Using Vis-NIR Spectroscopy for Predicting Quality Compounds in Foods

• Other Authors: Del Río Celestino, Mercedes (Editor), Villa, Rafael Font (Editor)
• Format: Electronic Book Chapter
• Language: English
• Published: Basel MDPI - Multidisciplinary Digital Publishing Institute 2023
• Subjects: Research & information: general; Biology, life sciences; hyperspectral; spatial-spectral features; classification; principal component analysis; convolutional neural network; near infrared spectra; chemometry; dry meat; artificial neural networks; organoleptic parameters; prediction; protected geographical indication distinguishing; near infrared; vitamin C; ellagic acid; wild harvest; Kakadu plum; chemometrics; proximal sensing; precision agriculture; E. coli; S. typhimurium; biofilm; hyperspectral imaging; discriminant analysis; pesticide residues; spectroscopy; PLS; soft computing; algorithm; NIRS; muscle; bovine; MUFA; PUFA; SFA; NIR spectrometer; intact potato; dry matter; reducing sugars; MPLS; pepper leaf; SPAD value; hyperspectral inversion; characteristic waveband selection; NIR; calibration models; PLS-R; volatile phenols; aged wine spirit; breast milk quality control; handheld; olive oil; near-infrared spectroscopy; quality parameters; mangetout; pea pod; near-infrared reflectance spectroscopy; n/a
• Online Access: DOAB: download the publication; DOAB: description of the publication

Near-Infrared reflectance spectroscopy (NIRS) has become one of the most attractive and used technique for analysis as it allows a fast and simultaneous qualitative and quantitative characterization of a wide variety of food samples. NIR spectroscopy is essential in various other fields, e.g., pharm...