Morphological characterization of introduced quinoa genotypes under Saudi Arabia conditions | ||
| Egyptian Journal of Agricultural Research | ||
| Article 27, Volume 101, Issue 2, July 2023, Pages 618-628 PDF (648.71 K) | ||
| Document Type: Original Article | ||
| DOI: 10.21608/ejar.2023.198267.1383 | ||
| Authors | ||
| Ehab H. Elharty* 1; Muhammad A. Khan2; Sulieman A. Al-Faifi2; Muhammed Afzal2; Salem S. Alghamdi2 | ||
| 1Food Legume Department, Field Crops Research Institute, Agricultural Research Center, Giza, Egypt. /Plant Production Department, College of Food and Agricultural Sciences, King Saud University, Riyadh, Saudi Arabia. | ||
| 2Plant Production Department, College of Food and Agricultural Sciences, King Saud University, Riyadh, Saudi Arabia | ||
| Abstract | ||
| Quinoa is a highly nutritious grain crop and has attracted attention for its strong growth potential under extremely harsh environments. Toward introducing it into Saudi Arabia's agriculture system, fifty-five quinoa genotypes were imported, and field evaluated during the winter seasons of 2016–17 and 2017–18. These genotypes were characterized by thirty-three characters using the descriptor from Bioversity International. Quinoa plant was green during the seedling stage, then pigments were scattered over many parts of the plant, and some colors changed during its life. Three colors were detected on the panicle at flowering and seven colors at maturity. Quinoa plant was between 60 and 193 cm in height, took 98 to 187 days to reach maturity, and produced 15.3 to 70.1 g of seeds per plant. Two genotypes (Ames 13747 and Ames 13720) produced high seed yields of 3.3 and 3.1 t/ha and belonged to the average maturing categories (118.1 and 122.3 days, respectively). A significant correlation was detected between seed yield and plant height, number of branches, leaf width, and leaf area. Based on K-means clustering, the genotypes were grouped into five clusters with high variation among them (87.3%) and only 12.7% within clusters. The results identified the morphological characters that could be used as selection criteria to increase the efficiency of quinoa seed yield improvement programs. | ||
| Keywords | ||
| Quinoa; morphology; description; K-means; cluster analysis | ||
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