| Pectobacteriaceae| Pectobacteriaceae Adeolu et al. 2016
Plant Pathogens: Pectobacteriaceae members, such as Pectobacterium and Dickeya species, are known for causing diseases in a wide range of plants, including potatoes, carrots, and other vegetables. They can lead to soft rotting of plant tissues.
Soft Rot and Blackleg Diseases: Soft rot diseases caused by Pectobacteriaceae often result in the breakdown of plant cell walls, leading to a mushy, water-soaked appearance in affected tissues. Blackleg is a term often used for the decay and discoloration of stems.
Economic Impact: Pectobacteriaceae-related diseases can have significant economic implications in agriculture by causing crop losses and reducing the quality of harvested produce.
Not Generally Pathogenic to Humans: While Pectobacteriaceae are known plant pathogens, they are not typically associated with causing infections or diseases in humans. The primary concern related to these bacteria is their impact on crops and agriculture.
A lot more information is available when you are logged in and raise the display level
Other Sources for more information:
Statistics | NCBI | Data Punk | End Products Produced |
Different labs use different software to read the sample. See this post for more details.
One lab may say you have none, another may say you have a lot! - This may be solely due to the software they are using to estimate.
We deem lab specific values using values from the KM method for each specific lab to be the most reliable.
Lab | Frequency | UD-Low | UD-High | KM Low | KM High | Lab Low | Lab High | Mean | Median | Standard Deviation | Box Plot Low | Box Plot High | KM Percentile Low | KM Percentile High |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Other Labs | 0.57 | 6 | 700 | 0 | 627 | 172.7 | 35 | 232 | 6 | 700 | 6.7 %ile | 86.7 %ile | ||
biomesight | 4.48 | 0 | 0 | 10 | 840 | 0 | 273 | 53.5 | 20 | 112 | 0 | 60 | 0 %ile | 100 %ile |
thorne | 100 | 27 | 180 | 2 | 141 | 71.3 | 62 | 35.4 | 34 | 108 | 0 %ile | 100 %ile | ||
thryve | 34.57 | 0 | 21 | 1 | 500 | 0 | 5131 | 281.9 | 42 | 2473.8 | 4 | 152 | 0 %ile | 95.6 %ile |
ubiome | 0.25 | 149 | 13750 | 0 | 25800 | 6949.5 | 6950 | 9617.4 | 149 | 13750 | 25 %ile | 50 %ile |
Source of Ranges | Low Boundary | High Boundary | Low Boundary %age | High Boundary %age |
---|---|---|---|---|
Thorne (20/80%ile) | 32.72 | 55.84 | 0.0033 | 0.0056 |
Lab | Frequency Seen | Average | Standard Deviation | Sample Count | Lab Samples |
---|---|---|---|---|---|
BiomeSight | 5.203 % | 0.006 % | 0.011 % | 149.0 | 2864 |
bugspeak | 100 % | 0.005 % | % | 1.0 | 1 |
CerbaLab | 66.667 % | 0.003 % | 0.001 % | 2.0 | 3 |
custom | 1.695 % | 0.003 % | % | 1.0 | 59 |
es-xenogene | 13.793 % | 0.049 % | 0.016 % | 4.0 | 29 |
Medivere | 42.857 % | 0.001 % | 0.001 % | 3.0 | 7 |
SequentiaBiotech | 2.778 % | 0.012 % | % | 1.0 | 36 |
Thorne | 82.955 % | 0.004 % | 0.004 % | 73.0 | 88 |
Thryve | 33.623 % | 0.025 % | 0.225 % | 465.0 | 1383 |
uBiome | 0.253 % | 0.695 % | 0.962 % | 2.0 | 792 |
Click on Impact for information if high or low levels are causing the impact
Magnitude | Impact | Symptom |
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Data comes from FoodMicrobionet. For the meaning of weight, see that site. The bacteria does not need to be alive to have an effect.
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