Sensing and AI Technologies for Orchard Management and Postharvest Fruit Monitoring
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Smart Agriculture".
Deadline for manuscript submissions: 31 December 2026 | Viewed by 134
Special Issue Editors
Interests: postharvest fruit treatments; physiological disorders of fruits in storage; the effect of preharvest factors on postharvest behavior of fruit; fruit quality; nondestructive methods of fruit quality determination; introduction of less known fruit species
Special Issues, Collections and Topics in MDPI journals
Interests: proximal soil sensors; precision agriculture; smartphone image-based soil characterization; portable X-ray fluorescence spectrometer; diffuse reflectance spectroscopy; cost-effective optical soil sensors
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The integration of sensor technologies and artificial intelligence is transforming both orchard management and postharvest fruit monitoring, offering new opportunities for efficiency, sustainability, and quality assurance. In orchards, advanced sensors and AI-driven decision support systems enable precise monitoring of plant growth, stress and health, as well as accurate fruit recognition, yield estimation and maturity prediction. During the postharvest phase, these technologies enable non-destructive quality assessment, support automated sorting processes, and improve logistics management, ensuring that fruit quality remains consistent and reducing losses throughout the supply chain.
This Special Issue presents cutting-edge research and practical innovations that utilise sensor and AI solutions throughout the fruit production process, from the orchard to the postharvest phase. Topics of interest include computer vision, multispectral and hyperspectral imaging, LiDAR, robotics, IoT-based sensor networks and UAV applications, multimodal sensor data fusion, real-time decision-support systems, sustainability metrics for smart orchard management, as well as machine learning and deep learning approaches for data analysis and predictive modelling.
We are seeking original papers, case studies and reviews from the fields of horticulture, agronomy, food technology, computer science and engineering. By linking the fields of fruit growing and postharvest, we aim to promote interdisciplinary collaboration and further the development intelligent, sustainable fruit production systems.
Prof. Dr. Tomislav Jemrić
Dr. Somsubhra Chakraborty
Guest Editors
Manuscript Submission Information
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Keywords
- orchard management
- postharvest monitoring
- fruit quality assessment
- sensing technologies
- precision horticulture
- machine learning
- UAV
- hyperspectral imaging
- smart agriculture
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