A novel strategy for improving radio frequency heating uniformity of dry food products using computational modeling

Highlights

• A computer model was used to determine effects of DPs and density on RF heating uniformity.

• Uniformity index was used as a criterion to evaluate RF heating uniformity in foods.

• The best UI was determined as a function DPs and density.

• Comparable dielectric constant and small density of container could achieve lowest UI.

Abstract

This study attempted to quantify effects of dielectric properties (DPs) and densities of a surrounding container and treated food products on heating uniformity in a 6 kW, 27.12 MHz parallel plate radio frequency (RF) system. A computer simulation model was established with finite element-based commercial software, COMSOL Multiphysics®, and experiments with 1.5 kg soybean flour packed in a rectangular polystyrene container were performed to validate the developed model. Surface temperature distributions of soybean flour in three different horizontal layers were obtained with an infrared camera, and temperature–time histories at two representative locations inside the container were monitored with two optical fiber sensors. The uniformity index (UI) was used as a criterion to evaluate the RF heating uniformity within food products. Results showed that the RF heating uniformity in food samples was clearly influenced by DPs and density of the surrounding container. UI was the lowest when the surrounding container dielectric constant was in a comparable range of the sample's, with the loss factor values of surrounding container lying between 0.01–0.1% of the sample's. The optimum RF heating uniformity in food products could be achieved with a smaller density value of the surrounding container. The correlations of DPs and density between surrounding container and food products derived from the validated simulation model could provide valuable information and strategy to improve the RF heating uniformity in low moisture foods for insect or microbial control. Thus, the established strategy can further be used for developing effective industrial-scale RF treatment protocols after optimization of this process by the food industry.

Industrial relevance

Although the most important characteristic of radio frequency (RF) treatments is fast and volumetric heating generated by dipole rotation and ionic conduction, edge over-heating is still a major problem for foods heated in rectangular containers. The validated model was used to study the effects of dielectric properties and density of sample and surrounding container on sample uniformity index. Simulated results illustrated that the RF heating uniformity could be improved when the dielectric constant and density of surrounding container and sample were in accordance with the established relationships. The established strategy may provide valuable optimized methods to ensure RF heating uniformity in industrial applications.

Introduction

Low moisture foods, such as wheat flour, corn meal, glutinous rice flour, nuts, spices, and milk powders, are normally considered as shelf stable foods and can be stored for a long time due to preventing bacterial growth in its low moisture environment. Soybean flour is a popular food due to its high nutritional value and functional characteristics, which contain flavonoids, fiber and bioactive peptides (Hassan, 2013). Pathogens and insect pests, however, are found to survive in a low moisture environment more easily for several months (Finn et al., 2013, Johnson et al., 2010, Mohapatra et al., 2015). The qualitative and quantitative losses can reach as high as 30% due to insect damages (FAOSTAT, 2013), which also promote mold growth, toxin production, and product degradation in low moisture foods (Jiao et al., 2012, Vijay et al., 2015). Several cases of soybean flour contamination with Plodia interpunctella greatly affect the quality and taste properties of the endproduct made by the flour (Singh, Satya, and Naik, 2013). Radio frequency (RF) heating involves utilizing electromagnetic energy at a frequency range of 3 kHz to 300 MHz to heat target foods. It has been considered as a novel heating technology for controlling insect and microbial populations in several dry products, such as almond (Gao, Tang, Villa-Rojas, Wang, and Wang, 2011), date (Ben-Lalli, Bohuon, Collignan, and Méot, 2013), lentil (Jiao et al., 2012), raisin (Alfaifi et al., 2014), spice (Kim, Sagong, Choi, Ryu, and Kang, 2012), and wheat (Jiao, Deng, Zhong, Wang, and Zhao, 2015).

Although the most important characteristic of RF treatments is fast and volumetric heating generated by dipole rotation and ionic conduction, edge over-heating is still a major problem for foods heated in rectangular containers (Alfaifi et al., 2014, Tiwari et al., 2011a, Tiwari et al., 2011b). Edges and corners always absorb more electromagnetic energy compared to other regions due to different dielectric properties (DPs) between food products and the surrounding media (usually air), resulting in an uneven electric field distribution (Birla, Wang, Tang, and Hallman, 2004). The non-uniform heating in RF treated products may cause either survivals of pathogens/insects or degraded quality (Birla et al., 2004, Jiao et al., 2012, Kim et al., 2012). A number of methods have been reported for overcoming non-uniform RF heating, such as combination with an external heating or cooling (Birla et al., 2004, Hou et al., 2014, Wang et al., 2010), enclosing in another medium (Ikediala et al., 2002, Jiao et al., 2014), mixing or rotating food (Birla et al., 2004, Chen et al., 2015), modifying electrode shapes (Tiwari et al., 2011a, Alfaifi et al., 2014), and sample movement (Hou et al., 2014). The trial and error procedures are time consuming, costly, and often provide limited information, which cannot easily identify the mechanism behind non-uniform RF heating. Finite element modeling may serve as valuable tools to acquire deep insights on the heating uniformity of products and offer opportunity to clearly understand RF interactions with food components without the necessity of extensive experiments.

Modeling RF processes is a multi-physics problem that involves the solution of coupled electromagnetic and heat transfer equations. Several simulation models have been developed to improve the RF heating uniformity for different food materials, such as apple (Birla et al., 2004), fish (Llave, Liu, Fukuoka, and Sakai, 2015), meat batters (Marra, Lyng, Romano, and McKenna, 2007), peanut butter (Jiao, Shi, Tang, Li, and Wang, 2015), raisins (Alfaifi et al., 2014), shell eggs (Lau, 2015), soybeans (Huang, Zhu, Yan, and Wang, 2015), wheat flour (Tiwari et al., 2011a, Tiwari et al., 2011b), and wheat kernels (Jiao, Deng, et al., 2015). The simulated uniformity index (UI) has been used as criteria to evaluate the temperature uniformity in RF treated products (Alfaifi et al., 2014, Huang et al., 2015, Jiao et al., 2015, Tiwari et al., 2011a). Simulated results show that the RF heating uniformity could be improved by immersing the model fruit in water, suggesting that the non-uniform heating is mainly caused by the difference between DPs of food and its surrounding medium (Birla et al., 2004, Huang et al., 2016, Jiao et al., 2014). When the dielectric constant of surrounding material is in a comparable range with the sample, the best heating uniformity would be achieved (Tiwari et al., 2011a, Huang et al., 2015). The dielectric constant determines the electric field distribution when the loss factor is far smaller than the dielectric constant (Jiao et al., 2014, Jiao et al., 2014, Metaxas, 1996). Following this approach, Jiao, Shi, et al. (2015) have shown that the temperature uniformity in peanut butter has been improved by minimizing the difference of dielectric constant between food sample and surrounding material. The temperature uniformity is greatly improved by placing soybean samples in a polystyrene container, which has the closest dielectric constant to that of soybeans and a lower dielectric loss factor value, as discussed in a recent study (Huang et al., 2016). Based on the study conducted by Huang et al. (2016), the container material, thickness, and corner radius have a significant effect on heating uniformity of soybeans during RF processes. Hence, the best combination of parameters in adjusting the thickness and corner radius of the polystyrene container has been established for heating uniformity improvement. However, there is no available mathematical modeling in literature to identify the specific relationship of DPs between surrounding material and treated products for RF heating uniformity improvement. Therefore, it is desirable to conduct a numerical analysis to systematically study the RF heating characteristics and design treatment protocols to improve RF heating uniformity in low moisture foods.

The objectives of the current study were to: (1) develop a computer simulation model to predict the electric field intensity and temperature distribution in three different layers of soybean flour in a rectangular shaped container, (2) conduct experiments with soybean flour in a 6 kW, 27.12 MHz RF system to verify the simulation results, (3) apply the validated model to evaluate the heating uniformity of soybean flour influenced by DPs and density of the surrounding container and treated products, and (4) establish the DP and density correlations between surrounding container and treated food sample when the best heating uniformity was obtained.