{"id":94,"date":"2019-04-03T18:19:12","date_gmt":"2019-04-03T18:19:12","guid":{"rendered":"https:\/\/cafnrfaculty.missouri.edu\/mupaa\/?page_id=94"},"modified":"2024-11-06T04:48:45","modified_gmt":"2024-11-06T04:48:45","slug":"jing","status":"publish","type":"page","link":"https:\/\/cafnrfaculty.missouri.edu\/mupaa\/jing\/","title":{"rendered":"z_old_JING ZHOU"},"content":{"rendered":"

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.<\/p><\/blockquote>\n

CURRENT PROJECT<\/h4>\n
    \n
  1. \u00a0 Automated phenotyping platform in greenhouse<\/span><\/a><\/span><\/li>\n
  2. Discrimination of Soybean Leaf Wilting due to Drought Stress Using UAV-Based phenotyping<\/span><\/a><\/li>\n<\/ol>\n

    PUBLICATION<\/h4>\n
      \n
    • 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.<\/li>\n
    • 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.<\/li>\n
    • 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.<\/li>\n<\/ul>\n

      PRESENTATIONS<\/h4>\n
        \n
      • 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.<\/li>\n
      • 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.<\/li>\n<\/ul>\n

        WORKING PHOTOS<\/p>\n

        \"\" \u00a0 \u00a0 \u00a0 \u00a0\u00a0 \"\"<\/p>\n","protected":false},"excerpt":{"rendered":"

        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. […]<\/p>\n","protected":false},"author":44,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"page.php","meta":{"footnotes":""},"class_list":["post-94","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/cafnrfaculty.missouri.edu\/mupaa\/wp-json\/wp\/v2\/pages\/94","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/cafnrfaculty.missouri.edu\/mupaa\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/cafnrfaculty.missouri.edu\/mupaa\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/cafnrfaculty.missouri.edu\/mupaa\/wp-json\/wp\/v2\/users\/44"}],"replies":[{"embeddable":true,"href":"https:\/\/cafnrfaculty.missouri.edu\/mupaa\/wp-json\/wp\/v2\/comments?post=94"}],"version-history":[{"count":6,"href":"https:\/\/cafnrfaculty.missouri.edu\/mupaa\/wp-json\/wp\/v2\/pages\/94\/revisions"}],"predecessor-version":[{"id":543,"href":"https:\/\/cafnrfaculty.missouri.edu\/mupaa\/wp-json\/wp\/v2\/pages\/94\/revisions\/543"}],"wp:attachment":[{"href":"https:\/\/cafnrfaculty.missouri.edu\/mupaa\/wp-json\/wp\/v2\/media?parent=94"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}