Research on infrared spectral characteristics and rapid detection technology of industrial hemp

Abstract

Objective: The aim of this study was to research the infrared spectroscopic features of various industrial hemp samples, establish a rapid infrared detection method for industrial hemp based on cannabidiol (CBD) content, and utilize infrared spectroscopy to differentiate industrial hemp flowers and leaves from different varieties and origins. Methods: Appropriate preprocessing was conducted on the industrial hemp samples based on their inherent characteristics. The samples were then scanned using the FTIR spectrometer, with careful subtraction of the background spectrum. A semi-quantitative rapid detection method for flowers and leaves using infrared spectroscopy was developed through partial least squares discriminant analysis. Data processing software was used to conduct principal component analysis and cluster analysis on the transmittance values of infrared characteristic absorption peaks, aiding in the identification and differentiation of samples from different varieties, origins, and harvest dates. Results: A semi-quantitative rapid detection method for industrial hemp flowers and leaves based on CBD content was successfully developed. Principal component analysis was able to clearly distinguish industrial hemp of different varieties and origins, effectively clustering samples of the same variety. This underscores the significant impact of mid-infrared spectroscopy in the identification and analysis of industrial hemp, providing an innovative approach to quickly identifying different hemp varieties.