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- W2284735529 abstract "Abstract Background Food quality, safety and authenticity are important issues for consumers, governments, as well as the food industry. In the last decade, several researchers have attempted to go beyond traditional microbiological, DNA-based and other methods using rapid techniques. This broad term involves a variety of sensors such as hyperspectral and multispectral imaging, vibrational spectroscopy, as well as biomimetic receptors. Scope and approach The resulting data acquired from the above-mentioned sensors require the application of various case-specific data analysis methods for the purpose of simple understanding and visualization of the acquired high-dimensional dataset, but also for classification and prediction purposes. Key findings and conclusions It is evident that rapid techniques coupled with data analysis methods have given promising results in several food products with various sensors. Additionally there are several applications, new sensors and new algorithms that remain to be explored and validated in the future." @default.
- W2284735529 created "2016-06-24" @default.
- W2284735529 creator A5040294637 @default.
- W2284735529 creator A5051737930 @default.
- W2284735529 creator A5055722083 @default.
- W2284735529 date "2016-04-01" @default.
- W2284735529 modified "2023-10-06" @default.
- W2284735529 title "Data mining derived from food analyses using non-invasive/non-destructive analytical techniques; determination of food authenticity, quality & safety in tandem with computer science disciplines" @default.
- W2284735529 cites W1183216373 @default.
- W2284735529 cites W1854305019 @default.
- W2284735529 cites W1966447169 @default.
- W2284735529 cites W1968698756 @default.
- W2284735529 cites W1968906418 @default.
- W2284735529 cites W1969605191 @default.
- W2284735529 cites W1973457817 @default.
- W2284735529 cites W1973852242 @default.
- W2284735529 cites W1974976639 @default.
- W2284735529 cites W1976251851 @default.
- W2284735529 cites W1978470156 @default.
- W2284735529 cites W1979193967 @default.
- W2284735529 cites W1980266419 @default.
- W2284735529 cites W1984059205 @default.
- W2284735529 cites W1989265625 @default.
- W2284735529 cites W1990118221 @default.
- W2284735529 cites W1994077427 @default.
- W2284735529 cites W1995283715 @default.
- W2284735529 cites W1996270074 @default.
- W2284735529 cites W2008322864 @default.
- W2284735529 cites W2015264016 @default.
- W2284735529 cites W2015714270 @default.
- W2284735529 cites W2016991841 @default.
- W2284735529 cites W2018244852 @default.
- W2284735529 cites W2018546263 @default.
- W2284735529 cites W2019115728 @default.
- W2284735529 cites W2020949188 @default.
- W2284735529 cites W2021754455 @default.
- W2284735529 cites W2022947185 @default.
- W2284735529 cites W2025014641 @default.
- W2284735529 cites W2025870492 @default.
- W2284735529 cites W2029575132 @default.
- W2284735529 cites W2031948875 @default.
- W2284735529 cites W2040149934 @default.
- W2284735529 cites W2041173503 @default.
- W2284735529 cites W2043219350 @default.
- W2284735529 cites W2044465660 @default.
- W2284735529 cites W2048378805 @default.
- W2284735529 cites W2049293347 @default.
- W2284735529 cites W2051216327 @default.
- W2284735529 cites W2051762037 @default.
- W2284735529 cites W2056457481 @default.
- W2284735529 cites W2060315146 @default.
- W2284735529 cites W2064816673 @default.
- W2284735529 cites W2069147120 @default.
- W2284735529 cites W2070723789 @default.
- W2284735529 cites W2071325350 @default.
- W2284735529 cites W2073503722 @default.
- W2284735529 cites W2075974331 @default.
- W2284735529 cites W2076810066 @default.
- W2284735529 cites W2083566418 @default.
- W2284735529 cites W2084668230 @default.
- W2284735529 cites W2084940723 @default.
- W2284735529 cites W2086144967 @default.
- W2284735529 cites W2088072521 @default.
- W2284735529 cites W2088347861 @default.
- W2284735529 cites W2089503626 @default.
- W2284735529 cites W2090416506 @default.
- W2284735529 cites W2090817050 @default.
- W2284735529 cites W2092193637 @default.
- W2284735529 cites W2097057782 @default.
- W2284735529 cites W2097526495 @default.
- W2284735529 cites W2103581881 @default.
- W2284735529 cites W2105762439 @default.
- W2284735529 cites W2111638058 @default.
- W2284735529 cites W2115254635 @default.
- W2284735529 cites W2125500141 @default.
- W2284735529 cites W2143711478 @default.
- W2284735529 cites W2151637704 @default.
- W2284735529 cites W2159834812 @default.
- W2284735529 cites W2162855759 @default.
- W2284735529 cites W2164583936 @default.
- W2284735529 cites W2165899560 @default.
- W2284735529 cites W2170505850 @default.
- W2284735529 cites W2332123535 @default.
- W2284735529 cites W3169738590 @default.
- W2284735529 cites W4239510810 @default.
- W2284735529 cites W574721709 @default.
- W2284735529 cites W60599040 @default.
- W2284735529 doi "https://doi.org/10.1016/j.tifs.2016.01.011" @default.
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