Phenotyping Technologies for Resistance Screening, Crop Breeding and Precision Agriculture
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Agriculture and Vegetation".
Deadline for manuscript submissions: closed (1 December 2023) | Viewed by 17297
Special Issue Editors
Interests: smart urban agriculture; artificial intelligence; agricultural robotics; automated control; unmanned aerial vehicle; plant phenotyping; computer vision; crop plant signaling; machine (deep) learning; food processing and safety; fluorescence imaging; hyper/multispectral imaging; Vis/NIR/MIR imaging spectroscopy
Special Issues, Collections and Topics in MDPI journals
Interests: precision agriculture; proximal and remote sensing; precision nitrogen management; integration of crop growth modeling; remote sensing and machine/deep learning; integrated precision crop management; food security and sustainable development
Special Issues, Collections and Topics in MDPI journals
Interests: crop yield prediction and phenotyping
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Climate change poses a great threat to sustainable food production worldwide, but the rapid growth of human demand for foods requires that plant yields have to continue to increase each year. The optimization of soil management, early diagnosis of crop diseases, and breeding of resistant cultivars are the keys to increasing global food production. Phenotyping technologies, from proximal to remote sensing, allow for rapid monitoring of orchards or crops at different scales, including single leaf, individual plant, and field, thereby informing the genetics of plant traits such as growth, development, resistance, architecture, physiology, and nutrients.
This Special Issue is looking for studies covering different phenotyping technologies such as RGB imaging, fluorescence imaging, multi/hyperspectral imaging, and related platforms to provide important information about how environmental stress, genetics, and precision management guide the selection of productive plants.
Topics may cover anything on the automatic identification and assessment of plant traits, including stress tolerance (e.g., biotic and abiotic stresses), chemical aspects (e.g., nutrients, secondary metabolites), and structural and functional aspects such as leaf characteristics, plant height, photosynthetic efficiency, root morphology, fruit traits, biomass, and yield, from individual plant organs to full fields. Hence, different sensing techniques and multiple scales of phenotyping platforms (e.g., ground vehicles, unmanned aerial vehicles, and satellites) or studies focused on resistance screening, crop breeding, precision agriculture and other related issues are welcome. Articles may address, but are not limited to, the following topics:
- Remote sensing applications for precision agriculture;
- Assessment of plant growth status;
- Crop nutrient management;
- Nitrogen management;
- Plant phenotypes;
- Plant instance detection;
- Resistance of plants to biotic and abiotic stresses;
- Smart sensing, monitoring, and control
- Smart breeding;
- Smart farming.
Dr. Wen-Hao Su
Dr. Yuxin Miao
Dr. Zhou Zhang
Guest Editors
Manuscript Submission Information
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Keywords
- sustainable agriculture
- proximal and remote sensing techniques
- phenotyping sensors
- non-destructive measurements
- high-throughput screening
- plant stress responses
- nutrient, weed and disease diagnosis
- computer vision
- deep learning
- image processing
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