Use of a phone App to optimize pesticide spray applications and reduce risk of resistance development in target pest populations

Tuesday, November 12, 2013
Exhibit Hall 4 (Austin Convention Center)
Christian Nansen , The University of Western Australia, Perth, Australia
Nicolas Garel , ngperceptive, Cloverdale, Australia
Olivier Baissac , The University of Western Australia, Perth, Australia
Jerome Gumley , The University of Western Australia, Perth, Australia
Low and inconsistent coverage of pesticide spray applications to field crops lead to poor pest control and is also believed to contribute to resistance development in target pest populations. Many variables are known to affect the actual spray coverage applied with ground rigs in field crops (including tractor speed, spray nozzles, spray volume, boom height, adjuvants, and weather conditions) - But which ones are the most important ones? And are there possible interactions among some of these variables? We present information on a phone App developed by the authors and with the following functionalities: 1) quantifies actual spray coverage (based on water sensitive spray cards), and 2) estimates predicted spray coverage (based on a multi-regression model). The latter functionality can be used for quality control to compare with obtained spray coverage and to forecast and optimize spray coverages based on weather and spray settings. With better quantitative understanding of which variables affect pesticide spray coverages, we can optimize spray applications and therefore: 1) obtain better pest control, 2) reduce risks of resistance development, and 3) optimize spray application costs by introducing a quality control procedure.
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