Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/109900
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dc.contributor.authorRecknagel, F.-
dc.contributor.authorOrr, P.-
dc.contributor.authorBartkow, M.-
dc.contributor.authorSwanepoel, A.-
dc.contributor.authorCao, H.-
dc.date.issued2017-
dc.identifier.citationHarmful Algae, 2017; 69:18-27-
dc.identifier.issn1568-9883-
dc.identifier.issn1878-1470-
dc.identifier.urihttp://hdl.handle.net/2440/109900-
dc.description.abstractAbstract not available-
dc.description.statementofresponsibilityFriedrich Recknagel, Philip T. Orr, Michael Bartkow, Annelie Swanepoel, Hongqing Cao-
dc.language.isoen-
dc.publisherELSEVIER-
dc.rights© 2017 Elsevier B.V. All rights reserved.-
dc.source.urihttp://dx.doi.org/10.1016/j.hal.2017.09.003-
dc.subjectEarly warning; Dolicospermum; Cylindrospermopsis; microcystins; in situ sensor monitoring; inferential models; HEA-
dc.titleEarly warning of limit-exceeding concentrations of cyanobacteria and cyanotoxins in drinking water reservoirs by inferential modelling-
dc.typeJournal article-
dc.identifier.doi10.1016/j.hal.2017.09.003-
dc.relation.granthttp://purl.org/au-research/grants/arc/LP0990453-
pubs.publication-statusPublished-
dc.identifier.orcidRecknagel, F. [0000-0002-1028-9413]-
Appears in Collections:Aurora harvest 3
Earth and Environmental Sciences publications

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