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Higher Order AMMI (HO-AMMI) analysis: A novel stability model to study genotype-location interactions
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Abstract
Additive main effects and multiplicative interaction (AMMI) model is most widely used to analyse genotype*environment interactions (GEI) wherein interaction effects of location is masked by year effect. Hence, presently available models are not able to estimate interaction effects of genotype*location (GLI) and genotype*year (GYI) separately. Moreover, genotype ranking differs as number of years of evaluation vary making selection of genotype for target location difficult. In the present study we propose a novel stability model i.e Higher-order-AMMI (HO-AMMI) analysis which is capable of calculating GLI without the confounding effect of GYI and GLYI. GEI of AMMI model and all 2-way interactions of HO-AMMI model follow χ
2
distribution, whereas 3-way interaction (GLYI) of HO-AMMI follow noncentral χ
2
distribution. With increase in number of years of evaluation contribution of GLI towards total variation increased whereas in AMMI model contribution of GEI towards total variation decreased. Variation explained by multiplicative components is higher in HO-AMMI compared to AMMI model. Genotypes were ranked using GL, GY and GL+GY+GLY interactions of HO-AMMI and GEI of AMMI for stability and yield and compared their ranks with field ranking. Correlation and linear regression analysis have indicated high association of GLI (HO-AMMI) with field ranking with high R
2
values. Further, HO-AMMI model was able to remove the confounding effect of GYI and GLYI on GLI for accurate identification of genotype for target location irrespective of number of years of evaluation. Hence, HO-AMMI model can be used under multi-environment trials (MET) for selecting genotypes efficiently.
Availability and Information
Source code implemented in R is available from corresponding author.
Title: Higher Order AMMI (HO-AMMI) analysis: A novel stability model to study genotype-location interactions
Description:
Abstract
Additive main effects and multiplicative interaction (AMMI) model is most widely used to analyse genotype*environment interactions (GEI) wherein interaction effects of location is masked by year effect.
Hence, presently available models are not able to estimate interaction effects of genotype*location (GLI) and genotype*year (GYI) separately.
Moreover, genotype ranking differs as number of years of evaluation vary making selection of genotype for target location difficult.
In the present study we propose a novel stability model i.
e Higher-order-AMMI (HO-AMMI) analysis which is capable of calculating GLI without the confounding effect of GYI and GLYI.
GEI of AMMI model and all 2-way interactions of HO-AMMI model follow χ
2
distribution, whereas 3-way interaction (GLYI) of HO-AMMI follow noncentral χ
2
distribution.
With increase in number of years of evaluation contribution of GLI towards total variation increased whereas in AMMI model contribution of GEI towards total variation decreased.
Variation explained by multiplicative components is higher in HO-AMMI compared to AMMI model.
Genotypes were ranked using GL, GY and GL+GY+GLY interactions of HO-AMMI and GEI of AMMI for stability and yield and compared their ranks with field ranking.
Correlation and linear regression analysis have indicated high association of GLI (HO-AMMI) with field ranking with high R
2
values.
Further, HO-AMMI model was able to remove the confounding effect of GYI and GLYI on GLI for accurate identification of genotype for target location irrespective of number of years of evaluation.
Hence, HO-AMMI model can be used under multi-environment trials (MET) for selecting genotypes efficiently.
Availability and Information
Source code implemented in R is available from corresponding author.
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