Potato Crop Yield Prediction Using Environmental and Soil Parameters

Authors

  • Yukti Kesharwani, Dr. Amrita Verma, Dr. Rajesh Tiwari

Keywords:

Machine Learning, Deep Learning, Potato Crop Growth, Atmospheric Parameters, Predictive Modelling

Abstract

Modern agricultural systems heavily depend on precise crop yield prediction to optimize farm management,boost productivity, and safeguard food security. Given the increasing unpredictability of climatic patternsand fluctuating soil conditions, traditional farming methods rooted in farmer intuition are no longeradequate for effective decision-making. Consequently, data-driven predictive modeling has emerged as a promising methodology

References

Shan, Y., Li, G., Su, L., Zhang, J., Wang, Q., Wu, J., Mu, W., & Sun, Y. (2022). Performance of AquaCrop model for maize growth

simulation under different soil conditioners in Shandong Coastal Area, China. Agronomy, 12(7), 1541.

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Published

2024-11-15

How to Cite

Yukti Kesharwani, Dr. Amrita Verma, Dr. Rajesh Tiwari. (2024). Potato Crop Yield Prediction Using Environmental and Soil Parameters . Journal of Computational Analysis and Applications (JoCAAA), 33(08), 6659–6667. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/3908

Issue

Section

Articles