Document Type : Research Paper
Authors
1 Department of Biotechnology and Plant Breeding, Faculty of Agriculture, Ferdowsi University of Mashhad
2 Dryland Agricultural Research Station of Shirvan,, Agricultural and Natural Resources Research and Education Center, North Khorasan, Agricultural Research Education and Extension Organization (AREEO)
3 Department of Biotechnology and Plant Breeding, Agriculture Faculty, Ferdowsi University
Abstract
Introduction: Cereals are considered to be among the most important sources of human energy, among which bread wheat is recognized as an important and strategic crop in the world. Currently, developing drought-tolerant cultivars is counted a major challenge for breeders. Various methods are used to assess diversity in plant species, including multivariate statistical approaches. This study aimed to evaluate genetic diversity and select the most promising lines for improvement programs in rain-fed conditions.
Methodology: The experiment was conducted during the 2022–23 agricultural year at the Shirvan Rain-fed Agricultural Research Station- North Khorasan. In this research, 193 lines and seven rain-fed wheat cultivars were evaluated using an alpha lattice design with two replications. Data on phonological and morphological traits were collected during the growing season and after harvest. Statistical analyses were performed using SAS software version 9.4. Correlation analysis, stepwise regression, and principal component analysis (PCA) were conducted using R software (version 4.2.1). The Ideal Genotype Selection Index (SIIG) was calculated in Excel to identify the best-performing lines.
Research findings: Analysis of variance revealed significant differences among genotypes for all studied traits (p<0.01). Seed yield showed the strongest positive and significant correlations with biological yield (0.824), harvest index (0.817), plant height (0.393), spike weight (0.236), and thousand-kernel weight (0.221) (p<0.01). ). In contrast, an inverse relationship was observed between phonological traits (e.g., days to maturity, heading, and anthesis) and morphological traits (e.g., harvest index and thousand-kernel weight), suggesting that late-maturing genotypes tended to have lower seed weight and yield. The results of PCA indicated that the first three principal components accounted for 69.1% of the total variation among traits. Based on the SIIG index, genotypes 25, 73, 90, 84 and 190 were identified as the most ideal lines, with SIIG values of 0.91, 0.83, 0.83, 0.81 and 0.80 respectively. The correlation between the SIIG index and the evaluated traits showed that grain yield, biological yield, and harvest index had a high correlation with the SIIG index. Therefore, genotypes 25, 73, 90, 84 and 190 with high SIIG index and high yield potential, can be used in future breeding programs.
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