AIMC Topic: Wine

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A rapid wine brand identification method based on the joint application of SERS and machine learning techniques.

Food chemistry
In this paper, an innovative approach is proposed to achieve no-preparation, rapid, and accurate identification of red wine brands by combining Surface-Enhanced Raman Scattering (SERS) spectroscopy with machine learning. SERS detects trace molecular ...

Wine discrimination based on multi-sensor fusion of GASF and Mel spectrogram features using an enhanced EfficientNet-B0 model.

Food chemistry
This study presents a novel multi-sensor fusion strategy for discriminating wines made from eight different raw materials using identical brewing processes. Aroma and taste signals were collected using a broad-spectrum electronic nose and noble metal...

Machine learning-assisted identification of core flavor compounds and prediction of core microorganisms in fermentation grains and pit mud during the fermentation process of strong-flavor Baijiu.

Food chemistry
The quality of strong-flavor Baijiu (SFB) is directly determined by key flavor compounds, which are influenced by microorganisms during fermentation. This study employed flavoromics and machine learning technologies to explore the relationship betwee...

Machine learning-assisted spectroscopic methods for detecting adulteration in Barrantes wine from Folla Redonda grapes.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
The present study explores the application of advanced machine learning algorithms combined with vis-NIRS and FTIR spectroscopy to detect and quantify adulteration in Barrantes wine, produced from the Folla Redonda grape, a variety exclusive to the G...

Uncorking white wine liking: Combining analytical chemistry and chemometrics with crowd-sourced data to predict quality ratings.

Food chemistry
Quality perception is a crucial aspect of wine research, particularly regarding consumer acceptance and quality impression. These assessments are challenging because consumers frequently incorporate extrinsic cues when evaluating hedonic quality. A u...

Rapid counting of Kazachstania humilis and Saccharomyces cerevisiae in sourdough by deep learning-based classifier.

Journal of microbiological methods
When maintaining sourdough through backslopping, bakers must ensure that the yeast mycobiota remains stable. By introducing two-staged incubation temperatures for cultivation, we found that the colonies of Kazachstania humilis and Saccharomyces cerev...

Fruit wines classification enabled by combing machine learning with comprehensive volatiles profiles of GC-TOF/MS and GC-IMS.

Food research international (Ottawa, Ont.)
Fruit wines, produced through the fermentation of various fruits, are well-documented for their distinct flavor profiles. Intelligent sensory analysis, GC-TOF/MS and GC-IMS were used for the analysis of the volatile profile of eight types of fruit wi...

Real-Time Classification of Ochratoxin a Contamination in Grapes Using AI-Enhanced IoT.

Sensors (Basel, Switzerland)
Ochratoxin A (OTA) contamination presents significant risks in viticulture, affecting the safety and quality of wine and grape-derived products. This study introduces a groundbreaking method for early detection and management of OTA, leveraging envir...

Stacked long and short-term memory (SLSTM) - assisted terahertz spectroscopy combined with permutation importance for rapid red wine varietal identification.

Talanta
Mislabeling of low-value red wines as high-value ones is common, which seriously undermines consumer rights and interests. However, traditional sensory and chemical analysis methods have limitations, which highlights the need for novel detection tech...

Machine learning assisted multi-signal nanozyme sensor array for the antioxidant phenolic compounds intelligent recognition.

Food chemistry
Identifying antioxidant phenolic compounds (APs) in food plays a crucial role in understanding their biological functions and associated health benefits. Here, a bifunctional Cu-1,3,5-benzenetricarboxylic acid (Cu-BTC) nanozyme was successfully prepa...