foodphotonic

Foodphotonic is a term used to describe the application of photonic technologies to food science and industry. It encompasses optical sensing, imaging, and spectroscopy used to characterize ingredients, monitor processing, detect adulteration, and verify authenticity, with the aim of improving quality, safety, and efficiency along the supply chain.

The field draws on techniques from optics, spectroscopy, and imaging to obtain information about food without destructive testing. Common methods include near-infrared (NIR) and mid-infrared (MIR) spectroscopy for estimating composition such as moisture, fat, and sugar content; Raman spectroscopy for molecular fingerprinting; fluorescence for detecting contaminants; and imaging approaches like hyperspectral imaging that combine spatial and spectral data. Terahertz imaging is also explored for packaging inspection and certain safety assessments.

Applications span inline quality control in production environments, assessment of ripeness or freshness, moisture and fat content determination, detection of adulterants, and shelf-life or storage condition evaluation. In packaging, photonic sensors can monitor internal gas composition or temperature history, enabling intelligent packaging solutions. These technologies can enable rapid, non-destructive analyses and support process optimization, traceability, and regulatory compliance.

Advantages include speed, non-destructive testing, and potential for real-time monitoring and automation. Limitations involve instrument costs, the need for robust calibration models, sensitivity to sample heterogeneity and scattering, and varying regulatory acceptance across food categories. Ongoing research focuses on improving robustness, reducing costs, and integrating photonic systems with data analytics, machine learning, and scalable manufacturing processes to broaden practical adoption in diverse food sectors.