Modification of Biotesting-Based Fermented Dairy Product Design for Curd and Curd Products

Zobkova, Z.S.; Yurova, E.A.; Semipyatny, V.K.; Lazareva, E.G.; Zenina, Daria V.; Shelaginova, Irina R.

doi:10.3390/foods11203166

Cited by 2 publications

(1 citation statement)

References 16 publications

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“…[7]. Therefore, nutritional value cannot act as a comprehensive characteristic of a product as a factor of nutrient supply [8,9]. In this regard, the issue of nutritional value should be considered more deeply, i. e. from the perspective of the digestibility of the product's nutrients.…”

Section: Introductionmentioning

confidence: 99%

Development of an approach to predicting the bioavailability of enteral nutrition products

Kondratenko,

Agarkova

2024

Teor. prakt. pererab. mâsa (Print)

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One of the key factors while developing nutritional supplements is their bioavailability. To determine it, expensive and timeconsuming clinical studies of developed products are necessary. Using in silico methods may speed up and reduce the costs of such clinical studies. The purpose of this study is to develop an approach to predicting the integral bioavailability of enteral nutrition products (ENPs) based on a comprehensive analysis of the matrices of components and indicators. The includes a comprehensive empirical study based on a comparative statistical analysis of the matrix of studied ENPs components. Available information on the composition and indicators of 52 commercial ENPs was used as a research object. This information was compiled into a matrix of components and indicators, marked according to the intended purposes of the products. The set of products included in the matrix was divided into 2 subsets: ENPs corresponding to a given intended purpose and other ENPs. This made it possible to separate statistically significant components and indicators that define the intended purpose of the product with a given threshold of the maximum error probability for inequality of mean values. Using Harrington’s desirability principle in relation to the identified components and indicators made it possible to obtain an integral estimate of desirability for a given intended purpose. A vector characterizing the distance from the integral estimate to the ideal value was introduced as equivalent predicted bioavailability. The upper limit of the optimal range is 0.37, the upper limit of the acceptable range is 0.63. The predicted bioavailability vector scale is the inverse of the integral desirability scale. In contrast to Harrington scaling, the lower the predicted bioavailability value, the more preferable it is. Analysis of the introduced indicator allowed us to establish significant variability in commercial ENPs with respect to predicted bioavailability for diabetes mellitus and thermal injury. Based on the proposed predicted bioavailability vector, a principle has been developed for the evolutionary development of a statistical approach to predicting bioavailability when designing ENPs. This principle is a universal addition to the principle of food combinatorics while developing meat, dairy and plant-based ENPs.

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Section: Introductionmentioning

confidence: 99%

Development of an approach to predicting the bioavailability of enteral nutrition products

Kondratenko,

Agarkova

2024

Teor. prakt. pererab. mâsa (Print)

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The Development and Adaptation of a Predictive Model of Full-Factor Optimisation of the Basic Probiotic Fermented Dairy Product Technological Process

Zobkova,

Kondratenko,

Pryanichnikova

et al. 2023

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Introduction: In the conditions of rapidly developing markets and the increasing needs of the population for new types of products with long shelf life, there is a need to expand their range, further improve their quality and biological value, and modernize traditional technologies. The main means of achieving these goals is to increase the efficiency and quality of scientific research and accelerate the introduction of scientific achievements in industry. The latter will make adjustments to accelerate the development of effective technologies of whole-milk products. The use of new methods of experiment planning in order to optimize technological processes will reduce the duration of research on the creation of new types of products.Purpose: The article is devoted to the research related to the development and adaptation of a predictive (mathematical) model for optimization of the technological process of probiotic fermented dairy product production. This approach will allow to ensure the design of a certain set of formulations for probiotic fermented dairy product, in which the relative biological value (RBV) will correspond to the maximum value at satisfactory given process parameters.Materials and Methods: The objects of research were: probiotic fermented dairy product manufactured in accordance with the developed mathematical model of the process. The search of specialized literature was carried out using electronic databases: E-library, Scopus, MDPI, Science Direct. Mathematical processing of experimental data for the development of the probiotic fermented dairy product model was carried out using Microsoft Excel 2010 (Microsoft Corporation, Ink.) with the "Solution Search" add-in, as well as specialized software packages TableCurve 2D v.5.01 (SYSTAT Software, Ink.) and Wolfram Mathematica 10.2 (Wolfram Research, Ink.).Results: A mathematical model for optimization of the technological process of probiotic fermented dairy product production was developed. A full-factor experiment (FFE) was conducted, in which the mass fraction of sucrose ( , %) and fat-protein index (r) - the ratio of the mass fraction of fat to the mass fraction of protein in the normalized mixture in the intervals from 0 to 10 and from 0 to 1.5%, respectively, were taken as independent factors. RBV was taken as the resultant factor. Based on the results of the research, a refined mathematical description of the dependence of RBV indicator on the mass fraction of sucrose and fat-protein index was obtained. The set of data on the influence of the mass fraction of sucrose on the dynamics of local maximum of RBV and the dynamics of the corresponding values of the mass fraction of fat showed that the maximum of RBV equal to 244.866% corresponded to the mass fraction of sucrose equal to 7.31%. The latter corresponded to the optimum fat-protein index of 1.241. In order to ensure maximum RBV, the lower limit of the mass fraction of fat had to correspond to 3.475%. The analysis of the FFE data showed the presence of additional corrective factors of RBV indicator dependence on fat and protein mass fraction indices. To refine the developed model taking into account additional factors, a correction factor (Q) was introduced into it.Conclusion: Approbation of the optimization model of the technological process of probiotic fermented dairy product production and the obtained mathematical dependencies can serve as a criterion for the formation of a set of formulations for the production of sugar-containing fermented dairy products with a high potential of relative biological value. It should be taken into account that the definition area of this approach is limited in terms of mass fraction of fat in the range from 0.06 to 4.84% and mass fraction of protein - from 2.8 to 3.9%. With this approach (model development) it is possible to analyze promising modes for the studied process, which in real conditions at the experimental stage are not always possible to obtain. The development of this model will significantly reduce the duration of research on the optimization of the technological process.

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Modification of Biotesting-Based Fermented Dairy Product Design for Curd and Curd Products

Cited by 2 publications

References 16 publications

Development of an approach to predicting the bioavailability of enteral nutrition products

Development of an approach to predicting the bioavailability of enteral nutrition products

The Development and Adaptation of a Predictive Model of Full-Factor Optimisation of the Basic Probiotic Fermented Dairy Product Technological Process

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