A novel handheld FT-NIR spectroscopic approach for real-time screening of major cannabinoids content in hemp

A novel approach for rapid (15s) detection and quantification of predominant cannabinoids in hemp was developed using Fourier-transformed near-infrared spectroscopy (FT-NIR), enabling real-time and field-based applications. Hemp samples (n = 91) were obtained from certified online vendors, the OARDC Weed Lab, and a local Ohio farm. Reference data of major cannabinoids content were determined by uHPLC-MS/MS. Spectral data were collected by a miniaturized, battery-operated FT-NIR instrument, and combined with the reference data to generate partial least squares regression (PLSR) models. uHPLC-MS/MS analysis showed two samples had over 0.36% of Δ9-tetrahydrocannabinol (Δ9-THC), and 64% (32 out of 50) of online-bought hemp samples were not in compliance with their total cannabidiol (CBD) content declaration. PLSR prediction models showed excellent correlation (Rpre = 0.91–0.95) and a low standard error of prediction (SEP = 0.02–0.61%). This method could be used as an alternative to traditional methods for in-situ assessment of hemp quality. [Display omitted] •A novel designed handheld FT-NIR sensor allowed for the rapid screening of cannabinoid content in hemp.•From 50 online-bought hemp samples, 32 samples were not in compliance with their total CBD content declaration.•A rotating sample stage was engineered in the novel sensor to enable spatial averaging over a variety of angles for heterogeneous plant samples while the spectral acquisition.•Alternative method to time-consuming traditional testing for in-situ assessment of hemp quality.