In Tanzania, field research stations play a crucial role in agricultural development and environmental management. The study employed DiD model to analyse pre-post intervention data from multiple research stations, accounting for potential confounders such as seasonal variations and regional differences. A significant increase of 15% in crop yields was observed post-intervention when compared to baseline conditions, with robust standard errors indicating a reliable trend. The DiD model provided a clear indication of efficiency gains attributable to the intervention at various stations across Tanzania. Further studies are recommended to validate these findings and explore scalability in different agricultural contexts. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.