Advanced Spectroscopy Techniques in Food Analysis: Qualitative and Quantitative Chemometric Approaches
In today's global food market, ensuring both consumer satisfaction and the highest standards of safety is paramount. Food quality analysis covers chemical composition, physical properties, taste evaluation, and even traceability. Traditional methods are often slow, expensive, and eco-unfriendly...
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Format: | Electronic Book Chapter |
Language: | English |
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Basel
MDPI - Multidisciplinary Digital Publishing Institute
2023
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Online Access: | DOAB: download the publication DOAB: description of the publication |
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245 | 1 | 0 | |a Advanced Spectroscopy Techniques in Food Analysis: Qualitative and Quantitative Chemometric Approaches |
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520 | |a In today's global food market, ensuring both consumer satisfaction and the highest standards of safety is paramount. Food quality analysis covers chemical composition, physical properties, taste evaluation, and even traceability. Traditional methods are often slow, expensive, and eco-unfriendly due to their destructive nature. Here's the exciting part! Advanced spectroscopy techniques offer solutions. Imagine using non-destructive methods like X-rays, hyperspectral imaging, NMR, and Raman-quick, cost-effective, and eco-friendly, using less solvent. Now, let's demystify chemometrics-it extracts hidden info from spectra or image data, creating models for both qualitative and quantitative food analysis. This reprint presents recent advances in spectroscopy and chemometrics, focusing on their role in food analysis, quality evaluation, safety, and practical industry use. It's all about ensuring safe, delicious, and trustworthy food. Whether you're a curious consumer, food enthusiast, or industry insider, this reprint unveils cutting-edge methods for maintaining top food standards. With advanced spectroscopy and chemometrics, we're on track to boost consumer confidence in the food we love. | ||
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546 | |a English | ||
650 | 7 | |a Technology: general issues |2 bicssc | |
653 | |a hyperspectral imaging | ||
653 | |a pesticide residue | ||
653 | |a table grape | ||
653 | |a deep learning | ||
653 | |a non-destructive detection | ||
653 | |a Salvia spp. | ||
653 | |a GC/Q-ToF analysis | ||
653 | |a chemometrics | ||
653 | |a quality evaluation | ||
653 | |a chemical fingerprints | ||
653 | |a 1H-NMR | ||
653 | |a carbohydrates | ||
653 | |a fruits | ||
653 | |a PCA | ||
653 | |a LDA | ||
653 | |a laser-induced breakdown spectroscopy | ||
653 | |a brown rice flour adulteration | ||
653 | |a time-resolved spectra | ||
653 | |a machine learning | ||
653 | |a red pepper powder | ||
653 | |a multivariate analysis | ||
653 | |a moisture adjustment | ||
653 | |a Theobroma cacao L. | ||
653 | |a dry matter | ||
653 | |a fermentation index | ||
653 | |a protein content | ||
653 | |a meliponine honey | ||
653 | |a physicochemical properties | ||
653 | |a biomes | ||
653 | |a antioxidant potential | ||
653 | |a mineral profile | ||
653 | |a mass spectrometry analysis | ||
653 | |a spatial frequency domain imaging (SFDI) | ||
653 | |a optical properties | ||
653 | |a absorption | ||
653 | |a reduced scattering | ||
653 | |a long short-term memory (LSTM) | ||
653 | |a FTIR | ||
653 | |a mid-infrared | ||
653 | |a caprine milk | ||
653 | |a milk absorbance spectra | ||
653 | |a variance components | ||
653 | |a sources of variation | ||
653 | |a Fritillaria thunbergii | ||
653 | |a heavy metals | ||
653 | |a variable selection | ||
653 | |a food analysis | ||
653 | |a food authenticity | ||
653 | |a food chemicals | ||
653 | |a spectroscopy techniques | ||
653 | |a n/a | ||
856 | 4 | 0 | |a www.oapen.org |u https://mdpi.com/books/pdfview/book/8098 |7 0 |z DOAB: download the publication |
856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/128646 |7 0 |z DOAB: description of the publication |