Comparison of Uncertainty Between Traditional and Alternative Methods for Food Microbiological Analysis


	American Journal of Food Technology
	Year: 2016 \| Volume: 11 \| Issue: 1-2 \| Page No.: 29-36 DOI: 10.3923/ajft.2016.29.36

Comparison of Uncertainty Between Traditional and Alternative Methods for Food Microbiological Analysis

Alyexandra Arienzo, Francesca Losito, Ottavia Stalio and Giovanni Antonini

Abstract: The objectives highlighted in the present study were to determine the estimates of measurement uncertainty associated with microbiological analysis in food samples performing a gage repeatability and reproducibility study on three different microbiological methods of analysis for the detection and quantification of total coliforms; Plate count method, 3M Petrifilm^TM count plates method and the MBS method. For all three methods the contribution the total gage R and R is less than 10%, demonstrating the ability to accurately evaluate the concentration of total coliforms in food samples. However, the repeatability and reproducibility follows the tendency; Plate count method<3M Petrifilm^TM count plates method<MBS method. The study also highlights that a significant variation is due to the interaction between the operators and the analyzed samples for plate count and 3M Petrifilm^TM count plates methods while for the MBS method it does not significantly affect the measure. Together these results demonstrate that greater repeatability and reproducibility are connected to a more simple analytical procedure demonstrating that uncertainty is certainly related to the amount of manual work and the individual interpretation of results. Results confirm that it is important to diminish these sources of error reducing labor and simplifying procedures and increasing automation.

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How to cite this article:

Alyexandra Arienzo, Francesca Losito, Ottavia Stalio and Giovanni Antonini, 2016. Comparison of Uncertainty Between Traditional and Alternative Methods for Food Microbiological Analysis. American Journal of Food Technology, 11: 29-36.

DOI: 10.3923/ajft.2016.29.36

URL: https://scialert.net/abstract/?doi=ajft.2016.29.36

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