Volume 7, Issue 3 (9-2025)                   alkhass 2025, 7(3): 1-6 | Back to browse issues page


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Taghizadeh Tabari Z, Roostaei M. Clustering Wheat (Triticum aestivum L.) Varieties Based on Agronomic Traits: A Key Approach for Breeding High-Yielding Cultivars under Rainfed Conditions. alkhass 2025; 7 (3) :1-6
URL: http://alkhass.srpub.org/article-4-282-en.html
1- Postdoctoral Researcher, Iran National Science Foundation (INSF), Iran , zt.tabari@gmail.com
2- Head of Department, Dryland Agricultural Research Institute (DARI), Maragheh, Iran
Abstract:   (54 Views)
Wheat is a vital crop for global food security, particularly in regions with unpredictable rainfall, such as Iran. Understanding the factors that influence wheat yield under adverse conditions is essential for developing effective management strategies to ensure sustainable productivity. Clustering analysis is a valuable tool for identifying distinct groups of wheat genotypes with similar agronomic traits, enabling targeted breeding for improved yield and adaptability, especially under rainfed conditions. This study evaluated seven wheat varieties (Nafis, Dehghan, Sadra, Kamal, Hashtrood, Baran, and Varan) to identify key agronomic traits influencing grain yield under such conditions. Traits measured included Shoot length (LSHOOT), the number of seeds (Nseed), thousand-grain weight (Wseed), number of spikes (Nspike), harvest index (HI), leaf area (LA), photosynthesis (Ps), vegetative stage (Veg), booting stage (BOOT), flowering stage (FLOW), grain filling period (Gfill), biological yield (Ybio), and grain yield (Ygrain). The clustering analysis revealed four distinct clusters based on these agronomic traits. Cluster 1 included Kamal and Varan, which shared strong similarities in harvest index and growth period. Cluster 2 consisted of Hashtrood and Sadra, exhibiting similar phenological traits such as stem elongation and booting dates. Cluster 3 was comprised solely of Baran, which demonstrated unique yield components distinguishing it from the other varieties. Finally, Cluster 4 grouped Dehghan and Nafis, which showed greater variability in their yield-related and phenological traits, indicating the need for more customized management practices. The results of the clustering analysis also highlighted two primary trait groups. The first group, including number of spikes (Nspike), thousand-grain weight (Wseed), photosynthesis (Ps), tillering stage (Till), and flowering stage (Flow), is associated with early growth and development stages. The second group, comprising grain yield (Ygrain), biological yield (Ybio), and leaf area (LA), is more closely related to the final yield outcome. These findings emphasize the importance of selecting wheat cultivars based on specific agronomic traits to enhance yield potential under rainfed conditions and underscore the potential for improving wheat production through targeted breeding strategies.
Full-Text [PDF 308 kb]   (27 Downloads)    
Type of Study: Research | Subject: Seed Science and Technology
Received: 2025/07/22 | Revised: 2025/08/17 | Accepted: 2025/09/15 | Published: 2025/09/30

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