How can unmanned aerial vehicles be used for detecting weeds in agricultural fields?

Weeds are among the most harmful abiotic factors in agriculture, triggering significant yield loss worldwide. Remote sensing can detect and map the presence of weeds in various spectral, spatial, and temporal resolutions. This review aims to show the current and future trends of UAV applications in...

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Main Authors: Mohidem, Nur Adibah, Che'Ya, Nik Norasma, Juraimi, Abdul Shukor, Fazlil Ilahi, Wan Fazilah, Mohd Roslim, Muhammad Huzaifah, Sulaiman, Nursyazyla, Saberioon, Mohammadmehdi, Mohd Noor, Nisfariza
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Published: MDPI 2021
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Online Access:http://eprints.um.edu.my/33992/
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Institution: Universiti Malaya
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spelling my.um.eprints.339922022-06-28T01:48:56Z http://eprints.um.edu.my/33992/ How can unmanned aerial vehicles be used for detecting weeds in agricultural fields? Mohidem, Nur Adibah Che'Ya, Nik Norasma Juraimi, Abdul Shukor Fazlil Ilahi, Wan Fazilah Mohd Roslim, Muhammad Huzaifah Sulaiman, Nursyazyla Saberioon, Mohammadmehdi Mohd Noor, Nisfariza S Agriculture (General) Weeds are among the most harmful abiotic factors in agriculture, triggering significant yield loss worldwide. Remote sensing can detect and map the presence of weeds in various spectral, spatial, and temporal resolutions. This review aims to show the current and future trends of UAV applications in weed detection in the crop field. This study systematically searched the original articles published from 1 January 2016 to 18 June 2021 in the databases of Scopus, ScienceDirect, Commonwealth Agricultural Bureaux (CAB) Direct, and Web of Science (WoS) using Boolean string: ``weed `` AND ``Unmanned Aerial Vehicle `` OR ``UAV `` OR ``drone ``. Out of the papers identified, 144 eligible studies did meet our inclusion criteria and were evaluated. Most of the studies (i.e., 27.42%) on weed detection were carried out during the seedling stage of the growing cycle for the crop. Most of the weed images were captured using red, green, and blue (RGB) camera, i.e., 48.28% and main classification algorithm was machine learning techniques, i.e., 47.90%. This review initially highlighted articles from the literature that includes the crops' typical phenology stage, reference data, type of sensor/camera, classification methods, and current UAV applications in detecting and mapping weed for different types of crop. This study then provides an overview of the advantages and disadvantages of each sensor and algorithm and tries to identify research gaps by providing a brief outlook at the potential areas of research concerning the benefit of this technology in agricultural industries. Integrated weed management, coupled with UAV application improves weed monitoring in a more efficient and environmentally-friendly way. Overall, this review demonstrates the scientific information required to achieve sustainable weed management, so as to implement UAV platform in the real agricultural contexts. MDPI 2021-10 Article PeerReviewed Mohidem, Nur Adibah and Che'Ya, Nik Norasma and Juraimi, Abdul Shukor and Fazlil Ilahi, Wan Fazilah and Mohd Roslim, Muhammad Huzaifah and Sulaiman, Nursyazyla and Saberioon, Mohammadmehdi and Mohd Noor, Nisfariza (2021) How can unmanned aerial vehicles be used for detecting weeds in agricultural fields? Agriculture-Basel, 11 (10). ISSN 2077-0472, DOI https://doi.org/10.3390/agriculture11101004 <https://doi.org/10.3390/agriculture11101004>. 10.3390/agriculture11101004
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic S Agriculture (General)
spellingShingle S Agriculture (General)
Mohidem, Nur Adibah
Che'Ya, Nik Norasma
Juraimi, Abdul Shukor
Fazlil Ilahi, Wan Fazilah
Mohd Roslim, Muhammad Huzaifah
Sulaiman, Nursyazyla
Saberioon, Mohammadmehdi
Mohd Noor, Nisfariza
How can unmanned aerial vehicles be used for detecting weeds in agricultural fields?
description Weeds are among the most harmful abiotic factors in agriculture, triggering significant yield loss worldwide. Remote sensing can detect and map the presence of weeds in various spectral, spatial, and temporal resolutions. This review aims to show the current and future trends of UAV applications in weed detection in the crop field. This study systematically searched the original articles published from 1 January 2016 to 18 June 2021 in the databases of Scopus, ScienceDirect, Commonwealth Agricultural Bureaux (CAB) Direct, and Web of Science (WoS) using Boolean string: ``weed `` AND ``Unmanned Aerial Vehicle `` OR ``UAV `` OR ``drone ``. Out of the papers identified, 144 eligible studies did meet our inclusion criteria and were evaluated. Most of the studies (i.e., 27.42%) on weed detection were carried out during the seedling stage of the growing cycle for the crop. Most of the weed images were captured using red, green, and blue (RGB) camera, i.e., 48.28% and main classification algorithm was machine learning techniques, i.e., 47.90%. This review initially highlighted articles from the literature that includes the crops' typical phenology stage, reference data, type of sensor/camera, classification methods, and current UAV applications in detecting and mapping weed for different types of crop. This study then provides an overview of the advantages and disadvantages of each sensor and algorithm and tries to identify research gaps by providing a brief outlook at the potential areas of research concerning the benefit of this technology in agricultural industries. Integrated weed management, coupled with UAV application improves weed monitoring in a more efficient and environmentally-friendly way. Overall, this review demonstrates the scientific information required to achieve sustainable weed management, so as to implement UAV platform in the real agricultural contexts.
format Article
author Mohidem, Nur Adibah
Che'Ya, Nik Norasma
Juraimi, Abdul Shukor
Fazlil Ilahi, Wan Fazilah
Mohd Roslim, Muhammad Huzaifah
Sulaiman, Nursyazyla
Saberioon, Mohammadmehdi
Mohd Noor, Nisfariza
author_facet Mohidem, Nur Adibah
Che'Ya, Nik Norasma
Juraimi, Abdul Shukor
Fazlil Ilahi, Wan Fazilah
Mohd Roslim, Muhammad Huzaifah
Sulaiman, Nursyazyla
Saberioon, Mohammadmehdi
Mohd Noor, Nisfariza
author_sort Mohidem, Nur Adibah
title How can unmanned aerial vehicles be used for detecting weeds in agricultural fields?
title_short How can unmanned aerial vehicles be used for detecting weeds in agricultural fields?
title_full How can unmanned aerial vehicles be used for detecting weeds in agricultural fields?
title_fullStr How can unmanned aerial vehicles be used for detecting weeds in agricultural fields?
title_full_unstemmed How can unmanned aerial vehicles be used for detecting weeds in agricultural fields?
title_sort how can unmanned aerial vehicles be used for detecting weeds in agricultural fields?
publisher MDPI
publishDate 2021
url http://eprints.um.edu.my/33992/
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