The detection of cannabinoids in veterinary feeds by microNIR/chemometrics: a new analytical platform

Abstract

In this work, the capabilities of a novel miniaturized and portable microNIR spectrometer were investigated in order to propose a practical and intelligible test allowing the rapid and easy screening of cannabinoids in veterinary feeds. In order to develop a predictive model that could identify and simultaneously quantify the residual amounts of cannabinoids, specimens from popular veterinary feeds were considered and spiked with increasing amounts of cannabidiol (CBD), Δ9-tetrahydrocannabinol (THC), and cannabigerol (CBG). Partial least squares discriminant analysis (PLS-DA) and partial least squares regression (PLSr) were applied for the simultaneous detection and quantification of cannabinoids. The results demonstrated that the microNIR/chemometric platform could statistically identify the presence of CBD, THC and CBG in the simulated samples containing cannabinoids from 0.001 to 0.01%w/w, with the accuracy and sensitivity of the official reference methods actually proposed. The method was checked against false positive and true positive responses, and the results proved to be those required for confirmatory analyses, permitting to provide a fast and accurate method for monitoring cannabinoids in veterinary feeds.