Utilizing the CROPGRO Simulation Model to Optimize Management Practices for Achieving High Soybean Yields

Abstract

A study was conducted during the kharif (June–September) season of 2018 at G.B.P.U.A.&T., Pantnagar, Uttarakhand, India to calibrate and validate the CROPGRO-soybean model for Terai region and determine the optimal management practices for soybean variety PS1347. The experiment followed a Two Factorial Randomized Block Design, involving two fertilizer treatments with three sowing dates replicated thrice. The CROPGRO model was calibrated and validated using the field data of 2018 and 2017, respectively. The RMSE% between the observed and simulated values of different crop stages and yield indicators were between 3.24% and 14.22%. Subsequently, the crop yield for different management practices was also simulated. The model encompassed yield simulations for various management practices viz., six tillage methods, five fertilizer treatments, nine sowing dates, and six irrigation levels. To achieve error minimization, soybean yield was simulated for four consecutive years (2015–2018) under various management practices, and the data was averaged. The simulation results indicated that the optimal management practices for achieving the highest soybean yield include sowing the seeds on the 20^th June after implementing a tillage regimen involving three ploughings and two harrowing operations and further nourishing the crop with fertilizer dose of N:P:K:S::25:60:40:20 and applying 90 mm of irrigation. These findings will aid in optimizing management practices and developing sustainable and efficient approaches to achieve higher soybean yields with minimal inputs.