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Using Vis-NIR Spectroscopy for Predicting Quality Compounds in Foods

Using Vis-NIR Spectroscopy for Predicting Quality Compounds in Foods

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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., pharmaceuticals, petrochemical, textiles, cosmetics, medical applications, and chemicals such as polymers. The high level of interest in NIR spectroscopy among scientific and professional sectors demonstrates its relevance. We feel that the Special Issue's scope has facilitated the interchange of ideas and thereby aided in expanding the new development in this field of knowledge. Furthermore, we aimed to provide the readership with a comprehensive summary of present state-of-the-art NIR spectroscopy, current development trends, and future possibilities. We also believe that by doing so, we will be able to provide an accceptable opportunity for all contributors to make their results and methodologies more visible, as well as to highlight their recent achievements in their respective fields which have been made possible by the use of NIR spectroscopy. The Special Issue had a resoundingly enthusiastic response, with several submissions from academics and professional spectroscopists, resulting in the collection of 13 papers, including 1 exhaustive review paper. The articles submitted well represent the variety of the application field. These articles cover a wide range of topics related to NIR spectroscopy in a broad sense. The majority of the papers concentrate on applied qualitative and quantitative analysis in a variety of fields.

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Keywords

  • aged wine spirit
  • Algorithm
  • Artificial Neural Networks
  • Biofilm
  • Biology, Life Sciences
  • bovine
  • breast milk quality control
  • calibration models
  • characteristic waveband selection
  • chemometrics
  • chemometry
  • Classification
  • convolutional neural network
  • Discriminant analysis
  • dry matter
  • dry meat
  • E. coli
  • ellagic acid
  • handheld
  • hyperspectral
  • hyperspectral imaging
  • hyperspectral inversion
  • intact potato
  • Kakadu plum
  • mangetout
  • Mathematics & science
  • MPLS
  • MUFA
  • muscle
  • n/a
  • near infrared
  • near infrared spectra
  • near-infrared reflectance spectroscopy
  • near-infrared spectroscopy
  • NIR
  • NIR spectrometer
  • NIRS
  • Olive oil
  • organoleptic parameters
  • pea pod
  • pepper leaf
  • pesticide residues
  • PLS
  • PLS-R
  • precision agriculture
  • prediction
  • principal component analysis
  • protected geographical indication distinguishing
  • proximal sensing
  • PUFA
  • quality parameters
  • reducing sugars
  • Reference, information & interdisciplinary subjects
  • Research & information: general
  • S. Typhimurium
  • SFA
  • Soft computing
  • SPAD value
  • spatial-spectral features
  • spectroscopy
  • thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
  • thema EDItEUR::P Mathematics and Science::PS Biology, life sciences
  • Vitamin C
  • volatile phenols
  • wild harvest

Links

DOI: 10.3390/books978-3-0365-7500-1

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