Approaches to the Algorithm of Analyzing the Results of Laboratory Testing of Micro- and Macronutrient Content of Bakery Products: Part 1

Introduction: The assessment of actual nutrition of the population, both at the individual and population level, strongly depends on the accuracy of data on the chemical composition of food products. Milk is an important component of a diet, and a precise estimation of micro- and macronutrients consumed with it is essential for public health assessment. Objective: To develop an algorithm for obtaining statistically accurate values of average concentrations and variability of basic micro- and macronutrients in milk. Materials and methods: To elaborate and check the algorithm, we used milk fat test results collected within the Federal Project on Public Health Strengthening by the laboratories of the Federal Service for Consumer Rights Protection and Human Wellbeing (Rospotrebnadzor) in the years 2020–2021. Results: Due to numerous missing and outlying values of milk composition testing, an appropriate adjustment of the algorithm was necessary. The best separating ability was demonstrated by the approach of dividing types of milk into clusters based on their fat and calcium content. The three clusters obtained included milk with a 2.5 % fat content and the average calcium concentration of 1,144 mg/L, milk with a 3.2 % fat content and the average calcium concentration of 1,180 mg/L, and milk with both fat contents and the mean calcium level of 597 mg/L. The algorithm was validated by checking the completeness of data on the fatty acid composition and a low variability of values. Conclusion: The developed algorithm has enabled us to obtain up-to-date information on the chemical composition of milk sold by food retailers in the Russian Federation. Low-calcium milk on the market is of special concern as its average consumption fails to satisfy human physiological needs. At the same time, the content of saturated fat was below 2.2 g/100 g in the cluster of milk types with the maximum fat content, thus raising no additional health concerns. Further studies should be aimed at determining the acceptable and correct stages of data preprocessing that maintain a balance between the obtained accuracy of values and their actual reproducibility.

Algorithm for Analyzing the Results of Laboratory Testing of Micro- and Macronutrient Composition of Milk

Shcherbakov¹,

Bessonov²

2022

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

Shcherbakov¹,

Bessonov²

2023

Self Cite

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.

Analysis of the Relationship between Names and Quality of Various Groups of Food Products

Shcherbakov,

Bessonov,

Shakhvaliyeva

2023

Introduction: The analysis of food names is an important task aimed at solving two problems, namely, determining the relationship between research results and individual words used and, as a result, obtaining a reliable, from the point of view of food quality, classification within subgroups. Objective: To analyze the relationship between the names of food products and their micro- and macronutrient composition. Materials and methods: The research object was the whole aggregate of the results of testing bakery products, processed meat products, and milk carried out within the framework of the Federal Project on Public Health Promotion in 2020–2021 by laboratories of the Russian Federal Service for Surveillance on Consumer Rights Protection and Human Welfare (Rospotrebnadzor). We applied such linguistic analysis methods as tokenization, noise word removal, stemming, and N-gram analysis. Results: For bakery products, we selected words and their parts enabling us to divide samples into previously obtained groups with different contents of sodium, protein, and fat. For processed meat products, classified by the sodium and fat contents, we also compiled a list of words allowing a reverse classification by name. For fluid milk, we obtained a negative result since the products with the established low calcium content did not differ from other groups in terms of names and their parts. Conclusions: The analysis of food names has demonstrated the potential for classifying foods by their names in order to assess their likely micro- and macronutrient composition. It is necessary to conduct a number of further studies aimed at expanding the list of analyzed product groups, especially those included in the consumer basket.