RESUMO
In the evolving field of cannabis research, scholars are exploring innovative methods to quantify cannabinoids rapidly and non-destructively. This study evaluates the effectiveness of a hand-held near-infrared (NIR) device for quantifying total cannabidiol (total CBD), total delta-9-tetrahydrocannabinol (total THC), and total cannabigerol (total CBG) in whole cannabis inflorescences. Employing pre-processing techniques, including standard normal variate (SNV) and Savitzky-Golay (SG) smoothing, we aim to optimize the portable NIR technology for rapid and non-destructive cannabinoid analysis. A partial least-squares regression (PLSR) model was utilized to predict cannabinoid concentration based on NIR spectra. The results indicated that SNV pre-processing exhibited superior performance in predicting total CBD concentration, yielding the lowest root mean square error of prediction (RMSEP) of 2.228 and the highest coefficient of determination for prediction (R2P) of 0.792. The ratio of performance to deviation (RPD) for total CBD was highest (2.195) with SNV. In contrast, raw data exhibited the least accurate predictions for total THC, with an R2P of 0.812, an RPD of 2.306, and an RMSEP of 1.651. Notably, total CBG prediction showed unique characteristics, with raw data yielding the highest R2P of 0.806. SNV pre-processing emerges as a robust method for precise total CBD quantification, offering valuable insights into the optimization of a hand-held NIR device for the rapid and non-destructive analysis of cannabinoid in whole inflorescence samples. These findings contribute to ongoing efforts in developing portable and efficient technologies for cannabinoid analysis, addressing the increasing demand for quick and accurate assessment methods in cannabis cultivation, pharmaceuticals, and regulatory compliance.
RESUMO
Plastid metabolism is critical in both photoautotrophic and heterotrophic plant cells. In chloroplasts, fructose-1,6-bisphosphate aldolase (FBA) catalyses the formation of both fructose 1,6-bisphosphate and sedoheptulose 1,7-bisphosphate within the Calvin-Benson cycle. Three Arabidopsis genes, AtFBA1-AtFBA3, encode plastidial isoforms of FBA, but the contribution of each isoform is unknown. Phylogenetic analysis indicates that FBA1 and FBA2 derive from a recently duplicated gene, while FBA3 is a more ancient paralog. fba1 mutants are phenotypically indistinguishable from the wild type, while both fba2 and fba3 have reduced growth. We show that FBA2 is the major isoform in leaves, contributing most of the measurable activity. Partial redundancy with FBA1 allows both single mutants to survive, but combining both mutations is lethal, indicating a block of photoautotrophy. In contrast, FBA3 is expressed predominantly in heterotrophic tissues, especially the leaf and root vasculature, but not in the leaf mesophyll. We show that the loss of FBA3 affects plastidial glycolytic metabolism of the root, potentially limiting the biosynthesis of essential compounds such as amino acids. However, grafting experiments suggest that fba3 is dysfunctional in leaf phloem transport, and we suggest that a block in photoassimilate export from leaves causes the buildup of high carbohydrate concentrations and retarded growth.
