Document Type : Original Article
Authors
1
Ph.D. graduate, Department of Plant Production and Genetic Engineering, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran
2
Professor, Department of Plant Production and Genetic Engineering, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran
3
Ph. D. Student, Department of Plant Production and Genetic Engineering, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran
4
Professor, Department of Biotechnology and Plant Breeding, Faculty of Agricultural Sciences, University of Ferdowsi, Mashhad , Iran
5
Professor, Department of Genebank, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Leibniz, Germany
Abstract
In plant breeding programs, selection is one of the most important steps, and its efficiency is highly depends on the genetic diversity of the population and the heritability of traits. Due to the complexity of grain yield inheritance, direct selection is not very effective to improve it, so it is possible to obtain the necessary information for indirect selection to improve selection for grain yield by using multivariate statistical methods. The purpose of this research was to investigate the relationships between important agricultural traits, evaluate basic selection indices and provide the best indices to improve grain yield and identify the best quinoa genotypes to continue the breeding program to introduce the cultivar. For this purpose, 60 quinoa genotypes received from IPK Institute of Germany and were evaluated in the frame of randomized complete block design with 3 replications in 2022 in the research farm located in Kohdasht city. The results of phenotypic and genotypic path analysis of grain yield showed that the two traits of 1000-grain weight and number of panicle per plant had the most positive and significant direct effect on the grain yield of the studied genotypes. Also, the use of phenotypic and genotypic correlation coefficients and the first row traits included in the path analysis model of grain yield as economic value led to the highest genetic benefit of the traits and therefore, they can be good and suitable indicators for the selection of superior quinoa genotypes.
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