Researchers at the University of Adelaide, in collaboration with German tech company Compolytics, have developed a non-destructive leaf scanning method that can accurately predict the cannabinoid concentrations of cannabis plants.
The technique, known as fan leaf hyperspectral reflectance (FLHR), involves taking measurements across a plant’s canopy during early and late flowering periods and was found to reliably predict the final cannabinoid content in the mature plant.
“This measurement technique was overlayed with machine learning models trained on FLHR spectra and achieved high predictive accuracy that outperformed previous approaches,” says the University of Adelaide’s Dr Aaron Phillips.
“Importantly, our method utilises a hand-held, non-destructive hyperspectral device that enables rapid, in situ assessment of intact fan leaves without the need for sacrificial sampling or laboratory analysis.”
FLHR uses specialised lighting and detectors to capture subtle differences in light reflected from a plant’s leaves.
“Every chemical and structural feature in a leaf – such as pigments, water, and sugars – affects how it reflects light at different wavelengths,” says Dr Phillips, whose study was published in Industrial Crops & Products .
“By scanning across hundreds of narrow bands of light, we can record a detailed “spectral signature” for each leaf. These spectral signatures can then be used to develop mathematical models that can predict all sorts of plant traits.”
Dr Phillips says there are a range of industry applications for the technology.
“The capacity to predict cannabinoid profiles weeks before harvest has significant implications for cannabis production, enabling growers and breeders to enhance product quality, reduce costs, and ensure regulatory compliance,” says Dr Phillips.
“This is particularly important for industrial hemp growers, whose crops are subject to strict THC limits, and medicinal cannabis operations, which can now track and predict their yields.”
The development of an accurately predictive tool will also help growers avoid expensive regulatory penalties.
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