Implementation of XGBoost Models for Predicting CO<sub>2</sub> Emission and Specific Tractor Fuel Consumption

Implementation of XGBoost Models for Predicting CO<sub>2</sub> Emission and Specific Tractor Fuel Consumption

Tillage is one of the most energy-intensive operations in crop production, leading to high fuel consumption and the emission of harmful gases such as CO<sub>2</sub> and NO<sub>x</sub>. This study was conducted under real field conditions to explore how soil parameters influen...

Full description

Saved in:
Bibliographic Details
Main Authors: Nebojša Balać, Zoran Mileusnić, Aleksandra Dragičević, Mihailo Milanović, Andrija Rajković, Rajko Miodragović, Olivera Ećim-Đurić
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Agriculture
Subjects:
tractor exhausts emission
predictive soil tillage
VRA soil tillage
precision agriculture
machine learning
XGBoost model
Online Access:https://www.mdpi.com/2077-0472/15/11/1209
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items