Genetic and Genotype × Environment Interaction Effects for Appearance Quality of Rice

Genotype–environment interaction and yield stability were evaluated for 19 genotypes of lovegrass (Eragrostis curvula). The study was conducted in the central semi-arid region of Argentina. Three locations and two growing seasons in combination generated six environments. Genotypic responses and stability of yield under variable environments were investigated. The genotype–environment interaction was analysed by three methods: regression analysis, AMMI and principal coordinates analysis (PCO). Analysis of variance showed that effects of genotype, environment and genotype–environment interaction were highly significant (P < 0·01). The genotypes accounted for 20% of the treatment sum of squares, with environment responsible for 65% and interaction for 14·5%. The biplot indicated that there was partial agreement between the AMMI and regression model. However the scatter point diagrams obtained from PCO analysis revealed only limited agreement with the results obtained by the regression analysis and the AMMI model. The results show that the AMMI model as a whole explained twice as much of the interaction sum of squares as did regression analysis and was more adequate than PCO analysis in quantifying environment and genotype effects for forage yield. AMMI analysis of the genotype–environment interaction effects showed that there were responses characteristic of a particular location. This type of association implies some predictability of genotype–environment interaction effects on forage yield production when differential responses across genotypes are associated with locations. Environmental factors may contribute to the interpretations of genotype–environment interaction. However in the semi-arid region, where fluctuations in growing conditions are unpredictable, additional research is required to obtain an integration of interaction analysis with external environmental (or genotypic) variables.

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Analysis of yield stability of strawberry varieties and hybrids

BIO Web of Conferences ◽

10.1051/bioconf/20202502014 ◽

2020 ◽

Vol 25 ◽

pp. 02014

Author(s):

Vadim Lapshin ◽

Valentina Yakovenko ◽

Sergey Shcheglov

Keyword(s):

Cluster Analysis ◽

Hierarchical Cluster ◽

Yield Stability ◽

Environment Interaction ◽

Multivariate Statistical ◽

Genotype Environment Interaction ◽

Yield Structure ◽

Biological Yield ◽

Factor Of Influence

The profitability of strawberry cultivation is largely determined by the capacity and quality of the yield, depended on the features of the variety genotype. The aim of this work was to estimate the yield stability of varieties and hybrids by the methods of multivariate statistical analysis and identify the best genotypes. To solve this problem, we have used the two-factor analysis of variance and hierarchical cluster analysis according to the Ward’s method as well as the integral estimate of the differences between the values of yield. The results of the studies have shown that the genotype of the variety (hybrid) are makes a decisive factor of influence for variability of the yield structure signs from 17,1% (number of inflorescences) to 32,2% (number of berries). The «genotype × environment» interaction is comparable with the genotype influence, the share of influence of the year conditions of the year is insignificant. Cluster analysis according to complex of economic valuable signs allows us to identify the eight forms that the most adapted to the conditions of the Krasnodar Territory as 13-1-15, Florence, Roxana, 18-1-15, Asia, Onda, Kemia, Nelli from which the Roxana, Florence, 18-1-15, 13-1-15 have a high and steadily rising biological yield.

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