Modelling for Prediction of Horticultural Plant Growth and Defense—2nd Edition
A special issue of Plants (ISSN 2223-7747). This special issue belongs to the section "Plant Modeling".
Deadline for manuscript submissions: 31 May 2026
Special Issue Editor
Interests: applied mathematical modelling of plant physiology; biological dynamical systems; stochastic differential equations; Bayesian inference; signal processing; decision theory; optimisation and control
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Data-driven precision horticulture is transforming the way we understand and manage plant systems. Advances in monitoring technologies and computational modelling provide new opportunities to enhance productivity and product quality in horticultural systems, while navigating increasingly strict environmental and legislative constraints. The rapid progress in sensor networks, remote and proximal sensing, and data analytics has made it feasible to construct complex models that integrate biological mechanisms of plants with environmental dynamics and management practices.
This Special Issue of Plants focuses on novel developments and applications of descriptive, predictive, and prescriptive models in two key domains:
- Plant growth: Innovations in factor identification, dynamic modelling, forecasting, and impact analysis related to growth processes such as ageing, crop load, yield, dormancy, flowering, and nutrition.
- Plant defence: Advances in modelling and analysing natural defence mechanisms against diseases and pests, including system dynamics, multi-scale interaction analysis among plants, pests, biocontrols, and the environment, as well as decision-support tools for Integrated Pest Management (IPM).
The contributions in this issue span multiple modelling paradigms, from mechanistic and physiological models to data-centric approaches leveraging machine learning and artificial intelligence. Collectively, these studies illustrate the expanding role of modelling in understanding complex plant–environment interactions and supporting evidence-based management in modern horticultural systems.
Dr. Maryam Alavi-Shoshtari
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 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. Plants 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 2700 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 horticulture
- growth or defence mechanisms in plants
- artificial intelligence (AI) in horticulture
- machine learning (ML) for plant systems
- computational biology
- plant–environment system dynamics
- monitoring and forecasting in horticultural systems
- decision-support tools for horticultural inventory management
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