ISSN 1313 - 8820Volume 7, Number 1

March 2015

2015

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Genetics and Breeding

Atanas Atanasov (Bulgaria)Nikolay Tsenov (Bulgaria)Max Rothschild (USA)Ihsan Soysal (Turkey)Horia Grosu (Romania)Bojin Bojinov (Bulgaria)Stoicho Metodiev (Bulgaria)

Nutrition and Physiology

Nikolai Todorov (Bulgaria)Peter Surai (UK)Zervas Georgios (Greece)Ivan Varlyakov (Bulgaria)

Production Systems

Dimitar Pavlov (Bulgaria)Bogdan Szostak (Poland)Dimitar Panaiotov (Bulgaria)Banko Banev (Bulgaria)Georgy Zhelyazkov (Bulgaria)

Agriculture and Environment

Georgi Petkov (Bulgaria)Ramesh Kanwar (USA)Martin Banov (Bulgaria)

Product Quality and Safety

Marin Kabakchiev (Bulgaria)Stefan Denev (Bulgaria)Vasil Atanasov (Bulgaria)

English Editor

Yanka Ivanova (Bulgaria)

2015

ISSN 1313 - 8820 Volume 7, Number 1March 2015

Correlation between grain yield and yield components in winter barley varieties

1 2 2 1 1 1N. Markova Ruzdik *, D.Valcheva , D.Vulchev , Lj. Mihajlov , I. Karov , V. Ilieva

1Faculty of Agriculture, "Goce Delchev” University, 2000 Stip, Macedonia2Institute of Agriculture, 8400 Karnobat, Bulgaria

Abstract. The objective of this study was to determine the correlation between yield and its components and their direct and indirect effects on grain yield in two-row winter barley varieties. The experimental work was conducted during the period of 2012-2014 on the research fields of the Faculty of Agriculture, in two different areas in the Republic of Macedonia, Ovche Pole and Strumica. As far as material is concerned, 21 genotypes were used with Macedonian, Serbian,

2Croatian and Bulgarian origin. Significant and positive coefficient of correlations were obtained between grain yield and number of spike per m , number of productive tillers per plant and grain weight per plant, number of grain per spike and grain weight per spike, grain weight per spike and 1000 grains weight in

2both localities. The highest direct effect to grain yield was obtained by number of spikes per m in both localities. Therefore, this trait can be used as a criterion in breeding to improve the yield of barley varieties.

Keywords: correlation, yield, path coefficient analysis, barley

AGRICULTURAL SCIENCE AND TECHNOLOGY, VOL. 7, No 1, pp , 201540 - 44

Introduction weight of grains per spike (Dyulgerova, 2012). The aim of this study was to determine the correlation between

yield and its components and their direct and indirect effects on grain Barley is one of the most important crops because it's used as yield in winter two-row barley genotypes.raw material in beer production and animal feed, cultivated

successfully in a wide range of climate. Grain yield is a complex quantitative trait controlled by a large number of genes and is highly

Material and methodsinfluenced by environmental, morphological and physiological characters. Grain yield in barley, like other crops, is a function of many traits which have interrelation among themselves and affect The experiment was carried out during the period 2012 – 2014 the grain yield directly or indirectly. in the research fields of the Faculty of Agriculture, "Goce Delchev”

Correlation coefficient and path coefficient analyses are used University in two localities in the Republic of Macedonia. The first widely in many crop species by plant breeders to define the nature of one was Ovche Pole with altitude between 200 – 400 m and soil type complex interrationships among yield components (Dofing and smolnica and the other one was Strumica with 280 m altitude with Knight, 1994; Hosin Babaiy et al., 2011; Al-Tabbal and Al-Fraihat, alluvial soil type. Compared to Strumica location, Ovche Pole locality 2012). Correlation coefficient is very important to determine the traits is characterized by lower average temperatures and lower amount that directly affect the grain yield. The path coefficient analysis is one of rainfall as well. The average monthly values for the temperature of the statistical tools which is used to determine the direct or indirect and rainfall in the period when this research took place did not differ effects of any yield component on grain yield in relation to the other significantly, compared to the general long-term weather data for yield components. Correlation coefficient and path coefficient both of the regions.analysis assist to identify the traits that are useful as selection criteria In total 21 two-row winter barley genotypes were used in this to improve yield (Singh 1987; Milomirka et al., 2005; Drikvand et al., study. Five of them are Macedonian (Hit, Izvor, Egej, Line 1 and Line 2011; Khaiti, 2012). 2), two varieties are Serbian (NS 525 and NS 565), two varieties are

Some studies reported that grain yield was determined by three Croatian (Zlatko and Rex) and the other 12 varieties are with 2yield components, spike number per m , number of grain per spike Bulgarian origin (Obzor, Perun, Emon, Lardeya, Orfej, Imeon,

and grain weight per spike (Grafius, 1964; Fathi and Rezaie, 2000). Zagorec, Asparuh, Kuber, Sajra, Devinija andOdisej). On the other hand, Singh et al. (1987) found that grain yield in barley The experiment was conducted in a randomized block design

2significantly correlated with plant height and this component had with three replications. Each replication plot had 1 m , consisted of high positive direct effects on yield. Some researchers reported 10 rows and the amount of cultivated seed was evaluated at 500

2positive and significant correlation between plant height and grain seeds per m . The seeds were hand sown 3 to 5 cm deep on the yield (Kisana et al., 1999; Bhutta et al., 2005; Jabbari at al., 2010; same day in both localities. The method of setting up the experiment Biroland Necmettin, 2011; Niazi-Fard et al., 2012). In many studies, was the same in both localities. The standard growing measures

2 it has been shown that the number of spike in m has a positive direct were applied during the vegetation. During the study period effect on grain yield (Jabbari at al., 2010; Drikvand et al., 2011). phonological phase, degree of lodging and diseases were recorded. Akdeniz et al. (2004) observed positive and significant correlation Then plant samples were randomly chosen from the middle part of

2between grain yield and number of spike per m . Significant positive each replication plot from both localities. Plants were evaluated for 2correlation was determined between grain number per spike and traits including: number of spikes m , plant height (cm), total tillers

* e-mail: natalija.markova@ugd.edu.mk

40

41

number per plant, number of productive tillers per plant, spike length Correlation between yield and components of yield, coefficient (cm), number of grain per spike, number of sterile spikelets per of variation and path coefficient analysis were performed using spike, grain weight per spike (g), grain weight per plant (g) and 1000 SSPS.grains weight (g).

Table 1. Average, minimum, maximum and coefficient of variation for examined traits of barley varieties in both localities

Loca

lity

Str

umic

aO

vche

Pol

e Average

Min.

Max.

CV, %

Average

Min.

Max.

CV, %

673

567

776

8.56

711

590

811

9.57

104

99

110

3.19

102

98

109

3.18

18

14

20

7.12

18

16

20

7.11

8

7

9

8.78

9

8

10

7.29

8.5

7.2

9.5

7.77

8.6

7.3

10.0

8.60

27

26

29

2.57

27

26

29

2.55

2

1

3

23.32

1

1

3

49.46

1.28

1.23

1.38

3.15

1.27

1.20

1.39

4.36

9.53

7.54

10.65

8.64

9.93

8.43

11.26

6.93

47.30

45.93

49.63

1.82

46.37

42.86

48.57

3.18

4282

3120

5277

13.51

4863

3423

5821

14.11

2N

umbe

r of

spi

kes,

m

Pla

nt h

eigh

t, cm

Tota

l till

er n

umbe

r pe

r pl

ant

Num

ber

of p

rodu

ctiv

etil

lers

per

pla

nt

Spi

ke le

ngth

, cm

Num

ber

of g

rain

s pe

r sp

ike

Num

ber

of s

teril

e sp

ikel

ets

per

spik

e

Gra

in w

eigh

t pe

r sp

ike,

g

Gra

in w

eigh

t pe

r pl

ant,

g

1000

gra

ins

wei

ght,

g

Yie

ld, k

g/ha

Table 2. Correlation coefficient between yield and components of yield of barley varieties from locality Ovche Pole

*, ** Statistical significance at P<0.05 and P<0.01.

PH TTNP NPTP SL NGS NSSS GWS GWP 1000 GW Y2NS mComponents of yield

Components of yield

2 2Number ofspikes, m (NS m )

Plant height (PH)

Total tiller number per plant (TTNP)

Number of productive tillers per plant (NPTP)

Spike length (SL )

Number of grains per spike (NGS)

Number of sterile spikelets per spike (NSSS)

Grain weight per spike (GWS)

Grain weight per plant (GWP)

1000 grains weight (1000 GW)

Yield (Y)

0.936**

0.452*

0.047

0.123

0.119

-0.207

-0.015

-0.142

0.209

0.055

1

-0.155

-0.007

0.436*

0.047

-0.093

-0.006

-0.102

0.559**

0.079

1

0.166

0.303

0.363

0.919**

-0.475

-0.009

-0.249

0.036

1

-0.480*

-0.109

0.152

-0.033

-0.085

0.826**

0.342

1

-0.129

0.087

-0.026

-0.286

0.120

0.480

1

-0.473

-0.126

-0.111

-0.070

-0.034

1

0.127

-0.222

-0.146

-0.422

1

0.112

0.337

0.500*

1

-0.020

0.415

1

0.437*

1

1

Table 3. Correlation coefficient between yield and components of yield of barley varieties from locality Strumica

*, ** Statistical significance at P<0.05 and P<0.01.

PH TTNP NPTP SL NGS NSSS GWS GWP 1000 GW Y2NS m2 2Number of spikes, m (NS m )

Plant height (PH)

Total tiller number per plant (TTNP)

Number of productive tillers per plant (NPTP)

Spike length (SL)

Number of grains per spike (NGS)

Number of sterile spikelets per spike (NSSS)

Grain weight per spike (GWS)

Grain weight per plant (GWP)

1000 grains weight (1000 GW)

Yield (Y)

0.901**

0.238

0.210

0.118

0.139

-0.059

-0.021

0.072

0.376

0.149

1

-0.228

0.147

0.168

-0.121

-0.082

0.151

0.184

0.823**

0.407

1

0.196

0.297

0.583**

0.569**

-0.051

0.043

0.064

0.320

1

-0.367

-0.070

0.140

-0.028

0.043

0.685**

0.240

1

-0.110

0.270

0.141

-0.414

-0.293

0.183

1

-0.339

-0.304

0.029

0.116

0.184

1

0.109

-0.325

0.017

0.365

1

0.107

-0.122

0.239

1

0.131

0.464*

1

0.260

1

1

42

Tab

le 4

. Path

coeffic

ient

analy

sis

show

ing t

he d

irect

and indirect

eff

ect

of

yie

ld c

om

ponents

on g

rain

yie

ld in locality

Ovche P

ole

Com

pone

nts

of y

ield

Dire

ct e

ffect

Indi

rect

effe

ct

2N

S m

PH

TT

NP

NP

TP

SL

NG

SN

SS

SG

WS

22

Num

ber

of s

pike

s, m

(NS

m)

Pla

nt h

eigh

t (P

H)

Tota

l tille

r nu

mbe

r pe

r pl

ant (

TTN

P)

Num

ber

of p

rodu

ctiv

e til

lers

per

pla

nt (N

PTP

)

Spi

ke le

ngth

SL

Num

ber

of g

rain

s pe

r sp

ike

(NG

S)

Num

ber

of s

teril

e sp

ikel

ets

per

spik

e (N

SS

S)

Gra

in w

eigh

t per

spi

ke (G

WS

)

Gra

in w

eigh

t per

pla

nt (G

WP

)

1000

gra

ins

wei

ght (

1000

GW

)

1.1

1885

30

0.0

0564

70

-0.0

0403

60

0.0

1970

80

0.0

1755

60

0.3

7622

00

0.0

0000

54

-0.0

6191

20

-0.0

0287

20

0.2

6806

10

0.0

0246

77

0.0

0008

07

0.0

0220

73

0.0

0222

96

-0.1

7795

21

-0.0

0000

07

0.0

2971

78

-0.0

0047

68

-0.0

4154

95

-0.0

0167

49

0.0

0664

16

-0.0

0389

74

-0.0

4740

37

0.0

0000

05

0.0

0674

84

-0.0

0087

02

-0.0

0187

64

0.00

9854

0

-0.0

0256

32

-0.0

4176

04

-0.0

0000

01

-0.0

0941

06

-0.0

0104

25

0.1

1687

46

-0.0

0740

86

-0.0

2633

54

-0.0

0000

16

0.0

0204

31

-0.0

0263

94

0.0

1259

89

-0.0

1279

15

0.0

0000

07

0.0

0526

25

0.0

0136

42

-0.0

2492

97

0.0

0000

26

-0.0

5113

93

0.0

0002

58

-0.0

0160

84

-0.0

2117

39

0.0

0071

51

-0.0

2734

22

-0.0

0010

34

0.1

4984

61

-0.5

3704

94

-0.0

0061

55

-0.0

0061

35

-0.0

0065

04

-0.0

0149

23

0.31

0757

7

0.00

0001

9

-0.1

4433

20

0.00

0491

3

0.00

0104

9

-0.0

0563

65

0.00

2106

7

0.18

0585

6

-0.5

2921

75

-0.0

0071

15

0.00

0448

0

-0.0

0137

96

-0.0

0059

69

0.1

4209

43

-0.0

0125

36

0.0

0058

93

-0.0

0831

68

0.1

2531

15

0.0

0190

30

-0.0

0201

80

-0.0

2237

71

0.0

0234

35

0.48

8938

8

Tota

l ind

irect

effe

ct

0.02

1176

8

-0.4

6432

4

0.0

0629

6

-0.0

0630

8

0.0

2175

7

-0.0

2159

3

0.1

7945

6

0.0

0000

1

-0.0

7478

9

-0.0

0325

4

0.2

0319

0

-0.1

7342

22

-0.0

0003

95

-0.0

0175

97

0.00

0926

3

-0.0

0163

27

-0.0

0225

73

-0.0

0000

06

-0.0

3460

88

-0.0

0022

69

0.18

5729

6

0.00

1711

0

-0.0

0146

51

0.01

8111

7

-0.0

0833

91

-0.0

0338

60

-0.0

0000

13

-0.0

0222

88

GW

P10

00 G

W

Tab

le 5

. Path

coeffic

ient

analy

sis

show

ing t

he d

irect

and indirect

eff

ect

of

yie

ld c

om

ponents

on g

rain

yie

ld in locality

Str

um

ica

Com

pone

nts

of y

ield

Dire

ct e

ffect

Indi

rect

effe

ct

2N

S m

PH

TT

NP

NP

TP

SL

NG

SN

SS

SG

WS

22

Num

ber

of s

pike

s, m

(NS

m)

Pla

nt h

eigh

t (P

H)

Tota

l tille

r nu

mbe

r pe

r pl

ant (

TTN

P)

Num

ber

of p

rodu

ctiv

e til

lers

per

pla

nt (N

PTP

)

Spi

ke le

ngth

SL

Num

ber

of g

rain

s pe

r sp

ike

(NG

S)

Num

ber

of s

teril

e sp

ikel

ets

per

spik

e (N

SS

S)

Gra

in w

eigh

t per

spi

ke (G

WS

)

Gra

in w

eigh

t per

pla

nt (G

WP

)

1000

gra

ins

wei

ght (

1000

GW

)

1.0

6634

-0.0

1851

0.0

0264

0.0

0912

-0.0

0127

-0.0

7556

-0.0

0539

0.5

5592

0.0

1403

-0.0

5585

-0.0

0481

37

0.0

0034

59

0.0

0097

62

-0.0

0013

84

0.0

2561

47

0.0

0059

32

-0.2

0402

25

0.0

0275

11

0.0

1273

48

0.0

0122

53

-0.0

0111

30

0.0

0041

26

0.0

2297

01

-0.0

0145

61

-0.0

3891

44

0.0

0416

88

-0.0

0821

06

0.0

0218

04

-0.0

0002

16

-0.0

0219

12

-0.0

0076

04

0.0

7782

87

0.0

0818

32

-0.0

0938

35

-0.0

0046

34

-0.0

0876

49

0.0

0223

26

-0.0

1556

57

0.0

0798

67

0.0

0675

84

-0.0

1390

30

0.0

0158

01

0.0

2390

45

-0.0

0071

59

0.0

0458

01

-0.0

0098

69

0.3

8080

49

0.0

0060

36

-0.0

0843

40

0.1

3342

07

0.0

0089

83

-0.0

1027

72

0.0

0449

16

-0.0

4596

81

-0.3

9135

00

0.0

0129

60

0.0

0036

97

-0.0

0025

54

-0.0

0005

46

-0.0

5175

84

-0.0

0129

43

-0.1

1729

84

-0.0

0499

89

0.0

0037

23

-0.0

0377

69

0.0

0037

20

-0.0

1382

74

-0.3

6149

22

0.0

0562

84

0.0

0007

66

0.0

0105

83

-0.0

0023

36

0.11

6232

0

0.00

6017

2

0.00

0044

9

0.00

3329

9

0.11

4099

3

0.00

2258

8

0.00

0631

1

0.1

3969

17

-0.0

0859

07

0.27

7250

7

Tota

l ind

irect

effe

ct

-0.0

2273

27

-0.2

5699

0

-0.0

1142

3

0.0

0504

9

0.0

0648

6

0.0

0004

1

-0.0

5651

8

-0.0

0142

9

0.9

9287

2

0.0

3408

0

-0.0

8093

2

-0.2

4312

75

-0.0

0272

16

0.0

0044

36

-0.0

0110

39

0.0

0010

41

-0.0

1140

95

-0.0

0099

23

0.4

5752

18

0.0

0571

28

0.2

0900

44

-0.0

0549

88

0.0

0153

95

0.0

0519

10

0.0

0006

47

-0.0

0324

91

-0.0

0034

51

0.1

7789

43

GW

P10

00 G

W

43

between total tiller number per plant with grain weight per plant in the Results and discussionlocality Strumica was not proved in locality Ovche Pole. On the other side, the significant and positive correlation coefficients that have In Table 1 are given the values for average, minimum, maximum been proven the properties plant height with number of spikes per and coefficient of variation of all tested traits in both localities. The

22 m , plant height with yield and total tiller number per plant with average values for number of spikes per m , number of productive

number of productive tillers per plant for locality Ovche Pole were not tillers per plant, spike length, grain weight per plant and yield for observed for locality Strumica. The differences in correlations in both locality Strumica are higher than locality Ovche Pole. That is locations are probably due to the different climatic conditions in the probably consequence to the favorable climatic conditions in the two localities.locality Strumica. The highest coefficient of variation in both localities

The purpose of using the path coefficient analysis in this study has the number of sterile spikelets per spike while the lowest was to obtain further information about the interrelationships coefficient of variation has 1000 grain weight (1.82%) in locality between the yield and yield components and about the influence of Ovche Pole and number of grains per spike (2.55%) in locality yield components on grain yield. In Table 4 and 5 are presented the Strumica. direct and indirect effects of yield components on grain yield for both The correlation between grain yield and yield components for localities. In our study, path coefficient analysis for locality Ovche the examined traits in barley varieties for locality Ovche Pole are

2 Pole showed that number of spikes per m has the highest direct presented in Table 2. Significant and positive correlation was 2 positive effect on grain yield, followed by number of grains per spike. determined between grain yield and number of spikes per m (r =

2For locality Strumica number of spikes per m and grain weight per 0.936). A similar significant positive coefficient was also observed by spike have the highest direct positive effect on yield. Similar direct Ataei (2006), Jabbari at al. (2010), Drikvand et al. (2011). Plant positive effect on grain yield was observed by Budakli Carpici and height is an important trait directly linked with the productive Celik (2012). These results indicate that an increase in any of these potential of the plant and many researchers require correlation yield components causes some increase in yield. Indirect effect on between plant height and yield. In our study the correlation between yield have the properties total tiller number per plant and weight of grain yield and plant height was significant and positive (r = 0.452). grain per plant for locality Ovche Pole and for locality Strumica the This means that the varieties tested in the locality Ovche Pole have properties number of sterile spikelets per spike and plant height.higher values for this property. According to Kisana et al. (1999),

Bhutta et al. (2005), Jabbari at al. (2010), Drikvand et al. (2011) and Niazi-Fard et al. (2012) significant and positive correlation between grain yield and plant height was also observed. Significant and Conclusionpositive correlation was determined between number of productive tillers per plant and grain weight per plant (r = 0.919). Grain number

Through correlation and path coefficient analysis it was per spike is an important yield component and is usually used as a

observed that in locality Ovche Pole the grain yield depends on the selection trait in barley breeding programmes. In our study the 2number of spikes per m and the plant height while in locality correlation between number of grains per spike and grain weight per

Strumica the grain yield depends only on the number of spikes per spike was significant and positive (r = 0.826). A similar significant and 2m . The number of productive tillers per plant has a crucial role to positive coefficient was also observed by Dyulgerova (2012).

grain weight per plant. In both localities, the trait 1000 grains weight Positive and significant correlation was obtained between total tiller

has strong influence on grain weight per spike. number per plant and number of productive tillers per plant (r =

The highest direct positive effect on grain yield had the number 20.500). Number of spikes per m showed significant positive 2of spikes per m in both localities. In selecting the productive variety relationship with plant height (r = 0.437). 1000 grains weight is an

in locality Ovche Pole the established indirect effect of total tiller important yield component and it is influenced by genetic and

number per plant and in locality Strumica the number of sterile environmental factors. In our study, 1000 grains weight showed

spikelets per spike should be taken into account. In other significant and positive correlations with grain weight per spike (r =

examinations more importance should be given to the traits which 5.559) and with total tillers number per plant (r = 0.436). It was also

have direct positive effect on yield as criteria in breeding to improve determined that 1000 grains weight and grain yield were non-

the yield of barley varieties.significantly related. Similar results were reported by Drikvand et al. (2011) and Budakli Carpici and Celik (2012).

In Table 3 are given the coefficient of correlation between grain Referencesyield and yield components for the examined traits in barley varieties

for locality Strumica. Significant and positive coefficient of 2 correlation between yield and number of spikes per m (r = 0.901) Akdeniz H, Keskin B, Yılmaz I and Oral E, 2004. A research on

was also obtained in locality Strumica. As in locality Ovche Pole, in yield and yield components of some barley cultivars. Yüzüncü Yil locality Strumica, the correlation between number of grains per spike University. Journal of Agriculture Science, 14, 119-125.and grain weight per spike was significant and positive (r = 0.685). Al-Tabbal JA and Al-Fraihat AH, 2012. Genetic variation Grain weight per spike showed significant and positive relationship heritability, phenotypic and genotypic correlation studies for yield with 1000 grain weight (r = 0.823). Positive and significant and yield components in promising barley genotypes. Journal of correlation was obtained between grain weight per plant with total Agricultural Science, 4, 193-210.tiller number per plant (r = 0.583) and number of productive tillers per Ataei M, 2006. Path analysis of barley (Hordeum vulgare L.) yield. plant (r = 0.569). Plant height showed significant and positive Ankara University, Faculty Journal of Agriculture Science, 12, 227-relationship with total tiller number per plant (r = 0.464). 232.

Comparing the correlation coefficients in both localities it can be Bhutta WM, Barley T and Ibrahim M, 2005. Path-coefficient concluded that the obtained significant and positive correlation analysis of some quantitative characters in husked barley. Caderno

44

de pesquisa, Série biologia, 17, 65-70. Zolfaghari F, 2010. Correlation and path analysis of morphological Birol TA and Necmettin CEL, 2011. Determination of seed yield traits associated with grain yield in drought stress and non-stress and some yield components through path and correlation analyses conditions in barley Agronomy. Journal Pajouhesh and Sazandegi, in many sixrowedbarley (Hordeum vulgare conv. hexastichon). 93, 112-119.African Journal of Agricultural Research, 6, 4902-4905. Khaiti M, 2012. Correlation between grain yield and its components Budakli Carpici E and Celik N, 2012. Correlation and Path in some Syrian barley. Journal of Applied Sciences Research, 8, Coefficient Analyses of Grain Yield and Yield Components in Two- 247-250.Rowed of Barley (Hordeum vulgare convar. distichon). Varieties Kisana NS, Tahir M, Mujahid MY and Ahmed I, 1999. Variability Notulae Scientia Biologicae, 4, 128-131. and relationship between morpho-phenological traits and grain yield Dofing SM and Knight CW, 1994. Yield component compensation in winter and facultative barley under stress environments. Pakistan in uniculm barley lines. Agronomy Journal, 86, 273-276. Journal of Biological Science, 2, 767-771. Drikvand R, Samiei K and Hossinpor T, 2011. Path coefficient Milomirka AM, Paunovic A, Djurovic D and Knezevic D, 2005. analysis in hull-less barley under rainfed condition. Australian Correlation and path coefficient analysis for yield and yield Journal of Basic and Applied Sciences, 5, 277-279. components in winter barley. Acta Agriculture Serbica, 20, 3-9.Dyulgerova B, 2012. Correlations between grain yield and yield Niazi-Fard A, Nouri F, Nouri A, Yoosefi B, Moradi A and Zareei A, related traits in barley mutant lines. Agriculture Science and 2012. Investigation of the relationship between grain yield andyield Technology, 4, 208-210. components under normal and terminal droughtstress conditions in Fathi G and Rezaie K, 2000. Path analysis of barley yield and yield advanced barley lines (Hordeumvulgar) using path analysis in components in Ahvaz region. Agriculture Science and Industrial, 14, Kermanshah province. International Journal of Agriculture and Crop 39-48. Sciences, 4, 1885-1887.Grafius JE, 1964. Geometry for Plant Breeding. Crop Science, 4, Singh MK, Pandey RL and Singh RP, 1987. Correlation and path 241-246. coefficient analysis in barley grown on saline soil. Current Hosin Babaiy A, Aharizad S, Mohammadi A and Yarnia M, 2011. Agriculture, 11, 55-58. Survey, correlation of yield and yield components in 40 lines barley Singh RM, 1978. Correlation and co heritability studies in certain (Hordeum vulgare L.) in region Tabriz. Middle-East Journal of gamma ray induced mutants of barley (Hordeum vulgare). Barley Scientific Research, 10, 149-152. Genetics Newsletter, 8, 91-92.Jabbari M, Siahsar BA, Ramroodi M, Koohkan ShA and

Review

Genetics and Breeding

Nutrition and Physiology

Production Systems

Molecular mechanisms and new strategies to fight stresses in egg-producing birds E. Shatskikh, E. Latypova, V. Fisinin, S. Denev, P. Surai

Gene action in the inheritance of date to ear emergence and time to physiological maturity in bread wheat crosses (Triticum aestivum L.)N. Tsenov, T. Gubatov, E. Tsenova

Productivity and stability of the yield from common winter wheat cultivars developed at IPGR Sadovo under the conditions of Dobrudzha region P. Chamurliyski, E. Penchev, N. Tsenov

Effectof black (stem) rust (Puccinia Graminis F.SP. Tritici) attack to the spike characteristics in Polishwheat (Triticum Polonicum L.)H. Stoyanov

Analysis of DNA polymorphism of CAST gene in Local Karnobat and Stara Zagora sheep breedsD. Hristova, S. Georgieva, S. Tanchev

Correlation between grain yield and yield components in winter barley varieties N. Markova Ruzdik, D.Valcheva, D.Vulchev, Lj. Mihajlov, I. Karov, V. Ilieva

Genetic diversity in different accessions of oat (Avena sativa L.)T. Savova, B. Dyulgerova, G. Panayotova

Interspecific hybridization in cotton and its use in breedingA. Stoilova, I. Saldzhiev

Influence of the direction of crossing on heterosis and transgression events in relation to the length of the vegetative period of Burley tobaccos variety group Y. Dyulgerski, T. Radoukova, L. Dospatliev

The performance of female dairy calves fed texturized starters with different protein sources E. Yavuz, N. Todorov, G. Ganchev, K. Nedelkov

Feeding value estimation of spring forage pea (Pisum sativum L.) in organic cultivationI. Nikolova, N. Georgieva, Y. Naydenova

Treatment of post harvest residues with cellulose decomposing preparationsI. Effect on grain yield from wheatG. Milev, I. Iliev, A. Ivanova

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Seasonal dynamics of important for Coriandrum sativum virus pathogensB. Dikova, H. Lambev

Crop relationship "yield-evapotranspiration" for green beanR. Kalaydzhieva, D. Davidov, A. Matev, V. Kuneva

Species composition and density of weeds in a wheat crop depending on the soil tillage system in crop rotationP. Yankov, M. Nankova, M. Drumeva, D. Plamenov, B. Klochkov

Assessment of Bulgarian Black Sea coastal water using the biological quality element phytoplanktonD. Petrova, D. Gerdzhikov

Evaluation on reaction of late maturing maize hybrids and lines to Fusarium ear rotM. Haddadi, M. Zamani

Contemporary state of macrophytobenthos along the Bulgarian coast of the Black SeaD. Petrova, V. Vachkova, D. Gerdzhikov

Bioconversion of nitrogen in eco-technical system for eggs productionA. Gencheva

Mixed viral infections in tomato as a precondition for economic lossN. Petrov

Storage and its effect on the antioxidant capacity of dried Bulgarian Chrysanthemum balsamita L.A. Popova, D. Mihaylova, I. Alexieva

Correcting the breadmaking quality of flour damaged by Sunn pest (Eurygaster integriceps) by using apple pectinI. Stoeva

Investigation the influence of dietary fiber on the rheological properties of alginate beadsZ. Manev, N. Petkova, P. Denev, D. Ludneva, S. Zhelyazkov

Occurrence of Pseudomonas syringae pv. tomato in BulgariaM. Stoyanova, K. Aleksandrova, D. Ganeva, N. Bogatzevska

Agriculture and Environment

Product Quality and Safety

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Мо, Greek = Gr, Georgian = Geor., Japanese = Jа, Chinese = Ch, Arabic = Аr, etc.)The following order in the reference list is recommended:Journal articles: Author(s) surname and initials, year. Title. Full title of the journal, volume, pages. Example:Simm G, Lewis RM, Grundy B and Dingwall WS, 2002. Responses to selection for lean growth in sheep. Animal Science, 74, 39-50Books: Author(s) surname and initials, year. Title. Edition, name of publisher, place of publication. Example: Oldenbroek JK, 1999. Genebanks and the conservation of farm animal genetic resources, Second edition. DLO Institute for Animal Science and Heal th, Netherlands.Book chapter or conference proceedings: Author(s) surname and initials, year. Title. In: Title of the book or of the proceedings followed by the editor(s), volume, pages. Name of publisher, place of publication. Example: Mauff G, Pulverer G, Operkuch W, Hummel K and Hidden C, 1995. C3-variants and diverse phenotypes of unconverted and converted C3. In: Provides of the Biological Fluids (ed. H. Peters), vol. 22, 143-165, Pergamon Press. Oxford, UK.Todorov N and Mitev J, 1995. Effect of level of feeding during dry period, and body condition score on reproductive perfor-

thmance in dairy cows,IX International Conference on Production Diseases in Farm Animals, September 11–14, Berlin, Germany.Thesis:Hristova D, 2013. Investigation on genetic diversity in local sheep breeds using DNA markers. Thesis for PhD, Trakia University, Stara Zagora, Bulgaria, (Bg).

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Volume 7, Number 1March 2015

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