Pet food brand discrimination via near-infrared spectroscopy combined with modified SPA-SI information enhancement
Abstract
-RF strategy proposed by us has the best model performance, with a total accuracy of 94.32% and a single accuracy of 88-100%, which is far better than the discrimination performance of Full-RF (total: 92.05%) and SPA-RF (total: 89.77%). The number of wavelengths was reduced from 183 to 9, a 95.08% decrease, providing a basis for developing spectral equipment for discrimination between low-cost pet food brands. This study not only achieved spectral discrimination of pet food brands for the first time but also provided a new method for pet food brand discrimination, expanded the application potential of spectral analysis technology in pet food detection, and laid the foundation for the development of low-cost, specialized spectral equipment.
Fields of Study & Subjects
Identification and Quantification in Food
Spectroscopy and Chemometric Analyses
Food Supply Chain Traceability
Publication details
- Journal / source
- Analytical Methods
- Publisher
- Royal Society of Chemistry (RSC)
- Volume
- 18
- Issue
- 18
- Pages
- 3765–3771
- Publication date
- 1 January 2026
- Language
- EN