@article{lu_young_linder_whipker_suchoff_2022, title={Hyperspectral Imaging With Machine Learning to Differentiate Cultivars, Growth Stages, Flowers, and Leaves of Industrial Hemp (Cannabis sativa L.)}, volume={12}, ISSN={["1664-462X"]}, DOI={10.3389/fpls.2021.810113}, abstractNote={As an emerging cash crop, industrial hemp (Cannabis sativa L.) grown for cannabidiol (CBD) has spurred a surge of interest in the United States. Cultivar selection and harvest timing are important to produce CBD hemp profitably and avoid economic loss resulting from the tetrahydrocannabinol (THC) concentration in the crop exceeding regulatory limits. Hence there is a need for differentiating CBD hemp cultivars and growth stages to aid in cultivar and genotype selection and optimization of harvest timing. Current methods that rely on visual assessment of plant phenotypes and chemical procedures are limited because of its subjective and destructive nature. In this study, hyperspectral imaging was proposed as a novel, objective, and non-destructive method for differentiating hemp cultivars, growth stages as well as plant organs (leaves and flowers). Five cultivars of CBD hemp were grown greenhouse conditions and leaves and flowers were sampled at five growth stages 2–10 weeks in 2-week intervals after flower initiation and scanned by a benchtop hyperspectral imaging system in the spectral range of 400–1000 nm. The acquired images were subjected to image processing procedures to extract the spectra of hemp samples. The spectral profiles and scatter plots of principal component analysis of the spectral data revealed a certain degree of separation between hemp cultivars, growth stages, and plant organs. Machine learning based on regularized linear discriminant analysis achieved the accuracy of up to 99.6% in differentiating the five hemp cultivars. Plant organ and growth stage need to be factored into model development for hemp cultivar classification. The classification models achieved 100% accuracy in differentiating the five growth stages and two plant organs. This study demonstrates the effectiveness of hyperspectral imaging for differentiating cultivars, growth stages and plant organs of CBD hemp, which is a potentially useful tool for growers and breeders of CBD hemp.}, journal={FRONTIERS IN PLANT SCIENCE}, author={Lu, Yuzhen and Young, Sierra and Linder, Eric and Whipker, Brian and Suchoff, David}, year={2022}, month={Feb} }
 @article{lu_li_young_li_linder_suchoff_2022, title={Hyperspectral imaging with chemometrics for non-destructive determination of cannabinoids in floral and leaf materials of industrial hemp (Cannabis sativa L.)}, volume={202}, ISSN={["1872-7107"]}, DOI={10.1016/j.compag.2022.107387}, abstractNote={With the passage of the 2018 Farm Bill, industrial hemp (Cannabis sativa L.) has become a legal and economically promising crop commodity for U.S. farmers. There has been a surge of interest in growing industrial hemp for producing cannabinoids, such as cannabidiol (CBD), because of their medical potential. Quantitative determination of cannabinoids in harvested materials (primarily floral tissues) is critical for cannabinoid production and compliance testing. The concentrations of cannabinoids in hemp materials are conventionally determined using wet-chemistry chromatographic methods, which require destructive sampling, and are time-consuming, costly, and thus not suitable for on-site rapid testing. This study presents a novel effort to utilize hyperspectral imaging technology for non-destructive quantification of major cannabinoids, including CBD, THC (tetrahydrocannabinol), CBG (cannabigerol) and their acid forms in fresh floral and leaf materials of industrial hemp on a dry weight basis. Hyperspectral images in the wavelength range of 400–1000 nm were acquired from floral and leaf tissues immediately after harvest from a total of 100 industrial hemp plants of five cultivars at varied growth stages. Linear discriminant analysis showed hyperspectral imaging could identify CBD-rich/poor and THC-legal/illegal flower samples with accuracies of 99% and 97%, respectively. Quantitative models based on full-spectrum PLS (partial least squares) achieved prediction accuracies of RPD (ratio of prediction to deviation) = 2.5 (corresponding R2 = 0.84) for CBD and THC in floral tissues. Similar accuracies were obtained for their acid forms in flower samples. The predictions for CBG and its acid form in floral tissues and all six cannabinoids in leaf tissues were unsatisfactory with noticeably lower RPD values. Consistently improved accuracies were obtained by parsimonious PLS models based on a wavelength selection procedure for minimized variable collinearity. The best RPD values of approximately 2.6 (corresponding R2 = 0.85) were obtained for CBD and THC in floral materials. This study demonstrates the utility of hyperspectral imaging as a potential valuable tool for rapid quantification of cannabinoids in industrial hemp.}, journal={COMPUTERS AND ELECTRONICS IN AGRICULTURE}, author={Lu, Yuzhen and Li, Xu and Young, Sierra and Li, Xin and Linder, Eric and Suchoff, David}, year={2022}, month={Nov} }
 @article{linder_young_li_inoa_suchoff_2022, title={The Effect of Harvest Date on Temporal Cannabinoid and Biomass Production in the Floral Hemp (Cannabis sativa L.) Cultivars BaOx and Cherry Wine}, volume={8}, ISSN={["2311-7524"]}, url={https://doi.org/10.3390/horticulturae8100959}, DOI={10.3390/horticulturae8100959}, abstractNote={The objectives of this study were to model the temporal accumulation of cannabidiol (CBD) and tetrahydrocannabinol (THC) in field-grown floral hemp in North Carolina and establish harvest timing recommendations to minimize non-compliant crop production. Field trials were conducted in 2020 and 2021 with BaOx and Cherry Wine cultivars. Harvest events started two weeks after floral initiation and occurred every two weeks for 12 weeks. Per-plant threshed biomass accumulation exhibited a linear plateau trend. The best fit model for temporal accumulation of THC was a beta growth curve. As harvest date was delayed, total THC concentrations increased until concentrations reached their maximum, then decreased as plants approached senescence. Logistic regression was the best fit model for temporal accumulation of CBD. CBD concentrations increased with later harvest dates. Unlike THC concentrations, there was no decline in total CBD concentrations. To minimize risk, growers should test their crop as early as possible within the USDA’s 30-day compliance window. We observed ‘BaOx’ and ‘Cherry Wine’ exceeding the compliance threshold 50 and 41 days after flower initiation, respectively.}, number={10}, journal={HORTICULTURAE}, author={Linder, Eric R. and Young, Sierra and Li, Xu and Inoa, Shannon Henriquez and Suchoff, David H.}, year={2022}, month={Oct} }
 @article{linder_young_li_inoa_suchoff_2022, title={The Effect of Transplant Date and Plant Spacing on Biomass Production for Floral Hemp (Cannabis sativa L.)}, volume={12}, ISSN={["2073-4395"]}, url={https://doi.org/10.3390/agronomy12081856}, DOI={10.3390/agronomy12081856}, abstractNote={Floral hemp cultivated for the extraction of cannabinoids is a new crop in the United States, and agronomic recommendations are scarce. The objective of this study was to understand the effects of plant spacing and transplant date on floral hemp growth and biomass production. Field trials were conducted in North Carolina in 2020 and 2021 with the floral hemp cultivar BaOx. Transplant date treatments occurred every two weeks from 11 May to 7 July (±1 d). Plant spacing treatments were 0.91, 1.22, 1.52, and 1.83 m between plants. Weekly height and width data were collected throughout the vegetative period, and dry biomass was measured at harvest. Plant width was affected by transplant date and spacing. Plant height was affected by transplant date. Earlier transplant dates resulted in taller, wider plants, while larger plant spacing resulted in wider plants. Individual plant biomass increased with earlier transplant dates and larger plant spacing. On a per-hectare basis, biomass increased with earlier transplant dates and smaller transplant spacing. An economic analysis found that returns were highest with 1.22 m spacing and decreased linearly by a rate of −163.098 USD ha−1 d−1. These findings highlight the importance of earlier transplant timing to maximize harvestable biomass.}, number={8}, journal={AGRONOMY-BASEL}, author={Linder, Eric R. and Young, Sierra and Li, Xu and Inoa, Shannon Henriquez and Suchoff, David H.}, year={2022}, month={Aug} }