Shubat Camel Cheese(Turkey)

The data comes from FoodMicrobionet and does not cover yogurts with probiotics added. Most foods have not been studied. Weight indicate the relative amount of the total bacteria. Bacteria not found in the NCBI list may be omitted. See the above site for a full list.

Data is aggregate from multiple studies which often use different measurement techniques

Bacteria RankWeight
Acetobacteraceae family 0.00193
Acinetobacter genus 1.93
Acinetobacter guillouiae species 0.0298
Acinetobacter haemolyticus species 0.133
Acinetobacter johnsonii species 2.27
Aeromonas genus 1.86
Aeromonas caviae species 0.0354
Ameyamaea genus 0.0584
Citrobacter genus 1.66
Enhydrobacter aerosaccus species 0.696
Enterobacter genus 0.0884
Enterobacteriaceae family 0.0766
Enterococcus genus 0.39
Janthinobacterium genus 0.0126
Lacticaseibacillus genus 0.212
Lactiplantibacillus genus 0.0737
Lactobacillaceae family 0.0221
Lactobacillus genus 4.73
Lactobacillus delbrueckii species 34.8
Lactobacillus helveticus species 29.1
Lactobacillus kefiranofaciens species 10.4
Lactococcus genus 5.94
Lactococcus raffinolactis species 2.47
Lelliottia genus 8.7
Lentilactobacillus genus 9.96
Leuconostoc genus 4.08
Leuconostoc pseudomesenteroides species 0.00295
Limosilactobacillus genus 0.524
Macrococcus genus 0.0337
Micrococcales order 0.00996
Moraxella genus 0.00578
Pseudomonas genus 0.267
Psychrobacter genus 0.063
Raoultella genus 0.176
Raoultella ornithinolytica species 0.156
Serratia genus 0.146
Streptococcus genus 23
Streptococcus parauberis species 0.153
Streptococcus salivarius species 0.352
Yersinia genus 0.233
Yersiniaceae family 0.0629

BOOM

All suggestions are computed solely on their predicted microbiome impact. Safety, side-effects etc must be evaluated by your medical professionals before starting. Some items suggests have significant risk of adverse consequences for some people.

Special thanks to David F Morrison and Geert Van Houcke for doing Quality Assurance. Special thanks to Oliver Luk, B.Sc. (Biology) from BiomeSight for spot checking the coding of data from the US National Library of Medicine

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