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Research Article Open access CC BY 4.0

Yield Predication by DSSAT Model of Wheat Crop: A Review

Devi Lal, Ram Niwas

International Journal of Environment and Climate Change · pp. 519–524 · Published 13 Feb 2024

10.9734/ijecc/2024/v14i23965

Abstract

The DSSAT model predicts crop productivity under different crop management scenarios and fluctuating climate circumstances, necessitating the identification of a crop cultivar's genetic coefficient. The precision with which various parameters are calibrated and validated is essential to the effective application of crop models. The model was calibrated using the data on irrigation and nitrogen's impact on wheat yield, and it was validated using the date of sowing. The closer estimation of crop growth time, grain yields, and biomass yields was demonstrated by the model findings. The percentage error discrepancy between the simulated and actual wheat variety grain yields was 8.70% to 10.98%, respectively. There is a substantial correlation with a higher R2 value between the simulated and observed grain yields and crop duration during both the calibration and validation processes.

DSSAT model wheat yield simulated validation

Cited by 3

A DSSAT Model Approach for Yield Optimization: A Case Study of Mae Na Rua, Phayao, Thailand

Pongsak Jindasee, Sawarin Lerk-U-Suke, Jirabhorn Chaiwongsai · 2024 Geoinformatics for Spatial-Infrastructure Development in Earth and Allied Sciences (GIS-IDEAS) · 2024

Crop modelling for impact assessment and identifying adaptation strategies under changing climate scenarios: a comprehensive review

Rahul Tripathi, Rajshri Rajlaxmi Mohapatra, Smruti Ranjan Sahu · Proceedings of the Indian National Science Academy · 2026

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