The Journal of Research ANGRAU

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Research Notes J.Res. ANGRAU 41(1) 109-113, 2013 GENETIC DIVERGENCE STUDIES FOR YIELD AND PHYSIOLOGICAL ATTRIBUTES IN GROUNDNUT (Arachis hypogaea L.) D. NIRMALA, V. JAYALAKSHMI, B. NARENDRA and P. UMAMAHESHWARI Deptartment of Genetic & Plant Breeding, Agricultural College, ANGRAU, Mahanandi – 518 503 Date of Receipt : 07.06.2012 Date of Acceptance : 26.12.2012 Selection of genotypes from the available genetic variation is crucial for any crop improvement programme. Estimating genetic diversity available in the existing germplasm provides clue to the choice of most desirable parents for use in hybridization programmes. Selections based on physiological traits that confer water use efficiency have been suggested for improving drought tolerance in Groundnut. In the present investigation an attempt was made to identify most diverse groundnut genotypes for practical plant breeding programmes utilizing physiological traits like SPAD Chlorophyll Metre Reading (SCMR), specific leaf area, crop growth rate (CGR), relative growth rate (RGR) etc. Thirty genotypes of Groundnut were evaluated during Kharif 2011 at Agricutural College Mahanandi, A.P. The experimental material was procured from the Groundnut Breeding Station, RARS, Tirupati comprising of diverse breeding material generated in All India Coordinated Groundnut Improvement Programme. The experiment was laid out in a Randomized Block Design replicated thrice. Each genotype in a replication was grown in two rows of 4.2 m length with a spacing of 30 cm between the rows and 10 cm within a row. All the recommended package of practices were followed to raise a good crop. Observations were recorded on five randomly chosen plants in each genotype in a replication for 19 characters. The data collected was analyzed as per the standard procedures described by Mahalanobis’s (1936) and Rao (1952). Analysis of variance for both quantitative and physiological traits in all the 30 genotypes under study revealed significant differences for all the characters indicating the wealth of variability available in the germplasm. Further the data was subjected to D 2 analysis and the results were presented in Table 1 to 3. Based on D 2 analysis all the 30 genotypes were grouped into 14 clusters with a variable number of entries in each cluster revealing the presence of a considerable amount of genetic diversity in the material (Table 2). Cluster I had maximum number of 10 genotypes followed by cluster II with 6 genotypes and cluster X with 3 genotypes. Remaining all other clusters possessed one genotype each. Cluster I alone had one-third of the total genotypes studied indicating that the genotypes under study had narrow genetic diversity among them. Similarity in the base population from which they have been evolved might be the cause of genetic uniformity. However, the uni-directional selection potential for one particular character or a group of linked traits in several places may produce similar phenotypes which can be aggregated into one cluster irrespective of geographical diversity. Sudhir Kumar et al (2010), Awatade (2007) and Garajappa et al. (2005) reported that there is no correlation between genetic diversity and geographical diversity in the groundnut genotypes studied by them. Average inter cluster and intra cluster D 2 values among the 30 genotypes were furnished in Table 2. The maximum intra cluster distance was recorded for cluster X (6.31) followed by cluster II (5.13) and cluster I (4.95) revealing substantial diversity within the clusters. Maximum inter-cluster values were observed between cluster III and cluster XII (12.35) followed by cluster V and cluster XIII (12.10) indicating maximum divergence between the genotypes included in these clusters. Cluster means for all the traits were given in Table 2. Cluster means for different characters indicated that none of the clusters contained genotype with all the desirable characters and so recombinant breeding between genotypes of different clusters is needed. Cluster XII showed higher cluster means for email: veera.jayalakshmi@gmail.com 114
NIRMALA et al weight of pods per plant (17.67), kernel weight per plant (12.93) and plant height (67.00) whereas, cluster XIV showed highest mean values for number of mature pods per plant (19.20) and number of sound mature kernels per plant (31.6). Cluster X showed high mean values for harvest index (47.0), shelling out turn (82.18) and the genotypes of the clusters XIII possessed high mean value for 100 seed weight (59.33) and number of primary branches per plant (6.67). Among various traits studied, the highest contribution (Table 3) towards divergence was found for number of secondary branches per plant (29.89%) followed by CGR at 75 DAS to harvest (18.39%) CGR at 30-75 DAS (10.57%), 100 seed weight (8.51%), plant height (8.51%), SCMR (6.9%) and harvest index (5.75%). The manifestation of genetic diversity due to number of secondary branches per plant was reported by Muralidharan and Manivannan (2004), Garajappa et al. (2005), Dolma et al. (2010) and Pavan kumar (2010) for harvest index, Sonone et al. (2011) for plant height and 100 seed weight. These results corroborate with the findings of present study. The data on inter cluster distances and per se performance of genotypes were used to select genetically diverse and agronomically superior genotypes. The genotypes exceptionally good for one or more characters seemed to be more desirable. On this basis, CAUG-1, CSMG 2006-6, LGN 123, R- 2001-2, and TCGS 150 were selected. Inter crossing of divergent groups would lead to greater opportunity for crossing over and realizing hidden potential variability by disrupting the undesirable linkages. The progenies obtained from such diverse genotypes provides a greater scope for isolating transgressive segregants in advanced generations particularly in segmental allotetraploid like groundnut. Hence these genotypes could be utilized in a multiple crossing programme to recover desirable transgressive segregants. Table 1. Distribution of 30 genotypes of groundnut in different clusters (Tocher’s method) Cluster No. No. of Genotype(s) genotypes I 10 TCGS 876, ICGV 00351, Tirupati 4, TPT 25, TPT 1, ICGV 91114, Narayani, DH 218, TCGS-913 ,TPT-2 II 6 TCGS 901A, UG 6, K 1392, TCGS 901 A, GPBD 4, PBS 30086 III 1 CSMG 2006-6 IV 1 TCGS-584 V 1 TCGS-150 VI 1 CTMG 7 VII 1 TG 68 VIII 1 CSMG 2006-6 IX 1 RTNG 2 X 3 K 1463, Greeshma, Bheema XI 1 J 71 XII 1 CAUG 1 XIII 1 LGN 123 XIV 1 R-2001-2 115
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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)
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
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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 and 112: SUDHARANI et al Table 1. Genotypic
Page 113: SUDHARANI et al At genotypic level,
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
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