Selection of quinoa superior genotypes using geraphical methods in Kashmar region

Introduction
Quinoa (Chenopodium quinoa Willd.) is an annual seed crop from the Andean region of South America. The broad adap‌tation, high nutritional value, and health benefits of quinoa have contributed to its recent rise in popularity across the globe (Hinojosa et al., 2019).Quinoa seeds provide a high-quality protein diet to humans, as they typi‌cally contain significant amounts of the nine essential amino acids (Wu, 2015). Quinoa also possesses high concentrations of iron, calcium, and phosphorus (Wu, 2015; Vilcacundo and Hernández-Ledesma, 2017), has unique extrusion properties (Kowalski et al., 2016), and has important end-use quality and consumer acceptance characteristics (Aluwi et al., 2017). Quinoa has the capacity to grow and adapt to marginal environments in many regions across the globe, and it exhibits notable tolerance to abiotic stressors such as drought and salinity (Ruiz et al., 2014, 2016; Hinojosa et al., 2018). In breeding studies, when trying to develop a cultivar trait, it is possible to disrupt another trait. For this reason, the genotype × yield × trait (GYT) biplot evaluates all the traits together and provides more accurate results. In this regard, quinoa breeders should know whether any trait is negatively or positively correlated with grain yield. The aim of this study was to assess genotypes evaluation and trait profiles of quinoa using the GYT and GT biplot techniques and characterization of quinoa based on multiple traits under irrigation conditions.
Materials&Methods
10 quinoa genotypes (G1-G10) were studied during 2017 and 2018 at Kashmar Agricultural Research Station. The experimental design was a randomized complete block with three replications. Several main traits i. e., days to heading (DH), days to maturity (DMA), plant height (PLH), thousand kernel weight (TKW), length of Inflorescences (LI), saponin content (S) and grain yield (GY) were recorded for all genotypes. Genotype by yield by trait (GYT) biplot and genotype by trait (GT) biplot methods were used to select and characterize superior genotypes based on multiple traits. The combined analysis of variance for GY and other traits was conducted using ADEL-R software. The GYT biplot and GT biplot methodologies were employed to select and characterize quinoa genotypes based on multiple traits using GEA-R software.
Results&Discussion
The combined analysis of variance showed that the effect of genotype and genotype×year was significant at 1% probability level for all traits whereas the effect of genotype×year was significantn only for GY. On the whole, the mean of GY for the evaluated genotypes in the all years of the trial varied from 812 (Q31) to 1246 (Titicaca) kg/ha. Based on GT-Biplot polygon, Titicaca, Redcarina and Giza1 genotypes displayed high grain yield, thousand kernel weight, length of Inflorescences and saponin content. The vector view of GT biplot showed high positive correlation between grain yield with thousand kernel weight, length of Inflorescences, saponin content and negative correlation with number of Inflorescences, plant height and diameter of plant crown. Based on the GYT results, the genotypes Titicaca, Redcarina and Giza1 were the best in combining grain yield with the evaluated traits, respectively. According to the GYT index, Titicaca, Redcarina and Giza1 had the highest values, respectively. On the other hand, these theree cultivars did not have negative values for combined yield with different traits. This indicated the relative superiority of these genotypes in combining grain yield with the evaluated traits. The value of GYT index for Q18 genotyoe was close to zero (0.001) and this means that this genotype had average values of traits in this study.
Conclusion: Based on the results, the cultivars Titicaca, Redcarina and Giza1 were the most high-yielding genotypes as were characterized by high thousand kernel weight, length of Inflorescences and saponin content and low to medium plant height and diameter of plant crown in Kashmar condition. Also the GYT and GT biplot offer a useful analytic tool for examining the variation among sets of genotypes, exploring multiple trait data, which will aide in multi-trait selection.