Statistical methods for the analysis of genotype-environment interactions

Freeman, G. H.

doi:10.1038/hdy.1973.90

Cited by 314 publications

(181 citation statements)

References 83 publications

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“…Duncan multiple range test (DMRT) was used to calculate to compare mean differences for significant cultivar and environment effect by using MSTAT-C software (Russel 1994). Combined analysis of variance was done for six environments according to a statistical model explained by Freeman and Dowker (1973).…”

Section: Discussionmentioning

confidence: 99%

Stability analysis of yield and capsaicinoids content in chili (Capsicum spp.) grown across six environments

2012

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There is a need for identifying chili cultivars with stable amounts of capsaicinoids so that the amount of pungency in the final product can be controlled. Therefore, six cultivars were evaluated for yield and capsaicinoid contents across six environments, four in Thailand and two in Bhutan, ranging from 200 to 1,630 m above mean sea level. Combined analyses showed significant differences among cultivars, environments, and for cultivar by environment interactions for fruit yields, individual capsaicinoid and total capsaicinoid contents. A large proportion (46.1 %) of variation on yield was attributed to environments; however, for total capsaicinoid contents, genotype effect accounted for 74.2 % of variation. Variation due to environment was 5.8 %, while for cultivar by environment interaction was 15.8 %. Cultivar Dallay khorsaney had high capsaicin, dihydrocapsaicin and total capsaicinoids but was very sensitive to environmental changes, and therefore good for specific adaptation. Cultivar KKU-P-11003 with total capsaicinoid contents of 78,721 Scoville heat unit was stable for dry fruit yield, capsaicin, dihydrocapsaicin, and total capsaicinoids with regression coefficients b = 1.06, 1.06, 0.78, and 0.96 respectively. Therefore, KKU-P-11003 was considered suitable for diverse environments. In addition, this result indicates that it is possible to select stable cultivar for capsaicinoid contents.

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Section: Discussionmentioning

confidence: 99%

Stability analysis of yield and capsaicinoids content in chili (Capsicum spp.) grown across six environments

2012

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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: 94%

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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“…Various methods have been proposed for the statistical analysis of these interactions (Freeman, 1973). An experimental design for *Correspondence 237 self-pollinating plants -consisting of individuals, each belonging to a specific F7 family which segregates for a SG -and the corresponding statistical procedures were developed by Elkind & Cahaner (1986) to estimate the components of a mixed model which includes the effects of SG, PG and their interaction.…”

Section: Introductionmentioning

confidence: 99%

Mixed model for estimating the effects of the Rht1 dwarfing allele, background genes, CCC and their interaction on culm and leaf elongation of Triticum aestivum L., spring wheat

1994

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A model for the effects of a single gene (SG), background genes (BG), an environmental factor (EF) and the effects of their interactions on quantitative traits is developed. It is a mixed model where SG and EF have fixed effects while BG have a random effect. This model is applied to the analysis of the effects of the dwarfing alleles at the RhtJ locus (SG), interfamily variation (representing BG) and the growth regulant CCC (EF) on coleoptile, leaf and culm length of spring wheat. Culm length of F7 families was tested in a field experiment in the absence of lodging. Coleoptile and leaf lengths of F9 seedlings were examined in a growth room at 18°C. Each family was descended from a single F5 plant, heterozygous at the RhtI locus. Within each family the homozygous tall (rhtl) and the homozygous semi-dwarf (Rhtl) genotypes were identified. Thus, comparing nearly isogenic genotypes within random families in advanced generations enabled the estimation of all the main effects and interactions between SG, BG and EF. The restricted maximum likelihood (REML) method was used in the analysis of variance.In all the three organs CCC caused significant shortening which was somewhat greater in the rhtl than in the Rhtl genotype and the CCC X RhtI interaction effect on culm length was significant. Considerable and significant interfamily variation was found for all three characters. A significant CCC x family interaction effect on the length of the first leaf was obtained. This interaction effect was of a specific trend indicating a distinct increase in the response to CCC with greater leaf length.No CCC X Rht] X family or Rhtl X family interaction effects were detected. The use of two graphical/analytical methods proved to be complementary for a complete evaluation of two-way interactions (CCC x families and CCC x Rhtl in the present study).Keywords: environmental factor, interaction, polygene, quantitative trait, single gene. IntroductionMany quantitative traits (QT) are known to be controlled by one or more single genes of major effect (SG) as well as by variation in background (BG) which is akin to the polygene (PG) system discussed by Falconer (1981)andbyMather&Jinks(1971.The existence of interactions between genotypes and environmental factors has long been recognized (Fisher & Mackenzie, 1923). Various methods have been proposed for the statistical analysis of these interactions (Freeman, 1973). An experimental design for *Correspondence 237 self-pollinating plants -consisting of individuals, each belonging to a specific F7 family which segregates for a SG -and the corresponding statistical procedures were developed by Elkind & Cahaner (1986) to estimate the components of a mixed model which includes the effects of SG, PG and their interaction.A modification of this design for advanced generations has been applied by Beharav eta!. (1988Beharav eta!. ( , 1992. This report presents the application of a mixed model which enables the estimation and the analysis of the main effects and interaction effects of an environ...

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Statistical methods for the analysis of genotype-environment interactions

Cited by 314 publications

References 83 publications

Stability analysis of yield and capsaicinoids content in chili (Capsicum spp.) grown across six environments

Stability analysis of yield and capsaicinoids content in chili (Capsicum spp.) grown across six environments

Non-linear genotype × environment interactions arising from response thresholds

Mixed model for estimating the effects of the Rht1 dwarfing allele, background genes, CCC and their interaction on culm and leaf elongation of Triticum aestivum L., spring wheat

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