Author

D. R. Wang

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Plant Biology· 3

Signature Assays, Organisms & Methods

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Organism:plant (other)· 3 Approach:statistical model· 3 Research Focus:ecology & biodiversity· 2 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Assay:imaging· 1

Frequent Co-Authors

C. R. Guadagno· 2 shared D. S. Mackay· 2 shared A. Souza· 1 shared B. E. Ewers· 1 shared B. M. Stevens· 1 shared C. D. Messina· 1 shared C. Hoagland· 1 shared C. Hunter· 1 shared

Activity by Year

2018-2022 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 19 mutual co-author links

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2 shared papersPlant Biology

C. R. Guadagno

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3 papers

Recent·Most cited

Quantifying physiological trait variation with automated hyperspectral imaging in rice

T.-C. Ting, A. Souza, R. Imel, C. R. Guadagno, C. Hoagland, Y. Yang, D. R. Wang

This study uses automated hyperspectral imaging to classify nitrogen treatments and predict leaf nitrogen content and carbon-to-nitrogen ratio in rice with high accuracy.

bioRxiv · Dec 14, 2022 · PreprintPlant Biology

Physiological trait networks enhance understanding of crop growth and water use in contrasting environments

S. M. Gleason, D. M. Barnard, T. R. Green, D. S. Mackay, D. R. Wang, E. A. Ainsworth, J. Altenhofen, T. J. Brodribb, H. Cochard, L. H. Comas, M. Cooper, D. Creek, K. C. DeJonge, S. Delzon, F. B. Fritschi, , H. Zhang

The paper uses a process-based model to identify contrasting trait networks in maize that enhance growth and water use in different environments.

bioRxiv · Mar 11, 2022Plant Biology

A framework for genomics-informed ecophysiological modeling in plants

D. R. Wang, C. R. Guadagno, X. Mao, D. S. Mackay, J. R. Pleban, R. L. Baker, C. Weinig, J.-L. Jannink, B. E. Ewers

The paper develops a framework linking genetic variation to plant physiological responses using genomic prediction and process-based modeling in Brassica rapa.

bioRxiv · Dec 17, 2018Plant Biology