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Assessment of food microbiological indicators applied on poultry carcasses by culture combined MALDI-TOF MS identification and 16S rRNA amplicon sequencing

Published on Sep 1, 2019in Food Microbiology4.09
· DOI :10.1016/j.fm.2019.01.018
Zhongjia Yu (UGent: Ghent University), Maria Francesca Peruzy2
Estimated H-index: 2
(UGent: Ghent University)
+ 2 AuthorsKurt Houf33
Estimated H-index: 33
(UGent: Ghent University)
Abstract
Abstract Examination of the bacterial contamination on food products is still largely performed by standardized culture methods, though culture-independent methods are suggested as a more reliable approach. Knowledge of the diversity of bacteria isolated from food as well as the impact of the plate incubation conditions applied are still understudied. The impact of incubation at 7 °C and 30 °C on total aerobic bacterial count and diversity, and the performance of ISO methods generally applied in microbiological quality examination were assessed by culture combined MALDI-TOF MS identification and 16S rRNA amplicon sequencing. Examining breast skin of 16 chicken carcasses, no significant impact of the incubation temperature on the total aerobic bacteria level and diversity was detected, limiting the usefulness of additional psychrophilic examination. Bacteria phenotypically similar to Pseudomonas, were identified on selective CFC plates, and on MRS agar plates for lactic acid bacteria, Escherichia coli and Staphylococcus were commonly present. Application of 16S rRNA amplicon sequencing revealed a higher bacterial diversity, but the impact of the DNA extraction kit applied, and the detection of non-viable bacteria should be taken into account to interpret the final outcome.
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  • Citations (1)
References32
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#1Amélie Rouger (INRA: Institut national de la recherche agronomique)H-Index: 3
#2Nicolas Moriceau (INRA: Institut national de la recherche agronomique)H-Index: 1
Last.Monique Zagorec (INRA: Institut national de la recherche agronomique)H-Index: 33
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#1Amélie Rouger (INRA: Institut national de la recherche agronomique)H-Index: 3
#2Benoit Remenant (INRA: Institut national de la recherche agronomique)H-Index: 7
Last.Monique Zagorec (INRA: Institut national de la recherche agronomique)H-Index: 33
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#1Linda Höll (TUM: Technische Universität München)H-Index: 2
#2Jürgen Behr (TUM: Technische Universität München)H-Index: 15
Last.Rudi F. Vogel (TUM: Technische Universität München)H-Index: 55
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#1Xiang Yang (CSU: Colorado State University)H-Index: 6
#2Noelle R. Noyes (CSU: Colorado State University)H-Index: 7
Last.Kenneth L. Jones (University of Colorado Denver)H-Index: 23
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