The Journal of Research ANGRAU

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GENETIC VARIABILITY, HERITABILITY AND CHARACTER ASSOCIATION STUDIES Brix per cent registered has considerable environment influence. However, high heritability and moderate genetic advance expressed as per cent of mean was recorded revealing the major role of additive gene action in genetic control of this trait. These results were in accordance with the reports of Sankarapandian (2002), Sandeep et al. (2009a) and Rajappa (2009) for heritability and genetic advance, but contradicts with the results obtained by Sankarapandian et al. (1996) and Rajappa (2009) with respect to GCV and PCV estimates who reported relatively higher values. Higher heritability and genetic advance for this trait indicate effectiveness of simple direct selection in improvement programmes. Juice yield registered higher PCV and GCV values with negligible difference between them, indicating less influence of environment on the expression of this trait. This also recorded high broad sense heritability (98.27%) coupled with high genetic advance as per cent of mean (123.06%) indicating predominant role of additive gene action in the genetic control of this trait. Higher values for this trait was earlier reported by Rajappa (2009) for PCV and GCV values and by Sankarapandian et al. (1996), Sankarapandian (2002), Kachapur and Salimath (2009) and Rajappa (2009) for heritability and genetic advance. This trait can be considered as a potential for improvement by simple selection owing to high heritability and genetic advance. Juice extraction per cent exhibited higher values of PCV and GCV with narrow difference between them, indicating less influence of environment on the expression of the trait. This is coupled with high heritability (95.03%) and genetic advance as per cent of mean (43.80%) indicating predominant role of additive gene action. Similar results with respect to heritability and genetic advance were reported earlier by Sankarapandian (2002) and Sandeep et al. (2009a). Total soluble sugars exhibited moderate value of PCV and low value of GCV with negligible differences between them indicating less influence of environment on the expression of this trait. Broad sense heritability and genetic advance estimates were also higher. Moderate variability of this trait coupled with high heritability and genetic advance indicate higher scope for further improvement through simple selection procedures. Moderate value of PCV and low value of GCV were registered by bioethanol yield coupled with high broad sense heritability and moderate genetic advance expressed as per cent of mean indicating major role of additive gene action in the genetic control of this trait. Sugar yield registered higher values of PCV and GCV compared to all other traits under study with considerable difference between them indicating substantial environmental influence on the expression of this trait, which is reflected in relatively higher broad sense heritability (95.16%) and high genetic advance expressed as per cent of mean (123.47%) indicating major role of additive gene action in the genetic control of this trait. Result of the present study is in conformity with the earlier reports of Krishnakumar et al. (2004) and Patel et al. (2006) with respect to heritability and genetic advance. Though heritability and genetic advance indicate scope for simple direct selection to be effective for this trait, actual gain would entirely depend on its intrinsic association with its attributing traits. Correlation Coefficients The correlation co-efficients among the selected characters related to fresh stalk yield and sugar yield in F 2 population of ‘27 B × SSV 84’ sweet sorghum cross were estimated; results were tabulated in Table 2 and 3 and briefly described in the following paragraphs. Association of fresh stalk yield with its component characters Fresh stalk yield per plant was significantly and positively associated with total biomass per plant, grain yield per plant, plant height, nodes per plant, stem girth, days to 50% flowering and days to maturity. Similar trends were evident from the studies of Hapase and Repale (1999), Nahar et al. (2002), Krishnakumar et al., (2004), Singh and Khan (2004), Kadian and Mehta (2006), Patel et al. (2006) and Unche et al. (2008b). Among the fresh stalk yield attributing characters, positive and significant association was noticeable between days to 50% flowering with days to maturity, plant height, grain yield per plant, nodes per plant, total biomass per plant and stem girth; plant height with nodes per plant, total biomass per plant, stem girth and grain yield per plant; nodes per plant with total biomass per plant, grain yield per plant and stem girth; stem girth with total biomass per plant and grain yield per plant; total biomass per plant with 38
VEMANNA et al grain yield per plant. These findings were in confirmation with the findings of Manickam and Das (1994), Ganesh et al. (1995), Verma et al. (1999) and Kachapur and Salimath (2009). However, positive and significant association of days to flowering and plant height observed in the present study contradicts with the report of Manickam and Das (1994) who observed negative significant correlation of days to flowering with plant height and plant height with stem girth. Thus, to improve the fresh stalk yield in sweet sorghum it is important to select the plants with relatively higher plant height, total biomass, stem girth, nodes per plant and days to maturity, as these traits had direct relation with fresh stalk yield as indicated by their positive and significant association. Hence, fresh stalk yield can be increased by following indirect selection using above associated traits in sweet sorghum. Association of sugar yield with its component characters Association between sugar yield was positive and highly significant with juice yield per plant, fresh stalk yield per plant, total biomass per plant, grain yield per plant, total soluble sugars, brix per cent, bioethanol yield per plant and juice extraction per cent. The results of the present investigation were in corroborative with Mallikarjun et al. (1998), Hapase and Repale (1999), Verma et al. (1999), Singh and Khan (2004), Kadian and Mehta (2006) and Unche et al. (2008b). Association among sugar yield attributing characters The association of total biomass with fresh stalk yield per plant, juice yield per plant, grain yield per plant, brix per cent, total soluble sugars and bioethanol yield per plant; fresh stalk yield per plant with juice yield per plant, grain yield per plant, brix per cent, total soluble sugars and bioethanol yield per plant; grain yield per plant with juice yield per plant; brix per cent with total soluble sugars, bioethanol yield per plant, juice extraction per cent and juice yield per plant; juice yield per plant with juice extraction per cent, total soluble sugars and bioethanol yield per plant; juice extraction per cent with total soluble sugars and bioethanol yield per plant; total soluble sugar with bioethanol yield per plant were positive and significant. The reports of Ganesh et al. (1995), Singh and Khan (2004), Kadian and Mehta (2006), Kachapur and Salimath (2009), Unche et al. (2008b) and Sandeep et al. (2010) were in agreement with the above results. The results on association of sugar yield with its attributing traits indicated importance of juice yield, fresh stalk yield, total biomass, grain yield, total soluble sugars, brix per cent, bioethanol yield and juice extraction per cent in improving sugar yield as these traits had direct relation with sugar yield. Hence, improvement in these traits automatically improve sugar yield. Thus, the above correlated traits can be effectively utilized in formulating indirect selection schemes. Path analysis The correlation estimates are the sum total of direct effect and indirect effects of an independent character on a dependent character and it is quite obvious that the correlation (positive or negative) may be of small magnitude and non-significant in spite of its direct effect and/or some of the indirect effects are operating in the opposite direction. Therefore, path analysis is required to partition the correlation value of independent characters on dependent character into direct and indirect effects so as to get a correct picture of the association of characters. Hence, path co-efficient analysis was carried out to know the direct and indirect effects of the component characters on sugar yield and the results are presented in Table 4. The results of path analysis of component characters of sugar yield indicated maximum positive direct effect of total soluble sugars and juice yield on sugar yield whereas bioethanol yield, fresh stalk yield and total biomass has very high, moderate and low negative direct effect, respectively on sugar yield. However, all the traits exhibited moderate to high positive indirect effect via juice yield and total soluble sugars. The indirect effect via total biomass and fresh stalk yield is negative and low to moderate while juice extraction per cent is negligible and negative. These results were in accordance with the earlier reposts of Mallikarjun et al. (1998), Hapase and Repale (1999) and Kachapur and Salimath (2009). In general, the results revealed that the indirect contribution of the characters viz., total biomass, fresh stalk yield and juice extraction per cent via juice yield resulted in their positive correlation with sugar yield. 39
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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 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: VEMANNA et al The range in mean val
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
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ABIRAMI et al Socio-economic Impact
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ABIRAMI et al socio-economic impact
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Research Notes J.Res. ANGRAU 41(1)
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VEMANNA et al Table 1. Discriminant
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VEMANNA et al total biomass, fresh
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RAO et al Table 1. Plant height, nu
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DEVI et al S.No Category Frequency
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DEVI et al extension contact and ma
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NIRMALA and VASANTHA earliness in a
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NIRMALA and VASANTHA adopted this t
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SUDHARANI et al Table 1. Genotypic
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SUDHARANI et al At genotypic level,
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NIRMALA et al weight of pods per pl
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NIRMALA et al Table 3. Cluster mean
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PUNYAVATHI and VIJAYALAKSHMI 6.5 6.
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PUNYAVATHI and VIJAYALAKSHMI REFERE
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KATTEL et al Table 1. Item Analysis
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RADHIKA et al Thus, the results of
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RAJU et al estimated daily dietary
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RAJU et al Table 3. Physico-chemica
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MINNIE et al Table 2. Estimates of
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Statement about ownership and other
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GUIDELINES FOR THE PREPARATION OF M
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ESSENTIAL REQUIREMENTS FOR CONSIDER
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