The Journal of Research ANGRAU

More documents

Recommendations

Info

CONSTRUCTION OF SELECTION INDICES FOR F 2 POPULATION Sl. No. Discriminant Function GA RE (%) 34 Y = 0.61X 3 – 0.31X 2 + 15.62X 6 63.10 1923.78 35 Y = 0.05X 2 + 14.19X 4 + 0.10X 5 50.80 1548.63 36 Y = 0.07X 2 + 7.56X 4 + 1.41X 6 33.99 1036.31 37 Y = 0.05X 2 + 0.11X 5 + 16.13X 6 50.66 1544.42 38 Y = 0.15X 3 + 13.04X 4 – 0.09X 5 44.76 1364.64 39 Y = 0.10X 3 + 5.14X 4 + 1.09X 6 28.13 857.65 40 Y = 0.15X 3 – 0.09X 5 + 14.83X 6 44.64 1360.77 41 Y = 4.70X 4 + 0.04X 5 + 2.43X 6 20.10 612.67 42 Y = 0.13X 1 – 0.32X 2 + 0.62X 3 + 14.89X 4 66.73 2034.16 43 Y = 25.21X 1 – 0.22X 2 + 0.81X 3 – 4.64X 5 88.64 2702.34 44 Y = 0.14X 1 – 0.32X 2 + 0.62X 3 + 16.95X 6 66.61 2030.74 45 Y = 13.16X 1 + 0.15X 2 + 4.80X 4 – 2.24X 5 57.71 1759.40 46 Y = 0.82X 1 + 0.04X 2 + 7.36X 4 + 1.11X 6 37.91 1155.67 47 Y = 13.19X 1 + 0.15X 2 – 2.25X 5 + 5.35X 6 57.59 1755.58 48 Y = 13.73X 1 + 0.28X 3 + 3.26X 4 – 2.55X 5 52.37 1596.68 49 Y = 0.06X 1 + 0.10X 3 + 6.05X 4 + 1.57X 6 31.65 964.76 50 Y = 13.76X 1 + 0.28X 3 – 2.55X 5 + 3.61X 6 52.26 1593.20 51 Y = 4.57X 1 + 3.75X 4 – 0.68X 5 + 0.26X 6 25.16 766.93 52 Y = 0.74X 3 – 0.35X 2 + 21.70X 4 – 0.17X 5 80.55 2455.56 53 Y = 0.61X 3 – 0.31X 2 + 10.07X 4 + 4.58X 6 63.86 1946.72 54 Y = 0.74X 3 – 0.35X 2 – 0.17X 5 + 24.72X 6 80.42 2451.75 55 Y = 0.05X 2 + 11.34X 4 + 0.11X 5 + 3.61X 6 51.56 1571.89 56 Y = 0.14X 3 + 10.01X 4 – 0.09X 5 + 3.81X 6 45.48 1386.50 57 58 59 60 61 Y = 21.88X 1 – 0.23X 2 + 0.81X 3 + 5.40X 4 – 4.12X 5 Y = 0.17X 1 – 0.32X 2 + 0.62X 3 + 10.78X 4 + 5.02X 6 Y = 21.93X 1 – 0.23X 2 + 0.81X 3 – 4.12X 5 + 6.02X 6 Y = 13.31X 1 + 0.15X 2 + 8.60X 4 – 2.27X 5 – 4.17X 6 Y = 13.89X 1 + 0.28X 3 + 6.57X 4 – 2.57X 5 – 3.61X 6 89.70 2734.65 67.39 2054.36 89.59 2731.24 58.50 1783.51 53.12 1619.52 GA = Genetic advance; RE = Relative efficiency 96
VEMANNA et al total biomass, fresh stalk yield, brix per cent and juice yield which exhibited maximum relative efficiency, same could be considered for selection schemes. Bhat and Shariff (1994) in finger millet, Patil et al. (1997) in sunflower and Khulbe and Pant (1999) in mustard obtained similar results of increased efficiency through indirect selection using different combination of characters excluding yield in selection index. Hence, it can be inferred that the maximum gain using indirect selection schemes could be achieved using highly correlated characters like total biomass, fresh stalk yield, brix per cent and juice yield, which is further confirmed by path coefficient as well as discriminant function analysis. REFERENCES Agrawal, R. K., Lal, I. P and Richharia, A. K., 1978. Note on selection indices and path coefficients in semi dwarf rice varieties. Indian Journal of Agricultural Science. 48: 58-60. Bhat, B. V and Shariff, R. A., 1994. Selection criteria in Finger millet (Eleusine coracana Gaertn.). Mysore Journal of Agricultural Sciences. 28: 5-7. Fisher, R. A., 1936. The use of multiple measurements to taxonomic problems. Annals of Eugenics. 7: 87-104. Khulbe, R. K and Pant, D. P., 1999. Selection indices in Indian mustard. [Brassica juncea (L.) Czern & Coss]. Crop Improvement. 26: 109-111. Mahadevappa, M and Ponnaiya, B. W. X., 1967. Discriminant functions in the selection of pearl millet (Pennisetum typhoids Stapf and Hubb.) population for grain yield. The Madras Agricultural Journal. 54: 211-222. Mannur, D. M., Salimath, P. M., Patil, S. S and Parameshwarappa, R., 1991. Genetic studies in interspecific crosses of soybean Glycine max (L.) Merill × Glycine formosa. Indian Journal of Genetics and Plant Breeding. 51: 471-475. Mathur, R. K and Gupta, S. C., 1992. Discriminant function analysis in Niger (Guizotia abyssinica Cass.). Crop Research. 5: 164-165. Nahar, S. M. N., Khaleque, M. A and Miah, M. A., 2002. Correlation, path co-efficient and construction of selection index in sugarcane. Pakistan Sugar Journal. 17: 2-10. Paroda, R. S and Joshi, A. B., 1970. Correlations, path co-efficients and the implication of discriminate function for selection in wheat (Triticum aestivum). Heredity. 25: 383-392. Patil, B. R., Rudraaradhya, M and Basappa, H., 1997. Construction of selection indices for varietal selection in sunflower (Helianthus annuus L.). Journal of Oilseed Research. 14: 172-174. Rahangdale, S. L., Khoragade, P. W and Raut, S. K., 1987. Construction of selection indices for varietal selection in upland Rice. Journal of Maharashtra Agricultural Universities. 12: 223- 224. Singh, S. P and Khan, A. Q., 1998. Selection indices for cane yield in sugarcane. Indian Journal of Genetics and Plant Breeding. 58: 353-357. Smith, H. F., 1936. A discriminant function for plant selection. Annals of Eugenics. 7: 240-250. 97
Page 1 and 2:
1
Page 3 and 4:
CONTENTS PART I : PLANT SCIENCE Eff
Page 5 and 6:
J.Res. ANGRAU 41(1) 1-4, 2013 EFFEC
Page 7 and 8:
EFFECT OF FOLIAR APPLICATION OF NPK
Page 9 and 10:
J.Res. ANGRAU 41(1) 5-13, 2013 NUTR
Page 11 and 12:
NUTRIENT UPTAKE BY RICE CROP UNDER
Page 13 and 14:
Page 15 and 16:
Page 17 and 18:
Page 19 and 20:
LAKSHMI et al Fig 1. Changes in C/N
Page 21 and 22:
LAKSHMI et al Changes in C/N ratio
Page 23 and 24:
LAKSHMI et al Table 3. Changes in h
Page 25 and 26:
J.Res. ANGRAU 41(1) 20-29, 2013 INF
Page 27 and 28:
PRASAD and PRASADINI of bulk densit
Page 29 and 30:
PRASAD and PRASADINI to as high as
Page 31 and 32:
PRASAD and PRASADINI Table 4 . Infl
Page 33 and 34:
PRASAD and PRASADINI Table 8. Influ
Page 35 and 36:
J.Res. ANGRAU 41(1) 30-38, 2013 GEN
Page 37 and 38:
VEMANNA et al The range in mean val
Page 39 and 40:
VEMANNA et al grain yield per plant
Page 41 and 42:
VEMANNA et al 41
Page 43 and 44:
VEMANNA et al Singh, S. P and Khan,
Page 45 and 46: RAMANA et al RESULTS AND DISCUSSION
Page 47 and 48: J.Res. ANGRAU 41(1) 42-46, 2013 A S
Page 49 and 50: RAJANNA et. al. Table 2. Reasons fo
Page 51 and 52: RAJANNA et al the present findings
Page 53 and 54: NARASIMHA et al Table 1. Proximate
Page 55 and 56: NARASIMHA et al Maynard, L., Lossli
Page 57 and 58: RAMANA et al with small follicles m
Page 59 and 60: 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: VEMANNA et al Table 1. Discriminant
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
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
show all

The Journal of Research ANGRAU

Create successful ePaper yourself

Delete template?

Save as template?