EFFECT OF SULFUR AND APPLICATION STAGES ON YIELD AND YIELD COMPONENTS OF SOYBEAN

Soybean is a vital crop for food and oil production, yet its yield and quality are often compromised by suboptimal nutrient management. This study aimed to address this issue by investigating the effects of sulfur and its time of application on soybean at the Research Farm of The University of Agriculture Peshawar during Kharif season of 2022. The experiment followed a randomized complete block design with three replicates. It aimed to evaluate the effects of four sulfur levels (0, 20, 40, and 60 kg ha-1) applied at three different growth stages (S1=sowing, V3=vegetative, and R1=flowering) using elemental sulfur as the sulfur source. The results showed significant impacts, particularly when sulfur was applied at a rate of 40 kg ha-1. This treatment extended days to flowering (56), improved yield components as well as biological (7917 kg ha-1) and seed yield (2882 kg ha-1). Sulfur at 40 kg ha-1 positively influenced oil content (18.95%), elevated oil yield (571 kg ha-1) and protein content (32.39%). In contrast supplementation of sulfur at 60 kg ha-1 extended days to maturity and improved the harvest index. Regarding application stages sulfur applied at V3 stage delayed flowering (56), increased leaves count and plant height. Application at R1 stage increased days to maturity (129), yield components, biological and seed yield (7992 and 2806 kg ha-1, respectively), oil content and yield (556 kg ha-1, 19.54%, respectively). Moreover, yield and yield components showed positive correlation with quality components of soybean. In last, economic analysis revealed high net benefit and BC ratio by applying 40 kg ha-1 of sulfur. In conclusion, applying 40 kg ha-1 of sulfur at the R1 stage is highly effective and economically feasible in enhancing soybean yield and quality under the agro-climatic conditions of Peshawar. Future research should explore the long-term effects of sulfur application on soil health and productivity, as well as the economic feasibility of these practices for large-scale adoption.