Quinoa (Chenopodium quinoa Willd.), a native South American crop with high nutritional value, is a promising option for sustainable agriculture in arid and semi-arid regions of Iran, due to its environmental tolerance and valuable composition. This study aimed to evaluate quinoa genotypes using genotype by trait (GT) and genotype by yield × trait (GYT) graphical methods. Twenty genotypes obtained from the IPK Gene Bank in Germany were evaluated in a randomized complete block design with three replications over two cropping seasons (2023 and 2024) in Rasht, Iran. The evaluated traits comprised morphological, phenological, yield-related characteristics, and grain saponin content. The combined analysis of variance (ANOVA) revealed highly significant genetic variation among the genotypes for all traits, with significant effects of year and genotype × year interaction on key traits, including grain yield. GT analysis indicated that the first and second principal components accounted for 26.35% and 19.52%, respectively, explaining a total of 47% of the variance, and confirmed significant positive correlations between grain yield and traits such as panicle length and thousand-grain weight, as well as significant negative correlations between grain yield and specific phenological characteristics. Based on the GT biplot, genotypes 2 and 17, being closest to the center of the concentric circles, were identified as near-ideal genotypes with balanced performance across most traits. In contrast, GYT analysis revealed that the first two principal components accounted for 91.51% of the total variance, and the alignment of GY×PH, GY × SD, and GY×NPP vectors indicated positive correlations among these traits. The GYT biplot suggested that genotypes 6, 8, and 20 had balanced yield-trait profiles, highlighting their potential usefulness for further evaluation. Overall, this study provides preliminary evidence of quinoa performance under the tested conditions and emphasizes the theoretical applicability of the GYT approach in quinoa breeding programs.
Saravani et al. (Sat,) studied this question.