リモートセンシングでジカンバによる作物損傷を検出(New land grant research detects dicamba damage from the sky)

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2025-07-07 イリノイ大学アーバナ・シャンペーン校

リモートセンシングでジカンバによる作物損傷を検出(New land grant research detects dicamba damage from the sky)
Dicamba-damaged soybean leaves. Photo by Aaron Hager.

イリノイ大学ACESの研究により、ドローンと高感度センサーを使って、大気中の微量なジカンバによる非耐性大豆への被害を検出する技術が開発された。農薬の1万分の1濃度でも、処理8日後に葉の形状変化などの症状を正確に捉え、29日目には全濃度で症状が悪化したが、致命的ではなかった。この技術は、人間の目では見逃しやすい早期被害を定量化し、農薬ドリフトの科学的評価と報告に役立つ。

<関連情報>

無人航空センシングを用いたジカンバ蒸気ドリフトのシミュレーションに対するダイズ(Glycine max L.)のキャノピー応答 Soybean (Glycine max L.) canopy response to simulated dicamba vapor drift using unmanned aerial sensing

Dylan R. Kerr, Aaron G. Hager, Dylan Allen, Andrew D.B. Leakey, Dennis Bowman, Martin M. Williams II
Pest Management Science  Published: 23 June 2025
DOI:https://doi.org/10.1002/ps.8954

Abstract

BACKGROUND

Concerns about off-target dicamba exposure to sensitive vegetation have escalated following the commercialization of dicamba-tolerant (DT) soybean [Glycine max (L.) Merr.] and cotton (Gossypium hirsutum L.) The spectral response of plant injury at the field scale is a crucial knowledge gap that may help researchers understand dicamba’s fate in the environment. Non-DT soybean is the ideal sentinel crop owing to its extreme sensitivity. Field experiments were conducted to characterize the reflectance spectra associated with dicamba vapor drift injured soybean canopies. The objective was, under field conditions and using land-based remote sensing, to determine what regions of the EM correlate to dicamba-injured soybean canopies.

RESULTS

Soybean injury was observed 8 days after treatment at only 1/10000th of a labeled use rate of dicamba. Correlations between simulated vapor drift and reflectance spectra at the single channel red-edge and vegetative indices excess red (ExR) and green leaf index (GLI) were observed. The study demonstrates the potential for detecting off-target dicamba vapor drift injury in soybean, with reflectance spectra following dicamba treatments observed at all spectral channels.

CONCLUSIONS

Differentiating dicamba-injured from dicamba-tolerant soybean canopies can be achieved using single spectral channels and vegetative indices. These findings usher in the possibility that remote sensing satellites, which are well-documented for identifying crop stress on the landscape, could be harnessed to understand the extent to which dicamba injury appears following over-the-top (OTT) application in DT soybean. Remote sensing technology could be instrumental in monitoring off-target herbicide injury and mitigating the effects of dicamba drift. © 2025 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

1202農芸化学
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