Zoeken
Zoeken kan via de modus 'eenvoudig zoeken' (één veld) of uitgebreid via 'geavanceerd zoeken' (meerdere velden). Zo kan je bv. zoeken op een combinatie van een auteursnaam (auteur), een jaartal (jaar) en een documenttype.
Boekenmand
Nuttige resultaten kan je aanvinken en toevoegen aan een mandje. De inhoud hiervan kan je exporteren of afdrukken (naar bv. PDF).
RSS
Op de hoogte blijven van nieuw toegevoegde publicaties binnen uw interessegebied? Dit kan door een RSS-feed (?) te maken van jouw zoekopdracht.
nieuwe zoekopdracht
FlowCAM optimization: Attaining good quality images for higher taxonomic classification resolution of natural phytoplankton samples
Camoying, M.G.; Yñiguez, A.T. (2016). FlowCAM optimization: Attaining good quality images for higher taxonomic classification resolution of natural phytoplankton samples. Limnol. Oceanogr., Methods 14(5): 305-314. http://dx.doi.org/10.1002/lom3.10090
In: Limnology and Oceanography: Methods. American Society of Limnology and Oceanography: Waco, Tex.. ISSN 1541-5856; e-ISSN 1541-5856
|  |
| Auteurs | | Top |
- Camoying, M.G.
- Yñiguez, A.T.
|
|
|
| Abstract |
Taxonomic data on phytoplankton composition is important for ecological studies, however, such information is not easy to gather. Imaging devices and image classification software have been developed in the past decades for rapid phytoplankton assessment. Taxonomic resolution output of classification software are primarily limited by the quality of images produced by these imaging instruments. FlowCAM has been utilized in several studies for this endeavor. However, the phytoplankton categories that the instrument is currently able to discriminate are still few compared to the outputs of microscopy. This study aimed to produce high resolution FlowCAM images of fixed phytoplankton samples from natural environments without compromising sample analysis time. It was also aimed to optimize the capability of FlowCAM’s VisualSpreadsheet software to automatically classify phytoplankton images. The use of FOV300 flow cell and 10X objective combination has roven to be effective in producing good quality images at a faster rate. The modified hardware configuration resulted to FlowCAM counts that were comparable to that of the standard microscopy method. FlowCAM was able to automatically classify images of dominant phytoplankton groups in the two key sardine fishery areas in the Philippines with relatively high accuracy values. These phytoplankton groups are represented by genera with complex morphological structures (e.g., setae) such as Chaetoceros and Bacteriastrum as well as those genera with simple shapes such as Pseudo-nitzschia (thin-elongate) and Coscinodiscus (spherical). |
IMIS is ontwikkeld en wordt gehost door het VLIZ.
