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Updated: Mar 31, 2026

O-cresol Concentration Online Measurement Based On Near Infrared Spectroscopy Via Partial Least Square Regression
Published on: November 8, 2019
Spectroscopy-driven authentication of agro-industrial products: A comprehensive review of NMR, FT-IR, NIR and
Juarez Vicente1, Volmir Kist2, Caciane Peinhopf Mega2
1Laboratório Multiusuário para Detecção de Fraudes, Agrotóxicos e Minerais (LABFAM-IFC), Instituto Federal Catarinense (IFC), SC 283 km 17 - Vila Fragosos, Concórdia/SC, 89703-720, Brazil.
Abstract:
Spectroscopic fingerprinting (1H/13C NMR, mid-infrared FT-IR, and near-infrared NIR) combined with multivariate chemometrics has matured into a core analytical paradigm for rapid screening, classification, and quantification of fraudulent and adulterated matrices across the agro-food chain. This review synthesizes advances (2005-2025) in instrumentation, spectral preprocessing, algorithmic modeling, validation strategies and data fusion, with particular emphasis on robustness, transferability and on-site deployment. We discuss matrix-specific challenges (oils, dairy, beverages, seeds, feeds, fertilizers), summarize performance metrics reported in the literature, and identify critical gaps (model generalizability, open-world detection, standardized reference libraries) that constrain regulatory uptake. Recent comparative and systematic reviews and domain-specific studies are used to underpin recommendations for best practice.
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