Genotype-environment interaction – a challenge for plant breeding

Hill, J.

doi:10.1017/s0021859600062365

Cited by 139 publications

(94 citation statements)

References 65 publications

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“…Hill (1975 (Crossa et al, 1990 On the basis of our results, we concluded that the line x environment interaction for biomass dry matter yield in maize could essentially be due to differences in line earliness and lodging susceptibility (and to the different ability of the environments to reveal them), and to differences in environment rainfalls (and to the variable susceptibility of the lines to water stress).…”

Section: Factorial Regressionmentioning

confidence: 71%

Statistical analysis and interpretation of line x environment interaction for biomass yield in maize

Argillier

Hébert²,

Barrière³

1994

Agronomie

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Section: Factorial Regressionmentioning

confidence: 71%

Statistical analysis and interpretation of line x environment interaction for biomass yield in maize

Argillier

Hébert²,

Barrière³

1994

Agronomie

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“…While there is no comparable analysis of any other cross, the literature now contains many reports, too numerous to cite individually, of linear relationships between genotype x environment interactions and some 57 environmental index (see, for example, reviews by Freeman, 1973;Hill, 1975). There are many others, however, as was shown by Perkins and Jinks (I 968a, b, and 1973) with J'*Iicotiana rustica material, where the relationship is non-linear.…”

Section: Introductionmentioning

confidence: 99%

Non-linear genotype × environment interactions arising from response thresholds

Jinks

Pooni

1979

Heredity

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SUMMARYExamples of genotype x environment interactions in Xicotiene rustica that appear to be simply linearly related to the additive environmental value (ej) and others in which this does not appear to be tbe case have been analysed hy testing the goodness-of-fit of linear, quadratic and two intersecting-straightline models of this relationship. In varieties 1 and 5 and their F5 cross there is no significant improvement in goodness-of-fit over the linear model from either the quadratic or the two straight-line models. En a stratified sample of 10 inbred lines derived from this cross a pair of intersecting-straight-lines was the best model for the only two inbreds to show significant non-linearity. In varieties 2 and 12, their F1 cross and the four inbred selections derived from it, the best fit is always obtained with the two intersecting-straight-lines. The reasons, however, differ for the different genotypes. In variety 2 it is because the linear rate of response is relatively higher in the better than in the poorer environments, in variety 12 it is because of a change in the reverse direction, while in the F1 it is because the rate of response more than doubles in the very best environments. Among the four inbreds it is because one of them, Dl0, reaches a limit to its response in the environments with above average ej values while of the remaining three inbreds two increase their linear responses in these environments while the third shows a small decrease.While, therefore, two intersecting-straight-lines appear to be a widely applicable model of the relationship between the interaction of genotype and environment and the additive environmental value, in only one case, D10, which is a low mean performance and low environmental sensitivity selection, is the use of this model necessitated by a genotypic limit to further response to environmental improvement.

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“…However, in the current example, the heterogeneity mean square was large enough to be significant when tested against the deviation mean square (Table 8). Thus, according to Perkins and Jinks (1968) and Hill (1975), the coefficients of the linear model have practical value, although the predictive value of regression is not the same for each genotype.…”

Section: Joint Regression Analysesmentioning

confidence: 99%

“…However, variance component analyses alone often do not provide a satisfactory explanation for GE interactions. Simply recognizing different genotypic responses to environmental stress does not distinguish between crossover and noncrossover interactions, and it is desirable to interpret, rather than correct, the GE component (Hill 1975;Baker 1988a;Baker 1988b). Consequently, a number of parametric methods have been developed to assist in the interpretation of GE interactions (Freeman 1973;Hill 1975;Westcott 1986) and to determine the level of adaptation of genotypes (Finlay and Wilkinson 1963).…”

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confidence: 99%

Genotype–environment interaction of no-till winter wheat in Western Canada

Domitruk¹,

Duggan²,

Fowler³

2001

Can. J. Plant Sci.

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. 2001. Genotype-environment interaction of no-till winter wheat in Western Canada. Can. J. Plant Sci. 81: 7-16. Differences among cultivars in their response to changes in crop water availability are reflected in genotype-environment (GE) interactions for grain yield. With the recent expansion of the winter wheat production area in western Canada, it is important that plant breeders and agronomists have an understanding of the significance of GE interactions as they relate to regional adaptation of genotypes. Consequently, the objective of this study was to determine the phenotypic stability of recent high-yielding winter wheat genotypes grown under drought and low stress conditions on the Canadian prairies and to assess the effect that crop water status has on GE interactions. Eighteen field trials were conducted throughout Saskatchewan over a 3-yr period. Five hard red winter wheat genotypes were selected for evaluation in these trials on the basis of unique characteristics identified in earlier studies. Natural variation in weather among locations and years and irrigation produced a wide range in the timing and intensity of drought stress. The high yield potential of recent winter wheat selections was confirmed. A nonsignificant genotype-location effect meant that geographic subregions requiring specific adaptive traits could not be identified. In contrast, significant effects of years and genotype-year and location-year interactions indicated that annual differences in weather had a greater influence on relative genotype performance than weather differences among locations. Significant within-site genotypic variation for grain yield was observed only at high rainfall and irrigated sites, and the GE interaction was larger than the genotypic variance component when there were wide differences in environmental conditions. The GE interaction effect was not significant when only dryland sites were considered. A poor association between yield rank at the highly productive and droughtstressed sites was attributed to genotypic differences in yield potential and the effect of drought on the expression of yield potential. Joint regression, pairwise correlated response, stability, and convergence analyses were conducted in an effort to better interpret the practical importance of the GE interactions. A tendency for the genotype regression lines to converge below the range of grain yields expected in the region indicated that genotypes with the highest mean yield were widely adapted and that winter wheat breeders should select for high yield potential in low stress environments. However, the expression of grain yield potential was reduced enough to suggest that winter wheat yields in western Canada are likely to benefit from this "high" yield potential only under moderate and low stress conditions. Therefore, because there is a wide diversity of crop water conditions in this region, trial locations should also include targeted high stress environments to identify genotypes with high performance over a wide range of env...

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Genotype-environment interaction – a challenge for plant breeding

Cited by 139 publications

References 65 publications

Statistical analysis and interpretation of line x environment interaction for biomass yield in maize

Statistical analysis and interpretation of line x environment interaction for biomass yield in maize

Non-linear genotype × environment interactions arising from response thresholds

Genotype–environment interaction of no-till winter wheat in Western Canada

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