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Reflectance indices as a diagnostic tool for weed control performed by multipurpose equipment in precision agriculture

机译:反射率作为精准农业中杂草控制的诊断工具

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Several tools of precision agriculture have been developed for specific uses. However, this specificity may hinder the implementation of precision agriculture due to an increasing in costs and operational complexity. The use of vegetation index sensors which are traditionally developed for crop fertilization, for site-specific weed management can provide multiple utilizations of these sensors and result in the optimization of precision agriculture. The aim of this study was to evaluate the relationship between reflectance indices of weeds obtained by the GreenSeekerTM sensor and conventional parameters used for weed interference quantification. Two experiments were conducted with soybean and corn by establishing a gradient of weed interference through the use of pre- and post-emergence herbicides. The weed quantification was evaluated by the normalized difference vegetation index (NDVI) and the ratio of red to near infrared (Red/NIR) obtained using the GreenSeekerTM sensor, the visual weed control, the weed dry matter, and digital photographs, which supplied information about the leaf area coverage proportions of weed and straw. The weed leaf coverage obtained using digital photography was highly associated with the NDVI (r = 0.78) and the Red/NIR (r = -0.74). The weed dry matter also positively correlated with the NDVI obtained in 1 m linear (r = 0.66). The results indicated that the GreenSeekerTM sensor originally used for crop fertilization could also be used to obtain reflectance indices in the area between rows of crops to support decision-making programs for weed control.
机译:针对特定用途,已经开发了几种精密农业工具。但是,由于成本和操作复杂性的增加,这种特殊性可能会阻碍精准农业的实施。传统上为作物施肥开发的植被指数传感器用于特定地点的杂草管理,可以对这些传感器进行多种利用,从而优化精准农业。这项研究的目的是评估GreenSeekerTM传感器获得的杂草的反射指数与用于杂草干扰定量的常规参数之间的关系。通过使用芽前和芽后除草剂建立杂草干扰的梯度,对大豆和玉米进行了两个实验。通过归一化差异植被指数(NDVI)和使用GreenSeekerTM传感器,可见杂草控制,杂草干物质和数码照片获得的红色照片与近红外线的比率(Red / NIR)评估杂草的定量,该信息可提供信息关于杂草和稻草的叶面积覆盖率。使用数码摄影获得的杂草叶覆盖率与NDVI(r = 0.78)和Red / NIR(r = -0.74)高度相关。杂草干物质也与以1 m线性获得的NDVI正相关(r = 0.66)。结果表明,最初用于农作物施肥的GreenSeekerTM传感器还可用于获取农作物行之间区域的反射率指数,以支持杂草控制决策程序。

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