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Extended Abstract
Background: With increasing population and limited resources, the production of high-yielding and high-quality crops is essential. Plant breeding, as a foundation of modern agriculture, plays a key role in ensuring food security and adapting to environmental changes. Sunflower (Helianthus annuus L.), due to its drought tolerance and adaptability to low-fertility soils, is a suitable crop for cultivation in arid and semi-arid regions of Iran. This study aimed to evaluate the combining ability of sunflower lines and testers for important agronomic traits such as seed yield, and oil content using the line × tester analysis method.
Methods: The study was conducted at the Research Farm of the Seed and Plant Improvement Institute (SPII) in Karaj, Iran, over two growing seasons (2023 and 2024). The experimental materials included 9 fertility restorer lines and 2 cytoplasmic male sterile (CMS) lines as testers. In the second year, 18 hybrids and 11 parents were cultivated in a randomized complete block design with three replications. The measured traits included days to flowering (DTF), flowering duration (FD), days to maturity (DTM), seed filling period (SFP), plant height (PH), head diameter (HD), thousand seed weight (TSW), seeds per head (SPH), oil content (OC), seed yield per hectare (SYH), and oil yield (OY). Data were analyzed using the line × tester method to estimate general combining ability (GCA) and specific combining ability (SCA).
Results: Analysis of variance (ANOVA) revealed that the effects of lines, testers, and their interactions were significant for most traits. The effect of lines was significant for days to maturity, seed filling period, and thousand seed weight, while the effect of testers was significant for plant height and seed yield per hectare. The line × tester interaction (SCA) was highly significant for key traits such as days to flowering, seed yield, and oil content. Specific combinations, such as Line 6 × Tester 1, showed the highest positive effects on seed yield per hectare (726.2 kg ha⁻¹) and seeds per head (156.6). The GCA for lines and testers indicated that Line 2 and Line 8 had the most positive effects on days to flowering and seed filling period, respectively. Additive and dominance variances showed that key traits such as seed yield and oil content were strongly influenced by dominance effects.
Conclusion: The results demonstrated that selecting appropriate line × tester combinations can significantly improve agronomic traits such as seed yield and oil content. GCA and SCA were key indicators for identifying superior lines and testers. Lines such as Line 2 and Line 8 had the most positive effects on days to flowering and seed filling period, while specific combinations like Line 6 × Tester 1 showed the highest positive effects on seed yield per hectare and seeds per head. These findings highlight the importance of optimal line × tester combinations in improving crop performance and quality. SCA played a crucial role in controlling key traits such as seed yield and oil content. Specific combinations, such as Line 6 × Tester 1, showed the highest positive effects on seed yield per hectare (726.2 kg ha⁻¹) and seeds per head (156.6), while other combinations, such as Line 1 × Tester 2, showed strong negative effects. These results indicate that the interaction between lines and testers can significantly influence agronomic traits, and selecting appropriate combinations can contribute to the development of new cultivars with improved yield and quality. Overall, this study underscores the importance of the line × tester analysis method in breeding programs. The identified combinations can serve as a foundation for developing high-yielding and stress-tolerant sunflower cultivars. Additionally, the use of these combinations can enhance productivity, reduce production costs, and promote sustainable agricultural systems. Future studies should consider greater genetic diversity and environmental effects to improve the generalizability of the results.
Background: With increasing population and limited resources, the production of high-yielding and high-quality crops is essential. Plant breeding, as a foundation of modern agriculture, plays a key role in ensuring food security and adapting to environmental changes. Sunflower (Helianthus annuus L.), due to its drought tolerance and adaptability to low-fertility soils, is a suitable crop for cultivation in arid and semi-arid regions of Iran. This study aimed to evaluate the combining ability of sunflower lines and testers for important agronomic traits such as seed yield, and oil content using the line × tester analysis method.
Methods: The study was conducted at the Research Farm of the Seed and Plant Improvement Institute (SPII) in Karaj, Iran, over two growing seasons (2023 and 2024). The experimental materials included 9 fertility restorer lines and 2 cytoplasmic male sterile (CMS) lines as testers. In the second year, 18 hybrids and 11 parents were cultivated in a randomized complete block design with three replications. The measured traits included days to flowering (DTF), flowering duration (FD), days to maturity (DTM), seed filling period (SFP), plant height (PH), head diameter (HD), thousand seed weight (TSW), seeds per head (SPH), oil content (OC), seed yield per hectare (SYH), and oil yield (OY). Data were analyzed using the line × tester method to estimate general combining ability (GCA) and specific combining ability (SCA).
Results: Analysis of variance (ANOVA) revealed that the effects of lines, testers, and their interactions were significant for most traits. The effect of lines was significant for days to maturity, seed filling period, and thousand seed weight, while the effect of testers was significant for plant height and seed yield per hectare. The line × tester interaction (SCA) was highly significant for key traits such as days to flowering, seed yield, and oil content. Specific combinations, such as Line 6 × Tester 1, showed the highest positive effects on seed yield per hectare (726.2 kg ha⁻¹) and seeds per head (156.6). The GCA for lines and testers indicated that Line 2 and Line 8 had the most positive effects on days to flowering and seed filling period, respectively. Additive and dominance variances showed that key traits such as seed yield and oil content were strongly influenced by dominance effects.
Conclusion: The results demonstrated that selecting appropriate line × tester combinations can significantly improve agronomic traits such as seed yield and oil content. GCA and SCA were key indicators for identifying superior lines and testers. Lines such as Line 2 and Line 8 had the most positive effects on days to flowering and seed filling period, while specific combinations like Line 6 × Tester 1 showed the highest positive effects on seed yield per hectare and seeds per head. These findings highlight the importance of optimal line × tester combinations in improving crop performance and quality. SCA played a crucial role in controlling key traits such as seed yield and oil content. Specific combinations, such as Line 6 × Tester 1, showed the highest positive effects on seed yield per hectare (726.2 kg ha⁻¹) and seeds per head (156.6), while other combinations, such as Line 1 × Tester 2, showed strong negative effects. These results indicate that the interaction between lines and testers can significantly influence agronomic traits, and selecting appropriate combinations can contribute to the development of new cultivars with improved yield and quality. Overall, this study underscores the importance of the line × tester analysis method in breeding programs. The identified combinations can serve as a foundation for developing high-yielding and stress-tolerant sunflower cultivars. Additionally, the use of these combinations can enhance productivity, reduce production costs, and promote sustainable agricultural systems. Future studies should consider greater genetic diversity and environmental effects to improve the generalizability of the results.
Keywords: Specific Combining Ability, Genetic Variance of Dominance, Heterosis (Hybrid Vigor), Additive Genetic Variance, Genetic Diversity.
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