PP20 Development of a methodology for the prediction of cannabinoid content in the plant Cannabis sativa by means of infrared spectroscopy combined with chemometry
DOI:
https://doi.org/10.3407/azjh7m93Keywords:
Near-infrared spectroscopy, partial least squares regression, cannabinoidsAbstract
Cannabis sativa L. is a plant with industrial and pharmacological applications due to its content of cannabinoids, such as THC, CBD and CBG. Increasing regulation demands fast and accurate analytical methods. This study evaluates near-infrared spectroscopy (NIRS) combined with chemometry as an alternative to high-resolution liquid chromatography (HPLC-DAD) for quantifying cannabinoids in inflorescences. PLS regression models were developed and validated using metrological metrics. The results show that NIRS is a robust, fast and non-destructive technique with potential to optimize cannabinoid analysis by reducing costs and time.
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