Utilization of image-based spectral reflectance to detect herbicide resistance in glufosinate-resistant and glufosinate-susceptible plants: a proof of concept

Abstract Glufosinate is an effective postemergence herbicide, and overreliance on this herbicide for weed control likely to increase select glufosinate-resistant weeds. Common assays confirm resistance are dose–response molecular sequencing techniques; both can require significant time, labor, unique technical equipment, a specialized skillset perform. As alternative, we propose image-based approach that uses relatively inexpensive multispectral sensor designed unmanned aerial vehicles measure quantify surface reflectance from glufosinate-treated leaf disks. Leaf disks were excised glufosinate-susceptible corn ( Zea mays L.), cotton Gossypium hirsutum soybean [ Glycine max (L.) Merr.] varieties placed into 24-well plate containing eight different concentrations (0 10 mM) of glufosinate 48 h. Multispectral images collected after the 48-h incubation period across five discrete wave bands: blue (475 507 nm), green (560 587 red (668to 682 edge (717 729 near infrared (842 899 nm). The index (GLI; metric chlorophyll content) was utilized determine relationships between measured tested bands treated concentration. Clear differences spectral observed corn, cotton, at mM concentration GLI. two additional each crop subjected similar assay with concentrations: 0 mM. No in all spectrally distinct green, blue, red-edge bands. results provide basis rapidly detecting plants via reflectance. Future research will need concentrations, useful bands, susceptible/resistant thresholds weeds evolve resistance.