Evaluation of important agronomic traits related to yield and identification of superior quinoa genotypes

Introduction
Quinoa (Chenopodium quinoa Willd) is adapted to many regions and has the ability to grow in desert and frosts conditions, and hot and dry climates. Due to the low water requirement of quinoa, the development of its cultivation can be expanded in most provinces of the country, and in addition to providing the food needs of the growing population, it can also help in creating jobs in these areas. Since the economic value of a variety depends on the value of its various traits, it is necessary to know the status of traits and the variation between genotypes in the studied population to improve and introduce cultivars. Although early maturity quinoa cultivars have been identified and/or improved in the native land of this plant in South America and in many European countries, so far, early maturity cultivars with the other suitable quantitative and qualitative characteristics such as high grain yield and quality have not been introduced. The present study was conducted to investigate the important morphological and phenological traits related to grain yield and growth period among a number of foreign quinoa genotypes. The objectives of this experiment were to evaluate genetic diversity between genotypes in term of the studied traits and to identify and introduce high-yielding, early maturity and plantable genotypes in the region.
Materials and methods
The plant materials of this research were sixty foreign quinoa genotypes with the origin of Peru, Chile and Bolivia, obtained from the Genebank of Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Leibniz, Germany. The studied genotypes were planted in randomized complete block design with three replications in Koohdasht, Khorramabad province, Iran, in 2021 and were investigated in for important quantitative traits related to yield and yield components. The studied traits included number of days from seed sowing to growth stages of three leaves, inflorescence formation, inflorescence coloring, pollination and physiological maturity, as well as plant height, panicle length, number of panicles per plant, 1000-grain weight, grain yield, harvest index, grain saponin percentage and grain protein percentage. For data analysis, in addition to analysis of variance and comparison of means, the relationship between the studied traits was also evaluated by phenotypic and genotypic correlation coefficients, the traits affecting grain yield were identified by stepwise regression analysis, and direct and indirect effects of each trait on grain yield were estimated using path analysis method. Also, factor analysis was used to identify the hidden and independent factors affecting the studied traits and the reasons of traits correlation, and cluster analysis was used to group the genotypes and select the superior genotypes of this experiment. All statistical analyzes of this experiment were performed using SAS ver. 9.2 and SPSS ver. 25 statistical softwares.
Research findings
The results obtained from the various statistical indices indicated the existence of statistically significant differences and high diversity among the studied quinoa genotypes for most of the evaluated traits. Calculating phenotypic and genotypic correlation coefficients showed significant correlations between grain yield and 1000-grain weight (0.938 and 0.934), harvest index (0.964 and 0.852), panicle length (0.762 and 0.750) and number of panicles per plant (0.677 and 0.651), respectively. The results of stepwise regression and path analyses of grain yield showed that 1000-grain weight and main panicle length with the highest positive and significant direct effects on grain yield, were the most important predictive variables for grain yield. Based on the results of factor analysis, three independent factors justified 81% (40%, 32% and 9%, respectively) of total variation in the studied population. Cluster analysis based on Ward’s minimum variance method grouped 60 quinoa genotypes into three clusters, which included 25, 19 and 16 genotypes, respectively. The grouping resulting from the cluster analysis corresponded to the geographical distribution of the genotypes, so that the genotypes of Bolivia, Peru and Chile were grouped in the first, second and third clusters, respectively. A number of genotypes in the first and second groups with the higher values for grain yield, 1000-grain weight and panicle length, as well as the lower values for grain saponin content and phenological characteristics related to growth period, can be selected and suggested for use in the multi-regional trials to introduce the variety programs or for use in the future breeding programs.
Conclusion
The results of the present study showed a significant and very high phenotypic diversity among the studied quinoa genotypes. The superior genotypes identified in this research, after confirming the results in repeating the experiment, can be directly introduced as the new varieties and/or used as the suitable genetic resources in different quinoa breeding programs.