Development of Crop Yield Estimation Model using Soil and Environmental Parameters
Abstract
Crop yield is affected by various soil and environmental parameters and can vary significantly. Therefore, a crop yield estimation model which can predict pre-harvest yield is required for food security. The study is conducted on tea forms operating under National Tea Research Institute, Pakistan. The data is recorded on monthly basis for ten years period. The parameters collected are minimum and maximum temperature, humidity, rainfall, PH level of the soil, usage of pesticide and labor expertise. The design of model incorporated all of these parameters and identified the parameters which are most crucial for yield predictions. Feature transformation is performed to obtain better performing model. The designed model is based on an ensemble of neural networks and provided an R-squared of 0.9461 and RMSE of 0.1204 indicating the usability of the proposed model in yield forecasting based on surface and environmental parameters.
Keywords
Cite
@article{arxiv.2102.05755,
title = {Development of Crop Yield Estimation Model using Soil and Environmental Parameters},
author = {Nisar Ahmed and Hafiz Muhammad Shahzad Asif and Gulshan Saleem and Muhammad Usman Younus},
journal= {arXiv preprint arXiv:2102.05755},
year = {2025}
}
Comments
crop yield forecasting, regression, data mining, artificial neural network, ensemble learning