Machine Vision Applications in Crop Harvesting and Quality Control
A special issue of AgriEngineering (ISSN 2624-7402).
Deadline for manuscript submissions: 15 March 2026 | Viewed by 95
Special Issue Editors
Interests: machine learning; image recognition; precision agriculture; remote sensing technology and methods; crop growth monitoring; nutrition diagnosis; crop nutrient management
Interests: machine vision; machine learning; pattern recognition
Special Issues, Collections and Topics in MDPI journals
Interests: precision agriculture; remote sensing; crop monitoring; machine learning; crop model; unmanned aerial vehicle; satellite; image processing
Interests: remote sensing; precision agriculture; deep learning; crop model; crop mapping
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The Special Issue "Machine Vision Applications in Crop Harvesting and Quality Control" explores cutting-edge advancements in automated agricultural technologies, focusing on the integration of machine vision systems to enhance efficiency and precision in crop harvesting and post-harvest quality assessment. Contributions highlight innovative approaches such as deep learning, hyperspectral imaging, and robotic automation for tasks including fruit/vegetable detection, yield estimation, defect identification, and grading. These technologies address critical challenges in modern agriculture, such as labor shortages, resource optimization, and sustainability, by enabling real-time, non-destructive monitoring and decision-making. This Special Issue also emphasizes the development of scalable solutions tailored to diverse crops and environments, from field-based robotic harvesters to AI-driven quality control systems in processing facilities. By bridging the gap between theoretical research and practical implementation, this collection aims to accelerate the adoption of smart farming practices, ultimately improving productivity, reducing waste, and ensuring food security in a rapidly evolving agricultural landscape.
We look forward to receiving your contributions.
Dr. Ke Zhang
Dr. Xiaodong Bai
Dr. Jiayi Zhang
Dr. Jibo Yue
Guest Editors
Manuscript Submission Information
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Keywords
- AI
- image interpretation
- precision agriculture
- remote sensing
- crop yield and quality
- machine vision
- crop harvesting
- quality control
- image processing
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