Soil-Machine Systems and Its Related Digital Technologies Application
A special issue of Agriculture (ISSN 2077-0472). This special issue belongs to the section "Agricultural Technology".
Deadline for manuscript submissions: 30 September 2025 | Viewed by 119
Special Issue Editors
Interests: agricultural engineering; agricultural ergonomics; agricultural field machinery; digital agriculture; soil–machine systems; terramechanics
Special Issues, Collections and Topics in MDPI journals
Interests: precision agriculture; remote sensing; geospatial engineering; UAS; data science/management
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The mechanization of agricultural works has greatly contributed to the improvement of agricultural productivity and the reduction in production costs. Since the beginning of mechanization, various kinds of agricultural machinery related to soil preparation, sowing, harvesting, post-harvesting, etc., have been developed. In addition, customized agricultural machines that are suitable for cultivation type and soil characteristics of each country and region have been developed. Agricultural machinery, unlike other industrial machinery, targets living organisms and operates on the soil, so it should be designed in consideration of the interaction with the soil. It is possible to optimally design agricultural machinery by understanding both the characteristics of the soil and the characteristics of the mechanical system. Furthermore, in the fourth industrial revolution digital agriculture using various types of data obtainable from different sensors is also being applied to the agriculture domain. Cutting-edge agricultural machinery such as unoccupied aircraft systems (UAS, also known as drone), autonomous tractors, and automated harvesting robots are being developed and commercialized for cost-effective production and sustainable agriculture, based on an understanding of both digital agriculture technologies such as sensors, AI, and ICT technologies and soil-machine systems.
This Special Issue focuses on research regarding soil–machine systems and digital agriculture technologies, including development of new agricultural equipment, application of new technologies to existing systems, integration of big data and AI into machine systems, and development of new concept and technology in precision agriculture. The scope is from traditional to cutting-edge agricultural systems. Soil-related and data-driven research is also of interest. Both original research articles and comprehensive reviews are welcome.
Dr. Ju-Seok Nam
Dr. Anjin Chang
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. Agriculture is an international peer-reviewed open access semimonthly 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
- digital agriculture
- artificial intelligence
- deep learning
- machine vision
- soil-machine systems
- biosystems engineering
- precision agriculture
- machine vision
- smart farming
- soil and crops
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