Integrating Yield Maps, Soil Data, and IoT for Smarter Farming
A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Precision and Digital Agriculture".
Deadline for manuscript submissions: 28 February 2026 | Viewed by 83
Special Issue Editor
Interests: precision agriculture; management zones; geostatistics; smart farms
Special Issue Information
Dear Colleagues,
The integration of yield maps, soil data, and Internet of Things (IoT) technologies is a crucial tool in precision agriculture (PA), allowing for smarter, data-driven farming practices that optimize crop yields, resource utilization, and sustainability. Recent research has demonstrated that integrating real-time sensor networks, advanced data analytics, and machine learning models enables the precise monitoring of soil health, crop growth, and environmental conditions, ultimately leading to enhanced decision-making and operational efficiency.
Agriculture 4.0 emerged in the early 2010s, driven by the adoption of the IoT, sensors, and data analytics for PA; next, Agriculture 5.0 was conceptualized in the late 2010s and early 2020s, with implementation still in its early stages, integrating advanced technologies like artificial intelligence and robotics, with a stronger emphasis on sustainability, human-centric design, and social impact. Cutting-edge research demonstrates that integrating yield maps, soil data, and IoT technologies into machine learning enables smarter, more sustainable farming practices. These technologies deliver real-time insights, optimize resources, and significantly improve crop yields; however, further research and broader adoption are needed to maximize their full impact.
This Special Issue aims to promote advances in modeling and integrating yield maps, soil data, and IoT for Agriculture 4.0 and 5.0. We invite you to submit articles on these subjects.
It is our great pleasure to invite you to submit articles on this Special Issue "Integrating Yield Maps, Soil Data, and IoT for Smarter Farming", which aims to bring together the application of the State of the Art in IoT sensors and data collection, yield mapping, and soil data analysis, as well as machine learning and predictive analytics.
We look forward to receiving your contributions!
Prof. Dr. Eduardo Godoy de Souza
Guest Editor
Manuscript Submission Information
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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
- smart IoT-driven
- precision agriculture
- land mapping
- crop prediction
- productivity maps
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