Optimizing Sowing Date, Irrigation Scheduling and Nitrogen Management for Wheat (Triticum aestivum L.): Two-Year Pooled Analysis and DSSAT-CERES-Wheat Model Evaluation for the Vindhyan Zone
Year: 2026
Type: preprint
Abstract: Sowing time, irrigation scheduling and nitrogen management jointly determine wheat productivity, and crop simulation models such as DSSAT-CERES-Wheat offer a route to extend two-year field results to a wider range of conditions. This study evaluated the pooled (2019-20 and 2020-21) effect of these three factors on growth, yield and profitability of wheat, and calibrated/validated the DSSAT-CERES-Wheat model (v4.7) for the Vindhyan agro-climatic zone. A split-plot field trial with three replications was conducted over two rabi seasons at the Crop Research Farm, SHUATS, Prayagraj, with two sowing dates (20 November, 20 December), three irrigation schedules and three nitrogen levels (80, 120, 160 kg N ha⁻¹) as eighteen treatment combinations. First-year data were used to calibrate genetic coefficients of cultivar HD 2967, and second-year data were used for independent validation of phenology, leaf area index (LAI) and yield. On a pooled basis, 20 November sowing, four irrigations (CRI, tillering, booting, milking) and 160 kg N ha⁻¹ produced the tallest plants, highest dry matter, LAI and yield attributes, with grain yield of 3.44 and biological yield of 7.94 t ha⁻¹ and the highest net return and benefit-cost ratio, the D₁I₃N₃ combination giving the best economics. The calibrated model predicted days to anthesis and maturity within 1–2 days of observation (nRMSE < 1.5%, d > 0.98) and reproduced LAI closely (nRMSE 7.8% calibration, 6.2% validation; d > 0.95). Grain and biological yields were simulated with r² of 0.92–0.96 in calibration and 0.93–0.95 in validation, confirming good-to-excellent model accuracy. Timely sowing, adequate irrigation and higher nitrogen consistently improved wheat productivity and profitability, and the DSSAT-CERES-Wheat model, once calibrated for cultivar HD 2967, reliably reproduced phenology, LAI and grain yield for the Vindhyan Zone, supporting its use as a decision-support tool for regional wheat management.
Source: Research Square
Author: Wasim Khan
Institution: Sam Higginbottom Institute of Agriculture
Language: English
Subfield: Soil Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: green
OpenAlex ID: W7204206604