Enhancing Crop Productivity Through Precision Agriculture Technologies
A special issue of Plants (ISSN 2223-7747). This special issue belongs to the section "Plant Modeling".
Deadline for manuscript submissions: 31 December 2026 | Viewed by 121
Special Issue Editors
Interests: seed; smart agriculture; modern agriculture
Interests: plant phenotyping; imaging and computer vision; machine learning; deep learning; genomic- phenomics studies
Interests: near-infrared hyperspectral imaging; algorithm; deep learning; machine vision; pattern recognition; image processing; spectral detection technology
2. Agrotecnio-CERCA Center, Lleida, Catalonia, Spain
Interests: precision agriculture; fruit; fruit orchards; low-cost monitoring systems; sensors; climate; soil; rootstock
Special Issue Information
Dear Colleagues,
Against the backdrop of global population growth, climate change and growing food security challenges, traditional agricultural models are facing bottlenecks in improving crop productivity and resource utilization efficiency. Precision agriculture technologies, integrating modern breeding, digital management and intelligent regulation, have become the core driving force for sustainable and efficient crop production. This Special Issue aims to collect cutting-edge original research and comprehensive reviews on the application of precision agriculture technologies in the whole chain of crop production, focusing on precision crop breeding, seed vigor precise regulation, intelligent field management, digital agricultural monitoring, crop stress resistance regulation and efficient agricultural resource utilization. We hope to build an academic exchange platform for innovative technologies to enhance crop productivity and provide theoretical and technical support for the green, high-yield and efficient development of modern crop production.
Dr. Yang Wang
Dr. Frank Gyan Okyere
Dr. Liangquan Jia
Dr. Gemma Reig
Guest Editors
Manuscript Submission Information
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Keywords
- precision agriculture
- crop productivity
- smart farming
- crop breeding
- seed vigor
- digital agriculture
- field management
- crop stress resistance
- sustainable crop production
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