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1 October 2011 Reliability of a Visual Recognition System for Detection of Johnsongrass (Sorghum halepense) in Corn
Dionisio Andújar, Ángela Ribeiro, Cesar Fernández-Quintanilla, José Dorado
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Abstract

The feasibility of visual detection of weeds for map-based patch spraying systems needs to be assessed for use in large-scale cropping systems. The main objective of this research was to evaluate the reliability and profitability of using maps of Johnsongrass patches constructed at harvest to predict spatial distribution of weeds during the next cropping season. Johnsongrass patches visually were assessed from the cabin of a combine harvester in three corn fields and were compared with maps obtained in the subsequent year prior to postemergence herbicide application. There was a good correlation (71% on average) between the position of Johnsongrass patches on the two maps (fall vs. spring). The highest correlation (82%) was obtained with relatively large infestations, whereas the lowest (58%) was obtained when the infested area was smaller. Although the relative positions of the patches remained almost unchanged from 1 yr to the next, the infested area increased in all fields during the 4-yr experimental period. According to our estimates, using a strategy based on spraying full rates of herbicides to patches recorded in the map generated in the previous fall resulted in higher net returns than spraying the whole field, either at full or half rate. This site-specific strategy resulted in an average 65% reduction in the volume of herbicide applied to control this weed.

Nomenclature: Johnsongrass, Sorghum halepense (L.) Pers. SORHA; corn, Zea mays L.

Weed Science Society of America
Dionisio Andújar, Ángela Ribeiro, Cesar Fernández-Quintanilla, and José Dorado "Reliability of a Visual Recognition System for Detection of Johnsongrass (Sorghum halepense) in Corn," Weed Technology 25(4), 645-651, (1 October 2011). https://doi.org/10.1614/WT-D-10-00082.1
Received: 21 June 2010; Accepted: 27 April 2011; Published: 1 October 2011
JOURNAL ARTICLE
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KEYWORDS
patch spraying
patchy weed distribution
visual estimation
Weed maps
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