*Extended column highlighted in blue
Each year, our laboratory summarizes the organisms we have identified as contributing to high farm bacteria counts. For some years, we have also done bacterial isolation and identification for farm samples that show high counts, trying to identify causative organisms when screening samples once a week using traditional plating procedures (Petrifilm). Our routine included a standard plate count and a preliminary incubation count.Three years ago, we switched to using the Foss Bactoscan for determining bacterial counts of milk samples.
We also decided to test every load of milk received rather than testing weekly. We continued to do bacterial identification on elevated samples, which amount to between 500 and 600 bacteria counts per year.
The pie chart shows the types of organisms isolated for farm samples cultured during 2009. In most cases, a sample will grow multiple types of bacteria or mixed cultures. However, most samples also show one or two organisms as the dominant isolate. The most commonly isolated organisms fell into four groups. E. coli and Klebsiella represent a limited number of species of organisms; Pseudomonas represents a wide range. Environmental Strep. includes any Streptococcus species other than Strep. agalactiae.
Information such as this helps us determine the organism present in an elevated sample, but it is by no means perfect. It's still important to do a thorough and complete analysis of each farm's situation. Many times, there are multiple issues contributing to elevated counts.
This information helps the most with counts that are elevated for a single load and then go back to normal at the next pickup. While there is always a possibility of laboratory or sampling mistakes, we have found that the vast majority of these transient high counts are farm-related.
We use the information in the table below to guide our investigations. Again, this is not a perfect system but it does help to get us focused and get problems solved.
When information is not available regarding the specific organism, it is often possible to get a rough idea of which organism might be involved by comparing the relative level of the raw (standard plate) count and PI (preliminary incubation) count for the same sample.
The second chart shows the ratio of PI count to raw count for each sample cultured grouped by the predominant organism found. You can see that the Environmental Streptococcus and Klebsiella tend to show raw and PI counts that are fairly close to each other. E. coli tends to result in PI counts that are 5 to 10 times higher than the paired raw count, while Pseudomonas tends to produce samples with PI counts that are a factor of greater than 10 to 20 higher than the raw count.
So, for example, if your raw count is 50,000 cfu/ml and the PI is 50,000 to 100,000, you probably are dealing with Environmental Strep. or Klebsiella. If the PI is more like 250,000 to 500,000, you be more likely to suspect E. Coli or maybe Pseudomonas. If the PI is 1,000,000 or greater, you almost always will find Pseudomonas.
While information such as this should always be interpreted in the context of a thorough on-farm analysis, combining information about the relative levels of the raw and PI counts with information regarding possible sources can help you get focused faster on likely causes of bacteria count problems.