Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Xingche Guo"'
Publikováno v:
Plant Phenomics, Vol 5 (2023)
High-throughput plant phenotyping—the use of imaging and remote sensing to record plant growth dynamics—is becoming more widely used. The first step in this process is typically plant segmentation, which requires a well-labeled training dataset t
Externí odkaz:
https://doaj.org/article/7381028f2df7461d80e2201f87cf4238
Autor:
Xingche Guo, Yumou Qiu, Dan Nettleton, Cheng-Ting Yeh, Zihao Zheng, Stefan Hey, Patrick S. Schnable
Publikováno v:
Plant Phenomics, Vol 2021 (2021)
High-throughput phenotyping enables the efficient collection of plant trait data at scale. One example involves using imaging systems over key phases of a crop growing season. Although the resulting images provide rich data for statistical analyses o
Externí odkaz:
https://doaj.org/article/b91b1151e69c4173b9a57e7aedc2f3eb
Autor:
Fredy A. Silva, Elizabeth C. Chatt, Siti-Nabilla Mahalim, Adel Guirgis, Xingche Guo, Daniel S. Nettleton, Basil J. Nikolau, Robert W. Thornburg
Publikováno v:
Metabolites, Vol 10, Iss 5, p 214 (2020)
Floral nectar is a rich secretion produced by the nectary gland and is offered as reward to attract pollinators leading to improved seed set. Nectars are composed of a complex mixture of sugars, amino acids, proteins, vitamins, lipids, organic and in
Externí odkaz:
https://doaj.org/article/4853ba20eb40403dafb088a3576b2e79
Autor:
Yumou Qiu, Stefan Hey, Cheng Ting Yeh, Zihao Zheng, Dan Nettleton, Xingche Guo, Patrick S. Schnable
High-throughput phenotyping is a modern technology to measure plant traits efficiently and in large scale by imaging systems over the whole growth season. Those images provide rich data for statistical analysis of plant phenotypes. We propose a pipel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8293c8df5886af5ec9b4b27bb6d7735c
https://doi.org/10.1101/2020.09.09.289769
https://doi.org/10.1101/2020.09.09.289769