Utilization of Image-Based Spectral Reflectance to Detect Herbicide Resistance in Glufosinate-Resistant and Glufosinate-Susceptible Plants: A Proof of Concept

IF 2.1 2区 农林科学 Q2 AGRONOMY
Weed Science Pub Date : 2022-12-19 DOI:10.1017/wsc.2022.68
E. Jones, R. Austin, J. Dunne, C. Cahoon, Katherine M. Jennings, R. León, W. Everman
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引用次数: 2

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.
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
摘要:草铵膦是一种有效的羽化后除草剂,过度依赖草铵膦来控制杂草可能会增加对草铵膦抗性杂草的选择。确定除草剂抗性的常用检测方法是剂量反应和分子测序技术;两者都需要大量的时间、劳动力、独特的技术设备和专门的技能来完成。作为替代方案,我们提出了一种基于图像的方法,该方法使用一种相对便宜的多光谱传感器,设计用于无人机,以测量和量化草铵膦处理过的叶片的表面反射率。从抗草铵膦和对草铵膦敏感的玉米(Zea mays L.)、棉花(Gossypium hirsutum L.)和大豆(Glycine max (L.))上切除叶片。稳定。放置在含有8种不同浓度(0至10 mM)草铵膦的24孔板中48小时。孵育48小时后,在5个不同波段收集多光谱图像:蓝色(475至507 nm)、绿色(560至587 nm)、红色(668至682 nm)、红边(717至729 nm)和近红外(842至899 nm)。绿叶指数(GLI;利用测量叶绿素含量的度量来确定从处理过的叶片的测试波段测量的反射率与草铵膦浓度之间的关系。在10 mM浓度下,玉米、棉花和大豆抗草铵膦品种叶片的光谱反射率和GLI存在明显差异。另外两种作物的抗草铵膦和感草铵膦品种的叶盘进行了类似的试验,浓度分别为0和10 mM。在所有波段和GLI中,玉米和大豆品种的光谱反射率没有差异。抗草铵膦和感草铵膦棉花品种的叶片在绿、蓝、红边波段具有明显的光谱差异。研究结果为利用光谱反射率快速检测草铵膦抗性植物提供了依据。未来的研究将需要确定草铵膦浓度,有用的波段,以及对杂草产生抗性的敏感/抗性阈值。
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来源期刊
Weed Science
Weed Science 农林科学-农艺学
CiteScore
4.60
自引率
12.00%
发文量
64
审稿时长
12-24 weeks
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.
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