exhibited 100% similarity. Again under

group I, in sub-group II Anjania, Kanak Jira, Jhumera and Kakeda (I) shows 100%

similarity whereas in same sub-group 100% similarity exists between Bhuau, Rani

Kajar and Sundar Mani. Under group II in sub-group II 100% similarity exists

between Gajpati, Gadursela, Adanchilpa, Unknown, Sajachhilau, Nagbel and

Mudariya in the same sub-group Bhado Kanker, Jhumarwa and Bishnu shows

100% similarity, again in the same sub-group Ganja Kali, Banas Kupi III, and

Dhangri Khusha shows 100% similarity.

Fig 4.36: UPGMA-based molecular dendogram of ISSR marker showing 48

rice germplasm

Coefficient

0.52 0.64 0.76 0.88 1.00

Farsaphool JayBajrang Khatiapati Khatriyapati Ruchi Kanthideshi Mani Banreg Gilas Lanji Girmit Safedluchai AtmaSital DubrajII Anjania KanakJira Jhumera Kakeda(I) Bhulau Ranikajar Sundarmani ADT:27 LoktiMachhi LoktiMachhi Kakdi BasaBhog KrishnaBhog LoktiMaudi Kariyabodelabij Bhaniya PisoIII GganjaKali BanasKupiII DhangariKhusha Gajpati Gadursela Aadanchilpa Unknown Sajachhilau Nagbel Mudariya Bhadokanker Jhumarwa Bishnu Narved HiraNakhi ParmalSafri Safri

165

4.6.1.2b Polymorphism Information Content of ISSR markers

Polymorphism Information Content provides an estimate of determining

power of a marker based on the number of alleles at a locus and relative

frequencies of these alleles. PIC value represents the relative informativeness of

each marker and in the present study, PIC values ranged between 0 for UBC 818 to

0.5 for UBC 824 and UBC 841 followed by 0.46 for UBC 856 with an average PIC

value of 0.24(Table 4.18). ISSR markers are frequently used for varietal

diagnostic purposes in many crop species (Raina et al., 2001 and Gorji et al.,

2011).

Phenotypic analysis and genotypic analysis did not conceded with each

other because the grain length is a quantitative trait and is affected by number of

genes/ QTLs. These observations demonstrate that molecular marker especially

SSR technology can be useful to track the genomic regions from different rice

parents including those for grain length and can greatly improve the pricesion and

efficiency of rice breeding programs (Aslam and Arif, 2014).

Fig 4.37a: PCR amplification of 48 short (24) and long (24) grain accessions of

rice with ISSR primer UBC 834

166

Fig 4.37b: PCR amplification of 48 aromatic short and long grain accessions

of rice with ISSR primer UBC 842

Fig 4.38: Graphical representation of PIC value of ISSR marker

0.00

0.10

0.20

0.30

0.40

0.50

0.60

UBC

808

UBC

809

UBC

818

UBC

824

UBC

834

UBC

841

UBC

842

UBC

856

UBC

873

UBC

885

PIC VALUE

PIC VALUE

167

CHAPTER- V

SUMMARY AND CONCLUSION

The present study “Molecular and agro-morphological characterization

of selected rice (Oryza sativa L.) germplasm accession based on grain length”

was carried out by using forty eight short and long grain rice landraces, with the

objective of their characterization at morphological, quality and molecular level.

The experiment was conducted at Research cum Instructional farm of IGKV,

Raipur during Kharif 2015. The experiment was conducted in Randomized Block

Design (RBD), with two replications. The plants were observed regularly at

different growth stages in order to find out the diagnostic descriptors of each land

race which were uniformly present in the population and to be stable. Apart from

morphological descriptors and quality analysis, molecular markers were also

applied in order to characterize these rice germplasm lines at DNA level. In order

to propose elite plant type with desired characters i.e. mean, range, phenotypic and

genotypic coefficient of variances, heritability, genetic advance and genetic

advance as percentage of mean were also studied.

Rice genetic diversity assessed so far suggests a broad genetic base in

India. Genotype specific pattern have been developed particularly for the elite

Basmati types for use in trade and commerce. The landraces available today

preserve the allelic richness. Commercial cultivars are genetically homogenous

while the landraces studied revealed composite genetic structure. Forty eight short

and long grain landraces of rice from Chhattisgarh were selected for this study; the

results can be summarized as below:

To establish distinctiveness among rice genotypes qualitative (DUS)

characters have been used. Qualitative characters are considered as morphological

markers in the identification of germplasm accessions of rice because they are less

influenced by environment. In the present investigation, among the qualitative

characters observed, leaf blade pubescence, leaf blade colour, panicle type, lemma

168

and palea colour, lemma and palea pubescence, sterile lemma colour recorded

highest variation among accessions.

Analysis of variance revealed the existence of significant variability for all

the characters included for study. The high magnitude of phenotypic coefficient of

variation was higher in magnitude than the genotypic coefficient of variation. The

highest value of PCV coupled with GCV was recorded for harvest index followed

by grain yield, length of longest awn, thousand grain weight, L:B ratio of milled

rice, grain length, L:B ratio of decorticated grain, Decorticated grain length, length

of milled grain, length of cooked kernel, L:B ratio of cooked kernel and elongation

index.

High heritability coupled with high genetic advance exhibited in twenty

traits such as grain length, thousand grain weight, elongation ratio, amylose

content, head rice recovery etc. High estimate of heritability was found for all the

quantitative characters related to yield and quality characters under study showed

more than 90% heritability estimate.

Grain yield had significant high positive genotypic correlation with

thousand grain weight. Number of panicle per plant, biological yield per plant,

grain length showed highly significant genotypic correlation with grain yield per

plant indicating the co-segregation of the concerned characters either due to linked

gene or pleiotropy effect or both. The trait biological yield per plant also had

significant very high positive direct effect on grain yield per plant revealing the

true relationship with grain yield.

On the basis of cluster analysis rice accession lines were grouped into 10

clusters. The highest numbers of accessions were in cluster VII, VI, and I had 16,

10 and 8 genotypes, respectively. The maximum inter cluster distance was

observed between cluster IX and cluster X (32.12). The inter cluster distances in

present study were higher than the intra cluster distance in all cases reflecting

wider diversity among the breeding lines of distant groups.

The result of the PCA explained the genetic diversity of the long and short

grain accessions of rice. From the results of PCA, it is cleared that Nagbel is the

best accession for both quality and yield attributing traits followed by Khatria pati,

169

Anjania, Banreg, Khatia pati, Piso III, Jay Bajrang, Safed luchai and Mudariya. A

total of 59 RM primers and 10 ISSR markers were utilized to provide genetic

diversity among 48 selected rice landraces.

After analysis the data generated from 59 microsatellite markers (SSR), 53

markers showed polymorphic reaction and out of 10 ISSR primers 8 markers

showed polymorphic reaction in forty eight rice accessions. SSR and ISSR markers

are also used to detect the genetic similarity of long and short grain accessions of

rice under study. The accessions that are derivatives of genetically similar dropped

in one group. In UPGMA tree, three major clusters were formed having 22, 20 and

6 genotypes in SSR marker while two major clusters were formed in ISSR having

24 genotypes in each cluster.

CONCLUSIONS:

Agro-morphological and quality descriptors showed remarkable differences

in their distribution and amount of variations within them.

Significant variation in all 33 yield and yield attributing traits were

obtained. Highest variation (PCV and GCV along with high heritability and

genetic advance) was observed in thousand grain weight followed by grain

length, decorticated grain length, length of milled grain, length of cooked

kernel and elongation index.

Biological yield, stem thickness, plant height, panicle per plant, time of

maturity and decorticated grain length exhibited positive and highly

significant correlation with grain yield as well as positive direct effect on

grain yield per plant.

Principal component analysis showed the contribution of each character to

the classification of rice accessions. The first four principal components

explained 63.74% of total variation among 33 traits. Top ten PC scores

revealed that Khatriya Pati is the best accession for both yield and quality

followed by Banreg, Khatiya Pati, Piso III, Jay Bajrang, Nagbel, Safed

Luchai, Mudariya, Safri and Kanthi Deshi.

Ten cluster groups were obtained from 33 yield and quality characters

using multivariate analysis. Inter crossing of genotypes from diverse cluster

170

showing high mean performance will be helpful in obtaining better

recombinants with higher genetic variability.

A total of 59 SSR and 10 ISSR markers were used, A total of 199 and 46

alleles with an average of 3.37 and 2.9 alleles per locus were detected by

SSR and ISSR markers respectively. Out of which 53 SSR and 8 ISSR

showed polymorphism. Genetic similarity coefficient ranged from 0.21-

0.93 and 0.52-1.00 as revealed by UPGMA cluster analysis of SSR and

ISSR markers.

171

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190

Appendix A: Weekly Meteorological Data during Crop Growth Period of Kharif -2015)

Wk No. Date Max.

Temp.

(0C)

Min.

Temp.

(0C)

Rainfall

(mm)

Rainy

days

Relative Humidity

(%)

Vapour Pressure

(mm of Hg)

Wind

Velocity

(Kmph)

Evaporation

(mm)

Sunshine

(hours)

I II I II

26 25-01 33.5 25 25.8 4 87 59 22.8 21.6 9.3 6.4 4.3

27 Jul 02-08 33.6 25.2 41.8 2 79 64 21.7 22 9.1 6.4 5.9

28 09-15 31.2 25.2 72.8 5 89 80 23.2 24.1 7.9 3.3 1.7

29 16-22 31.8 25.6 7.8 1 91 71 23.4 23.6 8 4.7 2.4

30 23-29 30.7 25.1 43.6 1 90 70 22.3 21.6 7.9 4.1 3.4

31 30-05 31.2 25.2 48.7 3 86 69 21.3 21.2 10.4 4.6 4.6

32 Aug 06-12 30.8 24.7 36.6 1 94 73 23.2 23.7 4.8 3.1 2.5

33 13-19 31.7 25.3 126.4 3 94 73 24 24.2 7.5 4.7 4.1

34 20-26 32.3 25.9 23.6 1 87 65 22.6 22 8.1 5 6.5

35 27-02 30.8 25 37.9 6 94 80 23.5 24.7 4.9 2.5 1.2

36 Sep 03-09 33 25.5 10 1 93 64 23.7 21.5 4.7 3.9 6.9

37 10-16 33.5 25.4 68.4 2 93 62 23.9 22 3.8 4.7 6.8

38 17-23 30.1 25.1 135.4 2 94 78 23.6 24 5.8 2.6 3.1

39 24-30 32.5 24.6 0 0 92 57 22.3 20.2 3 3.8 7.2

40 Oct 01-07 33.7 24.4 0 0 92 51 22.7 19.3 2.4 4.4 7.7

41 08-14 33.9 22.2 0 0 89 47 19.5 17.9 3 4.3 8.7

42 15-21 33.4 22.8 0 0 91 45 20.2 16.7 2.4 3.8 8.7

43 22-28 33.7 21.3 0 0 90 37 18.5 13.8 2.1 3.6 8.2

44 29-04 30 19.4 0 0 90 55 16.6 16.4 4.1 3.2 6.7

45 Nov 05-11 31.7 18.8 0 0 91 37 15.8 12.4 2.6 3.5 7.8

46 12-18 31.7 16.3 0 0 89 33 13.3 11 2.4 3.3 7.5

47 19-25 30.6 15.5 0 0 88 36 12.6 11.3 2.8 3.3 8.3

48 26-02 31.9 16.7 0 0 87 34 13.4 11.6 2.4 3.3 7.5

49 Dec 03-09 31.2 14.8 0 0 88 31 12 10 2.3 3 8

50 10-16 30.1 17.3 4.4 1 77 46 12.2 13.6 2.9 2.7 4.4

51 17-23 27.7 16.6 9.4 1 85 52 13.1 13.3 3.1 2.3 2

52 24-31 26.9 10.8 0 0 87 29 9.1 7.4 2.4 2.6 6.2

191

Appendix B: Description of agro-morphological characters

S.

No.

Characteristics States Note Stage of

observation

Type of

assessment

1.

(+)

Coleoptile: Colour Colourless

Green

purple

1

2

3

10 VS

2

(*)

Basal leaf: Sheath Green Green

Light purple

Purple lines

Uniform purple

1

2

3

4

40 VS

3. Leaf: Intensity of

green colour

Light

Medium

dark

3

5

7

40 VG

4. Leaf: Anthocyanin

colourization

Absent

present

1

9

40 VG

5. Leaf: Distribution

of anthocyanin

Colouration

On tips only

On margins only

In blotches only

Uniform

1

2

3

4

40 VG

6.

(+)

Leaf Sheath: anthocyanin

Colouration

Absent

present

1

9

40 VG

7. Leaf sheath:

Intensity of

anthocyanin

Colouration

Very weak

Weak

Medium

Strong

Very strong

1

3

5

7

9

40 VG

8.

(*)

Leaf; pubescence of

blade surface

Absent

Weak

Medium

Strong

Very strong

1

3

5

7

9

40 VS

9

(*)

(+)

Leaf: Auricles Absent

Present

1

9

40 VS

10.

(*)

Leaf: Anthocyanin

colourization of auricles

Colourless

Light purple

purple

1

2

3

40 VS

11

(+)

.

Leaf: collar Absent

Present

1

9

40 VS

12. Leaf: Anthocyanin

colourization of collar

Absent

Present

1

9

40 VS

13.

(+)

Leaf: Ligule Absent

Present

1

9

40 VS

14.

(+)

(*)

Leaf: Shape of Ligule Truncate

Acute

Split

1

2

3

40 VS

15.

(*)

Leaf: Colour of Ligule White

Light purple

purple

1

2

3

40 VS

16. Leaf: length of blade Short(<30cm)

Medium(30-

40cm)

Long(>45cm)

3

5

7

40 MS

17. Leaf: Width of blade Narrow(<1cm) 3 40 MS

192

Medium(1-2cm)

Broad(>2cm)

5

7

18. Culm: Attitude (for

floating rice only)

Non procumbent

Procumbent

1

9

40 VS

19

(+)

.

Culm: Attitude Erect

Semi-erect

Open

spreading

1

3

5

7

40 VS

20

(*)

Time of heading (50%

plants with panicles)

Very early

Early

Medium

Late

Very late

1

3

5

7

9

55 VG

21

(*)

(+)

Flag leaf: attitude of

blade(early observation)

Erect

Semi-erect

Horizontal

Drooping

1

3

5

7

60 VG

22

(*)

Spikelet: Density of

pubescence of lemma

Absent

Weak

Medium

Strong

Very strong

1

3

5

7

9

60-80 VS

23 Male sterility Absent

Present

1

9

65 VG

24

(+)

Lemma: Anthocyanin

colouration of keel

Absent or very

weak

Weak

Medium

Strong

Very strong

1

3

5

7

9

65 VS

25

(+)

Lemma: Anthocyanin

colouration of area below

apex

Absent

Weak

Medium

Strong

Very strong

1

3

5

7

9

65 VS

26

(*)

(+)

Lemma: Anthocyanin

colouration of apex

Absent

Weak

Medium

Strong

Very strong

1

3

5

7

9

65 VS

27

(*)

(+)

Spikelet: colour of

stigma

White

Light green

Yellow

Light purple

purple

1

2

3

4

5

65 VS

28 Stem: Thickness Thin

Medium

Thick

3

5

7

70 MS

29

(*)

Stem: length Very short

Short

Medium

Long

Very long

1

3

5

7

9

70 70

30

(*)

Stem: Anthocyanin

colouration of nodes

Absent

Present

1

9

70 70


Anthocyanin colouration

Weak

Medium

3

5

70 70

193

of nodes strong 7


Anthocyanin colouration

of internodes

Absent

Present

1

9

70 70

33

(*)

(+)

Panicle: length of main

axis

Very short

Short

Medium

Long

Very long

1

3

5

7

9

70-90 MS

34

(*)

(+)

Flag leaf: Attitude of

blades

Erect

Semi-erect

Horizontal

Deflexed

1

3

5

7

90 VG

35

(*)

(+)

Panicle: Curvature of

main axis

Straight

Semi-Straight

Deflexed

Dropping

1

3

5

7

90 VG

36 Panicle: number per

plant

Few

Medium

many

3

5

7

80-90 MS

37

(*)

Spikelet: colour

of tip of lemma

White

Yellowish

Brown

Red

Purple

Black

1

2

3

4

5

6

80-90 VS

38

(+)

Lemma and palea: colour Straw

Gold and gold

furrows on straw

background

brown spots on

straw

1

2

3

80-90 VG

39

(*)

(+)

Panicle: Awns Absent

Present

1

9

90 VG

40

(*)

Panicle: colour of awns

(late observation)

Yellowish White

Yellowish brown

Brown

Reddish brown

Light red

Red

Light purple

Purple

Black

1

2

3

4

5

6

7

8

9

90 VS

41 Panicle: length of

longest Awns

Very short

Short

Medium

Long

Very long

1

3

5

7

9

90 VG-MS

42

(*)

Panicle: Distribution of

Awns

Tip only

Upper half only

Whole length

1

3

5

90 VS

43

(+)

Panicle: Presence of

secondary branching

Absent

Present

1

9

90 VG

194

44

(+)

Panicle: secondary

branching

Weak

Strong

clustered

1

2

3

90 VG

45

(+)

(*)

Panicle: attitude of

branches

Erect

Erect to semi

erect

Semi-erect

Semi erect to

spreading

spreading

1

3

5

7

9

90 VG

46

(*)

(+)

Panicle: Exertion Partly exerted

Mostly exerted

Well exerted

3

5

7

90 VG

47 Time maturity(days) Very early

Early

Medium

Late

Very late

1

3

5

7

9

90 VG

48 Leaf: Senescence Early

medium

late

3

5

7

92 VG

49

(*)

(+)

Sterile lemma: colour Straw

Gold

Red

purple

1

2

3

4

92 VS

50 Grain: Weight of 1000

fully developed grains

Very low

Low

Medium

High

very high

1

3

5

7

9

92 MG

51

(+)

Grain: Length Very short

Short

Medium

Long

Very long

1

3

5

7

9

92 MS

52 Grain: Width Very narrow

Narrow

Medium

Broad

Very broad

1

3

5

7

9

92 MS

53

(+)

Grain: Phenol reaction of

lemma

Absent

Present

1

9

92 VG

54

(*)

(+)

Decorticated grain:

length

Short

Medium

Long

Extra long

1

3

5

9

92 MS

55

(*)

(+)

Decorticated grain: width Narrow

Medium

broad

3

5

7

92 MS

56

(*)

(+)

Decorticated grain:

shape(in lateral view)

Short slender

Short bold

Medium slender

Long bold

Long slender

Extra Long

slender

1

2

3

4

5

6

92 MS

57 Decorticated grain: White 1 92 VG

195

(*) colour Light brown

Variegated brown

Dark brown

Light red

Red

Variegated

purple

Purple

Dark purple

2

3

4

5

6

7

8

9

58

(+)

Endosperm: presence of

amylose

Absent

Present

1

9

92 MG

59

(*)

(+)

Endosperm: content of

amylose

Very low

Low

Medium

High

very high

1

3

5

7

9

92 MG

60

(+)

Varieties with

endosperm of amylose

absent only polished

grain: Expressed of white

core

Absent or very

small

Small

Medium

Large

Fully chalky

1

3

5

7

9

90 MG

61

(+)

Gelatinization

temperature through

alkali spreading value

low

Medium

High

Medium

High

1

3

5

7

92 MG

62

(*)

(+)

Decorticated grain:

Aroma

Absent

Present

1

9

92 MG

196

Appendix C(i) : Agromorphological characters studied in short (24) and long (24) grain germplasm of rice

CGR

no.

IC No. Name Source (Village/

Block/Distt.)

Coleoptile

colour

Basal

leaf:

Sheath

colour

Leaf:

Intesity

of

green

colour

Leaf:

Anthocyanin

colouration

Leaf:

Distribution

of

Anthocyanin

colouration

Leaf

sheath:

anthocyanin

colouration

Leaf

sheath:Intensity

of anthocyanin

colourarion

Leaf:

Pubescence

of blade

surface

10031 116093 Lokti Machhi Bade Rajpur/Bade Rajpur/

Bastar

Green Green Medium Absent Absent Absent Absent Medium

10036 116098 Atma Sital Antagarh/Antagarh/ Bastar Green Green Medium Absent Absent Absent Absent Medium

10029 116091 Lokti Machhi Narayanpur/

Narayanpur/Bastar


1686 132619 ADT:27 Rajim/Fingeshwar/ Raipur Purple Green Medium Absent Absent Absent Absent Medium

1829 132767 Anjania Pandarbhattha/

Bemetara/Durg

Purple Purple

Line

Medium Absent Absent Absent Absent Medium

2845 NA Kanak Jira Dadesara/Durg/Durg Purple Purple

Line


2890 134280 Jhumera Martara/Bemetara/ Durg Purple Purple

Line

Medium Absent Absent Absent Absent Weak

2947 134337 Kakeda (I) Kuamalji/Pandariya/Bilaspur Green Green Medium Absent Absent Absent Absent Medium

6475 125708 Dubraj II Chandkhuri/Arang/ Raipur Green Green Medium Absent Absent Absent Absent Weak

2300 133269 Bhulau Gidhpuri/Palari/ Raipur Purple Green Medium Absent Absent Absent Absent Medium

2929 134319 Rani kajar Garra/Palari/Raipur Green Green Medium Absent Absent Absent Absent Medium

3870 135260 Sundar mani Kodohatha/Deobhog/Raipur Purple Green Medium Absent Absent Absent Absent Medium

5855 NA Bhado kanker Turanga/Pusaur/ Raigarh Green Green Medium Absent Absent Absent Absent Weak

2888 134278 Jhumarwa Charbhatha/

Fingeshwar/Raipur

Green Green Medium Absent Absent Absent Absent Weak

6062 114188 Bishnu Bishnupur/

Baikundpur/Sarguja


512 123552 Basa Bhog Pratappur/Pratappur/Sarguja Green Green Dark

Green

Absent Absent Absent Absent Weak

5375 124958 Krishna Bhog Mohgaon/Mandla/ Mandla Green Green Medium Absent Absent Absent Absent Medium

7087 NA Hira Nakhi Khekha/Bichhiya/ Mandla Green Green Medium Absent Absent Absent Absent Medium

197

10032 116094 Lokti Maudi Abujhmad/Abujhmad/Bastar Green Green Medium Absent Absent Absent Absent Medium

6069 NA Kariya bodela

bija

Kodo/Abujhmad/ Bastar Green Green Medium Absent Absent Absent Absent Medium

6688 125922 Gganja Kali Kudum Kala/Ghar

Ghoda/Raigarh


5528 125109 Banas KupiII Jhilwada/Waraseoni/Balagha

t


6444 125677 Dhangari

Khusha

Darrabhatha/Saraipali/Raipur Green Green Medium Absent Absent Absent Absent Hard

6446 125679 Bhaniya Fashakar/Durgkondal/Bastar Green Green Medium Absent Absent Absent Absent Weak

6637 125871 Farsa phool Koyalibeda/

Koyalibeda/Bastar

Green Purple

Line


7125 114272 Jay Bajrang Fingeshwar/

Fingeshwar/Raipur

Green Purple

Line


6726 125960 Gilas Enhoor/Durgkondal/Bastar Green Green Medium Absent Absent Absent Absent Medium

7615 NA Khatia pati Odan/Palari/Raipur Purple Purple

Line


8421 114979 Mani Rajim/Rajim/Raipur Green Green Dark

Green

Absent Absent Absent Absent Weak

7539 NA Khatriya pati Odan/Palari/Raipur Green Purple

Line


6729 NA Girmit Kokodi/Kirnapur/ Balaghat Green Green Medium Absent Absent Absent Absent Medium

7960 NA Lanji Deverda/Baldevgarh/Tikamg

arh

Green Green Dark

Green

Absent Absent Absent Absent Strong

5772 114018 Banreg Khutgaon/Deobhog/Raipur Purple Purple

Line

Dark

Green


9209 NA Ruchi Kusumi/Kusumi/ Sarguja Green Green Dark

Green


8187 NA Safed luchai Nagajhare/Barghat/ Seoni Green Green Medium Absent Absent Absent Absent Medium

3090 134480 Kanthi deshi Vijaipali/Barghat/ Seoni Purple Purple

Line


9068 NA Piso III Barghat/Barghat/ Seoni Green Green Medium Absent Absent Absent Absent Medium

7301 114358 Kakdi Kukanar/Darma/ Bastar Green Purple

Line


6656 125890 Gajpati Kosamghat/Ghar

Ghoda/Bastar

Purple Purple

Line


198

6650 125884 Gadur sela NA/Mohala/ Rajnandgaon Green Green Medium Absent Absent Absent Absent Weak

5103 124686 Aadan chilpa Kesherpal/Bastar/ Bastar Green Purple

Line


5078 214553 Unknown NA/NA/NA(CG) Green Green Medium Absent Absent Absent Absent Medium

9420 115695 Saja chhilau Kanker/Kanker/ Bastar Green Purple

Line

Medium Absent Absent Absent Absent Strong

9395 NA Parmal Safri Tilda/Tilda/Raipur Green Purple

Line


9254 115573 Safri Varasioni/Waraseoni/Balagh

at

Green Green Medium Absent Absent Absent Absent Strong

8711 NA Narved Muraina/NA/Muraina Green Green Medium Absent Absent Absent Absent Medium

8673 NA Nagbel Dev Bhog/Devbhog /Raipur Green Purple

Line


8558 115101 Mudariya Abhanpur/Abhanpur/Raipur Green Purple

Line


199

Appendix C (ii): Agromorphological characters studied in short (24) and long (24) grain germplasm of rice

CGR

no.


Block/Distt.)

Leaf:

Auricles

Leaf:

Anthocyanin

colouration

of auricles

Leaf:

Collar

Leaf:

Anthocyanin

colouration

of collar

Leaf:

Ligule

Leaf:

Shape of

Ligule

Leaf:

Colour of

ligule


Bastar

Present Colourless Present Absent Present Split White

10036 116098 Atma Sital Antagarh/Antagarh/ Bastar Present Colourless Present Absent Present Split White


Narayanpur/Bastar


1686 132619 ADT:27 Rajim/Fingeshwar/ Raipur Present Colourless Present Absent Present Split White


Bemetara/Durg

Present Colourless Present Present Present Split White

2845 NA Kanak Jira Dadesara/Durg/Durg Present Colourless Present Present Present Split White

2890 134280 Jhumera Martara/Bemetara/ Durg Present Colourless Present Absent Present Split White

2947 134337 Kakeda (I) Kuamalji/Pandariya/Bilasp

ur


6475 125708 Dubraj II Chandkhuri/Arang/ Raipur Present Colourless Present Absent Present Split White

2300 133269 Bhulau Gidhpuri/Palari/ Raipur Present Colourless Present Absent Present Acute White

2929 134319 Rani kajar Garra/Palari/Raipur Present Colourless Present Absent Present Split White

3870 135260 Sundar mani Kodohatha/Deobhog/

Raipur


5855 NA Bhado kanker Turanga/Pusaur/ Raigarh Present Colourless Present Absent Present Split White


Fingeshwar/Raipur



Baikundpur/Sarguja

Present Colourless Present Absent Present Acute White

512 123552 Basa Bhog Pratappur/Pratappur/

Sarguja


5375 124958 Krishna Bhog Mohgaon/Mandla/ Mandla Present Colourless Present Absent Present Split White

7087 NA Hira Nakhi Khekha/Bichhiya/ Mandla Present Colourless Present Absent Present Split White

10032 116094 Lokti Maudi Abujhmad/Abujhmad/ Present Colourless Present Absent Present Split White

200

Bastar


bija

Kodo/Abujhmad/ Bastar Present Colourless Present Absent Present Split White


Ghoda/Raigarh

Present Colourless Present Absent Present Acute White

5528 125109 Banas KupiII Jhilwada/Waraseoni/

Balaghat


6444 125677 Dhangari Khusha Darrabhatha/Saraipali/

Raipur


6446 125679 Bhaniya Fashakar/Durgkondal/

Bastar



Koyalibeda/Bastar



Fingeshwar/Raipur

Present Colourless Present Present Present Split White

6726 125960 Gilas Enhoor/Durgkondal/Bastar Present Colourless Present Absent Present Split White

7615 NA Khatia pati Odan/Palari/Raipur Present Colourless Present Absent Present Split White

8421 114979 Mani Rajim/Rajim/Raipur Present Colourless Present Absent Present Split White

7539 NA Khatriya pati Odan/Palari/Raipur Present Colourless Present Absent Present Split White

6729 NA Girmit Kokodi/Kirnapur/ Balaghat Present Colourless Present Absent Present Split White

7960 NA Lanji Deverda/Baldevgarh/

Tikamgarh


5772 114018 Banreg Khutgaon/Deobhog/Raipur Present Colourless Present Absent Present Split White

9209 NA Ruchi Kusumi/Kusumi/ Sarguja Present Colourless Present Absent Present Split White

8187 NA Safed luchai Nagajhare/Barghat/ Seoni Present Colourless Present Absent Present Split White

3090 134480 Kanthi deshi Vijaipali/Barghat/ Seoni Present Colourless Present Absent Present Split White

9068 NA Piso III Barghat/Barghat/ Seoni Present Colourless Present Absent Present Split White

7301 114358 Kakdi Kukanar/Darma/ Bastar Present Colourless Present Absent Present Split White


Ghoda/Bastar


6650 125884 Gadur sela NA/Mohala/ Rajnandgaon Present Colourless Present Absent Present Split White

5103 124686 Aadan chilpa Kesherpal/Bastar/ Bastar Present Colourless Present Absent Present Split White

201

5078 214553 Unknown NA/NA/NA(CG) Present Colourless Present Absent Present Split White

9420 115695 Saja chhilau Kanker/Kanker/ Bastar Present Light Purple Present Absent Present Split White

9395 NA Parmal Safri Tilda/Tilda/Raipur Present Colourless Present Absent Present Split White

9254 115573 Safri Varasioni/Waraseoni/

Balaghat


8711 NA Narved Muraina/NA/Muraina Present Colourless Present Absent Present Split White

8673 NA Nagbel Dev Bhog/Devbhog /Raipur Present Colourless Present Absent Present Split White

8558 115101 Mudariya Abhanpur/Abhanpur/Raipur Present Light Purple Present Present Present Split White

202

Appendix-C (iii): Agromorphological characters studied in short (24) and long (24) grain germplasm of rice

CGR

no.


Block/Distt.)

Leaf:

Length

of

blade

Leaf:

Width

of

blade

Culm:

Attitude

(For

floating

rice only)

Culm:

Attitude

Flag leaf:

Attitude of

blade(Early

observation)

Spikelet:

Density of

pubescence

of lemma

Male

sterility

Lemma:

Anthocyanin

colouration

of keel

Lemma:

Anthocyanin

colouration

of area

below apex


Bastar

Medium Narrow Absent Erect Erect Weak Absent Strong Medium

10036 116098 Atma Sital Antagarh/Antagarh/ Bastar Medium Narrow Absent Erect Erect Medium Absent Absent Absent


Narayanpur/Bastar

Medium Narrow Absent Erect Erect Weak Absent Strong Strong

1686 132619 ADT:27 Rajim/Fingeshwar/ Raipur Medium Narrow Absent Erect Erect Medium Absent Weak Absent


Bemetara/Durg

Short Narrow Absent Semi

erect

Erect Strong Absent Medium Weak

2845 NA Kanak Jira Dadesara/Durg/Durg Medium Narrow Absent Erect Erect Medium Absent Absent Absent

2890 134280 Jhumera Martara/Bemetara/ Durg Medium Narrow Absent Erect Erect Strong Absent Very weak Absent

2947 134337 Kakeda (I) Kuamalji/Pandariya/Bilaspur Long Narrow Absent Erect Erect Very strong Absent Absent Absent

6475 125708 Dubraj II Chandkhuri/Arang/ Raipur Medium Narrow Absent Erect Erect Medium Absent Absent Absent

2300 133269 Bhulau Gidhpuri/Palari/ Raipur Medium Narrow Absent Semi

erect

Erect Strong Absent Strong Strong

2929 134319 Rani kajar Garra/Palari/Raipur Medium Narrow Absent Erect Erect Strong Absent Strong Strong

3870 135260 Sundar mani Kodohatha/Deobhog/ Raipur Short Narrow Absent Semi

erect

Erect Strong Absent Strong Strong

5855 NA Bhado kanker Turanga/Pusaur/ Raigarh Medium Narrow Absent Erect Erect Strong Absent Strong Absent


Fingeshwar/Raipur

Short Narrow Absent Semi

erect

Erect Medium Absent Strong Strong


Baikundpur/Sarguja

Medium Narrow Absent Erect Erect Strong Absent Absent Absent

512 123552 Basa Bhog Pratappur/Pratappur/ Sarguja Medium Narrow Absent Erect Semi erect Medium Absent Weak Weak

5375 124958 Krishna Bhog Mohgaon/Mandla/ Mandla Short Narrow Absent Erect Erect Medium Absent Weak Absent

7087 NA Hira Nakhi Khekha/Bichhiya/ Mandla Medium Narrow Absent Semi

erect

Erect Strong Absent Weak Weak

203

10032 116094 Lokti Maudi Abujhmad/Abujhmad/

Bastar

Medium Narrow Absent Erect Erect Weak Absent Strong Medium


bija

Kodo/Abujhmad/ Bastar Medium Narrow Absent Semi

erect

Erect Weak Absent Strong Strong


Ghoda/Raigarh

Medium Narrow Absent Semi

erect

Erect Medium Absent Absent Absent


Balaghat


erect



Khusha

Darrabhatha/Saraipali/

Raipur


erect

Erect Strong Absent Weak Weak

6446 125679 Bhaniya Fashakar/Durgkondal/ Bastar Medium Narrow Absent Erect Semi erect Medium Absent Weak Absent


Koyalibeda/Bastar


erect

Erect Very strong Absent Very strong Very strong


Fingeshwar/Raipur

Medium Narrow Absent Erect Erect Medium Absent Very strong Very strong

6726 125960 Gilas Enhoor/Durgkondal/Bastar Medium Narrow Absent Erect Erect Medium Absent Absent Absent

7615 NA Khatia pati Odan/Palari/Raipur Medium Narrow Absent Erect Erect Strong Absent Very strong Very strong

8421 114979 Mani Rajim/Rajim/Raipur Medium Narrow Absent Semi

erect

Semi erect Strong Absent Absent Absent

7539 NA Khatriya pati Odan/Palari/Raipur Medium Narrow Absent Spreding Erect Medium Absent Very strong Very strong

6729 NA Girmit Kokodi/Kirnapur/ Balaghat Medium Narrow Absent Erect Erect Strong Absent Absent Absent


Tikamgarh

Long Narrow Absent Erect Erect Medium Absent Absent Absent

5772 114018 Banreg Khutgaon/Deobhog/Raipur Long Narrow Absent Semi

erect

Erect Strong Absent Absent Absent

9209 NA Ruchi Kusumi/Kusumi/ Sarguja Long Narrow Absent Erect Semi erect Medium Absent Very strong Very strong

8187 NA Safed luchai Nagajhare/Barghat/ Seoni Medium Narrow Absent Erect Semi erect Medium Absent Absent Absent

3090 134480 Kanthi deshi Vijaipali/Barghat/ Seoni Medium Narrow Absent Semi

erect


9068 NA Piso III Barghat/Barghat/ Seoni Medium Narrow Absent Semi

erect


7301 114358 Kakdi Kukanar/Darma/ Bastar Medium Narrow Absent Semi

erect

Semi erect Medium Absent Absent Absent


Ghoda/Bastar

Medium Narrow Absent Erect Erect Medium Absent Absent Absent

204

6650 125884 Gadur sela NA/Mohala/ Rajnandgaon Medium Narrow Absent Erect Erect Medium Absent Absent Absent

5103 124686 Aadan chilpa Kesherpal/Bastar/ Bastar Medium Narrow Absent Erect Erect Strong Absent Strong Very strong

5078 214553 Unknown NA/NA/NA(CG) Medium Narrow Absent Erect Semi erect Very strong Absent Absent Absent

9420 115695 Saja chhilau Kanker/Kanker/ Bastar Medium Narrow Absent Erect Semi erect Very strong Absent Absent Absent

9395 NA Parmal Safri Tilda/Tilda/Raipur Medium Narrow Absent Spreding Erect Weak Absent Absent Weak


Balaghat

Medium Narrow Absent Erect Erect Strong Absent Absent Absent

8711 NA Narved Muraina/NA/Muraina Medium Narrow Absent Erect Erect Medium Absent Absent Absent

8673 NA Nagbel Dev Bhog/Devbhog /Raipur Medium Narrow Absent Erect Erect Very strong Absent Very strong Very strong

8558 115101 Mudariya Abhanpur/Abhanpur/Raipur Medium Narrow Absent Spreding Erect Very strong Absent Very strong Very strong

205

Appendix C (iv): Agromorphological characters studied in short (24) and long (24) grain germplasm of rice

CGR

no.


Block/Distt.)

Lemma:

Anthocyanin

colouration

of apex

Spikelet:

colour

of

stigma

Stem:

Thickness

Stem:

Length(exc

luding

panicle)

Stem:

Anthocyanin

colouration of

nodes

Stem:

Intensity of

anthocyanin

colouration

of nodes

Stem:

Anthocyanin

colouration

of internode

Flag leaf:

Attitude of

blade(Late

observation)


Bastar

Medium White Medium Long Absent Absent Absent Erect

10036 116098 Atma Sital Antagarh/Antagarh/

Bastar

Absent White Medium Medium Absent Absent Absent Erect


Narayanpur/Bastar


1686 132619 ADT:27 Rajim/Fingeshwar/ Raipur Absent Purple Medium Very Short Present Medium Present Erect


Bemetara/Durg

Weak Purple Thick Short Present Medium Present Horizontal

2845 NA Kanak Jira Dadesara/Durg/Durg Absent Purple Medium Medium Present Medium Present Horizontal

2890 134280 Jhumera Martara/Bemetara/ Durg Absent Purple Medium Medium Present Medium Present Desceading

2947 134337 Kakeda (I) Kuamalji/Pandariya/

Bilaspur

Absent White Medium Long Present Medium Present Erect

6475 125708 Dubraj II Chandkhuri/Arang/ Raipur Absent White Thin Medium Absent Absent Absent Erect

2300 133269 Bhulau Gidhpuri/Palari/ Raipur Strong Purple Medium Medium Present Medium Present Horizontal

2929 134319 Rani kajar Garra/Palari/Raipur Strong White Thin Medium Present Medium Present Erect


Raipur

Absent Purple Thin Medium Present Medium Present Horizontal

5855 NA Bhado kanker Turanga/Pusaur/ Raigarh Strong White Medium Long Present Medium Present Erect


Fingeshwar/Raipur

Strong White Medium Long Present Medium Present Erect


Baikundpur/Sarguja

Absent White Medium Long Absent Absent Present Erect


Sarguja

Weak White Medium Very Short Present Medium Present Erect

5375 124958 Krishna Bhog Mohgaon/Mandla/ Mandla Absent White Medium Long Present Medium Present Erect

7087 NA Hira Nakhi Khekha/Bichhiya/ Mandla Weak White Medium Long Present Medium Present Erect

206


Bastar

Strong Purple Medium Long Present Medium Present Erect


bija

Kodo/Abujhmad/ Bastar Strong White Thick Long Absent Absent Absent Erect


Ghoda/Raigarh

Absent White Medium Long Present Medium Present Horizontal


Balaghat

Absent White Medium Medium Present Medium Present Horizontal


Khusha

Darrabhatha/Saraipali/

Raipur



Bastar

Absent White Medium Medium Present Medium Present Horizontal


Koyalibeda/Bastar

Very strong Purple Medium Long Present Medium Present Erect


Fingeshwar/Raipur

Very strong White Thick Very Long Present Strong Present Horizontal

6726 125960 Gilas Enhoor/Durgkondal/

Bastar

Absent White Medium Long Present Medium Present Horizontal

7615 NA Khatia pati Odan/Palari/Raipur Very strong White Medium Very Long Absent Absent Absent Horizontal

8421 114979 Mani Rajim/Rajim/Raipur Absent Purple Medium Long Absent Absent Absent Horizontal

7539 NA Khatriya pati Odan/Palari/Raipur Very strong White Medium Very Long Present Medium Present Erect

6729 NA Girmit Kokodi/Kirnapur/

Balaghat

Weak Purple Thick Long Absent Absent Absent Horizontal


Tikamgarh

Absent White Medium Very Long Absent Absent Absent Erect

5772 114018 Banreg Khutgaon/Deobhog/

Raipur

Absent Purple Medium Very Long Present Medium Present Erect

9209 NA Ruchi Kusumi/Kusumi/ Sarguja Very strong White Thick Very Long Absent Absent Absent Erect

8187 NA Safed luchai Nagajhare/Barghat/ Seoni Absent White Medium Very Long Absent Absent Absent Horizontal

3090 134480 Kanthi deshi Vijaipali/Barghat/ Seoni Absent Purple Medium Long Present weak Present Horizontal

9068 NA Piso III Barghat/Barghat/ Seoni Absent White Thick Very Long Absent Absent Absent Horizontal

7301 114358 Kakdi Kukanar/Darma/ Bastar Absent White Medium Long Absent Absent Absent Erect


Ghoda/Bastar

Absent Purple Medium Very Long Present Medium Present Horizontal

207

6650 125884 Gadur sela NA/Mohala/ Rajnandgaon Absent White Medium Long Absent Absent Absent Erect

5103 124686 Aadan chilpa Kesherpal/Bastar/ Bastar Very strong White Medium Very Long Absent Absent Absent Erect

5078 214553 Unknown NA/NA/NA(CG) Absent White Medium Very Long Absent Absent Absent Semi erect

9420 115695 Saja chhilau Kanker/Kanker/ Bastar Absent White Medium Very Long Absent Absent Absent Erect

9395 NA Parmal Safri Tilda/Tilda/Raipur Weak White Medium Very Long Absent Absent Absent Erect


Balaghat

Absent White Medium Very Long Absent Absent Absent Erect

8711 NA Narved Muraina/NA/Muraina Absent White Medium Very Long Absent Absent Absent Erect

8673 NA Nagbel Dev Bhog/Devbhog

/Raipur

Very strong White Medium Very Long Absent Absent Absent Horizontal

8558 115101 Mudariya Abhanpur/Abhanpur/

Raipur

Very strong Purple Medium Very Long Present Medium Present Horizontal

208

Appendix C (v): Agromorphological characters studied in short and long grain accessions of rice

CGR

no.


Block/Distt.)

Panicle:

Curvature of

main axis

Spikelet:

Colour of tip

of lemma

Lemma and Palea

colour

Panicle:Awns Panicle:

Colour of

awns (late

observation)

Panicle:

Length of

longest awn


Bastar

Semi straight Purple Purple furrows on

straw

Absent Absent Absent


Bastar

Semi straight Yellow Straw Absent Absent Absent


Narayanpur/Bastar

Semi straight Black Purple furrows on

straw


1686 132619 ADT:27 Rajim/Fingeshwar/ Raipur Straight Brown Straw Absent Absent Absent


Bemetara/Durg

Straight Black Brown furrows on

straw


2845 NA Kanak Jira Dadesara/Durg/Durg Semi straight Black Brown furrows on

straw


2890 134280 Jhumera Martara/Bemetara/ Durg Semi straight Brown Brown furrows on

straw



Bilaspur

Semi straight Yellow Brown furrows on

straw


6475 125708 Dubraj II Chandkhuri/Arang/ Raipur Semi straight Yellow Brown spot on

straw


2300 133269 Bhulau Gidhpuri/Palari/ Raipur Semi straight Brown Red Absent Absent Absent

2929 134319 Rani kajar Garra/Palari/Raipur Semi straight Brown Red Absent Absent Absent


Raipur

Straight Brown Brown furrows on

straw


5855 NA Bhado kanker Turanga/Pusaur/ Raigarh Semi straight Brown Red Absent Absent Absent


Fingeshwar/Raipur

Semi straight Brown Reddish to light

purple



Baikundpur/Sarguja

Straight Yellow Gold and gold

furrows on straw

background



Sarguja

Semi straight Yellow Straw Absent Absent Absent

5375 124958 Krishna Bhog Mohgaon/Mandla/ Mandla Straight Black Straw Absent Absent Absent

209

7087 NA Hira Nakhi Khekha/Bichhiya/ Mandla Straight Brown Gold and gold

furrows on straw

background



Bastar

Semi straight Purple Purple furrows on

straw


6069 NA Kariya bodela bija Kodo/Abujhmad/ Bastar Semi straight Purple Brown Absent Absent Absent


Ghoda/Raigarh

Straight Yellow Straw Absent Absent Absent


Balaghat

Straight Yellow Straw Absent Absent Absent


Raipur

Straight Yellow Brown furrows on

straw



Bastar

Straight Brown Straw Absent Absent Absent


Koyalibeda/Bastar

Deflexed Brown Red Present Red Short


Fingeshwar/Raipur

Semi straight Red Red Present Red Short


Bastar

Deflexed Yellow Straw Present Yellowish

white

Short

7615 NA Khatia pati Odan/Palari/Raipur Deflexed Red Straw Present Yellowish

white

Long

8421 114979 Mani Rajim/Rajim/Raipur Semi straight Yellow Straw Present Yellowish

white

Medium

7539 NA Khatriya pati Odan/Palari/Raipur Semi straight Brown Straw Present Red Medium


Balaghat


white

Medium


Tikamgarh


white

Medium


Raipur


white

Short

9209 NA Ruchi Kusumi/Kusumi/ Sarguja Deflexed Yellow Red Present Brown Short

8187 NA Safed luchai Nagajhare/Barghat/ Seoni Deflexed Yellow Straw Absent Absent Absent

3090 134480 Kanthi deshi Vijaipali/Barghat/ Seoni Semi straight Yellow Straw Present Yellowish

white

Medium

9068 NA Piso III Barghat/Barghat/ Seoni Semi straight Yellow Straw Present Yellowish Medium

210

white

7301 114358 Kakdi Kukanar/Darma/ Bastar Semi straight White Straw Present Yellowish

white

Short


Ghoda/Bastar

Semi straight Yellow Straw Present Yellowish

white

Medium

6650 125884 Gadur sela NA/Mohala/ Rajnandgaon Deflexed Yellow Straw Present Yellowish

white

Short

5103 124686 Aadan chilpa Kesherpal/Bastar/ Bastar Deflexed White Reddish to light

purple


5078 214553 Unknown NA/NA/NA(CG) Semi straight White Straw Absent Absent Absent

9420 115695 Saja chhilau Kanker/Kanker/ Bastar Semi straight White Gold and gold

furrows on straw

Present Yellowish

white

Short

9395 NA Parmal Safri Tilda/Tilda/Raipur Semi straight Yellow Straw Present Yellowish

white

Short


Balaghat

Semi straight Yellow Straw Present Yellowish

white

Short

8711 NA Narved Muraina/NA/Muraina Deflexed White Straw Absent Absent Absent


/Raipur

Deflexed Red Red Present Red Short


Raipur

Deflexed Red Red Present Red Short

211

AppendixC (vi): Agromorphological characters studied in short (24) and long (24) grain germplasm of rice

CGR

no.


Block/Distt.)

Panicle:

Distribu

tion of

awns

Panicle:

Presence of

secondery

branching

Panicle:

Secondery

branching

Panicle:

Attitude

of

branches

Panicle:

Exertion

Time

Maturity

(Days)

Leaf:

senescence

Sterile

lemma:

Colour


Bastar

Absent Present Strong Spreading Mostly exerted Late Medium Purple


Bastar

Absent Present Strong Spreading Well exerted Late Medium Straw


Narayanpur/Bastar

Absent Present Strong Semi erect

to

spreding

Mostly exerted Late Medium Purple

1686 132619 ADT:27 Rajim/Fingeshwar/ Raipur Absent Present Weak Erect to

semi erect

Mostly exerted Early Early Gold


Bemetara/Durg

Absent Present Strong Spreading Well exerted Medium Early Straw

2845 NA Kanak Jira Dadesara/Durg/Durg Absent Present Cluster Spreading Mostly exerted Medium Early Straw

2890 134280 Jhumera Martara/Bemetara/ Durg Absent Present Cluster Semi erect Mostly exerted Medium Early Straw


Bilaspur

Absent Present Cluster Semi erect Mostly exerted Medium Early Straw

6475 125708 Dubraj II Chandkhuri/Arang/ Raipur Absent Present Cluster Erect to

semi erect

Mostly exerted Late Medium Straw

2300 133269 Bhulau Gidhpuri/Palari/ Raipur Absent Present Strong Erect to

semi erect

Mostly exerted Medium Early Straw

2929 134319 Rani kajar Garra/Palari/Raipur Absent Present Cluster Spreading Partly exerted Medium Medium Straw


Raipur

Absent Present Cluster Spreading Mostly exerted Medium Early Gold

5855 NA Bhado kanker Turanga/Pusaur/ Raigarh Absent Present Strong Semi erect Well exerted Medium Medium Straw


Fingeshwar/Raipur

Absent Present Weak Erect to

semi erect

Mostly exerted Medium Medium Gold


Baikundpur/Sarguja

Absent Present Cluster Semi erect Well exerted Medium Medium Straw


Sarguja

Absent Present Weak Erect to

semi erect

Well exerted Early Medium Straw

212

5375 124958 Krishna Bhog Mohgaon/Mandla/ Mandla Absent Present Strong Erect to

semi erect

Mostly exerted Medium Medium Gold

7087 NA Hira Nakhi Khekha/Bichhiya/ Mandla Absent Present Strong Semi erect

to

spreding

Mostly exerted Medium Medium Straw


Bastar

Absent Present Strong Semi erect

to

spreding

Well exerted Medium Medium Purple

6069 NA Kariya bodela bija Kodo/Abujhmad/ Bastar Absent Present Weak Semi erect Partly exerted Medium Medium Purple


Ghoda/Raigarh

Absent Present Weak Semi erect Mostly exerted Medium Medium Gold


Balaghat

Absent Present Strong Erect to

semi erect

Mostly exerted Medium Medium Yellow


Raipur

Absent Present Cluster Semi erect Well exerted Medium Medium Gold


Bastar

Absent Present Weak Semi erect Mostly exerted Medium Medium Gold


Koyalibeda/Bastar

Tip only Present Weak Erect to

semi erect

Mostly exerted Late Medium Red


Fingeshwar/Raipur

Tip only Present Weak Erect to

semi erect

Well exerted Late Medium Gold


Bastar

Tip only Present Weak Semi erect Well exerted Late Medium Straw

7615 NA Khatia pati Odan/Palari/Raipur Tip only Present Cluster Erect to

semi erect

Mostly exerted Late Medium Straw

8421 114979 Mani Rajim/Rajim/Raipur Tip only Present Strong Erect Well exerted Late Medium Straw

7539 NA Khatriya pati Odan/Palari/Raipur Tip only Present Weak Spreding Mostly exerted Late Medium Gold


Balaghat

Tip only Present Strong Spreding Well exerted Late Medium Gold


Tikamgarh

Tip only Present Weak Spreding Well exerted Late Medium Gold


Raipur

Tip only Present Weak Semi erect Well exerted Late Medium Gold

9209 NA Ruchi Kusumi/Kusumi/ Sarguja Tip only Present Cluster Spreding Mostly exerted Late Medium Straw

8187 NA Safed luchai Nagajhare/Barghat/ Seoni Absent Present Weak Semi erect Well exerted Late Medium Straw

3090 134480 Kanthi deshi Vijaipali/Barghat/ Seoni Tip only Present Weak Erect Mostly exerted Late Early Straw

213

9068 NA Piso III Barghat/Barghat/ Seoni Tip only Present Strong Spreding Mostly exerted Late Medium Straw

7301 114358 Kakdi Kukanar/Darma/ Bastar Tip only Present Weak Spreding Well exerted Late Medium Straw


Ghoda/Bastar

Tip only Present Weak Spreding Well exerted Late Medium Straw

6650 125884 Gadur sela NA/Mohala/ Rajnandgaon Tip only Present Strong Spreding Well exerted Late Medium Gold

5103 124686 Aadan chilpa Kesherpal/Bastar/ Bastar Absent Present Weak Semi erect Well exerted Late Medium Straw

5078 214553 Unknown NA/NA/NA(CG) Absent Present Weak Semi erect Mostly exerted Late Early Straw

9420 115695 Saja chhilau Kanker/Kanker/ Bastar Tip only Present Strong Semi erect

to

spreading

Well exerted Late Medium Straw

9395 NA Parmal Safri Tilda/Tilda/Raipur Tip only Present Strong Erect to

semi erect

Well exerted Late Medium Gold


Balaghat

Tip only Present Cluster Spreding Well exerted Late Medium Straw

8711 NA Narved Muraina/NA/Muraina Absent Present Weak Erect Well exerted Late Medium Straw


/Raipur

Tip only Present Weak Erect Mostly exerted Late Medium Gold


Raipur

Tip only Present Weak Erect Well exerted Late Medium Straw

214

Appendix D1: Mean performance of 33 yield and quality traits of 48 (24 short and 24 long grains length) rice germplasm

accessions S.

No.

CGR

No.

IC No. Name 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

1 10031 116093 Lokti

Machhi

33.55 0.75 121.50 0.40 137.40 22.05 159.45 6.21 0.00 149.50 10.65 5.65 2.30 26.46 3.85 2.30 0.60

2 10036 116098 Atma Sital 34.85 0.50 125.50 0.40 130.30 22.40 152.70 6.38 0.00 155.50 11.50 5.70 2.15 27.28 4.35 2.35 0.50

3 10029 116091 Lokti

Machhi

34.90 0.70 126.00 0.45 134.50 21.05 155.55 6.80 0.00 154.00 12.25 5.25 2.25 29.45 4.00 1.80 0.56

4 1686 132619 ADT:27 34.50 0.70 91.00 0.45 82.20 20.80 103.00 8.72 0.00 119.00 15.60 6.25 2.75 19.05 4.15 2.30 0.66

5 1829 132767 Anjania 29.30 0.75 113.00 0.65 100.70 19.60 120.30 8.93 0.00 141.00 16.45 5.85 2.40 24.11 4.15 2.95 0.58

6 2845 NA Kanak Jira 31.15 0.65 102.50 0.45 114.80 21.20 136.00 8.45 0.00 130.50 16.30 6.05 2.65 21.58 4.25 1.95 0.62

7 2890 134280 Jhumera 33.75 0.70 102.00 0.50 120.70 20.30 141.00 8.72 0.00 132.00 15.15 5.75 2.45 22.96 4.00 2.85 0.61

8 2947 134337 Kakeda (I) 47.00 0.75 99.50 0.40 135.50 22.15 157.65 8.06 0.00 129.50 13.50 5.80 2.45 22.33 4.15 2.60 0.59

9 6475 125708 Dubraj II 38.00 0.70 118.50 0.35 125.50 16.45 141.95 5.85 0.00 146.50 13.00 5.80 2.95 25.28 4.20 2.45 0.70

10 2300 133269 Bhulau 32.00 0.75 104.00 0.45 122.60 16.15 138.75 8.17 0.00 132.00 14.60 5.55 2.75 23.87 4.10 2.65 0.67

11 2929 134319 Rani kajar 32.00 0.85 104.00 0.35 112.90 14.05 126.95 7.06 0.00 134.00 13.75 5.20 2.40 25.79 4.00 2.65 0.60

12 3870 135260 Sundar

mani

28.00 0.60 104.00 0.30 129.50 17.00 146.50 6.05 0.00 134.00 15.80 6.00 2.45 22.33 4.10 2.65 0.60

13 5856 NA Bhado

kanker

35.00 0.70 104.50 0.50 137.70 22.85 160.55 7.98 0.00 132.50 13.20 5.50 2.65 24.11 4.05 2.80 0.65

14 2888 134278 Jhumarwa 27.50 0.65 104.00 0.40 138.80 16.85 155.65 8.88 0.00 132.00 13.70 5.15 2.40 25.68 3.70 2.75 0.65

15 6062 114188 Bishnu 32.50 0.60 113.00 0.50 138.00 21.25 159.25 8.73 0.00 143.00 14.10 5.75 2.25 24.88 4.25 2.50 0.53

16 512 123552 Basa Bhog 32.25 0.85 88.00 0.50 86.00 20.10 106.10 6.95 0.00 116.00 18.10 5.25 2.75 22.20 4.20 2.65 0.65

17 5375 124958 Krishna

Bhog

27.00 0.70 106.50 0.45 133.50 22.20 155.70 7.77 0.00 134.50 10.35 5.25 2.45 25.66 4.05 2.25 0.61

18 7087 NA Hira Nakhi 33.25 0.85 110.00 0.40 130.90 20.90 151.80 6.22 0.00 140.00 15.60 5.90 2.70 23.73 3.95 2.80 0.68

19 10032 116094 Lokti Maudi 34.50 0.60 111.50 0.50 141.45 23.45 164.90 8.00 0.00 139.50 10.65 5.85 2.60 23.84 4.15 2.30 0.63

215

20 6069 NA Kariya

bodela bija

30.85 0.60 110.00 0.60 139.40 20.50 159.90 7.06 0.00 140.00 16.50 6.70 2.45 20.89 4.65 2.75 0.53

21 6688 125922 Gganja Kali 31.25 0.60 105.00 0.45 126.80 26.05 152.85 7.76 0.00 135.00 18.75 5.70 2.65 23.73 4.25 2.55 0.62

22 5528 125109 Banas

KupiII

30.00 0.85 110.50 0.45 122.15 17.90 140.05 6.97 0.00 140.50 15.50 6.10 2.20 23.05 4.05 2.50 0.54

23 6444 125677 Dhangari

Khusha

30.70 0.55 105.00 0.50 130.90 21.55 152.45 6.80 0.00 133.00 17.25 5.25 1.90 25.33 3.95 2.65 0.48

24 6446 125679 Bhaniya 35.25 0.70 99.50 0.40 122.00 18.65 140.65 6.15 0.00 127.50 12.70 6.50 1.85 19.63 4.55 2.85 0.41

25 6637 125871 Farsa phool 41.10 0.55 115.50 0.45 137.20 25.20 162.40 6.65 0.60 145.50 31.70 10.85 3.15 13.41 6.85 2.65 0.46

26 7125 114272 Jay Bajrang 40.80 0.60 116.00 0.55 158.00 22.60 180.60 6.67 1.25 146.00 38.65 11.80 2.40 12.38 8.35 1.80 0.29

27 6726 125960 Gilas 39.25 0.75 114.50 0.40 146.80 23.70 170.50 6.17 0.70 144.50 26.80 10.35 2.55 13.96 6.85 1.70 0.37

28 7615 NA Khatia pati 44.70 0.80 119.00 0.45 179.60 28.00 207.60 7.21 3.40 147.00 29.65 9.70 2.40 15.15 6.95 1.90 0.35

29 8421 114979 Mani 39.05 0.60 119.00 0.40 142.50 20.50 163.00 6.26 2.15 147.00 25.00 9.85 2.15 14.92 6.60 1.85 0.33

30 7539 NA Khatriya

pati

44.45 0.85 116.00 0.40 163.30 26.70 190.00 6.88 1.50 146.00 38.55 11.40 2.30 12.81 8.05 2.00 0.29

31 6729 NA Girmit 40.10 0.85 115.50 0.60 143.90 23.80 167.70 5.93 2.05 145.50 30.45 10.45 2.70 13.92 7.25 2.15 0.37

32 7960 NA Lanji 45.55 0.90 116.00 0.55 179.20 25.45 204.65 6.98 2.15 146.00 22.40 10.05 2.70 14.53 6.75 2.20 0.40

33 5772 114018 Banreg 48.70 0.85 119.00 0.50 159.20 24.95 184.15 8.80 0.85 149.00 25.50 11.10 2.35 13.42 7.85 1.95 0.30

34 9209 NA Ruchi 47.90 0.75 117.00 0.55 170.35 28.00 198.35 7.21 1.00 147.00 31.80 10.70 2.65 13.74 7.10 2.45 0.37

35 8187 NA Safed luchai 39.10 0.75 116.50 0.50 161.50 25.82 187.32 7.80 0.00 144.50 28.55 10.45 2.00 13.83 7.65 1.85 0.26

36 3090 134480 Kanthi

deshi

40.60 0.80 116.50 0.40 147.60 27.20 174.80 8.54 2.55 146.50 24.90 10.90 1.95 13.44 7.35 2.05 0.27

37 9068 NA Piso III 37.60 0.65 114.50 0.60 163.80 26.55 190.35 7.95 1.90 144.50 26.85 10.80 2.20 13.38 7.70 1.85 0.29

38 7301 114358 Kakdi 38.25 0.60 118.50 0.55 142.70 21.85 164.55 9.83 0.70 148.50 25.60 10.70 2.40 13.88 7.30 1.95 0.33

39 6656 125890 Gajpati 33.90 0.65 117.00 0.45 161.80 24.05 185.85 7.18 1.20 142.00 25.25 10.55 2.65 13.46 7.35 2.10 0.36

40 6650 125884 Gadur sela 38.55 0.70 117.00 0.50 151.10 22.10 173.20 6.45 0.80 147.00 27.35 10.50 2.70 14.00 7.65 2.20 0.35

41 5103 124686 Aadan

chilpa

38.80 0.70 118.00 0.45 169.50 27.35 196.85 7.01 0.00 147.00 33.15 10.95 3.05 13.42 7.25 2.45 0.42

216

42 5078 214553 Unknown 36.65 0.75 118.50 0.55 156.80 26.35 183.15 7.33 0.00 146.50 31.25 10.75 3.25 13.63 7.75 2.50 0.42

43 9420 115695 Saja chhilau 34.35 0.60 116.00 0.40 155.60 25.15 180.75 6.77 0.90 146.00 30.45 10.40 3.55 14.04 7.65 3.05 0.46

44 9395 NA Parmal Safri 35.60 0.70 116.50 0.45 160.90 23.30 184.20 6.96 0.85 146.50 29.20 10.80 1.85 13.57 7.60 1.65 0.24

45 9254 115573 Safri 37.80 0.75 116.50 0.45 165.00 25.85 190.85 8.57 0.75 146.50 29.30 10.45 2.40 14.02 7.90 2.15 0.30

46 8711 NA Narved 35.35 0.85 117.50 0.40 155.80 26.75 182.55 8.72 0.00 147.50 27.50 10.10 2.25 14.61 7.35 2.05 0.31

47 8673 NA Nagbel 38.10 0.75 116.50 0.40 177.60 27.15 204.75 8.99 0.95 144.50 37.50 11.45 3.15 12.62 8.30 2.65 0.38

48 8558 115101 Mudariya 31.05 0.70 115.50 0.55 167.60 26.20 193.80 7.69 1.10 146.00 35.30 11.05 2.90 13.21 7.90 2.45 0.37







217

Appendix D2: Mean performance of 33 yield and quality traits of 48 (24 short and 24 long grains length) rice germplasm

accessions

S.

No.

CGR

No.

IC No. Name 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33

1 10031 116093 Lokti Machhi 675.50 70.00 12.92 78.95 66.30 50.69 4.05 2.10 1.93 6.35 3.10 2.05 1.57 1.07 14.92 86.50

2 10036 116098 Atma Sital 1037.00 157.00 17.19 72.08 60.67 46.60 3.95 2.05 1.93 7.20 2.70 2.67 1.82 1.39 21.59 100.00

3 10029 116091 Lokti Machhi 586.00 61.00 15.32 77.27 67.92 54.89 3.75 1.55 2.44 5.75 3.20 1.80 1.53 0.75 20.34 54.50

4 1686 132619 ADT:27 476.50 85.00 17.19 69.71 54.72 35.87 3.75 2.05 1.83 5.50 2.85 1.93 1.47 1.06 16.51 100.00

5 1829 132767 Anjania 760.00 498.50 111.98 70.55 58.87 48.51 3.90 2.75 1.42 6.80 3.70 1.84 1.74 1.30 22.21 100.00

6 2845 NA Kanak Jira 709.50 191.00 25.33 72.96 63.72 49.78 3.70 1.65 2.27 6.95 3.35 2.08 1.88 0.93 23.25 94.50

7 2890 134280 Jhumera 674.50 96.00 14.24 69.72 58.45 47.41 3.70 2.60 1.43 7.00 3.25 2.16 1.89 1.51 17.23 100.00

8 2947 134337 Kakeda (I) 699.00 86.00 12.50 76.60 69.81 59.46 3.35 2.40 1.40 5.55 3.00 1.85 1.66 1.33 26.18 100.00

9 6475 125708 Dubraj II 667.00 137.00 20.47 73.84 65.17 41.70 3.85 2.15 1.79 8.70 3.05 2.85 2.26 1.60 20.37 100.00

10 2300 133269 Bhulau 582.00 141.50 24.43 75.75 63.07 41.50 3.55 2.35 1.51 6.55 3.35 1.96 1.85 1.29 25.28 93.00

11 2929 134319 Rani kajar 673.50 163.00 24.26 75.38 60.80 37.74 3.50 2.30 1.53 6.65 3.35 1.99 1.90 1.31 27.55 57.00

12 3870 135260 Sundar mani 802.00 175.00 22.25 74.14 63.66 51.52 3.80 2.35 1.62 7.15 2.95 2.42 1.88 1.50 29.33 96.00

13 5856 NA Bhado kanker 912.00 154.50 16.37 75.25 58.49 27.41 3.50 2.45 1.43 6.40 2.95 2.17 1.83 1.52 24.91 100.00

14 2888 134278 Jhumarwa 814.00 164.00 20.22 68.89 54.82 29.42 3.25 2.40 1.35 5.50 3.00 1.83 1.70 1.36 28.39 100.00

15 6062 114188 Bishnu 1281.50 201.50 16.18 76.26 66.43 58.38 3.95 2.20 1.80 6.80 3.05 2.23 1.72 1.24 23.71 97.50

16 512 123552 Basa Bhog 414.00 66.00 15.40 67.67 61.04 49.77 3.80 2.40 1.59 6.25 2.95 2.12 1.65 1.34 28.82 100.00

17 5375 124958 Krishna Bhog 1070.00 188.00 18.63 77.77 68.82 47.63 3.60 1.95 1.85 6.20 2.95 2.10 1.72 1.14 15.50 100.00

18 7087 NA Hira Nakhi 774.50 145.00 24.56 77.10 63.10 54.59 3.85 2.50 1.55 6.60 3.70 1.78 1.72 1.16 15.42 100.00

19 10032 116094 Lokti Maudi 956.00 179.50 18.82 77.71 71.38 49.15 3.90 2.00 1.95 7.40 3.10 2.39 1.90 1.23 16.70 82.00

20 6069 NA Kariya bodela

bija

782.00 190.00 24.21 75.80 62.67 53.96 3.95 2.35 1.69 9.10 3.70 2.46 2.30 1.47 18.00 72.50

21 6688 125922 Gganja Kali 1249.50 220.50 17.96 77.96 67.35 50.91 3.95 2.25 1.76 7.95 2.80 2.84 2.01 1.62 18.12 72.00

218

22 5528 125109 Banas KupiII 880.50 173.00 19.86 76.63 63.45 39.15 3.90 2.30 1.70 5.75 2.50 2.30 1.48 1.36 23.96 77.00

23 6444 125677 Dhangari

Khusha

1211.00 219.00 18.24 77.70 69.70 56.49 4.05 2.40 1.69 5.70 3.25 1.75 1.41 1.04 22.31 62.00

24 6446 125679 Bhaniya 546.00 140.00 26.72 78.83 63.54 36.70 4.10 2.60 1.58 7.30 2.50 2.92 1.78 1.86 16.17 32.50

25 6637 125871 Farsa phool 969.00 192.50 21.33 74.02 60.53 43.77 6.35 2.75 2.31 9.45 3.30 2.86 1.49 1.24 27.37 100.00

26 7125 114272 Jay Bajrang 807.50 180.00 21.93 75.12 60.68 50.05 7.20 2.15 3.35 8.10 3.30 2.46 1.13 0.74 24.71 97.50

27 6726 125960 Gilas 853.00 178.50 20.69 56.44 50.59 49.95 6.85 2.05 3.34 9.05 3.00 3.02 1.32 0.91 25.30 100.00

28 7615 NA Khatia pati 983.50 199.50 20.53 74.92 64.05 49.95 6.20 2.20 2.82 10.05 3.35 3.00 1.62 1.07 25.53 96.50

29 8421 114979 Mani 755.50 196.50 25.84 62.29 56.36 52.96 6.90 1.70 4.07 10.30 3.15 3.27 1.49 0.81 18.50 78.00

30 7539 NA Khatriya pati 721.50 191.00 26.25 72.25 64.27 48.45 7.10 2.10 3.39 9.80 3.85 2.55 1.38 0.75 18.25 98.00

31 6729 NA Girmit 946.50 179.00 18.60 75.94 64.12 49.32 6.65 2.30 2.90 9.40 3.75 2.51 1.41 0.87 20.52 92.50

32 7960 NA Lanji 928.00 202.00 21.94 56.90 44.88 55.77 6.20 2.20 2.83 8.70 3.25 2.69 1.40 0.96 21.97 93.50

33 5772 114018 Banreg 937.50 252.50 26.71 71.59 62.41 55.90 6.95 2.10 3.31 11.30 3.20 3.54 1.63 1.08 17.31 100.00

34 9209 NA Ruchi 894.00 215.50 24.02 74.53 67.15 56.27 6.60 2.35 2.81 9.50 2.60 3.65 1.44 1.30 18.76 100.00

35 8187 NA Safed luchai 816.00 189.00 23.22 73.78 66.59 59.88 7.25 1.80 4.04 9.10 3.30 2.76 1.26 0.69 20.25 100.00

36 3090 134480 Kanthi deshi 957.00 189.50 18.97 71.14 78.91 58.51 6.40 1.95 3.28 10.50 4.25 2.47 1.64 0.76 25.35 96.50

37 9068 NA Piso III 1005.00 204.00 19.27 78.43 67.39 62.14 6.45 2.05 3.15 13.15 3.85 3.42 2.04 1.09 21.98 94.50

38 7301 114358 Kakdi 870.50 138.50 15.99 62.03 59.15 41.08 6.50 2.05 3.17 8.80 3.10 2.84 1.35 0.90 23.46 97.00

39 6656 125890 Gajpati 804.50 217.00 25.27 65.89 58.55 52.95 6.50 2.30 2.83 8.80 2.95 2.98 1.35 1.05 20.06 93.50

40 6650 125884 Gadur sela 910.00 168.50 18.61 68.80 58.08 54.75 6.75 2.25 3.01 10.25 3.85 2.66 1.52 0.89 26.23 84.00

41 5103 124686 Aadan chilpa 827.50 183.50 21.37 57.44 46.10 37.82 6.40 2.15 2.99 9.15 3.70 2.48 1.43 0.83 20.11 91.00

42 5078 214553 Unknown 928.50 234.50 25.22 75.61 67.69 55.44 6.10 2.65 2.31 10.25 3.00 3.42 1.68 1.49 26.43 85.50

43 9420 115695 Saja chhilau 788.50 173.50 21.94 67.46 58.00 49.45 6.70 3.00 2.23 9.35 3.10 3.02 1.40 1.36 25.42 88.00

44 9395 NA Parmal Safri 902.50 193.00 21.06 66.12 61.20 55.89 6.95 3.00 2.32 11.20 3.25 3.45 1.61 1.49 25.57 81.00

45 9254 115573 Safri 1439.50 284.50 20.71 77.52 68.18 56.43 6.70 2.05 3.27 10.40 3.05 3.41 1.55 1.05 28.23 98.00

46 8711 NA Narved 1130.00 178.50 15.15 73.21 60.13 50.87 6.70 2.15 3.12 9.10 3.00 3.04 1.36 0.98 26.16 100.00

219

47 8673 NA Nagbel 430.00 259.00 229.71 64.34 54.58 46.27 7.10 2.95 2.41 10.35 3.25 3.19 1.46 1.33 28.33 100.00

48 8558 115101 Mudariya 706.00 190.50 26.98 72.71 51.89 60.20 7.10 2.30 3.09 11.45 3.75 3.05 1.61 0.99 25.50 100.00







220

Appendix E: Microsatellite (SSR) markers used for molecular characterization in 24 short and 24 long grain accessions of rice.

S.

No.

Marker Amplicon

Size

Forward Primer Reverse Primer Chromo-

some No. #

PIC

Value

1 RM 1 67-119 GCGAAAACACAATGCAAAAA GCGTTGGTTGGACCTGAC 1 0.87

2 RM 5 94-138 TGCAACTTCTAGCTGCTCGA GCATCCGATCTTGATGGG 1 0.74

3 RM11 118-151 TCTCCTCTTCCCCCGATC ATAGCGGGCGAGGCTTAG 7 0.49

4 RM 19 192-250 CAAAAACAGAGCAGATGAC CTCAAGATGGACGCCAAGA 12 0.85

5 RM 25 121-159 GGAAAGAATGATCTTTTCATGG CTACCATCAAAACCAATGTTC 8 0.79

6 RM 30 100-140 GGTTAGGCATCGTCACGG TCACCTCACACGACACG 6 0

7 RM 104 222-238 GGAAGAGGAGAGAAAGATGTGTGTCG TCAACAGACACACCGCCACCGC 1 0

8 RM 105 100-141 GTCGTCGACCCATCGGAGCCAC TGGTCGAGGTGGGGATCGGGTC 9 0.59

9 RM 125 105-147 ATCAGCAGCCATGGCAGCGACC AGGGGATCATGTGCCGAAGGCC 7 0.12

10 RM 130 73-81 TGTTGCTTGCCCTCACGCGAAG GGTCGCGTGCTTGGTTTGGTTC 3 0.22

11 RM 132 70-85 ATCTTGTTGTTTCGGCGGCGGC CATGGCGAGAATGCCCACGTCC 3 0.5

12 RM 134 92-94 ACAAGGCCGCGAGAGGATTCCG GCTCTCCGGTGGCTCCGATTGG 7 0.04

13 RM 135 100-150 CTCTGTCTCCTCCCCCGCGTCG TCAGCTTCTGGCCGGCCTCCTC 3 0.81

14 RM 148 190-210 ATACAACATTAGGGATGAGGCTGG TCCTTAAAGGTGGTGCAATGCGAG 3 0.65

15 RM 152 133-157 GAAACCACCACACCTCACCG CCGTAGACCTTCTTGAAGTAG 8 0.64

16 RM 154 148-230 ACCCTCTCCGCCTCGCCTCCTC CTCCTCCTCCTGCGACCGCTCC 2 0.55

17 RM 161 154-187 TGCAGATGAGAAGCGGCGCCTC TGTGTCATCAGACGGCGCTCCG 5 0.28

18 RM 168 96-116 TGCTGCTTGCCTGCTTCCTTT GAAACGAATCAATCCACGGC 3 0.64

19 RM 171 307-347 AACGCGAGGACACGTACTTAC ACGAGATACGTACGCCTTTG 10 0.77

221

20 RM 172 159-165 TGCAGCTGCGCCACAGCCATAG CAACCACGACACCGCCGTGTTG 7 0.49

21 RM 175 80-90 CTTCGGCGCCGTCATCAAGGTG CGTTGAGCAGCGCGACGTTGAC 3 0.15

22 RM 186 115-132 TCCTCCATCTCCTCCGCTCCCG GGGCGTGGTGGCCTTCTTCGTC 3 0.51

23 RM 201 155-350 CTCGTTTATTACCTACAGTACC CTACCTCCTTTCTAGACCGATA 9 0.48

24 RM 215 126-161 CAAAATGGAGCAGCAAGAGC TGAGCACCTCCTTCTCTGTAG 9 0.38

25 RM 218 100-120 TGGTCAAACCAAGGTCCTTC GACATACATTCTACCCCCGG 3 0.64

26 RM 231 157-182 CCAGATTATTTCCTGAGGTC CACTTGCATAGTTCTGCATTG 3 0.55

27 RM 234 133-163 ACAGTATCCAAGGCCCTGG CACGTGAGACAAAGACGGAG 7 0.26

28 RM 242 200-290 AAACACATGCTGCTGACACTTGC TTACTAGATTTACCACGGCCAACG 9 0.32

29 RM 248 75-100 TCCTTGTGAAATCTGGTCCC GTAGCCTAGCATGGTGCATG 7 0.53

30 RM 287 82-118 TTCCCTGTTAAGAGAGAAATC GTGTATTTGGTGAAAGCAAC 11 0.46

31 RM 316 194-216 CTAGTTGGGCATACGATGGC ACGCTTATATGTTACGTCAAC 9 0.55

32 RM 338 178-184 CACAGGAGCAGGAGAAGAGC GGCAAACCGATCACTCAGTC 3 0.35

33 RM 408 112-128 CAACGAGCTAACTTCCGTCC ACTGCTACTTGGGTAGCTGACC 8 0.50

34 RM 422 385-500 TTCAACCTGCATCCGCTC CCATCCAAATCAGCAACAGC 3 0.76

35 RM 431 233-261 TCCTGCGAACTGAAGAGTTG AGAGCAAAACCCTGGTTCAC 1 0.25

36 RM 432 150-187 TTCTGTCTCACGCTGGATTG AGCTGCGTACGTGATGAATG 7 0.76

37 RM 433 216-248 TGCGCTGAACTAAACACAGC AGACAAACCTGGCCATTCAC 8 0.49

38 RM 436 83-134 ATTCCTGCAGTAAAGCACGG CTTCGTGTACCTCCCCAAAC 7 0.66

39 RM 447 95-146 CCCTTGTGCTGTCTCCTCTC ACGGGCTTCTTCTCCTTCTC 8 0.72

40 RM 455 127-144 AACAACCCACCACCTGTCTC AGAAGGAAAAGGGCTCGATC 7 0.79

41 RM 468 250-350 CCCTTCCTTGTTGTGGCTAC TGATTTCTGAGAGCCAACCC 3 0.72

222

42 RM 481 95-200 CAGCTAGGGTTTTGAGGCTG TAGCAACAACCAGCGTATGC 7 0.79

43 RM 489 248-314 ACTTGAGACGATCGGACACC TCACCCATGGATGTTGTCAG 3 0.29

44 RM 501 130-179 GCCCAATTAATGTACAGGCG ATATCGTTTAGCCGTGCTGC 7 0.53

45 RM 517 260-287 GGCTTACTGGCTTCGATTTG CGTCTCCTTTGGTTAGTGCC 3 0.57

46 RM 520 200-290 AGGAGCAAGAAAAGTTCCCC GCCAATGTGTGACGCAATAG 3 0.69

47 RM 523 130-150 AAGGCATTGCAGCTAGAAGC GCACTTGGGAGGTTTGCTAG 3 0.55

48 RM 527 190-245 GGCTCGATCTAGAAAATCCG TTGCACAGGTTGCGATAGAG 6 0.33

49 RM 545 150-230 CAATGGCAGAGACCCAAAAG CTGGCATGTAACGACAGTGG 3 0.53

50 RM 546 115-150 GAGATGTAGACGTAGACGGCG GATCATCGTCCTTCCTCTGC 3 0

51 RM 560 237-268 GCAGGAGGAACAGAATCAGC AGCCCGTGATACGGTGATAG 7 0.52

52 RM 569 170-185 GACATTCTCGCTTGCTCCTC TGTCCCCTCTAAAACCCTCC 3 0.15

53 RM 22565 200-280 TCCACGCGTTGTCGTAGAAATTTAGC AGCCCGAGCACCATGAAACACC 8 0.55

54 RM 22710 150-180 CGCGTGGGCGAGACTAATCG CCTTGACTCCGAGGATTCATTGT 0.44

55 RM 3825 147-200 AAAGCCCCCAAAAGCAGTAC GTGAAACTCTGGGGTGTTCG 1 0.7

56 OSR-13 85-122 CATTTGTGCGTCACGGAGTA AGCCACAGCGCCCATCTCTC 8 0

57 Xa- 5 S 300 GTCTGGAATTTGCTCGCGTTCG TGGTAAAGTAGATACCTTATCAA 5 0

58 Xa-13 Pro 290-610 GGCCATGGCTCAGTGTTTAT GAGCTCCAGCTCTCCAAATG 8 0

59 Xa-21 800-1200 AGACGCGGAAGGGTGGTTTCCCG AGACGCGGTAATCGAAAGATGA 11 0.23

223

Appendix F: ISSR markers used for molecular characterization in 24 short and 24long grain accessions of rice.

S. No Marker No. Of

Alleles

Forward Sequence (5'→3') Annealing Temp. Tm Value PIC VALUE

1 UBC 808 3 AGAGAGAGAGAGAGAGC 54 46.8 0.25

2 UBC 809 6 AGAGAGAGAGAGAGAGG 52 46.6 0.29

3 UBC 818 3 CACACACACACACACAG 48 48 0.00

4 UBC 824 2 TCTCTCTCTCTCTCTCG 54 49 0.50

5 UBC 834 6 AGAGAGAGAGAGAGAGAT 48 45.2 0.07

6 UBC 841 6 GAGAGAGAGAGAGAGAGC 48 49.7 0.50

7 UBC 842 6 GAGAGAGAGAGAGAGAGG 48 49.5 0.07

8 UBC 856 5 ACACACACACACACACYA 48 52 0.46

9 UBC 873 6 GACAGACAGACAGACA 48 54 0.15

10 UBC 885 3 TATGAGAGAGAGAGAGA 52 42 0.08

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“MOLECULAR AND AGRO-MORPHOLOGICAL … · 2018-12-07 · short and 24 long grains length) rice germplasm accessions 88 4.3 Mean and Variability parameters for 33 yield and quality