I am now doctoral student in Bioengineering at the University of Missouri. I received my B.S. in Agricultural Mechanization and its Automation from Nanjing Agricultural University in 2013 and my master in Agricultural Engineering in 2015. In 2017, I joined the Precision Automated Agricultural Lab and I am working on High-throughput phenotyping for soybean breeding.
CURRENT PROJECT
- Automated phenotyping platform in greenhouse
- Discrimination of Soybean Leaf Wilting due to Drought Stress Using UAV-Based phenotyping
PUBLICATION
- Zhou, J., X. Fu, S. Zhou, J. Zhou*, H. Ye, H. Chen, and H. Nguyen. 2019. Automated segmentation of soybean plants in greenhouse from 3D imagery point cloud using machine learning methods. Computers and Electronics in Agriculture. In Review.
- Zhou, J., X. Fu, L. Schumacher, and J. Zhou*. 2018. Evaluating geometric measurement accuracy based on 3D reconstruction of automated imagery in greenhouse. Sensors. 18(7), 2270-2286. DOI: https://doi.org/10.3390/s18072270.
- Zhou, J., Chen, H., Zhou, J., Fu, X., Ye, H., & Nguyen, H. T. (2018). Development of an automated phenotyping platform for quantifying soybean dynamic responses to salinity stress in greenhouse environment. Computers and Electronics in Agriculture, 151, 319-330.
PRESENTATIONS
- Zhou, J., H. Ye, M. L. Ali, H. Nguyen, and J. Zhou*. 2019. Discrimination of soybean leaf wilting due to drought stress using UAV-based imaging. 2019 IBE Annual Conference, St. Louis, MO, April 4 -6, 2019.
- Zhou, J., X. Fu, S. Zhou, and J. Zhou*. 2018. Evaluation of the performance of machine learning methods in soybean segmentation for image-based high-throughput phenotyping in greenhouse. ASABE Paper No. 1801362. St. Joseph, MI.: ASABE.
WORKING PHOTOS
