1- ssistant Professor, Crop and Horticultural Science Research Department, Golestan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Gorgan, Iran.
2- Associate Professor, Oil Crops Research Department, Seed and Plant Improvement Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran
3- Assistant Professor, Plant Protection Department, Golestan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Gorgan, Iran.
2- Associate Professor, Oil Crops Research Department, Seed and Plant Improvement Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran
3- Assistant Professor, Plant Protection Department, Golestan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Gorgan, Iran.
Abstract: (325 Views)
Extended Abstract
Background: Sunflower is one of the most important sources of vegetable oil production that plays a pivotal role in food security, income and livelihood of the country's farmers. Currently, drought and the resulting stress are among the most common environmental stresses that lead to yield reduction, especially in dry and rainfed areas. Like most crops, sunflower productivity is significantly impacted by drought stress. Therefore, effective solutions to mitigate drought stress are essential. Given that sunflower hybrids are now cultivated as commercial varieties, producing superior hybrids with high seed and oil yields that are also tolerant to abiotic stress is crucial, considering climate change and aridity. The genotype-trait (GT) biplot analysis is a powerful statistical method that can identify correlations among traits by evaluating genotypes across multiple traits and identifying genotypes that excel in specific characteristics. this study employs the GT biplot method to explore the interrelationships between various traits and sunflower hybrids. The objectives of this research include identifying sunflower hybrids with desirable traits, investigating the relationships among the studied traits, and categorizing hybrids based on these traits using the GT biplot method.
Methods: Eighteen new sunflower hybrids, along with the Zarin hybrid as a control, were evaluated under both dryland and irrigated conditions. The experiment was conducted using a randomized complete block design with three replications at the National Agricultural Research Station and Dryland Seed Production of Gonbad-e Kavous (in dryland condition and winter cultivation in February) and the Agricultural Research Station in Gorgan (in irrigated condition and spring cultivation in April) during the 2023-2024 cropping season. Each hybrid was planted in plots with three rows, spaced 60 centimeters apart, with within-row spacing of 25 centimeters. Planting was done manually in hills. The planting was on flat beds in dryland conditions, while in irrigated conditions, it was on furrows created by a furrower. Agronomic traits, including day to maturity, plant height, head height from the ground, head diameter, stem diameter, seed number per head, thousand-seed weight, and seed yield, were evaluated. The oil content of 30-gram samples randomly selected from the seeds of each plot was measured in the oilseed laboratory of the Institute of Crop Improvement and Seed Production in Karaj. Subsequently, oil yield was calculated in kilograms per hectare. After obtaining the experimental data, the GGE biplot software was used for data analysis using the graphical GT biplot method with an appropriate statistical model.
Results: The GT biplot analysis explained a total of 78.3% of the standardized data diversity under dryland conditions (with the first and second principal components explaining 61.8% and 16.5%, respectively). Similarly, under irrigated conditions, the GT biplot explained 58.7% of the standardized data variation (with the first and second principal components explaining 39.4% and 19.3%, respectively). Overall, based on the polygonal representation of the GT biplot, hybrids numbered 4 and 16 excelled in dryland conditions, while hybrids numbered 2, 3, 4, and 16 performed well under irrigated conditions across most evaluated traits. The GT biplot analysis revealed that head diameter and stem diameter were positively correlated with seed yield under both dryland and irrigated conditions. Additionally, in dryland conditions, plant height was closest to the ideal trait, while under irrigation, the seed number per head exhibited the highest distinctiveness and representativeness. The overall comparison using the GT biplot indicated that, under dryland conditions, hybrids numbered 4, 16, 1, 10, and 2 were the most desirable across all evaluated traits. Similarly, under irrigated conditions, hybrids numbered 16, 4, and 10 stood out as the preferred hybrids based on the studied traits. Furthermore, hybrid number 3 (under dryland conditions) and hybrid number 11 (under irrigated conditions) were the least desirable hybrids compared to the ideal hybrid. The graphical analysis of hybrid stability revealed that hybrid number 16 was selected as the best and most stable hybrid for both dryland and irrigated conditions.
Conclusion: Breeding drought-tolerant sunflower varieties and hybrids with high yield potential is crucial to improve water resource limitation. Hybrids performing well in both dryland and irrigated conditions, concerning seed and oil yield, should be prioritized. Improving plant height and stem diameter in dryland conditions enhances seed yield, while in irrigated conditions, improving head diameter leads to better seed performance. Hybrids 4 and 16 performed favorably in both dryland and irrigated conditions, while hybrids 2 and 3 excelled under irrigated conditions in terms of seed and oil yield. This study demonstrates the effectiveness of the GT biplot method in identifying various traits and selecting productive and stable hybrids.
Background: Sunflower is one of the most important sources of vegetable oil production that plays a pivotal role in food security, income and livelihood of the country's farmers. Currently, drought and the resulting stress are among the most common environmental stresses that lead to yield reduction, especially in dry and rainfed areas. Like most crops, sunflower productivity is significantly impacted by drought stress. Therefore, effective solutions to mitigate drought stress are essential. Given that sunflower hybrids are now cultivated as commercial varieties, producing superior hybrids with high seed and oil yields that are also tolerant to abiotic stress is crucial, considering climate change and aridity. The genotype-trait (GT) biplot analysis is a powerful statistical method that can identify correlations among traits by evaluating genotypes across multiple traits and identifying genotypes that excel in specific characteristics. this study employs the GT biplot method to explore the interrelationships between various traits and sunflower hybrids. The objectives of this research include identifying sunflower hybrids with desirable traits, investigating the relationships among the studied traits, and categorizing hybrids based on these traits using the GT biplot method.
Methods: Eighteen new sunflower hybrids, along with the Zarin hybrid as a control, were evaluated under both dryland and irrigated conditions. The experiment was conducted using a randomized complete block design with three replications at the National Agricultural Research Station and Dryland Seed Production of Gonbad-e Kavous (in dryland condition and winter cultivation in February) and the Agricultural Research Station in Gorgan (in irrigated condition and spring cultivation in April) during the 2023-2024 cropping season. Each hybrid was planted in plots with three rows, spaced 60 centimeters apart, with within-row spacing of 25 centimeters. Planting was done manually in hills. The planting was on flat beds in dryland conditions, while in irrigated conditions, it was on furrows created by a furrower. Agronomic traits, including day to maturity, plant height, head height from the ground, head diameter, stem diameter, seed number per head, thousand-seed weight, and seed yield, were evaluated. The oil content of 30-gram samples randomly selected from the seeds of each plot was measured in the oilseed laboratory of the Institute of Crop Improvement and Seed Production in Karaj. Subsequently, oil yield was calculated in kilograms per hectare. After obtaining the experimental data, the GGE biplot software was used for data analysis using the graphical GT biplot method with an appropriate statistical model.
Results: The GT biplot analysis explained a total of 78.3% of the standardized data diversity under dryland conditions (with the first and second principal components explaining 61.8% and 16.5%, respectively). Similarly, under irrigated conditions, the GT biplot explained 58.7% of the standardized data variation (with the first and second principal components explaining 39.4% and 19.3%, respectively). Overall, based on the polygonal representation of the GT biplot, hybrids numbered 4 and 16 excelled in dryland conditions, while hybrids numbered 2, 3, 4, and 16 performed well under irrigated conditions across most evaluated traits. The GT biplot analysis revealed that head diameter and stem diameter were positively correlated with seed yield under both dryland and irrigated conditions. Additionally, in dryland conditions, plant height was closest to the ideal trait, while under irrigation, the seed number per head exhibited the highest distinctiveness and representativeness. The overall comparison using the GT biplot indicated that, under dryland conditions, hybrids numbered 4, 16, 1, 10, and 2 were the most desirable across all evaluated traits. Similarly, under irrigated conditions, hybrids numbered 16, 4, and 10 stood out as the preferred hybrids based on the studied traits. Furthermore, hybrid number 3 (under dryland conditions) and hybrid number 11 (under irrigated conditions) were the least desirable hybrids compared to the ideal hybrid. The graphical analysis of hybrid stability revealed that hybrid number 16 was selected as the best and most stable hybrid for both dryland and irrigated conditions.
Conclusion: Breeding drought-tolerant sunflower varieties and hybrids with high yield potential is crucial to improve water resource limitation. Hybrids performing well in both dryland and irrigated conditions, concerning seed and oil yield, should be prioritized. Improving plant height and stem diameter in dryland conditions enhances seed yield, while in irrigated conditions, improving head diameter leads to better seed performance. Hybrids 4 and 16 performed favorably in both dryland and irrigated conditions, while hybrids 2 and 3 excelled under irrigated conditions in terms of seed and oil yield. This study demonstrates the effectiveness of the GT biplot method in identifying various traits and selecting productive and stable hybrids.
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