AI Medical Compendium Journal:
Food research international (Ottawa, Ont.)

Showing 1 to 10 of 133 articles

A nanozyme colorimetric sensor combined with cloud-based machine learning algorithm-assisted WeChat mini program for intelligent identification of Chinese green tea.

Food research international (Ottawa, Ont.)
Green tea has become increasingly renowned among consumers by virtue of its exceptional flavor and high nutritional value. There is often a strong correlation between the varieties of green tea, quality and corresponding price. In this work, a simple...

Miniaturized spectroscopy and AI-driven probes in food industry automation.

Food research international (Ottawa, Ont.)
Spectroscopy is a rapidly advancing analytical technique, which is increasingly employed in the food industry as a non-destructive and rapid quality control tool. Based on spectral analysis and developed multivariate predictive models this technique ...

Effect of cooking and food serving robot design images and information on consumer liking, willingness to try food, and emotional responses.

Food research international (Ottawa, Ont.)
The utilization of robots in the food industry, including restaurants and cafés, has increased in recent years. This study investigated participants' responses to robots in the serving and cooking domains, which require varying degrees of consumer in...

Fusion of near-infrared and Raman spectroscopy with machine learning strategies: Non-destructive rapid assessment of freshness and TVB-N value prediction in Pacific white shrimp (Litopenaeus vannamei).

Food research international (Ottawa, Ont.)
Total volatile base nitrogen (TVB-N) is a key indicator of shrimp freshness. Nevertheless, traditional detection methods are cumbersome, time-intensive, and destructive. Here, a rapid and non-destructive method based on near-infrared (NIR) and Raman ...

Characterize and explore the dynamic changes in the volatility profiles of sauce-flavor baijiu during different rounds by GC-IMS, GC-MS and GC×GC-MS combined with machine learning.

Food research international (Ottawa, Ont.)
The production process of sauce-flavor baijiu (SFB) involves seven distillations, yielding base baijiu of 7 rounds (RSFB), which are then blended to form the final product. Therefore, the quality of the base baijiu is closely related to the quality o...

A machine learning multimodal profiling of Per- and Polyfluoroalkyls (PFAS) distribution across animal species organs via clustering and dimensionality reduction techniques.

Food research international (Ottawa, Ont.)
Per- and polyfluoroalkyl substances (PFAS) contamination in aquatic and terrestrial organisms poses significant environmental and health risks. This study quantified 15 PFAS compounds across various tissues (liver, kidney, gill, muscle, skin, lung, b...

Rapid identification of coffee species and origin using affordable multi-channel spectral sensor combined with machine learning.

Food research international (Ottawa, Ont.)
The rapid identification of coffee species and origin is critical for ensuring quality control and authenticity in the coffee industry. This study explores the use of an affordable multi-channel spectral sensor, AS7265X (410-940 nm), combined with ma...

Improvement of near-infrared spectroscopic assessment methods for the quality of Keemun black tea: Utilizing transfer learning.

Food research international (Ottawa, Ont.)
Keemun black tea, a renowned Chinese black tea, presents challenges in quality assessment due to variability in data across different years. To address this, we developed transfer learning algorithms using near-infrared spectral data. The qualitative...

Progress in machine learning-supported electronic nose and hyperspectral imaging technologies for food safety assessment: A review.

Food research international (Ottawa, Ont.)
The growing concern over food safety, driven by threats such as food contaminations and adulterations has prompted the adoption of advanced technologies like electronic nose (e-nose) and hyperspectral imaging (HSI), which are increasingly enhanced by...

Deep-learning-assisted chemo-responsive alizarin red S-based hydrogel sensor for the rapid freshness sensing of aquatic product.

Food research international (Ottawa, Ont.)
Rapid detection of freshness particularly in aquatic products demands efficient sensing strategies. Here, a novel deep-learning-assisted chemo-responsive alizarin red S-based hydrogel sensing platform was established for rapid freshness assay of aqua...