| Chapter title |
FlowCam: Quantification and Classification of Phytoplankton by Imaging Flow Cytometry
|
|---|---|
| Chapter number | 17 |
| Book title |
Imaging Flow Cytometry
|
| Published in |
Methods in molecular biology, January 2016
|
| DOI | 10.1007/978-1-4939-3302-0_17 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-3300-6, 978-1-4939-3302-0
|
| Authors |
Nicole J. Poulton, Poulton, Nicole J. |
| Abstract |
The ability to enumerate, classify, and determine biomass of phytoplankton from environmental samples is essential for determining ecosystem function and their role in the aquatic community and microbial food web. Traditional micro-phytoplankton quantification methods using microscopic techniques require preservation and are slow, tedious and very laborious. The availability of more automated imaging microscopy platforms has revolutionized the way particles and cells are detected within their natural environment. The ability to examine cells unaltered and without preservation is key to providing more accurate cell concentration estimates and overall phytoplankton biomass. The FlowCam(®) is an imaging cytometry tool that was originally developed for use in aquatic sciences and provides a more rapid and unbiased method for enumerating and classifying phytoplankton within diverse aquatic environments. |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 3% |
| Unknown | 34 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 20% |
| Student > Master | 6 | 17% |
| Student > Bachelor | 4 | 11% |
| Researcher | 3 | 9% |
| Professor | 2 | 6% |
| Other | 3 | 9% |
| Unknown | 10 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Environmental Science | 7 | 20% |
| Agricultural and Biological Sciences | 7 | 20% |
| Engineering | 3 | 9% |
| Physics and Astronomy | 2 | 6% |
| Earth and Planetary Sciences | 2 | 6% |
| Other | 3 | 9% |
| Unknown | 11 | 31% |