Using Vis-NIR Spectroscopy for Predicting Quality Compounds in Foods
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...
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| Формат: | Online |
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| Мова: | Англійська |
| Опубліковано: |
MDPI - Multidisciplinary Digital Publishing Institute
2023
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| Предмети: | |
| Онлайн доступ: | ONIX_20230623_9783036575018_4 |
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| _version_ | 1869527997527097344 |
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| collection | Directory of Open Access Books |
| description | 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. |
| format | Online |
| id | doab-20.500.12854ir-100772 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1007722024-03-28T03:33:51Z Using Vis-NIR Spectroscopy for Predicting Quality Compounds in Foods Del Río Celestino, Mercedes Villa, Rafael Font 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 thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science::PS Biology, life sciences 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. 2023-06-23T09:40:12Z 2023-06-23T09:40:12Z 2023 book ONIX_20230623_9783036575018_4 9783036575018 9783036575001 https://directory.doabooks.org/handle/20.500.12854/100772 eng image/jpeg Attribution 4.0 International https://mdpi.com/books/pdfview/book/7234 https://mdpi.com/books/pdfview/book/7234 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-7500-1 10.3390/books978-3-0365-7500-1 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036575018 9783036575001 236 Basel open access |
| spellingShingle | 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 thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science::PS Biology, life sciences Using Vis-NIR Spectroscopy for Predicting Quality Compounds in Foods |
| title | Using Vis-NIR Spectroscopy for Predicting Quality Compounds in Foods |
| title_full | Using Vis-NIR Spectroscopy for Predicting Quality Compounds in Foods |
| title_fullStr | Using Vis-NIR Spectroscopy for Predicting Quality Compounds in Foods |
| title_full_unstemmed | Using Vis-NIR Spectroscopy for Predicting Quality Compounds in Foods |
| title_short | Using Vis-NIR Spectroscopy for Predicting Quality Compounds in Foods |
| title_sort | using vis nir spectroscopy for predicting quality compounds in foods |
| topic | 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 thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science::PS Biology, life sciences |
| topic_facet | 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 thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science::PS Biology, life sciences |
| url | ONIX_20230623_9783036575018_4 |