In Pursuit of Optimal Quality: Cultivar-Specific Drying Approaches for Medicinal Cannabis.

A limited number of studies have examined how drying conditions affect the cannabinoid and terpene content in cannabis inflorescences. In the present study, we evaluated the potential of controlled atmosphere drying chambers for drying medicinal cannabis inflorescence. Controlled atmosphere drying chambers were found to reduce the drying and curing time by at least 60% compared to traditional drying methods, while preserving the volatile terpene content. On the other hand, inflorescences subjected to traditional drying were highly infested by Alternaria alternata and also revealed low infestation of Botrytis cinerea. In the high-THC chemovar ("240"), controlled N2 and atm drying conditions preserved THCA concentration as compared to the initial time point (t0). On the other hand, in the hybrid chemovar ("Gen12") all of the employed drying conditions preserved THCA and CBDA content. The optimal drying conditions for preserving monoterpenes and sesquiterpenes in both chemovars were C5O5 (5% CO2, 5% O2, and 90% N2) and pure N2, respectively. The results of this study suggest that each chemovar may require tailored drying conditions in order to preserve specific terpenes and cannabinoids. Controlled atmosphere drying chambers could offer a cost-effective, fast, and efficient drying method for preserving cannabinoids and terpenes during the drying process while reducing the risk of mold growth.

Improved Long-Term Preservation of Cannabis Inflorescence by Utilizing Integrated Pre-Harvest Hexanoic Acid Treatment and Optimal Post-Harvest Storage Conditions.

The effort to maintain cannabinoid and terpene levels in harvested medicinal cannabis inflorescence is crucial, as many studies demonstrated a significant concentration decrease in these compounds during the drying, curing, and storage steps. These stages are critical for the preparation and preservation of medicinal cannabis for end-use, and any decline in cannabinoid and terpene content could potentially reduce the therapeutic efficacy of the product. Consequently, in the present study, we determined the efficacy of pre-harvest hexanoic acid treatment alongside four months of post-harvest vacuum storage in prolonging the shelf life of high THCA cannabis inflorescence. Our findings indicate that hexanoic acid treatment led to elevated concentrations of certain cannabinoids and terpenes on the day of harvest and subsequent to the drying and curing processes. Furthermore, the combination of hexanoic acid treatment and vacuum storage yielded the longest shelf life and the highest cannabinoid and mono-terpene content as compared to all other groups studied. Specifically, the major cannabinoid's-(-)-Δ9-trans-tetrahydrocannabinolic acid (THCA)-concentration decreased by 4-23% during the four months of storage with the lowest reduction observed following hexanoic acid pre-harvest treatment and post-harvest vacuum storage. Hexanoic acid spray application displayed a more pronounced impact on mono-terpene preservation than storage under vacuum without hexanoic acid treatment. Conversely, sesqui-terpenes were observed to be less prone to degradation than mono-terpenes over an extended storage duration. In summation, appropriate pre-harvest treatment coupled with optimized storage conditions can significantly extend the shelf life of cannabis inflorescence and preserve high active compound concentration over an extended time period.

Hydroponic versus soil-based cultivation of sweet basil: impact on plants' susceptibility to downy mildew and heat stress, storability and total antioxidant capacity.

BACKGROUND: In recent years, hydroponically cultivated basil has gained extensive popularity over soil-based cultivation. Evidence for potential differences between both cultivation methods, in terms of resistance to biotic and abiotic stress factors, storage properties and shelf-life, is still lacking and the potential effect of cultivation method on the antioxidant capacity has not yet been fully explored. This study aimed to determine which of the two basil cultivation methods produces plants that are more resilient to downy mildew and external heat treatment and that exhibit better storage and shelf-life performance. RESULTS: Hydroponically grown basil was significantly more affected by browning than the soil-grown basil at the end of the storage and end of the shelf-life period. Under both cultivation methods, the extent of browning increased significantly between the end of the storage and end of the shelf-life period, by a factor of 1.4. Moreover, hydroponically grown plants were significantly more sensitive to heat treatment than soil-grown basil. However, the soil-grown basil exhibited significantly greater susceptibility to downy mildew than the hydroponically grown basil. At harvest, and at the end of the storage period, the antioxidant capacity of hydroponically cultivated basil was significantly greater than that of soil-grown basil. CONCLUSIONS: Hydroponically cultivated basil exhibited greater resistance to downy mildew, but less resilience to heat and browning during storage and a shelf-life period, resulting in poorer storage and shelf-life performance as compared to soil-cultivated basil. The greater total antioxidant capacity of the hydroponically cultivated basil seems to be the major cause for the observed phenomena. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Use of near-infrared spectroscopy for the classification of medicinal cannabis cultivars and the prediction of their cannabinoid and terpene contents.

Cannabis sativa L. is used to treat a wide variety of medical conditions, in light of its beneficial pharmacological properties of its cannabinoids and terpenes. At present, the quantitative chemical analysis of these active compounds is achieved through the use of laborious, expensive, and time-consuming technologies, such as high-pressure liquid-chromatography- photodiode arrays, mass spectrometer detectors (HPLC-PDA or MS), or gas chromatography-mass spectroscopy (GC-MS). Hence, we aimed to develop a simple, accurate, fast, and cheap technique for the quantification of major cannabinoids and terpenes using Fourier transform near infra-red spectroscopy (FT-NIRS). FT-NIRS was coupled with multivariate classification and regression models, namely partial least square-discriminant analysis (PLS-DA) and partial least squares regression (PLS-R) models. The PLS-DA model yielded an absolute major class separation (high-THC, high-CBD, hybrid, and high-CBG) and perfect class prediction. Using only three latent variables (LVs), the cross-validation and prediction model errors indicated a low probability of over-fitting the data. In addition, the PLS-DA model enabled the classification of chemovars with genetic-chemical similarities. The classification of high-THCA chemovars was more sensitive and more specific than the classifications of the remaining chemovars. The prediction of cannabinoid and terpene concentrations by PLS-R yielded 11 robust models with high predictive capabilities (R2CV and R2pred > 0.8, RPD >2.5 and RPIQ >3, RMSECV/RMSEC ratio <1.2) and additional 15 models whose performance was acceptable for initial screening purposes (R2CV > 0.7 and R2pred < 0.8, RPD >2 and RPIQ <3, 1.2 < RMSECV/RMSEC ratio <2). Our results confirm that there is sufficient information in the FT-NIRS to develop cannabinoid and terpene prediction models and major-cultivar classification models.

CLASS-II KNOX genes coordinate spatial and temporal ripening in tomato.

Fruits can be divided into dry and fleshy types. Dry fruits mature through senescence and fleshy fruits through ripening. Previous studies have indicated that partially common molecular networks could govern fruit maturation in these different fruit types. However, the nature of such networks remains obscure. CLASS-II KNOX genes were shown to regulate the senescence of the Arabidopsis (Arabidopsis thaliana) dry fruits, the siliques, but their roles in fleshy-fruit development are unknown. Here, we investigated the roles of the tomato (Solanum lycopersicum) CLASS-II KNOX (TKN-II) genes in fleshy fruit ripening using knockout alleles of individual genes and an artificial microRNA line (35S:amiR-TKN-II) simultaneously targeting all genes. 35S:amiR-TKN-II plants, as well as a subset of tkn-II single and double mutants, have smaller fruits. Strikingly, the 35S:amiR-TKN-II and tknII3 tknII7/+ fruits showed early ripening of the locular domain while their pericarp ripening was stalled. Further examination of the ripening marker-gene RIPENING INHIBITOR (RIN) expression and 35S:amiR-TKN-II rin-1 mutant fruits suggested that TKN-II genes arrest RIN activity at the locular domain and promote it in the pericarp. These findings imply that CLASS-II KNOX genes redundantly coordinate maturation in both dry and fleshy fruits. In tomato, these genes also control spatial patterns of fruit ripening, utilizing differential regulation of RIN activity at different fruit domains.

Multivariate classification of cannabis chemovars based on their terpene and cannabinoid profiles.

Cannabis is used to treat various medical conditions, and lines are commonly classified according to their total concentrations of Δ9-tetrahydrocannabinol (THC) and cannabidiol (CBD). Based on their ratio of total THC to total CBD, cannabis cultivars are commonly classified into high-THC, high-CBD, and hybrid classes. While cultivars from the same class have similar compositions of major cannabinoids, their levels of other cannabinoids and their terpene compositions may differ substantially. Therefore, a more comprehensive and accurate classification of medicinal cannabis cultivars, based on a large number of cannabinoids and terpenes is needed. For this purpose, three different chemometric-based classification models were constructed using three sets of chemical profiles. We examined those models to determine which provides the most accurate "chemovar" classification. This was done by analyzing profiles of cannabinoids, terpenes, and the combination of these substances using the partial least square-discriminant analysis multivariate (PLS-DA) technique. The chemical profiles were selected from the three major classes of medicinal cannabis that are most commonly prescribed to patients in Israel: high-THC, high-cannabigerol (CBG), and hybrid. We studied the correlations between cannabinoids and terpenes to identify major bio-indicators representing the plant's terpene and cannabinoid content. All three PLS-DA models provided highly accurate classifications, utilizing six to nine latent variables with an overall accuracy ranging from 2 to 11% CV. The PLS-DA model applied to the combined cannabinoid-and-terpene profile did the best job of differentiating between the chemovars in terms of misclassification error, sensitivity, specificity, and accuracy. The combined cannabinoid-and-terpene PLS-DA profile had cross-validation and prediction misclassification errors of 4% and 0%, respectively. This is the first study to demonstrate the highly accurate classification of samples of medicinal cannabis based on their cannabinoid and terpene profiles, as compared to cannabinoid profiles alone. Furthermore, our correlation analysis indicated that 11 cannabinoids and terpenes might serve as bio-indicators for 32 different active compounds. These findings suggest that the use of multivariate statistics could assist in breeding studies and serve as a tool for minimizing the mislabeling of cannabis inflorescences.

Optimization of sweet basil harvest time and cultivar characterization using near-infrared spectroscopy, liquid and gas chromatography, and chemometric statistical methods.

BACKGROUND: Terpene, eugenol and polyphenolic contents of basil are major determinants of quality, which is affected by genetics, weather, growing practices, pests and diseases. Here, we aimed to develop a simple predictive analytical method for determining the polyphenol, eugenol and terpene content of the leaves of major Israeli sweet basil cultivars grown hydroponically, as a function of harvest time, through the use of near-infrared (NIR) spectroscopy, liquid/gas chromatography, and chemometric methods. We also wanted to identify the harvest time associated with the highest terpene, eugenol and polyphenol content. RESULTS: Six different cultivars and four different harvest times were analyzed. Partial least square regression (PLS-R) analysis yielded an accurate, predictive model that explained more than 93% of the population variance for all of the analyzed compounds. The model yielded good/excellent prediction (R2 > 0.90, R2 cv and R2 pre > 0.80) and very good residual predictive deviation (RPD > 2) for all of the analyzed compounds. Concentrations of rosmarinic acid, eugenol and terpenes increased steadily over the first 3 weeks, peaking in the fourth week in most of the cultivars. Our PLS-discriminant analysis (PLS-DA) model provided accurate harvest classification and prediction as compared to cultivar classification. The sensitivity, specificity and accuracy of harvest classification were larger than 0.82 for all harvest time points, whereas the cultivar classification, resulted in sensitivity values lower than 0.8 in three cultivars. CONCLUSION: The PLS-R model provided good predictions of rosmarinic acid, eugenol and terpene content. Our NIR coupled with a PLS-DA demonstrated reasonable solution for harvest and cultivar classification. © 2021 Society of Chemical Industry.

Development of a point-of-care technology for bacterial identification in milk.

Rapid and sensitive methods for the detection of pathogenic microorganisms are required to monitor contamination in milk and assure public health. A colorimetric antibody-based stack pad system (biosensor) was developed to detect microbiological content of milk based on nitrocellulose membranes. This modification of the lateral flow immunoassay uses a multiple-membrane biosensor containing (from top to bottom): a sample pad, a conjugation pad (with anti-Escherichia coli antibodies conjugated to horseradish peroxidase), six Escherichia coli strain DH5α bacteria-blocking layers and an absorption pad with dry substrate. Different milk samples were tested, with and without DH5α bacteria. This multistep diagnostic assay was up to 1000-fold more sensitive than the standard laboratory ELISA. This is the first step in the development of a simple and portable device for milk-safety monitoring during all processing stages, with the aim of ensuring fresh and healthy milk for consumption.