Crop Models: Important Tools in Decision Support System to Manage Wheat Production under Vulnerable Environments

Aftab Wajid, Khalid Hussain, Ayesha Ilyas, Muhammad Habib-ur-Rahman, Qamar Shakil and Gerrit Hoogenboom
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Aftab Wajid: Agro-Climatology Laboratory, Department of Agronomy, University of Agriculture, Faisalabad 38040, Pakistan
Khalid Hussain: Agro-Climatology Laboratory, Department of Agronomy, University of Agriculture, Faisalabad 38040, Pakistan
Ayesha Ilyas: Agro-Climatology Laboratory, Department of Agronomy, University of Agriculture, Faisalabad 38040, Pakistan
Muhammad Habib-ur-Rahman: Department of Agronomy, MNS University of Agriculture, Multan 60000, Pakistan
Qamar Shakil: Fooder Research Sub-Station, AARI, Faisalabad 38850, Pakistan
Gerrit Hoogenboom: Institute of Food and Agricultural Sciences, University of Florida, Gainesville, FL 32611, USA

Agriculture, 2021, vol. 11, issue 11, 1-22

Abstract: Decision support systems are key for yield improvement in modern agriculture. Crop models are decision support tools for crop management to increase crop yield and reduce production risks. Decision Support System for Agrotechnology Transfer (DSSAT) and an Agricultural System simulator (APSIM), intercomparisons were done to evaluate their performance for wheat simulation. Two-year field experimental data were used for model parameterization. The first year was used for calibration and the second-year data were used for model evaluation and intercomparison. Calibrated models were then evaluated with 155 farmers’ fields surveyed for data in rice-wheat cropping systems. Both models simulated crop phenology, leaf area index (LAI), total dry matter and yield with high goodness of fit to the measured data during both years of evaluation. DSSAT better predicted yield compared to APSIM with a goodness of fit of 64% and 37% during evaluation of 155 farmers’ data. Comparison of individual farmer’s yields showed that the model simulated wheat yield with percent differences (PDs) of −25% to 17% and −26% to 40%, Root Mean Square Errors ( RMSE s) of 436 and 592 kg ha −1 with reasonable d-statistics of 0.87 and 0.72 for DSSAT and APSIM, respectively. Both models were used successfully as decision support system tools for crop improvement under vulnerable environments.

Keywords: model intercomparison; rice-wheat cropping system; model uncertainty; survey data; farmer yield; model evaluation (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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