Machine Learning

Gemmacert applies machine learning algorithms and statistical models to effectively decipher the complex composition and variable potency of cannabis. These mathematical tools enable the analysis of massive quantities of data which cannot be achieved by other traditional analytical means. GemmaCert’s global community of users benefit from the accumulated analytical insights derived from the world’s largest database of unique cannabis spectral images, each correlated with industry gold-standard HPLC results. GemmaCert’s proprietary library has been meticulously collected in its ISO 17025 certified lab since 2015 and continues to expand daily as cannabis spectral data is amassed, contributing to continual improvement to analytical capabilities and performance.

NIR Spectroscopy

Near-infrared spectroscopy (NIRS) is a proven, FDA-recognized analytical tool that uses the electromagnetic spectrum to assess the chemical makeup of any given sample. Crucially, NIRS can estimate chemical contents without damaging or altering flowers. Compared to traditional HPLC, NIRS testing has no need for chemical additives, ongoing overhead, or specialist training. It offers quick, accurate results in minutes.

Image Analysis

Cannabis flowers are heterogeneous by nature and typically have uneven trichome distribution, which makes batch analysis notoriously ineffective and can even hinder accurate potency readings for a single flower. GemmaCert utilizes advanced optics and digital image analysis to ensure optimal calibration for every measurement, delivering precise, rapid readings that give complete peace of mind.