Another View of Genotype by Environment Interaction (G × E) Through Correspondence Analysis

Understanding genotype × environment (G × E) interaction is essential for the improvement of aromatic crops such as basil (Ocimum basilicum), where yield is strongly influenced by environmental variability. In this study, five basil varieties (Burns Lemon, Cinnamon, Sweet, Red Rubin, and Thai) were evaluated across two years (2015–2016, 2016–2017) and three irrigation levels (40%, 70%, and 100% of the full water requirement) to assess dry biomass yield. ANOVA and mean performance plots confirmed significant varietal differences (F = 33.972, p < 0.001) and substantial Y × V interaction (F = 23.578, p < 0.001), motivating a deeper exploration of association patterns. To this end, we proposed the use of a modified version of Simple Correspondence Analysis (CA) combined with three variations of bi-plot analyses in order to explore the (G × E) interaction. In addition, another modification of CA is proposed and used, CA of raw data (CA-raw), for the same reason. For the purpose of the study, the combinations of the two cultivation periods (years) by the three irrigation levels were considered as six environments. Results showed that the proposed modification of CA of raw data serves as a faithful baseline for the study of (G × E) interaction. On the other hand, the proposed modified version of simple CA, after proper normalization (row, column, symmetrical, principal) of the factorial scores of the five basil varieties and the six environments, provide insights depending on whether the research focus lies on varieties, environments, or their joint associations (interaction). Overall, the combined use of ANOVA, mean plots, and CA under multiple normalizations and modifications demonstrated the robustness of the primary varietal–environment contrast, while also showing how methodological choices shape interpretation. The proposed methods are “model free” and can be used also with secondary published data.