Molecular characterization and fertilizer optimization in soybean to maximize productivity and minimize environmental impact

Climate change and deteriorating soil conditions have exacerbated water resource challenges, significantly limiting soybean yields. This situation necessitates the optimization of macronutrients, soil moisture, and drought indexing to enhance resilience, moving beyond molecular characterization of germplasm. The molecular characterization and correlation analysis of germplasm elucidates its genetic potential, variability, and diversity, while productivity depends on essential nutrients provided by soil or the application of NPK fertilizers. However, indiscriminate use of excessive NPK fertilizers, devoid of strategic optimization, compromises soil vitality and accelerates environmental damage. The central composite design (CCD) was used to examine soybean yield with four independent variables: moisture level from 0 to 200 mm and macronutrients (NPK) from 0 to 100kg per acre for each with RSM model and contour plot. A screening experiment utilizing PEG-6000 on forty-eight soybean accessions demonstrated significant correlations between growth indicators. SSR markers were employed to assess genetic diversity, with principal component analysis (PCA) accounting for up to 73.8% of the variation The RSM model predicts the optimal conditions, which include the application rates of nitrogen, phosphorus, and potassium (65, 40, and 20 kg/acre), while maintaining soil moisture levels between 100 and 150 mm. In the validation experiment, eleven out of forty-eight soybean accessions improved up to 70% more yield than control plants when the above optimum conditions were applied. The results of this study demonstrate that optimizing fertilizer application rates can significantly decrease emissions of greenhouse gases and alleviate soil and environmental pollution linked to agricultural practices.