AIMC Topic: Alcoholic Beverages

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Machine Learning-Enhanced Chemiresistive Sensors for Ultra-Sensitive Detection of Methanol Adulteration in Alcoholic Beverages.

ACS sensors Jun 11, 2025
Methanol poisoning poses significant health risks, particularly in less developed countries, where adulterated alcoholic beverages often lead to severe morbidity and mortality. Current diagnostic methods, such as gas-liquid chromatography and blood g...
Machine Learning Food Contamination Principal Component Analysis Methanol Graphite Alcoholic Beverages Limit of Detection Metal-Organic Frameworks
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A machine learning-based electronic nose system using numerous low-cost gas sensors for real-time alcoholic beverage classification.

Analytical methods : advancing methods and applications Aug 29, 2024
This study introduces numerous low-cost gas sensors and a real-time alcoholic beverage classification system based on machine learning. Dogs possess a superior sense of smell compared to humans due to having 30 times more olfactory receptors and thre...
Gases Electronic Nose Humans Dogs Machine Learning Odorants Animals Alcoholic Beverages
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Application of fuzzy algorithms in conjunction with H-NMR spectroscopy to differentiate alcoholic beverages.

Journal of the science of food and agriculture Jan 4, 2023
BACKGROUND: Recent statistics from the European Commission indicate that wine is one of the commodities most commonly subject to food fraud. In this context, the development of reliable classification models to differentiate alcoholic beverages requi...
Alcoholic Beverages Magnetic Resonance Spectroscopy Artificial Intelligence Wine
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Artificial intelligence-based approaches for traditional fermented alcoholic beverages' development: review and prospect.

Critical reviews in food science and nutrition Oct 31, 2022
Traditional fermented alcoholic beverages (TFABs) have gained widespread acceptance and enjoyed great popularity for centuries. COVID-19 pandemics lead to the surge in health demand for diet, thus TFABs once again attract increased focus for the heal...
Beverages Alcoholic Beverages Diet Big Data Artificial Intelligence
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Development and validation of the Alcoholic Beverage Identification Deep Learning Algorithm version 2 for quantifying alcohol exposure in electronic images.

Alcoholism, clinical and experimental research Oct 15, 2022
BACKGROUND: Seeing alcohol in media has been demonstrated to increase alcohol craving, impulsive decision-making, and hazardous drinking. Due to the exponential growth of (social) media use it is important to develop algorithms to quantify alcohol ex...
Deep Learning Electronics Alcoholic Beverages Beer Ethanol Beverages
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Marker-Independent Food Identification Enabled by Combing Machine Learning Algorithms with Comprehensive GC × GC/TOF-MS.

Molecules (Basel, Switzerland) Sep 22, 2022
Reliable methods are always greatly desired for the practice of food inspection. Currently, most food inspection techniques are mainly dependent on the identification of special components, which neglect the combination effects of different component...
Gas Chromatography-Mass Spectrometry Alcoholic Beverages Algorithms Support Vector Machine Machine Learning
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Identification of liquors from the same brand based on ultraviolet, near-infrared and fluorescence spectroscopy combined with chemometrics.

Food chemistry Sep 5, 2022
Accurate identification of various liquors from the same brand is of great significance for safeguarding the rights and interests of consumers and the market economy. Here, the spectral properties of liquors were studied based on ultraviolet (UV), ne...
Spectrometry, Fluorescence Discriminant Analysis Chemometrics Alcoholic Beverages Support Vector Machine
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How much are we exposed to alcohol in electronic media? Development of the Alcoholic Beverage Identification Deep Learning Algorithm (ABIDLA).

Drug and alcohol dependence Jan 9, 2020
BACKGROUND: Evidence demonstrates that seeing alcoholic beverages in electronic media increases alcohol initiation and frequent and excessive drinking, particularly among young people. To efficiently assess this exposure, the aim was to develop the A...
Humans Algorithms Reproducibility of Results Adult Female Alcohol Drinking Beer Mass Media Male Alcoholic Beverages Adolescent Wine Deep Learning Pattern Recognition, Automated
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Alcohol outlets and firearm violence: a place-based case-control study using satellite imagery and machine learning.

Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention Aug 29, 2019
INTRODUCTION: This article proposes a novel method for matching places based on visual similarity, using high-resolution satellite imagery and machine learning. This approach strengthens comparisons when the built environment is a potential confounde...
Violence Satellite Imagery Wounds, Gunshot Philadelphia Humans Firearms Machine Learning Case-Control Studies Alcoholic Beverages Residence Characteristics Urban Population Commerce
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Characterization of Key Aroma Compounds in a Commercial Rum and an Australian Red Wine by Means of a New Sensomics-Based Expert System (SEBES)-An Approach To Use Artificial Intelligence in Determining Food Odor Codes.

Journal of agricultural and food chemistry Mar 26, 2019
Although to date more than 10 000 volatile compounds have been characterized in foods, a literature survey has previously shown that only 226 aroma compounds, assigned as key food odorants (KFOs), have been identified to actively contribute to the ov...
Odorants Olfactometry Australia Smell Volatile Organic Compounds Expert Systems Flavoring Agents Chromatography, Gas Wine Humans Alcoholic Beverages Artificial Intelligence
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