The Application of Machine Learning and Deep Learning Techniques in Agriculture
A special issue of AgriEngineering (ISSN 2624-7402). This special issue belongs to the section "Computer Applications and Artificial Intelligence in Agriculture".
Deadline for manuscript submissions: 28 February 2026 | Viewed by 350
Special Issue Editors
Interests: advanced mobile communications; Artificial Intelligence; deep learning; digital technologies; machine learning; neural networks; Internet of Things; precision agriculture; sensor networks; satellite communications; unmanned aerial vehicles
Special Issues, Collections and Topics in MDPI journals
Interests: Internet of Things; machine learning; mobile communications; global navigation satellite system (GNSS); satellite communications
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
With the requirement for farming to become more efficient and environmentally sustainable to meet the needs of an expanding global population, the employment of Machine Learning and Deep Learning techniques to inform and enhance agricultural practice and production is gathering pace.
This Special Issue aims to showcase the latest research findings in the use of Machine Learning and Deep Learning techniques and related technologies when applied to agricultural practice.
The introduction of technologies, such as the wireless sensor networks, the Internet of Things, and high-resolution camera drones, is creating new opportunities to gather extensive digital datasets in real-time, which can then be used by models with the ability to learn from and interpret this information. At the core of this manner of working are the concepts of Artificial Intelligence, Machine Learning and Deep Learning.
In this Special Issue, original, high-quality research articles and reviews are welcome.
Research areas include but are not limited to how machine learning and deep learning techniques may be applied to the following:
- Improving crop yields using datasets provided by the Internet of Things (IoT) technologies.
- Enhancing land usage from geographical imagery produced by high-resolution Earth observation satellites or Unmanned Aerial Vehicle (UAV) platforms.
- Targeting the use of weed control products to areas where needed by analyzing the quality of the soil from in situ sensors.
- Determining the health and quality of plants and the risk of disease from high-resolution graphical imagery.
- Applying irrigation to areas where needed from information provided by wireless sensor networks.
- Identifying the optimum time to sow, fertilise and harvest crops.
- Case studies that demonstrate the effectiveness of machine learning and deep learning techniques on precision agriculture in practical situations.
This Special Issue follows on from the Guest Editors’ previous Special Issue The Application of Artificial Neural Network in Agriculture.
Prof. Dr. Ray E. Sheriff
Dr. Chiew Foong Kwong
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. AgriEngineering 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 1600 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
- artificial intelligence
- deep learning
- drones
- Internet of Things
- neural networks
- machine learning
- precision agriculture
- unmanned aerial vehicles
- wireless sensor networks
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