Precision Management Strategies for Orchards and Vineyards
A special issue of Horticulturae (ISSN 2311-7524). This special issue belongs to the section "Fruit Production Systems".
Deadline for manuscript submissions: 31 January 2026 | Viewed by 13
Special Issue Editors
Interests: remote sensing; precision viticulture; unmanned aerial vehicles; crops variability; vegetation indices; deep learning; object-based image analysis; machine learning; horticulture; spatial variability; mapping; crop nutritional status; grapevine modelling
Special Issue Information
Dear Colleagues,
We are pleased to announce a forthcoming Special Issue dedicated to the application of precision agriculture in orchard and vineyard systems. The aim is to gather original research and review articles that explore how innovative, data-driven approaches enhance the sustainability and performance of tree crop production.
Precision orchard management increasingly relies on the integration of advanced technologies to effectively capture spatial and temporal variability. Tools such as remote and proximal sensing, plant-based sensors, computer vision, and crop modeling contribute to a more informed and adaptive management of fruit trees and vineyards. These technologies enable the assessment of key physiological indicators, such as plant vigor and nutrient or water status, and support timely decisions throughout the growing season. A comprehensive approach also involves soil characterization, multivariate analysis, and the delineation of site-specific management zones, allowing for a more precise allocation of inputs and resources.
Of particular interest are contributions employing data fusion strategies and machine or deep learning techniques to integrate multisource datasets and support operational decision-making. Relevant topics include yield and quality estimation, early stress detection, and the implementation of digital platforms for precision horticulture.
By showcasing scalable and effective solutions, this Special Issue fosters innovation and supports the transition toward more resilient and resource-efficient orchard and vineyard systems.
Dr. Massimo Ferro
Prof. Dr. Pietro Catania
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 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. Horticulturae 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 2200 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
- precision viticulture
- remote sensing
- proximal sensors
- machine learning and deep learning for orchard management
- fertilization management
- fruit tree and grapevine stress tolerance
- variable rate application
- precision irrigation
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