ISSN 0974-0775

Bimonthly

(International Journal of Applied Agricultural & Horticultural Sciences)

GREEN FARMING

May-June 2016

CONTENTS

Number 3Volume 7

Screening of pigeonpea genotypes for drought stress at early vegetative phase in Alfisol and Vertisol

Heterosis, combining ability and molecular characterization in fieldpea ( L. var arvense)

Assessment of variability, heritability and divergence among the traditional rice genotypes using PVC pipes under

control and low-moisture stress condition

Genetic variability for yield and related attributes in rice under aerobic and normal condition

Pattern of relationship among yield and yield component traits in rice ( ) under drought condition

Evaluation of landraces of rice ( L.) for genetic diversity

Inter-relationship of yield and its component characters in French bean ( L.)

Correlation and path analysis studies for growth and quality traits in sweet sorghum ( )

Combining ability analysis and gene action of yield and yield contributing characters in popcorn ( var. )

Correlation and path coefficient analysis among maize ( ) hybrids for yield and yield components

Study of genetic variability parameters among linseed ( ) genotypes for yield & yield components

Induction of mutations for yield attributing characters in groundnut ( L.)

Studies on genetic diversity in groundnut ( L.) germplasm

Genetic variability, heritability, genetic advance and correlation of yield and quality traits in segregating generation

of upland cotton

Genetic variability and correlation studies in biparental progenies of eggplant ( L.)

Combining ability, gene action and heterosis studies involving SI and CMS lines and testers in cabbage

Stability analysis for fruit yield and its components in tomato ( L.)

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M.G. MULA, S.B. PATIL, J. ADEN, A. RATHORE , ANILKUMAR VEMULA and R.V. KUMAR

SURABHI CHAUHAN, A.M. PATEL, SWETA MISHRA, P.T. PATEL, TARUN J. KHATRANI and D.J. JOSHI

UDAY KUMAR H.R., GANGAPRASAD S., RAGHAVENDRA P. and SHASHIDHAR H.E.

KHUSHBOO CHANDRA, NILANJAYA and RAJESH KUMAR

SANTOSH KUMAR, N.K. SINGH, RAJESH KUMAR, NILANJAYA, CHANDAN KUMAR and PRITI KUMARI

E. UMARANI, K. RADHIKA, V. PADMA and L.V. SUBBARAO

M.G. PATIL, KUSHAL, K. KAVITA, S.S. PATIL, Y. PAMPANNA and R.P. JAIPRAKASHNARAYAN

S.B. ZADE, S.S. AMBEKAR, D.G. INGOLE and S.A. KADAM

M. SRIDHAR, K. MURALI KRISHNA, RAZIA SULTANA and M.H.V. BHAVE

K. SRAVANTI, I. SWARNALATHA DEVI, M.R. SUDARSHAN and K. SUPRIYA

NIMIT KUMAR and SATISH PAUL

M.R. KHARADE, V.V. UJJAINKAR and S.N. DESHMUKH

MUKESH BHAKAL, G.M. LAL and P.K. RAI

K.S. USHARANI, P. AMALABALU and N.M. BOOPATHI

AANCHAL CHAUHAN and K.S. CHANDEL

HAMENT THAKUR and VIDYASAGAR

SONAM SPALDON, R.K. SAMNOTRA, SANJEEV KUMAR, SANDEEP CHOPRA and ANIL BHUSHAN

Pisum sativum

Oryza sativa

Oryza sativa

Phaseolus vulgaris

Sorghum biocolor

Zea mays Everta

Zea mays

Linum usitatissimum

Arachis hypogaea

Arachis hypogaea

Solanum melongena

Solanum lycopersicum

Contd. ....

Previous issue :

Vol. No. pp. 254-5067, 2,Research Papers

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NAAS Rating : 4.79

(Abbreviation : )Green Farming Int. J.

........ 562

........ 566

Genetic divergence in ( (L.) Gaertn.)

Studies on genetic variability in M generation for yield characters in rice ( L.)

Genetic diversity analysis in blackgram [ (L.) Hepper] based on quantitative traits

Genetic variability, heritability and genetic advance studies in brinjal ( L.)

Impact of land configuration and nutrient management on productivity, quality and moisture use efficiency of cotton

Response of time of application and different N levels through fertigation on growth, cob yield & WUE of sweet corn

Effect of different fertility levels and weed management practices on productivity, profitability, soil fertility

and weed dynamics in winter maize ( L.)

Effect of zinc and sulphur on the biochemical characteristics of Indian mustard ( L.) Czern and Coss

Determination of critical limits of boron for in soils of Kumoun region of Uttarakhand

Effect of fertility levels and weed management practices on physiological growth parameters of irrigated wheat

Yield maximization of late sown wheat through INM approach and its consequence on physico-chemical

properties of soil

Workload of women in conventional and organic farming in the selected agro-climatic zones of northern Karnataka

Tree plantation for the control of soil salinity and water table in canal commands, India

Nutritional status of apple orchards in district Shimla of Himachal Pradesh

Yield and economics of organic nutrition in direct seeded rice

Evaluation studies of oriental pickling melon ( ) genotypes for growth, yield and quality traits

Character association and path analysis studies in wild melon ( subsp. )

Assessment of different chinese cabbage genotypes for growth, yield and quality

Growth, flowering and corm production of gladiolus as influenced by various planting time and chemicals

ragi Eleusine coracana

Oryza sativa

Vigna mungo

Solanum melongena

Bt

Zea mays

Brassica juncea

Brassica napus

Cucumis melo

Cucumis melo agrestis

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K. IMTIAZ AHMED, N.V. NAIDU, V. RAJA RAJESWARI and K.H.P. REDDY

LAISANGBAM BANDANA DEVI, RAVI BISHNOI and G. SURESH BABU

ASIF HADIMANI, C.R. KONDA, J.M. NIDAGUNDI and RAJENDRAGOUDA PATIL

M.H. IBAAD, V. SRINIVASA and H.T. SHRUTHI

W.N. NARKHEDE, S.K. NAYAK, V.K. SUTAR and B.R. JAWARE

J.R. PATEL, G.J. PATEL, K.N. PRAJAPATI and K.P. PATEL

SANJU KUMAWAT, A.C. SADHU, SEEMA SHARMA and HANSA LAKHRAN

MANJULA UDIKERI, B.G. KOPPALKAR, B.K. DESAI and KESHAVAMURTHY G.M.

N.A. KHAN, RAJA HUSAIN, NITIN VIKRAM, AKHTAR ALI, KUNVAR GYANENDRA and SHIVANI

SHILPI GUPTA, P.C. SRIVASTAVA and D.K. SINGH

JANMEJAY SHARMA, S.S. TOMAR, R.L. RAJPUT, BHUSHAN LAL PRAJAPATI and SHASHI YADAV

U.P. SHAHI, DESHRAJ, ASHISH DWIVEDI, B.P. DHYANI, ASHOK KUMAR and ROOP KISHORE

RAJESHWARI DESAI and SUMANGALA P.R.

M.V. MANJUNATHA, M. HEBBARA, V.B. KULIGOD and S.G. PATIL

KANWAR SINGH, J.N. RAINA and ASHOK KUMAR NANGLIYA

M.A. NISHAN, L. GIRIJADEVI and V.L. GEETHAKUMARI

SHRUTI P.G., V.M. GANIGER, BHUVANESHWARI G., M.B. MADALAGERI, Y.K. KOTIKAL, MANJUNATHA G.

and KANTESH G.

SHIVAPPA M. KARADI, V.M. GANIGER, SIDDAPPA, VITTAL MANGI and BHUVANESHWARI G.

S. BASFORE, U. THAPA and S.B. CHATTOPADHYAY

M. RAJA NAIK, D. SREEDHAR and M. RAMAIAH

3

Yield and yield components of pigeonpea as influenced by nutrient management practices in pigeonpea

and clusterbean intercropping system

Contd. ....

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Study of INM on growth, yield and quality in China aster ( ) cv. “Phule Ganesh Pink”

Growth, yield & quality of Kalmegh ( Nees.) as influenced by seedling treatment with

plant growth promoting rhizobacteria

Integrated management of wilt of chickpea ( L.) caused by f. sp.

Effects of antagonistic and compatibility of some native spp. under Terai agro-ecological region of W.B.

Nutrients changes during off-season flowering in custard apple cv. Arka Sahan induced by pruning and defoliation

Effect of rooting media on growth, survival and economics production of air layers of guava cv. Sardar

Genetic variability and correlation studies for fruit yield and quality parameters in mango ( L.)

Physical properties of 'Rajapuri' & 'Kesar' mango fruits and testing of weight fruit grader based on the physical properties

Effect of pre-harvest foliar application of calcium on post-harvest life of guava fruits

Physical, functional, nutrient and sensory characteristics of ready to eat flakes of little millet ( L.)

Development of low gluten biscuits using Buckwheat ( : Safety and quality studies

Studies on low temperature storage and duration on flower and bulb production in cv 'Elite'

Supercritical fluid extraction (SFE) of bioactive flavonoids from mulberry ( L.) leaf powder

Production of tea vinegar by semicontinuous fermentation using immobilized cells of

Development and standardization of tulsi-kokum herbal tea

Shelf-life and cost of production of blended with coconut by sensory evaluation

Phytochemicals in noni fresh fruit juice and their composition in response to applied nutrients

Effect of age of seedlings on growth, yield and quality of onion ( ) in under North Gujarat condition

Natural Farming : A Key to Uplift Rural India

Callistephus chinensis

Andrographis paniculata

Cicer arietinum Fusarium oxysporum ciceri

Trichoderma

Mangifera indica

Panicum miliare

Fagropyrum esculentum)

Asiatic Lilium

Morus alba

Acetobacter aceti

khoa burfi

Allium cepa rabi

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ILA PITHIYA, D.K. VARU and MITAL VAGHASIYA

MANJUNATHA B., MALLIKARJUNA GOWDA A.P., HAREESH D. and T.N. RANJINI

P.N. SHYLA, FATIMA SADATULLA, PALLAVI and BHANUPRAKASH K.J.

D.S. THAWARE, O.D. KOHIRE and V.M. GHOLVE

M.K. ROY, S. HEMBRAM, S. DUTTA and S. RAY

G.M. VINAY, R. CHITHIRAICHELVAN, ENETTE GEETHIKA SEQUIRA and JAGANATH S.

M.C. PATEL, D.A. PATEL, K.V. PATEL, N.V. SONI, B.N. SATODIYA and R.G. JADAV

SUNKAM MAHESH, KULAPATI HIPPARAGI, I.B. BIRADAR, S.R. PATIL and BALESH GOUDAPPANAVAR

V.B. BHALODIYA, D.C. JOSHI and B.L. JANI

K.A. DAPEWAR, S.G. BHARAD, K. SATKAR and P.M. VARANE

KAVITA PATIL and BHARATI CHIMMAD

QURAAZAH AKEEMU AMIN, HAFIZA AHSAN, TOWSEEF A. WANI and QAZI NISSAR

K.M. MALIK, M.Q. SHIEKH and I.T. NAZKI

RAMYAV., UDAYKUMAR NIDONI, JAYARAMANAIK N.,ASHOKAJ., SHARANAGOUDAHIREGOUDAR,

RAMACHANDRA C.T., LAVANYA V. and GOUDRA PROMOD GOUDA

NAVEET KAUSHAL and R.P. PHUTELA

P.P. THAKUR, P.N. SATWADHAR and H.W. DESHPANDE

S.S. TALEKAR, S.P. PATIL, N.S. SHIKALGAR and D.V. BAINWAD

H.R. BHOOMIKA, M. VASUNDHARA and K.G. SANTOSH

B.R. KUMBHKAR, N.M. PATEL and S.G. MORE

NARENDRA SINGH RATHORE

RAVINDRANATH N., S.N. PATIL, SATISH P., ANUPAMA H. and SUNKAM M.

Growth and yield parameters of V mulberry and rearing performance of silkworm L. as influenced

by customized fertilizers

1 Bombyx mori

Effect of mango variety and time of grafting on graft-take, leaves & girth of rootstock in polyhouse and shade net

Strategic Vision Message : 33

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Back Inner Page

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Rice ( L.), the most important staple food

crop of the globe. Nearly 90 per cent of world's rice is grown

and consumed with 60 per cent of population, where, about

two-thirds of world's poor live in Asian subcontinent. Hence,

'Rice is life' for human world (Khush and Virk, 2000). World

wide there are 54 million ha of rainfed lowlands, which

contribute 19% of the world's total rice production and 14

million ha of rainfed uplands, which contribute 4% of the

world's total rice production (Maclean , 2002). Rainfed

low lands are characterised by uncertain and erratic rainfall,

which destabilises the yield in yearly fluctuations. Therefore,

drought is considered to be one of the major constrains for

rice production in worldwide areas (Herdt, 1991). Breeding for

drought tolerance is really a challenging task because of

complexity involved in the genetics of its component traits.

The genotypic coefficient of variation measures the range

of variability available in a crop and also enables to compare

the amount of variability present in different characters. The

phenotypic expression of the character is the result of

interaction between genotype and environment. Hence, the

total variance needs to be partitioned into heritable and non-

heritable components to assess the inheritance pattern of the

particular character under study. Heritability indicates the

relative degree at which a character is transmitted from

parent to offspring. Hence, it is essential to know the degree of

diversity and variability present if local germplasm lines,

which forms the basis for selecting desirable genotypes. In

this context the present study was undertaken to study the

diversity and variability parameters among the 64 selected

local rice cultivars.

Oryza sativa

et al.

ABSTRACT

The nature and magnitude of variability and genetic divergence were estimated in 64 rice genotypes by considering 10 traits

under controlled condition (PVC pipes).Analysis of variance found to be significant for all the characters under both in control

and low-moisture stress condition. The higher magnitude of PCV and GCV was recorded for traits like root length, root

number, root volume, dry root weight and grain yield indicates the presence of considerable degree of variability. High

heritability coupled with high genetic advance as per cent mean was registered for root length, root number, root volume, dry

root weight and grain yield suggested preponderance of additive gene action in the expression of these characters. Based on

D values, 64 genotypes were grouped into 12 clusters in control and 13 clusters in low-moisture stress indicates that

genotypes under study were genetically diverse. The maximum inter-cluster D value of 34.78 between cluster II and cluster

VIII under control condition, whereas 42.45 between cluster V and cluster XI under low-moisture stress condition indicated

wider genetic diversity among the genotypes between these groups. Cluster IV with overall score of 112.5 in control and 98 in

low-moisture stress condition across the 10 characters received highest rank, indicating the presence of most promising

genotypes in this clusters. Among the traits studied, grain yield contributed maximum to divergence in both contrasting

moisture regimes, hence importance has to be given for this during selection. In all the studied genotypes, Azucena, SKAU-

98, Bangaradagundu, Kougisaale, Navalaisaale, Mukkanna, Sampige and Doddiga could be utilized for further breeding

programmes to obtain suitable varieties for drought.

2

2

Key words : Diversity, Drought tolerant, Moisture stress, Rice genotype, Root traits, PVC pipes, Variability.

INTRODUCTION

Received : 06 November 2015 ; Revised accepted : 09 April 2016

Green Farming Vol. (3) : 520-526 ;7 May-June, 2016

UDAY KUMAR H.R. , GANGAPRASAD S. RAGHAVENDRA P. and SHASHIDHAR H.E.a1* b2 a3+ a4

,a

b

Department of Genetics and Plant Breeding, University of Agricultural Sciences, Bangalore - 560065

Deptt. of Genetics and plant breeding, College of Agriculture, Shivamogga, (UAS, Bangalore) - 560 065 (Karnataka)

Research Paper

Assessment of variability, heritability and divergence among

the traditional rice genotypes using PVC pipes under control

and low-moisture stress condition

1,3

2,4

P.G. Student *(udayhr7096@gmail.com)

(raghavendra9078@gmail.com), Professor+

19

MATERIALS AND METHODS

RESULTS AND DISCUSSION

Plate 1

& 2

Plate 3

Genetic variability parameters for grain yield and root

related characters : Table 1

Table 2

The material for the present study consisted of 64

traditional rice genotypes drawn from the rice germplasm

maintained at Organic Farm Research Centre, Zonal Agric.

Res. Station, Navile, Shimoga. This experiment was

conducted during season 2012, under rain water

shelter at Deptt. of Biotechnology, College of Agriculture,

UAS, G.K.V.K, Bangalore. The experiment was carried out

using PVC pipes in 8 x 8 Simple Lattice Design. PVC pipes of

60cm length and 18cm diameter were arranged in 8 columns

and 8 rows under rain water shelter with two replications for

control and low-moisture stress conditions. The pipes were

filled with a mixture of sandy clay loam and FYM in 4:1

proportion. Seeds were directly sown into the pipes. Few

days after germination seedlings were thinned out leaving

only one seedling in each pipe. (Hemamalini 2000). The

low-moisture stress was imposed thirty days after sowing by

withholding the irrigations and the plants were irrigated only

when they showed wilting symptoms, whereas in control

treatments the plants were irrigated once in two days (

).

The sampling in both the condition was done at maturity

stage. The pipes were removed carefully and put in water

over night to loosen the soil. The next day, roots were cleaned

thoroughly and carefully using fine jet of water. The intact root

system and separated roots of each plant were collected and

stored in poly bags containing water for recording

observations ( ).

The observations were recorded on sample plant of each

genotype for yield & root related characters.

The data collected on sample plant of

each genotype were subjected to the statistical analysis by

using WINDOSTAT software for estimation of genetic variability

parameters and diversity analysis using Mahalanobis D (1936)

method.

As evident from the the analysis of

variance are given for various morphological characters were

statistically tested and found to be significant for all the

characters under both in control and low-moisture stress

condition.

The genetic variability parameter for all the 10 traits under

control and low-moisture stress conditions are furnished in the

.

The variability parameters revealed that a narrow difference

between phenotypic and genotypic coefficient of variation for

most of the characters studied indicated that lesser influence of

environment for those traits. The higher magnitude of

phenotypic and genotypic coefficient of variation was recorded

for traits like root length, root number, root volume, dry root

weight and grain yield indicates the presence of considerable

degree of variability. The same was reported by Latha (1996)

and Gireesha (2000). However moderate estimates were

observed for plant height, number of tillers per plant and

number of productive tillers per plant indicated that presence of

considerable variability. Whereas for days to 50 per cent

flowering and days to maturity showed lower estimates of

phenotypic and genotypic coefficient of variation indicated

lower degree of variability in both control and low moisture

stress condition (Table 2).

The proportion of genetic variability which is transmitted

from parents to offspring is reflected by heritability (Lush 1949).

Heritability and genetic advance as per cent mean when

calculated together would prove more useful in predicting the

resultant effect of selection on phenotypic expression (Johnson

1955). Based on this consideration high heritability

coupled with high genetic advance as per cent mean was

registered for root length, root number, root volume, dry root

kharif

et al.,

et al.

et al.,

Method of sampling and recording of observations :

Statistical analysis :

2

521 Kumar et al.

20

Green Farming 7 (3)

Plate 1. Method of filling PVC pipes for root study

Plate 2. Over view of 64 traditional rice genotypes

evaluated for root morphological characters

Plate 3. Method of root sampling

weight and grain yield. Similarly Hemamalini (1997) reported

high heritability and genetic advancement as per cent mean for

root number, root volume and dry root weight, suggesting the

preponderance of additive gene action in the expression of

these characters. Therefore selection may be effective through

these characters. Whereas, high heritability associated with

moderate genetic advancement as per cent mean was

observed for plant height, whereas days 50 per cent flowering

and days to maturity recorded high heritability and low genetic

advancement as per cent mean in both control and low

moisture stress condition which revealed that non-additive

gene action in the expression of these characters in their

inheritance, hence in this case selection may not be effective

(Table 2). These findings were in agreement with the findings of

earlier researchers Khare (2014); Pratap (2012);

Gangashetty (2013); Vaithiyalingal & Nadarajan (2006).

In the present experiment the higher phenotypic and

genotypic coefficient of variability for number of productive tillers

per plant, root volume, dry root weight and grain yield with high

heritability coupled with very high genetic advancement as per

cent mean was observed under low-moisture stress condition

as compared to control condition, hence direct selection for

these characters improves the stress tolerance (Table 2).

et al. et al.

et al.

21 Green Farming

522May-June 2016

Source of variation dfDays to 50% flowering Days to maturity Plant height (cm) Root length (cm) Root number

C S C S C S C S C S

Replication 1 0.031 31.00 0.07 116.28 6.57 4.88 101.53 1.12 731.53 38.28

Genotypes (unadjusted) 63 97.98** 86.08** 214.61** 104.93** 290.10** 254.99** 542.56** 456.01** 1872.15** 1127.71**

Blocks within adjusted 14 4.66 8.30 13.92 8.41 4.00 3.85 11.02** 4.84 5.89 15.89

Error intra block 49 7.97 6.31 10.21 7.07 5.87 5.23 3.10 6.48 5.22 8.47

CD (5%) 5.20 5.18 6.61 5.44 4.61 4.41 3.81 4.92 4.65 6.14

CV (%) 2.74 3.02 2.40 2.18 2.78 2.98 2.97 4.16 2.60 4.14

Source of variation dfNo. of tiller/plant No. of productive Tiller/plant Root volume Dry root weight Grain yield (g)/plant

C S C S C S C S C S

Replication 1

Genotypes (unadjusted) 63

Blocks within adjusted 14

Error intra block 49

CD (5%)

CV (%)

0.78 29.07 1.53 27.19 279.19 39.38 128.00 6.57 105.12 45.12

21.95** 27.73** 13.47** 15.24** 789.47** 473.46** 116.30** 70.47** 44.19** 38.63**

4.90 1.33 4.94* 2.17 68.31 2.33 6.47** 2.29 1.65 1.75

2.74 3.38 2.20 1.99 83.24 5.25 2.53 3.32 2.40 1.72

3.48 3.00 3.16 2.86 17.88 3.91 3.411 3.47 2.95 2.64

9.30 9.49 11.66 13.611 20.55 6.66 9.09 18.102 9.88 16.49

** Significance at 1 %, * Significance at 5 % C-control, S-low-moisture stress

Table 1. Analysis of variance for yield and root related characters in traditional rice genotypes evaluated by using PVC

pipes under control and low-moisture stress condition

Variability, heritability and divergence among rice genotypes using PVC pipes

Sr.Characters

Mean ± SE Range PCV (%) GCV (%)h broad

GAM (%)

C S C S C S C S C S C S

2

No.sense (%)

1 Days to 50% flowering 94.59±2.59 85.16±2.57 75.50-110.50 70.50-100.00 7.66 7.99 7.12 7.39 86.24 85.45 13.62 14.08

2 Days to maturity 136.85±3.28123.96±2.70 111.50-164.50105.00-144.00 7.76 6.04 7.37 5.63 90.22 86.86 14.42 10.81

3 Plant height (cm) 82.30±2.29 73.50±2.19 62.50-111.50 51.50-103.50 14.77 15.50 14.49 15.21 96.31 96.21 29.30 30.73

4 Root length (cm) 63.81±1.89 58.78±2.45 34.00-109.00 25.00-95.50 25.92 25.86 25.69 25.51 98.22 97.35 52.45 51.86

5 Root number 89±2.31 73.00±3.05 21.50-153.50 21.50-125.50 34.42 32.32 34.32 32.03 99.43 98.22 70.51 65.41

6 No. of tillers per plant 18.65±1.73 15.74±1.49 9.00-27.50 10.00-23.50 19.01 24.87 16.40 22.37 74.37 80.90 29.13 41.44

7 No. of productive tillers 13.50±1.57 10.47±1.42 5.50-20.50 5.50-16.50 21.14 28.05 17.10 24.52 65.42 76.43 28.49 44.17

8 Root volume 43.30±8.9 29.24±1.9 11.50-89.00 6.50-71.00 46.99 52.87 46.69 52.35 98.69 98.07 95.55 106.81

9 Dry root weight 18.67±1.69 9.55±1.73 6.00-33.50 2.50-31.00 32.39 63.47 40.79 60.75 90.37 91.59 60.29 119.76

10 Grain yield (g)/plant 14.87±1.47 7.69±1.31 5.50-29.50 2.50-25.50 32.39 56.37 30.79 53.90 90.37 91.44 60.29 106.18

per plant

C-control, S-low-moisture stress

Table 2. Estimates of range, mean, variability, heritability and genetic advance for yield and root related characters in

traditional rice genotypes evaluated by using PVC pipes under control and low-moisture stress condition

22

523

Genetic divergence among grain yield and root related

parameters :

Genetic diversity in different groups :

In order to quantify the diversity in 64 genotypes

of rice, 10 quantitative root related characters were considered

and their fitness was assessed using the concept of

Mahalanobis generalized distance (D ).

Based on D values,

64 genotypes were grouped into 12 clusters in control and 13

clusters in low-moisture stress. Maximum of 15 genotypes were

included in cluster X followed by 14 genotypes in cluster VI ,9

genotypes in cluster I, 6 genotypes were present in cluster XI,

four genotypes were included in cluster II and IX, two genotypes

were included in each of cluster III, IV, V, VII, VIII and XII under

control condition ( ). These results are in conformity with

the observations made by Shahidullah (2009). While

Under low-moisture stress condition maximum of 14 genotypes

were represented in both cluster III and VI followed by 11

genotypes in cluster I, 7 genotypes in cluster IX, Three

genotypes in cluster V and VII two genotypes were present in

each of cluster II, IV, VIII, X and XI, Whereas single genotypes

represented the cluster XII and XIII ( ).

The inter cluster D values also ranged widely with a

minimum distance of 11.83 between cluster III and cluster V and

maximum value of 34.78 between cluster II and cluster VIII

under control condition ( ) Whereas minimum distance of

13.82 between cluster II and cluster IV and maximum value of

42.45 between cluster V and cluster XI under low-moisture

stress condition ( ), indicating high diversity among the

genotypes. (Subudhi 2009). Cluster II with four genotypes

and cluster VIII with two genotypes were the most divergent

groups with a maximum inter cluster distance (34.78) under

control condition and Cluster V with 3 genotypes and cluster XI

with two genotypes were the most divergent groups with a

maximum inter cluster distance (42.45) under low-moisture

stress condition. Therefore, inter crossing between these

genotypes would yield better recombinants (Banumathy

2010).

The intra cluster distance varied from 7.36 in cluster III to a

maximum distance of 32.11 in cluster XII in control condition,

whereas the intra cluster distance varied from 5.60 in cluster II

to a maximum distance of 22.07 in cluster I in low-moisture

stress condition (Table 5 & 6). This reveals the presence of

diverse genotypes in different clusters. The selection within the

clusters with maximum intra cluster distance may be exercised

based on the highest areas for the desirable traits, which would

be made use of in improvement through inter varietal

hybridization (Joshi 2008).

2

2

2

Table 3

Table 4

Table 5

Table 6

et al.

et al.,

et al.,

et al.,

Green Farming 7 (3)Kumar et al.

Clusters No. of entries Genotypes

I 9 Doddamullare, China-988, SKAU-98,K-336, SKAU-23, MGD-101, CH-1007,J-192,Andrabasumathi

II 4 Wazulkreer, Jaya199, Kagga,Navalaisaale

III 2 Gowrisanna, Badashiparimalakki

IV 2 Dappa batta, Kaduvalai

V 2 Banavasiselection, Doddibhatta

VI 14 Sri-214, Kyasari-202, Uma-213,Salamsanna, SK339, Zadagi, SKAU-334, Champakali,Ashoka-228f, Jeerga,

Anekombinabatta, Huggibhatta, BI-33,Jeerisanna

VII 2 Kuduvekalanji,Azucena

VIII 2 Chinanapunni, Mukkanna

IX 4 Salambatt ibhara, KH-10/NMS-2,Burmablack, Karimundaga

X 15 Madilaisaamba, Intin, Kempukharu,Hmt, Kougisaale, Nms-2, Mattakhara,Abhilasha,Athnalu, Mysore Mallige,

Banga radagundu , Bang la r i ce ,Elatagyagidda, Kushiadiksham, IR-64

XI 6 Bangaru sanna, Padmarekha, Mallige,Kichadisaamba, Doddiga, Sampige

XII 2 Basumathi, Delhibasumathi

Table 3. Clustering pattern of 64 traditional rice

genotypes evaluated by using PVC pipes

under control condition

Clusters No. of entries Genotypes

I 11 Doddamullare, China-988, SKAU-98,

K-336, SKAU-23, MGD-101, Wazulkreer,

Jaya199, HMT, Mukkanna

II 2 Salamsanna,BI-33

III 14 Sri-214, Kyasari-202, Uma-213, SK339,

Zadagi, SKAU-334, Champakali, J-192,

Banavasiselection, Ashoka-228f, Jeerga,

Anekombinabatta, Kushiadiksham,

Doddibhatta

IV 2 Dappa batta, Delhibasumathi

V 3 Huggibhatta, Gowrisanna,

Madilaisaamba

VI 14 Salambattibhara, KH-10/NMS-2, Kagga,

Kuduvekalanj, Intin, Kempukharu,

Andrabasumathi, Kougisaale,

Chinanapunni, NMS-2,

Badashiparimalakki, Mattakhara,

Abhilasha, Kaduvalai

VII 3 Navalaisaale, Kichadisaamba,

Karimundaga

VIII 2 Azucena, Sampige

IX 7 Athnalu, Mysore mallige,

Bangaradagundu, Banglarice,

Elatagyagidda, Padmarekha, Doddiga

X 2 Jeerisanna, IR-64

XI 2 Bangaru sanna, Mallige

XII 1 Basumathi

XIII 1 Burmablack

Table 4. Clustering pattern of 64 traditional rice

genotypes evaluated by using PVC pipes

under low-moisture stress condition

Analysis of cluster means :

Contribution of characters towards divergence :

All the genotypes were spread

over 12 clusters in control and 13 clusters in low-moisture stress

condition and means were scored across the clusters for all the

10 characters. The highest cluster mean was given the first rank

and next cluster possessing next best means were given 2 , 3

and so on for all the traits (except for days to 50 per cent

flowering and days to maturity where least mean was given

score 1). Based on the overall score across 10 traits, the

clusters were ranked. The lowest scoring cluster were given first

rank and next cluster possessing the score above the previous

one were 2 , 3 and so on. Accordingly, cluster IV with overall

score of 112.5 in control and 98 in low-moisture stress condition

across the 10 characters received highest rank, indicating the

presence of most promising genotypes in this cluster (

). Overall, the clusters could be regarded as useful sources of

genes for yield and its components and the genotypes from

these clusters, therefore, could be used in crop improvement

programmes to incorporate superior drought tolerant traits.

Among

the 10 quantitative characters studied, the most important

character contributing to the divergence under control condition

was grain yield. This was followed by root volume, dry root

weight, root number. Whereas under low-moisture stress

condition most important character contributing to the

divergence was grain yield, followed by dry root weight, root

volume, root length, these traits are responsible for increasing

yield under stress ( ). Hence, these characters should bend rd

nd rd

Table 7 &

8

Table 9

May-June 2016 524

23 Green Farming

Cluster I II III IV V VI VII VIII IX X XI XII

I 32.73 22.23 25.26 21.80 27.80 24.63 25.30 30.80 25.98 30.92 25.49

II 33.07 40.21 28.28 38.85 29.17 34.78 25.71 31.99 24.90 32.75

III 14.02 11.83 21.71 27.24 17.08 26.05 22.47 27.46 21.01

IV 16.59 24.10 31.35 23.99 31.52 26.97 34.26 22.12

V 23.71 24.45 21.66 22.09 22.06 23.93 20.12

VI 28.39 23.59 33.91 27.15 34.55 27.15

VII 23.87 31.45 23.14 29.94 25.77

VIII 29.31 22.78 29.79 23.76

IX 29.84 25.44 28.59

X 29.92 25.38

XI 30.24

XII

26.80

18.88

7.36

7.76

8.62

27.87

9.54

9.71

27.15

25.29

28.17

32.11

Table 5. Average inter and intra cluster distances for yield and root related characters in traditional rice genotypes

evaluated by using PVC pipes under control condition

* Diagonal values indicate intra cluster distances, * Above diagonal values indicate inter cluster distances

Variability, heritability and divergence among rice genotypes using PVC pipes

Cluster I II III IV V VI VII VIII IX X XI XII XIII

I 20.79 20.88 19.45 23.65 20.73 22.44 29.01 20.56 22.07 30.66 20.46 29.50

II 20.30 13.82 28.43 20.81 15.19 19.39 20.18 21.57 21.12 21.40 19.89

III 18.68 22.23 20.02 22.47 30.63 20.55 19.68 31.92 19.31 31.10

IV 25.09 17.80 15.81 23.83 18.90 20.20 25.87 15.83 27.63

V 21.76 31.30 38.06 21.31 21.10 42.45 19.18 41.17

VI 22.69 30.04 19.23 21.26 31.89 18.03 31.45

VII 23.44 23.26 23.55 21.73 23.98 21.21

VIII 28.15 34.75 19.92 27.13 20.33

IX 22.56 31.18 19.24 30.36

X 37.62 21.39 33.96

XI 33.70 15.22

XII 34.17

XIII

22.07

5.60

20.36

6.49

16.43

19.57

19.13

11.18

19.32

11.89

12.37

0.00

0.00

Table 6. Average inter and intra cluster distances for yield and root related characters in traditional rice genotypes

evaluated by using PVC pipes under low-moisture stress condition

* Diagonal values indicate intra cluster distances, * Above diagonal values indicate inter cluster distances

Sr.No. CharacterContribution (%)

C S

1 Days to 50 per cent flowering 0.24 1.38

2 Days to maturity 0.14 0.79

3 Plant height 3.27 6.00

4 Root length (cm) 8.82 10.46 (IV)

5 Root number 13.19 (IV) 2.67

6 No. of tiller per plant 0.19 0.74

7 No. of productive tiller per plant 0.00 0.49

8 Root volume 22.22 (II) 15.02 (III)

9 Dry root weight 18.05 (III) 18.65 (II)

10 Grain yield (g) 33.82 (I) 44.19 (I)

Total 100 100

*C-control, S-low-moisture stress

Table 9. Per cent contribution of each character towards

divergence in traditional rice genotypes

evaluated by using PVC pipes

given importance during hybridization and selection in the

segregating population. (Banumathy 2010).

The genotypes Azucena, SKAU-98, Bangaradagundu,

Kougisaale, Navalaisaale, Mukkanna, Sampige and Doddiga

colud be utilized for further breeding programmes to obtain

suitable varieties for drought as these genotypes are with early

to maturity, more number of tillers and number of productive

tillers, higher root length, root number and more importantly

higher grain yield both under control and low-moisture stress

condition.

et al.,

CONCLUSION

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525

24

Green Farming 7 (3)Kumar et al.

Clusters X X X X X X X X X X Overall score Rank1 2 3 4 5 6 7 8 9 10

I 95.611

(3) (2) (7) (8) (9) (6) (9) (7) (5) (8)

II 93.25

(5) (8.5) (4) (2) (2) (1) (2) (1) (1) (2)

III 95.00

(9) (10) (2) (11) (10) (4) (1) (5) (11) (12)

IV 99.25

(11) (8.5) (12) (12) (11) (12) (11) (12) (12) (11)

V 90.25

(4) (4) (10) (10) (12) (11) (12) (4) (8) (4)

VI 99.35

(12) (11) (5) (7) (8) (7) (7) (11) (9) (7)

VII 80.50

(1) (1) (8) (1) (5.5) (5) (5) (10) (2) (1)

VIII 88.50

(2) (5) (1) (9) (1) (10) (3.5) (9) (10) (9)

IX 94.00

(6) (6) (9) (5.5) (3) (8) (8) (2) (4) (3)

X 94.46

(7) (12) (6) (3) (7) (2) (6) (8) (7) (6)

XI 90.00

(10) (3) (3) (4) (5.5) (9) (10) (3) (3) (5)

XII 94.75

(8) (7) (11) (5.5) (4) (3) (3.5) (6) (6) (10)

130.61 81.611 60.056 14.94 18.16 12.72 83.160 49.05 13.77 64 7

135.75 85.00 71.75 25.75 22.75 15.62 132.12 79.00 18.12 28.5 1

139.50 88.00 48.50 10.75 19.00 16.25 85.00 27.25 12.25 75 9

135.75 63.75 43.75 10.00 16.00 12.25 69.50 26.50 12.27 112.5 12

131.75 74.75 56.00 9.00 17.00 11.25 93.50 34.25 15.75 79 10

141.036 84.07 61.57 15.50 18.03 13.28 71.85 30.78 14.10 84 11

125.25 81.50 82.50 21.50 18.25 14.25 76.50 62.00 20.50 39.5 2

134.00 97.00 60.00 33.25 17.50 14.75 81.25 30.50 12.50 59.5 5

134.37 75.87 62.00 24.37 18.00 12.87 119.87 50.00 16.75 54.5 3

142.46 83.26 70.10 20.00 19.56 13.90 82.66 44.03 15.13 64 8

131.25 86.08 64.91 21.50 17.91 12.33 119.08 52.50 15.50 55.5 4

135.50 68.50 62.00 22.50 19.25 14.75 83.75 47.00 12.25 64 6

Table 7. Cluster means for yield and root related characters in traditional rice genotypes evaluated by using PVC pipes

under control condition

Figures in parenthesis, indicate the ranks based on cluster mean, highest (1) to lowest (12) except for days to 50 per cent flowering and days to

maturity. Overall score is the summation of rank number for 10 characters.

X - Days to 50 per cent flowering X - Root number X - Dry root weight (g)

X - Days to maturity X - No. of tiller per plant X - Grain yield (g) per plant

X - Plant height X - No. of productive tiller per plant

X - Root length (cm) X - Root volume (cc)

1 5 9

2 6 10

3 7

4 8

where,

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3199-3207.

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Genetic diversity studies of promising varieties of eastern

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7 :

45 :

12 :

27 :

10 :

8

46 :

31 :

th

rd

2

25 Green Farming

May-June 2016 526Variability, heritability and divergence among rice genotypes using PVC pipes

Clusters X X X X X X X X X X Overall score Rank1 2 3 4 5 6 7 8 9 10

I

II 95.25 136.00 74.50 54.25 19.50 21.25 14.75 80.50 38.25 7.50 66 5

(13) (13) (6) (10) (3) (1) (1) (6) (4) (9)

III 87.14

(10) (10) (4) (9) (3) (1) (1) (6) (4) (9)

IV 92.50

(12) (11.5) (12) (7) (9.5) (13) (12) (5) (6) (10)

V 88.33 126.50 73.16 65.33 6.50 14.16 10.00 39.66 14.16 9.00 90.5 0

(11) (9) (8.5) (4) (13) (9) (7) (13) (12) (4)

VI 81.53 122.32 72.14 60.64 7.25 17.82 12.10 73.35 24.50 7.60 68.5 7

(4) (4) (10) (6) (9.5) (5) (3) (8) (11) (8)

VII 85.50 123.16 73.16 48.33 9.16 14.33 9.83 96.66 36.83 8.83 67 6

(7.5) (5) (8.5) (12) (6) (7) (8) (3) (5) (5)

VIII 79.75 123.50 60.75 74.50 26.50 15.50 10.25 90.75 67.50 12.25 41.5 2

(3) (6) (11) (1) (1.5) (6) (6) (4) (1) (2)

IX 84.35 125.00 75.78 69.00 13.14 18.14 11.57 73.42 27.21 10.28 49 4

(5) (8) (3) (2) (5) (3) (4) (7) (9) (3)

X 85.50 128.75 73.50 29.75 7.50 12.50 8.00 55.25 10.00 13.75 97 11

(7.5) (11.5) (7) (13) (8) (12) (13) (11) (13) (1)

XI 85.25 124.75 84.50 68.50 14.50 18.00 11.25 122.50 63.50 3.76 46 3

(6) (7) (2) (3) (4) (4) (5) (1) (2) (12)

86.22 119.22 75.09 58.40 8.18 14.31 9.50 71.95 29.22 8.40 72.5 8

(9) (3) (5) (8) (7) (8) (9.5) (9) (8) (6)

126.64 75.28 54.28 6.92 14.03 9.14 67.25 25.46 6.14 97 12

128.75 57.75 58.75 7.25 12.25 8.75 86.75 35.50 6.75 98 13

XII 75.50 118.50 52.50 64.50 7.00 14.00 9.50 54.00 35.00 3.50 84.5 9

(1) (2) (13) (5) (11) (11) (9.5) (12) (7) (13)

XIII 76.50 111.00 90.50 50.50 26.50 18.50 12.50 113.50 48.50 8.00 32.5 1

(2) (1) (1) (11) (1.5) (2) (2) (2) (3) (7)

Table 8. Cluster means for yield and root related characters in traditional rice genotypes evaluated by using PVC pipes

under low-moisture stress condition

Figures in parenthesis, indicate the ranks based on cluster mean, highest (1) to lowest (13) except for days to 50 per cent flowering and days to

maturity. Overall score is the summation of rank number for 10 characters.