Hyperspectral imaging (HSI) is a robust and nondestructive method that can detect foreign
particles such as microbial, chemical, and physical contamination in food. This review …

Routine, remote, and process analysis for foodstuffs is gaining attention and can provide
more confidence for the food supply chain. A new generation of rapid methods is emerging …

Pork batter quality significantly affects its product. Herein, this study explored the use of
Raman spectroscopy combined with deep learning algorithms for rapidly detecting pork …

The fat content of salmon is an essential indicator to evaluate its quality, and is related to its
commercial value. An attention residual convolutional neural network (CNN), namely …

Food allergies impose a significant health concern on the community. A small number of
certain food items can cause an allergic reaction within the human body. The symptoms can …

Spectroscopy coupled with deep learning is widely studied for powdered food materials
authentication, such as quality ranking and powder identification. However, the models need …

The quality of glutinous rice (GR) is susceptible to deterioration and losses due to biological
or environmental factors during storage. Traditional quality assessment techniques are often …

The market and aesthetic value of honey relies on the source of nectar collected by a
honeybee from a specific flower, and the authenticity of honey based on botanical origin is of …

Hyperspectral imaging (HSI) is one of the non-destructive quality assessment methods
providing both spatial and spectral information. HSI in food quality and safety can detect the …

Accurate assessment of isoflavone and starch content in Puerariae Thomsonii Radix (PTR)
is crucial for ensuring its quality. However, conventional measurement methods often suffer …