Data-Driven and Mechanistic Soil Modeling for Precision Fertilization Management in Cotton

Data-Driven and Mechanistic Soil Modeling for Precision Fertilization Management in Cotton

This study introduces a novel methodology for predicting cotton yield by integrating machine learning (ML) with mechanistic soil modeling. This hybrid approach enhances yield prediction by combining data-driven ML techniques with soil process modeling. Using the developed yield model, yield curves f...

Full description

Saved in:
Bibliographic Details
Main Authors: Miltiadis Iatrou, Panagiotis Tziachris, Fotis Bilias, Panagiotis Kekelis, Christos Pavlakis, Aphrodite Theofilidou, Ioannis Papadopoulos, Georgios Strouthopoulos, Georgios Giannopoulos, Dimitrios Arampatzis, Evangelos Vergos, Christos Karydas, Dimitris Beslemes, Vassilis Aschonitis
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Nitrogen
Subjects:
cotton
nitrogen fertilization
machine learning
SHAP analysis
mechanistic modeling
Online Access:https://www.mdpi.com/2504-3129/6/2/29
Tags: Add Tag
No Tags, Be the first to tag this record!
Login for hold and recall information

Internet

https://www.mdpi.com/2504-3129/6/2/29

Similar Items