Mitigation of mechanical damage and protein deterioration in giant river prawn (Macrobrachium rosenbergii) by multi-frequency ultrasound-assisted immersion freezing.

In order to investigate the effects of multi-frequency ultrasound-assisted immersion freezing (MUIF) on the meat quality of Macrobrachium rosenbergii, tail meat was subjected to different MUIF treatments respectively, namely 20 + 40 kHz (MUIF-20 + 40), 20 + 60 kHz (MUIF-20 + 60), 40 + 60 kHz (MUIF-40 + 60) and 20 + 40 + 60 kHz (MUIF-20 + 40 + 60), and the immersion freezing (IF) as control. Results showed that average diameter of ice crystals was 28 µm in IF, and that was only 8 µm in MUIF-20 + 40 + 60. When compared to IF, MUIF alleviated oxidative deterioration of lipids and proteins, but only at higher ultrasound frequency (MUIF-40 + 60; MUIF-20 + 40 + 60). Carbonyl content of MUIF-20 + 40 + 60 was only 40% of that in IF. Similarly, protein denaturation was inhibited in MUIF (except for MUIF-20 + 40). Transmission electron microscopy showed greater distortion of the ultrastructural components in IF, MUIF-40 + 60, and MUIF-20 + 40 + 60, suggested by bended Z-line. In conclusion, MUIF can be an effective strategy to mitigate mechanical damage and protein deterioration in the meat of Macrobrachium rosenbergii.

SleepFC: Feature Pyramid and Cross-Scale Context Learning for Sleep Staging.

Automated sleep staging is essential to assess sleep quality and treat sleep disorders, so the issue of electroencephalography (EEG)-based sleep staging has gained extensive research interests. However, the following difficulties exist in this issue: 1) how to effectively learn the intrinsic features of salient waves from single-channel EEG signals; 2) how to learn and capture the useful information of sleep stage transition rules; 3) how to address the class imbalance problem of sleep stages. To handle these problems in sleep staging, we propose a novel method named SleepFC. This method comprises convolutional feature pyramid network (CFPN), cross-scale temporal context learning (CSTCL), and class adaptive fine-tuning loss function (CAFTLF) based classification network. CFPN learns the multi-scale features from salient waves of EEG signals. CSTCL extracts the informative multi-scale transition rules between sleep stages. CAFTLF-based classification network handles the class imbalance problem. Extensive experiments on three public benchmark datasets demonstrate the superiority of SleepFC over the state-of-the-art approaches. Particularly, SleepFC has a significant performance advantage in recognizing the N1 sleep stage, which is challenging to distinguish.

Multi-source deep domain adaptation ensemble framework for cross-dataset motor imagery EEG transfer learning.

Objective. Electroencephalography (EEG) is an important kind of bioelectric signal for measuring physiological activities of the brain, and motor imagery (MI) EEG has significant clinical application prospects. Convolutional neural network has become a mainstream algorithm for MI EEG classification, however lack of subject-specific data considerably restricts its decoding accuracy and generalization performance. To address this challenge, a novel transfer learning (TL) framework using auxiliary dataset to improve the MI EEG classification performance of target subject is proposed in this paper.Approach. We developed a multi-source deep domain adaptation ensemble framework (MSDDAEF) for cross-dataset MI EEG decoding. The proposed MSDDAEF comprises three main components: model pre-training, deep domain adaptation, and multi-source ensemble. Moreover, for each component, different designs were examined to verify the robustness of MSDDAEF.Main results. Bidirectional validation experiments were performed on two large public MI EEG datasets (openBMI and GIST). The highest average classification accuracy of MSDDAEF reaches 74.28% when openBMI serves as target dataset and GIST serves as source dataset. While the highest average classification accuracy of MSDDAEF is 69.85% when GIST serves as target dataset and openBMI serves as source dataset. In addition, the classification performance of MSDDAEF surpasses several well-established studies and state-of-the-art algorithms.Significance. The results of this study show that cross-dataset TL is feasible for left/right-hand MI EEG decoding, and further indicate that MSDDAEF is a promising solution for addressing MI EEG cross-dataset variability.

Decoding Natural Grasping Behaviors: Insights Into MRCP Source Features and Coupling Dynamics.

The effective decoding of natural grasping behaviors is crucial for the natural control of neural prosthetics. This study aims to investigate the decoding performance of movement-related cortical potential (MRCP) source features between complex grasping actions and explore the temporal and frequency differences in inter-muscular and cortical-muscular coupling strength during movement. Based on the human grasping taxonomy and their frequency, five natural grasping motions-medium wrap, adducted thumb, adduction grip, tip pinch, and writing tripod-were chosen. We collected 64-channel electroencephalogram (EEG) and 5-channel surface electromyogram (sEMG) data from 17 healthy participants, and projected six EEG frequency bands into source space for further analysis. Results from multi-classification and binary classification demonstrated that MRCP source features could not only distinguish between power grasp and precision grasp, but also detect subtle action differences such as thumb adduction and abduction during the execution phase. Besides, we found that during natural reach-and-grasp movement, the coupling strength from cortical to muscle is lower than that from muscle to cortical, except in the hold phase of γ frequency band. Furthermore, a 12-Hz peak of inter-muscular coupling strength was found in movement execution, which might be related to movement planning and execution. We believe that this research will enhance our comprehension of the control and feedback mechanisms of human hand grasping and contributes to a natural and intuitive control for brain-computer interface.

Explainable cross-task adaptive transfer learning for motor imagery EEG classification.

Objective. In the field of motor imagery (MI) electroencephalography (EEG)-based brain-computer interfaces, deep transfer learning (TL) has proven to be an effective tool for solving the problem of limited availability in subject-specific data for the training of robust deep learning (DL) models. Although considerable progress has been made in the cross-subject/session and cross-device scenarios, the more challenging problem of cross-task deep TL remains largely unexplored.Approach. We propose a novel explainable cross-task adaptive TL method for MI EEG decoding. Firstly, similarity analysis and data alignment are performed for EEG data of motor execution (ME) and MI tasks. Afterwards, the MI EEG decoding model is obtained via pre-training with extensive ME EEG data and fine-tuning with partial MI EEG data. Finally, expected gradient-based post-hoc explainability analysis is conducted for the visualization of important temporal-spatial features.Main results. Extensive experiments are conducted on one large ME EEG High-Gamma dataset and two large MI EEG datasets (openBMI and GIST). The best average classification accuracy of our method reaches 80.00% and 72.73% for OpenBMI and GIST respectively, which outperforms several state-of-the-art algorithms. In addition, the results of the explainability analysis further validate the correlation between ME and MI EEG data and the effectiveness of ME/MI cross-task adaptation.Significance. This paper confirms that the decoding of MI EEG can be well facilitated by pre-existing ME EEG data, which largely relaxes the constraint of training samples for MI EEG decoding and is important in a practical sense.

A comprehensive review of ultrasonic assisted extraction (UAE) for bioactive components: Principles, advantages, equipment, and combined technologies.

The increasing focus on health and well-being has sparked a rising interest in bioactive components in the food, pharmaceutical, and nutraceutical industries. These components are gaining popularity due to their potential benefits for overall health. The growing interest has resulted in a continuous rise in demand for bioactive components, leading to the exploration of both edible and non-edible sources to obtain these valuable substances. Traditional extraction methods like solvent extraction, distillation, and pressing have certain drawbacks, including lower extraction efficiency, reduced yield, and the use of significant amounts of solvents or resources. Furthermore, certain extraction methods necessitate high temperatures, which can adversely affect certain bioactive components. Consequently, researchers are exploring non-thermal technologies to develop environmentally friendly and efficient extraction methods. Ultrasonic-assisted extraction (UAE) is recognized as an environmentally friendly and highly efficient extraction technology. The UAE has the potential to minimize or eliminate the need for organic solvents, thereby reducing its impact on the environment. Additionally, UAE has been found to significantly enhance the production of target bioactive components, making it an attractive method in the industry. The emergence of ultrasonic assisted extraction equipment (UAEE) has presented novel opportunities for research in chemistry, biology, pharmaceuticals, food, and other related fields. However, there is still a need for further investigation into the main components and working modes of UAEE, as current understanding in this area remains limited. Therefore, additional research and exploration are necessary to enhance our knowledge and optimize the application of UAEE. The core aim of this review is to gain a comprehensive understanding of the principles, benefits and impact on bioactive components of UAE, explore the different types of equipment used in this technique, examine the various working modes and control parameters employed in UAE, and provide a detailed overview of the blending of UAE with other emerging extraction technologies. In conclusion, the future development of UAEE is envisioned to focus on achieving increased efficiency, reduced costs, enhanced safety, and improved reliability. These key areas of advancement aim to optimize the performance and practicality of UAEE, making it a more efficient, cost-effective, and reliable extraction technology.

A Novel Soft Glove Utilizing Honeycomb Pneumatic Actuators (HPAs) for Assisting Activities of Daily Living.

Fabric-based pneumatic actuators (FPAs) are extensively employed in the design of lightweight and compliant soft wearable assistive gloves. However, conventional FPAs typically exhibit limited output force, thereby restricting the applications of such gloves. This paper presents the development of a novel honeycomb pneumatic actuator (HPA) constructed using flexible thermoplastic polyurethane (TPU) coating through hot pressing or ultrasonic welding techniques. Compared to the previously utilized double-layer fabric-based pneumatic actuators (DLFPAs), the HPAs yields a remarkable 862% increase in end output force. It can produce a tip force of 13.57 N at a pressure of 150 kPa. The integration of HPAs onto a soft pneumatic glove enables the facilitation of various activities of daily living. A series of trials involving nine patients were conducted to assess the effectiveness of the soft glove. The experimental results indicate that when assisted by the glove, the patients' finger metacarpophalangeal (MCP) and proximal interphalangeal (PIP) joints achieved angles of 87.67 ± 19.27° and 64.2 ± 30.66°, respectively. Additionally, the average fingertip force reached 10.16 ± 4.24 N, the average grip force reached 26.04 ± 15.08 N, and the completion rate of daily functions for the patients increased from 39% to 76%. These outcomes demonstrate that the soft glove effectively aids in finger movements and significantly enhances the patients' daily functioning.

Continuous shared control of a mobile robot with brain-computer interface and autonomous navigation for daily assistance.

Although the electroencephalography (EEG) based brain-computer interface (BCI) has been successfully developed for rehabilitation and assistance, it is still challenging to achieve continuous control of a brain-actuated mobile robot system. In this study, we propose a continuous shared control strategy combining continuous BCI and autonomous navigation for a mobile robot system. The weight of shared control is designed to dynamically adjust the fusion of continuous BCI control and autonomous navigation. During this process, the system uses the visual-based simultaneous localization and mapping (SLAM) method to construct environmental maps. After obtaining the global optimal path, the system utilizes the brain-based shared control dynamic window approach (BSC-DWA) to evaluate safe and reachable trajectories while considering shared control velocity. Eight subjects participated in two-stage training, and six of these eight subjects participated in online shared control experiments. The training results demonstrated that naïve subjects could achieve continuous control performance with an average percent valid correct rate of approximately 97 % and an average total correct rate of over 80 %. The results of online shared control experiments showed that all of the subjects could complete navigation tasks in an unknown corridor with continuous shared control. Therefore, our experiments verified the feasibility and effectiveness of the proposed system combining continuous BCI, shared control, autonomous navigation, and visual SLAM. The proposed continuous shared control framework shows great promise in BCI-driven tasks, especially navigation tasks for brain-driven assistive mobile robots and wheelchairs in daily applications.

Recognizing emotions induced by wearable haptic vibration using noninvasive electroencephalogram.

The integration of haptic technology into affective computing has led to a new field known as affective haptics. Nonetheless, the mechanism underlying the interaction between haptics and emotions remains unclear. In this paper, we proposed a novel haptic pattern with adaptive vibration intensity and rhythm according to the volume, and applied it into the emotional experiment paradigm. To verify its superiority, the proposed haptic pattern was compared with an existing haptic pattern by combining them with conventional visual-auditory stimuli to induce emotions (joy, sadness, fear, and neutral), and the subjects' EEG signals were collected simultaneously. The features of power spectral density (PSD), differential entropy (DE), differential asymmetry (DASM), and differential caudality (DCAU) were extracted, and the support vector machine (SVM) was utilized to recognize four target emotions. The results demonstrated that haptic stimuli enhanced the activity of the lateral temporal and prefrontal areas of the emotion-related brain regions. Moreover, the classification accuracy of the existing constant haptic pattern and the proposed adaptive haptic pattern increased by 7.71 and 8.60%, respectively. These findings indicate that flexible and varied haptic patterns can enhance immersion and fully stimulate target emotions, which are of great importance for wearable haptic interfaces and emotion communication through haptics.

Starches modification with rose polyphenols under multi-frequency power ultrasonic fields: Effect on physicochemical properties and digestion behavior.

As the main source of energy for human beings, starch is widely present in people's daily diet. However, due to its high content of rapidly digestive starch, it can cause a rapid increase in blood glucose after consumption, which is harmful to the human body. In the current study, the complexes made from edible rose polyphenols (ERPs) and three starches (corn, potato and pea) with different typical crystalline were prepared separately by multi-frequency power ultrasound (MFPU). The MFPU includes single-frequency modes of 40, 60 kHz and dual-frequency of 40 and 60 kHz in sequential and simultaneous mode. The results of the amount of complexes showed that ultrasound could promote the formation of polyphenol-starch complexes for all the three starches and the amount of ERPs in complexes depended on the ultrasonic parameters including treatment power, time and frequency. Infrared spectroscopy and X-ray diffraction indicated that ERPs with or without ultrasound could interact with the three starches through non-covalent bonds to form non-V-type complexes. Scanning electron microscopy showed that the shape of starches changed obviously from round/oval to angular and the surface of the starches were no longer smooth and appeared obvious pits, indicating that the ultrasonic field destroyed the structure of starches. In addition, compared to the control group, the in vitro digestibility study with 40/60 kHz sonication revealed that ultrasonic treatment greatly improved the digestive properties of the polyphenol-starch complexes by significantly increasing the content of resistant starch (20.31%, 17.27% and 14.98%) in the three starches. Furthermore, the viscosity properties of the three starches were all decreased after ERPs addition and the effect was enhanced by ultrasound both for single- and dual-frequency. In conclusion, ultrasound can be used as an effective method for preparing ERPs-starch complexes to develop high value-added products and low glycemic index (GI) foods.

Individual and synergistic effect of multi-frequency ultrasound and electro-infrared pretreatments on polyphenol accumulation and drying characteristics of edible roses.

The freeze-dried (FD) edible roses with high content of bioactive substances and superior flavor have been favored by consumers. Nevertheless, the development of freeze-dried rose industry has been plagued by a long drying time and low efficiency. This study investigated the effects of ultrasonic pretreatment (UP) in multi-frequency modes and electro-infrared pretreatment (EIP) prior to FD on polyphenol accumulation and drying characteristics of roses. The mechanism was explored by the changes in microstructure, equivalent circuit parameters, and phenol identifications of rose. The results showed that the FD time of roses decreased by 26 % after ultrasonic-infrared sequential synergistic pretreatment (UP + EIP) due to the damage of cell membrane permeability from UP. The quality attributes of UP + EIP products including color, phenols, and antioxidant activity (DPPH and ABTS radical scavenging rates) remarkably improved. UP + EIP significantly (p < 0.05) increased the content of polyphenols, namely quercetin-3ß-d-glucoside, phlorizin, procyanidin B2, gallicacid, and rutin in the FD roses quantified by ultra-high performance liquid chromatography-quadrupole time of flight mass spectrometry (UPLC-qTOF-MS/MS). Therefore, UP + EIP is an effective pretreatment method for shortening FD time and producing high-quality FD rose products with enhanced polyphenol content.

Vitamin D Fortification and Its Effect on Athletes' Physical Improvement: A Mini Review.

Poor vitamin D status is a widespread problem regardless of age and sex, emphasizing the necessity of new food sources to improve vitamin D levels. Currently, approximately 60% of dietary vitamin D consumption occurs via fortified foods. Vitamin D insufficiency (50-90%) is widespread according to age and region, despite different levels of sunlight exposure. The food industry must identify more effective strategies to increase normal dietary vitamin D intake and improve overall health. Strategies for vitamin D fortification include bioaddition, wherein a vitamin D-rich food source is added to staple foods during processes. These bioadditive strategies expand the range of vitamin D-containing foods and appeal to different preferences, cultures, and economic statuses. In several countries, vitamin D deficiency places athletes at a high risk of disease susceptibility. Due to low sun exposure, athletes in countries with higher and lower levels of sunlight have similar risks of vitamin D deficiency. In this review, we summarize recent technical advances to promote vitamin D utilization by humans during sports activities and in relation to the normal practices of athletes.

Natural grasping movement recognition and force estimation using electromyography.

Electromyography (EMG) generated by human hand movements is usually used to decode different action types with high accuracy. However, the classifications of the gestures rarely consider the impact of force, and the estimation of the grasp force when performing natural grasping movements is so far overlooked. Decoding natural grasping movements and estimating the force generated by the associated movements can help patients to improve the accuracy of prosthesis control. This study mainly focused on two aspects: the classification of four natural grasping movements and the force estimation of these actions. For this purpose, we designed an experimental platform where subjects could perform four common natural grasping movements in daily life, including pinch, palmar, twist, and plug grasp, to complete target profiles. On the one hand, the results showed that, for natural grasping movements with different levels of force (three levels at 20, 50, and 80%), the average accuracy could reach from 91.43 to 97.33% under five classification schemes. On the other hand, the feasibility of force estimation for natural grasping movements was demonstrated. Furthermore, in the process of force estimation, we confirmed that the regression performance about plug grasp was the best, and the average R 2 could reach 0.9082. Besides, we found that the regression results were affected by the speed of force application. These findings contribute to the natural control of myoelectric prosthesis and the EMG-based rehabilitation training system, improving the user's experience and acceptance.

Effect of Multi-Mode Thermosonication on the Microbial Inhibition and Quality Retention of Strawberry Clear Juice during Storage at Varied Temperatures.

Strawberry juice, which is rich in nutrients and charming flavor, is favored by consumers. To explore whether multi-mode thermosonication (MTS) can ensure the quality stability of strawberry clear juice (SCJ) during storage, the effects of microbial inhibition, enzyme activity, and physicochemical properties of SCJ pretreated by MTS were evaluated during storage at 4, 25, and 37 °C in comparison with thermal pretreatment (TP) at 90 °C for 1 min. The MTS, including dual-frequency energy-gathered ultrasound pretreatment (DEUP) and flat sweep-frequency dispersive ultrasound pretreatment (FSDUP), were conducted at 60 °C for 5 and 15 min, respectively. Results showed that the total phenols, flavonoids, anthocyanins, ascorbic acid, and DPPH free radical scavenging ability of SCJ decreased during the storage period. The control sample of SCJ was able to sage for only 7 days at 4 °C based on the microbiological quality, while the FSDUP and DEUP group extended the storage period up to 21 and 14 days, respectively. The polyphenol oxidase in SCJ pretreated by MTS did not reactivate during the storage period. The MTS remarkably (p < 0.05) reduced the color deterioration, browning degree, and nutrient degradation during the storage period. Moreover, the FSDUP group exhibited the maximum shelf life with a minimum loss of quality, demonstrating that it was the most suitable processing method for obtaining high-quality SCJ. It can be concluded that the MTS has the potential to inhibit enzymatic browning, inactivating microorganisms, preserve original quality attributes, and prolong the shelf life of SCJ.

The Effects of Bilateral Phase-Dependent Closed-Loop Vibration Stimulation With Motor Imagery Paradigm.

Vibration stimulation has been shown to have the potential to improve the activation pattern of unilateral motor imagery (MI) and to promote motor recovery. However, in the widely used left and right hand MI brain-computer interface (BCI) paradigm, the vibration stimuli cannot be directly applied to the imaginary side due to the spontaneity of imagery. In this study, we proposed a method of phase-dependent closed-loop vibration stimulation to be applied on both hands, and explored the effects of different vibration stimuli on the left and right hand MI-BCI. Eighteen healthy subjects were recruited and asked to perform, in sequence, MI tasks under three different conditions of vibratory feedback, which were no vibration stimulus (MI), phase-dependent closed-loop vibration stimulus (PDS), and continuous vibration stimulus (CS). Then the performance of the left and right hand MI-BCI and the patterns of brain oscillation were compared and analyzed under these different stimulation conditions. The results showed that vibration stimulation effectively boosted the activation of the sensorimotor cortex and enhanced the functional connectivity among sensorimotor-related brain regions during MI. The closed-loop stimulation evoked stronger event-related desynchronization patterns on the contralateral side of the imagined hand compared to continuous stimulation. There was a more obvious distinction between left hand task and right hand task. In addition, phase-dependent closed-loop vibration stimulation increased classification accuracy by approximately 7% (paired t-test, p=0.004, n=18) compared to MI alone, while continuous vibration stimulation only increased it by 4% (paired t-test, p=0.067, n=18). This result further demonstrated the effectiveness of the phase-dependent closed-loop vibration stimulation method in improving the overall performance of the MI paradigm and is expected to be further applied in areas such as stroke rehabilitation in the future.

Multi-frequency power ultrasound as a novel approach improves intermediate-wave infrared drying process and quality attributes of pineapple slices.

This study evaluated the effect of mono-frequency ultrasound (MFU, 20 kHz), dual-frequency ultrasound (DFU, 20/40 kHz), and tri-frequency ultrasound (TFU, 20/40/60 kHz) on mass transfer, drying kinetics, and quality properties of infrared-dried pineapple slices. Pretreatments were conducted in distilled water (US), 35 °Brix sucrose solution (US-OD), and 75% (v/v) ethanol solution (US-ET). Results indicated that ultrasound pretreatments modified the microstructure of slices and shortened drying times. Compared to the control group, ultrasound application reduced drying time by 19.01-28.8% for US, 15.33-24.41% for US-OD, and 38.88-42.76% for US-ET. Tri-frequency ultrasound provoked the largest reductions, which exhibited time reductions of 6.36-11.20% and better product quality compared to MFU. Pretreatments increased color changes and loss of bioactive compounds compared to the control but improved the flavor profile and enzyme inactivation. Among pretreated sample groups, US-OD slices had lower browning and rehydration abilities, higher hardness values, and better retention of nutrients and bioactive compounds. Therefore, the combination of TFU and osmotic dehydration could simultaneously improve ultrasound efficacy, reduce drying time, and produce quality products.

Selection of drying techniques for Pingyin rose on the basis of physicochemical properties and volatile compounds retention.

Awareness of edible rose being beneficial for health has attracted researchers in exploring different rose products. The study aimed to investigate effects of vacuum freeze drying (VFD), hot air drying (HAD), heat pump drying (HPD), relative humidity drying (RHD) and catalytic infrared drying (CID) on the physicochemical properties, and volatile organic compounds (VOCs) of Pingyin roses. Results showed that the VFD roses had significantly (p < 0.05) bright color, complete tissue cells, low shrinkage, and good plasma membrane permeability. CID roses showed the highest total phenols content (164.09 ± 0.88 mg/g) and the strongest antioxidant activity. Besides, the odor is the most crucial indicator for dried roses. VFD can well prevent the odor from diminishing/destroying and preserve the natural smell of rose. Thermal drying including HAD, HPD, RHD, and CID, could cause significant losses of VOCs. Consequently, the findings can provide the scientific basis for future large-scale production of dried rose products.

Recent development in high quality drying of fruits and vegetables assisted by ultrasound: A review.

The preservation of agri-products with a high moisture content like fruits and vegetables is challenging. Traditional dehydration techniques (sun drying and hot air drying) were used to limit food degradations and extend shelf life. However, few issues have been raised regarding the long processing time during the dehydration process causing the pronounced oxidation of nutrients and significant energy losses. Recent studies emphasize different process intensification methods, such as ultrasound (US), to rapidly and economically obtain quality dehydrated food to tackle quality deteriorating issues. The current work provides a comprehensive state-of-art of the drying of fruits and vegetables using ultrasound as an improvement technique for quality retention. The review will first provide a global knowledge of ultrasound in the drying field with a special focus on the equipment as well as mechanisms involved when US is used as a pretreatment or simultaneously during various drying processes. Discussion on the efficiency of each ultrasonic device and its potential use in industry is also provided along the way. The second part will cover a critical report and analysis of recent studies highlighting the effects of the two ultrasound application modes in the drying field (pretreatment and combined with the drying process) on the quality of fruits and vegetables. Overall, applying ultrasound to assist the dehydration of fruits and vegetables is a promising way to reduce drying time and obtain nutritious dehydrated products. This non-thermal technology alleviates the oxidation of nutrients, thus offering a favorable perspective to increase the marketability of finished products as public awareness of food quality is surging.

The temperature induced disruption process of amylopectin under ultrasonic treatments.

In this study, amylopectin was ultrasonicated at different temperatures to explore its disruption process. Results showed a significant decrease in amylopectin Mw after ultrasonic treatments and a retarded effect was detected with the increase of temperatures. The amylopectin disruption process fitted to the second order kinetic model (1/Mwt - 1/Mw0 = kt) and its disruption rate coefficient decreased from 2.203 × 10-8 to 0.986 × 10-8 mol/g min as the temperatures increased from 20 to 80 °C. This was ascribed to the higher vapour pressure and the lower viscosity of the solution at higher temperatures. Ultrasound induced break points preferentially occurred to B3 chains of amylopectin at higher temperatures which contributed to an increase of A chains, which because that amylopectin would be more extended at higher temperatures. The activation energy of amylopectin disruption was negative (-11.6 KJ/mol), which indicated that its scission process by ultrasound was essentially a mechanical action.

Effects of flat sweep frequency and pulsed ultrasound on the activity, conformation and microstructure of mushroom polyphenol oxidase.

The effects of thermal processing (TP) and flat sweep frequency and pulsed ultrasound (FSFPU) treatment with different frequency modes on the activity, conformation and physicochemical properties of mushroom polyphenol oxidase (PPO) were investigated. The results showed that the relative enzymatic activity of PPO gradually decreased with increasing temperature and duration, and thermosonication decreased the PPO activity to a greater extent compared with thermal processing. FSFPU treatment with dual-frequency of 22/40 kHz mode showed the most significant effect. Circular dichroism (CD) showed that the content of α-helix and ß-turn dropped, while that of ß-sheet and random coil raised after FSFPU treatment. The intensity of endogenous fluorescence decreased, indicating that PPO protein unfolded and the tertiary structure was destroyed. The amount of free sulfhydryl, protein aggregation index, and turbidity all rose. Moreover, FSFPU treatment led to the aggregation of protein from the analysis of atomic force microscope (AFM). Conclusively, FSFPU can be used as an effective method to inhibit the activity of endogenous enzymes in food.