PCA- and PLSR-Based Machine Learning Model for Prediction of Urea-N Content in Heterogeneous Soils Using Near-Infrared Spectroscopy

PCA- and PLSR-Based Machine Learning Model for Prediction of Urea-N Content in Heterogeneous Soils Using Near-Infrared Spectroscopy

Determining the soil’s nitrogen supply accurately and quickly is essential for effective agricultural management. This study explores the use of near-infrared (NIR) spectroscopy combined with spectral pre-processing techniques (such as Savitzky–Golay filtering) and partial least squares regression (...

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Bibliographic Details
Main Authors: Damiano Crescini, Gabriele Mascialino, Nicola Moggia, Giordano Piubeni, Mauro Serpelloni, Emilio Sardini
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Sensors
Subjects:
partial least squares regression (PLSR)
reflectance spectroscopy
sensors
various soil
data models and Urea-N
Online Access:https://www.mdpi.com/1424-8220/25/13/4176
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