Knowledge Bank

Hemp is a crop that has agricultural, economic, and pharmaceutic potential yet is still being researched. Hemp is known to produce over 100 phytocannabinoids, including cannabidiol (CBD) and Δ9-tetrahydrocannabinol (Δ9-THC). Hemp is a plant that must contain less than 0.3% THC w/w, per the 2018 Farm Bill. Current analytical methods of High-Performance Liquid Chromatography- tandem mass spectrometry (HPLC-MS/MS), which is a selective and sensitive method, but is cost inefficient, time-consuming, and requires complex analysis. Fourier Transform Near Infrared (FT-NIR) is a non-destructive, non-invasive method with the potential to be added to inline production settings. The analysis of FT-NIR is almost instantaneous compared to HPLC-MS/MS with a fraction of the cost. Hemp samples were scanned using a handheld FT-NIR scanner. Cannabinoids were extracted from hemp inflorescence and analyzed by HPLC-MS/MS. The two data matrices were correlated by Partial Least Squares Regression (PLSR) and a prediction model was generated. The prediction model allowed for the differentiation between drug-type (THC>0.3%) and fiber-type (THC<0.3%) hemp by their content of THCA (.27-.80%) and THC (.021-.056%), and the ability to quantify 4 different cannabinoids in a single measurement, including CBDA (7.7 – 20.7%). The prediction model yielded a small standard error of cross-validation and high correlation coefficient of cross-validation of Rcv>0.95. This experimentation shows the use of a small handheld scanner to provide a faster and cheaper analysis of a very heavily regulated crop with relatively no standardized methodology of analysis. This technology will benefit hemp growers and analysts of hemp material greatly.