What question did this study set out to answer?

The aim is to develop an intelligent system that recommends suitable crops based on soil and environmental conditions.

April 17, 2026Open Access

Crop Sense AI: Data-Driven Crop Recommendation Using ML And Deep Learning

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Demonstrates a crop recommendation system using AI techniques, improving yields in agriculture.

The aim is to develop an intelligent system that recommends suitable crops based on soil and environmental conditions.
Implemented machine learning and deep learning algorithms including Decision Tree and Random Forest.
Analyzed agricultural parameters such as nitrogen, phosphorus, potassium, rainfall, and soil pH.
Trained predictive models using a publicly available agricultural dataset.
Evaluated model performance using accuracy, precision, recall, and F1-score.
Ensemble and deep learning models achieved high prediction accuracy for crop recommendations.
The system provides real-time crop suggestions based on user-inputted soil and environmental parameters.
Facilitates precision agriculture by improving crop yield and decision-making for farmers.

Harika et al. (2026) studied this question.

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April 17, 2026Open Access

View Full Paper

Ask AI

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Authors

Demonstrates a crop recommendation system using AI techniques, improving yields in agriculture.

The aim is to develop an intelligent system that recommends suitable crops based on soil and environmental conditions.
Implemented machine learning and deep learning algorithms including Decision Tree and Random Forest.
Analyzed agricultural parameters such as nitrogen, phosphorus, potassium, rainfall, and soil pH.
Trained predictive models using a publicly available agricultural dataset.
Evaluated model performance using accuracy, precision, recall, and F1-score.
Ensemble and deep learning models achieved high prediction accuracy for crop recommendations.
The system provides real-time crop suggestions based on user-inputted soil and environmental parameters.
Facilitates precision agriculture by improving crop yield and decision-making for farmers.

Harika et al. (2026) studied this question.

View Full Paper

Ask AI

Bookmark