Approaches to the Algorithm of Analyzing the Results of Laboratory Testing of Micro- and Macronutrient Content of Bakery Products: Part 2

Abstract

Introduction: Obtaining correct data on the chemical composition of food products is required for solving different problems, including those related to human health. It is important not only to organize the process of collecting sufficient data, but also to develop an analytical algorithm that considers different periods of data collection and types of foods. Objective: To test and adjust the algorithm for obtaining statistically correct values of average concentrations and variability of the main micro- and macronutrients in bakery products. Materials and methods: In order to test and then improve the algorithm, we used the results of laboratory testing of bakery products collected within the framework of the Federal Project on Public Health Strengthening in 2020–2021 by the laboratories of the Federal Service for Surveillance on Consumer Rights Protection and Human Wellbeing (Rospotrebnadzor). Results: An increase in the sample size made it possible to identify new groups of bakery products. At the same time, the data of the sample combined over two years demonstrated the best convergence. The sodium content was determined as an additional clustering feature. The implementation of the algorithm on the pooled data enabled further reduction of the coefficient of variability. Conclusion: Sequential processing of laboratory test results using the developed algorithm allowed us to update information on the chemical composition of bread currently sold by retailers and determine the presence of products that are critical in terms of their sodium content. It is of interest to expand capabilities of the algorithm in terms of automating the selection of priority indicators for clustering and, as a result, the possibility of processing similar data arrays.