NSave Nature to Survive - The Bioscan

NSave Nature to Survive

An International Quarterly Journal of Life Sciences

ISSN : 0973-7049Volume 13, Number 1: 2018

Published as an official organ by

NATIONAL ENVIRONMENTALISTS ASSOCIATION

P a g eP a g eP a g eP a g eP a g e


CONTENTSCONTENTSCONTENTSCONTENTSCONTENTS

Website : www.thebioscan.com : www.neaindia.org

Cell : 94313-60645; 9572649448

Ph. : 0651-2244071

E-mails : [email protected]@gmail.com

[email protected]

For information regarding Association :SECRETARY,National Environmentalists Association,D-13, Sai Roofs, 1st Floor,H. H. Colony,Ranchi - 834002Jharkhand, India

Contact :For Editorial Information

Prof. M. P. SinhaVice ChancellorSido Kanhu Murmu UniversityDumka - 814 110Jharkhand, INDIA

NATIONAL ENVIRONMENTALISTSASSOCIATION

The National Environmentalists Associationis chartered in Ranchi as a nonprofit scientificand educational association of like mindedacademician, researchers, scientists from allover the nation for the furtherance and diffusionof knowledge of Life Sciences in general andEnvironmental Science in particular.

U.S .A . Of f i ce2827 Videre Dr.,Wilmington,DE 19808 We, USA

The association not only honours its membersbut also provides FELLOWSHIP tooutstanding contributors to the subject andthe society.

NAAS Rating : 5.26

A. RESEARCH PAPER

1. Evaluation of fungicides against leaf spot disease of apple (Malusdomestica cv. red delicious) caused by Alternaria mali RobertsU. S. Fais, V. Kumar and P. Vijimole

2. Chemical and sensory evaluation of flat bread supplemented withpearl millet and soy protein isolatesParamjot Kaur, Monika Sood and Julie D. Bandral

3. Genetic architecture of quality traits in bell pepper [Capsicumannum L. var. Grossum Sendt.]

Vibhuti Sharma and Sonia sood

4. Microbial diversity of moisture stress tolerant rhizobacteriaassociated with sorghum and allied weeds during sorghum cropproduction under drought condition

Kalindee S. Shinde and S. G. Borkar

5. Development and evaluation of extruded product of rice flourand apple pomaceMunazah Mehraj, H. R. Naik, Monica Reshi, S. A. Mir andA. Rouf

6. Sustainability through resource recycling, soil fertility and carbonsequestration from integrated farming systems in West coast, India

B. L. Manjunath, V. Paramesh, G. R. Mahajan, Bappa Das,K.Viswanatha Reddy, E. B. Chakurkar and N. P. Singh

7. Bio-efficacy of Tebuconazole 060 Fs (Raxil 060 FS) as seedtreatment against Karnal bunt, Loose smut and Flag smut of wheat

Bijender Kumar8. Assessment of genetic divergence among sugarcane genotypes

(Saccharum officinarum L.) based on molecular markersNaveen Arora, Lenika Kashyap, R. S . Gill and K. S Thind

9. Gamma ray induced viable mutants in soybean (Glycine max. (L.)Merrill)N. Verma, M. Chakraborty, K. Prasad, T. Izhar

10. Extent of heterosis over environments in rice hybrids using CMSsystemK. Parimala and CH. Surender Raju

11. Genetics of cotyledon colour in lentil (Lens culinaris Medik.)Yogesh Kumar, Jitendra Kumar and Sushil Kumar Chaturvedi

12. Catch efficiency of trawlers off Ratnagiri Coast of Maharashtra,IndiaB. R. Kharatmol, Latha Shenoy, V. V. Singh, A. T. Landgeand A. S. Mohite

Type seter Bandana Solutions Facility Management LLP

Published by Aditi Publications, Patliputra, Patna

01 - 03

05 - 08

09 - 13

15 - 19

21 - 26

27- 32

47 - 52

53 - 57

65 - 72

41 - 45

33 - 39

59 - 65


PagePagePagePagePage

D I S C L A I M E R

The Publisher and Editors cannot beheld responsible for errors or anyconsequences arising from the use ofinformation in this journal; the viewsand opinions expressed do notnecessarily reflect those of thePublisher/ Association and Editors,neither does the publication ofadvertisements constitute anyendorsement by the Publisher /Association and Editors of the productsadvertised.

The Journal is CurrentlyAbstracted / Indexed in

© National Environmentalists Association

• Paryavarn Abstract,INDIA

• Indian Science Abstract,INDIA

• Cambridge Science Abstract,U.S.A.

• Zoological Record,U.K.

• Directory of Open AccessJournal (DOAJ)

• Chemical Abstract,U. S. A.

• Research BIB

• Indian Science

• Journal Seek

• Scientific Indexing Service(SIS)

Journal is currently rated by

Index Copernicus

Universal Impact Factor

NAAS

81 - 84

73- 76

77 - 80

13. Area under disease progress curve and influence abiotic factorson wilt of pomegranateR. Somu, R. K. Mesta, K. C. Kiran Kumar andChidanand P. Mansur

14. Exploitation of heterosis and inbreeding depression for yield,hybrid seed yield, nutritional and processing quality improvementin tomato (Solanum lycopersicum L.) under North IndianconditionsChandan Kumar and Surendra Prasad Singh

15. Correlation studies in some of the germplasm lines of kharifsorghumV. V. Kalpande, R. B. Ghorade, S. B. Thawari andY. G. Kedar

16. Genetic analysis of tropical maize (Zea mays L.) inbred linesunder heat stressAkula Dinesh, Ayyanagouda Patil, P. H. Zaidi, P. H.Kuchanur, M. T. Vinayan, K. Seetha Ram and AmareGouda

17. Heterosis studies for yield and yield components in greengram[Vigna radiata (L.) Wilczek]Anamika Nath and S. R. Maloo

18. Assessment of genetic diversity in germplasm collection of linseed(Linum usitatissimum L.)Chhaya Atri and Hitesh Kumar

19. Determination of selection criteria for grain yield in climateresilient small millet crop Kodo millet (Paspalum scrobiculatumL.)Abhinav Sao, Preeti Singh, Prafull Kumar and PraveenPanigrahi

20. Genetic assessment studies for yield and yield parameters indiverse genotypes of eggplant (Solanum melongena L.)Ashutosh Kumar, Anand Kumar Singh, Durga PrasadMoharana, Vaibhav Singh and Pushpendra Singh

21. Genetic variability and association analysis for yield and itscomponents in F

2 and F

3 segregating generations of the maize

(Zea mays L.) cross BM125 x BM135T. M. Deepu, S. K . Deshpande and B. R. Mani

22. Identification of best general combiners for yield and yield relatedtraits in maize (Zea mays L.) through pooled score techniquesB. C. Chandana and S. K. Deshpande

23. Studies on genetic variability, heritability and genetic advancein African marigold (Tagetes erecta L.)Jitendra Kumar Sahu, Gaurav Sharma, S. K. Nair and RamSingh

24. Correlation and path analysis in F2 generation of mungbean(Vigna radiata (L.) R. Wilczek)

A.Yusufzai Sana, M. S. Pithia, D. R. Mehta and Lata Raval

25. Combining ability and heterosis analysis for seed yield and it’scontributing traits in karingada [Citrulus lanatus (Thumb) Mansf.]

Satyendra Singh, S. D. Solanki, N. N. Prajapati and BharatChaudhary

26. Genetic variability and correlations in french bean for yieldimprovement

Savita, D. K. Singh and Ajay Tomer27. Influence of gamma rays on germination, survival and pollen

sterility in black gram (Vigna mungo L.) mutants

S. Anandhi Lavanya, C. Vanniarajan and J. Souframanien

85 - 88

89 - 94

95 - 99

101 - 104

105 - 108

109 - 112

113 - 116

117 - 120

121 - 124

125 - 128

129 - 136

137 - 140


ZONAL CO-ORDINATORS OF THEA S S O C I AT I O N

• Prof. N. BeheraSchool of Life Science,Sambalpur University

• Dr. Nirmal KumarISTAR, Vallabh Vidyanagar,Anand, Gujarat

• Dr. P. N. SudhaD. K. M. College for Women,Vellore

• Prof. S. P. S. DuttaDept. of Environmental Science,Jammu University, Jammu

• Dr. V. Salom Gnana ThangaDept. of Env. Scs.,University of Kerala, KariavattomTiruvananthapuram, Kerala

FEATURES OF ASSOCIATION

• Association is registered under80G of I.T.

• Prestigious fellowship of theAssociation (F. N. E. A.) toacademicians of the nation.

• Regular annual conference ofnational and international levelsorganized by the Association.

• Young Scientist and SeniorScientist award during theconference of the Association.

Publications of theAssociation

© National Environmentalists Association

An International Quarterly Journal of Life Sciences

An International Quarterly Journal of

Environmental Sciences

The Ecoscan

The Bioscan

www.theecoscan.inwww.thebioscan.in

Both the Journals areo n l i n e

Both the Journals areavailable on Google.com

Websites of the Journals are

PagePagePagePagePage28. Studies on effectiveness and efficiency of gamma rays in black

gram (Vigna mungo (L.) Hepper)

M. Dhasarrathan, S. Geetha, N. Meenakshiganesaan andD. Sassikumar

29. Hybridization of different gerbera (Gerbera jamesonii Bolus exHooker f.) lines for breeding novel traits

M. Aakanksha and Rajiv Kumar30. Screening of some long duration genotypes of pigeonpea [Cajanus

cajan (L.) Millisp.] against the infestation of pod fly[Melanagromyza obtusa (Malloch)]

Sabuj Ganguly, C. P. Srivastava and Sitanshu31. Estimation of genetic variability, heritability and genetic advance

in genotypes of maize (Zea mays L.)

Dan Singh Jakhar, Rajesh Singh, Vivek Kumar Ojha,Chandan Kumar and Aneesh Kumar Chandel

32. Estimation of heterosis for earliness and yield contributing traitsin cucumber (Cucumis sativus L.)

Manisha Thakur, Ramesh Kumar and Sandeep Kumar33. Genetic variability among genotypes and character association

in kharif potato (Solanum tuberosum L.) for different traits

Jyotshnarani Maharana, C. M. Panda and Praveen Jakhar34. Genotypic variation in pollen biology of jackfruit (Artocarpus

heterophyllus Lam.)

Aditi Guha Choudhury, Sonam Ongmu Bhutia, S. K. Sarkarand B. C. Das

35. SSR marker based parent selection of maize (Zea mays L.) inbredlines

Shashi Kumar, Rajesh Kumar, Ajay Kumar, NilmaniPrakash, Pankaj Kumar, Santosh Kumar, Gauttam Kumarand Vinay Kumar

36. Correlation and path coefficient analysis for yield and yieldcomponents in blackgram (Vigna mungo (L.) hepper)

Ch. Shalini and G. M. Lal37. Genetic variability, heritability and genetic advance in marigold

hybrids (Tagetes spp.)

V. P. Deepa and V. S. Patil38. Effectiveness and efficiency of gamma rays on sesame (Sesamum

indicum L.) genotypes

Sruba Saha and Amitava Paul

39. Genetic diversity analysis among mungbean genotypes based onrapd markers

L. Swathi, D. M. Reddy, K. H. P. Reddy and V. Sai Sruthi

40. Combining ability analysis for seed yield and its contributingtraits in linseed (Linum usitatissimum L.)

Ajeet Kumar, K. P. S. Tomar, V. Rathi, A. Kumar andN. K. Vasistha

41. Effect of pod related traits on shattering in M3 mutants ofmungbean (Vigna radiata (L.) wilczek)

N. Vairam

42. Genetic analysis of resistance to rice weevil Siltophilus oryzae L.in bread wheat

Ekhlaque Ahmad and J. P. Jaiswal43. Non-parametric methods for analyzing stability of chickpea (Cicer

arietinum L.) genotypes

A.Trivikrama Reddy, T. Lakshmi Pathy, A.Vijayabharathi andJayarame Gowda

141 - 145

147 - 151

153 - 157

159 - 162

163 - 168

169 - 176

177 - 180

181 - 186

187 - 192

193 - 195

197 - 201

203 - 206

207 - 214

215 - 218

219 - 222

223 - 229

Manoj Kumar

Highlight


THE BIOSCAN : SUBSCRIPTION RATESIndia SAARC Other(Rs.) Countries Countries

Individuals One Year 1,000 2,000(I:C) US $200

Life Member* 10,000

Institutions One Year 3,000 6,000(I:C) US $400

Life Member* 30,000

*Life Member will receive the journal for 15 years while other benefits will continue whole life

THE BIOSCAN : MEMBERSHIP FORM

Please enter my subscription for the above journal for the year ............................................ / life member.

Name: ....................................................................................................................................................

Address: .................................................................................................................................................

E-mail: ...................................................................................................................................................

Payment Rs. : .................................................................................................. by DD / MD in favour of

National Environmentalists Association payable at Ranchi, No. ..................................... Dated................................... is enclosed.

NOTE: FOR MEMBERSHIP THE ABOVE INFORMATION CAN BE SENT ON SEPARATE SHEET

P a g eP a g eP a g eP a g eP a g e

014 & 020

040 & 046

44. Identification of hybrid rice (Oryza sativa L.) and its parental linesbased on morphological characters

Mampi Debbarma, Sharmila D. Deka and Debojit Sarma45. Molecular marker analysis of selected rice lines for aerobic traits

under water limited conditions

Kuldeep Kumar, Kanika Rani, Rahul Kumar Meena,Mahavir, Rajinder Kumar Jain and Sunita Jain

B. INSTRUCTION TO ATUTHORS

C. NATIONAL ENVIRONMENTALISTS ASSOCIATION: ANINTRODUCTION

231 - 236

237 - 243


13(1):207-214,2018www.thebioscan.com

207

COMBINING ABILITY ANALCOMBINING ABILITY ANALCOMBINING ABILITY ANALCOMBINING ABILITY ANALCOMBINING ABILITY ANALYSIS FOR SEED YIELD AND ITSYSIS FOR SEED YIELD AND ITSYSIS FOR SEED YIELD AND ITSYSIS FOR SEED YIELD AND ITSYSIS FOR SEED YIELD AND ITSCONTRIBUTING TRAITS IN LINSEED (CONTRIBUTING TRAITS IN LINSEED (CONTRIBUTING TRAITS IN LINSEED (CONTRIBUTING TRAITS IN LINSEED (CONTRIBUTING TRAITS IN LINSEED (LLLLLinuminuminuminuminum usitatissimumusitatissimumusitatissimumusitatissimumusitatissimum L.)L.)L.)L.)L.)

AJEET KUMAR1*, K. P. S. TOMAR1, V. RATHI1, A. KUMAR1 AND N. K. VASISTHA 2

1Department of Genetics and Plant Breeding,SVP University of Agriculture and Technology, Meerut - 250 110, INDIA2Department of Genetics and Plant Breeding, CCS University Meerut - 250 004, INDIAe-mail: [email protected]

INTRODUCTION

Linseed (Linum usitatissimum L.) is an ancient plant, which isalso known as flax. Linseed (2n = 30) is one of the first cropsdomesticated by man. Every part of the linseed plant is utilizedcommercially either directly or after processing. India is thethird largest producer in the world (Kiran et.al. 2012). In India,the crop is mainly cultivated in the states like Madhya Pradesh,Chhattisgarh, Uttar Pradesh, Maharashtra, Rajasthan, WestBengal, Karnataka, Orissa and Bihar. Chhattisgarh is one ofthe important linseed growing states of India, which account112.52 thousand hectare area and 34.20 thousand metrictons production (Deepak Gauraha et.al.2011). However, inthe world it covers 2270.35 thousand hectare area withproduction of 2238.94 thousand tons having productivity of986.16 kg per hectare, where as in India it covers 338thousand hectares area and a production of 147 thousandtons with the productivity of 434.91 kg per hectare,(Anonymous, 2013). Linseeds, particularly in their groundform are a great vegetarian source of the Omega 3 essential fattyacid, Alpha-Linolenic Acid (ALA). Linseed oil is an edible oil indemand as a nutritional supplement as a source of á-Linolenicacid (an omega-3 fatty acid) (Simopoulos 2002 and HassaneinM.S. et.al 2012). Combining ability is a powerful tool to selectgood combiners and thus selecting the appropriate parentallines for hybridization programme. In addition, the informationon nature of gene action will be helpful to develop efficientcrop improvement programme. General combining ability isdue to additive and additive × additive gene action and isfixable in nature while specific combining ability is due to

non-additive gene action which may be due to dominance orepistasis or both and is non-fixable. The presence of non-additive genetic variance is the primary justification forinitiating the hybrid breeding programme (Cockerham, 1961).Several workers like Singh et al. (1990), Khorgade et al. (1993)and Kumar and Paul (2015) have reported combining abilityon seed yield and its attributing traits in linseed.

There are several techniques for the evaluation of varieties orstrains in terms of their combining ability especially diallelmating system set excluding reciprocals. This technique wasdeveloped by Jinks and Hayman (1953). Keeping in view withthe above problem, the present investigation is taken up withthe following objectives: To study the general and specificcombining ability of parents and crosses for seed yield andyield contributing characters.

MATERIALS AND METHODS

The experiment field was conducted at Crop Research Centre,SardarVallabhbhai Patel University of Agriculture &Technology, Meerut (U.P.), during Rabi 2012-13. Theexperimental material comprised of ten parents namely, Sweta,Garima, Shekhar, Surbhi, Shubhra, Kiran, T-397, Neelam,Heera and Mukta and their all possible single cross was madeunder 10×10 diallel (Jinks 1953 and Hayman 1953) matingsystem set excluding reciprocals. The final trial was laid out inRandomized Block Design (RBD) with 45 F1’s and ten diversifiedparents during the year rabi 2013-14 in three replications.The observations were recorded on 5 randomly taken plantsper entry and per replication in case of parents and 45 crosses.

ABSTRACTA field experiment was conducted at Crop Research Centre (Chirodi), Sardar Vallabhbhai Patel University ofAgriculture & Technology, Meerut (U.P.), during Rabi 2012-13 and 2013-14 to estimate combining ability (GCAand SCA) of seed yield and its components of linseed. The experimental material comprised of ten parents andtheir 45s F2. The hybrids F2 were evaluated along with their parents in randomized complete block design withthree replications. It revealed highly significant variances for GCA and SCA for all the characters. Combiningability studies revealed that the lines Shekhar, Kiran, T-397 and Mukta, which were showed high generalcombining ability effects in desirable direction for seed yield and yield components. Moreover,. Among thespecific cross combinations, the crosses for seed yield per plant viz., Kiran×T-397, Shubhra×Hira, Neelam×Hira,T-397×Neelam and T-397×Hira exhibited good specific combining ability effects for seed yield and its contributingtraits.

KEYWORDSLinseedCombining abilitySeed yieldQuality characters

Received on :26.04.2017

Accepted on :21.05.2017

*Correspondingauthor

208

AJEET KUMAR et al.,

Data on the basis of randomly taken competitive plants wererecorded on viz., days to 50% flowering, days to maturity,plant height (cm), primary branches per plant, secondarybranches per plant, capsules per plant, seeds per capsule,biological yield per plant (g), seed yield per plant (g), harvestindex (%), 1000-seed weight (g) and oil content. Oil content ofeach genotype was determined by Soxhlet procedure (BISNo. 15:548 Part I 1964 and Official and Tentative Methods1973).

RESULTS AND DISCUSSION

Analysis of variance for combining abilityThe combining ability analysis under diallel mating approachwas done by the procedure advocated by Griffing (1956),which involves the study of covariances of full sibs andcovariances of half sibs to get the estimates of generalcombining ability and specific combining ability variancesand their effects. Analysis of variance for combining ability(Table 1) exhibited the variance due to general combiningability highly significant for all the characters and specificcombining ability variance was also observed highly significantfor all the traits, indicating involvement of both additive andnon-additive types of gene action in the inheritance of thesecharacters. Similar trend of involvement of both additive andnon-additive gene action has been earlier reported (Kalia,1972,Patil and Chopde, 1983, Khorgade et al., 1993), Popescu etal.,1995), Singh et al., 2008), Mohammadi et al., 2010, Yadavet al., 2013, Pali and Mehta, 2014).

The variance components for ó2s values were found higherthan estimates values ó2g for all the characters, suggestingmajor role of additive gene action in expression of these traits.Similar kind of additive gene action for various attributes wasreported earlier by Nie et al. (1991), Pillai et al. (1995), Awasthiand Rao (2005), Singh et al. (2008), Goral et al. (2008),Yadavet al. (2013) and Pali and Mehta (2014).

The proportion of ó2g / ó2s being less than unity for days to50% flowering, days to maturity, plant height, number ofprimary branches per plant, number of capsules per plant,number of secondary branches per plant, number of seedsper capsule, 1000 seed weight, biological yield per plant,harvest index, oil content and seed yield per plant suggestedthat involvement of non-additive kind of gene action for thesecharacters, which indicated that involvement of additive typeof gene action for this trait. The similar findings are inconformity with Mishra and Rai (1993), Popescu et al. (1995),Tiwari (1999), Awasthi and Rao (2005), Mohammadi et al.(2010) and Yadav et al. (2013).

The mean degree of dominance (ó2g / ó2s)½ was found greaterthan unity for all the characters, indicating the genetic controlof over dominance type of gene effect in them. These types offindings were also reported by Kaushal et al. (1974), Rai andDas (1975), Patil and Chopde (1983), Manfroni et al. (1989),Khorgade et al. (1993), Vishnu et al. (2005) and Yadav et al.(2013).

General combining ability effectsThe estimates of general combining ability effects and per seperformance of ten parents for all the 12 attributes are presented So

urce

of

D.F

.D

ays

toD

ays

toPl

ant

Num

ber

Num

ber

Num

ber

ofN

umbe

r of

1000

see

dB

iolo

gica

lH

arve

stO

ilSe

ed y

ield

vari

atio

n50

%m

atur

ityhe

ight

prim

ary

seco

ndar

yca

psul

es p

erse

eds

per

wei

ght

yiel

d pe

rin

dex

cont

ent

per

plan

tflo

wer

ing

(cm

)br

anch

esbr

anch

espl

ant

caps

ule

(g)

plan

t (g)

(%)

(%)

(g)

per

plan

tpe

r pl

ant

GC

A9

56.6

14**

32.6

93**

422.

033*

*2.

671*

*13

.120

**17

98.0

83**

0.65

8**

3.40

8**

3.41

1**

34.8

18**

5.19

5**

1.28

8**

SCA

4529

.149

**18

.676

**70

.893

**1.

685*

*5.

138*

*39

3.86

9**

0.90

1**

2.45

4**

5.03

8**

39.7

36**

2.61

6**

1.20

7**

Erro

r10

80.

784

1.22

20.

589

0.03

10.

209

5.59

90.

049

0.06

20.

094

2.22

40.

570

0.04

0

Tabl

e 1:

Ana

lysi

s of

var

ianc

e fo

r co

mbi

ning

abi

lity

of y

ield

and

its

com

pone

nts

in li

nsee

d(Li

num

usi

tati

ssim

umL.

)

Estim

ated

var

ianc

es d

ue to

σ2 g4.

653

2.62

335

.120

0.22

01.

076

149.

374

0.05

10.

279

0.27

62.

716

0.38

51.

104

σ2 s28

.365

17.4

5470

.304

1.65

44.

929

388.

270

0.85

22.

392

4.94

33.

512

2.04

51.

168

σ2 g/σ

2 s0.

164

0.15

00.

500

0.13

30.

218

0.38

50.

060

0.11

70.

056

0.07

20.

188

0.08

9(σ

2 s/σ

2 g)1/

22.

469

2.57

91.

414

2.74

22.

140

1.61

24.

087

2.92

84.

231

3.71

62.

305

3.35

1

209

COMBINING ABILITY ANALYSIS FOR SEED YIELD

Tabl

e 2:

Est

imat

es o

f GC

A e

ffec

ts a

nd p

er s

e pe

rfor

man

ce o

f par

ents

for

yiel

d an

d qu

ality

com

pone

nts

in li

nsee

d (L

inum

usi

tati

ssim

um L

.)

Cha

ract

ers

Day

s to

50%

flo

wer

ing

Day

s to

mat

urity

Plan

t hei

ght (

cm)

Num

ber

pri

mar

yN

umbe

r se

cond

ary

Num

ber

of c

apsu

les

bran

ches

per

pla

ntbr

anch

es p

er p

lant

per

plan

tPa

rent

sG

CA

Effe

ctM

ean

GC

A E

ffect

Mea

nG

CA

Effe

ctM

ean

GC

A E

ffect

Mea

nG

CA

Effe

ctM

ean

GC

A E

ffect

Mea

n

Swet

a-2

.638

**89

.407

-1.5

57**

140.

610

3.55

1**

65.3

170.

034

3.40

31.

276*

*16

.360

1.82

3**

124.

100

Gar

ima

-3.

325*

*81

.857

-3.4

45**

127.

873

5.13

8**

53.5

93-0

.230

4.77

70.

838*

*16

.873

5.62

3**

121.

287

Shek

har

0.5

3885

.097

-0.6

9113

2.92

01.

498*

*56

.597

0.2

586.

890

0.15

617

.310

1.91

8**

170.

233

Shub

hra

2.75

4**

96.7

53-0

.699

140.

103

2.5

16**

68.7

00-0

.073

5.73

3-0

.989

**12

.367

1.54

5*

126.

410

Kir

an -

0.40

886

.980

0.18

013

3.24

7-1

.886

**49

.967

0.0

315.

540

-0.0

8218

.100

5.00

7**

116.

100

Surb

hi0.

562

87.3

901.

193*

*13

7.65

75.

880*

*48

.953

-0.

127

4.37

70.

823*

*22

.867

10.4

09**

107.

300

T-39

7 -

1.91

0**

85.1

771.

555*

*14

5.01

0-4

.618

**56

.417

1.00

1**

7.86

31.

040*

*23

.290

26.7

06**

101.

467

Nee

lam

2.2

02**

91.9

531.

184*

*13

9.39

3-3

.475

**57

.870

0.3

227.

250

-0.2

9112

.800

13.2

11**

166.

210

Muk

ta2.

712*

*93

.380

0.30

712

9.93

31.

342*

*57

.803

1.52

6**

3.23

3-0

.747

13.6

0315

.928

**15

8.76

7H

ira

-0.4

8897

.050

1.97

3**

142.

000

14.0

85**

92.7

931.

691*

*3.

077

2.02

413

.383

5.72

0**

150.

187

SE(g

i)0.

549

0.68

50.

476

0.10

90.

283

0.46

6SE

(gi-g

j)0.

818

0.02

10.

709

0.16

30.

423

0.18

5

*Sig

nific

ant a

t 5%

pro

babi

lity

leve

l; **

Sig

nific

ant a

t 1%

pro

babi

lity

leve

l

in (Table 2). The genotypes Garima (-3.325), Sweta (-2.638)and T-397 (-1.910) exhibited significant negative generalcombining ability effects and were found to be best generalcombiners for days to 50% flowering. The genotype Garima(-3.445) and Sweta (-1.557) exhibited significant negativegeneral combining ability effects and appeared to be bestgeneral combiners for early maturity. In the case of plant heightgenotypes T-397 (-4.618), Neelam (-3.475) and Kiran (-1.886)were found to be best general combiners for dwarfness andexhibited significant negative general combining ability effects.Out of ten parents, only three genotypes Hira (1.691), Mukta(1.526) and T-397 (1.001) showed significant positive generalcombining ability effects and appeared to be best generalcombiners for number of primary branches per plant. Thegenotypes Sweta (1.276), T-397 (1.040) Garima (0.838) andSurbhi (0.823) emerged as best general combiners for numberof secondary branches per plant which revealed significantand positive general combining ability effects. Among theparental lines, the genotypes T-397 (26.706), Mukta (15.928),Neelam (13.211), Surbhi (10.409), Hira (5.720), Garima(5.623), Kiran (5.007), Shekhar (1.918), Sweta (1.823) andShubhra (1.545) recorded significant and positive generalcombining ability effects for number of capsules per plant.Out of all parental lines, only three genotypes Surbhi (3.273),Shubhra (1.158) and Shekhar (1.105) revealed significant andpositive general combining ability effects and were found tobe best general combiners for number of seeds per capsules.The genotypes T-397 (3.745), Neelam (2.358), Shubhra (0.897)and Hira (0.412) exhibited significant positive generalcombining ability effects and emerged as best generalcombiners for 1000 seed weight. In the case of biologicalyield per plant the genotypes, Shekhar (2.128), Mukta (2.241),Kiran (1.554), T-397 (1.375) and Garima (1.031) exhibitedsignificant and positive general combining ability effects andappeared to be good general combiners for biological yieldper plant. Significant and positive general combining abilityeffects was observed for Kiran (3.164), T-397 (2.977), Mukta(2.294), Shekhar (1.894) and Sweta (1.117), which appearedas best general combiners for harvest index. The parents Mukta(5.537) and Sweta (1.278) revealed significant and positivegeneral combining ability effects and were emerged to be bestgeneral combiners for high oil content. Out of all parentallines, only four genotypes viz., T-397 (2.272), Shekhar (2.247),Mukta (1.291) and Kiran (1.080) observed significant andpositive general combining ability effects and were found tobe best general combiner for seed yield per plant. These resultsare in conformity with Thakur et al. (1988), Singh et al. (1990),Mishra and Rai (1993), Popescu et al. (1995), Tiwari (1999),Bhateria et al. (2002), Awasthi and Rao (2005), Goral etal.(2008), Yadav et al. (2013) and Pali and Mehta (2014).

Specific combining ability effectsThe specific combining ability effects and per se performanceof crosses is given in (Table-3). To confirm whether the crossesselected on the basis of specific combining ability effects werereally the best performance ones, the out of forty five crosscombinations, thirteen best cross combinations viz., Kiran×T-397 (11.180), Shubhra×Hira (10.967), Neelam×Hira(10.917), T-397×Hira (10.613), T-397×Neelam (10.296),Garima×Hira (9.515), Mukta×Hira (9.183), Sweta×Surbhi

210

Table 3: Estimation of SCA effects and per se performance of crosses for yield components in linseed (Linum usitatissimum L.)

Characters Days to 50% flowering Days to maturity Plant height(cm)Crosses SCA Effect Mean SCA Effect Mean SCA Effect Mean

Sweta x Garima 4.032** 84.240 0.267 135.593 4.886** 65.580Sweta x Shekhar 6.796** 90.867 -4.550** 136.807 -0.594 63.740Sweta x Shubhra -11.234** 75.053 -10.925** 135.593 -0.188 68.160Sweta x Kiran -12.771** 70.353 8.106** 136.807 -6.192** 58.753Sweta x Surbhi -3.888** 80.207 2.696* 135.593 4.002** 63.953Sweta x T-397 -2.190* 79.433 1.604 136.807 3.633** 64.847Sweta x Neelam 1.899* 87.633 -0.999 135.593 -2.984** 59.373Sweta x Mukta -2.778** 83.467 -6.124** 136.807 -8.114** 59.060Sweta x Hira 3.109** 86.153 -3.894** 135.593 13.683** 93.600Garima x Shekhar 2.616** 86.000 -1.369 136.807 -0.079 55.567Garima x Shubhra -1.067 84.533 -2.421* 135.593 -0.393 59.267Garima x Kiran -16.471** 65.967 1.800 136.807 -3.057** 53.200Garima x Surbhi 4.246** 87.653 -0.530 135.593 -0.730 50.533Garima x T-397 -3.703** 77.233 0.945 136.807 3.125** 55.650Garima x Neelam 2.853** 87.900 3.446** 135.593 5.172** 58.840Garima x Mukta 2.442** 88.000 3.820** 136.807 -0.269 58.217Garima x Hira 0.382 82.740 -1.856 135.593 -11.831** 59.397Shekhar x Shubhra -1.263 88.200 2.622* 136.807 3.844** 67.143Shekhar x Kiran 2.486** 88.787 -1.487 135.593 -3.080** 56.817Shekhar x Surbhi -2.837** 84.433 4.279** 136.807 -0.660 54.243Shekhar x T-397 -1.849* 82.950 -0.649 135.593 -0.405 55.760Shekhar x Neelam -0.377 88.533 -4.738** 136.807 -0.682 56.627Shekhar x Mukta 2.319** 91.740 7.806** 135.593 -4.759** 57.367Shekhar x Hira -3.588** 82.633 3.113** 136.807 11.792** 86.660Shubhra x Kiran 8.483** 97.000 -1.275 135.593 -6.361** 57.550Shubhra x Surbhi 0.097 89.583 0.035 136.807 9.476** 68.393Shubhra x T-397 -0.832 86.183 -0.730 135.593 1.854 62.033Shubhra x Neelam -0.573 90.553 -4.313** 136.807 7.218** 68.540Shubhra x Mukta 0.279 91.917 3.765** 135.593 -7.336** 58.803Shubhra x Hira -4.037** 84.400 4.869** 136.807 -10.889** 67.993Kiran x Surbhi 6.326** 92.650 -0.622 135.593 -6.814** 48.700Kiran x T-397 2.447** 86.300 0.850 136.807 -0.577 56.200Kiran x Neelam 3.302** 91.267 -2.586** 135.593 0.600 58.520Kiran x Mukta 4.458** 92.933 0.495 136.807 28.603** 91.340Kiran x Hira -1.508 83.767 3.566** 142.533 17.961** 93.440Surbhi x T-397 1.477 86.300 -2.363** 137.200 5.987** 57.770Surbhi x Neelam -0.207 88.727 2.034** 141.227 3.444** 56.370Surbhi x Mukta -3.028** 86.417 2.985** 141.300 -1.199 56.543Surbhi x Hira -2.378** 83.867 -5.424** 134.557 -10.372** 60.113T-397 x Neelam -0.829 85.633 -1.554 138.000 -3.065** 51.123T-397 x Mukta 1.936* 88.910 0.330 139.007 -3.318** 55.687T-397 x Hira -2.106* 81.667 -7.606** 132.737 -13.978** 57.770Neelam x Mukta -2.218** 88.867 3.221** 141.527 -1.508 58.640Neelam x Hira -6.608** 81.277 5.068** 145.040 -13.274** 59.617Mukta x Hira -6.978** 81.417 -0.317 138.777 12.222** 89.930S.E.(Sij) 0.644 0.052 1.425SE(Sij-Sik) 1.417 0.016 0.095

Characters Number Primary branches Number secondary branches Number of capsulesper plant per plant per plant

Crosses SCA Effect Mean SCA Effect Mean SCA Effect Mean

Sweta x Garima -1.088 3.733 -0.326 18.400 17.101** 123.427Sweta x Shekhar 0.124 5.433 0.633 18.667 16.089** 120.733Sweta x Shubhra 1.489 6.467 -0.489 16.400 15.584** 152.033Sweta x Kiran 1.585** 6.667 0.837 18.633 10.902** 140.800Sweta x Surbhi 0.376 5.300 1.126 19.827 15.005** 139.500Sweta x T-397 1.481 7.533 2.722** 21.640 17.901** 126.100Sweta x Neelam 1.374 6.747 0.879 18.467 -43.216** 104.900Sweta x Mukta -0.385 4.140 -1.744 15.387 21.201** 172.033Sweta x Hira -1.593 2.767 1.943 17.797 13.776** 154.400

Table 3: Cont......

AJEET KUMAR et al.,

211

* Significant at 5% probability level; ** Significant at 1% probability level

Characters Number Primary branches Number secondary branches Number of capsulesper plant per plant per plant

Crosses SCA Effect Mean SCA Effect Mean SCA Effect Mean

Garima x Shekhar -2.611** 2.433 1.171 18.767 18.442** 162.710Garima x Shubhra 0.520 5.233 -0.884 15.567 34.075** 177.970Garima x Kiran -0.117 4.700 0.529 17.887 40.940** 178.283Garima x Surbhi 3.507** 8.167 2.937** 21.200 -10.797** 121.143Garima x T-397 -0.221 5.567 2.113*** 16.367 37.882** 153.527Garima x Neelam -2.542** 3.567 1.084 18.233 7.855** 147.707Garima x Mukta -0.028 4.233 0.767 17.460 18.494** 139.783Garima x Hira 3.138** 5.233 -0.366 15.050 23.720** 124.350Shekhar x Shubhra -0.968 4.233 -1.552 14.217 -11.956** 128.233Shekhar x Kiran -0.972 4.333 -0.492 16.183 -16.781** 116.857Shekhar x Surbhi 2.086** 7.233 0.053 17.633 0.059 102.177Shekhar x T-397 -1.209 5.067 -4.148** 13.650 0.906 101.033Shekhar x Neelam 0.703 6.300 0.667 17.133 -1.506 150.350Shekhar x Mukta -0.516 4.233 3.723** 17.733 0.171 157.743Shekhar x Hira 0.650 5.233 1.150 15.883 0.342 146.707Shubhra x Kiran -1.440 3.533 1.969 17.500 -16.605** 116.660Shubhra x Surbhi -1.483 3.333 -0.135 16.300 -14.229** 113.633Shubhra x T-397 -0.878 5.067 1.247 17.900 -0.230 108.337Shubhra x Neelam -1.032 4.233 2.911** 18.233 13.423** 164.907Shubhra x Mukta 2.049** 6.467 0.501 15.367 6.270** 160.470Shubhra x Hira 0.015 4.267 0.945* 14.533 0.481 147.473Kiran x Surbhi 2.386** 3.533 5.609** 11.733 -0.211 112.100Kiran x T-397 -0.548 5.500 4.360** 13.200 -1.948 86.067Kiran x Neelam -0.836 4.533 1.371 17.600 17.818** 162.750Kiran x Mukta 0.612 5.133 1.894 17.667 11.619** 159.267Kiran x Hira 2.177** 6.533 0.538 15.033 1.493 138.933Surbhi x T-397 -0.357 5.533 2.132** 16.333 1.621 101.233Surbhi x Neelam -0.578 4.633 -3.501** 15.633 31.438** 170.967Surbhi x Mukta -0.830 3.533 -1.977 14.700 14.355** 156.600Surbhi x Hira -0.565 3.633 -2.000** 13.400 15.096** 147.133T-397 x Neelam -0.140 6.200 0.715 18.067 -0.966 99.267T-397 x Mukta 0.441 5.933 0.138 17.033 -0.682 105.267T-397 x Hira -0.260 5.067 -1.285 14.333 15.975** 99.767Neelam x Mukta -0.280 4.533 2.303** 17.867 0.234 171.100Neelam x Hira -0.848 3.800 -1.987 12.300 0.508 158.167Mukta x Hira 3.400** 4.200 -0.597 13.233 -0.041 155.333S.E.(Sij) 0.327 0.849 1.393SE(Sij-Sik) 0.481 0.249 1.457

Table 3: Cont.....

Characters Number of seeds per capsule 1000 seed weight (g) Biological yield per plant (g)Crosses SCA Effect Mean SCA Effect Mean SCA Effect Mean

Sweta x Garima 0.478 9.433 0.753 8.030 -0.852 14.110Sweta x Shekhar -0.922 7.100 -10.800** 7.643 1.897 15.700Sweta x Shubhra 0.442 8.200 0.382 8.213 -0.339 13.113Sweta x Kiran -0.470 7.400 -0.526 8.200 0.971 15.457Sweta x Surbhi -1.690 6.500 -1.537 6.877 2.197** 16.123Sweta x T-397 0.318 8.067 0.148 8.337 -0.163 13.393Sweta x Neelum -0.080 7.533 -2.043** 6.533 -1.18 12.733Sweta x Mukta -1.147 6.467 2.359** 8.650 3.027** 17.200Sweta x Hira 0.337 8.600 2.587** 8.933 1.144 15.110Garima x Shekhar 1.022 8.867 10.683** 8.153 -10.909** 14.787Garima x Shubhra 3.885** 8.467 10.041 8.900 12.101** 13.243Garima x Kiran -0.126 7.567 11.366** 8.120 -0.311 16.067Garima x Surbhi 0.321 8.333 0.535* 8.977 1.975 17.793Garima x T-397 -0.238 7.333 -0.087 8.130 -1.049 14.400Garima x Neelam 5.636** 6.800 0.323 8.927 -0.630 15.183Garima x Mukta 10.497** 7.933 -0.658 8.660 -3.542** 12.523Garima x Hira -0.553 7.533 0.326 9.700 -1.852 14.007Shekhar x Shubhra -4.181** 6.467 -0.169 8.857 -0.719 13.467

Table 3: Cont.....


212

* Significant at 5% probability level; ** Significant at 1% probability level

Characters Number of seeds per capsule 1000 seed weight (g) Biological yield per plant (g)Crosses SCA Effect Mean SCA Effect Mean SCA Effect Mean

Shekhar x Kiran 7.042** 8.800 4.123** 8.043 2.188** 17.407Shekhar x Surbhi 1.255 9.333 -0.271 7.337 0.787 15.447Shekhar x T-397 -0.204 7.433 -0.850 6.533 0.034 14.323Shekhar x Neelam -1.102 6.400 -0.517 7.253 2.121** 12.533Shekhar x Mukta 0.331 7.833 -1.601 6.883 2.912** 11.993Shekhar x Hira -1.552 6.600 1.070 9.610 1.634** 16.333Shubhra x Kiran -1.662 5.833 2.509** 8.817 -0.324 14.543Shubhra x Surbhi 0.218 8.033 2.397** 8.393 -1.412 12.897Shubhra x T-397 8.059** 8.433 1.835 8.607 1.682 15.620Shubhra x Neelam -0.039 7.200 -1.545 7.613 -0.647 13.657Shubhra x Mukta 9.028** 8.267 -0.296 8.577 2.799** 17.353Shubhra x Hira -0.822 7.067 -0.242 8.687 -1.465 12.883Kiran x Surbhi -0.526 7.400 -0.774 7.117 3.485** 18.827Kiran x T-397 -1.018 6.467 -1.103** 6.563 -1.178 13.793Kiran x Neelam 0.850 8.200 0.417 8.470 -2.207** 13.130Kiran x Mukta 0.117 7.467 -2.084** 6.683 -3.108** 12.480Kiran x Hira 0.033 8.033 11.396** 7.427 -1.515** 13.867Surbhi x T-397 -1.338 6.467 -0.761 6.593 0.588* 15.000Surbhi x Neelam 10.797** 8.467 -0.055 7.687 3.111** 11.667Surbhi x Mukta 11.397** 9.067 10.782 7.673 -0.219 14.810Surbhi x Hira -0.553 7.767 -0.614 7.897 -1.619 13.203T-397 x Neelam -0.529 6.700 1.533 9.050 -0.338 14.070T-397 x Mukta -1.096 6.133 0.339 8.570 -0.065 14.593T-397 x Hira 0.454 8.333 -1.063 7.223 -0.185 14.267Neelam x Mukta 0.439 7.533 3.549** 8.167 13.391** 11.633Neelam x Hira 0.089 7.833 -1.240 7.433 3.073** 17.890Mukta x Hira 0.223 7.967 2.079** 8.467 0.695 15.763S.E.(Sij) 0.413 0.461 0.570SE(Sij-Sik) 0.607 .678 0.838

Table 3: Cont.....

Characters Harvest index (%) Oil content (%) Seed yield per plant (g)Crosses SCA Effect Mean SCA Effect Mean SCA Effect Mean

Sweta x Garima 2.125** 56.910 -0.187 41.617 -0.165 8.023Sweta x Shekhar 4.945** 61.640 0.490 42.333 5.847** 9.677Sweta x Shubhra 3.385* 56.143 1.374 43.157 0.282 7.333Sweta x Kiran 4.237** 57.873 -0.696 39.987 6.280** 8.943Sweta x Surbhi -0.829 54.203 -1.845 39.833 8.144** 8.723Sweta x T-397 -1.488 56.290 0.583 42.207 -0.324 7.530Sweta x Neelum 3.121** 58.387 -0.745 41.647 -0.174 7.403Sweta x Mukta -5.210** 47.297 0.114 42.577 0.816 8.107Sweta x Hira -10.070** 43.567 0.445 42.227 -0.910 6.583Garima x Shekhar -0.761 54.800 1.345 41.790 -0.621 8.100Garima x Shubhra -0.098 49.527 -4.541** 35.843 -5.385** 6.557Garima x Kiran -4.916** 47.587 1.562 40.847 -0.871 7.683Garima x Surbhi -3.892** 50.007 -3.413** 36.867 0.420 8.890Garima x T-397 -1.801 54.843 0.645 40.870 -0.872 7.873Garima x Neelam 0.711 54.843 -0.200 40.793 -0.152 8.317Garima x Mukta 9.607** 60.980 -0.697 40.367 -0.706 7.477Garima x Hira -3.460* 49.043 0.377 40.757 9.515** 6.870Shekhar x Shubhra 4.145** 57.680 0.316 40.740 0.087 7.670Shekhar x Kiran -0.417 51.997 1.466 40.790 0.831 9.027Shekhar x Surbhi 0.708 56.517 0.914 41.233 0.625 8.737Shekhar x T-397 1.862 60.417 -2.378** 37.887 0.270 8.657Shekhar x Neelam 3.234* 59.277 0.401 41.433 -0.623 7.487Shekhar x Mukta -0.350 52.933 0.096 41.200 6.470** 6.353Shekhar x Hira 11.550** 42.863 2.799** 37.620 -5.026** 7.000Shubhra x Kiran 3.026** 53.503 -0.036 39.227 0.364 7.780Shubhra x Surbhi 13.091** 64.963 2.245** 42.503 1.047 8.380Shubhra x T-397 13.365** 41.253 1.153 41.357 1.171 6.437Shubhra x Neelam 6.320** 45.787 1.129 42.100 -1.077** 6.253

Table 3: Cont.....

AJEET KUMAR et al.,

213

(8.144), Surbhi×T-397 (7.127), Shekhar×Mukta (6.470),Sweta×Kiran (6.280), Sweta×Shekhar (5.847) andShubhra×Mukta (1.596) exhibited significant and positivespecific combining ability effects with good per se performancefor seed yield per plant. It clearly suggests that while selectingbest cross combinations this evidence needs to be given dueconsideration.

For instance the crosses Sweta×Shekhar had high anddesirable specific combining ability effect for days to maturity,number of capsules per plant, harvest index and seed yieldper plant; Sweta×Kiran for number of primary branches perplant, number of capsules per plant, harvest index and seedyield per plant; Sweta×Surbhi fornumber of capsules perplant, biological yield per plant and seed yield per plant;Garima×Hira for number of primary branches per plant,number of capsules per plant and seed yield per plant;Shekhar×Mukta forplant height, number of secondarybranches per plant, biological yield per plant and seed yieldper plant; Shubhra×Mukta for plant height, number of primarybranches per plant, number of capsules per plant,number ofseeds per capsule, biological yield per plant and seed yieldper plant; Shubhra×Hira for days to flowering, plant height,number of secondary branches per plant and seed yield perplant; Kiran×T-397 for number of secondary branches perplant and seed yield per plant; Surbhi×T-397 for days tomaturity, number of secondary branches per plant, biologicalyield per plant, harvest index and seed yield per plant; T-397×Neelam for harvest index and seed yield per plant; T-397×Hira for number of capsules per plant harvest indexand seed yield per plant; Neelam×Hira for days to flowering,plant height, biological yield per plant and seed yield perplant and Mukta×Hira for days to flowering, number ofprimary branches per plant, 1000 seed weight, harvest indexand seed yield per plant. These findings were supported byKalia (1972), Kaushal et al. (1974), Patil and Chopde (1983),Thakur et al. (1988), Singh et al. (1990), Khorgade et al. (1993),Popescu et al. (1995), Tiwari (1999), Goral et al.(2008), Yadav

Characters Harvest index (%) Oil content (%) Seed yield per plant (g)Crosses SCA Effect Mean SCA Effect Mean SCA Effect Mean

Shubhra x Mukta 0.413 49.760 -0.066 40.977 1.596** 8.640Shubhra x Hira -1.790 48.687 -0.318 40.040 10.967** 6.280Kiran x Surbhi -9.151** 43.600 -0.885 38.273 -0.191 7.753Kiran x T-397 -4.457** 51.040 -1.381 37.723 11.180** 7.040Kiran x Neelam 6.392** 59.377 -2.429** 37.443 -0.149 7.793Kiran x Mukta 4.191** 54.417 -1.609 38.333 -0.850 6.807Kiran x Hira 8.565** 59.920 -1.365 37.893 0.457 8.317Surbhi x T-397 4.755** 61.647 -1.413 38.687 7.127** 9.263Surbhi x Neelam 2.767* 57.147 -0.274 40.593 1.182 6.677Surbhi x Mukta 5.083** 56.703 -0.061 40.877 0.837 8.410Surbhi x Hira -0.887 51.863 -0.773 39.480 -0.985 6.790T-397 x Neelam 2.744** 59.870 -1.386 39.427 10.296** 8.430T-397 x Mukta -1.113 53.253 0.023 40.907 -0.095 7.753T-397 x Hira 5.247** 60.743 1.161 41.360 10.613** 8.663Neelam x Mukta 10.996** 62.850 -0.048 41.603 -0.121 7.450Neelam x Hira -4.247** 48.737 0.847 41.813 10.917** 8.690Mukta x Hira 2.682** 52.907 -0.074 40.963 9.183** 8.670S.E.(Sij) 2.768 1.402 0.370SE(Sij-Sik) 4.069 2.061 0.543

Table 3: Cont....

et al. (2013) and Pali and Mehta (2014).

REFERENCES

Anonymous. 2013. Annual report linseed, AICRP (All IndiaCoordinated Research Project) on linseed, Kanpur., India.

Arora, N., Kashyap, L., Gill, R. S. and Thind, S. 2018. Assessment ofgenetic divergence among sugarcane genotypes (Saccharum officinarumL.) based on molecular markers. The Bioscan. 13(1): 41- 45.

Atri, C. and Kumar, H. 2018. Assessment of genetic diversity ingermplasm collection of linseed (Linum usitatissimum L.). The Bioscan.13(1): 95 - 99.

Awasthi, S. K. and Rao, S. S. 2005. Selection parameters for yield andits components in linseed (Linum usitatissimum L.). Indian J. Geneticsand Plant Breeding. 65(4): 323-324.

Bhateria, S., Sood, S. P. and Pathania, A. 2002. Genetic analysis ofquantitative traits across environments in linseed (Linum usitatissimumL.). Euphytica. 150(1/2): 185-194.

BIS No. 15:548 (Part I). 1964. and 15:2052. 1968. Bureau of IndianStandards, New Delhi.

Cockerham, C. C. 1961. Implication of genetic variance in a hybridbreeding programme. Crop Sci.1: 47-52.

Deepak Gauraha, S. S. Rao and Pandagare, J. M. 2011. Geneticanalysis of yield and yield attributing characters in linseed (Linumusitatissimum L.). Asian. J. Bio. Science Vol. 6 Issue 1 (April, 2011) :PP.16-22.

Deepu, T. M., Deshpande, S. K. and Mani, B. R. 2018. Geneticvariability and association analysis for yield and its components in F2and F3 segregating generations of the maize (Zea mays L.) cross BM125x BM135. The Bioscan. 13(1): 109-112.

Goral, H., Ejsmond, M., Biuletyn, I. H. and Aklimatyzacji, R. 2008.Combining ability and heritability of yield componentsin linseed (Linum usitatissimum L.).Plant Archive. 12(249): 209-215.

Griffing, B. 1956. Concept of general and specific combining abilityin relation to diallel crossing system. Anst. J. Biol. Sci. 9: 463-493.

Hassanein, M. S., Al-Kordy, M. A. A. and El-Hariri, D. M. Evaluation2012. Correlation and Path Coefficient Analysis among Straw Yieldand Its Attributes of Fiber Flax (Linum usitatissimum L.) Cultivars. J.


214

AJEET KUMAR et al.,

Applied Sciences Research. 8(3): 1539-1546.

Jakhar, D. S., Singh, R., Ojha, V. K., Kumar, C. and Chandel A. K.2018. Estimation of genetic variability, heritability and genetic advancein genotypes of maize (Zea mays L.). The Bioscan. 13(1): 159 – 162.

Jinks, J. L. and Hayman, B. I. 1953. The analysis of diallel crosses.Maize Genetics Coop. News Letter. 27: 48-54.

Kalia, N. R. 1972. Combining ability graphical analysis and heterosisin linseed (Linum usitatissimumL.). M.Sc. Thesis, P.A.U., Ludhiana.

Kaushal, P. K., Srivastava, S. R. and Goswami, U. 1974. Combiningability for oil content in linseed. Indian J. Agric. Sci. 44: 859-862.

Khorgade, P. W., Sakhare, B. N., Narbhede, M. N. and Rout, S. K.1993.Genetic analysis of seed yield and its attributes in linseed.Biovigyan.19(1-2): 7-10.

Kiran, V. K. Sood and Bhateria, S. 2012. Detection of GeneticComponents of Variation for Yield, Fibre and Quality Traits in Flax(Linum usitatissimum L.). J. Agricultural Science. Vol. 4, No. 10.

Kumar, C., and Singh, S. P. 2018. Exploitation of heterosis andinbreeding depression for yield, hybrid seed yield, nutritional andprocessing quality improvement in tomato (Solanum lycopersicumL.) under North Indian conditions. The Bioscan. 13(1): 77 – 80.

Kumar, N. and Paul, S. 2015. Genetic analysis of yield and yieldcontributing traits in linseed (Linum usitatissimum L.). The Bioscan.10(4): 1951-1955.

Manfroni De Silvero., Sang, D. H., Copnde, A. A. and Sievero Sanz,O.I.1989. Combining ability in a diallel cross of linseed. BoletinGenetico. 15: 9-14.

Mishra, V. K. and Rai, M. 1993. Estimates of heterosis for seed yieldand oil linseed (Linum usitatissimumL.). Indian J. Genetics. 53(2):161-164.

Mohammadi, A. A., Saeidi, G. and Arzani, A. 2010. Genetic analysis ofsome agronomictraits in flax (Linum usitatissimum L.). Australian J.Crop Science .4(5): 343-352.

Nath, A. and Maloo, S. R. 2018. Heterosis studies for yield and yieldcomponents in greengram [Vigna radiata (L.) Wilczek]. The Bioscan13(1): 89- 94.

Nie, Z., Gui, B. C. Chen, F. T. and liang, A. Q. 1991. Study on thecombining ability of the principle agronomic characters in flax (LinumusitatissimumL.). Ningxia J. Agro forestry Sci. and Tech. 4: 4-7.

Official and Tentative Methods, of the American Oil Chemists’ Society(AOCS), 3rd edition. AOCS, Champaign, Illinois. 1973.

Pali, V. and Mehta, N. 2014. Combining ability and heterosis forseed yield and it’sattributesin linseed (Linum usitatissimum L.). TheBioscan. 9(2): 701-706.

Parimala, K. and Raju C. S. 2018. Extent of heterosis over environmentsin rice hybrids using CMS system. The Bioscan. 13(1): 53- 57.

Patil, V. D. and Chopde, P. R. 1983. Heterosis in relation to GCAand SCA effects in linseed. Indian J. Genet. 43(2): 226-228.

Pillai, B., Khorgade, P. W. and Narkhede, M. N. 1995. Geneticbehaviour of yield and its components in linseed. J. Oilseeds Res.12(1): 5-9.

Popescu, E., Vasile, I. and Marinescu, I. 1995. Studies on the geneticscontrol of flowering duration in flax. Problem de Genetica TheoreticasiApplicata. 27(2): 79-100.

Rai, M. and Das, K. 1975. Combining ability for components of yieldin linseed. Indian J. Genet. 34: 371-375.

Sahu, J. K., Sharma, G., Nair, S. K. and Singh, R. 2018. Studies ongenetic variability, heritability and genetic advance in African marigold(Tagetes erecta L.). The Bioscan 13(2): 117-120.

Sana, A. Y., Pithi, M. S., Mehta, D. R. and Raval, L. 2018. Correlationand path analysis in F2 generation of mungbean (Vigna radiata (L.) R.Wilczek). The Bioscan. 13(1): 121-124.

Savita, Singh, D. K. and Tomer A. 2018. Genetic variability andcorrelations in French bean for yield improvement. The Bioscan 13(1):137- 140.

Simopoulos, A. P. 2002. Omega -3 fatty acids in inflammation andautoimmune diseases. J. the American College of Nutrition. 21: 495-505.

Singh, S. B., Marker, S. and Kaleem, M. 2008. Combining abilityanalysis for grain yield and its attributes in linseed (Linum usitatissimumL.). J. Maharashtra Agricultural Universities. 33(2): 184-186.

Singh, S., Solanki, S. D., Prajapati, N. N. and Chaudhary B. 2018.Combining ability and heterosis analysis for seed yield and it’scontributing traits in karingada [Citrus lanatus (Thumb) Mnsf.]. TheBioscan. 13(1): 125- 128.

Singh, V., Pachauri, O. P. and Tiwari, S. N. 1990. Combining abilitystudies in linseed (Linum usitatissimum L.). Indian J. Genet. 47:171-178.

Thakur, H. L., Rana, N. D. and Sood, O. P. 1988. Combining abilityanalysis for some quantitative characters in linseed. Indain J. Genet.47(1): 6-10.

Thakur, M., Kumar, R. and Kumar, S. 2018. Estimation of heterosis ofearliness and yield contributing traits in cucumber (Cucumis sativusL.). The Bioscan. 13(1): 163 -168

Tiwari, N. 1999. Genetic analysis of yield and quality parameters inlinseed.(Linum usitatissimumL.). Adin. Plant Sci. 8:155-168.

Vishnu, A.; Shah, M. A. and Lakshyadeep 2005. Studies on heterosisand combining ability for fatty acids in linseed (Linum usitatissimumL.).Indain J. Genetics. 63(5): 29-35.

Yadav, P., Verma, P. N., Yadav, R. K. and Singh, S. 2013. Combiningability and heterosis analysis for seed yield and its related traits inlinseed (Linum usitatissimum L.). Research. 8: 593-596.

NSave Nature to Survive - The Bioscan

Documents

Transcript of NSave Nature to Survive - The Bioscan