Journal of Food Process Engineering最新文献

This study investigated the synergistic effects and mechanism of high-frequency ultrasound (HFUS) combined with sodium hypochlorite (NaClO) against Escherichia coli O157:H7 (E. coli). The bactericidal effect of HFUS alone against E. coli was limited (reduced 0.14–0.30 log CFU/mL), while that of NaClO (3 mg/L) was relatively better (reduced 1.10–2.02 log CFU/mL). When combining HFUS and NaClO, the decontamination of E. coli increased as decreasing ultrasonic frequency and increasing ultrasonic power at the range of 2.16–5.76 log CFU/mL, which achieved an additional maximum 3.58 log CFU/mL-reduction (581 kHz, 167 W, 18 min) comparing to the total reduction of sole NaClO and HFUS treatments. The remarkable cell membrane damages caused by HFUS during the combined treatment were confirmed by membranal integrity, membranal permeability, and ultrastructural morphology analyses. Incredibly, as one of membrane damages, pores observed on the cell membrane could provide new channels for hypochlorous acid and hydrogen peroxide induced by HFUS to enter E. coli cells. Furthermore, those chemical substances significantly increased the reactive oxygen species (ROS) levels at a lower ultrasonic frequency and higher power, which were part of the reason for subsequent DNA damage in addition to the mechanical effects of HFUS. These results may broaden the application of high-frequency ultrasound in food sterilization.

Practical applications

There is an increasing trend toward food sterilization that prefers non-thermal processing. E. coli is a typical pathogen associated with foodborne disease outbreaks and has one of the broadest disease spectra. Ultrasound is a promising non-thermal technology due to its gentle action, simple operation, and environmental friendliness. This study combined ultrasound with sodium hypochlorite against E. coli, which obtained a remarkable synergistic bactericidal effect, making potential applications in the future food industry.

This study designs, models, and compares microwave and ultrasound-assisted extraction (MAE and UAE) methods for bioactive compounds from bael leaves, highlighting their advantages over conventional techniques in optimizing extraction efficiency. MAE achieved 45.50 ± 0.44 mg GAE/g, 11.41 ± 0.13 μg TAE/g, 0.29 ± 0.02 mg QE/g, 1.30 ± 0.09 mg diosgenin/g, and 80.40% ± 0.89% DPPH scavenging activity at optimized conditions (550 W microwave power, 2 min treatment time, and 26.74 mL solvent:BLP). However, UAE yielded 77.13 ± 0.62 mg GAE/g, 30.19 ± 0.18 μg TAE/g, 0.78 ± 0.02 mg QE/g, 1.09 ± 0.13 mg diosgenin/g, and 83.37% ± 0.80% DPPH scavenging activity at optimized conditions (32% amplitude, 18.5 min treatment time, and 40.9 mL solvent: BLP). Statistical analysis validated RSM model's accuracy, with UAE and MAE models achieving R² > 0.95 and low error values. UAE demonstrated superior efficiency in extracting bioactive compounds, reducing antinutritional components, and enhancing antimicrobial activity. FTIR and SEM confirmed higher phenolic content and greater cell disruption. These methods boost extraction efficiency, supporting the development of nutraceuticals, and pharmaceuticals.

Practical Application

The introduction of innovative extraction methods such as microwave and ultrasound assistance has developed the isolation of bioactive compounds from bael leaves, with wide-ranging applications in pharmaceuticals, cosmetics, agriculture, food industries, and so forth. Significant findings reveal that optimized ultrasound and microwave extraction processes yield higher amounts of bioactive compounds and preserve thermolabile components, demonstrating strong potential for industry-scale production. These advanced techniques efficiently extract compounds with potent antioxidant, anti-inflammatory, antimicrobial, and anticancer properties, developing novel drugs, nutraceuticals, skincare products, natural pesticides, and growth enhancers. The resulting extracts, rich in bioactive components, offer significant health benefits and robust antimicrobial activity, making them valuable ingredients for cutting-edge products in healthcare and wellness. By leveraging the medicinal potential of bael leaves through modern extraction processes, researchers and industries can create functional foods, pharmaceuticals, and cosmetics that meet the demand for natural, effective, and sustainable solutions. These innovations represent a significant leap in product development, emphasizing the importance of nature-derived ingredients in addressing progressing consumer needs for health and well-being.

The traditional alkaline peeling method generates high-salinity wastewater, posing significant environmental risks. To avoid water waste and chemical use, a dry method using high-temperature thermal radiation was explored for removing walnut skins. The mechanism of the high-temperature thermal radiation dry method for removing walnut skins was revealed by studying the physical properties of walnut kernels. Research on the performance of the peeling device identified the optimal parameters: an infrared emitter surface temperature of 600°C, a radiation time of 20.7 seconds, and a distance of 129.46 mm between emitters, achieving a 95.18% skin removal rate with only 0.8% moisture loss and a quality score of 96.82. Raman spectroscopy showed that this method increased the unsaturated fatty acid content of walnut kernels by 27.26%, greatly enhancing their quality. SEM analysis revealed different microstructural changes between skins removed by infrared and alkaline methods, revealing the differences in their peeling mechanisms. These findings provide a scientific foundation for developing thermal radiation dry peeling technology and devices.

Practical applications

The removal of walnut skins is an essential process for enhancing the added value of products. However, current industrial peeling methods such as hot alkaline peeling and steam peeling are water and energy-intensive industries, generating large amounts of wastewater that negatively impact the environment. There is an urgent need to develop an efficient, green, and environmentally friendly dry peeling technology for walnut kernels in the food industry to replace traditional chemical peeling methods. The high-temperature thermal radiation dry peeling technology provides a new approach that avoids the use of water and chemical reagents while maintaining high product quality after peeling. Research focuses on the theoretical study and several key points of dry peeling technology for achieving walnut kernel peeling. The research results provide scientific basis for the replacement of traditional alkaline peeling with high-temperature thermal radiation dry peeling technology and offer theoretical support and reference for the development and optimization of related equipment.

Visualization and analysis of damage in honey peaches is important to reduce the occurrence of impact damage during postharvest handling. The finite element simulation method was used to visualize impact damage of honey peach. Firstly, the mechanical parameters such as maximum force, damage area, damage volume and absorbed energy during the collision between honey peaches and the surfaces of alloy steel, high density polyethylene (HDPE) and expandable polyethylene (EPE) were obtained by the collision device. Then, the elastic modulus and Poisson's ratio were obtained by compression tests of honey peach pulp. Finally, the process of collision between honey peaches and different material surfaces were simulated by finite element method. The results showed that the maximum error between the measured and simulated values of parameters were less than 25.1%. The study provides a reference for the selection of packaging materials for honey peaches and the biomechanical properties of various agricultural products.

Practical applications

Impact damage is one of the most common mechanical injuries in postharvest handling of honey peaches, and it is of great significance to quantitatively study the impact damage of honey peaches to reduce the occurrence of impact damage of honey peaches during packaging and transportation. The study shows the feasibility of using the finite element method for quantitative prediction and assessment of impact damage in honey peaches. In addition, the selection of suitable packaging materials can be used to effectively reduce the occurrence of impact damage of honey peaches in the transportation process. The results of the study can not only provide theoretical support for the packaging and transportation of honey peaches and other aspects, but also provide a reference for the biomechanical properties of various agricultural products.

In this study, a computational fluid dynamics and discrete element (CFD–DEM) coupling model for sorting fresh tea leaves by aspirated-air type was established, an experimental study of adsorption on bench was carried out, and computational fluid dynamics (fluent) was used to analyze the flow characteristics of two kinds of air-suction tea leaf models, The coupling model of CFD–DEM is established, the motion process of fresh tea leaves from being adsorbed by a porous turntable to moving and falling with the turntable was simulated, 3D printing technology was used to print the key parts of the air suction tea leaf sorting equipment, and the porous turntable adsorption test of air suction tea leaf sorting was carried out. The results show that the model with the falling guard device has no airflow at the hole of the porous turntable, and the gas field flow characteristics are stable, which can ensure the smooth falling of fresh tea leaves; The results of the bench test for the separation of fresh tea leaves by air suction are the same as those simulated by the established CFD–DEM coupling model, which indicates that the establishment of the CFD–DEM coupling model and the simulation parameters are reasonable, and the coupling model lays a foundation for the later optimization and design of the multi-scale air suction separation mechanism for tea particles.

Practical applications

This research is applied to the field of food engineering and sorting of fresh tea leaves. This research innovatively proposes the principle of air-suction sorting of fresh tea leaves. The air sucked in by negative pressure can carry out the next operation and save energy better. In this study, a CFD–DEM coupling model for air-suction separation of fresh tea leaves was established. The key components of air-suction separation equipment were printed using 3D printing technology, and the test results were the same as the simulation results.

Mangifera pajang Kosterm., or 'Bambangan,' a fruit known for its rich phytochemical content, was investigated for the effects of ultrasound-assisted osmotic dehydration (UAOD) on pretreated M. pajang fruit pulp (PMPF) and drying at different temperatures (40, 50, 60, 70, and 80°C). Thin-layer drying kinetics were analyzed using six models, with the Midilli and Kucuk model being the most suitable, showing optimal effective moisture diffusivity and activation energy. PMPF dried at 50°C, using natural deep eutectic solvents (NADES) as the extraction solvent, exhibited the highest extraction yield (64.13 ± 1.08%), mangiferin content (0.5818 ± 0.00164 mg/g), total phenolic content (146.2081 ± 1.33 mg GAE/g DW), total flavonoid content (2.4737 ± 0.06 mg RE/g DW), and DPPH inhibition activity (95.87 ± 0.16%), along with the best color retention compared to untreated M. pajang fruit pulp. This highlights its potential for nutraceutical and functional food applications, with UAOD as pretreatment effectively preserving food quality and color.

Practical Applications

This article provides new insights into the drying and pretreatment of Mangifera pajang fruits. Rich in phytochemicals, M. pajang offers numerous health benefits. Pretreatment methods such as ultrasound-assisted osmotic dehydration (UAOD) and oven drying at different temperatures significantly enhance the retention of bioactive compounds like phenolics and flavonoids, as well as antioxidant activity and color stability. The study identified optimal drying temperatures, conditions, drying rates, and activation energy to maximize these qualities. Using mathematical models for drying kinetics, this research offers practical guidance for the food processing industry. It provides an operational tool for manufacturers to optimize the drying process, reduce operational costs, and ensure the preservation of chemical qualities while extending the shelf life of M. pajang fruits. This work supports the development of high-quality nutraceutical and functional food ingredients, promoting their commercialisation and use in health-focused markets.

Catfish fillets are produced from whole catfish through a series of processing operations including de-heading, gutting, filleting, skinning, trimming, and freezing. Catfish processing facilities usually chill or freeze a certain number of catfish fillets as backup storage. Later, catfish fillets are pulled out of storage for further processing, where significant manual labor is needed to separate and flatten all the fillets for downstream processing, such as portioning, breading, and individually quick-frozen (IQF). Due to the labor force shortage and increasing labor cost, there is a pressing need to automate the singulation task, thereby reducing labor dependence. Machine vision technology has been researched for automated quality evaluation of fish products. However, research is lacking on using machine vision for automated singulation of fish fillets. This study presents a novel machine vision system consisting of a color camera for the recognition of the folding status and orientations of catfish fillets toward realizing automated fillet singulation. A set of 400 images of catfish fillets in four different orientations was captured and annotated for each catfish fillet. Two deep learning-based image segmentation models, that is, YOLOv8 and SegFormer-B5, were trained on the dataset for catfish fillet recognition. YOLOv8 outperformed SegFormer in catfish recognition and achieved overall masked mAP (mean average precision) scores of 97.1% and 97.4% for underwater and out-of-water catfish fillets, respectively. The vision system combined with YOLOv8 has the potential to automate the recognition and subsequent handling operations of catfish fillets.

Practical applications

The U.S. catfish industry is shrinking and facing great challenges because of international market competition and increasing production costs. The outbreak of COVID-19 revealed a sharp deficiency in the labor force for the entire catfish industry, which has relied on manual labor for various processing operations. Mandatory lockdowns severely disrupted seafood supply chains and labor access. The tightening labor market has resulted in the delay of not only catfish processing but also production and distribution. It is imperative to increase the level of automation for processing operations such as IQF preparation process. At present, each processing facility needs 6–10 laborers for the manual catfish fillet IQF preparation process, implying that automating the process would potentially save hundreds of thousands of dollars in annual labor costs per processing line. The automation technology developed in this article has the potential to benefit the U.S. catfish processor by minimizing labor dependence and costs.

With the development of machine vision and spectral detection technology, online sorting of fruit internal and external quality has been developed rapidly. However, for spherical fruits, it is difficult to obtain full surface images during sorting, so it is difficult to accurately calculate the size of the surface defects and the ratio of defects to the full surface. In this paper, a full surface line scanning image acquisition device for spherical fruit is proposed. Based on this device, the line scanning hyperspectral image of spherical fruit is collected, and the original image is extracted by feature extraction and background removal. Next, the isometric projection image and the equivalent projection image of the feature image is obtained through cartography projection transformation; The number of feature pixels in the original feature image, the isometric projection image, the equivalent projection image, and the width of the original feature image are used as input parameters to predict the actual defect area with the help of the shallow neural network. In this paper, the equipment and method are verified using three test balls with different diameters and pasting different sizes of identification blocks at different positions on their surfaces. The experimental results show that the prediction accuracy R of the test set of the model is 0.9937, and the RMSE is 0.3391 cm². It can be seen that the method has good prediction accuracy, which can provide a reference for the hyperspectral on-line sorting method of external quality of spherical fruit.

Practical application

This method provides an effective solution for the quality sorting production line of spherical fruits. In addition to agricultural product quality testing and food quality testing, similar to the detection of industrial products such as ball balls, the scheme provided in this manuscript can also be used as one of the options.

The method proposed in this manuscript is suitable for all kinds of line scanning equipment, including hyperspectral imager and laser profilometer.

Given the seasonal nature and high perishability of Eriobotrya japonica fruits, employing effective preservation techniques like drying is crucial to minimize economic losses and extend the fruit's availability throughout the year. This study rigorously examines the drying kinetics of Eriobotrya japonica fruits using an indirect forced convection solar dryer and highlights the technological advantages of utilizing this dryer over traditional open-air methods, showing that controlled conditions provide improved drying rates. The research develops the equation for the characteristic drying curve. The Midilli-Kucuk model was demonstrated to be the most appropriate for describing these kinetics under various conditions, offering a reliable method for predicting drying behavior at untested temperatures. The thermal diffusivity was determined and rises as the temperature increases. The application of the Arrhenius approach enabled the determination of an activation energy of 17.79 kJ/mol, confirming the substantial impact of temperature on the drying process.

Practical applications

The global challenge of food preservation, especially for perishable fruits like Eriobotrya japonica, requires innovative and efficient solutions to minimize economic losses and ensure the year-round availability of nutritious produce. Our research demonstrates the technological advantages of using a forced convection solar dryer over traditional methods for drying E. japonica. This system maintains a consistent air temperature, ensuring a stable energy supply, faster, and more uniform drying. A major contribution of this study is the development of the characteristic drying curve equation, which is crucial for optimizing drying parameters and designing an efficient solar dryer specifically for E. japonica. This research not only advances the understanding of the drying kinetics and thermal properties of E. japonica but also provides a foundation for the development of more efficient and sustainable drying technologies. By optimizing the drying process, this study contributes to improving the preservation and quality of loquat fruits, thereby supporting agricultural sustainability and reducing post-harvest losses. This work is highly relevant to the broader energy community, as it showcases the potential of solar drying technologies in enhancing food preservation while promoting the use of renewable energy sources.