Diverse local calibration approaches for chemometric predictive analysis of large near-infrared spectroscopy (NIRS) multi-product datasets

Yang Xueping, Yang Fuyu, Lesnoff Matthieu, Berzaghi Paolo, Ferragina Alessandro. 2024. Diverse local calibration approaches for chemometric predictive analysis of large near-infrared spectroscopy (NIRS) multi-product datasets. Chemometrics and Intelligent Laboratory Systems, 251:105173, 10 p.

https://doi.org/10.1016/j.chemolab.2024.105173

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Résumé : This study aimed to assess the predictive accuracy of Near-Infrared Spectroscopy (NIRS) across a large multi-product library, employing novel local calibration methodologies. Three local strategies were examined: LOCAL Algorithm, Locally Weighted Regression predicted on k-nearest neighbor selection (kNN-LWPLSR), along with a newly proposed algorithm within this study called Hybrid Local. These strategies were applied to an extensive multi-product dataset. When compared with Global PLS models, the results exhibited significant reductions in RMSEP values for all local strategies. Particularly, the kNN-LWPLSR demonstrated proficient prediction for the constituents of ADF and DM. The newly proposed method [Hybrid Local] exhibits comparable performance to the LOCAL Algorithm; however, it notably reduces the prediction time by half compared to the latter, representing a significant advancement for the practical implementation of NIRS technology within industrial processing scenarios.

Mots-clés Agrovoc : spectroscopie infrarouge, modèle mathématique, technique de prévision, application des ordinateurs, méthode statistique, spectroscopie

Mots-clés complémentaires : chimiométrie

Mots-clés libres : Near infrared spectroscopy (NIRS), Chemometrics, Local calibration, Large multi-products dataset, LOCAL algorithm

Classification Agris : U30 - Méthodes de recherche
U10 - Informatique, mathématiques et statistiques

Champ stratégique Cirad : CTS 7 (2019-) - Hors champs stratégiques

Agences de financement hors UE : National Key Research and Development Program of China, China Scholarship Council

Projets sur financement : (CHN) SensorFint

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