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Evaluation of soybean [Glycine max (L.) Merrill] genotypes for grain yield and associated agronomic traits under low and high phosphorus environments.

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Phosphorus is an important element for growth, development and seed formation in soybean and other plant species. This element is less available for plants. The capacity of absorbing phosphorus in the soil varies from one genotype to another, so that, the selection of phosphorus use efficient soybean lines is crucial in order to enhance the production. The main objectives of this study were: i) to identify soybean varieties that are tolerant to phosphorus deficiency ii) to determine the agronomic characters that contribute directly and indirectly to the yield improvement by correlation and path coefficient analysis and iii) to determine genotype x environment interaction effects and stability of soybean genotypes in respect to grain yield across low and optimum phosphorous environments. Thirty advanced soybean lines were evaluated in an alpha-lattice design, with two replications during 2016/2017cropping season under low phosphorus (0 kg/ha) and high phosphorus (100 kg/ha) levels in seven environments. Data were collected for fifteen phenotypic traits (both quantitative and qualitative) and analysed using SAS, breeding view (BV) in breeding management system (BMS), and Excel. Correlation and path coefficient analysis were done to determine the traits that contributed directly and indirectly to yield. Results for correlation and path coefficient analysis demonstrated strong and significant associations of yield with yield components. Harvest index was highly significant and positively correlated with grain yield but negatively with plant height, days to maturity and days to flowering. Path analysis revealed that under low P environment, total dry biomass, harvest index, number of pods could be used to screen soybean lines for low P, likewise in high P, harvest index, 100-seed weight, and plant height could be used in selection for high P use efficiency. Plant height, number of pods and nodule weight were identified as the traits that could be used for selection of the lines across all environments. The yield was high under high phosphorus (1551.20 kg/ha) than under low phosphorus environment (1154.30 kg/ha). The best yielding genotypes under high phosphorus were TGx2025-9E, TGx2025-6E and TGx2016-3E. Likewise, for low phosphorus the best genotypes were TGx2025-9E TGx2016-3E and TGx2023-3E. Across the two environments, genotypes TGx2025-9E and TGx2016-4E were the best. The genotypes were clustered into six groups with the maximum dissimilarity index of 0.6. In AMMI analysis, genotype TGx2025-9E, was the most stable and high yielding, suggesting the potential value of the variety as an alternative for soybean production across all environments. GGE biplot resulted in three mega-environments from the seven environments; Kabwe1, Lilongwe1, Lilongwe2 and Lusaka composed mega environment one, Gurue1 and Gurue2 formed mega environment two and Kabwe2 mega environment three. The best performing genotypes in these mega-environments were SCSAFARI and TGx2019-1E (mega-environment 1), TGx2025-9E (mega-environment 2) and TGx2025-6E (mega-environment 3). These findings highlighted the need for increased GxE studies to enhance efficiencies of breeding for broad adaptability in respect to responsiveness to low phosphorus.


Masters Degree. University of KwaZulu-Natal, Pietermaritzburg.