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

Abstract

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.

Phytosociological variability of weeds in soybean field

“…The technique was effective; however, it becomes more time consuming with the increasing complexity of the spatial distribution of weeds in the area. Recently, with the use of optical sensors in Brazilian agriculture, some studies have shown promising results for use in weed mapping (Silva Jr. et al, 2012;Merotto Jr. et al, 2012).…”

“…As for the automatic collection of data, one can use color cameras and infrared coupled to a land (Silva Jr. et al, 2012) or air equipment (Candón et al, 2012b) and sensors and vegetation index (Chang et al, 2004;Merotto Jr. et al, 2012). On the other hand, in the conventional sampling meshes are commonly used sample, dividing the area into smaller squares, where the georeferenced samples of the weed are held (Merotto Jr. & Bredemeier, 2010).…”

About Effect of Weeds on Spectral Reflectance Properties of Winter Wheat Canopy

“…Как уже указывалось выше, СОС сорняков статистически значимо (при р  0,05) отличается от СОС пшеницы. Наибольшие различия наблюдаются в ИК и зеленой области спектра вследствие того, что сорная растительность имеет более зеленый цвет, чем листья пшеницы (особенно в начале послезимней вегетации и после прохождения максимума вегетации), что подтверждает данные, полученные исследователями ранее (19,34). Меньшие, но в некоторых случаях достаточно заметные различия наблюдаются в красной области спектра, где сорная растительность немного сильнее отражает солнечную энергию в сравнении с листьями пшеницы из-за несколько большего содержания в ней влаги (35).…”

Agricultura de precisão: particularidades de sua adoção no sudoeste de Goiás – Brasil

“…Esses índices podem ser utilizados, como referência, na adubação das culturas e no manejo de p lantas daninhas (MEROTTO et al, 2012).…”