Prediction of Soil Total Nitrogen Through Vis–NIR Spectroscopy and Machine Learning: From Model Comparison to Explainability

Rapid and cost-effective estimation of soil total nitrogen (TN) is essential for soil fertility assessment and nutrient management. However, the performance of laboratory visible–near-infrared (Vis–NIR) models is shaped not only by preprocessing and modeling strategy but also by sample preparation a...

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Auteurs principaux:	Shengchang Huai, Qingyue Zhang, Yuwen Jin, Shenzhong Tian, Yueming Chen, Xilin Guan, Tao Sun, Shenqiang Lv, Zichao Zhao, Weijia Yu, Ran Li, Gilles Colinet, Changai Lu, Xinhao Gao
Format:	Artigo
Langue:	Inglês
Publié:	MDPI AG 2026-05-01
Collection:	Soil Systems
Sujets:	soil total nitrogen Vis–NIR particle size SHAP interpretability XGBoost
Accès en ligne:	https://www.mdpi.com/2571-8789/10/5/59
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