Precision Farming Applied to Grazing Lands
A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Grassland and Pasture Science".
Deadline for manuscript submissions: 28 February 2026 | Viewed by 61
Special Issue Editors
Interests: precision agriculture; mapping; GIS analysis; image processing; sensor design; agricultural engineering; advanced machine learning
Special Issue Information
Dear Colleagues,
The global population increase and concerns about food security highlight the urgent need for improvements in agricultural efficiency. Grazing lands play a crucial role in sustaining agricultural systems. Therefore, adopting enhanced management practices in these areas is vital for their long-term sustainability. Data collection is essential for informing management decisions. However, current labor shortages in agricultural fields emphasize the need for innovative technologies that can facilitate large-scale data collection and enable timely decision-making in grazing lands.
Emerging technologies, such as remote sensing, proximal sensors, the Internet of Things (IoT), artificial intelligence (AI), machine learning (ML), and cloud computing, are now being used to collect and analyze data across various agricultural systems. These technologies can support better decision-making in grazing management. While significant advances have been made in precision agriculture for crop fields, research specifically targeting grazing lands, such as rangelands and grasslands, remains limited.
We invite cutting-edge research on precision farming in grazing lands, including grazable croplands, forestlands, grasslands, and rangelands. We welcome short communications, original research, and literature review papers on this topic. Submissions that contribute to developing new tools, such as programming scripts (e.g., Python or R), GIS plugins, decision-making tools, software, and apps for image analysis, data automation, and on-farm implementation of new technologies, are strongly encouraged.
This Special Issue requests papers exploring new technologies applied to, but not limited to, the following areas: biomass estimation, canopy height and forage nutritive value predictions, weed detection and control, botanical composition classification, soil monitoring, precision fertilization, and grazing management.
Prof. Dr. Domingos Sarvio Valente
Guest Editor
Dr. Igor L. Bretas
Guest Editor Assistant
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
- biomass
- canopy height
- fertilization
- forages
- decision tools
- digital technologies
- grassland management
- grazing management
- nutritive value
- rangelands
- weed control
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