STATISTICAL ANALYSIS OF THE RESULTS OF LABORATORY RESEARCH AS ONE OF THE METHODS OF INCREASING THE COMPETITIVENESS OF A MILK PROCESSING ENTERPRISE
Abstract
Ensuring the stable quality of food products is the primary production for any enterprise, as well as a priority for government bodies whose activities aim to protect consumers and detect adulteration of consumer products. From time to time, food manufacturers receive complaints from buyers regarding the inconsistency of the content of individual indicators with those declared in the specification or on the label. The causality of such appeals can be intentional falsification of the product and non-compliance with the accuracy of research methods, usually due to low technical support of analytical laboratories of enterprises. That is why the statistical analysis of research results will allow the evaluation of the obtained product and establish its "compliance" with the buyers requirements. The articles purpose is a theoretical overview of individual statistical analysis methods of research and their practical application in the laboratory of a milk processing enterprise. The article examines using intervals as an element of statistical analysis of laboratory research results. The indicators of the average value and variance allow us to characterize both the studied sample and the methodology. An example of this is the analysis of the study results of the mass fraction of fat in milk by various analysis methods. The approach for testing hypotheses is also considered because, for any laboratory, it is necessary to understand whether the method of analysis applied to the selected sample provides a certified value. This issue is especially acute in the production laboratory during the incoming control of raw materials ingredients and during the study of the finished product. If, based on the experimental results, it is decided that the technique used is flawed, we conclude that it has a systematic error. Such errors will cause unreliable results, which will cause financial and reputational losses for the company. Given the complex situation in the dairy market of our country, such losses can be fatal for a milk processing enterprise, which is why it is necessary to provide a statistical analysis of the applied methods for confidence in our own products.
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Dong W., Zhang Y., Zhang B. (2012) Quantitative analysis of adulteration of extra virgin olive oil using Raman spectroscopy improved by bayesin framework least squares support vector machines. Analytical Methods, vol. 4, рр. 2772–2777.
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Kumar N., Bansal A., Sarma G. S. (2014) Chemometrics tools in analytical chemistry: An overview. Talanta, vol. 123, рр. 186–199.
Maning L. (2016) Food Fraud: policy and food chain. Current Opinion in Food Science, vol. 10, рр. 16–21.
Ortiz M. C., Herrero A., Sanllorente S., Reguera C. (2005) The Quality of the Information Contained in Chemical Measures. [The Quality of the Information Contained in Chemical Measures]. Servicio de Publicaciones Universidad de Burgos. Burgos. Spain.
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Oca M. (2016) Robustness Testing in the Determination of Seven Drugs in Animal Muscle by Liquid Chromatography–Tandem Mass Spectrometry. Chemom. Intel. Lab. Syst, vol. 151, рр. 172–180.
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Spink J. (2019) The application of public policy theory to the emerging food fraud risk: next steps. Trends in Food Science & Technology, vol. 85, рр. 116–128.
