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Title: | Microbial Performance of Food Safety Control and Assurance Activities in a Fresh Produce Processing Sector Measured Using a Microbial Assessment Scheme and Statistical Modeling | Authors: | Njage, Patrick Murigu Kamau Sawe, Chemutai Tonui Onyango, Cecilia Moraa Habib, Ihab NJAGI, Edmund AERTS, Marc MOLENBERGHS, Geert |
Issue Date: | 2017 | Publisher: | INT ASSOC FOOD PROTECTION | Source: | JOURNAL OF FOOD PROTECTION, 80(1), p. 177-188 | Abstract: | Current approaches such as inspections, audits, and end product testing cannot detect the distribution and dynamics of microbial contamination. Despite the implementation of current food safety management systems, foodborne outbreaks linked to fresh produce continue to be reported. A microbial assessment scheme and statistical modeling were used to systematically assess the microbial performance of core control and assurance activities in five Kenyan fresh produce processing and export companies. Generalized linear mixed models and correlated random-effects joint models for multivariate clustered data followed by empirical Bayes estimates enabled the analysis of the probability of contamination across critical sampling locations (CSLs) and factories as a random effect. Salmonella spp. and Listeria monocytogenes were not detected in the final products. However, none of the processors attained the maximum safety level for environmental samples. Escherichia coli was detected in five of the six CSLs, including the final product. Among the processing-environment samples, the hand or glove swabs of personnel revealed a higher level of predicted contamination with E. coli, and 80% of the factories were E. coli positive at this CSL. End products showed higher predicted probabilities of having the lowest level of food safety compared with raw materials. The final products were E. coli positive despite the raw materials being E. coli negative for 60% of the processors. There was a higher probability of contamination with coliforms in water at the inlet than in the final rinse water. Four (80%) of the five assessed processors had poor to unacceptable counts of Enterobacteriaceae on processing surfaces. Personnel-, equipment-, and product-related hygiene measures to improve the performance of preventive and intervention measures are recommended. | Notes: | [Njage, Patrick Murigu Kamau; Sawe, Chemutai Tonui] Univ Nairobi, Dept Food Sci Nutr & Technol, Nairobi, Kenya. [Onyango, Cecilia Moraa] Univ Nairobi, Dept Plant Sci & Crop Protect, Nairobi, Kenya. [Habib, I] Murdoch Univ, Coll Vet Med, Murdoch, WA 6150, Australia. [Njagi, Edmund Njeru] London Sch Hyg & Trop Med, Canc Res UK Canc Survival Grp, Keppel St, London WC1E 7HT, England. [Njagi, Edmund Njeru; Aerts, Marc; Molenberghs, Geert] Univ Hasselt, Interuniv Inst Biostat & Stat Bioinformat, B-3590 Diepenbeek, Belgium. [Molenberghs, Geert] Katholieke Univ Leuven, Interuniv Inst Biostat & Stat Bioinformat, B-3000 Louvain, Belgium. [Njage, Patrick Murigu Kamau] Tech Univ Denmark, Natl Food Inst, Div Epidemiol & Microbial Genom, DK-2800 Lyngby, Denmark. | Keywords: | correlated random effects joint models; empirical Bayes estimates; fresh produce; generalized linear mixed models; microbial assessment scheme;Correlated random effects joint models; Empirical Bayes estimates; Fresh produce; Generalized linear mixed models; Microbial assessment scheme | Document URI: | http://hdl.handle.net/1942/23789 | ISSN: | 0362-028X | e-ISSN: | 1944-9097 | DOI: | 10.4315/0362-028X.JFP-16-233 | ISI #: | 000392483900024 | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2018 |
Appears in Collections: | Research publications |
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File | Description | Size | Format | |
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microbial.pdf Restricted Access | Published version | 747.07 kB | Adobe PDF | View/Open Request a copy |
Njage et al Manuscript.pdf | Peer-reviewed author version | 196.53 kB | Adobe PDF | View/Open |
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