caa a22 4500 467904332 CHVBK 20180406152829.0 cr unu---uuuuu 170328e20060301xx s 000 0 eng 10.1007/s10661-006-5031-4 doi (NATIONALLICENCE)springer-10.1007/s10661-006-5031-4 Characterization of Escherichia Coli Isolates from Different Fecal Sources by Means of Classification Tree Analysis of Fatty Acid Methyl Ester (Fame) Profiles [Elektronische Daten] [Sylvie Seurinck, Ellen Deschepper, Bishaw Deboch, Willy Verstraete, Steven Siciliano] Microbial source tracking (MST) methods need to be rapid, inexpensive and accurate. Unfortunately, many MST methods provide a wealth of information that is difficult to interpret by the regulators who use this information to make decisions. This paper describes the use of classification tree analysis to interpret the results of a MST method based on fatty acid methyl ester (FAME) profiles of Escherichia coli isolates, and to present results in a format readily interpretable by water quality managers. Raw sewage E. coli isolates and animal E. coli isolates from cow, dog, gull, and horse were isolated and their FAME profiles collected. Correct classification rates determined with leaveone-out cross-validation resulted in an overall low correct classification rate of 61%. A higher overall correct classification rate of 85% was obtained when the animal isolates were pooled together and compared to the raw sewage isolates. Bootstrap aggregation or adaptive resampling and combining of the FAME profile data increased correct classification rates substantially. Other MST methods may be better suited to differentiate between different fecal sources but classification tree analysis has enabled us to distinguish raw sewage from animal E. coli isolates, which previously had not been possible with other multivariate methods such as principal component analysis and cluster analysis. Springer Science + Business Media, Inc., 2006 classification tree analysis nationallicence Escherichia coli nationallicence fatty acid methyl ester nationallicence microbial source tracking nationallicence Seurinck Sylvie Laboratory of Microbial Ecology and Technology (LabMET), Ghent University, Coupure Links 653, Ghent, Belgium aut Deschepper Ellen Department of Applied Mathematics, Biometrics and Process Control, Ghent University, Coupure Links 653, Ghent, Belgium aut Deboch Bishaw Laboratory of Microbial Ecology and Technology (LabMET), Ghent University, Coupure Links 653, Ghent, Belgium aut Verstraete Willy Laboratory of Microbial Ecology and Technology (LabMET), Ghent University, Coupure Links 653, Ghent, Belgium aut Siciliano Steven Department of Soil Science, University of Saskatchewan, 51 Campus Drive, S7N 5A8, Saskatoon, Saskatchewan, Canada aut Environmental Monitoring and Assessment Springer Netherlands 114/1-3(2006-03-01), 433-445 0167-6369 114:1-3<433 2006 114 10661 https://doi.org/10.1007/s10661-006-5031-4 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s10661-006-5031-4 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Seurinck Sylvie Laboratory of Microbial Ecology and Technology (LabMET), Ghent University, Coupure Links 653, Ghent, Belgium aut NATIONALLICENCE 700 1- Deschepper Ellen Department of Applied Mathematics, Biometrics and Process Control, Ghent University, Coupure Links 653, Ghent, Belgium aut NATIONALLICENCE 700 1- Deboch Bishaw Laboratory of Microbial Ecology and Technology (LabMET), Ghent University, Coupure Links 653, Ghent, Belgium aut NATIONALLICENCE 700 1- Verstraete Willy Laboratory of Microbial Ecology and Technology (LabMET), Ghent University, Coupure Links 653, Ghent, Belgium aut NATIONALLICENCE 700 1- Siciliano Steven Department of Soil Science, University of Saskatchewan, 51 Campus Drive, S7N 5A8, Saskatoon, Saskatchewan, Canada aut NATIONALLICENCE 773 0- Environmental Monitoring and Assessment Springer Netherlands 114/1-3(2006-03-01), 433-445 0167-6369 114:1-3<433 2006 114 10661 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer