EventsThe 5th International Electronic Conference on Foods
Published
This submission belongs to the session S8. Food Quality and Safety of the event The 5th International Electronic Conference on Foods
Published date
25 Oct, 2024
Academic Editor
author-avatarAntonello Santini
Citation
Yara Loforte, Vasco Cadavez, Ursula Gonzales-Barron, Modelling the microbial competition of Listeria monocytogenes and selected lactic acid bacteria strains in reconstituted milk, in Proceedings of The 5th International Electronic Conference on Foods, 28 October–30 October 2024, MDPI: Basel, Switzerland
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Modelling the microbial competition of Listeria monocytogenes and selected lactic acid bacteria strains in reconstituted milk

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1. Centro de Investigação de Montanha (CIMO), Instituto Politécnico de Bragança, Campus de Santa Apolónia 5300-253 Bragança, Portugal., Mozambique
2. Laboratório para a Sustentabilidade e Tecnologia em Regiões de Montanha, Instituto Politécnico de Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal
3. Divisão de Agricultura, Instituto Superior Politécnico de Manica, Campus de Matsinho, Província de Manica, Distrito de Vanduzi, Moçambique.
4. Centro de Investigação de Montanha (CIMO), Instituto Politécnico de Bragança, Campus de Santa Apolónia 5300-253 Bragança, Portugal., Portugal
Abstract

Lactic acid bacteria (LAB) and/or their antimicrobial metabolites limit the growth of pathogenic bacteria. This study aims to determine the growth kinetics of Listeria monocytogenes (LM) in heat-treated reconstituted milk, as affected by three LAB strains from the species Leuconostoc mesenteroides (LME), Lacticaseibacillus paracasei (LP) and Loigolactobacillus coryniformis (LC) isolated from goats’ milk cheeses. Challenge tests of each LAB strain in monoculture (MC) and coculture (CC) with LM in milk adjusted to three initial pH (5.5, 6.0 and 6.5) were performed. Inoculated milk samples were left to ferment at 12ºC for 8 days. A pH-driven dynamic growth model was fitted in separate to the LM and LAB experimental curves from MC and CC; and a Jameson-effect growth model was fitted to the CC growth curves. In MC, LME showed the highest growth rates at the three initial pH levels; whereas in CC, this strain was able to better control the growth of LM, by decreasing their growth rates [day-1] to 1.469 ± 0.205 at pH 5.5; 2.293 ± 0.284 at pH 6.0 and 1.552 ± 0.132 at pH 6.5. LP and LC were only able to inhibit and reduce the growth of LM at pH 5.5. In relation to the maximum concentration of LM (LMmax), LME was again the most effective at all initial pH tested. The LMmax [ln CFU/ml] values were reduced to 15.05 ± 0.367; 16.32 ± 0.204 and 16.91 ± 0.132 at pH 5.5; 6.0 and 6.5, in comparison to the values obtained in MC (20.85 ± 0.060; 21.10 ± 0.212 and 21.31 ± 0.085, respectively). This indicates that the strain of LME has a broader and more inhibitory effect on LM growth across different pH, whereas the strains of LP and LC are effective in more acidic conditions. These results provide insights into the use of LAB as a natural biopreservative in dairy products.

Keywords
food safety
antimicrobial activity
foodborne pathogens
pH
modelling
predictive microbiology
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