1- Agricultural Research, Education and Extension Organization
Abstract: (23 Views)
Introduction and Objective: Rapeseed, after soybean, is considered the second most important oilseed crop worldwide. Given the impacts of climate change particularly in arid and warm regions such as Sistan, it is essential to identify and introduce spring rapeseed lines that combine desirable traits of high yield and early maturity.
Material and Methods: In this study, ten promising spring rapeseed lines, previously selected from preliminary trials conducted in the warm climates of northern and southern Iran, were evaluated under the environmental conditions of the Sistan region. These lines, along with three check cultivars—Dalgan, Safar, and RGS003—were cultivated and assessed over two cropping seasons (2019–2021) using a randomized complete block design (RCBD) with three replications. The spring-type lines used in this experiment were pure lines developed through the pedigree breeding method. During the growth period, several agronomic traits were recorded, including days to flowering initiation, days to the end of flowering, flowering duration, days to maturity, plant height, number of branches per plant, number of pods per plant, and number of seeds per pod. After harvest, seed yield and thousand-seed weight were also measured. A combined analysis of variance (ANOVA) was conducted for seed yield and other quantitative traits. Mean comparisons among genotypes were performed using the Least Significant Difference (LSD) method. Pearson correlation analysis was employed to assess the relationships among quantitative traits. Factor analysis, based on Pearson correlations, was carried out to identify the principal contributing factors. Additionally, simultaneous selection of genotypes based on agronomic traits and yield was performed using the SIIG (Selection Index of the Ideal Genotype) method. In this index, maximum values were considered ideal for traits such as flowering duration, number of lateral branches, plant height, number of pods per plant, number of seeds per pod, thousand-seed weight, and seed yield, while minimum values were preferred for days to flowering initiation, days to end flowering, and days to maturity. Statistical analyses were conducted using XLSTAT and SPSS software packages.
Results: The combined analysis of variance revealed that the effect of genotype was significant for all evaluated traits. Evaluation of the quantitative traits exhibited seed yield, number of branches per plant, number of seeds per pod, and flowering duration (number of days) as the highest coefficients of variation, with values of 10.9%, 10.1%, 9.8%, and 6.7%, respectively. Mean comparison of seed yield detected lines 9, 10, and 7, with average yields of 3137, 3105, and 3096 kg ha-1, as the top three promising lines, outperforming the check cultivars. The check varieties RGS003 (line 12) and Dalgan (line 11) followed with average yields of 2857 and 2806 kg/ha, respectively. Furthermore, lines 9 and 10 not only exhibited high yield performance but also demonstrated desirable earliness, with no significant difference in maturity compared to the very early-maturing check cultivar Safar (line 13). Correlation analysis among quantitative traits showed that seed yield had a significant positive correlation with plant height, number of seeds per pod, number of pods per plant, and number of branches per plant. Genotype ranking based on the Selection Index of the Ideal Genotype (SIIG) identified lines 10, 9, 7, 1, and 8 as the top-performing lines, showing the shortest distance from the ideal genotype and the greatest distance from the least desirable genotype. The genotype rankings obtained through the SIIG method were relatively consistent with those based on average seed yield, suggesting that the promising lines in this study possessed desirable agronomic traits in addition to high productivity. Evaluation of genetic gain using both ranking methods based on mean yield and the SIIG index indicated that while both approaches effectively identified high-yielding genotypes, the SIIG method showed greater genetic improvement in other quantitative traits such as plant height, number of branches per plant, number of pods per plant, and number of seeds per pod. Broad-sense heritability estimates revealed that seed yield, plant height, number of pods per plant, days to flowering initiation, and number of seeds per pod had the highest heritability values, respectively. Principal component analysis (PCA) showed that the first two components accounted for 69.83% of the total variation. Seed yield and its components including number of branches per plant, number of pods per plant, number of seeds per pod, and thousand-seed weight were most strongly associated with the first principal component. In contrast, plant height and phenological traits such as days to flowering initiation, days to end of flowering, and days to maturity were most correlated with the second component. PCA also revealed that the SIIG index was highly correlated with the first component, alongside traits such as seed yield, number of branches per plant, number of pods per plant, number of seeds per pod, and thousand-seed weight. The biplot based on the first two principal components confirmed that lines 9, 10, and 7 were the most promising genotypes in this study.
Conclusion: The significant differences observed in morphological and phenological traits, along with the presence of substantial variability in seed yield, number of branches per plant, number of seeds per pod, and flowering duration, highlight the potential of the evaluated promising rapeseed lines for future breeding programs. Genotype selection using the ideal genotype selection index (SIIG) demonstrated the utility of this multi-trait approach as an effective tool for identifying superior rapeseed lines. This method not only led to the identification of genotypes with high seed yield but also ensured the selection of genotypes with desirable agronomic characteristics.Overall, the results showed that the SIIG-based selection method was associated with considerable genetic improvement in both yield and other quantitative traits. The selected genotypes exhibited superior performance across multiple traits, indicating their suitability for further breeding and commercial cultivation. Ultimately, three promising lines—9 (SRL-98-17), 7 (SRL-98-15), and 10 (SRL-98-19)—were identified as the most adapted and high-performing genotypes under the environmental conditions of the Sistan region, due to their high yield potential, early maturity, and favorable agronomic traits.
Material and Methods: In this study, ten promising spring rapeseed lines, previously selected from preliminary trials conducted in the warm climates of northern and southern Iran, were evaluated under the environmental conditions of the Sistan region. These lines, along with three check cultivars—Dalgan, Safar, and RGS003—were cultivated and assessed over two cropping seasons (2019–2021) using a randomized complete block design (RCBD) with three replications. The spring-type lines used in this experiment were pure lines developed through the pedigree breeding method. During the growth period, several agronomic traits were recorded, including days to flowering initiation, days to the end of flowering, flowering duration, days to maturity, plant height, number of branches per plant, number of pods per plant, and number of seeds per pod. After harvest, seed yield and thousand-seed weight were also measured. A combined analysis of variance (ANOVA) was conducted for seed yield and other quantitative traits. Mean comparisons among genotypes were performed using the Least Significant Difference (LSD) method. Pearson correlation analysis was employed to assess the relationships among quantitative traits. Factor analysis, based on Pearson correlations, was carried out to identify the principal contributing factors. Additionally, simultaneous selection of genotypes based on agronomic traits and yield was performed using the SIIG (Selection Index of the Ideal Genotype) method. In this index, maximum values were considered ideal for traits such as flowering duration, number of lateral branches, plant height, number of pods per plant, number of seeds per pod, thousand-seed weight, and seed yield, while minimum values were preferred for days to flowering initiation, days to end flowering, and days to maturity. Statistical analyses were conducted using XLSTAT and SPSS software packages.
Results: The combined analysis of variance revealed that the effect of genotype was significant for all evaluated traits. Evaluation of the quantitative traits exhibited seed yield, number of branches per plant, number of seeds per pod, and flowering duration (number of days) as the highest coefficients of variation, with values of 10.9%, 10.1%, 9.8%, and 6.7%, respectively. Mean comparison of seed yield detected lines 9, 10, and 7, with average yields of 3137, 3105, and 3096 kg ha-1, as the top three promising lines, outperforming the check cultivars. The check varieties RGS003 (line 12) and Dalgan (line 11) followed with average yields of 2857 and 2806 kg/ha, respectively. Furthermore, lines 9 and 10 not only exhibited high yield performance but also demonstrated desirable earliness, with no significant difference in maturity compared to the very early-maturing check cultivar Safar (line 13). Correlation analysis among quantitative traits showed that seed yield had a significant positive correlation with plant height, number of seeds per pod, number of pods per plant, and number of branches per plant. Genotype ranking based on the Selection Index of the Ideal Genotype (SIIG) identified lines 10, 9, 7, 1, and 8 as the top-performing lines, showing the shortest distance from the ideal genotype and the greatest distance from the least desirable genotype. The genotype rankings obtained through the SIIG method were relatively consistent with those based on average seed yield, suggesting that the promising lines in this study possessed desirable agronomic traits in addition to high productivity. Evaluation of genetic gain using both ranking methods based on mean yield and the SIIG index indicated that while both approaches effectively identified high-yielding genotypes, the SIIG method showed greater genetic improvement in other quantitative traits such as plant height, number of branches per plant, number of pods per plant, and number of seeds per pod. Broad-sense heritability estimates revealed that seed yield, plant height, number of pods per plant, days to flowering initiation, and number of seeds per pod had the highest heritability values, respectively. Principal component analysis (PCA) showed that the first two components accounted for 69.83% of the total variation. Seed yield and its components including number of branches per plant, number of pods per plant, number of seeds per pod, and thousand-seed weight were most strongly associated with the first principal component. In contrast, plant height and phenological traits such as days to flowering initiation, days to end of flowering, and days to maturity were most correlated with the second component. PCA also revealed that the SIIG index was highly correlated with the first component, alongside traits such as seed yield, number of branches per plant, number of pods per plant, number of seeds per pod, and thousand-seed weight. The biplot based on the first two principal components confirmed that lines 9, 10, and 7 were the most promising genotypes in this study.
Conclusion: The significant differences observed in morphological and phenological traits, along with the presence of substantial variability in seed yield, number of branches per plant, number of seeds per pod, and flowering duration, highlight the potential of the evaluated promising rapeseed lines for future breeding programs. Genotype selection using the ideal genotype selection index (SIIG) demonstrated the utility of this multi-trait approach as an effective tool for identifying superior rapeseed lines. This method not only led to the identification of genotypes with high seed yield but also ensured the selection of genotypes with desirable agronomic characteristics.Overall, the results showed that the SIIG-based selection method was associated with considerable genetic improvement in both yield and other quantitative traits. The selected genotypes exhibited superior performance across multiple traits, indicating their suitability for further breeding and commercial cultivation. Ultimately, three promising lines—9 (SRL-98-17), 7 (SRL-98-15), and 10 (SRL-98-19)—were identified as the most adapted and high-performing genotypes under the environmental conditions of the Sistan region, due to their high yield potential, early maturity, and favorable agronomic traits.
Send email to the article author
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
