Analysis of genotype × environment interaction for seed yield in spring oilseed rape using the AMMI model

Abstract

In order to assess the genotype by environment interaction (GE) and select genotypes to exploit narrow and broad adaptations, twenty-two spring oilseed rape genotypes were subjected to field surveys at five experimental sites in the 2015-16 and 2016-17 growing seasons. Plant materials were sown in the form of a randomized complete block design with three replicates. The additive main effects and multiplicative interaction (AMMI) model was used to determine the genotype, environment, and GE effects. The sum of squares (SS) for the first three interaction principal components was very close to the SS for the GE signal; therefore, AMMI3 was diagnosed as the most accurate model to optimize predictive accuracy. Hyola 401 had the highest broad adaptability. In total, the chances of increasing yield were 55.

Stability, Adaptability Analysis of Wheat Genotypes by AMMI with BLUP for Restricted Irrigated Multi Location Trials in Peninsular Zone of India

“…An efficient assessment of GxE interaction had been emphasized to determine the yield potential and stability of the genotypes under multi location trials [1].…”

Identification of promising oilseed rape genotypes for the tropical regions of Iran using multivariate analysis

“…Several studies have been down to identify adopted cultivars of oilseed rape. Aghaei(Agahi et al , 2020) examined 22 genotypes of oilseed rape at five experimental sites and reported that Hyola 401 had the highest yield and adaptability. Likewise, eleven new oilseed rapes were evaluated in the seven different environments and the RBN-04722 genotype was identified as the most adaptable genotype(Tahira & Amjad, 2013).…”

“…The problem is that yield is a complex characteristic that is regulated by many genes and highly affected by environmental factors. The different experimental environments should be considered to identify genotypes with the highest yield and the lowest fluctuations in the different environments(Agahi et al , 2020). Evaluation of yield in the different environments could help us select high yield and stable genotypes with high accuracy (Roy, 2000).…”

Wheat genotypes as assessed by Additive main & multiplicative interactions (AMMI) and Best linear unbiased prediction (BLUP) for stability analysis under rainfed timely sown trials in Northern Hills Zone of India

“…Large number of stability analysis measures have been developed to model GxE interactions efficiently (Mohammadi et al, 2015;Bocianowski et al, 2019;Agahi et al, 2020). AMMI based stability measures evaluate the stability of genotypes after reduction of the noise from the GxE interaction effects (Gauch 2013;Oyekunle et al, 2017;Ajay et al, 2020).…”