Pre-harvest weed mapping of Cirsium arvense L. based on free satellite imagery – The importance of weed aggregation and image resolution

Rasmussen, Jesper; Azim, Saiful; Nielsen, Jon

doi:10.1016/j.eja.2021.126373

Cited by 19 publications

(9 citation statements)

References 36 publications

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“…Unmanned Arial Vehicles or drones integrated with advanced machine learning help in continuous weed management enabling selection decisions and reducing herbicide diffusion in the environment [ 56 ]. Also, Rasmussen et al, in 2021 studied the effect of engaging unmanned arial vehicles which receive data from satellite imagery to perform weed mapping of a particular variety of weed and the result showed that it provides higher resolution images and makes an individual variety of weed to be detected in the crops [ 57 ].…”

Section: Discussionmentioning

confidence: 99%

Artificial intelligence solutions enabling sustainable agriculture: A bibliometric analysis

2022

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There is a dearth of literature that provides a bibliometric analysis concerning the role of Artificial Intelligence (AI) in sustainable agriculture therefore this study attempts to fill this research gap and provides evidence from the studies conducted between 2000–2021 in this field of research. The study is a systematic bibliographic analysis of the 465 previous articles and reviews done between 2000–2021 in relation to the utilization of AI in sustainable methods of agriculture. The results of the study have been visualized and presented using the VOSviewer and Biblioshiny visualizer software. The results obtained post analysis indicate that, the amount of academic works published in the field of AI’s role in enabling sustainable agriculture increased significantly from 2018. Therefore, there is conclusive evidence that the growth trajectory shows a significant climb upwards. Geographically analysed, the country collaboration network highlights that most number of studies in the realm of this study originate from China, USA, India, Iran, France. The co-author network analysis results represent that there are multi-disciplinary collaborations and interactions between prominent authors from United States of America, China, United Kingdom and Germany. The final framework provided from this bibliometric study will help future researchers identify the key areas of interest in research of AI and sustainable agriculture and narrow down on the countries where prominent academic work is published to explore co-authorship opportunities.

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Section: Discussionmentioning

confidence: 99%

Artificial intelligence solutions enabling sustainable agriculture: A bibliometric analysis

2022

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“…Increasingly, the ambition for image‐based weed detection technologies is to develop algorithms that can distinguish weeds from crops and therefore enable the selective removal of weeds from crops (green on green technology, Allmendinger et al, 2022), though identifying specific weed species is still problematic, especially in crops and cover crops (Coleman et al, 2022). So far, using image‐based mapping and identification is only feasible for some species (e.g., C. arvense , Rasmussen et al, 2021). As technologies continue to evolve and are brought to EU markets at affordable costs, the prospects for enabling and requiring targeted glyphosate application to reduce field‐scale use rates for the control of perennial (and other) weeds present a promising way to greatly support EU herbicide use reduction targets.…”

Section: Options For Reducing Glyphosate Use In Europementioning

confidence: 99%

Current and future glyphosate use in European agriculture

Neve,

Matzrafi,

Ulber

et al. 2024

Weed Research

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There has been a longstanding and contentious debate about the future of glyphosate use in the European Union (EU). In November 2023, the European Commission approved the renewal of the use registration for glyphosate for a further 10 years. Nevertheless, the EU Farm to Fork strategy calls for a 50% reduction in pesticide use by 2030. In November 2022, the European Weed Research Society organised a 2 day workshop to identify critical glyphosate uses in current EU cropping systems and to review the availability of glyphosate alternatives. Workshop participants identified four current, critical uses in EU cropping systems; control and management of perennial weeds, weed control in conservation agriculture, vegetation management in tree and vine crops and herbicide resistance management. There are few herbicide alternatives that provide effective, economic, broad‐spectrum control of weeds, particularly perennial weeds. Mechanical weed control, and in particular, soil cultivation is the most obvious glyphosate alternative. However, this is not possible in conservation agriculture systems and, in general, increased soil cultivation has negative impacts for soil health. Emerging technologies for precision weed control can enable more targeted use of glyphosate, greatly reducing use rates. These technologies also facilitate the use and development of alternative targeted physical weed control (e.g. tillage, lasers, electricity), reducing the energy and environmental costs of these approaches. In tree crops, the use of organic and inorganic mulches can reduce the need for glyphosate use. In general, reduced use of glyphosate will require an even greater focus on integrated weed management to reduce weed establishment in agroecosystems, increase weed management diversity and limit the use of alternative resistance‐prone herbicides.

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“…Early‐season weed maps can be used to calculate the potential herbicide savings and plan site‐specific weed control application. Weed maps generated from aerial images close to harvest can be used to control patches of C. arvense L. in the following years (Rasmussen et al, 2021).…”

Section: Spatial Variation Of Weed Populationsmentioning

confidence: 99%

Advances in site‐specific weed management in agriculture—A review

et al. 2022

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The developments of information and automation technologies have opened a new era for weed management to fit physical and chemical control treatments to the spatial and temporal heterogeneity of weed distributions in agricultural fields. This review describes the technologies of site‐specific weed management (SSWM) systems, evaluates their ecological and economic benefits and gives a perspective for the implementation in practical farming. Sensor technologies including 3D cameras, multispectral imaging and Artificial Intelligence (AI) for weed classification and computer‐based decision algorithms are described in combination with precise spraying and hoeing operations. Those treatments are targeted for patches of weeds or individual weed plants. Cameras can also guide inter‐row hoes precisely in the centre between two crop rows at much higher driving speed. Camera‐guided hoeing increased selectivity and weed control efficacy compared with manual steered hoeing. Robots combine those guiding systems with in‐row hoeing or spot spraying systems that can selectively control individual weeds within crop rows. Results with patch spraying show at least 50% saving of herbicides in various crops without causing additional costs for weed control in the following years. A challenge with these technologies is the interoperability of sensing and controllers. Most of the current SSWM technologies use their own IT protocols that do not allow connecting different sensors and implements. Plug & play standards for linking detection, decision making and weeding would improve the adoption of new SSWM technologies and reduce operational costs. An important impact of SSWM is the potential contribution to the EU‐Green Deal targets to reduce pesticide use and increase biodiversity. However, further on‐farm research is needed for integrating those technologies into agricultural practice.

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Pre-harvest weed mapping of Cirsium arvense L. based on free satellite imagery – The importance of weed aggregation and image resolution

Cited by 19 publications

References 36 publications

Artificial intelligence solutions enabling sustainable agriculture: A bibliometric analysis

Artificial intelligence solutions enabling sustainable agriculture: A bibliometric analysis

Current and future glyphosate use in European agriculture

Advances in site‐specific weed management in agriculture—A review

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