The Journal of Research ANGRAU

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CORRELATION AND PATH ANALYSIS FOR YIELD AND ITS COMPONENTS Path coefficient analysis was used to compute direct and indirect effects of six characters on grain yield. The characters number of productive tillers per plant, panicle length and number of grains per panicle with positive direct effects on yield could be considered as major yield contributing characters in rice. These findings were in agreement with the reports made by Karad and Pol (2008) for number of productive tillers per plant and panicle length and Satish Chandra et al. (2009) for number of grains per panicle. On the contrary negative direct effects were existed by days to 50 per cent flowering, plant height and 1000 grain weight. Gupta et al. (1998) also recorded similar kind of negative direct effect of these traits on yield. The characters, panicle length, number of grains per panicle showed positive indirect effect through number of productive tillers per plant on grain yield. Similar results were obtained by Gupta et al. (1998). The panicle length exhibited positive indirect effect through number of productive tillers per plant and number of grains per panicle. Number of productive tillers per plant, 1000 grain weight and panicle length showed positive indirect effect on grain yield through number of grains per panicle. These results were in accordance with the results obtained by Madhavilatha (2002). The characters days to 50 per cent flowering, plant height and 1000 grain weight were not only having negative direct effect on grain yield but also had negative association with the yield contributing characters. This was in consonance with the results of Gupta et al. (1998). Path analysis revealed the importance of the characters, number of productive tillers per plant, panicle length and number of grains per panicle in influencing the grain yield. Hence, selection should be practiced for these characters in order to isolate superior plant types for improvement of grain yield. Table 1.Estimation of correlation coefficients between yield and yield attributing characters Character Days to 50 % flowering Plant Height (cm) Number of productive tillers per plant Panicle Length (cm) Number of grains per panicle 1000 Grain Weight (g) Grain Yield/ Plant (g) Days to 50% P 1.0000 0.0622 0.0434 0.0992 0.2648** -0.2933** -0.0001 Flowering G 1.0000 0.0727 0.0109 0.0987 0.2590** -0.3024** -0.0181 Plant Height P 1.0000 0.3113** 0.2865** 0.1525 0.1620* 0.3197** (cm) G 1.0000 0.5046** 0.2958 ** 0.1606* 0.1845* 0.3964** Number of P 1.0000 0.1010 0.2048** -0.0175 0.8501** productive tillers/plant G 1.0000 0.1508 0.2512** 0.0233 1.0014** Panicle P 1.0000 0.2383** 0.3725** 0.1047 Length (cm) G 1.0000 0.2546** 0.4021** 0.1599* Number of P 1.0000 -0.3270** 0.2483** grains/panicle G 1.0000 -0.3425** 0.2711** 1000 Grain Weight (g)plant P 1.0000 -0.0329 G 1.0000 -0.0157 * Significant at 5% level ** Significant at 1% level
MINNIE et al Table 2. Estimates of genotypic direct and indirect effects between yield and yield contributing characters Character Days to 50% Flowering Plant Height (cm) Number of productive tillers/plant Panicle Length (cm) Number of grains/panicle 1000 Grain Weight (g) Days to 50 % flowering Plant Height (cm) Number of productive tillers per plant Panicle Length (cm) Number of grains per panicle 1000 Grain Weight (g) Grain Yield/ Plant (g) -0.0418 -0.0109 0.0116 0.0067 0.0008 0.0156 -0.0181 -0.0030 -0.1504 0.5389 0.0199 0.0005 -0.0095 0.3964** -0.0005 -0.0759 1.0680 0.0102 0.0008 -0.0012 1.0014** -0.0041 -0.0445 0.1611 0.0674 0.0008 -0.0207 0.1599* -0.0108 -0.0242 0.2682 0.0172 0.0031 0.0176 0.2711** 0.0126 -0.0278 0.0249 0.0271 -0.0011 -0.0515 -0.0157 Bold = direct effects Residual effect = -0.1520 REFERENCES Gupta, J. C., Kotoch, P. C., Kaushik, R. P and Sharma, S. L. 1998. Cause and effect relationship of yield and its components under cold stress condition in rice (Oryza sativa L.). Indian Journal of Agricultural Sciences. 68 (1) : 13-15 Janardhanam, V., Nadarajan, N and Jebaraj, S. 2001. Correlation and path analysis in rice (Oryza sativa L.). Madras Agricultural Journal. 88 : 719-720 Karad, S. R and Pol, K. M. 2008. Character association, genetic variability and path coefficient analysis in rice (Oryza sativa L.). International Journal of Agricultural Sciences. 4 (2) : 663-666 Madhavilatha, L. 2002. Studies on genetic divergence and isozyme analusis on rice (Oryza sativa L.). M.Sc. (Ag). Thesis submitted to Acharya N. G. Ranga Agricultural University, Hyderabad. Satish Chandra, B., Dayakar Reddy, T., Ansari, N. A and Sudheer Kumar, S. 2009. Correlation and path analysis for yield and yield components in rice (Oryza sativa L.). Agricultural Science Digest. 29 (1) : 45-47 Yogameenakshi, P., Nadarajan, N and Anbumalarmathi, J. 2004. Correlation and path analysis on yield and drought tolerant attributes in rice (Oryza sativa L.) under drought stress. Oryza. 41 (3&4) : 68-70
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CONTENTS PART I : PLANT SCIENCE Eff
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J.Res. ANGRAU 41(1) 1-4, 2013 EFFEC
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EFFECT OF FOLIAR APPLICATION OF NPK
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J.Res. ANGRAU 41(1) 5-13, 2013 NUTR
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NUTRIENT UPTAKE BY RICE CROP UNDER
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LAKSHMI et al Fig 1. Changes in C/N
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LAKSHMI et al Changes in C/N ratio
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LAKSHMI et al Table 3. Changes in h
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J.Res. ANGRAU 41(1) 20-29, 2013 INF
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PRASAD and PRASADINI of bulk densit
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PRASAD and PRASADINI to as high as
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PRASAD and PRASADINI Table 4 . Infl
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PRASAD and PRASADINI Table 8. Influ
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J.Res. ANGRAU 41(1) 30-38, 2013 GEN
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VEMANNA et al The range in mean val
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VEMANNA et al grain yield per plant
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VEMANNA et al 41
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VEMANNA et al Singh, S. P and Khan,
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RAMANA et al RESULTS AND DISCUSSION
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J.Res. ANGRAU 41(1) 42-46, 2013 A S
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RAJANNA et. al. Table 2. Reasons fo
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RAJANNA et al the present findings
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NARASIMHA et al Table 1. Proximate
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NARASIMHA et al Maynard, L., Lossli
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RAMANA et al with small follicles m
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RAMANA et al Characteristics of fol
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Research Notes J.Res. ANGRAU 41(1)
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KIRTHY et al Akhtar et al., 2008; S
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KIRTHY et al El Gharras H. 2009. Po
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SANDYARANI et al Weed parameters li
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SANDYARANI et al Table 2. Influence
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KUMAR et al Table 2. Effect of seed
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DEEPAK et al Table 2 Price spread a
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YAMINI et al Table 3. Estimates of
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YAMINI et al coupled with high per
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LOKESH et al Table 1. Clustering pa
Page 87 and 88: LOKESH et al Table 4. Mean values o
Page 89 and 90: ABIRAMI et al Socio-economic Impact
Page 91 and 92: ABIRAMI et al socio-economic impact
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Page 95 and 96: VEMANNA et al Table 1. Discriminant
Page 97 and 98: VEMANNA et al total biomass, fresh
Page 99 and 100: RAO et al Table 1. Plant height, nu
Page 103 and 104: DEVI et al S.No Category Frequency
Page 105 and 106: DEVI et al extension contact and ma
Page 107 and 108: NIRMALA and VASANTHA earliness in a
Page 109 and 110: NIRMALA and VASANTHA adopted this t
Page 111 and 112: SUDHARANI et al Table 1. Genotypic
Page 113 and 114: SUDHARANI et al At genotypic level,
Page 115 and 116: NIRMALA et al weight of pods per pl
Page 117 and 118: NIRMALA et al Table 3. Cluster mean
Page 123 and 124: PUNYAVATHI and VIJAYALAKSHMI 6.5 6.
Page 125 and 126: PUNYAVATHI and VIJAYALAKSHMI REFERE
Page 127 and 128: KATTEL et al Table 1. Item Analysis
Page 131 and 132: RADHIKA et al Thus, the results of
Page 133 and 134: RAJU et al estimated daily dietary
Page 135 and 136: RAJU et al Table 3. Physico-chemica
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Page 141 and 142: Statement about ownership and other
Page 143 and 144: GUIDELINES FOR THE PREPARATION OF M
Page 145: ESSENTIAL REQUIREMENTS FOR CONSIDER
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