@article{bethke_huang_hensel_heinen_liu_wyant_li_quin_mccormick_morrell_et al._2023, title={UDP-glucosyltransferase HvUGT13248 confers type II resistance to Fusarium graminearum in barley}, ISSN={["1532-2548"]}, DOI={10.1093/plphys/kiad467}, abstractNote={Abstract
               Fusarium head blight (FHB) of barley (Hordeum vulgare) causes yield losses and accumulation of trichothecene mycotoxins (e.g. deoxynivalenol [DON]) in grains. Glucosylation of DON to the nontoxic DON-3-O-glucoside (D3G) is catalyzed by UDP-glucosyltransferases (UGTs), such as barley UGT13248. We explored the natural diversity of UGT13248 in 496 barley accessions and showed that all carried potential functional alleles of UGT13248, as no genotypes showed strongly increased seedling sensitivity to DON. From a TILLING population, we identified 2 mutant alleles (T368I and H369Y) that, based on protein modeling, likely affect the UDP-glucose binding of UGT13248. In DON feeding experiments, DON-to-D3G conversion was strongly reduced in spikes of these mutants compared to controls, and plants overexpressing UGT13248 showed increased resistance to DON and increased DON-to-D3G conversion. Moreover, field-grown plants carrying the T368I or H369Y mutations inoculated with Fusarium graminearum showed increased FHB disease severity and reduced D3G production. Barley is generally considered to have type II resistance that limits the spread of F. graminearum from the infected spikelet to adjacent spikelets. Point inoculation experiments with F. graminearum showed increased infection spread in T368I and H369Y across the spike compared to wild type, while overexpression plants showed decreased spread of FHB symptoms. Confocal microscopy revealed that F. graminearum spread to distant rachis nodes in T368I and H369Y mutants but was arrested at the rachis node of the inoculated spikelet in wild-type plants. Taken together, our data reveal that UGT13248 confers type II resistance to FHB in barley via conjugation of DON to D3G.}, journal={PLANT PHYSIOLOGY}, author={Bethke, Gerit and Huang, Yadong and Hensel, Goetz and Heinen, Shane and Liu, Chaochih and Wyant, Skylar R. and Li, Xin and Quin, Maureen B. and Mccormick, Susan and Morrell, Peter L. and et al.}, year={2023}, month={Aug} }
 @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} }