Consumer-grade UAV utilized for detecting and analyzing late-season weed spatial distribution patterns in commercial onion fields

Abstract

Studying weed spatial distribution patterns and implementing precise herbicide applications requires accurate weed mapping. In this study, a simple unmanned aerial vehicle (UAV) was utilized to survey 11 dry onion (Allium cepa L.) commercial fields to examine late-season weed classification and investigate weeds spatial pattern. In addition, orthomosaics were resampled to a coarser spatial resolution to simulate and examine the accuracy of weed mapping at different altitudes. Overall, 176 weed maps were generated and evaluated. Pixel and object-based image analyses were assessed, employing two supervised classification algorithms: Maximum Likelihood (ML) and Support Vector Machine (SVM). Classification processes resulted in highly accurate weed maps across all spatial resolutions tested. Weed maps contributed to three insights regarding the late-season weed spatial pattern in onion fields: 1) weed coverage varied significantly between fields, ranging from 1 to 79%; 2) weed coverage was similar within and between crop rows; and 3) weed pattern was patchy in all fields. The last finding, combined with the ability to map weeds using a low cost, off-the-shelf UAV, constitutes an important step in developing precise weed control management in onion fields.

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Acknowledgements

We would like to thank the farmers for allowing us to survey their fields. We also wish to thank Eli Margalit, Extension Service, Ministry of Agriculture. We are likewise grateful to Prof. Hanan Eizenberg and Dr. Ran Lati, from the Newe Yaar research station, and Prof. Yishai Weinstein from Bar Ilan University, for valuable discussions. The authors wish to thank the three anonymous reviewers and the editor for their constructive comments.

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Rozenberg, G., Kent, R. & Blank, L. Consumer-grade UAV utilized for detecting and analyzing late-season weed spatial distribution patterns in commercial onion fields. Precision Agric (2021). https://doi.org/10.1007/s11119-021-09786-y

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Keywords

  • Classification
  • UAV
  • Weed mapping
  • Site specific weed management
  • Spatial pattern