Parametric and Non Parametric measures to compare Fixed and random effects of malt barley genotypes

AMMI analysis of 21 malt barley genotypes evaluated at nine locations of north western plains zone revealed highly significant variation due to environments (61.8%), G x E interactions (19.5%) and genotypes (8.2%). Further, interaction effects were partitioned into seven interactions principal components. AMMI stability Value measures (ASV1 and ASV) had considered first two interaction principal components and based on 54.1% of total interaction variations had recommended (PL926, PL931, RD2849) and (BH1036, PL931, RD2849) malt barley genotypes respectively. Modified AMMI Stability Values measures (MASV1 and MASV) had exploited nearly 97.6% of total interaction variations, based on which BH1036, DWRB219, RD2849 and BH1036, DWRB219, PL926 malt barley genotypes were identified for stable yield performance. Geometric Mean (GM) based on BLUP effects of genotypes yield was in favour of DWRB219, BH1036 and DWRB221 while corresponding to Harmonic Mean of yield values, DWRB219, BH1036, DWRB221 genotypes would be of choice. Relative Performance of Genotypic Values (RPGV) favored DWRB219, BH1036 , DWRB221 barley genotypes and Harmonic Mean of Relative Performance of Genotypic Value (HMRPGV) measure favoured DWRB219, BH1036, DWRB220 malt genotypes. Non parametric composite measure, NPi (1) , suggested that UPB1097, RD3029, DWRB218 were suitable, whereas DWRB219, RD3029, G4 genotypes would be preferable as per values NPi (2) while NPi (3) identified DWRB219, BH1036, DWRB160. The composite measure NPi (4) found DWRB219, BH1036, DWRB160 as genotypes of choice for this zone. Measures MASV, MASV1, Si 1, Si 3, Si 4, Si 5,Si 6 ,Si 7, Si 2, NPi (1), ASV and ASV1 accounted more in first principal component, whereas NPi (2), NPi (3), NPi (4), Average, GM, HM, Mean, PRVG, HMPRVG were major contributors for second principal component. Small cluster of standard deviation (Stdev) with CV, IPC4 and IPC7 were placed in second quadrant. Smallest cluster of IPC1 and IPC6 was also observed in this quadrant. Large cluster comprised of NPi (1), Si 2 ,Si 5 Si 2 ,Si 5 ,Si 6 with ASV and ASV1. Measures GM, HM, PRVG and HMPRVG considered random effects of genotypes grouped with average and placed in last quadrant while adjacent cluster of NPi (2), NPi (3), and NPi (4) observed in same quadrant. Close association among the AMMI analysis based measures had been observed with adaptability measures based on BLUP effects of malt barley genotypes in the present study based on the Biplot analysis while considering first two principal components

Chickpea

The narrow genetic base of cultivated chickpea warrants systematic collection, documentation and evaluation of chickpea germplasm and particularly wild Cicer species for effective and efficient use in chickpea breeding programmes. Limiting factors to crop production, possible solutions and ways to overcome them, importance of wild relatives and barriers to alien gene introgression and strategies to overcome them and traits for base broadening have been discussed. It has been clearly demonstrated that resistance to major biotic and abiotic stresses can be successfully introgressed from the primary gene pool comprising progenitor species. However, many desirable traits including high degree of resistance to multiple stresses that are present in the species belonging to secondary and tertiary gene pools can also be introgressed by using special techniques to overcome pre- and post-fertilization barriers. Besides resistance to various biotic and abiotic stresses, the yield QTLs have also been introgressed from wild Cicer species to cultivated varieties. Status and importance of molecular markers, genome mapping and genomic tools for chickpea improvement are elaborated. Because of major genes for various biotic and abiotic stresses, the transfer of agronomically important traits into elite cultivars has been made easy and practical through marker-assisted selection and marker-assisted backcross. The usefulness of molecular markers such as SSR and SNP for the construction of high-density genetic maps of chickpea and for the identification of genes/QTLs for stress resistance, quality and yield contributing traits has also been discussed

Spatio-temporal genetic diversity in Indian barley (Hordeum vulgare L.) varieties based on SSR markers

545-552Barley is a popular cereal crop of nutritious and industrial importance and there is always a scope to improve a particular crop in view of its value and demand. Spatio-temporal studies discuss the diversity level among the existing varieties as well as the trend of genetic variation over a period of time and are useful in designing suitable strategies for genetic enhancement and improvement of a particular crop. Here, we used SSR markers to assess the level of spatio-temporal genetic diversity among fifty diverse released varieties of barley from India. Spatial diversity (0.233±0.16) was higher in varieties having exotic parentage as compared to the indigenous varieties (0.176±0.18) and significant diversity was also observed among the varieties released from different developing centers. There was a rising trend in % polymorphism and other diversity parameters among the barley varieties released before 1960s to 1970s, which may be attributed to the increasing usage of exotic germplasm during these decades. Increase in temporal diversity from 1970s to 1980s and to 1990s was not much as compared to earlier decades, which suggests that more diverse germplasm should be used to widen the genetic base of barley varieties released over the years. Further, structure and AMOVA results revealed strong differentiation among spatial groups, but not between temporal groups. The role of spatio-temporal genetic diversity studies and the importance of periodic monitoring of the varieties released for further crop improvement was emphasized

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Not AvailableAn experiment was conducted during 2003–05 to study genetic variability, genotypic and phenotypic correlation coefficients for 13 malting quality traits in a set of 131 barley (Hordeum vulgare L) genotypes grown at 2 locations. Significant genetic variability was observed for all the 13 characters studied. Significant location effects for most of the quality traits were observed. There were significant genotypic and phenotypic correlation co-efficients between 60 pairs of characters, 35 with positive and 25 with negative associations. Hot water extract, the most important malt quality trait showed significant correlation data with grain (hectolitre weight, 1 000 g weight, bold grain) and malt (friability and homogeneity) quality traitsNot Availabl

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