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...
Format: | eBook |
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Language: | English |
Published: |
Basel
MDPI - Multidisciplinary Digital Publishing Institute
2023
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Subjects: | |
Online Access: | Open Access: DOAB: description of the publication Open Access: DOAB, download the publication |
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245 | 0 | 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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650 | 7 | |a Technology: general issues |2 bicssc | |
653 | |a 1H-NMR | ||
653 | |a absorption | ||
653 | |a antioxidant potential | ||
653 | |a biomes | ||
653 | |a brown rice flour adulteration | ||
653 | |a caprine milk | ||
653 | |a carbohydrates | ||
653 | |a chemical fingerprints | ||
653 | |a chemometrics | ||
653 | |a deep learning | ||
653 | |a dry matter | ||
653 | |a fermentation index | ||
653 | |a food analysis | ||
653 | |a food authenticity | ||
653 | |a food chemicals | ||
653 | |a Fritillaria thunbergii | ||
653 | |a fruits | ||
653 | |a FTIR | ||
653 | |a GC/Q-ToF analysis | ||
653 | |a heavy metals | ||
653 | |a hyperspectral imaging | ||
653 | |a laser-induced breakdown spectroscopy | ||
653 | |a LDA | ||
653 | |a long short-term memory (LSTM) | ||
653 | |a machine learning | ||
653 | |a mass spectrometry analysis | ||
653 | |a meliponine honey | ||
653 | |a mid-infrared | ||
653 | |a milk absorbance spectra | ||
653 | |a mineral profile | ||
653 | |a moisture adjustment | ||
653 | |a multivariate analysis | ||
653 | |a n/a | ||
653 | |a non-destructive detection | ||
653 | |a optical properties | ||
653 | |a PCA | ||
653 | |a pesticide residue | ||
653 | |a physicochemical properties | ||
653 | |a protein content | ||
653 | |a quality evaluation | ||
653 | |a red pepper powder | ||
653 | |a reduced scattering | ||
653 | |a Salvia spp. | ||
653 | |a sources of variation | ||
653 | |a spatial frequency domain imaging (SFDI) | ||
653 | |a spectroscopy techniques | ||
653 | |a table grape | ||
653 | |a Theobroma cacao L. | ||
653 | |a time-resolved spectra | ||
653 | |a variable selection | ||
653 | |a variance components | ||
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856 | 4 | 0 | |u https://mdpi.com/books/pdfview/book/8098 |7 0 |z Open Access: DOAB, download the publication |