AIMC Topic: Taste

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Artificial intelligence revolutionize food detection? Vision, olfaction and taste integrated with machine learning/deep learning in food detection.

Food chemistry
The rapid advancement of artificial intelligence (AI) is profoundly transforming the theoretical framework and technological paradigm of food detection. The study focuses on elucidating the underlying mechanisms of machine learning (ML)- and deep lea...

Machine learning-assisted aroma profile prediction in tomato puree based on flavoromics.

Food chemistry
Flavor serves as a key quality indicator in tomato puree (TP) processing; however, conventional methods often fall short in providing rapid and accurate assessments. To address this limitation, this study integrated flavoromics with machine learning ...

Hybrid plant-dairy cheese: Effects of lactic acid bacteria and plant proteins on composition, proteolysis, and flavor profile.

Food chemistry
In the search to improve the sustainability of the food supply chain, the market for plant-based cheese analogs is growing. However, sensory defects, particularly related to flavor, remain a challenge. Here we developed a hybrid plant-dairy cheese th...

Intelligent sensory technologies, NIR spectroscopy and chemometrics combined with machine learning based on multi-source data fusion for comprehensive evaluation of Sinapis Semen in different processing degrees.

Journal of pharmaceutical and biomedical analysis
Sinapis Semen, as a traditional Chinese medicine, has an unclear relationship between its stir-frying degrees and sensory characteristics. Therefore, it is essential to develop a multi-index evaluation method to classify the processing degree of Sina...

Virtual screening of salty peptides from enzymatic and fermented products of wheat gluten and its molecular mechanism of interaction with TMC4 receptor.

Food chemistry
The health risks associated with excessive sodium intake have prompted an exploration of natural salt substitutes. This study was oriented to explore the salty peptides from enzymatic and fermented products of wheat gluten (WG) with different degrees...

Discovering of novel umami-enhancing peptides from Flammulina filiformis: Combining virtual screening, machine learning, molecular dynamics simulations, and sensory evaluation.

Food chemistry
This research employed integrated machine learning and bioinformatics approaches to identify umami-enhancing peptides from Flammulina filiformis, elucidate their mechanisms of umami augmentation, and validate their efficacy through sensory evaluation...

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...

iBitter-Stack: A multi-representation ensemble learning model for accurate bitter peptide identification.

Journal of molecular biology
The identification of bitter peptides is crucial in various domains, including food science, drug discovery, and biochemical research. These peptides not only contribute to the undesirable taste of hydrolyzed proteins but also play key roles in physi...

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...

Umami-Transformer: A deep learning framework for high-precision prediction and experimental validation of umami peptides.

Food chemistry
In food field, both identification of umami peptides and their sensory evaluation are limited by low efficiency of traditional methods and subjectivity of human-based assessments. To overcome these issues, Umami-Transformer was developed by integrati...