The Journal of Research ANGRAU

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CORRELATION AND PATH COEFFICIENT ANALYSIS FOR YIELD Table 2. Genotypic (G) and phenotypic(P) direct and indirect effects among grain yield, its components and physiological traits in F 1 hybrids of rice under saline soils Residual effect =0.08005 PH (cm): Plant height; DFF: Days to 50% flowering; TT: Number of tillers plant -1 ; PT: Number of productive tillers plant -1 ; PL (cm): Panicle length; PW(g): Panicle weight; NFGP -1 : Number of filled grains panicle -1 ; SF (%): Spikelet fertility per cent; TW (g): 1000-grain weight; GY (g): Grain yield (g plant -1 ); SES: SES for visual salt injury; RSR: Root /shoot ratio; HI (%): Harvest index per cent; Na + /K + R: Sodium Potassium ratio; SPAD: SPAD chlorophyll meter reading. 112
SUDHARANI et al At genotypic level, number of total tillers plant -1 (1.0876) exhibited highest positive effect on yield (Table 2), while substantial magnitude of positive direct effect was also exerted by spikelet fertility (0.4417). On the other hand, moderate direct effects were shown by SES for visual salt injury (0.2692) and root shoot ratio (0.2927). The direct effects of productive tillers plant -1 (-0.5877), panicle length (-0.3681) and panicle weight (-0.3495) were high, but negative, while moderate influence in the same direction was exhibited by SPAD chlorophyll meter readings (-0.2290). The direct positive effects on yield were reported for number of grains panicle -1 (Sajjad, 1990), harvest index (Tripathi et al., 2011) and productive tillers plant -1 (Natarajan et al., 2005 and Tripathi et al., 2011). Therefore, more emphasis may be given to spikelet fertility per cent and number of tillers plant -1 while executing selections under saline soil conditions. The results of present investigation indicate selection under saline condition would be effective for number of total tillers per plant, spikelet fertility per cent as they showed significant positive association as well as direct effect on yield. Similarly, selecting the plants with low Na + /K + ratio would help for yield improvement along with salt tolerance as this trait showed significant negative association as well as negative direct effect on grain yield under stressed conditions Hence, these traits may be prioritized for developing ideotype(s) for saline environment. REFERENCES Al-Jibouri, H.A., Miller, P.A and Robinson, H.F. 1958. Genotypic and environmental variances and co-variances in an upland cotton cross of interspecific origin. Agronomy Journal. 50: 633- 636. Asch, F., Dingkunn, M., Dorffling, K and Miezank. 2000. Leaf K/N ratio predicts salinity induced yield loss in irrigated rice. Euphytica. 113: 109- 118. Balan, A., Muthiah, A.R and Boopathi, S.N.M.R. 1999. Genetic variability, character association and path coefficient analysis in rainfed rice, under alkaline condition. Madras Agricultural Journal. 86 (1/3): 122-124. Bala, A. 2001. Genetic variability, association of characters and path coefficient analysis of saline and alkaline rice genotypes under rainfed condition. Madras Agricultural Journal. 88(4- 6): 356-357. Buu, C.B and Tuan, T.M. 1991. Genetic study in the F 2 crosses for high grain quality. International Rice Research Newletter. 16: 11. Dewey, D.R and Lu, K.N. 1959. Correlation and path coefficient analysis of components of crested wheat grass seed production. Agronomy Journal. 51: 515-518. Fisher. R.A and Yates, F. 1963. Statistical Tables for Biological, Agricultural and Medical Research (6 th Edition), Hafner Publishing Company, New York, Natarajan, S.K., Saravanan, S., Krishnakumar, S and Dhanalakshmi, R. 2005b. Interpretations on association of certain quantitative traits on yield of rice (Oryza sativa L.) under saline environment. Research Journal of Agriculture and Biological Sciences. 1(1): 101-103. Ravindra Babu, V. 1996. Study of genetic parameters, correlations and path coefficient analysis of rice (Oryza sativa L.) under saline conditions. Annals of Agricultural Research. 17(4): 370- 374. Sajjad, M.S. 1990. Correlations and path coefficient analysis of rice under controlled saline environment. Pakistan Journal of Agricultural Research. 11(3): 164-168. Singh, P. K and Chaudhary, B. D.1985. Biometrical Methods in Quantitative Genetic Analysis (1 st Edition), Kalyani Publishers, New Delhi, India. Tripathi, S., Verma, O.P., Dwived, D.K., Yadavendra Kumar., Singh, P.K and Verma, G.P. 2011. Association studies in Rice (Oryza Sativa L.) hybrids under saline alkaline environment. Environment and Ecology. 29(3) 1557-1560. Wright, S. 1921. Correlation and causation. Journal of Agricultural Research. 20: 557-585 Zeng, L and Shannon, M.C. 2000. Salinity effects on seedling growth and yield components of rice. Crop Science. 40: 996-1003. 113
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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
Page 61 and 62: Research Notes J.Res. ANGRAU 41(1)
Page 63 and 64: KIRTHY et al Akhtar et al., 2008; S
Page 65 and 66: KIRTHY et al El Gharras H. 2009. Po
Page 67 and 68: SANDYARANI et al Weed parameters li
Page 69 and 70: SANDYARANI et al Table 2. Influence
Page 73 and 74: KUMAR et al Table 2. Effect of seed
Page 77 and 78: DEEPAK et al Table 2 Price spread a
Page 81 and 82: YAMINI et al Table 3. Estimates of
Page 83 and 84: YAMINI et al coupled with high per
Page 85 and 86: 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
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: SUDHARANI et al Table 1. Genotypic
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
Page 139 and 140: MINNIE et al Table 2. Estimates of
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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