1- Sari Agricultural Sciences and Natural Resources University
Abstract: (4 Views)
Introduction and Objective: Flooding is one of the most significant abiotic stresses and a major limiting factor for agricultural production worldwide, adversely affecting the growth, development, and final yield of crop plants. Since Brassica genus like rapeseed (Brassica napus L.), is one of the most important sources of vegetable oil globally, identifying tolerant genotypes to flooding stress are essential. The development and enhancement of flooding-tolerant and stress-adapted rapeseed cultivars is important to sustainable increase in oil production. Accordingly, the present study was conducted to evaluate the response of Brassica genotypes under flooding stress using examining morphophysiological traits.
Materials and Methods: This study was conducted as a factorial experiment based on a randomized complete block design (RCBD) with three replications under greenhouse conditions during 2022–2023 growing season. The experiment examined three durations of flooding stress (0, 8, and 16 days) across 20 genotypes of Brassica spp. Flooding stress was applied at the four-leaf stage (BBCH=14). Subsequently, various morphological and physiological traits were measured, including stem and root lengths, stem diameter (SD), the number of green and yellow leaves (NGL and NYL), leaves, stems and roots fresh and dry weights (LFW, SFW, RFW, LDW, SDW and RDW), leaf area (LA), chlorophyll content (Chl), relative water content (RWC), and electrolyte leakage (EL). Additionally, analysis of variance (ANOVA), cluster analysis, and biplot (GGE) analysis were performed to evaluate the relationships among the morphological and physiological traits and to determine the relative importance of these traits in contributing to the performance of the studied genotypes.
Findings: The results of this study indicated that varying levels of flooding stress negatively affected the examined traits. Furthermore, different genotypes markedly varied under different flooding conditions. Cluster analysis categorized the genotypes into two clusters under control (non-flooded) and severe flooding conditions, and into three clusters under moderate flooding. Under non-flooded conditions, Group II, which included the genotypes Liberdona, Burgundy, and Barossa, demonstrated significantly better performance compared to Group I. Under moderate flooding, Group III, which also included Liberdona and Burgundy, exhibited the best performance. Under severe flooding, Group I, which comprised Burgundy and Liberdona, was identified as the superior group. Discriminant function analysis confirmed the accuracy of genotype grouping at all stress levels, achieving a 100% correct classification rate across all three levels. The Wilks' Lambda values for the first functions were statistically significant. Biplot analysis corroborated these findings, indicating that the Burgundy and Liberdona genotypes performed best across all three flooding levels and were closest to the ideal genotype. In contrast, the Topas and PGR genotypes consistently exhibited the weakest performance under all conditions. Mean comparisons of traits among groups in the control condition revealed significant differences in SD, LA, and DW. Under moderate flooding, the groups exhibited significant differences in LA, DW, and plant height (PH). In severe flooding conditions, SD, LA, and DW also contributed to significant differences among the groups. Correlation analysis revealed a significant positive correlation between LDW and SD, LA, and RDW. GGE biplot analysis under control conditions indicated that the first and second principal components explained 35.49% and 21.11% of the total variance, respectively, accounting for a cumulative total of 56.60% of the variation. Under moderate flooding, the two components explained 35.99% and 15.31% of the total variance, respectively, resulting in a cumulative total of 51.30%. Under severe flooding conditions, the first and second components accounted for 29.57% and 20.03% of the total variance, respectively, cumulatively explaining 49.78% of the total variation.
Conclusion: Based on the graphical GGE biplot analysis, LDW, RDW, and LA were identified as key morphophysiological indicators for selecting flooding-tolerant genotypes. Since both trait of yield and stability are essential for identifying superior genotypes across various environments, Burgundy and Liberdona were classified as tolerant genotypes, while Topas and PGR were identified as sensitive genotypes. In general, the mentioned genotypes will be recommended for further studies.
Materials and Methods: This study was conducted as a factorial experiment based on a randomized complete block design (RCBD) with three replications under greenhouse conditions during 2022–2023 growing season. The experiment examined three durations of flooding stress (0, 8, and 16 days) across 20 genotypes of Brassica spp. Flooding stress was applied at the four-leaf stage (BBCH=14). Subsequently, various morphological and physiological traits were measured, including stem and root lengths, stem diameter (SD), the number of green and yellow leaves (NGL and NYL), leaves, stems and roots fresh and dry weights (LFW, SFW, RFW, LDW, SDW and RDW), leaf area (LA), chlorophyll content (Chl), relative water content (RWC), and electrolyte leakage (EL). Additionally, analysis of variance (ANOVA), cluster analysis, and biplot (GGE) analysis were performed to evaluate the relationships among the morphological and physiological traits and to determine the relative importance of these traits in contributing to the performance of the studied genotypes.
Findings: The results of this study indicated that varying levels of flooding stress negatively affected the examined traits. Furthermore, different genotypes markedly varied under different flooding conditions. Cluster analysis categorized the genotypes into two clusters under control (non-flooded) and severe flooding conditions, and into three clusters under moderate flooding. Under non-flooded conditions, Group II, which included the genotypes Liberdona, Burgundy, and Barossa, demonstrated significantly better performance compared to Group I. Under moderate flooding, Group III, which also included Liberdona and Burgundy, exhibited the best performance. Under severe flooding, Group I, which comprised Burgundy and Liberdona, was identified as the superior group. Discriminant function analysis confirmed the accuracy of genotype grouping at all stress levels, achieving a 100% correct classification rate across all three levels. The Wilks' Lambda values for the first functions were statistically significant. Biplot analysis corroborated these findings, indicating that the Burgundy and Liberdona genotypes performed best across all three flooding levels and were closest to the ideal genotype. In contrast, the Topas and PGR genotypes consistently exhibited the weakest performance under all conditions. Mean comparisons of traits among groups in the control condition revealed significant differences in SD, LA, and DW. Under moderate flooding, the groups exhibited significant differences in LA, DW, and plant height (PH). In severe flooding conditions, SD, LA, and DW also contributed to significant differences among the groups. Correlation analysis revealed a significant positive correlation between LDW and SD, LA, and RDW. GGE biplot analysis under control conditions indicated that the first and second principal components explained 35.49% and 21.11% of the total variance, respectively, accounting for a cumulative total of 56.60% of the variation. Under moderate flooding, the two components explained 35.99% and 15.31% of the total variance, respectively, resulting in a cumulative total of 51.30%. Under severe flooding conditions, the first and second components accounted for 29.57% and 20.03% of the total variance, respectively, cumulatively explaining 49.78% of the total variation.
Conclusion: Based on the graphical GGE biplot analysis, LDW, RDW, and LA were identified as key morphophysiological indicators for selecting flooding-tolerant genotypes. Since both trait of yield and stability are essential for identifying superior genotypes across various environments, Burgundy and Liberdona were classified as tolerant genotypes, while Topas and PGR were identified as sensitive genotypes. In general, the mentioned genotypes will be recommended for further studies.
Keywords: Morphological and physiological traits, Brassica, Flooding Stress, Cluster analysis, GGE biplot
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