New technique accurately predicts cannabis crop potency
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.
Credit: Aaron Phillips.
The technique, known as fan leaf hyperspectral reflectance (FLHR), involves taking measurements across a plant鈥檚 canopy during early and late flowering periods and was found to reliably predict the final cannabinoid content in the mature plant.
鈥淭his measurement technique was overlayed with machine learning models trained on FLHR spectra and achieved high predictive accuracy that outperformed previous approaches,鈥 says the University of Adelaide鈥檚 Dr Aaron Phillips.
鈥淚mportantly, 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.鈥
FLHR uses specialised lighting and detectors to capture subtle differences in light reflected from a plant鈥檚 leaves.
鈥淓very chemical and structural feature in a leaf 鈥 such as pigments, water, and sugars 鈥 affects how it reflects light at different wavelengths,鈥 says Dr Phillips, whose study was published in .
鈥淏y scanning across hundreds of narrow bands of light, we can record a detailed 鈥渟pectral signature鈥 for each leaf. These spectral signatures can then be used to develop mathematical models that can predict all sorts of plant traits.鈥
Dr Phillips says there are a range of industry applications for the technology.
鈥淭he 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,鈥 says Dr Phillips.
鈥淭his 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.鈥
The development of an accurately predictive tool will also help growers avoid expensive regulatory penalties.
鈥淭his tool can be used by growers to eliminate plants that violate THC regulations, potentially saving entire crops from destruction,鈥 Dr Phillips says.
鈥淕rowers can also use the measurements to inform their decisions in the field, avoiding investment in low-quality and therefore less profitable individuals or to speed up grow cycles or breeding procedures.鈥
Dr Phillips says future work on the technology will include more genotypes and test the earliest timepoint that FLHR profiles can accurately predict cannabinoid content of flowers at harvest.
鈥淲e want to know whether we can, for example, measure FLHR on four-week-old plants and obtain reliable estimates of cannabinoids at final harvest,鈥 he says.
鈥淲e were surprised that for some cannabinoids the early measurements in our study did a better job of predicting cannabinoids than the later measurements. So, we just don鈥檛 know how far back we can push the measurements.
鈥淭he current tech is quite bulky and cumbersome to use, so Compolytics are also working on the deployment of hand-held devices, similar in size and shape to a barcode scanner you might find at the supermarket.
鈥淲e would also like to test our approach with drones that can scan fields of hemp to find plants that exceed legal THC thresholds.鈥
Media contact:
Dr Aaron Phillips, Research Officer, School of Agriculture, Food and Wine, University of Adelaide. Phone: +61 0426 505 851, Email: aaron.phillips@adelaide.edu.au
Johnny von Einem, Senior Media Officer, University of Adelaide. Phone: +61 0481 688 436, Email: johnny.voneinem@adelaide.edu.au