Precision Management Methods for High Yield and Quality in Horticultural Crops
A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Horticultural and Floricultural Crops".
Deadline for manuscript submissions: 31 March 2026 | Viewed by 2
Special Issue Editor
Interests: precision viticulture; spectral imaging; stress physiology; analysis of valuable ingredients of horticultural crops
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Horticultural crops and their secondary metabolites are important components of a healthy diet. Climate change poses the risk of disrupting production, which harms both farmers and consumers. While high yields are necessary to meet public demand, product quality is crucial for taste, nutrients, and shelf life. Modern techniques therefore help optimize both.
This Special Issue aims to demonstrate precise management methods that maximize the yields and quality of horticultural crops. Using modern technologies such as sensors, data analytics, and automated control systems allows farmers to tailor their irrigation, fertilization, and crop protection measures precisely to the needs of their plants. This results in the more efficient use of resources, increased crop yields, and improved product quality. This issue also aims to demonstrate methods that can improve shelf life. Overall, it will highlight the status of precise management as a promising approach to promoting sustainable, high-quality cultivation in the horticulture industry.
This Special Issue encourages the submission of studies and review articles documenting recent advances in horticulture through remote sensing and smart field monitoring. Particular emphasis will be placed on the development of novel methods and applications based on remote sensing data, with topics of interest including, but not limited to, the following:
- Monitoring horticultural vegetation using unmanned aerial vehicles (UAVs), aerial data, and satellite data;
- Vitality mapping and site-specific applications;
- Time-series and multi-temporal field horticulture analysis;
- Digital image processing;
- Computer vision;
- Machine learning methods;
- Precision horticulture methods;
- Advances in near-field sensing, including the use of image sensors;
- Estimation and mapping of water status, irrigation needs, and phytosanitary problems.
Dr. Nikolaus Merkt
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. 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
- precision horticulture
- horticulture management
- horticulture mapping and classification
- machine and deep learning
- decision support
- yield prediction
- estimation of biophysical and geometrical parameters
- intelligent monitoring
- multi-temporal analysis
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