Show simple item record

dc.contributor.editorDel Río Celestino, Mercedes
dc.contributor.editorVilla, Rafael Font
dc.date.accessioned2023-06-23T09:40:12Z
dc.date.available2023-06-23T09:40:12Z
dc.date.issued2023
dc.identifierONIX_20230623_9783036575018_4
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/100772
dc.description.abstractNear-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.
dc.languageEnglish
dc.subject.classificationthema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: generalen_US
dc.subject.classificationthema EDItEUR::P Mathematics and Science::PS Biology, life sciencesen_US
dc.subject.otherhyperspectral
dc.subject.otherspatial-spectral features
dc.subject.otherclassification
dc.subject.otherprincipal component analysis
dc.subject.otherconvolutional neural network
dc.subject.othernear infrared spectra
dc.subject.otherchemometry
dc.subject.otherdry meat
dc.subject.otherartificial neural networks
dc.subject.otherorganoleptic parameters
dc.subject.otherprediction
dc.subject.otherprotected geographical indication distinguishing
dc.subject.othernear infrared
dc.subject.othervitamin C
dc.subject.otherellagic acid
dc.subject.otherwild harvest
dc.subject.otherKakadu plum
dc.subject.otherchemometrics
dc.subject.otherproximal sensing
dc.subject.otherprecision agriculture
dc.subject.otherE. coli
dc.subject.otherS. typhimurium
dc.subject.otherbiofilm
dc.subject.otherhyperspectral imaging
dc.subject.otherdiscriminant analysis
dc.subject.otherpesticide residues
dc.subject.otherspectroscopy
dc.subject.otherPLS
dc.subject.othersoft computing
dc.subject.otheralgorithm
dc.subject.otherNIRS
dc.subject.othermuscle
dc.subject.otherbovine
dc.subject.otherMUFA
dc.subject.otherPUFA
dc.subject.otherSFA
dc.subject.otherNIR spectrometer
dc.subject.otherintact potato
dc.subject.otherdry matter
dc.subject.otherreducing sugars
dc.subject.otherMPLS
dc.subject.otherpepper leaf
dc.subject.otherSPAD value
dc.subject.otherhyperspectral inversion
dc.subject.othercharacteristic waveband selection
dc.subject.otherNIR
dc.subject.othercalibration models
dc.subject.otherPLS-R
dc.subject.othervolatile phenols
dc.subject.otheraged wine spirit
dc.subject.otherbreast milk quality control
dc.subject.otherhandheld
dc.subject.otherolive oil
dc.subject.othernear-infrared spectroscopy
dc.subject.otherquality parameters
dc.subject.othermangetout
dc.subject.otherpea pod
dc.subject.othernear-infrared reflectance spectroscopy
dc.subject.othern/a
dc.titleUsing Vis-NIR Spectroscopy for Predicting Quality Compounds in Foods
dc.typebook
oapen.identifier.doi10.3390/books978-3-0365-7500-1
oapen.relation.isPublishedBy46cabcaa-dd94-4bfe-87b4-55023c1b36d0
oapen.relation.isbn9783036575018
oapen.relation.isbn9783036575001
oapen.pages236
oapen.place.publicationBasel


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record

https://creativecommons.org/licenses/by/4.0/
Except where otherwise noted, this item's license is described as https://creativecommons.org/licenses/by/4.0/