The integrating analytical framework of the GxE interactions in tomato: a comprehensive multi-analytical approach toward across-elevations

Abstract

Developing new tomato varieties requires testing in several locations to determine how they perform in different environments, especially at different altitudes above sea level. This testing involves a careful study of the genetic potential of genotypes and the variation in their performance. Best Linear Unbiased Prediction (BLUP) analysis, multivariate analysis, and adaptability tests should be performed on tomato types at different altitudes. Therefore, this study aimed to develop a comprehensive selection framework for broad adaptation of tomato in various environments at different altitudes and to select potential lines with wide adaptation. The study was designed as a nested group randomized design, in which replications were nested in three locations. The main factor in this study was the 45 lines, and four check varieties were repeated thrice, resulting in a total of 441 experimental units. This study assessed tomato genotypes across environments using BLUP for heritability, multivariate analyses to identify key yield traits, and adaptability tests (Finlay–Wilkinson regression and RMSE). This study showed that using BLUP, factor, and path analyses helped in choosing tomato lines that adapt well to multiple environments. Focusing on the number of fruits per plant as a secondary trait, the developed selection index formulation was as follows: selection index = 0.04 yield + 0.16 number of fruits per plant. This index suggested 29 promising tomato lines. Based on adaptability using Finlay-Wilkinson regression and RMSE, 24 had a good adaptability index (AI > 0), and seven of them were consistently adapted to three different altitude environments. Therefore, the seven genotypes are recommended for evaluation in multilocation testing.

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