Recent Advances in Moderate Electric Field (MEF) Systems for Sustainable Food Processing

Abstract

Moderate electric field (MEF) technology is an electro-heating technology that involves the application of electric fields less than 1000 V cm⁻¹, with or without the effect of heat, to induce heating and enhance mass transfer in food processing operations. The rapid heating capabilities and higher energy efficiency make MEF a viable alternative to traditional processing methods in the food industry. Recent advancements in MEF processing of foods have focused on optimizing equipment design and process parameters and integrating digital tools to broaden their application across a wide range of food processes. This review provides a comprehensive overview of recent developments related to the design of MEF systems for various operations, including single and multicomponent food systems. The thermal efficiency and energy saving of MEF treatment in various food processing operations largely depend on the type and arrangement of the electrodes, and operating frequency and composition of the food matrix. A thorough understanding of the electrical properties of single and multicomponent food systems is crucial for analyzing their behavior and interactions with applied electric fields, and for designing an efficient MEF system. In addition, integrating digital tools and physics-based models could play a significant role in real-time monitoring, predictive process control, and process optimization to enhance productivity, reduce energy consumption, and ensure improved product quality and safety. This makes the MEF technology economically viable and sustainable, which also improves the scalability and integration into existing processing lines.

1. Introduction

The food industry is a dynamically developing sector driven by the continuously growing consumer demands and increased pressure to adopt sustainable and energy-efficient technologies for the sustainable processing of foods. Traditional techniques used for processing foods are often associated with drawbacks, including long processing time, high energy consumption, nutrient degradation, and undesirable changes in the properties of food [1]. Adopting innovative food processing technologies that minimize these drawbacks and reduce environmental impact while maintaining product quality and safety for extended shelf-life is essential for meeting the growing global demand for sustainable, nutritious, and safe foods [2].

The fast-increasing global population (to reach 10 billion in 2050) has exacerbated the challenges by increasing food production by approximately 70% [3]. This increase has a significant impact on global economic development and poses a great challenge to the food industry and the environment. These challenges can be addressed by adopting innovative technologies that contribute to green processing by reducing energy consumption and water consumption, while also allowing recycling of by-products through a bio-refinery. Food processing intensification and sustainable processing strategies, which make food production and manufacturing more efficient, sustainable, and cost-effective, are essential for the food system [4]. In addition, integrating advanced technologies and using innovative methods to improve productivity, reduce energy consumption, and minimize waste contribute not only to production efficiency but also reduces impacts on the environment.

In recent years, the application of both thermal and non-thermal emerging technologies that are based on electrical energy has shown a pivotal role in addressing the challenges faced by the food system, contributing to achieving sustainable development goals (SDGs) [5]. Among these, moderate electric field (MEF) is one of the efficient ways of using electrical energy in food processing operations, which arise from its advantages of direct application and volumetric heating, tremendously reducing heating times and providing an outstanding alternative processing method to conventional systems [6,7,8,9,10]. Unlike the high voltage pulsed electric field (PEF), which applies a high electric field strength (10–80 kV cm⁻¹) in the form of pulses for a short period (μs or ms), MEF involves the application of alternating electric fields typically under 1000 V cm⁻¹ with/without thermal effects. However, at low electric field strength (usually below 100 V cm⁻¹), thermal effect is more dominant than electrical effects, which is referred as ohmic heating. What makes MEF technology different is, therefore, its ability to involve both thermal and non-thermal effects, depending on the frequency and wave type used [11]. Studies have also indicated that MEF has the potential to improve processing efficiency and intensify sustainable processing of foods while also reducing impact on the environment [12,13,14,15,16,17]. Its application to solid, semi-solid, and liquid products also makes it a superior technology for a wide range of food-processing applications. However, the overall effectiveness and performance of MEF processing technology are highly affected by the behavior and properties of the food product, as well as the design of the system and materials used for construction.

Recent advancements in MEF processing have focused on the development of innovative equipment and control systems to improve the uniformity of electric field distribution, further enhancing processing efficacy and reducing energy losses [13]. Alongside equipment development, significant progress has been made in developing mathematical models to design and optimize MEF operations [18,19,20,21,22,23,24]. These tools not only help in the design of efficient MEF systems but also provide insights into the mechanism of MEF processing and the interaction of electrical energy with single or multicomponent food materials.

Therefore, this review aims to present an overview of the current developments, challenges, and prospects of MEF technology application for process intensification and sustainable processing of foods. This review discusses various MEF system designs and configurations, along with the processing parameters used for various food processing operations. Additionally, it summarizes experimentally measured electrical conductivities of single and multicomponent food systems as well as empirical models used to predict the conductivities. For this purpose, previously conducted original research articles that appeared in the scientific literature database that were relevant to the objectives of this review were examined and used.

2. Moderate Electric Field (MEF) Systems and Current Applications

2.1. Basic Mechanism of MEF Technology

The principle of MEF heating involves the passage of an alternating current (AC) through an electrically conductive material placed between two electrodes (Figure 1), which has inherent resistance and, as a result, generates heat volumetrically within the material [25]. These materials act as electrical resistors where electrical energy is dissipated and converted into thermal energy.

The thermal energy generated is directly proportional to the electrical conductivity of the material and the square of the electric field strength applied. Depending on the range of the electric field applied, the effects of MEF with or without attending heat tend to have effects on the food and biological materials [16,25]. Generally, the electric field strength considered for MEF applications is in the range between 1 and 1000 V cm⁻¹ [25]. The higher the electric field strength, the greater the interaction with biological cells and the impact on the cell structure. Generally, MEF treatment can be applied to all food materials that contain water over 30% and dissolved ions that can sufficiently conduct electricity [26]. However, the electrical conductivity range between 0.01 S m⁻¹ and 10 S m⁻¹ is considered the most satisfactory, with optimum efficiency between 0.1 S m⁻¹ and 5 S m⁻¹ [27].

A typical MEF system consists of a MEF chamber, a pair of electrodes, an AC power supply, temperature sensors, and a control system. The power supply delivers voltage and current to the system through electrodes depending on the conductivity of the medium, while the non-conducting chamber is used to hold food product (Figure 1).

MEF heating has been widely employed in food processing operations such as cooking ready-to-eat foods [15,28,29,30,31,32], pasteurization of fruit juice [33,34,35,36,37], pasteurization of milk [38], tempering/thawing of frozen foods [39,40], bread baking [41,42,43,44,45], and many other operations. MEF has also been successfully applied to assisting the permeabilization of cell membranes with/without the effect of heating in processing operations such as extraction [46,47,48], blanching [49,50,51], peeling [52,53], drying [54,55,56], and fermentation [16,57]. Figure 2 shows the major application areas of MEF in the food industry for process intensification and sustainable processing operations.

2.2. Advances in MEF Equipment Design

Advances in MEF equipment design primarily focus on improving efficiency, enhancing process control, optimizing energy usage, and improving heating uniformity for a range of food processing operations. A well-designed MEF system not only contributes to the efficient conversion of electrical energy into thermal energy but also improves the overall performance of the processing and control of the system. These improvements are driven by the need for sustainable and energy-efficient technologies that can help maintain the quality and safety of food products while also minimizing food waste generation and impact on the environment. The next section summarizes recent advances and developments in MEF system design, including electrode configuration and operating parameters.

2.2.1. MEF Chamber and Electrode Materials

The MEF chamber for food applications is constructed from highly insulating, electrically non-conductive, and food-grade materials to ensure the electric current is directed through the food material without causing contamination. Most commonly used construction materials for batch chambers or flow channels for continuous systems include polytetrafluoroethylene (PTFE or Teflon), polyethylene terephthalate polyester (PET-P or Ertalyte) and polyether ether ketone (PEEK), and polypropylene (PP) [58,59]. MEF cells can also be made from clear acrylic polymers for applications such as bread baking [42].

During MEF heating applications, the presence of electrodes in contact with the materials is the principal requirement to conduct electrical current and generate energy within the food materials [60]. For solid or semi-solid foods, electrical current flow is assured by direct contact with the food pressing against, or reliably contacting, electrodes (batch or continuous pumped flow); it can also be assured, for liquids, through immersion in a conductive environment or in a continuous pumped flow configuration where liquid materials are in direct contact with the electrodes. The arrangement, size, shape of the electrodes, spacing between the electrodes, the size of the MEF cell, and the type of configuration significantly affect the heating performance. Furthermore, the type of electrode materials also play a significant role in determining the overall behavior and performance due to their different capacity to withstand electrochemical reactions that might occur during processing. The electrodes used in MEF heating are generally made up of materials that are highly conductive to electric currents, such as stainless steel, aluminum, titanium, platinized titanium, and graphite [59]. For food applications, food-grade electrodes made up of aluminum, stainless steel, titanium, and platinized titanium are preferred for quality reasons. Generally, titanium and platinized titanium are the most preferred electrodes as they can reduce the electrochemical reactions compared to stainless steel and aluminum, which are prone to electrolysis [61]. The extent of the electrochemical reactions occurring on the electrodes is influenced by factors such as the pH of the food, frequency, and the type of material used [62,63,64]. Electrode materials made up of platinized-titanium showed the capacity to prevent electrochemical reactions while also being less affected by different pH conditions [63].

In addition, previous studies reported that the thickness of the electrode material also plays a significant role in minimizing heat loss [61] where thicker electrodes resulted in lower temperature rise, indicating a lower electrical resistance. Therefore, the selection of an appropriate electrode material is essential to prevent the formation of electrochemical reactions on the interface of the electrodes.

2.2.2. MEF System Design and Electrode Configurations

The most common electrode configuration used in a MEF system includes parallel plate or rod, collinear, coaxial, and staggered electrodes, which can be incorporated either in batch or continuous operating systems [59]. In a batch MEF system, two plate- or rod-type electrodes are typically arranged in parallel, with their distance set based on the required electric field strength and heating rate. In continuous systems, electrodes can be configured in parallel (transverse), collinear, or coaxial electrode arrangements. In parallel configuration, fluid products flow between two parallel electrodes (plate or rod electrodes) and perpendicular to the electric field, while in collinear configuration, products flow from one end of the electrode to the other one parallel to the electric field [65,66].

The parallel plate configuration offers uniform electric field distribution and has been widely used for many food-processing applications, including food products with low electrical conductivity (<5 S m⁻¹). In the coaxial configuration, the food product is placed between two cylinders, where the internal cylinder is used as a source of high voltage and the external cylinder is used as a ground electrode. This configuration is ideal for liquid products with small particles due to the small gap between electrodes, resulting in low resistance and high current flow. The collinear configuration consists of a hollow high-voltage electrode and grounded electrodes with a circular hole, separated by an insulating spacer. This type of configuration is widely used in continuous MEF treatment of liquid products with electrical conductivity in the range from medium to high [59]. However, the distribution of electric field strength is not uniform, and it depends strongly on the insulating spacer placed between the electrodes.

Staggered configuration consists of rod-type electrodes, which are placed at fixed distances on diametrically opposite ends of a tubular MEF chamber. Other types of electrode arrangement include the one used in continuous fluid jet ohmic heaters, where the electric field is applied to the falling jet between two electrodes [67]. This type of arrangement is applied to viscous products to minimize fouling problems. The desired electric field strength can be achieved by modifying the geometry and distance of the insulating spacer. Selection of the type of electrode arrangement may also depend on the process and type of product. For example, a system developed with five sets of electrodes arranged in sequence using elbow-shaped pipes [68] improved exposure to the applied electric field, allowing fast and uniform heating due to the sequential and zig-zag type flow between the electrodes. Similar improvement was also reported by [69] in which they used two sidewise parallel electrodes arranged in two chambers and powered by a generator (500 V and 60 A) to heat viscous foods.

MEF heating systems can also incorporate moving electrodes for synergistic processes involving high-pressure [70]. They developed a pressure-ohmic thermal sterilization system to investigate the synergistic effect of thermal and high-pressure sterilization of carrot samples which resulted in significantly reduced pre-heating and cooling time with better quality retention compared to treatments involving only the electric field.

Table 1. Different configurations of MEF chambers and electrode arrangements used for food applications.

MEF Chamber Configuration	Food Processing Applications	References
Parallel plate electrode–batch rectangular system	Ready–to–eat foods (solid–liquid mixtures)	[11,71,72,73]
	Cooking rice	[74,75,76]
	Cooking shrimps in brine mixtures	[59,77,78]
	Potato cubes and whole potatoes in NaCl solution	[79]
	Jalapeno and serrano peppers (solid–liquid)	[80]
	Orange juice with alginate particles	[81]
	Cooking meat and meat products, chicken sausage	[82,83,84]
	Bread baking	[41,42,45]
Parallel plate electrode—cylindrical system	Apple juice (sequential electric fields)	[85]
	Pasteurization of fermented red pepper paste	[86]
	Tomato juice (pulsed ohmic heating)	[87]
Cylindrical fermenters/reactors with parallel electrodes	Fermentation of soya bean in NaCl solution	[57]
	Fermentation–growth kinetics and metabolic activity of Lactobacillus acidophilus	[88]
	Fermentation–growth kinetics of yogurt starter cultures	[89]
Collinear MEF heater (cylindrical)	Sterilization of liquid food (mathematical model)–continuous system	[90]
The Emmepiemme design	The Emmepiemme design for continuous operation (60–480 kW)–tubular systems applied for industrial applications	[91]
Elbow electrodes (used five sequential elbow-type electrodes	Continuous ohmic heating for microbial inactivation	[68,85]
Sidewise parallel electrodes	Cooking high–viscosity food formulation (chicken chow Mein sauce)	[69]
Electrodes in flask	Ohmic-assisted hydro–distillation of citronella oil from Taiwanese citronella grass	[92]
	Oil extraction during ohmic–hydro-distillation	[93,94]
	Ohmic assisted–hydro–distillation–ethanol distillation, essential oil	[95,96]
Movable electrodes	Pressure-assisted thermal treatment of carrot samples in NaCl solution	[70]
Fluid jet heater system	Continuous flow heating using fluid jet–viscous foods.	[67,91]

presents a list of various electrode configurations used for various food processing operations.

2.2.3. MEF Frequency and Waveforms

Frequency and waveform are operating parameters that refer to the repetition rate and shape of the alternating current (AC) signal applied to the food material, respectively. These parameters significantly affect the heating behavior and MEF heating effectiveness. Some MEF systems operate at the standard AC frequencies of 50 Hz (most EU, China, and Australia) and 60 Hz (US and Canada) based on the operating area. However, modern AC power supplies that can deliver frequencies in the range of kHz are in use for improved heating performance and efficiency. The high frequencies are generally preferred to reduce the effect of electrochemical reactions on the electrodes, which may cause corrosion of the electrodes [79,97,98]. Ref. [79] observed an improvement in heating uniformity at 300 kHz compared to 12 kHz during heating potato samples, which could be due to the rapid change in its polarity, while lower frequencies tend to increase cell permeabilization. Similar results showed that lower frequencies between 50 Hz and 60 Hz are highly susceptible to promoting electrode corrosion and gas generation [35,99]. A study on the effects of using low and high frequencies (50 Hz and 10 kHz) on the corrosion of stainless-steel electrodes during cooking beef meat patties revealed that 10 kHz frequency significantly reduced corrosion of the electrodes [100]. Similarly, Ref. [101] also reported that a higher frequency of 20 kHz resulted in higher electrical conductivity compared to the beef samples treated at 50 Hz at the same electric field strength of 16.67 V cm^−1, which indicates a higher heating rate. Hence, increasing the frequency of the applied electric field could reduce the impedance of the food matrix while also increasing the heating rate due to the increased movement of electrons as a result of high frequency.

The most common waveforms used are sinusoidal, square, and triangular. In their study on heating salsa using different frequencies and waveforms, Ref. [102] indicated that the heating rate for square waves was slower at a lower frequency (60 Hz) compared to sine and sawtooth waves. However, they indicated that there was no significant difference in the heating rate at higher frequencies between 500 Hz and 20 kHz, as the shorter cycle times minimized waveform-dependent effects.

2.2.4. MEF Process Control

Controlling the power delivered during MEF heating operations is one of the critical parameters to maintain energy efficiency while achieving the desired effect on the food. The total power absorbed by the food material is dependent on the electric field strength applied and the resistance of the food matrix. Control of power for MEF systems working at regular frequency (50 Hz or 60 Hz) can be achieved by controlling the thyristor voltage whilst inverter technology is incorporated to generate a high-frequency supply [59]. Real-time monitoring of MEF parameters can be achieved using data received from sensors (voltage, current, temperature, pressure, humidity, etc.). The proportional-integral-derivative (PID) control method receives input data from sensors and determines the difference between the actual value and the setpoint, and adjusts the output to control the desired parameter. This indicates that the efficiency of the process significantly depends on proper control of the process, which requires an integration of programmable logic controller (PLC) or microcontrollers for real-time monitoring and adaptive control. Recently, Ref. [103] compared the advanced process controllers based on proportional-integral-derivatives (PID), model predictive control (MPC), and adaptive model predictive control (AMPC), and reported that AMPC systems, which use an online model running in real-time, effectively control highly dynamic systems that require continuous adaptation. Compared to PID and MPC, the AMPC method provides precise and measurable energy directly into a product, often very rapidly, and is well-suited to such advanced types of control method.

2.3. Electrical Conductivity of Foods

The electrical conductivity of food is a critical factor that helps us to understand how a food material behaves with the applied electric field during the conversion of electrical energy into heat. Whether the food system is a homogeneous single-component or heterogeneous multi-component system, understanding its electrical conductivity is essential for selecting proper processing conditions and designing MEF equipment tailored to the specific processing operation. The electrical conductivity (S m⁻¹) is determined using the following equation (Equation (1)):

$$\mathsf{\sigma }={\displaystyle \frac{\mathrm{I}}{\mathrm{V}}}\hspace{0.33em}{\displaystyle \frac{\mathrm{L}}{\mathrm{A}}}$$

(1)

where I is the current (A), V is the voltage (V), L is the distance between the electrodes, and A is the contact area (m²).

The electrical conductivity of a food product can be determined directly using a conductivity meter, impedance meter, two-electrode method (derived from the conductance, which is the inverse of resistance), or dielectric method, where dielectric properties are used to determine the electrical conductivity [79,104]. The parallel circuit equivalent model has also been used to determine the electrical conductivity of a mixture using the equivalent resistance of each component [76,105]. Due to the complex nature of food materials, which contain different compositions and ionic content, the value of electrical conductivity varies for each food product. In products containing higher values of ionic ingredients, the electrical conductivity is higher due to the electrolytic behavior of the contents. On the other hand, the structure of the products, such as muscle fiber structure in meat products, also affects the electrical resistance, which is attributed to the structural density or connective tissue and intracellular fat content of the meat [106]. Most food systems contain multicomponent systems in which both solid and liquid coexist or are mixed during preparation processes, each with varying electrical conductivities that influence their response to the applied electric fields. The solid particles dispersed in a liquid (solid–liquid mixture) interact with the applied electric field based on the size, shape, orientation, and concentration. The composition and ion content of the surrounding liquid, which is part of the food system or serves as a carrier to conduct electric current, also play a significant role during heating and contribute to the overall electrical conductivity of the solution. Ref. [107] measured the electrical conductivity of a mixed food system (chicken chow Mein) and individual components, and found that the electrical conductivity of the combined system was higher than each single component. The difference could be due to the contribution of ions from solid components to liquids and the presence of ionic compounds such as salt and other ingredients. Furthermore, the electrical conductivity of multicomponent foods can also be affected by the orientation of solid food products in the treatment chamber (series or parallel) or the level of particle mixing when treated together. Ref. [73] studied the effect of orientation and solid–liquid ratio on electrical conductivity and reported that the resistance to the electric current flow is slightly affected at lower solid concentrations, while no significant difference was reported for high solid concentration systems.

Table 2. Electrical conductivity of single and multicomponent food materials.

Food Materials	Temperature Range	Voltage Gradient and Frequency	References
Beef (wagyu beef)	5 to 65 °C	16.67 V cm−1, 50 Hz to 20 kHz	[101]
Chicken (breast, tender, thigh, drumstick, and separable fat)	25 to 140 °C	19–25 V cm−1, 60 Hz	[108]
Chicken Chow Mein (multicomponent)	25 to 140 °C	15 to 20 V, 60 Hz	[107]
Frozen Tuna fish	−30 to 20 ° C	100 V cm−1, 50 Hz and 20 Hz	[39]
Ham pastes and bologna emulsion	10 to 80 °C	64 to 103 V, 60 Hz	[109]
Lean beef and chicken	25 to 120 °C	60 V, 60 Hz	[110]
Meat emulsion batters (frankfurter and luncheon meats)	15 to 80 °C	4 V cm−1, 50 Hz	[111]
Meatball (lean pork)	30–90 °C	20.5 V cm−1, 50 Hz	[112]
Minced beef-fat blends (25.9% and 15% fat levels)	20–80 °C	20, 30, 40 V cm−1, 50 Hz	[113]
Pork cuts (leg lean, shoulder lean, belly lean, back fat and belly fat)	20 °C	3.6 V cm−1. 50 Hz	[106]
Whole meats and processed meat ingredients	5 to 85 °C	20 V cm−1, 50 Hz	[27]
Yellowtail muscle filets	15–80 °C	10 V cm−1, 50 Hz–20 kHz	[114]
Cubic particles (carrot, potato, radish, beef muscle, pork muscle and ham)/5% starch-water solution (0.15–1.5% w/w salt)	25–125 °C	60 Hz	[105]
Raw and cooked tuna	Room temperature	Measured with an electrical conductivity meter	[104]
Salmon muscles	5–70 °C	50 Hz–20 kHz	[115]
Orange juice containing alignate particles	25–100 °C	20 V, 50 Hz	[81]
Minced tuna and pollock surimi	−40–10 °C	50 Hz–20 kHz	[40]
Whole potato tubers and potato cubes	20–100 °C	1.38 kHz–11.2 MHz	[79]

lists food mixtures (multicomponent) with reported electrical conductivities in the literature, measured at different temperature ranges and voltage gradients.

2.4. Electrical Conductivity of Foods—Prediction Equations

The electrical conductivities of food materials can be either experimentally measured or predicted using empirical or semiempirical equations. However, the complex constituents or composition of food products made the prediction more difficult, as the properties of food products vary based on their type, origin, species, or maturity. The electrical property data of different food products measured and published by different authors have been presented in Table 1. In this section, the empirical equations used to model and/or predict the electrical conductivities of food materials are presented. Ref. [116] presented some models of electrical conductivities of different products developed over the years as a function of different influencing parameters. Unlike homogeneous products, the electrical conductivity of heterogeneous products can be influenced by multiple parameters. It is important to mention that finding an equation that can be implemented for different food products is difficult due to the complex nature of food compositions. In this case, multivariable prediction models are required to simulate conductivity. The values of electrical conductivity may also depend on different parameters’ dependency on the electrical conductivities of temperature, voltage gradient, frequency, and solid content, which were also discussed.

Table 3. Electrical conductivity of single and multicomponent food systems–prediction model equations.

Food Product	Electrical Conductivity—Model Equation	Description	References
Chicken, beef, and vegetables (potato, carrot, yam)	$\mathsf{\sigma }={\mathsf{\sigma }}_{\mathrm{ref}}\left[1+\mathrm{m}(\mathrm{T}-{\mathrm{T}}_{\mathrm{ref}})\right]$	σref is the σ of the product at the reference temperature Tref (25 °C), and m is the temperature compensation constant	[110]
Cooked meatballs	$\begin{array}{l}\mathsf{\sigma }\hspace{0.17em}=0.824+0.028\mathrm{T}+0.970{\mathrm{X}}_{\mathrm{salt}}-2.730{\mathrm{X}}_{\mathrm{pepper}}-\\ 0.347{\mathrm{X}}_{\mathrm{flour}}-0.388{\mathrm{X}}_{\mathrm{sugar}}+4.075{\mathrm{X}}_{\mathrm{STPP}}-1.780{\mathrm{X}}_{\mathrm{garlic}}\end{array}$	X is the weight ratio of ingredients to meat, STPP is added tripolyphosphate and T is the temperature (°C)	[112]
Fresh meatballs	$\begin{array}{l}\mathsf{\sigma }=1.23+0.036\mathrm{T}+0.920{\mathrm{X}}_{\mathrm{salt}}-2.070{\mathrm{X}}_{\mathrm{pepper}}-\\ 0.412{\mathrm{X}}_{\mathrm{flour}}-0.477{\mathrm{X}}_{\mathrm{sugar}}-0.840{\mathrm{X}}_{\mathrm{garlic}}\end{array}$	X is the weight ratio of ingredients to meat, and T is the temperature (°C)	[112]
Lamb	$\mathsf{\sigma }=0.344+6.8\times {10}^{-3}(\mathrm{T}-273.15)$	T is the temperature	[117]
Minced beef meat	$\mathsf{\sigma }=\mathrm{A}+\mathrm{B}\mathrm{T}\hspace{1em}(\mathrm{S}/\mathrm{m})$	A (S m−1) σ of a sample at a reference temperature of 0 °C and B (S m−1 °C) is the temperature dependency constant which is determined by regression	[113]
Minced beef-fat blend	$\mathsf{\sigma }=\mathrm{A}+\mathrm{B}\mathrm{T}+\mathrm{C}{(\mathrm{fat}\%)}^{\mathrm{N}}\hspace{1em}(\mathrm{S}/\mathrm{m})$	A (S m−1) σ of sample at a reference temperature of 0 °C, B (S m−1 °C) is the temperature dependency constant which is determined by regression, and C (S m−1 per fat%) is σ constant. The N power term indicates the effect of initial fat level on σ	[113]
Salt solution	${\mathsf{\sigma }}_{\mathrm{s}}=\mathrm{c}\left[1.47+0.027(\mathrm{T}-{\mathrm{T}}_{\mathrm{ref}})\right]$	c is the salt concentration (%) and Tref is the reference temperature (25 °C)	[118]
Sausages	$\mathsf{\sigma }=\mathsf{\omega }{\mathsf{\epsilon }}_0 {\mathsf{\epsilon }}^{″}$	ω = 2πf, f is the frequency (Hz), ε0 is the permittivity of free space (~8.85 × 10−22 F/m), and ε″ is the dielectric loss factor through the frequency of applied field	[22]

presents some models implemented for meat and meat products, including fish.

2.5. MEF Treatment in Electrically Conductive Packaging

In MEF heating, a product can be placed in an electrically conductive packaging system that allows the flow of current through it while also avoiding the direct contact of food with electrodes to ensure safe processing. During the manufacturing of food products such as sausages or frankfurters, the mixed batter can be filled into conductive casings that allow the passage of electrical current during direct contact with electrodes for MEF treatments. Other conductive packaging materials, which have been developed using polymers such as polypropylene with carbon black particles, have been used for packaging, which substantially reduced the need for aseptic packaging [119]. They produced carbon black films containing 30% (w/w) carbon black powder by extruding it with propylene pellets to form a 0.25 mm thick film that was successfully used for food pasteurization.

A flexible package for food reheating and sterilization using pulsed ohmic heating during long-duration space missions was also developed using a V-shaped flexible pouch material and powered with a pair of metal foil electrodes [120]. The heating in this package resulted in non-uniform heating, especially around the edges and corners. Later, it was redesigned using a rectangular shape containing stainless foils, which significantly improved the heating uniformity [121]. Recently, Wattanayon, Udompijitkul [81] reported on the use of electrically conductive packaging materials for solid–liquid mixture food products. Although heating in electrically conductive packaging material is an effective method, the cost of the package, food contact migration, and environmental impact are more concerning issues [119].

3. The Role of Digital Tools in MEF Processing

In this era of Industry 4.0, capitalizing on the application of digital technologies for sustainable food processing requires employing various digital tools to monitor, predict, optimize, and design food equipment, processes, and processing conditions. These digital tools that are employed to revolutionize and transform the food industry include the Internet of Things (IoT), digital twins, blockchain, physics-based digital tools, and integration of smart and advanced processing technologies driven by artificial intelligence and real-time data [19,122,123]. The implementation of physics-based digital tools in the food system has demonstrated its potential to optimize production, enhance food quality and safety, minimize waste generation, improve efficient resource utilization, and reduce energy consumption [124,125,126].

The development of digital twins and machine learning-based AI, which integrate computer simulations into real-world processes, is expanding the use of science-based computer simulations beyond process or product design and optimization [124]. Furthermore, the major problems related to quality loss, high energy consumption, and the production of large amounts of food waste from processing industries can be monitored and controlled with the help of these digital technologies. However, due to the extensive and high-quality dataset requirements to accurately capture the complexity and variability of food process, ML models may face the risks of limited accuracy and poor real-world performance. In this regard, future big-dataset platforms could enhance predictive accuracy by enabling better learning and integrating multimodal data for richer insights. Various digital tool models to predict physical and chemical changes that lead to quality changes during food processing operations have been developed for food processing operations, such as for the pasteurization of beverages [127,128], microwave cooking [129], meat supply chain [130], and cooking chicken filets in the oven [131]. Furthermore, these tools were also employed for predicting and controlling process parameters during kombucha fermentation [132], for performance improvement in the food industry [123], in the manufacturing of ingredients [133], monitoring and cooking of French crepes [134], monitoring fruit quality [135,136], and autonomous thermal food processing [131].

Developing a digital twin framework for processes assisted by MEF technology enables optimized control and monitoring, enhancing efficiency and productivity, and optimizing cost analysis and management tools [124,125,136,137]. In order to make food-processing applications that involve thermal treatment controllable, it is important to gather real-time data from the physical system, which is usually difficult as it cannot capture all the necessary information [131]. Therefore, integrating physics-based models with data-driven digital twins can revolutionize food processing and enhance control systems. Furthermore, standalone application tools (Apps) developed based on validated physics-based models, which show only input parameters and outputs while the complex multiphysics solution is hidden, are also broadening the capability of modeling and simulation.

The integration of digital technologies in MEF processing plays a crucial role in designing, predicting, and controlling processing conditions, ultimately improving efficiency while minimizing energy consumption. Machine learning algorithms, artificial intelligence, and digital twins enable real-time monitoring and optimization of MEF parameters, ensuring precise control over electric field distribution, heating effects, and interactions with food material. These advancements help prevent overprocessing, enhance process reproducibility, and reduce operational costs. Furthermore, physics-based digital technologies, including computational modeling and simulation tools, provide deeper insights into the fundamental mechanisms of MEF interactions with food matrices. By leveraging predictive modeling, these tools aid in optimizing electrode configurations, improving energy efficiency, and scaling up MEF applications from lab-scale to industrial-scale production.

However, modeling complex food matrices with heterogeneous composition and phase-separated systems is challenging due to multi-scale structures, non-uniform composition, and dynamic interactions of the components with the applied electric field during the processing. This requires complex coupled models to capture spatial variability, non-linear behavior and time/temperature dependent changes across different matrices.

4. Future Prospects of MEF Technology

MEF treatment has shown strong potential in various operations in food processing, applied alone or in combination with other processing techniques. Its application is not restricted to only heat treatments but also to inducing electroporation in biological materials. Despite its advantages of rapid heating, improved energy efficiency, and reduced environmental impact, MEF technology is not widely implemented in industrial manufacturing facilities. Many industrial MEF systems in use are in the areas of the dairy industry, fruit and vegetable processing, including juice and puree, and a few in the meat and meat products industry. Various applications of MEF are still at the laboratory scale, and industrial implementation remains a challenge. This could be attributed to the design of most industrial MEF systems, which are mainly intended to treat liquid and semi-liquid products. Its application for multicomponent food systems containing different phases is challenging due to its complex composition and interaction with the applied electric field.

Similarly to PEF, MEF has been reported to induce structural change and cell permeabilization. However, unlike PEF, MEF-assisted cell permeabilization is not well-established. The extent of cell disintegration as a result of mild heating and electrical effect applied during MEF requires a thorough study. Future studies should also focus on identifying the synergistic effect of mild heating and electroporation on enhancing mass transfer in various operations such as precision fermentation.

In recent days, there has been a high demand for sustainable food processing methods that can reduce processing time and energy consumption without compromising the quality and safety of the product. MEF applications in combination with other conventional and non-conventional treatments can also be considered. Integration of emerging technologies into existing systems plays a significant role in improving efficiency, reducing energy consumption, and reducing impacts on the environment. The future of MEF in the food industry lies in its seamless integration with traditional food processing systems and synergistic effect with other emerging thermal or non-thermal technologies. As food industries move forward towards smart and sustainable manufacturing, energy-efficient technologies such as MEF have significant potential to improve the environmental footprint of food processing by lowering food loss and food waste, and lowering greenhouse gas emissions, while also improving the quality and safety of food products. However, the capital cost required to replace conventional systems or integrate MEF in existing systems is a challenge and limits the industrial uptake of this technology. Further economic studies and in-depth research on optimization of MEF systems which improve the efficacy of the process while also reducing energy consumption and improving sustainable processing are suggested.

Future advancements in the application of digital tools, such as the Internet of Things (IoT), physics-based modeling and simulation, digital twins, and machine learning/artificial intelligence, hold great potential for transforming and revolutionizing food processing. Integration of these technologies with real-time monitoring using IoT sensors, machine learning/artificial intelligence-driven optimization tools, and digital twins can enhance the efficiency and scalability of MEF-assisted processes in the food industry. These tools can be implemented to model the electrochemical reactions on the electrodes to predict electrode wear and use predictive maintenance to improve process and energy efficiency. Future industrial application of MEF will require advanced control systems integrating real-time monitoring, adaptive feedback loss, and optimized configurations to enhance the sustainability of the process. Furthermore, a digital twin model, a virtual replica of the physical MEF system integrated with real-time sensor data, can be used to perform predictive maintenance and dynamically adjust parameters in real time to ensure consistent product quality while also minimizing energy consumption.

5. Conclusions

Moderate electric field (MEF) has become a promising alternative emerging technology for food process intensification and sustainable processing due to its advantages of efficient energy conversion and reducing impacts on the environment. The efficiency and effectiveness of the MEF applications depend on the proper design of the equipment and electrode configurations, and an in-depth understanding of the physicochemical properties of food systems and their transformation during application. Even though various designs and configurations of electrodes have been developed to capitalize on the use of MEF, the selection of a proper set-up for a specific process is significantly affected by the type of process and the behavior of the food material. Therefore, understanding the properties of food, especially the electrical conductivities of both single and multicomponent food systems, is fundamental to understanding the behavior of MEF treatment and also to accurately predicting and optimizing the processes.

Predictive tools and physics-based computer simulations can guide the design of MEF systems and develop robust process control systems, enabling more accurate, sustainable, and cost-effective implementation of MEF technology. Physics-based digital technologies are still underutilized in MEF processes, especially in multiphase systems and continuous operations, considering physical and chemical changes occurring during processes. As research progresses, the integration of MEF with advanced computational techniques will be key to overcoming current limitations and expanding its industrial applications.

Future efforts should focus on refining predictive modeling approaches, optimizing process parameters for complex food matrices, and ensuring scalability for widespread industrial adoption. The continued evolution of MEF technology, coupled with digital advancements, will play a pivotal role in shaping the future of sustainable, efficient, and intelligent food processing systems. In conclusion, the adoption of MEF technology represents a significant achievement in environmentally responsible and resource-efficient food processing techniques, aligning with the broader goals of sustainability in the global food system.