Breeding effects on the cultivar×environment interaction of durum wheat yield
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Understanding the effect of past durum wheat breeding activities on the cultivar × environment (C × E) interaction of yield and yield components may guide future breeding strategies. A historical series of 24 cultivars released in Italy and Spain during the 20th century was grown in 13 environments with average yields ranging between 1425 and 6670 kg ha−1. The most important environmental factors affecting the C × E interaction for yield were reference evapotranspiration before anthesis and water input during grain filling. The response of cultivars to environmental variables in terms of yield and yield components was associated to the allelic composition for the Rht-B1 locus. Improved semi-dwarf cultivars (carrying the Rht-B1b allele) had the best yield performance in environments with high water input after anthesis, while tall cultivars (carrying allele Rht-B1a) were better adapted to environments with high evapotranspirative demand before anthesis and low water input after it. The introduction of the Rht-B1b allele improved the capacity of the crop to respond to water availability during grain filling by increasing the number of grains spike−1 and grain weight. Yield increases due to breeding caused a loss of stability from the static viewpoint, but not from a dynamic approach based on the superiority measure (Pi). Some semi-dwarf cultivars maintained the levels of yield stability characteristic of the old tall ones. Our results suggest that durum breeding in the 20th century enhanced the response of the crop to environmental improvements.Keywords:
Anthesis
The objective of this study was to explore the effect of genotype (G) and genotype × environment interaction (GEI)
on grain yield of 20 chickpea genotypes under two different rainfed and irrigated environments for 4 consecutive
growing seasons (2008-2011). Yield data were analyzed using the GGE biplot method. According to the results of
combined analysis of variance, genotype × environment interaction was highly significant at 1% probability level,
where G and GEI captured 68% of total variability. The first two principal components (PC1 and PC2) explained
68% of the total GGE variation, with PC1 and PC2 explaining 40.5 and 27.5 respectively. The first megaenvironment
contains environments E1, E3, E4 and E6, with genotype G17 (X96TH41K4) being the winner; the
second mega environment contains environments E5, E7 and E8, with genotype G12 (X96TH46) being the winner.
The environment of E2 makes up another mega-environment, with G19 (FLIP-82-115) the winner. Mean
performance and stability of genotypes indicated that genotypes G4, G16 and G20 were highly stable with high
grain yield.
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The objective of this research was to evaluate and to quantify the magnitude of the genotype × environment interaction effects on mung bean grain yield and to determine the winning genotype for the test environments. Seven mung bean genotypes were tested at three locations for over two years. The grain yield data for each environment (location year combination) was first subjected to analysis of variance using generalized linear model. Mean grain yields of genotypes for the environments were computed to generate a genotype and environment two-way table data for the GGE biplot analysis. The analysis revealed the presence of significant genotype x environment interactions for grain yield. Location effect explained more than 60% of the total grain yield variation. GGE biplot analysis depicted the adaptation pattern of genotypes at different environments and discrimination ability of testing environments. MH-96-4, shown to have the potential of combining high yield with stable performance, can be recommended for production in mung bean growing ecologies in southern Ethiopia.
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Genotype × Environment Interaction and Stability Analysis for Grain Yield of Mid-hill Rice Genotypes
Genotype x Environment interaction limits the effectiveness of selection when selection is based only on mean yield. This G × E interaction was studied for grain yield in 7 genotypes of mid-hill rice in five different environments across the Nepal. Significant difference was observed among genotype (G), environment (E) and interaction (G × E) but could not identify the stable high yielding genotypes for diverse environments. Therefore, stability parameters were calculated and analyzed. On the basis of stability parameters, two genotypes, NR 10414, NR 10492 and NR 10515 were found to be most stable over different environments. NR 10353 was identified as suitable genotypes with high grain yield for favorable environment.Nepal Agric. Res. J. Vol. 8, 2007, pp. 14-17DOI: http://dx.doi.org/10.3126/narj.v8i0.11565
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Cultivars grown at the farmers’ Selds were selected and tested for three consecutive years at eight locations in Bulgaria, which were representative for the entire territory of the country and had contrasting soil and climatic conditions for crop growing. SigniScant variations of grain yield were found among the investigated cultivars regardless of their speciSc response to the year conditions and the location. The interaction genotype x environments was signiScant and high, and was of non-linear type. The changeable environmental conditions caused different reactions of the cultivars, which allowed dividing them into groups according to the plasticity and stability they demonstrated. The variation in this experiment determined through Principal Component Analysis (PCA reached level four, which is comparatively rare for this trait. On the whole, PC1 had low value (49%), while PC2 was high (16%). There were several cultivars with very high PC2 values, exceeding several times the values of their respective PC1. The percent of variation caused by the environment was signiScant for grain yield under the conditions of Bulgaria. The investigated cultivars differed not only by grain yield but also by their plasticity and stability under changeable environments, the percent of the genotype effect being about 12 % for the entire experiment. It was found that each cultivar can give high grain yield at high ecological stability regardless of its genetic potential for quality. Best balance between grain yield and stability was found in cultivars Aglika, Demetra, Iveta (Srst quality group), Galateya, Slaveya (second quality group) and Todora, Kristal and Pryaspa (third quality group)
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To evaluate the differences in NPK accumulation and translocation in dryland winter wheat cultivars with different yields,nine winter wheat cultivars were planted on field with no fertilizer application for six years.The results showed significant differ-ences in NPK accumulation,translocation and K loss for different cultivars.Before anthesis,increased fertilizer rate led to more rapid increase in N accumulation in high-yield cultivars than in medium-and low-yield cultivars.At pre-anthesis,however,there were no significant differences in P accumulation among different-yield wheat cultivars.High-yield cultivars were characterized as high post-anthesis N and P accumulation and low K loss levels.This was due to high ability to save translocated K in wheat grains.Also in high-yield cultivars,N and P translocation and remobilization efficiencies,and the contribution of remobilized N and P to grain yield were lower than those in low-yield cultivars.However,there was no obvious difference in K accumulation and translocation at pre-anthesis.Consequently,higher post-anthesis N and P accumulation and lower K loss were important driving factors of higher grain yields in dryland wheat cultivars.
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Winter wheat
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There is limitation of information on G x EI of bread wheat genotypes in Ethiopia. The study cried out with objectives to estimate Genotype x Environment interaction and stability of bread wheat genotypes in Ethiopia. Thirty Bread wheat genotypes were evaluated by Alpha lattice design using three replications at eight locations in Ethiopia. The mean grain yield of genotypes across environments was 4.53 ton ha -1 . Bread wheat grain yield was significantly affected by the E, G and G x E interaction. Environment, G x E interaction and genotype explained 45.59%, 25.37% and 2.59% of the total (G + E + GEI) variation respectively. Genotype ETBW71942 (3), ETBW7038 (9), ETBW8511 (1) and ETBW8512 (14) were considered specifically adapted. Considering simultaneously yield and stability, Genotype ETBW7871 (15), ETBW7058 (11), ETBW8513 (16) and ETBW7101 (25) showed the best performances. Keywords : genotype; environment; genotype x environment interaction; Stability.
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Genotype × environment interactions, cultivar response to environments and cultivar stability for yield of oilseed rape (Brassica napus L.) were studied using five cultivars grown for 3 yr at nine locations in Manitoba. The objectives were: (1) to estimate the components of variance associated with the first- and second-order interactions and to determine their effects on the standard error of a cultivar mean so that optimum test combinations of replications, locations and years for cultivar testing in Manitoba could be determined; (2) to measure cultivar response to varying environments; and (3) to measure cultivar stability. The genotype × year and the genotype × year × location interactions were significant. The genotype × location interaction was not significant, indicating the cultivars tested performed similarly relative to each other across locations over years. Increasing years, locations and replications in that order had the greatest effects on the standard error of a cultivar mean. Calculation of the contribution of each variety to the G × E sums of squares indicated that Westar made the largest contribution and Altex the smallest.Key words: Rape (oilseed), Brassica napus L., stability, cultivar testing
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Evaluation of Genotype × Environment Interaction and Grain Yield Stability of Advanced Bread Wheat Cross-bred lines by GGE Biplot Method
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Large genotype x environment (g x e) interaction variances for yield relative to those for genotypes have been recognized for wheat cultivars in Queensland. The utility of a linear model to explain these interactions was examined by yield-testing 100 different wheat cultivars at nine different environments, including four locations and three years, in south-eastern Queensland. The linear model was found to explain less than 40% of the total g x e interaction and to give only a general indication of cultivar responses to different environments. Selection strategies to identify widely adapted cultivar involving several parameters (mean cultivar yield over all environments, the g x e interaction for each cultivar and the regression coefficient for each cultivar), singly and in combination, were evaluated. Greater selection differentials were found in most environments when selection was practiced for high mean yield across all environments when the yield of each cultivar in each environment was expressed as a percentage of the environment mean yield.
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