A New Wave of Smart and Mechanized Techniques in Horticulture

Dear Colleagues,

The open access journal Horticulturae (IF: 3.0; Q1 in Horticulture) is pleased to announce that we have launched a new Special Issue titled “A New Wave of Smart and Mechanized Techniques in Horticulture”. Given your expertise in this field, we would like to invite you to contribute a paper (Review, Article, etc.) to the present Special Issue.

Over the past few decades, technological advancements have transformed agriculture, shifting from traditional manual labor to modernization, mechanization, automation, and intelligent technology. This is especially true in specialized agricultural environments like orchards and greenhouses, where labor costs are high, physical demands are significant, and timely operations are critical. In these areas, the application of automation and smart technologies is particularly relevant. From basic smart and mechanized techniques in horticulture to advanced technologies such as drone monitoring, fruit identification, and automated harvesting robots, these innovations have yielded promising results in some developed regions. Agricultural machinery is a crucial tool in enhancing production and improving economic efficiency. However, the level of mechanization in horticultural crop production varies significantly due to differences in operating processes, regional conditions, and crop varieties.

The development of mechanization technologies is heavily influenced by policy support, extension mechanisms, and technological innovations. To address these challenges, it is essential to adopt localized approaches that integrate smart agro-mechanical and agronomic solutions. This is key for advancing labor-saving technologies, improving labor productivity, and reducing production costs in horticulture.

This Special Issue aims to provide an in-depth examination of the current status and future trends in automation technologies for smart machinery (including those found in orchards and greenhouses). It will highlight how these innovations can help farmers manage their operations more efficiently, accurately, and cost-effectively. Key areas of exploration include:

(1) Cutting-edge automation and robotics technologies addressing harvesting and management challenges in orchards and facilities.

(2) Exploring the role of automation technologies in pest and disease prevention and control in orchards and facilities.

(3) Latest sensor technologies enabling growers to monitor tree health, fruit condition, and soil conditions in real time.

(4) In-depth exploration of how advanced automation technologies ensure environmentally friendly and economically sustainable agricultural practices in orchards and facilities.

(5) Use AI-driven recognition and localisation technologies (deep learning, image-processing technology, and LiDAR technology) to provide intelligent applications for orchards and facilities.

(6) Focusing on deepening the integration of smart agricultural machinery and agronomy to enhance the efficiency and adaptability of smart mechanization.

(7) Enhancing the performance and operational efficiency of agricultural machinery through smart technological innovations and sophisticated designs.

(8) Strengthening the quality and reliability of smart agricultural machinery and equipment to meet diverse agricultural production needs.

(9) Developing planting patterns and operational standards compatible with smart mechanization to achieve standardization and scalability in agricultural production.

This Special Issue will cover a number of topics of interest, including, but not limited to, the following:

• The integration of IoT-based environmental sensing and predictive modeling for dynamic control;
• The development of multi-sensor fusion systems and AI algorithms for the real-time monitoring and modeling of crop status.
• The application of multimodal sensing technologies (e.g., imaging, spectroscopy, olfaction and photoelectric sensors) combined with AI models to comprehensively increase the number of smart horticultural products.

Dr. Peng Qi
Dr. Kai Cao
Dr. Shilin Wang
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.

• agricultural mechanization

• smart farming

• computer vision

• agricultural robotics

• deep learning algorithms

• artificial intelligence

• multimodal sensing

• mechanized planting

• intelligent agricultural robot

• integration of agricultural machinery and agronomy