Intelligent Detection and Classification of External Traits in Crop Plants, Fruits, and Vegetables
A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Precision and Digital Agriculture".
Deadline for manuscript submissions: 31 July 2025 | Viewed by 867
Special Issue Editors
Interests: quality and safety assessment of agricultural products; harvesting robots; robot vision; robotic grasping; spectral analysis and modeling; robotic systems and their applications in agriculture
Special Issues, Collections and Topics in MDPI journals
2. Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, Shenzhen 518000, China
Interests: computer vision; deep learning; brain-inspired computing; edge computing; remote sensing; agricultural engineering; smart agriculture; precision agriculture; agricultural aviation; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Interests: digital agriculture; agriculture 4.0; computer image analysis; digital classification of agricultural and horticultural products; remote sensing and telematics in agriculture and horticulture; precision technologies in agriculture and horticulture; autonomous robots and drones in agriculture; smart greenhouses; internet of things in agriculture
Interests: agricultural biotechnology; plant genetics; 3D plant phenotyping; resistance breeding; application of molecular tools and convolutional neural network for variety classification and seed quality assessment
Special Issue Information
Dear Colleagues,
A technological revolution is currently taking place in agriculture, termed 'Agriculture 4.0'. Modern, intelligent solutions are being introduced, mainly based on the digitalization of production processes and the classification and qualitative assessment of agricultural crops, fruit, and vegetables. The basis of these intelligent solutions is artificial intelligence (AI), which allows for the modeling, simulation, and prediction of complex agricultural processes, especially in the case of complex relationships between variables related to weather and agrotechnical conditions. Intelligent solutions are extremely helpful for extracting quality characteristics of agricultural products based on shape, color, texture, and light spectrum. Digital techniques and methods provide new knowledge that can be applied to control the quality of food and agricultural products with high accuracy. Texture, shape, and color characteristics of agricultural products are used to detect damaged apple or orange areas, weeds, and pests. Computer image analysis has become one of the main techniques used in agriculture to assess seeds and grains in terms of quality losses, quantifying their degree of mechanical damage, maturity stage, disease infestation, or contamination with other plant species.
In this Special Issue, we aim to exchange knowledge on precision agriculture, the use of computer systems in agricultural production, the application of artificial neural networks and image analysis for qualitative and quantitative classification of field crops, vegetables, and fruit, and the use of genetic algorithms to manage machinery and evaluate its efficiency.
Dr. Baohua Zhang
Dr. Yuxing Han
Prof. Dr. Piotr Rybacki
Prof. Dr. Janetta Niemann
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. 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
- artificial intelligence
- neural networks
- image analysis
- qualitative classification
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