Phone App to Perform Quality Control of Pesticide Spray Applications in Field Crops

Christian Nansen, Gabriel Del Villar, Alexander Recalde, Elvis Alvarado and Krishna Chennapragada
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Christian Nansen: Department of Entomology and Nematology, University of California, Davis, CA 95616, USA
Gabriel Del Villar: Department of Computer Science, University of California, Davis, CA 95616, USA
Alexander Recalde: Department of Computer Science, University of California, Davis, CA 95616, USA
Elvis Alvarado: Department of Computer Science, University of California, Davis, CA 95616, USA
Krishna Chennapragada: Department of Computer Science, University of California, Davis, CA 95616, USA

Agriculture, 2021, vol. 11, issue 10, 1-12

Abstract: It has been recognized for decades that low and inconsistent spray coverages of pesticide applications represent a major challenge to successful and sustainable crop protection. Deployment of water-sensitive spray cards combined with image analysis can provide valuable and quantitative insight into spray coverage. Herein we provide description of a novel and freely available smartphone app, “Smart Spray”, for both iOS and Android smart devices (iOS and Google app stores). More specifically, we provide a theoretical description of spray coverage, and we describe how Smart Spray and similar image-processing software packages can be used as decision support tools and quality control for pesticide spray applications. Performance assessment of the underlying pixel classification algorithm is presented, and we detail practical recommendations on how to use Smart Spray to maximize accuracy and consistency of spray coverage predictions. Smart Spray was developed as part of ongoing efforts to: (1) maximize the performance of pesticide sprays, (2) minimize pest-induced yield loss and to potentially reduce the amount of pesticide used, (2) reduce the risk of target pests developing pesticide resistance, (3) reduce the risk of spray drift, and (4) optimize spray application costs by introducing a quality control.

Keywords: spray coverage; decision support tools; pesticide applications; spray performance; smartphone apps (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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