ISO 16297:2020

ISO 16297:2020 pdf free.Milk一Bacterial count- Protocol for the eva luation of alternative methods.
5.3.2 Upper limit of quantification
The upper limit of quantification is determined by the highest possible reading of the method or by methodological limitations, e.g. coincidence effects, inaccuracy in the upper measuring range, clogging of filters. Coincidence is when two or more elements of the measurand are detected simultaneously and identified as only one unit. For example, with flow cytometry, if two bacterial cells pass the detector simultaneously, they are detected as one. The coincidence effect is higher with higher concentrations of a measurand.
The upper limit of quantification is determined as the highest concentration where the instrument is still linear according to 5.3.3.
5.3.3 Linearity of the instrument signal
The relationship between the instrument readings and the expected values shall be linear within the concerned range of bacterial counts. Deviations from linearity may stem from non-specific signals and coincidence effects.
To evaluate linearity, use the raw data expressed in units of the alternative method without logarithmic or any other transformation.
A linearity check is at first performed visually using appropriate graphs to obtain an impression of the shape of the relationship. Whenever deviation from linearity appears evident, a quantitative parameter is 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, resulting in a set of at least 10 samples covering the concentration range of interest.
5.4 Carry-over
Carry-over effects can occur in analytical systems that operate continuously. It derives from the transfer of a certain portion of sample material from one test sample to the next or further sample(s).
This effect can be tested by analysing consecutively milk with high bacterial count and blank samples. Carry-over causes an increase of blank sample values compared to the target range of blank sample values (value of blank sample analysed after another blank sample).
The carry-over can be expressed as percentage of the corresponding preceding milk sample. To evaluate carry-over, use the raw data expressed in units of the alternative method without logarithmic or any other transformation.
For evaluation of carry-over, the number of samples and the bacterial count of the milk samples should be high enough to estimate the carry-over with sufficient certainty.
The samples should be representative of the routine samples, especially regarding the storage time (longer storage time leading to higher milk viscosity and potentially higher carry-over). One way of setting up the test is described in the example below. For detailed and theoretical aspects and alternative setups of carry-over estimation, refer to ISO 8 196-3 I IDF 128-3.
As an example, one way to estimate the carry-over effect is to analyse at least 10 sets of samples, each set containing one milk sample with very high bacterial count followed by two blank samples. Blank samples can be milk with negligible bacterial count and the high sample can be milk with a bacterial count of approximately 2 x 106 cfu/ml (where cfu/ml is colony forming units per millilitre milk sample).ISO 16297 pdf download.

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