Digitalization and Robotics as a Key Support Toward Sustainable Management of Agriculture
A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Farming Sustainability".
Deadline for manuscript submissions: 30 June 2026 | Viewed by 1
Special Issue Editors
Interests: sustainable management of turfs; non-chemical weed control in different agriculture contexts and urban and suburban areas; use of robotized automatic mowers in turfs and agriculture for cover crops management; automatic machines and robots for precision agriculture; smart strategies and machines for organic and conservation management of agriculture
Special Issues, Collections and Topics in MDPI journals
Interests: sustainable soil and weed management in orchards, horticultural crops, and turfgrass; development and evaluation of conservative organic farming strategies; use of autonomous machines for turfgrass management and weed control with a particular focus on vineyards, assessing the effectiveness, impacts on biodiversity, soil health, and operational performance
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Actually, there is a clear need to define sustainable agronomic strategies and equipment that ensure high crop performance, reducing the risks of environmental contamination from agrochemicals overuse, greenhouse gasses emissions, and mitigating soil degradation and biodiversity loss issues. The continuous development of digitalization and automation, supported by increasingly advanced and smart sensors, guidance systems and actuators, enhances the precision, thus the effectiveness and efficiency of agricultural operations. This represents a key element in supporting the sustainable management of farming systems, with potential agronomic, environmental, and economic benefits.
The aim of this Special Issue is to invite scientists working on the use of digital technologies, robots, and smart automated tools in agricultural contexts to submit their manuscripts (i.e., Agronomists, Agricultural Engineers, Entomologists, Plant pathologists, Soil and weed Scientists, etc.). Contributions should highlight the results achieved in terms of performance and progress compared with more traditional systems, thereby showing how and to what extent these advanced technologies can support a real transition towards more sustainable agriculture.
Prof. Dr. Andrea Peruzzi
Dr. Lorenzo Gagliardi
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
- precision agriculture
- smart management systems
- machine learning
- sensors and actuators
- automation
- agricultural robotics
- site specific pest control
- challenges
- low input
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