Evaluation of Diversity and Application of Agronomic, Morphological, and Physiological Traits to Improve Quinoa (Chenopodium quinoa Willd.) Grain Yield

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Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:

The purpose of this study was to evaluate the diversity and predict the response to selection in different traits of 16 quinoa genotypes, which was done in a randomized complete block design in Karaj and Kermanshah. The genotypes had a statistically significant difference (p ≤0.01) for the majority of the traits, and they were distributed in four biplot regions. Genotypes 14, 15, and 16 had the highest, and genotypes 5 and 6 had the lowest grain yield and grain harvest index. While the main panicle diameter, grain harvest index, day to physiological maturity, day to main panicle color change, 1000-grain weight, and day to flowering had the highest positive alignment with yield component, day to ten leaf trait had a strong but negative connection with it.  The highest genetic distance was observed between the first and third clusters, which can be achieved by crossing the selected genotypes of these two clusters, to create the greatest genetic diversity in the dividing generations. Grain harvest index and diameter of the main panicle with the highest coefficient of genetic diversity, high heritability, and the highest genetic progression were identified as two desirable traits with a high selection response.  Positive selection for these two traits and negative selection for day to ten leaf traits are suggested in future breeding programs of this plant. In general, due to the limitation of direct selection to improve grain yield, also according to the significant correlation (r = 0.994***) between the new parameter of "percentage difference between phenotypic variation coefficient and genotypic variation coefficient" with broad-sense heritability, the use of this new genetic parameter to select desirable agro morphophysiological traits is recommended.

Language:
Persian
Published:
Journal of Crop production and processing, Volume:11 Issue: 4, 2022
Pages:
53 to 68
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