Divergent gene pools in rice improvement

Kanwal, K. S.; Singh, R. D.; Singh, Jogendra

doi:10.1007/bf00308077

Cited by 11 publications

(7 citation statements)

References 5 publications

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“…Trotter) (Assefa et al 2003); sorghum (Sorghum bicolor (L.) Moench) (Ayana and Bekele 1999); barley (Hordeum vulgare L.) (Cross 1992); wheat (Triticum spp.) (Elings 1991;Pecetti et al 1992;Damania et al 1996); maize (Zea mays L.) (Alika et al 1993); rice (Oryza sativa L.) (Kanwal et al 1983). The multivariate analysis can be used to obtain idea about how to identify groups of accessions that have desirable traits for breeding, forming core collections, and enlightening the patterns of variation in germplasm collections (Camussi et al 1985;Cowen and Frey 1987;Peeters and Martinelli 1989).…”

Section: Introductionmentioning

confidence: 96%

Multivariate Analysis of Diversity of Tetraploid Wheat Germplasm from Ethiopia

Hailu

Merker

Harjit-Singh

et al. 2006

Genet Resour Crop Evol

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The variability of 2420 plants of tetraploid (2n = 4x = 28, AABB genome) wheat germplasm representing 121 accessions from Ethiopia were evaluated for 23 agro-morphological traits at Debre Zeit Agricultural Research Center area, Akaki substation, during the 2003 main season using multivariate methods. This enabled to assess the extent and pattern of variation of the germplasm with respect to regions, altitude classes and species and to identify the major traits contributing to the diversity. The first three and two principal components explained about 83 and 80% of the total variance among regions and altitudinal class, respectively. In the first principal component plant height, days to heading, the length and density of the spike, and kernel color were the most important traits contributing to variation that explained about 50% of regional variance. Cluster analysis grouped the accessions into 15 clusters, with 9 accessions remaining ungrouped. Based on the observed patterns of variation, it is concluded that there exists great variation in the germplasm, which provides opportunities to be utilized for genetic improvement.

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Section: Introductionmentioning

confidence: 96%

Multivariate Analysis of Diversity of Tetraploid Wheat Germplasm from Ethiopia

Hailu

Merker

Harjit-Singh

et al. 2006

Genet Resour Crop Evol

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“…Multivariate analysis of quantitative characters has been used previously to measure genetic relationships within crop species. Examples include barley (Hordeum vulgate L.); (Bekele, 1984), Ethiopian wheats (Triticum aestivum L.); (Negassa, 1986),durum wheats (Triticum turgidum L.); (Jain et al,1975), and rice (Oryza sativa L.); (Kanwal et al, 1983).…”

Section: Introductionmentioning

confidence: 99%

Agronomic evaluation of cowpea cultivars developed for the West African Savannas

Kamara

Ewansiha

Ajeigbe

et al. 2017

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The goal of this research was to evaluate diverse cowpea genotypes developed over the past 4 decades in the Nigerian Sudan Savannas for their agronomic performance and to identify groups of cultivars with similar quantitative characters. Characterization would facilitate the efficient synthesis of breeding populations for further improvement of cowpea. Also superior genotypes with desirable characteristics could be identified and disseminated in the dry savannas of West Africa. Significant variations were observed in the agronomic characteristics of the cultivars in this study. Principal component analysis (PCA) and cluster analysis were performed on these genotypes and found that there were significant correlations among the variables measured. Modern cultivars outperformed the older ones and from the results of PCA, it was found that the most important variables for the classification of cowpea cultivars are high canopy, high seed weight, high total dry matter, high HI, and high grain and fodder yield. This suggests that these traits could be used in selection index for genetic improvement of cowpea. Cluster analysis resulted in 5 groups mostly corresponding to era of release except cluster I which contained cowpea cultivars from all eras. Two distinct groups in clusters IV and V were identified. Cultivars in cluster IV which were released in the 1990-2000 eras, had high grain and fodder yield. These cultivars could be evaluated on-farm for eventual release to farmers. They could also be used in breeding program for improvements in grain and fodder yield of cowpea. Cluster V contained two cultivars that distinctly had the highest fodder yield suggesting that they could be used to improve fodder yield of cowpea.

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“…The most important cluster was cluster III (Table 6). The important characters reported by some researchers were plant height, panicle length, number of unfilled grains per panicle, 1000-grain weight (Latif et al, 2011 andSabesan et al, 2009), grain yield, number of effective tillers (Baradhan and Thangavel, 2011), harvest index (Ahmed et al, 2010), days to maturity (Kanwal et al, 1983) and number of secondary branches per panicle (Sinha et al, 1991). The most important characters contributing towards the divergence were number of unfilled grains per panicle, 1000-grain weight and grain yield per hill.…”

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confidence: 99%

GENETIC DIVERSITY ANALYSIS IN RICE (Oryza sativa L.)

Chakma

Huq

Mahmud

et al. 2012

Bangla J Plant Breeding & Genetics

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The experiment was conducted under the agro-ecological zone of Modhupur Tract (AEZ-28) to determine the genetic diversity among 39 rice genotypes, collected from Bangladesh Rice Research Institute, Lal Teer Seed Ltd. and Chittagong Hill Tracts. The genotypes were grouped into six clusters based on Mahalanobis's D 2 statistics and Canonical Variate Analysis. Cluster I consisted with the highest number of (11) genotypes from different origin, whereas cluster IV consisted with the lowest number of (3) genotypes. Cluster III consisted of BRRI dhan 28, BRRI dhan 45, Gold, Tia, Dowel and Moyna showed maximum mean yield. Maximum inter cluster distance was recorded between cluster II and cluster III. The highest inter genotypic distance was observed between Tharak dhan and BRRI dhan 45. Cluster III had the highest mean values for grain yield, harvest index, 1000-grain weight and number of effective tillers per hill and cluster V for number of primary branches per panicle and cluster VI for number of filled grains per panicle that had significant positive correlation with grain yield. Number of unfilled grains per panicle, 1000-grain weight and grain yield showed maximum contribution towards genetic divergence. The genotypes from these clusters with desirable characters may be used as potential donor for future hybridization program to develop high yielders.

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Divergent gene pools in rice improvement

Cited by 11 publications

References 5 publications

Multivariate Analysis of Diversity of Tetraploid Wheat Germplasm from Ethiopia

Multivariate Analysis of Diversity of Tetraploid Wheat Germplasm from Ethiopia

Agronomic evaluation of cowpea cultivars developed for the West African Savannas

GENETIC DIVERSITY ANALYSIS IN RICE (Oryza sativa L.)

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