E. Jones, R. Austin, J. Dunne, C. Cahoon, Katherine M. Jennings, R. León, W. Everman
{"title":"利用基于图像的光谱反射率检测草铵膦抗性和草铵膦敏感植物的除草剂抗性:概念验证","authors":"E. Jones, R. Austin, J. Dunne, C. Cahoon, Katherine M. Jennings, R. León, W. Everman","doi":"10.1017/wsc.2022.68","DOIUrl":null,"url":null,"abstract":"Abstract Glufosinate is an effective postemergence herbicide, and overreliance on this herbicide for weed control is likely to increase and select for glufosinate-resistant weeds. Common assays to confirm herbicide resistance are dose–response and molecular sequencing techniques; both can require significant time, labor, unique technical equipment, and a specialized skillset to perform. As an alternative, we propose an image-based approach that uses a relatively inexpensive multispectral sensor designed for unmanned aerial vehicles to measure and quantify surface reflectance from glufosinate-treated leaf disks. Leaf disks were excised from a glufosinate-resistant and glufosinate-susceptible corn (Zea mays L.), cotton (Gossypium hirsutum L.), and soybean [Glycine max (L.) Merr.] varieties and placed into a 24-well plate containing eight different concentrations (0 to 10 mM) of glufosinate for 48 h. Multispectral images were collected after the 48-h incubation period across five discrete wave bands: blue (475 to 507 nm), green (560 to 587 nm), red (668to 682 nm), red edge (717 to 729 nm), and near infrared (842 to 899 nm). The green leaf index (GLI; a metric to measure chlorophyll content) was utilized to determine relationships between measured reflectance from the tested wave bands from the treated leaf disks and the glufosinate concentration. Clear differences of spectral reflectance were observed between the corn, cotton, and soybean leaf disks of the glufosinate-resistant and glufosinate-susceptible varieties at the 10 mM concentration for select wave bands and GLI. Leaf disks from two additional glufosinate-resistant and glufosinate-susceptible varieties of each crop were subjected to a similar assay with two concentrations: 0 and 10 mM. No differences of spectral reflectance were observed from the corn and soybean varieties in all wave bands and the GLI. The leaf disks of the glufosinate-resistant and glufosinate-susceptible cotton varieties were spectrally distinct in the green, blue, and red-edge wave bands. The results provide a basis for rapidly detecting glufosinate-resistant plants via spectral reflectance. Future research will need to determine the glufosinate concentrations, useful wave bands, and susceptible/resistant thresholds for weeds that evolve resistance.","PeriodicalId":23688,"journal":{"name":"Weed Science","volume":"71 1","pages":"11 - 21"},"PeriodicalIF":2.1000,"publicationDate":"2022-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Utilization of Image-Based Spectral Reflectance to Detect Herbicide Resistance in Glufosinate-Resistant and Glufosinate-Susceptible Plants: A Proof of Concept\",\"authors\":\"E. Jones, R. Austin, J. Dunne, C. Cahoon, Katherine M. Jennings, R. León, W. Everman\",\"doi\":\"10.1017/wsc.2022.68\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract Glufosinate is an effective postemergence herbicide, and overreliance on this herbicide for weed control is likely to increase and select for glufosinate-resistant weeds. Common assays to confirm herbicide resistance are dose–response and molecular sequencing techniques; both can require significant time, labor, unique technical equipment, and a specialized skillset to perform. As an alternative, we propose an image-based approach that uses a relatively inexpensive multispectral sensor designed for unmanned aerial vehicles to measure and quantify surface reflectance from glufosinate-treated leaf disks. Leaf disks were excised from a glufosinate-resistant and glufosinate-susceptible corn (Zea mays L.), cotton (Gossypium hirsutum L.), and soybean [Glycine max (L.) Merr.] varieties and placed into a 24-well plate containing eight different concentrations (0 to 10 mM) of glufosinate for 48 h. Multispectral images were collected after the 48-h incubation period across five discrete wave bands: blue (475 to 507 nm), green (560 to 587 nm), red (668to 682 nm), red edge (717 to 729 nm), and near infrared (842 to 899 nm). The green leaf index (GLI; a metric to measure chlorophyll content) was utilized to determine relationships between measured reflectance from the tested wave bands from the treated leaf disks and the glufosinate concentration. Clear differences of spectral reflectance were observed between the corn, cotton, and soybean leaf disks of the glufosinate-resistant and glufosinate-susceptible varieties at the 10 mM concentration for select wave bands and GLI. Leaf disks from two additional glufosinate-resistant and glufosinate-susceptible varieties of each crop were subjected to a similar assay with two concentrations: 0 and 10 mM. No differences of spectral reflectance were observed from the corn and soybean varieties in all wave bands and the GLI. The leaf disks of the glufosinate-resistant and glufosinate-susceptible cotton varieties were spectrally distinct in the green, blue, and red-edge wave bands. The results provide a basis for rapidly detecting glufosinate-resistant plants via spectral reflectance. 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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 is likely to increase and select for glufosinate-resistant weeds. Common assays to confirm herbicide resistance are dose–response and molecular sequencing techniques; both can require significant time, labor, unique technical equipment, and a specialized skillset to perform. As an alternative, we propose an image-based approach that uses a relatively inexpensive multispectral sensor designed for unmanned aerial vehicles to measure and quantify surface reflectance from glufosinate-treated leaf disks. Leaf disks were excised from a glufosinate-resistant and glufosinate-susceptible corn (Zea mays L.), cotton (Gossypium hirsutum L.), and soybean [Glycine max (L.) Merr.] varieties and placed into a 24-well plate containing eight different concentrations (0 to 10 mM) of glufosinate for 48 h. Multispectral images were collected after the 48-h incubation period across five discrete wave bands: blue (475 to 507 nm), green (560 to 587 nm), red (668to 682 nm), red edge (717 to 729 nm), and near infrared (842 to 899 nm). The green leaf index (GLI; a metric to measure chlorophyll content) was utilized to determine relationships between measured reflectance from the tested wave bands from the treated leaf disks and the glufosinate concentration. Clear differences of spectral reflectance were observed between the corn, cotton, and soybean leaf disks of the glufosinate-resistant and glufosinate-susceptible varieties at the 10 mM concentration for select wave bands and GLI. Leaf disks from two additional glufosinate-resistant and glufosinate-susceptible varieties of each crop were subjected to a similar assay with two concentrations: 0 and 10 mM. No differences of spectral reflectance were observed from the corn and soybean varieties in all wave bands and the GLI. The leaf disks of the glufosinate-resistant and glufosinate-susceptible cotton varieties were spectrally distinct in the green, blue, and red-edge wave bands. The results provide a basis for rapidly detecting glufosinate-resistant plants via spectral reflectance. Future research will need to determine the glufosinate concentrations, useful wave bands, and susceptible/resistant thresholds for weeds that evolve resistance.
期刊介绍:
Weed Science publishes original research and scholarship in the form of peer-reviewed articles focused on fundamental research directly related to all aspects of weed science in agricultural systems. Topics for Weed Science include:
- the biology and ecology of weeds in agricultural, forestry, aquatic, turf, recreational, rights-of-way and other settings, genetics of weeds
- herbicide resistance, chemistry, biochemistry, physiology and molecular action of herbicides and plant growth regulators used to manage undesirable vegetation
- ecology of cropping and other agricultural systems as they relate to weed management
- biological and ecological aspects of weed control tools including biological agents, and herbicide resistant crops
- effect of weed management on soil, air and water.