# ONTOLOGY OF RHEOLOGY FOR FOOD LIQUIDS

Raphael Kamdoum, Maksimov A. S.

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<figure><img src="image_1.png" /></figure>
EONTOLOGY OF RHEOLOGY FOR FOOD LIQUIDS

Kamdoum Raphael

Ph.D. Student Russian Biotechnological University

125080, Moscow, Volokolamskoe Shosse, 11

kamdoumraphael5@gmail.com / kamdoum.raphael@yahoo.fr

Department of Automation and Control of Technological Processes and
Productions

A. S. Maksimov

Professor Russian Biotechnological University

125080, Moscow, Volokolamskoe Shosse, 11

maksimov@mgupp.ru

Department of Automation and Control of Technological Processes and
Productions

**abstract**

This scientific article is about the construction of an ontology of the rheology of food fluids, which will help to better understand the physical and mechanical properties of liquid foods, harmonize terminological understanding in the field of rheology, and contribute to the evolution of science. The objective is to have a functional ontology that can help categorize foods based on the description of their rheological properties after testing. The METHONLOGIE method was used as the basis for conceptualizing the ontology in formal language, and the ontology obtained in this phase is called a formal ontology. This formal ontology was then coded in OWL DL, which has very rich semantic features, using the Protege tool with a modular interface developed at Stanford Medical Informatics at Stanford University, allowing the editing, visualization, and control of ontologies. Ultimately, a stable ontology was obtained after launching the reasoner.

**Keywords:** Rheology, ontology, modeling, food liquids, viscosity.
## Introduction

Rheology of food products is a scientific discipline that studies the mechanical properties of deformable food products, such as viscosity, elasticity, cohesion, rupture, etc. These properties are highly significant for the food industry as they determine the quality, texture, taste, and stability of food products. However, measurement methods, food product samples, and testing conditions for obtaining these properties vary widely, making it difficult to compare results across studies and potentially leading to interpretation errors. To address this issue, the concept of ontology in the field of food rheology finds its application. Ontology is a tool that systematically and consistently describes concepts, relationships, and constraints within a knowledge domain. In the context of food rheology, ontology allows for the standardized and compatible description of rheological properties of food products across studies. Through this ontology, researchers can standardize rheological data of liquid food products, facilitating result comparison between studies. Additionally, ontology can enhance the quality and safety of food products by enabling researchers and regulators to better understand the relationships between the structure of food products and their rheological properties. In this article, we present the development of an ontology for the rheology of liquid food products, aimed at systematically and consistently classifying them based on their rheological properties. We explain the methodology of construction using the METHONTOLOGY method with a competency-based approach, involving multiple expert research works from different fields such as food science, rheology, and informatics. In conclusion, we present the results and discuss how the ontology can be improved and utilized for standardizing rheological data of food products.

## I: Rheology of Food Products

Rheology is a key discipline for the food industry as it enables the characterization of physical properties of food products and understanding their behavior at various stages of production, storage, and consumption. Currently, three physical characteristics of food products have been identified through extensive research: solid
products, liquid products, and viscoelastic products. Numerous studies have been conducted on the rheology of liquid food products using various measurement methods to characterize rheological properties. Common methods include dynamic shear rheometry, oscillatory rheometry, viscometry, and microfluidics. The outcomes of these studies reveal that rheological properties of liquid products, such as viscosity, elasticity, and plasticity, play a vital role in their appearance, texture, and taste, and that these properties are influenced by multiple factors. Developing mathematical models for the rheology of liquid food products is an active research area, as it would allow the prediction of rheological properties based on composition and processing conditions. These models can aid in optimizing production processes and designing new products with desired textural and sensory attributes.

**1- Factors Affecting the Rheological Properties of Food Products**

The rheological properties of liquid food products are influenced by various factors, such as the product's structure, temperature, pH, pressure, the presence of solid particles in the food products, which can affect rheological properties, as well as composition and processing technologies. For example, thermal processing can impact the viscosity of liquid food products by altering the texture and structure of proteins and carbohydrates. Ingredients like emulsifiers, stabilizers, and thickeners can also affect the rheological properties of liquid food products.

**2- Techniques for Measuring the Rheology of Food Products**

There are several measurement techniques for characterizing the physical properties of food products. The primary techniques used to measure the rheological properties of food products include:

*Rheometry:* This measurement method is often used to characterize the rheological properties of food products. It involves applying mechanical stress to a sample of the food product and measuring the material's response in terms of force and deformation. This technique can be carried out using a rheometer, which can measure
viscoelastic, plastic, and viscous properties of food products.

*Viscometry*: Viscosity is a measure of a liquid's resistance to flow. Methods for measuring viscosity include falling-ball viscometry, capillary viscometry, oscillatory viscometry, and more.

*Spectroscopy*: Spectroscopy is a measurement method that studies the properties of food products by analyzing the response of sample molecules to an energy source, such as light or sound waves. Spectroscopy methods include infrared spectroscopy, Raman spectroscopy, and light scattering spectroscopy.

*Imaging*: Imaging is a technique that allows for visualizing the structure and texture of food products. Imaging methods include X-ray tomography, scanning electron microscopy, confocal fluorescence microscopy, and others.

*Flow Sensors*: Flow sensors are devices used to measure the flow of liquids. They can be used to measure the rheological properties of liquid food products, such as sauces and soups.

## II - Ontologies in Food Science

Ontologies are data structures that enable a better understanding of concepts within a specific domain. In the context of food science, ontologies facilitate a deeper comprehension of food product properties and the relationships between them. This, in turn, enables more informed decisions in the areas of food quality and safety. The benefits of ontologies can be applied in various sectors of the food industry, including product development, regulation, risk management, and more. These advantages enhance the understanding of food-related information and ensure heightened food safety for all stakeholders, including producers, processors, distributors, regulators, and consumers. Ultimately, these advantages foster improved collaboration and information exchange within the food chain, facilitating a better grasp and utilization of food product knowledge. Ontologies are constructed using formal languages such as OWL (Web Ontology Language) or RDF (Resource Description Framework), which allow knowledge representation in the form of semantic graphs.
Although ontologies are computer tools primarily aimed at structuring and classifying information, their utilization in food science is hindered by the complexity and diversity of food data, as well as the absence of standardized methods for data collection and storage. Therefore, efforts must be directed toward standardization and regular data updates to facilitate their use in ontologies. Despite these challenges, ontologies can aid in classifying food products based on their rheological behavior and predicting the texture of food products based on their composition and processing methods. This can potentially lead to an enhancement in the quality of food products.

### III - Methodology for Ontology Creation

There are several methodologies for creating ontologies, but they all follow a common iterative process involving domain experts and information technology specialists. Here are some of the most frequently used methodologies for ontology creation:

1. NeOn Methodology: This method is based on a multi-stage iterative approach that includes domain analysis, requirement specification, conceptual modeling, implementation, and ontology evaluation. It's often used for large-scale projects and involves collaboration among multiple teams.

2. Methontology Methodology: This method focuses on developing comprehensive documentation for the ontology, starting from defining goals and users, through domain analysis and requirement specification, and ending with ontology creation and evaluation.

3. OntoClean Methodology: This method emphasizes ontology quality, using principles of cleanliness and modularity to ensure consistency and clarity of concepts and relationships. It's often used in large-scale projects involving multiple experts' collaboration.

4. Suggested Upper Merged Ontology (SUMO) Methodology: This method
focuses on creating a high-level ontology that can represent common concepts across various domains. It's often used as a foundation for creating other ontologies.

The Methontology methodology serves as the basis for our ontology creation, as it's considered highly effective with several advantages. For example, it allows for precise and strict description of concepts, relationships, and constraints, preventing errors. It also encourages the reuse of existing concepts, simplifying the creation of consistent and compatible ontologies. It facilitates checking the ontology at each stage of its development, enabling quick error detection. It fully documents the ontology, making it user-friendly. The major steps of this process are inspired by the "METHONTOLOGY" ontology building methodology [Fernandez97]. Applying each of the steps is based on the work of HEMMAM [Hemam04]. This process consists of five stages:

1. Specification of Requirements The development of the ontology begins with the specification phase, involving the creation of a requirements specification document. This document outlines the ontology to be built, focusing on five aspects:

*   **Knowledge Domain:** The ontology we are building falls within the realm of rheology of food liquids. It can draw concepts from fluid mechanics, food science, and our work will limit itself to concepts characterizing the context of studying rheological properties of liquid food products.

*   **Goal:** The goal of this rheology ontology is to classify food products into liquid categories (Newtonian, non-Newtonian, etc.) based on fluid mechanics, standardizing their rheological properties for compatibility across studies.

*   **Users:** This aspect encompasses all users who might utilize the ontology. In our case, ontology users could be researchers and scientists in the fields of rheology, food science, and informatics.

*   **Information Sources:** The information sources on which we base the creation
of the ontology application are the results of various studies in fluid mechanics,
rheology of food products, technical documents in the food industry,
technology of web services, and ontologies in informatics.

* Ontology Application Domain: This aspect involves defining a preliminary list of ontology terms (the most important ones). Among them, terms like food products, liquid type, graphical observation, evaluation test type, rheological parameter changes, etc., can be mentioned. For the studied food product, our ontology should provide answers to questions like:

* What type of test is used for research?

* What elements can affect the rheological behavior?

* How do these rheological parameters change?

* How does the characteristic graph behave after the test?

* To which liquid category does this food product belong?

## 2. Conceptualization

It's necessary to organize and structure knowledge using semi-formal
intermediate representations that are easily understood and independent of any
implementation language. Building a glossary of terms: This glossary contains
definitions of all terms related to the subject domain (concepts, instances, attributes,
relationships) that will be represented in the final ontology.

Fluid food, Observation graph, Type of test performed, Variation of
rheological, parameters Newtoniens fluid food, Non newtoniens fluid food, Non
newtoniens fluid with behavior independents of time, plastic fluids, Fluid food
without critical stress, dilatant fluids, pseudoplastic fluids, viscoelastic fluids,
foods_Fluids_non-Newtonian_to_the_behavior weather Dependent,
Rheopex, Thixotropic_fluids, observation_graph, Bingham_flowCurve,
curve_with_a_hysteresis_zone, dilatingCurve, negative_slope_Curve,
positive_slope_Curve, pseudoplastic_Curve, Stress-strain_Curve, Thixotropic_Curve
viscoelastic_Curve, linear_in_elastic_regime, nonlinear_in_the_plastic_regime,
Stress_relaxation_test, Capillary_rheology_test, compression_test,
Drop_viscosity_test, Dynamic_Shear_Stress_Curve_test,
Frequency Responses Test, Oscillatory_Flow_Viscosity_test,
Oscillatory_Shear_Viscosity_test, Pouring_test in a funnel,
rotary_cylindrical_test, shear_test tensile_test, constant_speed_shear_test
power_law, observation_of_stress-strain_records, shear_rate, shear_stress, viscosity
creepObservation, elasticity_module, frequency_of_stress_relaxation_with_time,
maximum_stress_limit, high_modulus_small_module, dependentFriction_angle,
dependent maximum constraint, irreversible_deformation, reversible_deformation,
constant_viscosity, decreasing_viscosity, increasing_viscosity, Intrinsic_viscosity
, Frequency_and_amplitude_of_stress, Method_of_stress_application, n_flow_index,
Temperature, The_composition_of_the_food, theVelocityGradientTiming, PH,
pressure, Rest_time

After this, it becomes easier to generate a dictionary of concepts, relationships
between these concepts, attributes, instances, and so on.

3 - Formalization

This stage involves formalizing the conceptual ontology created in the previous stage
to facilitate its subsequent representation in a fully formal and operational language.
The formalism used for representation is the description logic using the syntax of
SHOIN (which stands for S—Description logic, H—Role hierarchy, O—Inverse
roles, I—Number restrictions, and N—Nominals). SHOIN is known for providing a
highly expressive description logic with a rich set of constructors for describing
concepts. Description logic comprises two parts: the terminological part (TBOX) for
describing concepts and roles and the assertional part (ABOX) for describing
individuals. In our case, we focus on the latter, describing facts and using the
assertional language as follows:

* A(C): To indicate that A is an instance of class C. For example: `newtonian_fluid_food(fluid_food)`. [A1] (R) [A2]: To indicate that two
individuals A1 and A2 are related by the relation R. For example:
are_the_evalution_elements(fluid_food, observation_graph).

## 4 - Implementation

The ontology obtained in the previous stage, referred to as the formal ontology, is now encoded in OWL DL, which offers more extensive semantic capabilities than its predecessors, such as RDFS or DAML+OIL. At the end of this stage, the goal is to have an operational ontology. To simplify the encoding process, we use PROTEGE OWL version 3.1.1 [NOY00], which has a modular interface developed in medical informatics at Stanford University. It enables ontology editing, visualization, and control, and contains classes (concepts), slots (properties), edges (property values and constraints), as well as instances of classes and properties.

## 5 - Ontology Testing, Results, and Discussion

Our ontology should automatically classify food products after their tests into the class of food liquids. These food products will be classified after a test on food liquid, which, from a fluid mechanics perspective, divides food products into two subclasses: Newtonian and non-Newtonian fluids. In-depth mechanical research has identified several cases of non-Newtonian fluids depending on their rheological behavior.

Let's consider the results of the rheological test on pure water, which exhibit the following characteristics: "The flow curve is linear, and its viscosity constant is independent of stress or shear rate." For fruit puree, according to Joël SCHER, "deformation starts from the moment stress is applied. The resulting curve is nonlinear. Shear stress is not proportional to shear rate, as viscosity decreases with increasing shear rate." When modeling this description, the ontology should be capable of assigning it to a specific liquid type after the resonator test is conducted.

To achieve this, we will define them as individuals of the food products class and add constraints to these entities based on the results of their respective tests described above
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A good understanding of this modeling in the Protege tool requires a solid grasp of the subject area you need to model, followed by a deeper comprehension of the workings of different components in the Protege tool. So, we have:

<figure><img src="image_3.png" /><figcaption>* Concepts or Classes and Properties or Relationships</figcaption></figure>

Concepts or Classes: These are sets of instances. They can be divided into subclasses based on constraints regarding the membership of instances to a class or subclass to a class. For example, the concept "Foods" consists of instances like water, ketchup, etc. The class "type of test conducted" has subclasses (capillary rheological test, rotational cylindrical test, drop viscosity test), which are actually a set of rheological tests used for categorizing food products. To rapidly create these concepts in Protege, we'll use the "Create Class Hierarchy" tool in the "Tools" menu, inputting different classes and
pressing Enter after each class. For subclasses, use the Tab key on a new line after
each class, and eventually, we'll have a class hierarchy. Click "Continue". The tool
checks if the entered names adhere to a predefined style (no spaces, no accents, etc.).
It also checks if such names already exist.

Properties or Relationships: These are binary relationships between instances of classes. For example: [fluid_food] (re_the_evalution_elements)[observation_graph]. Relationships can be:

*   **Inverses**: Each relationship can have an inverse relationship. For instance, the relationship "has_characteristic_graph" has an inverse relationship "is_the_characteristic," and vice versa.

*   **Functional**: A relationship is declared functional when only one individual can be associated with it. For example, [fluid_food] (are_the_evalution_elements)[observation_graph]. "are_the_evalution_elements" is a functional relationship.

*   *Transitive, Symmetric, etc.*

To create relationships, go to the "Object Properties" tab. Click "Add Sub-Property" to create a new relationship. Below is a summary table of different relationships.

***Instances of Classes (Individuals):*** These are objects within the domain you want to model. For example: water, fruit juice, honey, ketchup, etc. Initially, they will be stored in the class "Food Products".

* **Domain and Range**

<figure><img src="image_4.png" /></figure>
**Domain and Range**: Domain and range are two important concepts in ontology that help define the scope and scale of the ontology. They can be represented as follows: [Domain] (Relation) [Range]. To define them:

1. Select the relationship in the hierarchy.

2. Set the domain by clicking on the + icon to the right of "Domains" and selecting the domain class.

3. Set the range (codomain) by clicking on the + icon to the right of "Ranges" and selecting the range class.

## Constraints:

There are two types of constraints in modeling:

1. **Existential Constraint (some)**

2. **Universal Constraint (Only**

<figure><img src="image_5.png" /></figure>

**Essential Constraint (some)**: The most common type of constraint in OWL ontologies is the existential constraint (some). This constraint describes a class of individuals that have at least one (some) relationship with an individual that is a member of a specific class. For instance, the class "Fluid_food" has at least one relationship with each of the classes "observation_graph," "type_of_test_performed," and "variation_of_rheological_parameters." To add this constraint:

1. Select the "Fluid_food" class in the tab.

2. Click on the + icon next to "SubClassOf."

3. This opens a dialog containing the "Class Expression Editor," where you enter
your constraint. a. You can either type "has_for_elements_of_evaluation" or
drag it from the available properties. b. Specify the constraint type, here it's
"some." c. Finally, write "observation_graph." The final script should be:
has_for_elements_of_evaluation some observation_graph.

*Universal Constraint (Only)*: A universal constraint (Only) is an axiom that states that for a given concept, all instances of that concept have a specific relationship with another concept or property. In other words, the universal constraint restricts instances of a concept by linking them to another concept or property. For example, the universal constraint "All fluids whose behavior is characterized by a linear flow curve and constant or stress-independent viscosity are called Newtonian" implies that all instances of the "newtonian_fluid_food" concept have a specific relationship with the "viscosity" concept and "observation_graph." In OWL, the notation for the universal constraint is "only." To add this constraint:

1. Select the "newtonian_fluid_food" class in the tab.

2. Click on the + icon next to "SubClassOf."

3. This opens a dialog with the "Class Expression" editor, where you input your constraint. a. You can either type "has_for_elements_of_evaluation" or drag it from the available properties. b. Specify the constraint type, here it's "Only." c. Finally, write "linearCurve." The final script should be:
   has_for_elements_of_evaluation only linearCurve.

To fully understand the principle of the "Only" constraint, it's important to know that
ontology works under the Closed World Assumption. In ontology, everything is true
unless explicitly declared otherwise. This is in contrast to databases, where if a query
returns nothing, it's considered false. To reproduce this behavior in an ontology, you
need to create a closed-world axiom, a universal constraint (Only).

Thus, we have a model that contains around 100 concepts organized into classes and subclasses, along with relationships between them. The use of these concepts helps to better understand different types of liquids and their characteristics. The results of our modeling show that there are two types of liquid foods depending on the performed
rheological tests: Newtonian and non-Newtonian fluids.

Newtonian fluids are the simplest viscous type of fluid. Their flow curve is linear, and their viscosity doesn't depend on stress or shear rate. Non-Newtonian fluids, on the other hand, can be divided into time-independent behavior and time-dependent behavior.

Time-independent non-Newtonian fluids are further classified into fluids without critical stress (shear-thinning fluids or pseudoplastic fluids and shear-thickening fluids or dilatant fluids) and fluids with critical stress or plastic fluids. The classification of non-Newtonian fluids with critical stress or plastic fluids involves ideal flow behavior (Bingham flow) with the existence of yield point, plasticity, and critical stress.

Time-dependent non-Newtonian fluids are divided into two categories: thixotropic fluids and rheopectic fluids. While rheopexy is a complex phenomenon, these types of fluids seem to undergo restructuring with weak shear impact. Thixotropic fluids, when subjected to shear after a rest period, gradually lose their structure, leading to a decrease in apparent viscosity over time. Viscoelastic fluids possess properties of both viscosity and elasticity, allowing them to recover part of their deformation after the load is removed.

Identifying these different fluid categories requires rheological testing, observing results corresponding to used rheological parameters, and graphically visualizing flow curves. It's worth noting that in certain conditions, rheological measurement strongly depends on parameters like temperature, pressure, structure, and physicochemical properties of the tested product.
The conclusions drawn from our model indicate that the rheological properties of a given food can determine its classification as a liquid after reasoning. This observation was made in the case of water, where the description of its rheology in our ontology classifies it as an instance of a Newtonian liquid. Similarly, fruit juice possesses the properties of a shear-thinning Newtonian fluid.

In conclusion, creating an ontology for the rheology of food liquids could be a promising area of research, enabling a better understanding of the physical and mechanical properties of liquid products. An ontology provides a common language to describe and understand the complex interactions that occur between food ingredients, production processes, and environmental conditions. It can aid scientists in understanding the terminology and assist food engineers in developing new liquid products, enhancing their texture and taste, and optimizing production processes for efficiency and quality.

Furthermore, the ontology can contribute to improving food safety by identifying factors that affect the stability and shelf life of liquid products. Overall, an ontology for the rheology of food liquids serves as a valuable tool for the food industry and scientific research, leading to significant improvements in designing and producing healthy and delicious liquid products.

While this article primarily focuses on the rheology of food liquids, it's important to note that the rheology of solid food products is also of great importance. Factors such as texture, structure, and consistency of solid products are key in determining quality

<figure><img src="image_6.png" /></figure>
and satisfying consumer preferences. The rheology of solid food products can help
understand and enhance the quality and stability of these products during production
and storage.

Therefore, it's crucial to continue research in the field of rheology of solid food
products and expand existing ontologies to include this significant component of food
science.

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