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Full-Text Articles in Plant Sciences
Interactive Effects Of The Co2 Enrichment And Nitrogen Supply On The Biomass Accumulation, Gas Exchange Properties, And Mineral Elements Concentrations In Cucumber Plants At Different Growth Stages, Xun Li, Jinlong Dong, Nazim S. Gruda, Wenying Chu, Zengqiang Duan
Interactive Effects Of The Co2 Enrichment And Nitrogen Supply On The Biomass Accumulation, Gas Exchange Properties, And Mineral Elements Concentrations In Cucumber Plants At Different Growth Stages, Xun Li, Jinlong Dong, Nazim S. Gruda, Wenying Chu, Zengqiang Duan
Chemistry & Biochemistry Faculty Publications
The concentration changes of mineral elements in plants at different CO2 concentrations ([CO2]) and nitrogen (N) supplies and the mechanisms which control such changes are not clear. Hydroponic trials on cucumber plants with three [CO2] (400, 625, and 1200 µmol mol−1) and five N supply levels (2, 4, 7, 14, and 21 mmol L−1) were conducted. When plants were in high N supply, the increase in total biomass by elevated [CO2] was 51.7% and 70.1% at the seedling and initial fruiting stages, respectively. An increase in net photosynthetic rate …
Semi-Supervised Adversarial Domain Adaptation For Seagrass Detection Using Multispectral Images In Coastal Areas, Kazi Aminul Islam, Victoria Hill, Blake Schaeffer, Richard Zimmerman, Jiang Li
Semi-Supervised Adversarial Domain Adaptation For Seagrass Detection Using Multispectral Images In Coastal Areas, Kazi Aminul Islam, Victoria Hill, Blake Schaeffer, Richard Zimmerman, Jiang Li
Electrical & Computer Engineering Faculty Publications
Seagrass form the basis for critically important marine ecosystems. Previously, we implemented a deep convolutional neural network (CNN) model to detect seagrass in multispectral satellite images of three coastal habitats in northern Florida. However, a deep CNN model trained at one location usually does not generalize to other locations due to data distribution shifts. In this paper, we developed a semi-supervised domain adaptation method to generalize a trained deep CNN model to other locations for seagrass detection. First, we utilized a generative adversarial network loss to align marginal data distribution between source domain and target domain using unlabeled data from …