Crop recommendation in precision agriculture: a systematic literature review of methods, trends, and challenges
The review showed that ensemble learning-based approaches, particularly Random Forest and Extreme Gradient Boosting (XGBoost), are powerful for predictive performance on various agricultural datasets and shows the importance of scalable and explainable AI systems for real applications in agriculture.