Data-Driven Agricultural Innovations
A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Precision and Digital Agriculture".
Deadline for manuscript submissions: closed (15 October 2021) | Viewed by 44395
Special Issue Editor
Interests: artificial intelligence; pattern recognition; computer vision; machine learning; computational science; data science; digital agriculture; agroinformatics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The agricultural sector has a rich history of innovations and adoption of novel technologies for productivity increase, risk reduction, and sustainability improvement. There is a growing trend of digital and communications technology uptake by farmers and policy makers alike to address issues that have arisen due to climate change, scarcity of resources, rising global population, disruption of supply chains by the pandemic and by natural disasters, etc., which can hamper efficiency and significantly impact business models in the agricultural sector. The opportunities are numerous, but they also come with new challenges.
In both industry and academia, new research and development projects have been proposed and undertaken to address some of these issues. Innovations including monitoring and controlling crop irrigation systems via smartphone, crop sensors, livestock farming technology, farm automation, indoor vertical farming, modern greenhouses, precision agriculture, blockchain, and artificial intelligence have all benefited the agricultural sector. One characteristic that these technologies have in common is the importance of “data” in driving success in achieving their proposed benefits.
This Special Issue will cover “Data-Driven Agricultural Innovations” across different data scales and resolutions. Contributions are welcome to address key issues in data collection, (big) data analysis, data storage, data management, and data transfer and sharing through applying scientific approaches and methodologies from multiple disciplines, including Artificial Intelligence, machine learning, computer vision, data science, geographical information system, remote sensing, crop science, horticulture, and animal science, to name a few.
Prof. Dr. Paul Kwan
Guest Editor
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
- agriculture
- agronomy
- artificial intelligence
- data science
- information systems
- robotics
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