AI Medical Compendium Journal:
Food chemistry

Showing 91 to 100 of 202 articles

Recent advances in artificial intelligence towards the sustainable future of agri-food industry.

Food chemistry
Artificial intelligence has the potential to alter the agricultural and food processing industries, with significant ramifications for sustainability and global food security. The integration of artificial intelligence in agriculture has witnessed a ...

Deep learning-assisted flavonoid-based fluorescent sensor array for the nondestructive detection of meat freshness.

Food chemistry
Gas sensors containing indicators have been widely used in meat freshness testing. However, concerns about the toxicity of indicators have prevented their commercialization. Here, we prepared three fluorescent sensors by complexing each flavonoid (fi...

Rapid classification of coffee origin by combining mass spectrometry analysis of coffee aroma with deep learning.

Food chemistry
Mislabeling the geographical origin of coffee is a prevalent form of fraud. In this study, a rapid, nondestructive, and high-throughput method combining mass spectrometry (MS) analysis and intelligence algorithms to classify coffee origin was develop...

Deep learning-based characterization and redesign of major potato tuber storage protein.

Food chemistry
Potato is one of the most important crops worldwide, to feed a fast-growing population. In addition to providing energy, fiber, vitamins, and minerals, potato storage proteins are considered as one of the most valuable sources of non-animal proteins ...

High-throughput analysis of hazards in novel food based on the density functional theory and multimodal deep learning.

Food chemistry
The emergence of cultured meat presents the potential for personalized food additive manufacturing, offering a solution to address future food resource scarcity. Processing raw materials and products in synthetic food products poses challenges in ide...

Visible detection of chilled beef freshness using a paper-based colourimetric sensor array combining with deep learning algorithms.

Food chemistry
This study developed an innovative approach that combines a colourimetric sensor array (CSA) composed of twelve pH-response dyes with advanced algorithms, aiming to detect amine gases and assess the freshness of chilled beef. With the assistance of m...

Characterization of lamb shashliks with different roasting methods by intelligent sensory technologies and GC-MS to simulate human muti-sensation: Based on multimodal deep learning.

Food chemistry
To simulate the functions of olfaction, gustation, vision, and oral touch, intelligent sensory technologies have been developed. Headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC/MS) with electronic noses (E-noses...

Geographical traceability of soybean: An electronic nose coupled with an effective deep learning method.

Food chemistry
The quality of soybeans is correlated with their geographical origin. It is a common phenomenon to replace low-quality soybeans from substandard origins with superior ones. This paper proposes the adaptive convolutional kernel channel attention netwo...

Geographical discrimination of Asian red pepper powders using H NMR spectroscopy and deep learning-based convolution neural networks.

Food chemistry
This study investigated an innovative approach to discriminate the geographical origins of Asian red pepper powders by analyzing one-dimensional H NMR spectra through a deep learning-based convolution neural network (CNN). H NMR spectra were collecte...

Functionalized nanofibers mat prepared through thiol-ene "click" reaction as solid phase extraction adsorbent for simultaneous detection of florfenicol and paracetamol residues in milk.

Food chemistry
Due to the significant differences in physical and chemical properties of various veterinary drugs, sample pretreatment is still the bottleneck of simultaneous detection of multiple veterinary drug residues. In order to achieve quantitative determina...