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Application of predictive food microbiology to reduce food waste
Dissertation (MSc)--University of Pretoria, 2017.
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| Format: | Thesis |
| Language: | English |
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University of Pretoria
2018
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| _version_ | 1867613500441886720 |
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| access_status_str | Open Access |
| author2 | Buys, E.M. (Elna Maria) |
| author_browse | Buys, E.M. (Elna Maria) |
| author_facet | Buys, E.M. (Elna Maria) |
| collection | Thesis |
| dc_rights_str_mv | © 2018 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. |
| description | Dissertation (MSc)--University of Pretoria, 2017. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/65935 |
| institution | University of Pretoria (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:37:08.286Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository |
| publishDate | 2018 |
| publishDateRange | 2018 |
| publishDateSort | 2018 |
| publisher | University of Pretoria |
| publisherStr | University of Pretoria |
| record_format | dspace |
| source_str | UPSpace — University of Pretoria Institutional Repository |
| spelling | oai:repository.up.ac.za:2263/65935 Application of predictive food microbiology to reduce food waste Buys, E.M. (Elna Maria) u13401922@tuks.co.za Coorey, R. Olaonipekun, Basirat Arinola UCTD Dissertation (MSc)--University of Pretoria, 2017. Universal food insecurity continue to be a challenge that needs attention from all stakeholders. The problem of food waste however is highly important as it slows down the effort to improve food security, most especially in the world’s poorest countries. Conservative shelf life estimation of RTE foods by food producers is one of the major contributor to food waste. After a survey was carried out on the different RTE food products (n=195) available on the shelf of 3 supermarkets in Hatfield, with their set shelf life and storage instructions. Microbiological quality (Total viable count, LAB, Enterobacteriaceae, yeasts and moulds, and Pseudomonas spp.) and safety (E. coli, Staphylococcus aureus, Listeria spp. and Salmonella spp.) was conducted on selected RTE products (used as a reference point) during storage at ± 5o C. This wass to evaluate the validity of the set shelf life of beef lasagne (3 days), egg noodles (3 days), pre-cut mango (4 days) and pre-cut papaya (4 days) by food producers. Challenge test study was also conducted on representative RTE food products (beef lasagne, egg noodles, and pre-cut mango) with relevant food borne pathogens (L. monocytogenes, Salmonella Typhimurium, and E. coli) during storage for 12 days at ± 5oC. Growth potential (?) of these pathogens in the RTE foods were calculated using the concept of EU-CRL technical guidance on shelf life for L. monocytogenes on RTE foods as ? values can be very useful in potential food safety risk evaluation. Performance of 4 different types of software (ComBase, PMP, MicroHibro & FSSP) was evaluated for use in shelf life estimation of these selected RTE foods. These software were selected based on different criteria (User-friendly, accessibility and availability and types of pathogens for its application). The predicted growth from these software were compared to observed growth (generated from experimental data got from challenge test) of L. monocytogenes in beef lasagne and egg noodles. Indices of performance; Coefficient of determination (R2), root mean square error (RMSE), bias factor (Bf) and accuracy factor (Af) were used to evaluate the performance of these software. All the RTE food products reviewed had no specific refrigeration storage temperature instruction on the product package. Storage test study indicated that some of these RTE foods (beef lasagne, pre-cut mango and papaya) could have longer shelf life (5, 13 and 5 days respectively), while egg noodles could be a potential public health risk due to the presence of food borne pathogens right from day of purchase. However, the challenge test results also confirmed the conservative shelf life estimation by food producers in that the shelf life of all the products evaluated can be extended (Beef lasagne by 6 days, Egg noodles by 6 days and pre-cut mango by 9 days) with no food safety risk associated with the extension. On the other hand. RTE egg noodles and beef lasagne may support the growth of L. monocytogenes (? > 0.5 log10 cfu/g) if present in the food while egg noodles may not support the growth of S. Typhimurium (? ? 0.5 log10 cfu/g). Beef lasagne and pre-cut mango may also not support the growth of E. coli (? ? 0.5 log10 cfu/g). Growth of L. monocytogenes predicted by ComBase, PMP, MicroHibro & FSSP in beef lasagne and egg noodles was in agreement with the observed growth from the challenge test study, with a fail-safe prediction. However, ComBase predictor had the closest prediction to the observed growth. Hence, it had overall best performance for prediction compared to the other software. Notwithstanding, all the software evaluated in this study can be applied in shelf life prediction of RTE food products. Predictive microbiology is a field of food microbiology that can be looked into and implemented by the authorities. Its use by the South African food industry to scientifically estimate the shelf life of RTE food products is thereby encouraged. This will assist in decision making with regards to food quality and safety, thereby reducing the problem of food waste as result of product shelf life and at the same time protect public health. Food Science MSc Unrestricted 2018-07-25T09:01:01Z 2018-07-25T09:01:01Z 2018/04/19 2017 Dissertation Olaonipekun, BA 2017, Application of predictive food microbiology to reduce food waste, MSc Dissertation, University of Pretoria, Pretoria, viewed yymmdd <http://hdl.handle.net/2263/65935> A2018 http://hdl.handle.net/2263/65935 en © 2018 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. application/pdf University of Pretoria |
| spellingShingle | UCTD Application of predictive food microbiology to reduce food waste |
| title | Application of predictive food microbiology to reduce food waste |
| title_full | Application of predictive food microbiology to reduce food waste |
| title_fullStr | Application of predictive food microbiology to reduce food waste |
| title_full_unstemmed | Application of predictive food microbiology to reduce food waste |
| title_short | Application of predictive food microbiology to reduce food waste |
| title_sort | application of predictive food microbiology to reduce food waste |
| topic | UCTD |
| url | http://hdl.handle.net/2263/65935 |