Application of Machine Learning and Modelling in Food Crops
A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Precision and Digital Agriculture".
Deadline for manuscript submissions: 31 December 2025 | Viewed by 97
Special Issue Editors
Interests: remote sensing; unmanned aerial vehicles; precision viticulture; precision agriculture; multi-temporal analysis; spectral imaging; machine learning
Special Issues, Collections and Topics in MDPI journals
Interests: crop modelling; model–data integration; GHG emission; climate impact assessment; climate-smart agriculture; crop phenotyping
Interests: crop modelling; agriclimatology; climate impact assessment; climate change adaptation; agro-environmental impacts
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
With the increasing demand for sustainable food production and the challenges posed by climate change, agriculture is undergoing a digital transformation. The integration of machine learning (ML) into agricultural science is revolutionising the way in which we monitor, predict and manage crop productivity, offering data-driven solutions to improve agronomic efficiency, sustainability and resilience.
This Special Issue aims to explore the latest advancements in the applications of ML and computational modelling (including process-based crop modelling) for agricultural crops in relation to remote sensing, Internet of Things (IoT), crop phenotyping, resource optimisation, climate impact assessment and adaptation strategies, pest and disease control, and AI-driven decision support systems, among others. Submissions adopting an innovative interdisciplinary approach across these areas are particularly encouraged, including novel studies that make use of data science to improve monitoring and predictions for crop growth and yield, improve crop management practices, and support crop breeding and policy formulation. Researchers and practitioners are invited to share their results and latest progress in this rapidly evolving field, contributing to the development of intelligent, sustainable and resilient cropping systems.
We look forward to your valuable contributions.
Dr. Luís Filipe Machado Pádua
Prof. Dr. Bing Liu
Guest Editors
Dr. Chenyao Yang
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
- crop production and management
- machine learning
- deep learning
- crop modelling
- Internet of Things (IoT)
- big data
- smart agriculture
- precision farming technologies
- sensor-based crop monitoring
- model-based decision support systems
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