Correlation Coefficient -1 0 1 Negative No Positive Correlation Correlation Correlation.
CORRELATION AND PATH ANALYSIS FOR YIELD AND YIELD ... · AGRICULTURAL RESEARCH COMMUNICATION CENTRE...
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AGRICULTURAL RESEARCH COMMUNICATION CENTRE www.arccjournals.com / indianjournals.com Legume Res., 34 (3) : 178 - 183, 2011 CORRELATION AND PATH ANALYSIS FOR YIELD AND YIELD COMPONENTS IN BLACK GRAM [VIGNA MUNGO (L.) HEPPER] H.A. Shivade*, A.P. Rewale and S.B. Patil Department of Agricultural Botany, Dr. Balasaheb Sawant Konkan Krishi Vidyapeeth., Dapoli - 415 712, India. Received : 17-01-2010 Accepted : 16-06-2011 ABSTRACT Thirty six genotypes of black gram were studied in randomized block design with three replications for correlations, and direct and indirect effects for fifteen quantitative characters. The yield contributing characters viz. , plant height, number of branches per plant, number of clusters per plant, number of pods per plant, number of pods per cluster, length of pod, number of seeds per pod and dry matter per plant had strong positive association with seed yield per plant at both the phenotypic and genotypic level. The characters days to first flowering, number of clusters per plant, number of pods per cluster, length of pod, 100-seed weight, dry matter per plant, harvest index, number of seeds per pod and number of branches per plant had positive direct effect on seed yield per plant at genotypic level. The selection based on number of clusters per plant, number of pods per plant, dry matter per plant, plant height, number of branches per plant, number of seeds per pod, length of pod and number of pods per cluster could help in genetic improvement of seed yield per plant in black gram population under study. Key words : Correlation, Path analysis, Blackgram. INTRODUCTION India has distinction of being world's largest producer of pulses. The production of pulses in the country is 132.46 lakh tones from an area of 223.64 lakh hectares, with productivity of 592 kg per hectare (Anonymous, 2007). Among the pulses, black gram is important pulse crop grown in Andhra Pradesh, Madhya Pradesh, Orissa, Karnataka, Maharashtra, Tamil Nadu and Uttar Pradesh during Kharif season. As seed yield is very complex character and depends upon numerous genetic factors interacting with the environment, it is always advisable to find out the interrelationship of yield component with highly heritable characters and giving selection pressure on these characters, which accounts for the indirect selection. To accumulate optimum contribution of yield contributing characters, it is essential to know the correlation of various characters along with path coefficients. The present study was undertaken to estimate phenotypic and genotypic associations between yield contributing characters alongwith path analysis for developing suitable selection criterion for blackgram improvement. MATERIALS AND METHODS The experimental material comprised of 25 promising lines of blackgram from the Oilseed Research Station, Jalgaon and 9 promising lines from Department of Agricultural Botany, Dr. Panjabrao Deshmukh Krishi Vidyapeeth, Akola, Maharashtra and 2 local cultivars collected, one *Regional Agricultural Research Station, Karjat - 410 201, Dist. Raigad, India. (E-mail : [email protected])
Transcript of CORRELATION AND PATH ANALYSIS FOR YIELD AND YIELD ... · AGRICULTURAL RESEARCH COMMUNICATION CENTRE...
AGRICULTURAL RESEARCH COMMUNICATION CENTRE
www.arccjournals .com / indianjournals .comLegume Res., 34 (3) : 178 - 183, 2011
CORRELATION AND PATH ANALYSIS FOR YIELD AND YIELD COMPONENTS INBLACK GRAM [VIGNA MUNGO (L.) HEPPER]
H.A. Shivade*, A.P. Rewale and S.B. Patil
Department of Agricultural Botany,Dr. Balasaheb Sawant Konkan Krishi Vidyapeeth., Dapoli - 415 712, India.
Received : 17-01-2010 Accepted : 16-06-2011
ABSTRACTThirty six genotypes of black gram were studied in randomized block design with three
replications for correlations, and direct and indirect effects for fifteen quantitative characters.The yield contributing characters viz., plant height, number of branches per plant, number of clustersper plant, number of pods per plant, number of pods per cluster, length of pod, number of seeds perpod and dry matter per plant had strong positive association with seed yield per plant at both thephenotypic and genotypic level. The characters days to first flowering, number of clusters per plant,number of pods per cluster, length of pod, 100-seed weight, dry matter per plant, harvest index,number of seeds per pod and number of branches per plant had positive direct effect on seed yieldper plant at genotypic level. The selection based on number of clusters per plant, number of podsper plant, dry matter per plant, plant height, number of branches per plant, number of seeds perpod, length of pod and number of pods per cluster could help in genetic improvement of seed yieldper plant in black gram population under study.
Key words : Correlation, Path analysis, Blackgram.
INTRODUCTIONIndia has distinction of being world's largest
producer of pulses. The production of pulses in thecountry is 132.46 lakh tones from an area of 223.64lakh hectares, with productivity of 592 kg per hectare(Anonymous, 2007). Among the pulses, black gramis important pulse crop grown in Andhra Pradesh,Madhya Pradesh, Orissa, Karnataka, Maharashtra,Tamil Nadu and Uttar Pradesh during Kharif season.As seed yield is very complex character and dependsupon numerous genetic factors interacting with theenvironment, it is always advisable to find out theinterrelationship of yield component with highlyheritable characters and giving selection pressureon these characters, which accounts for the indirect
selection. To accumulate optimum contribution ofyield contributing characters, it is essential to knowthe correlation of various characters along with pathcoefficients. The present study was undertaken toestimate phenotypic and genotypic associationsbetween yield contributing characters alongwithpath analysis for developing suitable selectioncriterion for blackgram improvement.
MATERIALS AND METHODSThe experimental material comprised of 25
promising lines of blackgram from the OilseedResearch Station, Jalgaon and 9 promising linesfrom Department of Agricultural Botany, Dr.Panjabrao Deshmukh Krishi Vidyapeeth, Akola,Maharashtra and 2 local cultivars collected, one
*Regional Agricultural Research Station, Karjat - 410 201, Dist. Raigad, India.(E-mail : [email protected])
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from Chandranagar and another from Tetawalivillages of Dapoli tehsil. Thirty six genotypes weregrown in randomized block design with threereplications at Research Farm, Department ofAgricultural Botany, Dr. Balasaheb SawantKonkan Krishi Vidyapeeth, Dapoli, (Maharashtra)during Kharif 2008. Each plot consisted of six rowsof 1.5m length with 15cm plant to plant and 45cmrow to row distance. The observations wererecorded on 5 randomly selected plants from eachplot for plant height, number of branches perplant, days to first flowering, days to 50 %flowering, days to maturity, clusters per plant, podsper plant, pods per cluster, length of pod, seedsper pod, 100-seed weight, dry matter per plant,harvest index, protein content and seed yield perplant. Correlation between fifteen quantitativecharacters was estimated according to the methodgiven by Singh and Chaudhary (1977); whereaspath coefficient analysis was done by methodgiven by Dewey and Lu (1959).
RESULTS AND DISCUSSIONThe estimates of genotypic and phenotypic
correlat ion coef f ic ient s between dif ferentcharacters of black gram genotypes are presentedin Table 1. In present investigation plant height,number of branches per plant, number of clustersper plant, number of pods per plant, number ofpods per cluster, length of pod, number of seedsper pod and dry matter per plant showed highlysignificant positive correlation with seed yield perplant at both phenotypic and genotypic level. Itsuggested that increase in growth related traits,pod characters and seed characters mightcontribute to high yields in black gram. Thissituation meant to select high yielding genotypesof black gram, it was essential to consider theabove characters with their increasing magnitude.It helped in simultaneous improvement of all thepositively correlated characters. Similar resultswere reported by Santha and Paramasivam(1999), Venkatesan et al. (2004) and Chauhan(2007). Protein content was negatively correlated
with seed yield per plant at both the phenotypicand genotypic level. Natarajan and Rathinasamy(1999), Veeranjaneyulu (2007) and Konda (2008)also reported the negative association with proteincontent.
Plant height, number of branches per plant,number of clusters per plant, number of pods perplant, length of pod, number of seeds per pod anddry matte r per plant were posit ively andsignificantly correlated with each other at bothphenotypic and genotypic level and they werenegatively correlated with harvest index andprotein content. These results were in agreementwith Savithramma et al. (1999), Konda (2008),Santha and Paramasivam (1999) and Chauhanet al. (2007).
Days to first flowering, days to 50 per centflowering and days to maturity were positively andsignificantly correlated with each other at bothphenotypic and genotypic level, while they hadpositive and significant correlation with length ofpod, number of seeds per pod and dry matters perplant at genotypic level. Number of pods per clustershowed positive and significant correlation withnumber of clusters per plant, number of pods perplant and number of seeds per pod. This characteralso exhibited positive correlation with all othercharacters except 100-seed weight and days to firstflowering at both the genotypic and phenotypic level.These results explained the simultaneousdevelopment in all the pod characters. Chauhan etal. (2007) reported similar results.
On the basis of correlation studies moreemphasis is to be given on number of clusters perplant, number of pods per plant, number of seedsper pod, number of pods per cluster, length of pod,plant height, number of branches per plant and drymatter per plant as yield contributing charactersbased on their strong correlation with seed yield perplant in black gram.
When more number of variables wereconsidered in correlation, the association becomes
180 LEGUME RESEARCH
Tabl
e 1
: E
stim
ates
of
geno
typi
c (a
bove
dia
gona
l) an
d ph
enot
ypic
(be
low
dia
gona
l) co
rrel
atio
n co
effic
ient
s am
ong
fifte
en q
uant
itativ
e ch
arac
ters
in
blac
kgra
m.
*Sig
nific
ant a
t 0.0
5 pr
obab
ility
leve
l.
**S
igni
fican
t at 0
.01
prob
abili
ty le
vel .
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Tabl
e 2:
D
irect
and
indi
rect
gen
otyp
ic e
ffect
of
14 q
uant
itativ
e ch
arac
ters
on
seed
yie
ld in
bla
ck g
ram
.
* Si
gnifi
cant
at 5
per
cen
t lev
el.
**
Sign
ifica
nt a
t 1 p
er c
ent l
evel
.
Res
idua
l effe
ct =
-0.0
9359
.
(Und
erlin
ed fi
gure
s ind
icat
e di
rect
effe
ct).
182 LEGUME RESEARCH
more complex and does not have the meaningfulinterpretation obvious. Hence, genotypic correlationpartitioned in to direct and indirect effects to specifythe cause and their relative importance, (Table 2).Days to first flowering, number of clusters per plant,number of pods per cluster, length of pod, 100-seedweight, dry matter per plant, harvest index, numberof seeds per pod and number of branches per plantexhibited positive direct effect on seed yield perplant. These characters have also been identifiedas major direct contributors towards seed yield inblackgram by earlier workers (Umadevi andMeenakshi 2005 and Konda 2008).
Plant height showed negative direct effecton seed yield per plant. This character had positiveindirect effect through number of clusters per plant,days to first flowering, length of pod and proteincontent, which resulted in positive and significantcorrelation with seed yield per plant. Higher positivedirect effect exhibited by days to first flowering onseed yield per plant but it had high negative indirecteffect via days to 50 per cent flowering, days tomaturity, plant height and number of pods per plant.This resulted in to positive but non-significantassociation between days to first flowering and seedyield per plant.
The direct positive effect of number ofclusters per plant and its positive indirect effectthrough length of pod, dry matter per plant andnumber of pods per cluster resulted in positiveand significant association with seed yield perplant. Umadevi and Meenakshi (2005) reportedpositive direct effect of number of clusters per planton seed yield per plant. The negative direct effect
of number of pods per plant was nullified bypositive indirect effects through number of clustersper plant, days to first flowering, length of pod,dry matter per plant and number of pods percluster which resulted in the posit ive andsignificant association with seed yield per plant.Number of pods per cluster had positive directeffect on seed yield per plant and positive indirecteffect through number of clusters per plant, lengthof pod, dry matter per plant and number of seedsper pod resulted in positive association with seedyield per plant.
The s t rong posi t ive associa t ion o fnumber o f seed per pod and number o fbranches per plant was observed due to theirpositive direct effects on seed yield per plantand positive indirect effect through number ofclusters per plant, days to first flowering andlength of pod. Kingshlin and Vanniarajan(2000) and Srividhya. et al. (2005) reportedpositive direct effect for these characters.
Length of pod and dry matter per plantexhibited positive association with seed yield perplant due to their positive direct effects on seed yieldper plant and positive indirect effect through eachother and days to first flowering, number of clustersper plant and protein content.
The study revealed that selection based onnumber of clusters per plant, number of pods perplant, dry matter per plant, plant height, number ofbranches per plant, number of seeds per pod, lengthof pod and number of pods per cluster could help ingenetic improvement of seed yield per plant in blackgram population under study.
REFERENCESAnonymous. (2007). Directorate of Pulses Development (Bhopal), Annual Progress report-2007.Chauhan, M.P., Mishra, A.C. and Singh, A.K. (2007). Correlation and path analysis in urdbean. Legume Res., 30 (3):
205-208.Dewey, D.R. and Lu, K.H. (1959). A Correlation and path coefficient analysis of component of wheat grass production.
Agron J., 51 : 515-518Kingshlin, M. and Vanniarajan, C. (2000). Association of yield attributes and component analysis among the quantitative
characters of rice fallow urdbean genotypes. Crop. Res., 19 (1): 102-105.
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Konda, C.R., Salimath, P.M. and Mishra, M.N. (2008). Correlation and path coefficient analysis in black gram (Vignamungo (L.) Hepper). Legume Res., 31 (3): 202-205.
Natarajan, C. and Rathinasamy, R. (1999). Genetic variability, correlation and path analysis in black gram. MadrasAgric. J., 86 (4-6): 228-231.
Singh, R.K. and Chaudhari, B.D. (1977). Biometrical methods in quantitative genetic analysis. Kalyani Publishers,New Delhi. pp.3938.
Santha, S. and Paramasivam, K. (1999). Correlation and path analysis in rice follow black gram (Vigna mungo).Madras Agric. J., 86 (7-9): 397-400.
Savithramma, D.L., Sridhara, Umashankar and Shivakumar, S. (1999). Genetic variability and D2 analysis in blackgram (Vigna mungo L.). Mysore J. agric. Sci., 33 (1): 64-68.
Srividhya, A., Reddy Sekhar, M. and Reddy. G.L.K. (2005). Correlation and path analysis in F2 generation of urdbean(Vigna mungo (L.) Hepper). Legume Res., 28 (4): 297-299.
Umadevi. M. and Meenakshi. N.G. (2005). Correlation and path analysis for yield and yields components in blackgram (Vigna mungo (L.)Hepper.) Madras Agric. J. 92 (10-12): 731-734.
Veeranjaneyulu, A., Eswari, K.B., Rao, V.S. and Ramana, J.V. (2007). Association analysis for yield and its componentsin black gram (Vigna mungo (L.) Hepper). The Andhra Agric. J., 54 (3-4): 385-387.
Venkatesan, M., Veeramani, N., Anbuselvam, J. and Ganesan, J. (2004). Correlation and path analysis in black gram(Vigna mungo L.) Legume Res., 27 (3): 197-200.
