About this document
Detecting Pepper Fraud with Fusion Models by romi.borz is a document available to read on EtoBox.
This study aims to develop a classification method using machine learning that can detect fraudulent additions to black pepper without knowing the type of adulterant in advance. The researchers analyzed authentic black pepper samples and samples adulterated with various substances using visible-near infrared spectrophotometry and direct analysis in real-time mass spectrometry. They found that individually, the models could detect some but not all adulterants, but fusing one-class and two-class classificatio
- Author
- romi.borz
- Language
- EN