New model shows which Indian districts respond most to nitrogen fertilizer
Crop Improvement
If you feed your vegetable beds or lawn by habit, this work shows that nitrogen drives most of the yield response in a major grain crop, and that some places gain far more from fertilizer than others.
Scientists trained a computer model on district-level rice records from Tamil Nadu, India. They first removed the effects of weather, watering, and location so they could see what fertilizer alone was doing. Nitrogen came out as the nutrient with the biggest effect on yield, and four districts (Theni, Dharmapuri, Thiruvarur, and Dindigul) showed the strongest response to fertilizer.
Key Findings
The Fertilizer-Focused Stacked Ensemble Model reached R2 of 0.9512, RMSE of 0.0406, MAE of 0.0287, and MAPE of 0.202 on Tamil Nadu district-level paddy yield data.
It outperformed existing ensemble models by combining LightGBM, XGBoost, and a multilayer perceptron with a Gradient Boosting meta-learner after removing climate, irrigation, and spatial effects.
SHAP analysis ranked nitrogen as the most important fertilizer component and flagged Theni, Dharmapuri, Thiruvarur, and Dindigul as the most fertilizer-sensitive districts.
chevron_right Technical Summary
Researchers built a machine learning model that predicts rice yields in Tamil Nadu, India, by isolating the effect of fertilizer from weather, irrigation, and location. It predicted yields accurately and showed nitrogen matters most, with a few districts responding especially strongly to fertilizer.
Abstract Preview
Original paper
Fertilizer-Focused Stacked Ensemble Model for Explainable Paddy Yield Prediction Using Context-Residualized Nutrient Sensitivity Learning
Objectives: To build an explainable model that predicts paddy yields based on the fertilizer application, removing the influence of the climatic, irrigation and spatial factors. Method: The study s...
open_in_new Read full abstractAbstract copyright held by the original publisher.
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