A novel microscopic hyperspectral imaging detection method for quantitative powdered food adulteration assessment: A comparative study of CNN-RNN attention models.

Hyperspectral Imaging-Based Adulteration Detection of Edible Oil using Optimized Machine Learning Models

Oil adulteration poses a significant risk to public health and compromises food quality and authenticity, necessitating reliable and rapid detection methods. This study proposes a non-destructive method for detecting edible oil adulteration using hyperspectral imaging integrated with spectral feature optimization and m...

Visible–Near-Infrared Hyperspectral Imaging for Rapid Quantitative Detection and Visualization of Complex Multicomponent Adulteration in Beef

Advances in Machine Learning and Deep Learning Algorithm-Assisted Hyperspectral Imaging for Food Quality and Safety Assessment

Food quality and safety have become increasingly critical public health concerns, while traditional detection approaches are constrained by laborious sample preparation, lengthy analysis times, and destructive procedures. Hyperspectral imaging (HSI) has emerged as a rapid, non-destructive method that synergistically fu...

Non-destructive detection of mercury and salicylic acid in beauty cream using hyperspectral imaging and chemometrics for toxicological risk assessment

Adulteration of cosmetic products with toxicants remains a public-health concern, especially in markets where surveillance is uneven. We developed a non-destructive screening method for mercury and salicylic acid using hyperspectral imaging (400–1000 nm, Specim FX10 camera) coupled with machine-learning (ML) chemometri...

Detection of Frost‐Damaged Maize Kernels for Food Quality Screening Using Hyperspectral Imaging and 2D‐COS‐Assisted Deep Learning

ABSTRACT Maize is a crucial cereal crop susceptible to subzero temperature stress, which causes physicochemical damage to kernels and compromises their processing quality and food value. Traditional analytical methods are destructive, labor‐intensive, and unable to meet the requirements of rapid and high‐throughput qua...

Hyperspectral Imaging Combined With a Hybrid Deep Learning Framework for Simultaneous Monitoring of Multiple Quality Indicators in Frozen-thawed Beef