AIMC Topic: Wine
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Optimization process of coffee pulp wines combined with the artificial neural network and response surface methodology.
Scientific reports
May 14, 2025
Coffee pulp wine was made from coffee pulp. The level range of fermentation factors was determined by one-factor experiment. The significance factors affecting fermentation were screened by Plackett-Burman and steepest climbing experiments, which wer...
[Determination of flavor compounds in foxtail millet wine by gas chromatography-mass spectrometry coupled with headspace solid phase microextraction].
Se pu = Chinese journal of chromatography
Nov 8, 2017
To comprehensively understand flavor compounds and aroma characteristics of foxtail millet wine, extraction conditions were optimized with 85 μm polyacrylate (PA), 100 μm polydimethylsiloxane (PDMS), 75 μm carboxen (CAR)/PDMS and 50/30 μm divinylbenz...
A critical review on the applications of artificial neural networks in winemaking technology.
Critical reviews in food science and nutrition
Sep 2, 2017
Since their development in 1943, artificial neural networks were extended into applications in many fields. Last twenty years have brought their introduction into winery, where they were applied following four basic purposes: authenticity assurance s...
Fruit Wines Inhibitory Activity Against α-Glucosidase.
Current pharmaceutical biotechnology
Jan 1, 2017
BACKGROUND: Fruit wines are well known for their profound health-promoting properties including both enzyme activations and inhibitions. They may act preventive in regard to diabetes melitus and other chronic diseases.
[Study on the Recognition of Liquor Age of Gujing Based on Raman Spectra and Support Vector Regression].
Guang pu xue yu guang pu fen xi = Guang pu
Mar 1, 2016
It is an important and difficult research point to recognize the age of Chinese liquor rapidly and exactly in the field of liquor analyzing, which is also of great significance to the healthy development of the liquor industry and protection of the l...
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