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ISSN: 2574 -1241
ISSN: 2574 -1241
Received: October 06, 2022; Published: October 13, 2022
*Corresponding author: Amira Ghezal and Andreas König, Lehrstuhl Integrierte Sensorsysteme (ISE), TU Kaiserslautern Deutschland, Germany
DOI: 10.26717/BJSTR.2022.46.007379
Food and beverage production is a complex rheological field to work with because it involves dealing with a wide range of sample types and behaviors. Viscosity property of food has a significant impact on the food quality, and it could be a risk factor for evaluating the relationship between food retention and human health caries, hence urgently raises the need of immediate analysis and evaluation and monitoring the viscosity of food. Viscosity measurements of food and beverage products help maximize both production and process-ability efficiency and ensures a consistently high quality of the product. This paper presents and reviews a survey of conventional viscometers and rheometers used and pre-sented in markets, comparing their efficiency with new technology and sensing methods for viscosity measuring of food products. The paper concludes by reviewing the new approach to a tiny and porta-ble device as a friendly user, accurate with low cost to be equivalent to the laboratory measurements efficiency.
Keywords: Viscosity Monitoring; Mobile Food Scanners; In-Line Sensors
Viscosity is one of the most important internal physical qualities to consider when analyzing liquid behavior and fluid motion for any application, it is defined as a fluid’s resistance to flow which is essential for detecting food authenticity, contamination, freshness, and consumption. When a material’s properties, such as molecular weight and density, vary, the viscosity of food changes, leading to unique functional products, and therefore the quality is altered [1]. It has been demonstrated that viscosity can affect its retention on tooth surfaces and oral clearance, particularly in 3-6-year-old children, where milk and dairy products are the most frequently consumed food products, which must be determined prior to consumption. Furthermore, viscosity can be considered a risk factor for evaluating the relationship between food retention and dental caries [2]. Additionally, research revealed that the viscosity of a semi-solid food effects postprandial metabolism and nutritional bioavailability by affecting eating and stomach emptying rates, and that long-term adjustment of rheological characteristics of diet influences the risk of chronic diseases [3]. Hence, it is necessary to detect and monitor the viscosity of food products that deal with the flow and deformation of foods in real-time. The most popular techniques to represent viscosity are dynamic and kinematic. Dynamic viscosity provides information on the force required to make the fluid flow at a certain rate [4]. If this is of interest, the mechanical stress that can be explained in terms of dynamic viscosity is more suitable for understanding the intermolecular interaction. Due to the simplicity of kinematic viscometers, it has been more convenient when the interest is the fluid motion and velocity field since it carries information about the propagation of movement by friction [5]. Most «kinematic» viscometers use gravity to drive the fluid flow. Moreover, take into consideration, not all fluids behave in the same way, there are two types: Newtonian and Non-Newtonian behaviors. Simple liquids with tiny molecules that do not interact or create any linked structure exhibit Newtonian behavior. However, it must be pointed out that long-chain polymers at low concentrations can also show Newtonian behavior. An easy way to demonstrate Newtonian behavior is to double the shear stress during a viscosity test, which should result in doubling the shear rate. In Newtonian fluids, the viscosity remains constant, regardless of changes to the shear rate [1,6].
Examples of typical Newtonian fluids include, water, filtered depectinized juices, refined vegetable oils, sugar syrup, and wines [7]. But, in non-Newtonian fluids, the viscosity fluctuates. These fluids in-clude these types: solutions of biopolymers (also called gums and hydrocolloids), chocolate, starch dispersions, baby foods and other pureed fruit ´ and vegetable products, orange juice, tomato juice, paste and concentrate, mustard, mayonnaise, salad dressing, concentrated milk, and yoghurt [7]. Non-Newtonian fluids has shear thinning properties because its viscosity decreases as you increase the shear stress [8]. Fluids with larger, more complex, molecules will have higher viscosities. This is particularly true for the long chain polymers that are found in foods such as proteins, starches, hydrocolloids, or gums, etc. Another striking property of these materials is that they consist of numerous chemical groups (hy-droxyl groups, anionic groups etc.) along the length of the polymer chain that are water loving or hy-drophilic and hence can bind water molecules. The polymer chains can also become entangled with one another, forming networks that are able to trap and immobilize water [9]. There are many different methods and instruments used for measuring the viscosity of food and bev-erage products have been reported in the literature. In Table1 we have explored the fundamental and common measuring devices for obtaining the dynamic and kinematic viscosity of fluidic samples [10-22]. Those traditional devices are the most frequently used viscosity measuring devices, viscometers and rheometers are very valuable in the food manufacture, which can deliver very precise results, it help food scientists in, evaluating the technological properties of food/liquid suspensions at different particle sizes, pH, concentration of ionic compounds, for instance, [23] measuring the viscosity of batters (non-Newtonian materials) to assess the stability of the dispersed phases within the system to different mixing regimes, mixing temperatures, concentration of hydrocolloids, floor times and baking tempera-tures, and predicting the pumpability, heat transfer and heat penetration properties for thermal pro-cessing of liquid foods, monitoring the viscosity of jams and syrups in the production of food condi-ments, to ensure batches are consistent, and analyzing milk’s flow properties when designing piping systems for it [24].
Table 1: Survey of Viscosity Sensing devices for Food Safety present on the market.
Furthermore, a diverse range of industries and sectors of applying viscosity measurements include, pharmaceutical, biotech and clinical research, chemical, beauty and cosmetics, environmental testing, petrochemical and oil [25]. However, in both rheometric and viscometry measurements, a large sample volume and a long measurement time are required. Working conditions are usually considered for sample conditions and pretreatment (constant flow, laminar flow, and constant temperature), since it can influence meas-urement results [23]. These viscometers can measure the viscosity in macroscopic materials but are insufficient for microscopic materials [26]. Researchers have exploited other techniques and sensing methods for viscosity detection for food quality control, listed in Table 2 [27-42]. Most of those techniques are laboratory-based measurement, the cost of viscometry measurements becomes very high since they require substantial labor contribution and need a qualified laboratory assistant. Furthermore, these methods generally involve direct contact with a liquid sample that is being measured, which is often undesirable, because the food sample can be easily contaminated during every point of production or processing. Hence, hygienic/food safety must be considered throughout the whole food supply chain, as it is directly related to the health of consumers whether they are buying canned food or dining in a restaurant [43]. Also, another issue of careful use of food and dumping due to the expiration of the product is getting more popular. Product quality depends not only on the capability and safety of the process and preventive measures but also on the quality of the equipment used, because in many cases washing process can be poor quality, which leads to distortions in measurement results.
Table 2: Survey of Viscosity Sensing Methods for Food Safety.
The efficiency of cleaning procedures is also highly dependent on the design of equipment used, there are some measurement techniques that suffer from the wear-out issue of sensors for contacting measurement, for instance, a tuning fork, has a design, that is difficult to clean and difficult to free from micro-organisms, therefore, increase the risk of post contamination. New technologies for measuring viscosity, have recently been reported using mobile applications and portable, tiny, wireless-based devices for viscosity measurement, such as: Z. B. Suleimenov et al. have proposed a viscometer system using a smartphone, the technology is based on a known method of viscosity measurement through defining characteristics of ball movement in a viscous environment, but setting by an external magnetic field., the processing of primary measurement signals and control of the measurement process is carried out using software installed on user’s smartphone. the advantages of the proposed type of viscometer are the simplicity of technical implementation since this device can be assembled on standard components (microcontroller and Bluetooth module) and this allows to significantly reduce the cost of equipment [44]. As a comparison, non-contact measurement is faster than contact measurement, especially for applications with high sampling rates, and can also measure more points at one time and without putting pressure on the object. They are also less prone to sensor wear and won’t dampen the motion of a target. Although non-contact system has its advantages, contact-based measurement is a good choice for applications with low levels of cleanliness. Contact devices are also recommended for measuring exterior features that are not visible to non-contact devices.
Figure 1 shows the main advantages and constraints of the traditional techniques in comparison with the mobile and in-line equipment for continuous and instantaneous monitoring of the food products properties. Eguchi et al. have developed a new type of non-contact optical and fast in-situ hand-held viscometer-based on a laser-induced capillary wave sensing method with incident angle and irradiation timing controls, where the experimental results confirmed the applicability of the system and provided high stability under hand-held conditions. The device also requires much smaller sample sizes compared to standard measurement methods, once again lending itself to mass-production applications. The obtained results of viscosity were 0.6 mPa·s above the heater at lower parts was calculated to be around 1.3 mPa·s. And 2.8 mPa·s at room temperature [45]. Those new concepts have the advantage of being used as a simple versatile detection application, where the quantification could also be done with a simple smartphone App, or a tiny handheld device without needing an expert, and could be one of our everyday uses, which allows signal analysis to be performed by untrained users without laboratory equipment. In accordance with the basic ideas of the Internet of Things concept [46,47], improvement of information and communication technologies allows eliminating all such factors by software means only (for example, to user’s smartphone computation power). In summary, we explored and criticized the SoA for mobile/inline devices for the viscosity measurement of food products. Recent advances in the field have made it possible to achieve sensitive and specific detection of food quality control using handheld and mobile/inline sensing application, however, even in an embodiment not meeting SoA desktop instrumentation quality can substantially enhance the sensorial fingerprint of a tiny mobile food scanner to efficiently monitor food quality, at an affordable cost.
Figure 1: Comparison for desktop versus integrated approaches.
Emerging microscopic with light scattering technologies (e.g. Raman micsoscopy) which don’t feature viscosity sensing yet, will be capable of offering direct contact with the sample, with no expert/ assistant need, and measuring the viscosity in a large range with an accuracy range of ±1% to ±0.2%. Thus, a novel handheld sensing device should implement the multi-sensory and ML-technique for continuous and instantaneous monitoring of a product’s properties to further approach SoA laboratory equipment.
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