Research on the Innovation of Smart Cultivation Technology for Fruit Trees and the Construction of Growth Models
A special issue of Horticulturae (ISSN 2311-7524). This special issue belongs to the section "Fruit Production Systems".
Deadline for manuscript submissions: 31 December 2026 | Viewed by 138
Special Issue Editors
Interests: grape; stress; cultivation; fruit quality; maturation
Special Issues, Collections and Topics in MDPI journals
Interests: climate change; agricultural sustainability; circular economy; soil, water and biodiversity conservation; remote sensing; plant breeding; ecosystem services; olive growing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The fruit tree industry, as a pillar sector of the global agricultural economy, plays an irreplaceable role in ensuring food security, optimizing dietary nutrition, and promoting rural revitalization. However, traditional cultivation models face challenges such as labor shortages and high post-harvest loss rates, which are at odds with consumers' upgraded demand for high-quality fruits. Against this backdrop, intelligent technologies centered around the Internet of Things, artificial intelligence, and big data, along with growth models that are deeply integrated with the physiological mechanisms of fruit tree growth, have become the core engine for addressing the industry's pain points.
To systematically organize the innovative achievements in the field of intelligent cultivation and growth models for fruit trees and to build a bridge between academic research and industrial application. This Special Issue invites original research papers, reviews, technical briefs, etc., in the field of intelligent cultivation and growth models for fruit trees from around the world. Specific topics include but are not limited to: intelligent perception technologies for fruit trees (multimodal sensors, AI phenotype recognition, data fusion, etc.); automation and precision operation equipment (functional robots, intelligent water and fertilizer systems, etc.); construction and optimization of growth models (coupled models, quality simulation, etc.); digital management systems (decision support systems, etc.); and the industrial application and benefit evaluation of intelligent technologies.
We sincerely invite researchers and technical promotion experts to submit their work to collaboratively create a high-end platform that showcases cutting-edge achievements, promotes academic exchange, and fosters industrial collaboration.
Dr. Qian Zha
Dr. Georgios Koubouris
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-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
- intelligent cultivation of fruit trees
- growth model construction
- intelligent sensing technology
- precision operation equipment
- digital management
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