An Automated Field Phenotyping Pipeline for Application in Grapevine Research
Abstract
:1. Introduction
2. Material and Methods
2.1. Plant Material
2.2. Automated Image Acquisition
2.3. Data Management
2.4. Image Analysis
2.5. Statistical Analysis
3. Results and Discussion
3.1. Field Application of the Phenotyping Robot
3.2. Image Analysis
Real Color Classes | |||||
---|---|---|---|---|---|
Predicted Color Classes | Black | Green | Grey | Red | Rose |
black | 197 | 7 | 2 | 5 | 3 |
green | 5 | 178 | 7 | 0 | 0 |
grey | 0 | 15 | 28 | 2 | 3 |
red | 0 | 0 | 1 | 26 | 13 |
rose | 0 | 0 | 1 | 4 | 3 |
3.3. Future Work
4. Conclusions
Acknowledgments
Author Contributions
Appendix
Conflicts of Interest
References
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Kicherer, A.; Herzog, K.; Pflanz, M.; Wieland, M.; Rüger, P.; Kecke, S.; Kuhlmann, H.; Töpfer, R. An Automated Field Phenotyping Pipeline for Application in Grapevine Research. Sensors 2015, 15, 4823-4836. https://doi.org/10.3390/s150304823
Kicherer A, Herzog K, Pflanz M, Wieland M, Rüger P, Kecke S, Kuhlmann H, Töpfer R. An Automated Field Phenotyping Pipeline for Application in Grapevine Research. Sensors. 2015; 15(3):4823-4836. https://doi.org/10.3390/s150304823
Chicago/Turabian StyleKicherer, Anna, Katja Herzog, Michael Pflanz, Markus Wieland, Philipp Rüger, Steffen Kecke, Heiner Kuhlmann, and Reinhard Töpfer. 2015. "An Automated Field Phenotyping Pipeline for Application in Grapevine Research" Sensors 15, no. 3: 4823-4836. https://doi.org/10.3390/s150304823
APA StyleKicherer, A., Herzog, K., Pflanz, M., Wieland, M., Rüger, P., Kecke, S., Kuhlmann, H., & Töpfer, R. (2015). An Automated Field Phenotyping Pipeline for Application in Grapevine Research. Sensors, 15(3), 4823-4836. https://doi.org/10.3390/s150304823