[Analysis of variance of bacterial counts in milk. 1. Characterization of total variance and the components of...

In contrast to the prevailing automatized chemical analytical methods, classical microbiological techniques are linked with considerable material- and human-dependent sources of errors. These effects must be objectively considered for assessing the reliability and representativeness of a test result. As an example for error analysis, the deviation of bacterial counts and the influence of the time of testing, bacterial species involved (total bacterial count, coliform count) and the detection method used (pour-/spread-plate) were determined in a repeated testing of parallel samples of pasteurized (stored for 8 days at 10 degrees C) and raw (stored for 3 days at 6 degrees C) milk. Separate characterization of deviation components, namely, unavoidable random sampling error as well as methodical error and variation between parallel samples, was made possible by means of a test design where variance analysis was applied. Based on the results of the study, the following conclusions can be drawn: 1. Immediately after filling, the total count deviation in milk mainly followed the POISSON-distribution model and allowed a reliable hygiene evaluation of lots even with few samples. Subsequently, regardless of the examination procedure used, the setting up of parallel dilution series can be disregarded. 2. With increasing storage period, bacterial multiplication especially of psychrotrophs leads to unpredictable changes in the bacterial profile and density. With the increase in errors between samples, it is common to find packages which have acceptable microbiological quality but are already spoiled by the time of the expiry date labeled. As a consequence, a uniform acceptance or rejection of the batch is seldom possible. 3. Because the contamination level of coliforms in certified raw milk mostly lies near the detection limit, coliform counts with high relative deviation are expected to be found in milk directly after filling. Since no bacterial multiplication takes place during storage, then error between samples always predominates the total variation. 4. The present results cannot be simply applied to other selective enumerations of microorganisms. Yet, a non-homogenous distribution should always be expected at microbial counts close to the detection limit. Technical errors arising from clustering as well as eugonic growth can additionally hamper the counting of colonies of such microorganisms. Effects of these observations in the decision-making process will be dealt with in the second communication.