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Precision Agriculture for the Next Generation: Linking Data, Environment, and Advanced Technologies

This special issue belongs to the section “Computer Applications and Artificial Intelligence in Agriculture“.

Special Issue Information

Dear Colleagues,

Precision agriculture leverages data-driven tools, such as remote sensing, GPS, IoT sensors, and drones, to optimize the management of crops, soil, and resources. These innovations enhance both efficiency and sustainability by tailoring inputs (e.g., water, fertilizers, pesticides) to site-specific conditions, thereby increasing yields while reducing waste and environmental impact.

This inherently interdisciplinary field brings together agricultural engineering, computer science, bioengineering, bioinformatics, and environmental science. Globally, the adoption of smart farming technologies is accelerating as these tools help address the challenges of climate change, resource scarcity, and food security. Advances in sensing technologies (e.g., UAVs and satellites), IoT networks, robotics, and artificial intelligence—including machine learning and deep learning—are transforming agriculture by enabling real-time, site-specific decision-making that enhances productivity and reduces environmental footprints.

In line with AgriEngineering’s mission as a cross-disciplinary journal at the intersection of engineering and agriculture, this Special Issue will highlight cutting-edge research that integrates phenotypic farm data and environmental conditions with next-generation technologies.

Aim of the Special Issue

This Special Issue invites contributions that present innovative precision farming systems integrating big data—including phenotypic and environmental data—with AI, machine learning, robotics, UAVs, IoT, remote sensing, and advanced analytics to improve agricultural sustainability and productivity. We seek interdisciplinary, system-level approaches from global teams that demonstrate practical and scalable solutions for smart farming. Submissions presenting field-scale implementations and real-world applications are especially encouraged.

Suggested Topics (include but are not limited to):

  • AI, machine learning, and deep learning for crop and livestock decision support;
  • Ground and aerial robotics for automated planting, harvesting, and monitoring;
  • IoT and sensor networks for real-time soil, weather, and crop analysis;
  • UAV and satellite-based remote sensing for mapping and diagnostics;
  • Integration of bioinformatics and phenotyping in breeding programs;
  • Environmental modeling and climate-resilient farming strategies;
  • Smart irrigation, fertilization, and pest control systems;
  • Case studies demonstrating the deployment of agri-tech across various regions and scales.

Article Types

We welcome high-quality Original Research Articles, Review Papers, Case/Field Studies, and Technical Notes. Submissions should present novel insights, comprehensive syntheses, or practical applications in precision agriculture, supported by reproducible methods and robust data.

We warmly invite researchers across engineering, computer science, agronomy, bioinformatics, and environmental sciences to submit manuscripts that advance the frontier of precision agriculture. By linking data, environment and technology, this Special Issue aims to chart the path toward more resilient, sustainable, and efficient agricultural systems worldwide.

Dr. Aijing Feng
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 250 words) can be sent to the Editorial Office for assessment.

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. AgriEngineering 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 1600 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 farming
  • artificial intelligence (AI)/machine learning
  • robotics
  • Internet of Things (IoT)
  • unmanned aerial vehicles (UAVs)
  • remote sensing
  • data analytics/big data
  • bioinformatics

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AgriEngineering - ISSN 2624-7402