Effects of Moisture, Temperature, and Salt Content on the Dielectric Properties of Pecan Kernels During Microwave and Radio Frequency Drying Processes

Radio Frequency Treatment of Food: A Review on Pasteurization and Disinfestation

Radio frequency (RF) is a novel technology with several food processing and preservation applications. It is based on the volumetric heating generated from the product's dielectric properties. The dielectric properties of each material are unique and a function of several factors (i.e., temperature, moisture content). This review presents a list of dielectric properties of several foods and describes the use of RF as an innovative technology for the food industry. This paper includes several examples of pasteurization, fungi inactivation, and disinfestation in selected food products. The aim of this review is to present the potential applications of RF in pasteurization and disinfestation and research needs that should be addressed. RF has been successfully applied in the inactivation of pathogens such as Salmonella spp., Listeria monocytogenes, and Escherichia coli in low- and high-moisture food. The disinfestation of crops is possible using RF because of selective heating. This process inactivates the insects first because of the different dielectric properties between the pests and the food. The products' final quality can be considerably better than conventional thermal processes. The processing time is reduced compared to traditional heating, and thermal damage to the food is minimized. The main drawback of the technology is the lack of uniform heating, mainly when the product is surrounded by a packaging material with different dielectric properties from the food.

Flavor characteristics of peeled walnut kernels under two-steps roasting processes

Currently, the effects of roasting methods on the flavor profile of peeled walnut kernels (PWKs) remain unknown. The effects of hot air binding (HAHA), radio frequency (HARF), and microwave irradiation (HAMW) on PWK were evaluated using olfactory, sensory, and textural techniques. Solvent Assisted Flavor Evaporation-Gas Chromatography-Olfactometry (SAFE-GC-O) identified 21 odor-active compounds with total concentrations of 229 μg/kg, 273 μg/kg and 499 μg/kg due to HAHA, HARF, and HAMW, respectively. HAMW exhibited the most prominent nutty taste, with the highest response among roasted milky sensors with the typical aroma of 2-ethyl-5-methylpyrazine. HARF had the highest values for chewiness (5.83 N·mm) and brittleness (0.68 mm); however, these attributes did not contribute to the flavor profile. The partial least squares regression (PLSR) model and VIP values showed 13 odor-active compounds were responsible for the sensory differences from different processes. The two-step treatment with HAMW improved the flavor quality of PWK.

Effect of relative humidity, storage days, and packaging on pecan kernel texture: Analyses and modeling

The studies expounding on the effects of storage conditions on texture changes are limited. The researchers have been proposing methods to measure pecan texture instrumentally. But current protocols and/or attributes fail to address huge variability during experimentation. Additionally, there are no predictive models to estimate changes in pecan texture during storage. This study addresses all the above concerns and investigates the effects of different relative humidity (RH, 30-90%) and packaging material (Polyethylene-Nylon [PEN], polypropylene [PP], low density polyethylene [LDPE], and metallic laminates [ML]) on pecan texture, introducing a rift ratio (F/H or fracturability to hardness ratio) to address variability in the data and predictive model to estimate changes in the textural attribute of pecans during storage. The textural analysis was conducted on pecan cores and intact pecans to measure the area under curve, fracturability, hardness, cohesiveness, chewiness, springiness, and rift ratio. It was observed that values for the rift ratio obtained using the intact pecan method had high R² (0.72) as compared to the rest of the textural attributes. A three-parameter logistic model was employed to predict pecan texture during storage. The pecans stored at 75, 80, and 90% reached the rift ratio (F/H) of 0.5 at approx. 115, 3, and 0.15 days (~ 4 hr), respectively. Similarly, pecans stored in LDPE, PP, and PEN packs at 80% reached rift ratio (F/H) of 0.5 at approx. 26, 57, and 78 days, respectively. The presence of any kind of package delayed fracturability loss by at least eight folds at 80% RH. The pecans stored in ML did not experience a significant change in textural attributes.

Identification of Fibre Content in Edible Flours Using Microwave Dielectric Cell: Concise Review and Experimental Insights

The quality of edible intake decides the health of the human body and is also responsible for building a healthy immune system in the body. A healthy immune system can protect the body even from invisible attacks of viral or bacterial infections. The assessment of the quality of edible items is not well defined and standardized in many developing countries due to quality assessment difficulties in practice. An alternative well-defined quality assessment approach for edible flours is presented in this paper. Every edible substance has dielectric properties, and it varies from material to material in nature. Edible flours and liquid have different microwave absorption capabilities, based on their natural molecular structure. Based on the microwave energy absorption characteristics of materials, the attenuation constant of edible flours is derived by the waveguide method in this work. In this approach, microwave energy absorption of the edible samples of different types of wheat, rice and millets are observed, and the attenuation constant factors of the samples are then calculated from the tabulated values. The work focuses on the identification of fibre content present in the edible flours. Inferences are made based on the attenuation and its variations with the number of samples, dielectric loss and dielectric constant of the samples. A systematic and concise review of the topic is also included for the benefit of future researchers.

Characteristics and Quality Analysis of Radio Frequency-Hot Air Combined Segmented Drying of Wolfberry (Lycium barbarum)

To overcome the problems of a long conventional drying time, low energy efficiency, and poor product quality, a segmented drying approach was developed for fresh wolfberry (Lycium barbarum) using a radio frequency (RF)-hot air drying process, which was investigated under different parameters of plate spacing (80, 90, 100 mm), vacuum degree (0.015, 0.025, 0.035 Mpa), and hot air temperature (50, 55, 60 °C). Analysis of the wolfberry’s drying characteristics, comprehensive quality, and microstructure indicated that: combined drying was faster and less time-consuming than natural drying or hot air drying, and components such as polysaccharides, ascorbic acid, and betaine in wolfberries were effectively retained. Based on the acceptable drying rate, stable temperature application, and avoidance of arcing effects, the optimal combined segmented drying parameters were determined to be as follows: a plate spacing of 90 mm, vacuum degree of 0.025 MPa, and air temperature of 55 °C. For the dried wolfberries under these conditions, the total drying time was 17 h and the berries had an improved comprehensive quality, the content of total soluble sugars was 0.62 g/g, total phenol was 10.01 mg/g, total flavonoids was 2.60 mg/g, V_C was 3.18 mg/100 g, betaine was 3.48%, oxidation resistance represented by an inhibition rate was 66.14%, color was better, and rehydration rate was 48.56%. The microstructure was more regular because of the special dielectric heating characteristics of RF vacuuming. Despite the differing drying characteristics of individual materials, the overall RF-hot air combined drying process was found to achieve high-quality dehydration of wolfberries.

Combined Effect of Temperature and Oil and Salt Contents on the Variation of Dielectric Properties of a Tomato-Based Homogenate

Tomato-based processed foods are a key component of modern diets, usually combined with salt and olive oil in different ratios. For the design of radiofrequency (RF) and microwave (MW) heating processes of tomato-based products, it is of importance to know how the content of both ingredients will affect their dielectric properties. Three concentrations of olive oil and salt were studied in a tomato homogenate in triplicate. The dielectric properties were measured from 10 to 3000 MHz and from 10 to 90 °C. Interaction effects were studied using a general linear model. At RF frequencies, the dielectric constant decreased with increasing temperature in samples without added salt, but this tendency was reversed in samples with added salt. The addition of salt and oil increased the frequency at which this reversion occurred. At MW frequencies, the dielectric constant decreased with increasing temperature, salt, and oil content. The loss factor increased with increasing salt content and temperature, except in samples without added salt at 2450 MHz. Penetration depth decreased with increasing frequency and loss factor. Salt and oil contents have a significant effect on the dielectric properties of tomato homogenates and must be considered for the design of dielectric heating processes.

Technologies for disinfection of food grains: Advances and way forward

Growing demand from the consumers for minimally processed and high-quality food products has raised the scientific quest for foods with improved natural flavours in conjunction with a restricted supplement of additives. In this context, achieving quality and safe food grains and the identification of suitable processing and disinfection technologies have also become the key issues. Microbial contamination is one of the major reasons responsible for the spoilage of food grains. Various sources of contamination such as air and water (both contaminated with dust and dirt), animals (insects, birds, rodents), environmental conditions (rainfall, drought, temperature), unhygienic handling, harvesting, processing equipment and improper storage conditions are responsible for the microbial spoilage of food grains. In order to maintain the food grains safe and un-contaminated, several food processing technologies have been explored and implemented, with the ultimate purpose of maintaining the safety, freshness and nutritional attributes of the food products. Among these technologies, microwave, radiofrequency, infrared, ohmic heating, novel drying methods along with non-thermal methods such as cold plasma, irradiation, ozonation and nanotechnology have attracted much attention because of considerable reduction in the overall processing time with minimum energy consumption. This review aims to discuss the advances involving the said technologies for controlling the microbial contamination of food grains in accordance with their inactivation. Current research status of the thermal and non-thermal emerging technologies for the preservation of food grains as well as perspectives for further research in this area are also elaborated in detail.

Use of Modern Regression Analysis in the Dielectric Properties of Foods

The dielectric properties of food materials is used to describe the interaction of foods with electromagnetic energy for food technology and engineering. To quantify the relationship between dielectric properties and influencing factors, regression analysis is used in our study. Many linear or polynomial regression equations are proposed. However, the basic assumption of the regression analysis is that data with a normal distribution and constant variance are not checked. This study uses sixteen datasets from the literature to derive the equations for dielectric properties. The dependent variables are the dielectric constant and the loss factor. The independent variables are the frequency, temperature, and moisture content. The dependent variables and frequency terms are transformed for regression analysis. The effect of other qualitative factors, such as treatment method and the position of subjects on dielectric properties, are determined using categorical testing. Then, the regression equations can be used to determine which influencing factors are important and which are not. The method can be used for other datasets of dielectric properties to classify influencing factors, including quantitative and qualitative variables.