Quality characterization of tobacco flavor and tobacco leaf position identification based on homemade electronic nose.

ABSTRACT: A set of nine unique tobacco extract samples was analyzed using a self-developed electronic nose (E-nose) system, a commercial E-nose, and gas chromatography-mass spectrometry (GC-MS). The evaluation employed principal component analysis, statistical quality control, and soft independent modeling of class analogies (SIMCA). These multifaceted statistical methods scrutinized the collected data. Subsequently, a quality control model was devised to assess the stability of the sample quality. The results showed that the custom E-nose system could successfully distinguish between tobacco extracts with similar odors. After further training and the development of a quality control model for accepted tobacco extracts, it was possible to identify samples with normal and abnormal quality. To further

SUBMITTER: Li H 

PROVIDER: S-EPMC11336110 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature