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Pest Management Science
Article . 2019 . Peer-reviewed
License: CC BY NC ND
Data sources: Crossref
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Pest Management Science
Article
License: CC BY NC ND
Data sources: UnpayWall
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PubMed Central
Other literature type . 2019
Data sources: PubMed Central
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Integration of remote‐weed mapping and an autonomous spraying unmanned aerial vehicle for site‐specific weed management

Authors: Joseph E Hunter; Travis W Gannon; Robert J Richardson; Fred H Yelverton; Ramon G Leon;

Integration of remote‐weed mapping and an autonomous spraying unmanned aerial vehicle for site‐specific weed management

Abstract

Abstract BACKGROUND Unmanned aerial vehicles (UAVs) have been used in agriculture to collect imagery for crop and pest monitoring, and for decision‐making purposes. Spraying‐capable UAVs are now commercially available worldwide for agricultural applications. Combining UAV weed mapping and UAV sprayers into an UAV integrated system (UAV‐IS) can offer a new alternative to implement site‐specific pest management. RESULTS The UAV‐IS was 0.3‐ to 3‐fold more efficient at identifying and treating target weedy areas, while minimizing treatment on non‐weedy areas, than ground‐based broadcast applications. The UAV‐IS treated 20–60% less area than ground‐based broadcast applications, but also missed up to 26% of the target weedy area, while broadcast applications covered almost the entire experimental area and only missed 2–3% of the target weeds. The efficiency of UAV‐IS management practices increased as weed spatial aggregation increased (patchiness). CONCLUSION Integrating UAV imagery for pest mapping and UAV sprayers can provide a new strategy for integrated pest management programs to improve efficiency and efficacy while reducing the amount of pesticide being applied. The UAV‐IS has the potential to improve the detection and control of weed escapes to reduce/delay herbicide resistance evolution. © 2019 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Keywords

Weed Control, Remote Sensing Technology, Plant Weeds, Agriculture, Research Articles

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    97
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
97
Top 1%
Top 10%
Top 10%
Green
hybrid