scholarly journals Simulation of the properties of a frying composition based on ostrich oil and СО2-marjoram extract

2021 ◽  
Vol 17 (4) ◽  
pp. 42-52
Author(s):  
M. V. Gorbacheva ◽  
V. E. Tarasov ◽  
I. M. Chebanov
Keyword(s):  
Mathematical Modeling ◽  
Desirability Function ◽  
Solid Fat Content ◽  
Component Composition ◽  
Deep Frying ◽  
Lattice Design ◽  
Simplex Lattice ◽  
High Level ◽  
Frying Fat ◽  
Qualitative Characteristics

The article reveals the optimization of a fat frying composition formulation based on ostrich oil and natural stabilizing additive using mathematical modeling of its component composition and analysis of the qualitative characteristics of the product. The object of the research was experimental versions of the frying composition obtained according to the developed recipes, which included liquid and solid fraction of ostrich oil in the following ratio, wt. %: 30,0–70,0 – the liquid one, 30,0–70,0 the solid one and 0,01–0,20 CO2 -marjoram extract. The selection and ratio of the components of the frying fat recipe was carried out using the mathematical modeling methods based on the Scheffe-simplex lattice design. A comparative analysis of the consumer properties of the fat frying composition was carried out using E.K. Harrington’s desirability function. It was shown that the best technological and qualitative characteristics of the properties of the fat frying composition were established at a ratio of 0,5 percent of liquid or 0,5 solid fractions of the frying composition mass with the addition of at least 0,1 wt. % CO2 -extract of marjoram. Positive results were also noted in samples with a minimum solid fat content of 30,0 wt. %, but with a significant amount of a stabilizing additive – 0,15 wt. %. The inhibiting effect of the introduced natural additive, which slowed down oxidative processes in the process of frying the product, were proven. It was determined that only experimental versions of deep-frying fat in the established optimum of the quantitative ratio of fractions and CO2 - extract had the highest desirability scores of 0,723 and 0,792, confirming the high level of product quality. In addition, the proposed combination of ingredients provided an increase in the time of use of the deep-frying composition, due to the increased resistance to oxidation.

scholarly journals MODELLING THE MELTING TEMPERATURE OF A LIPID‐BASED CRITICAL TEMPERATURE INDICATOR: A COMPARISION BETWEEN SIMPLEX-LATTICE AND SIMPLEX-CENTROID DESIGNS

2018 ◽  
Vol 35 (2) ◽  
Author(s):  
KARINE CRISTINE KAUFMANN ◽  
ODINEI HESS GONÇALVES ◽  
EVANDRO BONA ◽  
FERNANDA VITÓRIA LEIMANN
Keyword(s):  
Critical Temperature ◽  
Melting Point ◽  
Melting Temperature ◽  
Predictive Ability ◽  
Ternary Mixtures ◽  
Lipid Mixture ◽  
Color Changes ◽  
Lattice Design ◽  
Simplex Lattice ◽  
Improved Model

Critical temperature indicators (CTI) find applications in food industry in cases when defrost may not occur or a specific temperature may not be reached, , indicating changes through visual changes, such as melting, color changes, etc. Lipid mixtures are promising candidates to formulate CTI since the final melting point of the mixture may be manipulated by the proportion of each lipid. In this work a lipid mixture consisting of stearic acid, lard and peanut oil was used to develop a CTI mixture. Simplex-lattice and Simplex-centroid experimental designs were compared to modelling the melting temperature of the lipid mixture. Addition of axial points to the experimental design improved predictive ability of the models while the inclusion of inverse terms was necessary to improve models accuracy. Simplex-lattice design presented an improved ability to predict the melting point of binary mixtures, while the simplex-centroid design resulted in an improved model for predicting melting point of the ternary mixtures

scholarly journals BAYESIAN APPROACH TO THE D-OPTIMAL FOR MIXTURE EXPERIMENTAL DESIGN

2019 ◽  
Vol 3 (2) ◽  
pp. 109
Author(s):  
Uqwatul Alma Wizsa
Keyword(s):  
Optimal Design ◽  
Quadratic Model ◽  
Model Parameters ◽  
Potential Term ◽  
Lattice Design ◽  
Simplex Lattice Design ◽  
Simplex Lattice ◽  
Mixture Experimental Design ◽  
Special Case ◽  
Experimental Region

A mixture experiment is a special case of response surface methodology in which the value of the components are proportions. In case there are constraints on the proportions, the experimental region can be not a simplex. The classical designs such as a simplex-lattice design or a simplex-centroid design, in some cases, cannot fit to the problem. In this case, optimal design come up as a solution. A D-optimal design is seeking a design in which minimizing the covariance of the model parameter.  Some model parameters are important and some of them are less important. As the priority of the parameters, the prior information of parameters is needed in advance. This brings to a Bayesian D-optimal design. This research was focus on a baking experiment in which consisted of three ingredients with lower bounds on the proportion of the ingredients. The assumption model was a quadratic model. Due to the priority of the model parameters, the Bayesian D-optimal design was used to solve the problem. A point-exchange algorithm was developed to find the optimal design. Nineteen candidates is used to choose twelve design points. It found that the potential term is feasible to the actual model and design points represent overall points in the design area.

scholarly journals Distinction between the concepts of mathematical and logical modeling

2019 ◽  
Vol 19 (3) ◽  
pp. 262-267 ◽  
Author(s):  
E. N. Kolybenko
Keyword(s):  
Mathematical Modeling ◽  
Problem Solving ◽  
Practical Significance ◽  
Material Objects ◽  
Knowledge Domain ◽  
Organic Unity ◽  
Control Processes ◽  
Management Processes ◽  
Logical Modeling ◽  
High Level

Introduction. Technologies of mathematical and logical modeling of problem solving according to the existing practice of their distribution are divided into two areas: widespread mathematical modeling and infological modeling which is currently underdeveloped, especially for sophisticated systems. Fundamental differences between these technologies, in particular for the machining preproduction, are that logical modeling is informationally and logically related to organization systems, and mathematical modeling is associated with control processes in the organization systems. Logical modeling is used to operate with geometric objects in the technological schemes of their interaction through basing methods, geometric shaping in a static (ideal) setting of the corresponding schemes. Mathematical simulation is used to operate material objects in the control processes of their transformations through cutting methods, i.e. imperfectly, considering heterogeneous errors. Between the organization systems under study and management processes in them, there are information and logical links of their organic unity, which deny their separate consideration. In the information deterministic technology for solving problems of a high-level automation, the distinction between the concepts of “mathematical” and “logical” modeling is relevant; it has scientific novelty and practical significance.Materials and Methods. To characterize the properties of the concepts of “mathematical modeling”, “logical modeling” and the knowledge functions resulting from the formulation of these concepts, fundamentally different methods and appropriate tools are used. The differentiation of the concepts under consideration is based on the differentiation of technologies (methods, appropriate tools, algorithms, operations) for solving applied problems of any knowledge domain.Research Results. The ideas of “logical modeling” and “mathematical modeling” are conceptual general-theoretical notions with invariant properties required for solving practical problems of any application domain. In accordance with the distinction between these concepts, the problem solving technologies are divided into two types: system engineering technology – in the organization of information object systems, and system science – in the management processes of transformation of the corresponding material objects. These areas should exist in the information and logical link of their organic unity.Discussion and Conclusions. The author distinguishes between the concepts of “logical modeling” and “mathematical modeling”, which is a key condition for a successful transition to the deterministic information technology of a high-level automation in solving practical problems of any knowledge domain, for example, of the production design machining

OPTIMASI FORMULA EKSTRAK JAHE MERAH (Zingiber officinale) DENGAN METODE KEMPA LANGSUNG MENGGUNAKAN ANALISIS SIMPLEX LATTICE DESIGN

2017 ◽  
Vol 1 (1) ◽  
pp. 47
Author(s):  
Hayatus Sa'adah
Keyword(s):  
Dosage Form ◽  
Ethanol Extract ◽  
Zingiber Officinale ◽  
Disintegration Time ◽  
Lattice Design ◽  
Simplex Lattice Design ◽  
Optimum Proportion ◽  
Simplex Lattice ◽  
Red Ginger ◽  
Tablet Hardness

Processing of medicinal plants into the appropriate dosage form can ensure security during use. It is a motivation in making acceptable dosage form which is easy and convenient to use, especially the manufacture of ethanol extract red ginger tablets using a combination of starch 1500 and amprotab.The study begins with the manufacture of dry extract of red ginger. Optimization of making tablets using a combination of starch 1500 and disintegrator with simplex lattice design using three formulas is done by direct compaction method. Further testing on the tablet hardness, friability and disintegration time.The results showed starch 1500 has a greater influence increase hardness and disintegration time of tablets, as well as lowering the fragility of the tablet. While the interaction of starch 1500 and disintegrator has no effect on the physical tablet. The optimum proportion of the combination of starch 1500 and disintegrator meet the physical requirements of tablets with a ratio of 4: 6 with 7.99 kg hardness, the friability of 0.32% and disintegration time of 2.42 minutes

Application of Simplex Lattice Design in Formulation Development of Lozenges Containing Vernonia cinerea Extract for Smoking Cessation

2019 ◽  
Vol 819 ◽  
pp. 227-232
Author(s):  
Chaowalit Monton ◽  
Thanaporn Sangprapai ◽  
Narathip Mekwimonmas ◽  
Tinnapas Sawangsang ◽  
Natawat Chankana ◽  
...  
Keyword(s):  
Milk Powder ◽  
Angle Of Repose ◽  
Formulation Development ◽  
Disintegration Time ◽  
Powder Mixtures ◽  
Lattice Design ◽  
Simplex Lattice Design ◽  
Weight Variation ◽  
Simplex Lattice ◽  
Vernonia Cinerea

The aim of this work was to apply the simplex lattice design in the formulation development of lozenges containing Vernonia cinerea extract. The different ratios of three diluents; milk powder, xylitol, and inulin were investigated. The preformulation parameters of powder mixtures were evaluated. The compressed lozenges were evaluated for their weight variation, thickness, hardness, friability, and disintegration time. Results showed that the ratios of the three diluents affected the preformulation parameters. The angle of repose data revealed that all 12 powder mixtures had excellent flow property. The formulation containing milk powder had the highest values of Carr’s index and Hausner ratio, indicating the poor compressibility. While formulation containing inulin had the best compressibility. A formulation containing xylitol had the lowest moisture content. The compressed lozenges had a weight variation of less than 5%, a diameter of 1.5 mm, a thickness of 5-6 mm, and a hardness of 2-12 kP. The 8 of 12 formulations had friability of less than 1%. Use of milk powder provided the longest disintegration time. The desired properties of developed lozenge achieved when the medium amount of xylitol and inulin and low amount of milk powder were used. The optimal diluent ratio providing the weight variation not more than 5%, the hardness of 5-8 kP, friability not more than 1%, and disintegration time not more than 30 min was an equal weight ratio of milk powder, xylitol, and inulin.

Simulation analysis of the catalytic cracking process of biomass pyrolysis oil with mixed catalysts: Optimization using the simplex lattice design

2018 ◽  
Vol 42 (9) ◽  
pp. 2983-2996 ◽  
Author(s):  
Chawannat Jaroenkhasemmeesuk ◽  
Maria Elena Diego ◽  
Nakorn Tippayawong ◽  
Derek B. Ingham ◽  
Mohammed Pourkashanian
Keyword(s):  
Catalytic Cracking ◽  
Simulation Analysis ◽  
Pyrolysis Oil ◽  
Biomass Pyrolysis ◽  
Lattice Design ◽  
Simplex Lattice Design ◽  
Simplex Lattice ◽  
Cracking Process
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