Predicting oil palm yield using a comprehensive agronomy dataset and 17 machine learning and deep learning models

• Main Authors: Jamshidi, Ehsan Jolous, Yusup, Yusri, Hooy, Chee Wooi, Kamaruddin, Mohamad Anuar, Mat Hassan, Hasnuri, Muhammad, Syahidah Akmal, Mohd Shafri, Helmi Zulhaidi, Then, Kek Hoe, Norizan, Mohd Shahkhirat, Tan, Choon Chek
• Format: Article
• Language: English
• Published: Elsevier 2024
• Online Access: http://psasir.upm.edu.my/id/eprint/112419/1/112419.pdf; http://psasir.upm.edu.my/id/eprint/112419/; https://www.sciencedirect.com/science/article/pii/S1574954124001377
• Institution: Universiti Putra Malaysia

The rising global demand for oil palm emphasizes the importance of accurate oil palm yield predictions. This predictive capability is critical for effective crop management, supply chain optimization, and sustainable farming practices. However, the oil palm sector faces challenges in yield projectio...