Evaluation of new sunflower hybrids using multi-trait selection indices for identifying superior genotypes under dryland conditions | ||
| زراعت دیم ایران | ||
| Articles in Press, Accepted Manuscript, Available Online from 05 May 2026 PDF (1.55 M) | ||
| Document Type: Research Paper | ||
| DOI: 10.22092/idaj.2026.371453.455 | ||
| Authors | ||
| Hossein Ahmadi-Ochtapeh* 1; Mehdi Ghaffari2 | ||
| 1Horticulture Crops Research Department, Golestan Agricultural and Natural Resources Research and Education Center, AREEO, Gorgan, Iran. | ||
| 2Associate Professor, Oil Crops Research Department, Seed and Plant Improvement Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran | ||
| Abstract | ||
| Introduction: Sunflower is one of the most important oilseed crops worldwide, and its yield is highly affected by drought stress. Therefore, identifying superior genotypes with enhanced tolerance to environmental stresses is essential for cultivation under dryland conditions. Relying on a single trait in the selection process is unlikely to yield satisfactory results; hence, the use of multiple traits and multi-trait indices can improve the accuracy of identifying superior genotypes. Accordingly, the objective of this study was to select the best-performing sunflower hybrids under dryland conditions using the Selection index of ideal genotype (SIIG) and the Factor analysis ideotype-design-best linear unbiased prediction (FAI-BLUP). Methodology: This experiment was conducted using 12 newly developed sunflower hybrids along with three check cultivars (Zarrin, Shams, and Azar) at the National Agricultural Research Station and Dryland Seed Production of Gonbad-e Kavus over two cropping seasons (2023–2025). The trial was arranged in a randomized complete block design (RCBD) with four replications. Seeds of each hybrid were sown in a 2.7 m² experimental plot consisting of four rows, each 3 m in length, with a row spacing of 60 cm. The experimental field had been cultivated with wheat in the previous season. Planting was performed manually on flat soil, and weed control was carried out by hand. Traits including days to flowering, days to ripening, plant height, distance between ground and head, head diameter, stem diameter were recorded. After harvest, yield‑related characteristics such as thousand‑kernel weight, seed yield, oil content, and oil yield were measured. Statistical analyses, including analysis of variance (ANOVA) and the selection of the superior genotypes using the SIIG method, were performed with SAS ver. 9.4 and Microsoft Excel. In addition, the FAI-BLUP method was analyzed using R software and the multi-environment trials package (metan). Research findings: The results of the combined analysis of variance revealed that both the effect of year and the genotype × year interaction were significant at the 1% probability level for all studied traits, indicating the strong influence of environmental conditions and the differential responses of genotypes across years. Moreover, the main effect of genotype was significant for all traits. The comparison of means indicated significant differences among hybrids for the evaluated traits, particularly grain yield. Hybrids H1, H10, H11, and H9 produced the highest seed yields, while H6 and H7 recorded the lowest seed yields. The multi-trait SIIG index identified hybrids H1, H9, H11, H10, H13, and H2 as superior genotypes. The two-dimensional graph further confirmed that hybrids H1, H10, H11, and H9 clustered in the first group with both high yield and SIIG values. In addition, the FAI-BLUP index selected hybrids H1 and H9 as superior. Overall, hybrids H1, H9, H10, H11, and H13 consistently ranked among the best across most indices and agronomic traits, suggesting their suitability for cultivation under dryland conditions. | ||
| Keywords | ||
| Sunflower; Agronomic traits; Grain yield; Superior genotype; Dryland conditions | ||
| References | ||
|
| ||
|
Statistics Article View: 2 PDF Download: 1 |
||
Journal management system. designed by sinaweb