International Journal of Food Microbiology

SAS datasets

A) Sequencing results of PCR products B) Results from whole genome sequencing

The full program, .CSV file, for the developed Maelstrom 8 nucleic acid extraktion method.

Complete data on the values for the input variables of the QMRA model (consumption data, heating profile, salting parameters, freezing parameters, and Dutch/English translated names of the products), the risk per portion, the relative contribution, and mean number of predicted infections are available for all 83 meat products in the supplementary material-QMRA model. Information about the salting concentration, duration, temperature, salting method, type of tissue used in the experiment, use of sodium nitrite, bioassay animal (cat/mouse), number of infected/non-infected animals, and total number of experimental animals collected from selected relevant studies were included in the supplementary material-Salting model.

Raw data showing PFGE types of Salmonella

Raw data for secondary metabolite profiles food-borne small-spored Alternaria

Raw and cleaned data files related to 16S rRNA and ITS genes amplicon sequencing of the DNA extracted directly from maize starch samples after obtention (labelled “_0h”) and after fermentation (labelled “_6h”, “_8h”, “_12h”, or “_24h”, corresponding to the duration of the fermentation). The maize starch samples were obtained from starch slurries collected from traditional processors in Benin, West Africa. The fermented maize starch after fermentation is called “ogi”. The raw data were obtained from Novogene Company Ltd (Cambridge, United kingdom) and processed to generate clean data files, which were consequently used to investigate the microbial community composition in the maize starch and maize ogi samples. Details on the amplicon sequencing and bioinformatic analysis are provided as supplementary method attached to the related manuscript.

Raw and cleaned data files related to 16S rRNA and ITS genes amplicon sequencing of the DNA extracted directly from maize starch samples after obtention (labelled “_0h”) and after fermentation (labelled “_6h”, “_8h”, “_12h”, or “_24h”, corresponding to the duration of the fermentation). The maize starch samples were obtained from starch slurries collected from traditional processors in Benin, West Africa. The fermented maize starch after fermentation is called “ogi”. The raw data were obtained from Novogene Company Ltd (Cambridge, United kingdom) and processed to generate clean data files, which were consequently used to investigate the microbial community composition in the maize starch and maize ogi samples. Details on the amplicon sequencing and bioinformatic analysis are provided as supplementary method attached to the related manuscript.

Inadequate domestic refrigeration is frequently cited as a factor that contributes to foodborne poisoning and infection, and consumer behaviour in this regard can vary largely. This study provides insight into the temperature profiles of domestic refrigerators in the Netherlands and the impact on the number of listeriosis cases related to ready-to-eat (RTE) cooked meat products. A QMRA (Quantitative Microbiological Risk Assessment) was performed with emphasis on consumer handling and storage of RTE cooked meat products before consumption. Monte Carlo simulations were performed to determine the distribution of the Probability of illness using @Risk simulation software (@Risk 8.2 for Excel, Palisade, Ithaca, USA), as an add-in to Microsoft Excel, with 1,000,000 iterations.

Inadequate domestic refrigeration is frequently cited as a factor that contributes to foodborne poisoning and infection, and consumer behaviour in this regard can vary largely. This study provides insight into the temperature profiles of domestic refrigerators in the Netherlands and the impact on the number of listeriosis cases related to ready-to-eat (RTE) cooked meat products. A QMRA (Quantitative Microbiological Risk Assessment) was performed with emphasis on consumer handling and storage of RTE cooked meat products before consumption. Monte Carlo simulations were performed to determine the distribution of the Probability of illness using @Risk simulation software (@Risk 8.2 for Excel, Palisade, Ithaca, USA), as an add-in to Microsoft Excel, with 1,000,000 iterations.