ISO 16297-2020 pdf free

04-24-2021 comment

ISO 16297-2020 pdf free.Milk—Bacterial count — Protocol forthe evaluation of alternative methods.
A prerequisite for statistics most common in the evaluation of measuring methods is the approximationof a normal distribution of the data.The exponential multiplication of microorganisms usually leads to aright-tailed distribution with quantitative microbiological parameters.Thus,in general, transformationof the raw data is necessary for approximation of normality. This is usually a common logarithmictransformation.The most appropriate transformation can be checked by comparing histograms. Allstatistics are then computed from the transformed data, unless specified otherwise, and only the finalresults are re-transformed to give a more expressive idea of the situation to the user (see Reference[2].
For each alternative method, only the relevant parameters outlined in this clause shall be evaluated.For example, the measuring range (see 5.3) of the plate loop method is determined by the loop[s) usedand the determination of the parameter is not relevant.
Description of the method to be evaluated
The description of the method under study shall be in line with the checklist in 5.2.2.
Most of the information is found in the specification of the method given by the responsible supplier orany other source (author) of the technique specified.
The upper limit of quantification is determined by the highest possible reading of the method or bymethodological limitations,e.g.coincidence effects,inaccuracy in the upper measuring range, cloggingof filters.Coincidence is when two or more elements of the measurand are detected simultaneously andidentified as only one unit. For example, with flow cytometry, if two bacterial cells pass the detectorsimultaneously, they are detected as one.The coincidence effect is higher with higher concentrations ofa measurand.
The upper limit of quantification is determined as the highest concentration where the instrument isstill linear according to 5.3.3.
The relationship between the instrument readings and the expected values shall be linear within theconcerned range of bacterial counts. Deviations from linearity may stem from non-specific signals andcoincidence effects.
To evaluate linearity, use the raw data expressed in units of the alternative method without logarithmicor any other transformation.
A linearity check is at first performed visually using appropriate graphs to obtain an impression of theshape of the relationship. Whenever deviation from linearity appears evident, a quantitative parameteris calculated to indicate whether the observed trend is acceptable or not.
To achieve this, use a high bacterial count milk diluted serially with low bacterial count milk, resultingin a set of at least 10 samples covering the concentration range of interest.ISO 16297 pdf download.

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