AIMC Topic: Flavoring Agents
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Deep-Learning-Based Mixture Identification for Nuclear Magnetic Resonance Spectroscopy Applied to Plant Flavors.
Molecules (Basel, Switzerland)
Nov 1, 2023
Nuclear magnetic resonance (NMR) is a crucial technique for analyzing mixtures consisting of small molecules, providing non-destructive, fast, reproducible, and unbiased benefits. However, it is challenging to perform mixture identification because o...
Toxicity, genotoxicity, and carcinogenicity of 2-methylfuran in a 90-day comprehensive toxicity study in gpt delta rats.
Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association
Aug 13, 2022
2-Methylfuran (2-MF) exists naturally in foods and is used as a flavoring agent. Furan, the core structure of 2-MF, possesses hepatocarcinogenicity in rodents. Accumulation of toxicological information on furan derivatives is needed to elucidate thei...
Prediction of specialty coffee flavors based on near-infrared spectra using machine- and deep-learning methods.
Journal of the science of food and agriculture
Feb 18, 2021
BACKGROUND: Specialty coffee fascinates people with its bountiful flavors. Currently, flavor descriptions of specialty coffee beans are only offered by certified coffee cuppers. However, such professionals are rare, and the market demand is tremendou...
In vitro and in silico genetic toxicity screening of flavor compounds and other ingredients in tobacco products with emphasis on ENDS.
Journal of applied toxicology : JAT
Jul 13, 2020
Electronic nicotine delivery systems (ENDS) are regulated tobacco products and often contain flavor compounds. Given the concern of increased use and the appeal of ENDS by young people, evaluating the potential of flavors to induce DNA damage is impo...
Electronic Nicotine Delivery Systems
Consumer Product Safety
DNA Damage
Flow Cytometry
Tumor Suppressor Protein p53
Mutagenicity Tests
Histones
Flavoring Agents
Quantitative Structure-Activity Relationship
Cell Line
Phosphorylation
Models, Molecular
Risk Assessment
Mice
Rats
Biomarkers
Animals
Humans
Machine Learning
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...
Guava flavored whey-beverage processed by cold plasma: Physical characteristics, thermal behavior and microstructure.
Food research international (Ottawa, Ont.)
Oct 9, 2018
The present study aimed to compare the physicochemical (pH), physical (rheology parameters and particle size), microstructure (optical microscopy) and thermal properties (differential scanning calorimetry) of guava flavored whey-beverages submitted t...
Virtual screening of umami peptides during sufu ripening based on machine learning and molecular docking to umami receptor T1R1/T1R3.
Food chemistry
Sep 15, 2025
Umami peptides might significantly contribute to the taste of sufu. However, the inefficiencies of traditional identification methods had great limitations. This study explored a new approach for umami peptides characterization in sufu. Combining pep...
Machine learning models for terroir classification and blend similarity prediction: A proof-of-concept to enhance cocoa quality evaluation.
Food chemistry
Sep 15, 2025
Flavour is a key quality attribute of cocoa, essential for industry standards and consumer preferences. Automated methods for assessing flavour quality support industrial laboratories in achieving high sample throughput. Targeted and untargeted HS-SP...
Machine learning-assisted aroma profile prediction in Jiang-flavor baijiu.
Food chemistry
Jun 30, 2025
The complex flavor of Jiang-flavor Baijiu (JFB) arises from the interaction of hundreds of compounds at both physicochemical and sensory levels, making accurate perception challenging. Modern machine learning techniques offer precise and scientific a...
Machine learning-enhanced flavoromics: Identifying key aroma compounds and predicting sensory quality in sauce-flavor baijiu.
Food chemistry
May 30, 2025
The quality of Sauce-flavor baijiu hinges on sensory characteristics and key aroma compounds, which traditional methods struggle to evaluate accurately and effectively. This study explores the sensory characteristics and aroma compounds of Sauce-flav...
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