@article {10.3844/ajbbsp.2025.46.55,
article_type = {journal},
title = {Near Infrared Spectroscopy Identification Method for Five Chemical Types of Cinnamomum camphora},
author = {Tu, Bailian and Zhang, Yueting and Zheng, Yongjie and Liu, Xinliang and Wu, Yanfang},
volume = {21},
number = {1},
year = {2025},
month = {Feb},
pages = {46-55},
doi = {10.3844/ajbbsp.2025.46.55},
url = {https://thescipub.com/abstract/ajbbsp.2025.46.55},
abstract = {To more quickly and accurately identify the five chemical types of Cinnamomum camphora, a desktop and portable near-infrared spectrometer was used to collect the near-infrared spectra of the leaves of the five chemical types of C. camphora. Combined with chemometric methods, the near-infrared spectra of different chemical types of C. camphora were discriminated and analyzed. Using a desktop near-infrared spectrometer in the 1000-2000 nm wavelength range, we applied dg2 and SNV preprocessing techniques, combined with the SIMCA algorithm, to build a model. This model successfully identified the three chemical types- Linalool, Borneol, and Camphor-with 100% accuracy. Only two samples of Cineol and Iso-nerolidol were not correctly identified. In the wavelength range of 1600-2400 nm, the portable near-infrared spectrometer was pretreated with S-G smoothing and SNV pretreatment. The optimal model was established after spectral matching and the sample recognition rate of the model was as high as 99.73%. A sample of Cineol and Iso-nerolidol was incorrectly identified. In terms of the external verification test, the recognition rates of the two models reached 99.20 and 98% respectively, showing high recognition ability. This study provides a robust and efficient method for the rapid, field-based identification of five different chemotypes of C. camphora, which could significantly benefit practical applications in the field.},
journal = {American Journal of Biochemistry and Biotechnology},
publisher = {Science Publications}
}