Geospatial Approach to Chickpea Yield Estimation: DSSAT-CROPGRO Calibration in Bundelkhand, Uttar Pradesh

Author: Kancheti Mrunalini, Sellaperumal Pazhanivelan, Narendra Kumar, Ragunath Kaliaperumal, S.P. Ramanathan, N. Sritharan and A. Ragul

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Abstract

In this research, the DSSAT model was utilized to simulate the growth, development, and yield of crops by effectively capturing the interactions between soil, plants, atmospheric conditions, and agricultural practices. Ensuring the timely and accurate prediction of crop yields proves pivotal for effective agricultural land management and the formulation of informed policy decisions. The study focused on estimating the spatial yield of chickpeas in seven districts of the Bundelkhand region in Uttar Pradesh using the DSSAT model. Genetic coefficients for different chickpea cultivars were evaluated during rabi, 2021–22 and were subsequently validated using crop data of 2022-23. The accuracy of the model's yield predictions was confirmed through comparison with observed yields obtained from crop cutting experiments conducted in farmers' fields. Statistical evaluations revealed excellent performance, with calibration yielding an R2, NRMSE, d and MAPE of 0.942, 0.107, 0.89, & 10.2 and with the validation phase also showed strong results, with values of 0.923, 0.149, 0.827, & 13.9 respectively. The versatility of the DSSAT model and its crop simulation capabilities have led to its widespread application across various contexts. With successful calibration and validation for chickpea yields at a spatial level, the model is now well-positioned for further geospatial applications in the realm of natural resource management.

Keywords

CCE, Chickpea, CROPGRO, DSSAT, Spatial yield

Conclusion

The effectiveness of the DSSAT model in predicting chickpea yield has been established, signifying its utility as a valuable predictive tool. The incorporation of the CROPGRO module allows for spatial yield simulations under varying conditions of soil, weather, and management practices, thereby enhancing chickpea production prospects. In essence, the model's proficiency in rainfed environments is evident as the study area Bundelkhand region of Uttar Pradesh falls under rainfed zone.

References

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How to cite this article

Kancheti Mrunalini, Sellaperumal Pazhanivelan, Narendra Kumar, Ragunath Kaliaperumal, S.P. Ramanathan, N. Sritharan and A. Ragul (2023). Geospatial Approach to Chickpea Yield Estimation: DSSAT-CROPGRO Calibration in Bundelkhand, Uttar Pradesh. Biological Forum – An International Journal, 15(8a): 203-208.