Modeling the die-off of E. coli and Ascaris in wastewater-irrigated vegetables : implications for microbial health risk reduction associated with irrigation cessation
This study assessed the die-off of Escherichia coli (E. coli) and Ascaris suum on lettuce (Great Lakes 118) and cabbage (Brassica oleracea var capitata) in wastewater-irrigated fields using comparative mathematical die-off models. The study revealed that none of the survival curves of E. coli and A....
| Veröffentlicht in: | Water science and technology : a journal of the International Association on Water Pollution Research. - 1986. - 68(2013), 5 vom: 15., Seite 1013-21 |
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| Weitere Verfasser: | , , , , |
| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2013
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| Zugriff auf das übergeordnete Werk: | Water science and technology : a journal of the International Association on Water Pollution Research |
| Schlagworte: | Journal Article Research Support, Non-U.S. Gov't |
| Zusammenfassung: | This study assessed the die-off of Escherichia coli (E. coli) and Ascaris suum on lettuce (Great Lakes 118) and cabbage (Brassica oleracea var capitata) in wastewater-irrigated fields using comparative mathematical die-off models. The study revealed that none of the survival curves of E. coli and A. suum was best fitted with the log-linear model, indicating that the classical first-order kinetic approach is inadequate in many cases. The biphasic die-off model best described the die-off of E. coli on lettuce (kmax1 = 2.62 day(-1) and kmax2 = 0.22 day(-1)) and cabbage (kmax1 = 1.06 day(-1) and kmax2 = 0.53 day(-1)). The die-off of A. suum on lettuce was best described by the biphasic model (kmax1 = 0.48 day(-1) and kmax2 = 0.01 day(-1)) and best described by log linear + tail (kmax = 0.44) on cabbage. A comparative health risk assessment associated with the consumption of lettuce showed significant underestimation of the number of days of irrigation cessation required to achieve E. coli O157:H7 and Ascaris tolerable annual infection risk when using biphasic die-off rates compared with other die-off rates. The study stresses the need to test different die-off models as inputs for quantitative microbial risk assessment (QMRA) particularly for interventions associated with health risk reduction |
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| Beschreibung: | Date Completed 14.01.2014 Date Revised 09.01.2024 published: Print Citation Status MEDLINE |
| ISSN: | 0273-1223 |
| DOI: | 10.2166/wst.2013.335 |