Site-Specific Weed Management (SSWM): Integrating Weed Population Dynamics with Information-Communications Technologies (ICTs)
A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Weed Science and Weed Management".
Deadline for manuscript submissions: 31 October 2024 | Viewed by 164
Special Issue Editors
Interests: weed bioecology; integrated weed management; population dynamics; predictive modeling; soft computing; decision support systems
Special Issues, Collections and Topics in MDPI journals
Interests: weed population dynamics; seed ecology and physiology; crop physiology; weed management; ecological modeling
Interests: weed control; herbicide-resistance; modes of action of herbicides; integrated weed management
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The developing techniques in precision agriculture suggest that high-tech strategies, such as artificial intelligence (AI), machine learning, and deep learning techniques, are of the uppermost importance in the novel management of weeds, which aims to produce high crop yields while reducing the negative environmental impact of agronomic practices. In fact, ICTs are currently being used to empower site-specific weed management (SSWM). Site-specific weed management is based on the fact that weed populations are commonly irregularly distributed within crop fields, and it implies applying chemical and/or physical control measures only where and when they are needed. Currently, the use of AI models allows for the integration of photogrammetry or image analysis to establish databases for developing algorithms that enable weed management using automated or robotic techniques to distinguish weeds from crops. Both remote sensing (satellite) and unmanned aerial vehicles (UAVs) are being used to collect data at different spatial scales. The integration of both remote and proximal datasets to train and test AI algorithms is a novel route towards more precise and optimized management decisions. In this Special Issue, we invite researchers to contribute original researches, reviews, and opinion pieces covering all topics related to site-specific weed management, weed population dynamics, and ICTs.
Dr. Guillermo R. Chantre
Dr. Roberto Benech-Arnold
Dr. Marcos Yanniccari
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agronomy is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- weed bioecology
- population dynamics
- precision agriculture
- remote sensing
- proximal sensing
- artificial intelligence
- decision support systems
