Developing Prediction Models Using a Handheld Near-Infrared Device to Assess the Drying Process and Storage of Cannabis Sativa

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Date

2024-05

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The Ohio State University

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Abstract

Drying is the most critical post-harvest operation of cannabis, as it impacts the safety and shelf-life of the product, as well as changes in secondary metabolites, including essential oils, cannabinoids, and sterols. Current methods for moisture and water activity analysis are destructive and time-consuming. Here, we report using a handheld near-infrared spectroscopy (NIRS) for rapid measurement of moisture content (MC) and water activity of hemp to assess the quality during postharvest operations. Hemp samples were placed in desiccators containing different saturated salts that gave relative humidity ranging from 14% to 80%. After 2 weeks of incubation, the NIR spectra of hemp samples were measured by using a handheld NIRS device. The moisture content and water activity were determined by reference methods. Moisture isotherms showed a sigmoidal relationship with a critical aw of 0.38 and a monolayer value of 8.4% db. Partial Least Squares Regression (PLSR) showed excellent predictive models for moisture (SEP 0.5%) and water activity (SEP 0.02%). A handheld NIR device allowed rapid monitoring of the water content in hemp, providing a real-time tool for monitoring the quality of hemp during critical drying and curing operations.

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Third place, CFAES Research Forum and Poster Competition, April 9, 2024

Keywords

Isotherm, Cannabis, Water Activity, Near-Infared, Partial Least Squares Regression

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