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Precision Farming Practices for Sustainable Plant Protection

A Special Issue of Sustainability (ISSN 2071-1050) belonging to the section "Sustainable Agriculture".

Deadline for manuscript submissions: closed (12 July 2026) | Viewed by 1331

Editors


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Guest Editor
Department of Organic Agriculture and Environmental Protection, Institute of Plant ProtectionJakubowskaNational Research Institute, Władysława Węgorka 20, 60-318 Poznan, Poland
Interests: organic agriculture; sustainable agriculture; precision agriculture; biocontrol

E-Mail Website
Guest Editor
Department of Organic Agriculture and Environmental Protection, Institute of Plant Protection—National Research Institute, 60-318 Poznań, Poland
Interests: organic agriculture; sustainable agriculture; precision agriculture; biocontrol
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Monitoring and Signalling of Agrophages, Institute of Plant Protection–National Research Institute, 20 Władysława Węgorka, 60-318 Poznań, Poland
Interests: agrophages; pests control; integrated plant protection (decision support systems; IPM); biodiversity; traps/sensors; abiotic condition
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The growing demand for sustainable agriculture calls for innovative precision farming technologies that protect crops from biotic and abiotic stress while minimizing environmental impact. Breakthroughs in nanotechnology, small drones, the Internet of Things (IoT), sensors, mobile applications, and robotics are transforming plant protection, enabling targeted interventions and real-time monitoring.

This Special Issue, ‘Precision Farming Practices for Sustainable Plant Protection’, aims to explore new research in precision agriculture and its role in sustainable plant health management. We welcome submissions that present novel methodologies, experimental case studies, and comprehensive reviews that advance this field.

Potential themes include, but are not limited to, the following:

  • The applications of nanotechnology in plant protection.
  • The roles of IoT and smart sensors in real-time crop health monitoring.
  • The use of small unmanned aerial vehicles for pest and disease management.
  • The integration of robotics and autonomous vehicles in plant protection.
  • GPS-guided equipment and VRT applications in precision agriculture.
  • AI-based crop disease detection models and predictive analytics.
  • Advances in remote sensing for plant stress and pathogen monitoring.

We look forward to receiving your valuable contributions.

Dr. Joanna Krzymińska
Prof. Dr. Jolanta Kowalska
Dr. Magdalena Jakubowska
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 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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly 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 2400 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

  • plant protection
  • precision farming
  • precision agriculture. nanotechnology
  • IoT
  • drones
  • robotics
  • autonomous vehicles
  • detection models
  • remote sensing

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Published Papers (1 paper)

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Review

45 pages, 3600 KB  
Review
Application of Artificial Intelligence and Machine Learning in Vertical Farming: A Comprehensive Review
by Mi Young Kim, Geunwoo Park and Chang Ho Seo
Sustainability 2026, 18(16), 8261; https://doi.org/10.3390/su18168261 - 12 Aug 2026
Viewed by 644
Abstract
Vertical farming (VF) offers a smart way to grow crops in stacked layers inside controlled indoor environments. By doing so, it uses far less land and water than traditional open-field agriculture, making it a promising solution for cities with limited space and resources. [...] Read more.
Vertical farming (VF) offers a smart way to grow crops in stacked layers inside controlled indoor environments. By doing so, it uses far less land and water than traditional open-field agriculture, making it a promising solution for cities with limited space and resources. In recent years, artificial intelligence (AI), machine learning (ML), and Internet of Things (IoT) technologies have begun to transform vertical farming. These tools are moving the industry away from rigid, rule-based systems toward more flexible, data-driven operations that can adapt in real time. This paper presents a systematic review of 208 peer-reviewed studies from 2015 to 2025. It explores how AI, ML, and IoT are applied across the VF ecosystem, focusing on key areas such as computer vision for disease detection, crop growth and yield prediction, smart climate control, and precision nutrient and irrigation management. This review examines the performance of different algorithms, including Convolutional Neural Networks (CNNs), Random Forest, XGBoost, and LSTMs across hydroponic, aeroponic, and aquaponic systems. The review also covers IoT setups with multi-sensor networks, edge-cloud computing, and automated control systems. Commercial farms have shown real gains in resource efficiency and shorter supply chains. However, challenges remain: high energy use (especially from LED lighting, which makes up 40–60% of costs), expensive setup, scattered datasets, and limited real-world testing. Many high-accuracy claims (>95%) come from lab conditions and need better validation in actual farms. Overall, AI-powered vertical farming has strong potential to support resilient urban food systems. Future work should focus on lightweight edge AI models, improved data standards, explainable AI, and robust life cycle assessments to ensure the benefits outweigh the environmental and economic costs. Full article
(This article belongs to the Special Issue Precision Farming Practices for Sustainable Plant Protection)
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