Efficient imaging and computer vision detection of two cell shapes in young cotton fibers-Reference-Cited by-同舟云学术

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Efficient imaging and computer vision detection of two cell shapes in young cotton fibers

Published:2022-11 Issue:6 Volume:10 Page:
ISSN:2168-0450
Container-title:Applications in Plant Sciences
language:en
Short-container-title:Appl Plant Sci

Author:

Graham Benjamin P.¹²^ORCID,Park Jeremy³^ORCID,Billings Grant T.¹⁴^ORCID,Hulse‐Kemp Amanda M.¹⁴⁵^ORCID,Haigler Candace H.¹²^ORCID,Lobaton Edgar⁶^ORCID

Affiliation:

1. Department of Crop and Soil Sciences North Carolina State University Raleigh North Carolina 27695‐7620 USA

2. Department of Plant and Microbial Biology North Carolina State University Raleigh North Carolina 27695‐7612 USA

3. Department of Computer Science North Carolina State University Raleigh North Carolina 27695‐8206 USA

4. Bioinformatics Graduate Program North Carolina State University Raleigh North Carolina 27695‐7566 USA

5. Genomics and Bioinformatics Research Unit, U.S. Department of Agriculture, Agricultural Research Service Raleigh North Carolina 27606‐7825 USA

6. Department of Electrical and Computer Engineering North Carolina State University Raleigh North Carolina 27695‐7911 USA

Publisher

Wiley

Subject

Plant Science,Ecology, Evolution, Behavior and Systematics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/aps3.11503

Reference45 articles.

1. Cotton Fiber Cell Walls of Gossypium hirsutum and Gossypium barbadense Have Differences Related to Loosely-Bound Xyloglucan

2. Genetic Base of Upland Cotton Cultivars Released between 1970 and 1990

3. Registration of eight upland cotton (Gossypium hirsutumL.) germplasm lines withqFL‐Chr.25, a fiber‐length QTL introgressed fromGossypium barbadense

4. brms: An R Package for Bayesian Multilevel Models Using Stan

5. Advanced Bayesian Multilevel Modeling with the R Package brms

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