1- 1 Dryland Agricultural Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Gachsaran, Iran
Abstract: (9 Views)
Introduction and Objective: Understanding and utilizing genetic diversity is the main pillar of success in plant breeding programs and can be an effective approach to produce suitable varieties to improve grain yield and increase production efficiency in different climatic conditions. Multivariate statistical methods are widely used to evaluate genetic diversity and analyze relationships between different traits. Given the urgent need to produce varieties suitable for rainfed cultivation, this study was conducted with the aim of evaluating the genetic diversity of barley genotypes based on agronomic traits. The findings of this study can provide valuable data for improving and cultivating barley in low-rainfall areas of southern Iran, especially the tropical areas of Kohgiluyeh and Boyer-Ahmad.
Materials and Methods: This study aimed to investigate the genetic diversity and agronomic traits of 310 barley genotypes along with four control cultivars ("Behdad", "Khoram", "Rasta" and "Fardan") in the 1402-1403 crop year at Gachsaran Agricultural Research Campus and National Rainfed Site. The experiment was conducted in a large block design with a randomized complete block design in 23 blocks. Initially, for the control cultivars, analysis of variance was performed based on a randomized complete block design using InfoStat statistical software. Cluster analysis was performed based on Euclidean distance and Ward clustering algorithm using R software and dynamicTreeCut, colorspace and dendextend statistical packages. Correlation between traits was performed using the Pearson method and using the R statistical software. Online software (jvenn.toulouse.inra.fr) was used to draw Vann Diagram to identify genotypes with overlap in important traits.
Results: For the 13 best genotypes selected from the Venn diagram, MGIDI analysis was performed. Four factors (FA1 to FA4) explained 86.6% of the total variance in the following order: FA1 Phenological factor: including days to flowering, spike length, plant height (31.1% variance), FA2 Morphological factor: including panicle length, peduncle length, 1000-seed weight (24.3% variance), FA3 Yield factor: including grain yield, days to physiological maturity, number of seeds per spike (18.9% variance), FA4 Early emergence factor: including early emergence vigor (12.3% variance). Genotypes 184, 79, and 28 were identified as having the least distance from the ideal genotype and the best multi-trait performance. Genotype 79 performed better in traits related to the first factor (phenological) and genotype 28 in traits related to the second and third factors (morphological and yield). The condition of all three superior genotypes was more favorable than the theoretical average in terms of the fourth factor (initial germination strength). The grain yield of genotypes 79, 184, 25, 172 and 59 was higher than the average of the controls (3995 kg/ha). Genotype 28, despite a slightly lower yield than the average of the controls, had a higher yield than the cultivar 'Rosta' and the heat diagram showed that genotype 28 was favorable for almost all the traits studied. Genotype 184, with the highest yield among the selected genotypes, was less favorable than others in some traits (such as number of grains per spike and days to spike emergence).
Conclusion: The results of this study showed that there is considerable diversity among the genotypes studied and these genotypes can be used as germplasm in further breeding studies. However, among the high-yielding genotypes (more than 2900 kg/ha), 13 genotypes had desirable values in all five important traits. Among these genotypes, 9 genotypes were from the gene bank treasury and 4 genotypes were control cultivars. Finally, three selected genotypes (28, 79 and 184) were selected as the best genotypes and are expected to be used in future breeding programs.
Materials and Methods: This study aimed to investigate the genetic diversity and agronomic traits of 310 barley genotypes along with four control cultivars ("Behdad", "Khoram", "Rasta" and "Fardan") in the 1402-1403 crop year at Gachsaran Agricultural Research Campus and National Rainfed Site. The experiment was conducted in a large block design with a randomized complete block design in 23 blocks. Initially, for the control cultivars, analysis of variance was performed based on a randomized complete block design using InfoStat statistical software. Cluster analysis was performed based on Euclidean distance and Ward clustering algorithm using R software and dynamicTreeCut, colorspace and dendextend statistical packages. Correlation between traits was performed using the Pearson method and using the R statistical software. Online software (jvenn.toulouse.inra.fr) was used to draw Vann Diagram to identify genotypes with overlap in important traits.
Results: For the 13 best genotypes selected from the Venn diagram, MGIDI analysis was performed. Four factors (FA1 to FA4) explained 86.6% of the total variance in the following order: FA1 Phenological factor: including days to flowering, spike length, plant height (31.1% variance), FA2 Morphological factor: including panicle length, peduncle length, 1000-seed weight (24.3% variance), FA3 Yield factor: including grain yield, days to physiological maturity, number of seeds per spike (18.9% variance), FA4 Early emergence factor: including early emergence vigor (12.3% variance). Genotypes 184, 79, and 28 were identified as having the least distance from the ideal genotype and the best multi-trait performance. Genotype 79 performed better in traits related to the first factor (phenological) and genotype 28 in traits related to the second and third factors (morphological and yield). The condition of all three superior genotypes was more favorable than the theoretical average in terms of the fourth factor (initial germination strength). The grain yield of genotypes 79, 184, 25, 172 and 59 was higher than the average of the controls (3995 kg/ha). Genotype 28, despite a slightly lower yield than the average of the controls, had a higher yield than the cultivar 'Rosta' and the heat diagram showed that genotype 28 was favorable for almost all the traits studied. Genotype 184, with the highest yield among the selected genotypes, was less favorable than others in some traits (such as number of grains per spike and days to spike emergence).
Conclusion: The results of this study showed that there is considerable diversity among the genotypes studied and these genotypes can be used as germplasm in further breeding studies. However, among the high-yielding genotypes (more than 2900 kg/ha), 13 genotypes had desirable values in all five important traits. Among these genotypes, 9 genotypes were from the gene bank treasury and 4 genotypes were control cultivars. Finally, three selected genotypes (28, 79 and 184) were selected as the best genotypes and are expected to be used in future breeding programs.
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