The Journal of Research ANGRAU

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GENETIC VARIABILITY, HERITABILITY AND CHARACTER ASSOCIATION STUDIES RESULTS AND DISCUSSION The descriptive statistics and genetic variability parameters with respect to fourteen quantitative characters in F 2 population of the cross ‘27 B × SSV 84’ is presented in Table 1. These descriptive statistics, unravels basic idea of the breeding material. The characteristics of this F 2 population in respect of various quantitative characters as indicated by these first and second degree statistics are discussed below. Wide range of variability was present for the traits such as plant height, total biomass, fresh stalk yield, grain yield, juice yield, juice extraction per cent, sugar yield and bioethanol yield of this cross of sweet sorghum studied as indicated by their respective mean and variances. Existence of moderate variability was observed for days to 50% flowering and days to maturity. However, the variability range was low for the traits like nodes per plant, stem girth, brix per cent and total soluble sugars. The study of distribution properties such as co-efficients of skewness (third degree statistic) and kurtosis (fourth degree statistic) provides insight about the nature of gene action and number of genes controlling the traits, respectively. All the studies reported nature of genetic control of quantitative traits in sorghum is based on first degree (gene effects through generation mean analysis) and second degree (components of genetic variances through diallel, line × tester analysis, etc.) statistics. Skewness and kurtosis are greater than first and second degree statistics which reveal interaction genetic effects. The skewed distribution of a trait in general suggests that the trait is under the control of non-additive gene action, especially epistasis and influenced by environmental variables (Kimberg and Bingham, 1998 and Roy, 2000). Positive skewness is associated with complementary interaction and negative skewness is associated with duplicate (additive × additive) gene interactions predominantly in the same directions. Complete ambi-directional epistasis however produces kurtosis while distribution stays symmetrical around mean. The genes controlling the trait with skewed distribution tend to be predominantly dominant irrespective of whether they have increasing or decreasing effects on the expression of the trait. The traits with leptokurtic and platykurtic distribution are controlled by fewer and a large number of genes, respectively. Kurtosis is negative or close to zero in the absence of gene interactions and is positive in the presence of gene interactions. The inference on the relative number of genes and nature of genetic control of different traits in F 2 generation of this sweet sorghum cross is discussed below. Platykurtic and positively skewed distribution suggested the involvement of relatively large number of segregating genes with dominance based complementary type of interaction in the inheritance of days to 50% flowering, days to maturity, plant height, total biomass, fresh stalk yield, grain yield, juice yield, juice extraction per cent and sugar yield in ‘27 B × SSV 84’ cross. Maximizing the genetic gain in respect of these traits with positively skewed distribution requires intense selection from the existing variability. The inheritance of nodes per plant and stem girth recorded negatively skewed platykurtic distribution which indicates that these traits are governed by large number of dominant genes with duplicate type of epistasis. These traits have evolved with dominance and dominance based duplicate epistasis which helps to protect the individual plants from deleterious alleles arising from existing variability (Roy, 2000). The leptokurtic and positively skewed distribution for traits such as brix per cent, total soluble sugars and bioethanol yield suggested the involvement of relatively fewer number of segregating genes with dominance based complementary interaction in the inheritance of these traits. To achieve maximum genetic gain in respect of these traits needs intense selection. Estimation of variability parameters in a population is a pre-requisite for breeding programme aimed at improving yield, quality and other important characters under consideration. Unless a major portion of variation is heritable, attempts to improve characters by selection would be futile. Therefore, it is necessary to have information on both PCV and GCV, so that the heritability, which helps the breeder to predict the expected genetic advance possible by selection for characters, can be computed. According to Johnson et al. (1955), heritability estimates along with genetic gain would be more useful than the former alone in predicting the effectiveness of selection. Therefore it is essential to consider the predicted genetic advance along with heritability estimate as a tool in selection programme for better efficiency. 36
VEMANNA et al The range in mean values does not reflect the total variance in the material studied. Hence, actual variance has to be estimated for the characters to know the extent of existing variability. However absolute values of phenotypic and genotypic variance cannot be used for comparing the degree of variability in different characters because the characters differ in the unit of measurement. Hence, the co-efficient of variation (PCV and GCV) which is calculated by considering the respective means have been used for the comparisons. In the present study, the range of variability was quite high for most of the characters studied except days to 50% flowering, days to maturity, nodes per plant, stem girth, brix per cent and total soluble sugars, which exhibited low to moderate amount variability. This indicates ample scope for the improvement of highly variable characters, which were generated by segregation and recombination, whereas, it may not be equally effective for a character, which exhibited narrow range of variability. In general, PCV values were relatively higher than GCV values which is coupled with negligible differences between them, indicates less environmental influence on most of the traits except nodes per plant, stem girth, grain yield, brix per cent, total soluble sugars, sugar yield and bioethanol yield. Days to 50% flowering and days to maturity exhibited lower values of GCV and PCV. This was in conformity with the reports of Rajappa (2009). High heritability coupled with low genetic advance as per cent of mean exhibited by this cross, indicated predominant role of non-additive gene action for these traits and this result is in accordance with the reports of Sankarapandian (2002). Patil et al. (1996), Sankarapandian (2002), Unche et al. (2008a) and Kachapur and Salimath (2009) also reported high heritability for this trait. Plant height exhibited high values of GCV and PCV but differences between them was relatively narrow indicating less influence of environment in the expression of this trait. The high broad sense heritability (97.42%) coupled with high genetic advance as per cent of mean (48.37%) indicated predominant role of additive gene action in its genetic control. The results of heritability and genetic advance in the present study is in total agreement with the reports of Sankarapandian et al. (1996), Umakanth et al. (2004), Sandeep et al. (2009a) and Rajappa (2009). 37 Nodes per plant and stem girth registered moderate PCV and GCV values with negligible difference between them indicating less influence of environment on these traits. The results of PCV and GCV were in agreement with earlier report of Rajappa (2009). These traits exhibited high heritability coupled with moderate and high genetic advance expressed as per cent of mean, respectively indicating role of additive gene action in there genetic control. Results of the present study are in corroborative with the earlier reports of Sankarapandian et al. (1996), Krishnakumar et al. (2004), Rajappa (2009) and Sandeep et al. (2009a). Reliability can be placed on these traits for selection of segregants owing to its high heritability coupled with high genetic advance. Total biomass per plant recorded higher values of PCV and GCV with negligible difference between them indicating less influence of environment on the expression of trait of interest. The high estimates of broad sense heritability (97.04%) and genetic advance expressed as per cent of mean (93.74%) in this cross indicating preponderance of additive gene action in the genetic control of this trait. Similar results were earlier reported by Unche et al. (2008a) with respect to heritability and genetic advance indicating efficiency of simple selection in deriving desirable segregants. Fresh stalk yield registered higher values of PCV and GCV with negligible difference between them, indicating less influence of environment on the expression of this trait. Higher values for this trait were earlier reported by Sankarapandian et al. (1996) and Rajappa (2009). The broad sense heritability and genetic advance estimates were also higher indicating usefulness of this trait in selection of desirable segregants due to its genetic control by additive gene action. This is in accordance with the earlier observations made by Sankarapandian et al. (1996), Krishnakumar et al. (2004), Patel et al. (2006), Unche et al. (2008a), Sandeep et al. (2009a) and Rajappa (2009). Grain yield registered higher values of PCV and GCV with conspicuous difference between them indicating high environmental influence. Higher values for this trait were earlier reported by Sankarapandian et al. (1996) and Rajappa (2009). The broad sense heritability and genetic advance estimates were also higher indicating usefulness of this trait in selection of desirable segregants due to its genetic control by additive gene action.
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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: J.Res. ANGRAU 41(1) 30-38, 2013 GEN
Page 39 and 40: VEMANNA et al grain yield per plant
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Page 43 and 44: VEMANNA et al Singh, S. P and Khan,
Page 45 and 46: RAMANA et al RESULTS AND DISCUSSION
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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
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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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