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This study investigated the impact of isochoric freezing-thawing (ISF-T) cycles (C0–C5) on the quality of chicken breast. The results indicated a significant increase (P < 0.05) in pH from 5.41 to 5.96 after C1 to C4 before slightly decreasing to 5.72 (C5). Lightness (L*) varied between 50.13 and 44.55 across C1 to C4, with redness notably decreasing from −1.15 after C0 to −2.09 after C5 while yellowness (b) sharply increased from 2.65 (C0) to 4.65 (C5). Moisture content decreased from 74.01% to 68.13% after C5. WHC slightly reduced from 89.25% after C0 to 85.66% after C4, with an 83.78% reduction after C5. Cooking loss increased linearly across the ISF-T cycles from 18.08% reaching 24.14% after C5. Conversely, shear force decreased to 21.83 N after C5 from 25.21 N after C1. Protein solubility slowly increased to 88.79% after C3, then decreased to 72.84 after C5. The myofibrillar index remained stable until C3, then increased from 35.51 after C5. Lipid oxidation slowly increased to 0.27 mg MDA/kg after C3, then sharply increased to 0.44 mg MDA/kg after C5. In addition, Ca2+-ATPase activity showed that the samples obtained after C1 to C3 fluctuated between 23.59% and 24.71%, followed by a substantial reduction to 12.35% after C5. Furthermore, validation of the results by magnetic resonance imaging and nuclear magnetic resonance analysis confirmed the findings, suggesting that isochoric freezing could offer a viable solution to control temperature fluctuations, a challenging problem during meat storage and distribution in the cold chain food industry. [ABSTRACT FROM AUTHOR]

Background Advanced food processing technologies such as microwave heating have experienced increased popularity, as alternatives to conventional processing methods for diverse applications in the food industry. A new dimension, is the concept of microwave-assisted food processing techniques, which utilize the advantages of microwave energy to overcome the shortcomings of conventional and some emerging food processing methods. Scope and approach This paper reviews some microwave-assisted (MA) food processing technologies, such as MA-ultrasonication, MA-ohmic heating, MA-electron irradiation, MA-freezing, MA-osmotic dehydration, MA-infrared heating, and microwave-vacuum processing (MA-VC). In particular, their effects in terms of enhancing product quality and process efficiency, including principles and mechanisms are discussed. Promising food applications includes drying, extraction, baking, roasting, pasteurization/sterilization, tempering. Future strategies to further widen their applications are highlighted and salient drawbacks are also taken into consideration. Key findings and conclusions In general, the resultant benefits of microwave assistance to conventional or emerging food processing technologies include high thermal efficiency, shorter processing time, reduced operational cost and improved product quality. It is hoped that this paper will increase positive ratings for microwave assisted food processing technologies and promote their adoption by the food industry. However, it is important that appropriate simulation models for process optimization be developed alongside. [ABSTRACT FROM AUTHOR]

Background Proteins are essential nutrients required in various body functions and normal human life. However, in the food industry, the application of proteins especially those of plant origin have been limited due to their poor functionality. Although nowadays, diverse modification techniques are usually employed to improve their performance in food products, it is also important that effective methods for monitoring the resultant conformational changes induced during protein modification are developed. Scope and approach In this review, the relationship between protein conformation and functionality is briefly discussed. Thereafter, the underlying principles behind five selected spectroscopic techniques i.e. Fourier transform infrared, Raman, circular dichroism, fluorescence, and ultraviolet spectroscopies are introduced and their recent applications for monitoring conformational changes that occur during physical, chemical or enzymatic modification of proteins are addressed. In addition, the advantages and limitations of each spectroscopic technique are comparatively discussed and perspectives on the current situation alongside future trends are highlighted. Key findings and conclusions Spectroscopic techniques present an attractive panacea for evaluation of conformational changes during protein modification. Although certain challenges especially with complex food materials require urgent attention thus, more robust spectroscopic solutions should be exploited in the future. [ABSTRACT FROM AUTHOR]

Background Microwave-assisted extraction (MAE) have gained enormous popularity as a preferred method for the recovery of various active compounds from food materials. They proffer benefits such as the reduction of extraction time, environmental friendliness, low cost and enable automation or on-line coupling to other analytical procedures. Recently, newer add-ons or technological modifications have been incorporated into MAE systems, in an effort to continuously improve extraction efficiency and ensure a greener implementation. Scope and approach The core pathways of such meliorations include integrating microwave extraction with other technologies, e.g., ultrasound assisted extraction (UAE), negative pressure cavitation (NPC), enzyme assisted extraction (EAE), hydrodiffusion extraction (HDE), and supercritical fluid extraction (SFE) or replacement of extraction medium with suitable alternatives including ionic liquids, deep eutectic solvents, non-ionic surfactants, etc. This review confers their underlying principles and mechanisms, equipment and apparatuses, practicalities, as well as resultant benefits such as increased yield, intensification of mass transfer and reduction of energy consumption, in a manner not achievable by MAE alone or previous intermediary modifications. Key findings and conclusions It is hoped that this paper reinforces the need to initiate more studies focused on process validation and optimization of such emerging MAE systems, in furtherance of their scale-up, sustainability and robust adoption by the food industry. [ABSTRACT FROM AUTHOR]

Background Food quality and safety is of great concern to governments, the food industry, as well as consumers. Thus, research has been conducted to develop advanced detection techniques instead of traditional methods to provide rapid, non-destructive food quality and safety evaluation and analysis for the industry. Scope and approach As an emerging technology, Raman imaging has been successfully studied in food safety assessment and control. This review provides a comprehensive overview on the applications of Raman imaging in the area of food quality evaluation, assessment of adulterants and contaminants, and detection of pesticides. Other relevant techniques are also reported due to their close relationship with food safety control. Conclusions and key findings With these applications, it is evident that Raman imaging has given promising results and thus could be a powerful technique for food quality surveillance as well as for reducing the occurrence of food safety issues. [ABSTRACT FROM AUTHOR]

Background Microbial evaluation plays a very important role in food quality evaluation. By providing spectral information relevant to microbial attributes, spectroscopy technology has been introduced and applied for microbial quality evaluation of food products in a rapid and non-destructive way. By mining different range spectral data with appropriate chemometrics, some important microbial quality indicators could be potentially evaluated and quantified. Scope and approach In this review, recent progresses and applications of visible/infrared (Vis/IR), Raman and Fluorescence spectroscopy as efficient and promising tools in replacing traditional time-consuming, tedious, and destructive technologies for detecting spoilage microorganisms in various raw and processed food products are described. The challenges and future researches of these spectroscopy techniques are also suggested. Key findings and conclusions Although spectroscopy technology shows its prosing and potential in evaluating various microbial parameters, some challenges in terms of spectra pre-processing, model calibration and instrument development are still needed to be faced. Much more works are still required to improve the stability and suitability of spectroscopy before implementation in food industry. [ABSTRACT FROM AUTHOR]

Hyperspectral imaging (HSI) technology fusing spectroscopic technology and imaging technology has been proposed to achieve rapid and non-destructive inspection of food quality. In order to make full use of the hyperspectral data containing rich information, it is needed to develop effective and efficient data analysis methods to mine new information from hyperspectral data. The feature construction (FC) method, as a method of extracting information to construct new features, is applied to construct more representative and informative features from hyperspectral data for the detection of food quality. The review focuses on the construction methods of different dimensional features including zero-dimensional (0-D) features, one-dimensional (1-D) features, two-dimensional (2-D) features and three-dimensional (3-D) features in detail and presents their principles and implementation steps. In the review, applications of the HSI technology combined with different dimensional FC methods for the quality inspection of food are also discussed, and challenges and future work of the HSI technology combined with FC methods are presented. The current review is expected to provide some guidance to researchers on different dimensional FC methods, which should further encourage more applications of the HSI technology in food quality inspection. Despite the challenges in combining FC methods with hyperspectral technology, the encapsulation of FC methods in miniaturised hyperspectral instruments is an inevitable trend for future development. • Principles and implementation of different dimensional FC methods are discussed. • HSI technology combined with FC methods in food quality inspection is presented. • Challenges and future work of HSI technology combined with FC methods are offered. [ABSTRACT FROM AUTHOR]

Quality determination of frozen food is a time-consuming and laborious work as it normally takes a long time to thaw the frozen samples before measurements can be carried out. In this research, a rapid and non-destructive determination technique for frozen pork quality was tested with a hyperspectral imaging (HSI) system. In this study, 120 pieces of pork meat were frozen by four kinds of methods with various freezing temperatures from −20 to −120 °C. The hyperspectral images of the samples were acquired at the frozen state. Quality indicators including drip loss, pH value, color, cooking loss and Warner–Bratzler shear force (WBSF) of the samples were measured after thawing. The spectral characteristics of the frozen meat samples were studied and it was revealed that the reflectance at 1100 nm had a close relationship with the freezing temperature ( R =−0.832, p <0.01). Partial least squares regression (PLSR) was applied to establish the spectral models, and the models were then optimized. Results showed that the improved region of interest (ROI) method could be used to extract effective spectral information to withstand the interference of freezing, and choosing appropriate spectral bands and spectral pretreatment techniques were crucial to develop robust mathematical model. The performances of the models established were diverse based on different quality indicators. The coefficients of determination for prediction ( R p 2 ) for L *, cooking loss, b *, drip loss and a * were 0.907, 0.845, 0.814, 0.762, and 0.716, respectively. However there were low correlations ( R p 2 ) for pH and WBSF measurements. The current study indicated that HSI had the potential for non-destructive determination of frozen meat quality without thawing. [ABSTRACT FROM AUTHOR]

There are a large number of ham products produced and consumed throughout the world. The quality of ham is usually evaluated by human quality inspector based on grading standards. To maintain ham quality, processors need to carry out some destructive analysis of samples, which is usually laborious, time consuming and possesses the variability associated with human perception. Therefore, there is a need for the development of objective quality measurement or evaluation systems. Processors expect in-situ non-destructive measurements that can provide objective parameters with the incorporation of all the quality attributes and correlate them with the most demanding quality standards and consumer preferences. Hyperspectral imaging (HSI) is a promising technology that integrates conventional imaging and spectroscopy to attain both spatial and spectral information from the sample. Although the hyperspectral imaging approach has not been widely used for the quality evaluation of hams, it possesses a great potential in attaining information about different physico-chemical properties of ham. With the application of this technology, quality of ham could be ensured in a non-destructive manner and with confidence. The aim of this review is to discuss about the opportunities relating to hyperspectral imaging techniques in the quality evaluation and control of ham. [ABSTRACT FROM AUTHOR]

Abstract: Developing a rapid and non-destructive method for food safety and quality monitoring has become a crucial request from the meat industry. Hyperspectral imaging technique provides extraordinary advantages over the traditional imaging and spectroscopy techniques in food quality evaluation due to the spatial and spectral information that it can offer. In this study, a laboratory-based pushbroom hyperspectral imaging system in reflectance mode was developed in the near infrared (NIR) range (900–1700nm) for non-invasive determination of the major chemical compositions of beef. Beef samples collected from different breeds were scanned by the system followed by traditional assessment of their chemical composition by using the ordinary wet-chemical methods. The extracted spectral data and the measured quality parameters were modeled by partial least squares regression (PLSR) for predicting water, fat and protein contents yielding a reasonable accuracy with determination coefficients of 0.89, 0.84 and 0.86 concomitant with standard error of prediction (SEP) of 0.46%, 0.65% and 0.29%, respectively. Some image processing algorithms were developed and the most relevant wavelengths were selected to visualize the predicted chemical constituents in each pixel of the hyperspectral image yielding the spatially distributed visualizations of the sample contents. The results were promising and implied that hyperspectral imaging technique associated with appropriate chemometric multivariate analyses has a great potential for simultaneous assessment of various chemical constituents without using hazardous chemical reagents. [Copyright &y& Elsevier]

Abstract: By integrating two classical optical sensing technologies of imaging and spectroscopy into one system, hyperspectral imaging can provide both spatial and spectral information, simultaneously. Therefore, hyperspectral imaging has the capability to rapidly and non-invasively monitor both physical and morphological characteristics and intrinsic chemical and molecular information of a food product in the purpose of quality and safety analysis and assessment. As the first part of this review, some fundamental knowledge about hyperspectral imaging is reviewed, which includes the relationship between spectroscopy, imaging, and hyperspectral imaging, principles of hyperspectral imaging, instruments for hyperspectral imaging, processing methods for data analysis, and discussion on advantages and disadvantages. Industrial relevance: It is anticipated that real-time food monitoring systems with this technique can be expected to meet the requirements of the modern industrial control and sorting systems in the near future. [Copyright &y& Elsevier]

Abstract: In recent years, hyperspectral imaging has gained a wide recognition as a non-destructive and fast quality and safety analysis and assessment method for a wide range of food products. As the second part of this review, applications in quality and safety determination for food products are presented to illustrate the capability of this technique in the food industry for classification and grading, defect and disease detection, distribution visualization of chemical attributes, and evaluations of overall quality of meat, fish, fruits, vegetables, and other food products. The state of the art of hyperspectral imaging for each of the categories was summarized in the aspects of the investigated quality and safety attributes, the used systems (wavelength range, acquisition mode), the data analysis methods (feature extraction, multivariate calibration, variables selection), and the performance (correlation, error, visualization). With its success in different applications of food quality and safety analysis and assessment, it is evident that hyperspectral imaging can automate a variety of routine inspection tasks. Industrial relevance: It is anticipated that real-time food monitoring systems with this technique can be expected to meet the requirements of the modern industrial control and sorting systems in the near future. [Copyright &y& Elsevier]

Abstract: The investigation was conducted to develop a hyperspectral imaging system in the near infrared (NIR) region (900–1700nm) to predict the moisture content, pH and color in cooked, pre-sliced turkey hams. Hyperspectral images were acquired by scanning the ham slices (900–1700nm) originated from different quality grade of turkey hams. Spectral data were then extracted and analyzed using partial least-squares (PLSs) regression, as a multivariate calibration method, to reduce the high dimensionality of the data and to correlate the NIR reflectance spectra with quality attributes of the samples considered. Instead of using a wide range of spectra, the number of wavebands was reduced for more stable, comprehensive and faster model in the subsequent multispectral imaging system. From this point of view, important wavelengths were selected to improve the predictive power of the calibration models as well as to simplify the model by avoiding repetition of information or redundancies. With the help of PLS regression analysis, nine wavelengths (927, 944, 1004, 1058, 1108, 1212, 1259, 1362 and 1406nm) were selected as the optimum wavelengths for moisture prediction, eight wavelengths (927, 947, 1004, 1071, 1121, 1255, 1312 and 1641nm) for pH prediction and nine wavelengths (914, 931, 991, 1115, 1164, 1218, 1282, 1362 and 1638nm) were identified for color (a *) prediction. With the identified reduced number wavelengths, good coefficients of determination (R 2) of 0.88, 0.81 and 0.74 with RMSECV of 2.51, 0.02 and 0.35 for moisture, pH and color, respectively, were achieved, reflecting reasonable accuracy and robustness of the models. [Copyright &y& Elsevier]

Recently, food quality and safety have emerged as significant global issues. The rapid detection of food contaminants and spoilage markers has attracted increasing concerns. The grouping of illuminants based on the principle of aggregation-induced emission (AIE) mechanism for designing food safety and quality monitoring and analysis sensing platforms can address the shortcomings of conventional fluorophore aggregation-caused quenching (ACQ), offering the benefits of superb photoluminescence properties and trace-level detection accuracy. With the increasing demand for rapid and real-time monitoring in the food industry, such a robust sensing platform is becoming progressively important. In the current review, the luminescence mechanisms and structure design of AIE sensing platforms are first introduced. The sensing mechanisms are elucidated, including noncovalent interaction, solubility and viscosity change, specific recognition, and photophysical quenching/dequenching processes. Moreover, this review comprehensively summarizes the latest and representative applications of AIE sensing platforms in the detection of foodborne pathogens, environmental pollutants, biotoxins, agrochemicals, illegal additives, and spoilage markers. Lastly, the outlook and challenges of AIE sensing platforms are discussed. The emerging AIE sensing platform exhibits the outstanding advantages of rapidity, high sensitivity, and good accuracy in analytes detection, as well as predestined capabilities in constructing portable solid-state sensors. The combination of AIE sensing platforms with other technologies, such as immunosensing techniques, freshness labels, and smartphone platforms, can further facilitate the development of commercialized AIE sensing platforms, especially for portable, real-time, and on-site monitoring applications. From typical organic molecules to nature-derived AIE nanomaterials, the discovery, and synthesis of different types of AIE sensing substances are under active exploration to provide better solutions for food safety and quality inspection. • Review of the concept of AIE from the standpoint of sensing systems. • Introduction of AIE sensors in terms of structure design and sensing mechanism. • Summary of the novel trends of AIE sensors for food safety and quality detection. • Discussion on the future challenges in practical applications of AIE sensors. [ABSTRACT FROM AUTHOR]

This paper reviews the techniques available for image feature extraction and their applications in the food industry up to now according to the four major kinds of image features, i.e., colour, size, shape, and texture. Results from previous studies have shown that each kind of image features contained important information required for food quality evaluation and inspection. Furthermore, the proper combination of different kinds of image features can normally increase the accuracy of the evaluation results; sometimes such a combination might even reveal some quality attributes that cannot be identified by using only a single kind of image features. Further to this, the feature extraction techniques were compared with each other, and their advantages, disadvantages, and feasibilities in different applications were also discussed. [Copyright &y& Elsevier]

Abstract: The principle of vacuum cooling is based on rapid evaporation of part of the moisture of the product under vacuum. Vacuum cooling can be used to shorten processing time, extend product shelf life, and improve product quality and safety. Traditionally, vacuum cooling is used in the agricultural industry to pre-cool leafy vegetables and mushroom in order to rapidly remove field heats. Recently, vacuum cooling has been applied to cool viscous food products and bakery products in the food industry, and tuna in the fish industry. Food safety concern has driven cooked meat manufacturers to explore new method to reduce cooling time, which has consequently led to a comprehensive research study of vacuum cooling of large cooked meat joints in the past few years including mathematical modelling of the vacuum cooling process using finite element method and computational fluid dynamics (CFD), especially thorough research work has been carried out by the Food Refrigeration and Computerised Food Technology (FRCFT) Research Group in National University of Ireland. Currently, research studies on vacuum cooling of ready meal components have also been conducted in FRCFT Research Group. This paper first discusses the principles and equipment of vacuum cooling and critically analyses the advantages and disadvantages of this technique. Much effort is then spent on reviewing the development of this technology for the agri-food industry, in particularly, the latest research results from the FRCFT Research Group, which have carried out extensive research work since 1997 funded by the Non-Commissioned Food Research Programme and the Food Institutional Research Measures administered by the Irish Government Department of Agriculture and Food. Future prospects of research and development of vacuum cooling technology is finally addressed. [Copyright &y& Elsevier]

Abstract: Texture is an important image feature and has been applied greatly in the food industry for quality evaluation and inspection. Recent applications of texture-analysis techniques in the food industry were reviewed in the current paper. There are four different types of texture, i.e. statistical texture, structural texture, model-based texture, and transform-based texture. Statistical texture can be obtained using statistical approachs from the higher-order of pixel grey values of images while structural texture is acquired through some structural primitives constructed from grey values of pixels. Transform-based texture can be obtained by using statistical measurements from the images transformed with certain methods. Model-based texture can be attained by calculating coefficients from a model based on the relationship of the grey values between a pixel and its neighboring pixels. Among them, statistical texture is the most widely used one in the food industry for its high accuracy and less computation time. Transform-based texture and model-based texture are also used, although not as popular as statistical texture. However, structural texture is rarely used in the food industry. Due to the limited understanding of image texture up to now, it is difficult to identify which kind of method is the best for certain application. Therefore, it is expected that by employing different methods together, final results can be improved. [Copyright &y& Elsevier]

Abstract: Learning techniques have been applied increasingly for food quality evaluation using computer vision in recent years. This paper reviews recent advances in learning techniques for food quality evaluation using computer vision, which include artificial neural network, statistical learning, fuzzy logic, genetic algorithm, and decision tree. Artificial neural network (ANN) and statistical learning (SL) remain the primary learning methods in the field of computer vision for food quality evaluation. Among the applications of learning algorithms in computer vision for food quality evaluation, most of them are for classification and prediction, however, there are also some for image segmentation and feature selection. In this paper, the promise of learning techniques for food quality evaluation using computer vision is demonstrated, and some issues which need to be resolved or investigated further to expedite the application of learning algorithms are also discussed. [Copyright &y& Elsevier]

Image processing techniques have been applied increasingly for food quality evaluation in recent years. This paper reviews recent advances in image processing techniques for food quality evaluation, which include charge coupled device camera, ultrasound, magnetic resonance imaging, computed tomography, and electrical tomography for image acquisition; pixel and local pre-processing approaches for image pre-processing; thresholding-based, gradient-based, region-based, and classification-based methods for image segmentation; size, shape, colour, and texture features for object measurement; and statistical, fuzzy logic, and neural network methods for classification. The promise of image processing techniques for food quality evaluation is demonstrated, and some issues which need to be resolved or investigated further to expedite the application of image processing technologies for food quality evaluation are also discussed. [Copyright &y& Elsevier]

Stability of food is a great challenge that encompasses the interaction among the constituents, processing conditions and thermal history. The frozen storage of food sometimes incurs possible harmful effect due to the formation of large ice crystal and destruction of the cell structure. Glass transition state is a second-order transition of matter where a system reaches a thermodynamically non-equilibrium state due to the immobility of molecules, and it is a universal phenomenon observed when liquid goes to supercooled vitreous state because of extensive cooling or change in the composition. The cryostabilisation or storage at glassy conditions has been studied widely as it can prevent the quality degradation due to freezing. The review provides an overview of the theories and assumptions related to the concept of the glass transition and the response of different food components such as moisture, carbohydrate, protein, and lipid at the glassy state. Influences of processing conditions including moisture removal, freezing rate, annealing time on the relaxation process or the glass transition are also elaborated. In addition, the effects of novel freezing techniques such as ultrasound assisted, high pressure assisted, electric and magnetic field assisted freezing are also discussed in the current review. The glass transition is highly dependent on the presence of moisture and carbohydrate molecules for its great affinity to make hydrogen bond and increase viscosity. The fat and protein glass transitions take place at very low temperatures, at which commercial frozen storage is not considered feasible. Conventional freeze drying and dehydrofreezing require removal of water, which increases the glass transition temperature. Storage at or below the glass transition temperature is desired to increase stability and prevent any quality deterioration. Novel freezing processes such as high pressure, ultrasound, electric and magnetic assisted freezing incur changes in microstructure and metastable glassy states. The current review provides valuable information for designing products with optimized processing techniques and conditions. • Glass transitions for various food components are discussed. • Effects of novel freezing technologies on glass transition are elaborated. • Glass transitions have high impacts on stability and other food quality parameters. • Glass transitions are highly dependent on constituents and freezing conditions. [ABSTRACT FROM AUTHOR]

Fresh food are perishable, and freezing is a popular way of maintaining the quality and safety of foods. However, ice crystals formed during freezing may result in the breakage of cell structure, leading to quality deterioration. In order to better understand the relationship between microstructure and ice crystals and obtain high quality food products, it is critical to effectively measure and control the behavior of ice crystals. In the current review, the principles of measuring methods including optical and electron microscopy, electromagnetic spectroscopy, differential scanning calorimetry (DSC) and online techniques are introduced, novel technologies based on ultrasound, high pressure, and electromagnetic fields, as well as biological proteins to control the formation of ice crystals by inducing or suppressing ice crystallization are presented. Future prospects on measuring and controlling ice crystallization are also discussed. By obtaining the moisture behavior information with NMR, Raman and DSC and direct images or network structure of ice crystal, these direct and indirect measurements can characterize ice crystals in multi-perspectives, providing constructive information on the mechanisms of the freezing process. In addition, advanced novel freezing technologies show great promise in improving the crystallization process during freezing of foods. It is thus hoped that this review could provide better understanding on ice crystallization in frozen products, leading to the optimization of the freezing process for the frozen food industry. • We discussed quality loss and microstructure damage due to ice crystal formation. • We presented different techniques to observe crystalline structure. • We assessed novel technologies to control ice crystallization. • Nondestructive and online detection are inevitable trends in future studies. • Future efforts should be made to industrialize freezing assisting technologies. [ABSTRACT FROM AUTHOR]

Abstract Background Vacuum cooling (VC) is a cooling technology for moist and porous foodstuffs with superiority in cooling rate, uniformity and hygiene, and low energy consumption. However, there are still some disadvantages that weaken the competitiveness of industrial applications such as the inevitable mass loss and uneven cooling in different parts of leafy vegetables. In order to improve the performance of VC, many efforts have been performed. Scope and approach In this review, the basic information of VC and the main applications for fruit, vegetables and meat products as well as limitations are described first. Improvements for enhancing performances of this technology in terms of operation processes including pre-treatment, technical optimization and integration, as well as equipment upgrade, and optimized operation conditions such as final pressure and pressure reduction rate are discussed. In addition, the limitation and further prospects of VC in the food industry are also mentioned. Key findings and conclusions The findings presented in this review demonstrated that optimizing operation processes and controlling operation conditions can effectively improve the performance of VC including mass loss, cooling rate and energy consumption and temperature distribution. However, many enhancing strategies still have limitation for applied in the food industry. Future trends of VC are the study of moisture migration characteristics based on food microstructure and multi-functional optimization of VC process or system. It is hoped that the current review can provide some guidance for further developments of the VC technology. Highlights • Contemporary applications of vacuum cooling to foods are presented. • Limitations in application and performance of vacuum cooling are discussed. • Innovative operation processes to improve vacuum cooling technology are assessed. • Strategies to refine operation conditions of vacuum cooling are outlined. • Key research trends comprise moisture migration and multi-functional optimization. [ABSTRACT FROM AUTHOR]

Freezing reduces the temperature of the food system and extends the shelf life of food. However, the inevitable formation of ice crystals could impact food quality. Small-size ice crystals are more acceptable in frozen foods than large aggregates with irregular shapes. Undesired ice crystals could not only change food structure and cause serious quality deterioration, including texture alteration, nutrient loss and off-flavour. Ice-regulating materials have been proven to regulate ice nucleation, growth and recrystallization, which show promising applications in the food industry. The theoretical information on ice formation, particularly ice nucleation and recrystallization, was described. Current ice-regulating materials, such as active proteins, saccharides, and natural deep eutectic solvents (NADES), and their mechanisms of regulating ice formation were summarized. Based on the ice damage to foodstuffs with different microstructures, the applications of active ice-regulating materials in improving the quality of frozen food were also discussed. Ice-regulating materials showed superior actions in regulating ice formation and their addition alleviated ice damage and improved the quality of frozen foods by accelerating or inhibiting freezing. Moreover, the current challenges and future perspectives of ice formation regulation for high-efficiency food freezing were proposed. • The theory of ice nucleation and recrystallization is presented. • The mechanisms of ice-binding materials regulating ice formation are summarized. • Ice-binding materials enhance the quality of frozen food. • The safety concerns of ice-binding materials as food ingredients are discussed. • Challenges and perspectives of ice regulation for food freezing are proposed. [ABSTRACT FROM AUTHOR]

Background Fresh cellular food materials including fruits and vegetables and animal tissues normally consist of fine organized cellular structures. Freezing is a common method to preserve the quality and safety of these cellular foods. However, the formation of ice crystals during food freezing may cause damage to the food microstructure, leading to the deterioration of food quality after thawing. Scope and approach This review offers current knowledge on freezing damage to cell structure of fresh cellular food materials. Effects of cell structure and water distribution on the texture and sensory properties of fresh cellular foods are presented. Mechanisms of cell structure damages caused by freezing are discussed. Novel methods to control the formation of ice crystals and preserve cell structures are also provided. Key findings and conclusions The quality of cellular foods after frozen-thawed is highly correlated with the integrity and viability of tissue cells. The formation of ice crystals, water migration and the inherent characteristics of cell structure are regarded as the main factors affecting the cell structure during freezing. For obtaining better quality of frozen products, further investigation and understanding on freezing damage to cell structure of fresh cellular foods is necessary. It is hoped that the current review will provide more information on improving frozen food quality for the frozen food industry. [ABSTRACT FROM AUTHOR]

Background Microbial contamination is a serious challenge in the food industry. With the increasing demand for fresh, nutritious and healthy food, novel techniques for microbial inactivation are highly needed. By absorbing photoenergy, titanium dioxide (TiO 2 ) based photocatalyst can produce reactive oxygen species (ROS) that are capable of inactivating microorganisms. Scope and approach This review summarizes recent research developments of TiO 2 photocatalysis (TPC) for antibacterial applications in liquid, gas and solid systems in the food industry. Basic principles of TPC, the mechanism of photocatalytic inactivation, and strategies for improving photoactivity are described, and applications of TPC for decomposing organic substances are presented. Furthermore, applications of combining TPC with other technologies are also discussed. Conclusions and key findings : The review shows that TPC technology has the ability to inactivate foodborne microorganisms, but with some drawbacks such as catalyst deactivation and low utilization of visible light. Modification can widen the light response into visible range and improve the photoactivity. The combined technologies can enhance the effectiveness of microbial inactivation. However, further study is still needed to improve both photocatalytic disinfection efficiency and food quality maintenance. [ABSTRACT FROM AUTHOR]

Background Food safety and quality have gained much attention in recent years and the capability to evaluate food quality and safety in a sensitive, rapid, and reliable manner is of great importance in the food industry. Therefore, surface-enhanced Raman scattering (SERS) with the advantages of excellent sensitivity, high selectivity, non-destructive nature and significant enhancement to identify the target has demonstrated a great potential for quick detection of chemical contaminants, chemical constitutes, and pathogens in food samples. Scope and approach The enhancement of Raman signals for SERS is not only related to the interactions between substrates and samples but also the functionalization of substrates to gain SERS active substrates. In the present review, different types of substrates are briefly discussed, functionalization techniques for SERS active substrates are discussed, and applications of functionalized SERS substrate in food samples are presented. Conclusions and key findings It is evident that functionalization techniques for improving SERS substrates have given encouraging outcomes, which provides possibility for identifying multiple target analytes within a complex matrix, and thus could be used as a powerful analytical tool in real-world applications in food safety analysis as well as for enhancing food quality surveillance. [ABSTRACT FROM AUTHOR]

Background The quality of products depends on their processing. Effective way of monitoring and controlling these processes will ensure the quality and safety of products. Since traditional measurement methods cannot achieve on-line monitoring, imaging spectroscopy, as a fast, accurate and non-destructive detection tool, has been widely used to evaluate quality and safety attributes of foods undergoing various processes. Scope and Approach In the current review, detailed applications of hyperspectral imaging (HSI) system in various food processes are outlined, including cooking, drying, chilling, freezing and storage, and salt curing. The study emphasized the ability of HSI technique to detect internal and external quality parameters in different food processes. Also, the advantages and disadvantages of HSI applications on these food processes are discussed. Key Findings and Conclusions The literature presented in this review clearly demonstrate that HSI has the ability to inspect and monitor different food manufacturing processes and has the potential to control the quality and safety of the processed foods. Although still with some barriers, it can be expected the HSI systems will find more useful and valuable applications in the future evaluation of food processes. [ABSTRACT FROM AUTHOR]

There is a great interest in developing optical techniques that have the capability of predicting quality attributes, safety parameters and authenticity in real-time assessment. Recently, hyperspectral imaging technique has been widely used for rapid and non-destructive inspection of various food products. Although the technique is currently in an early development stage, its potential is promising. Due to the extensive time needed for the processing of the large volumes of data, hyperspectral imaging technique cannot be directly implemented in an online system. However, selecting some feature wavelengths from hyperspectral images can be useful to develop a multispectral imaging system, which can meet the speed requirement of industrial production. Indeed, the success of multispectral imaging heavily depends on the effectiveness of hyperspectral imaging (HSI) for providing the feature wavelengths. If the high dimensionality of hyperspectral data can be reduced properly in order to design/form a low-cost multispectral imaging sensor based on some selected feature wavelengths for certain applications, the technique would certainly be incomparable for process monitoring and real-time inspection. This review first introduces the fundamental steps for selecting feature wavelengths from hyperspectral data and then describes the feature wavelengths derived from hyperspectral imaging applications to make a more effective and efficient multispectral real-time imaging system. It is anticipated that this review can act as a basis for researchers and industry for further development of online multispectral inspection system for quality, safety and authenticity of muscles food. [ABSTRACT FROM AUTHOR]

Abstract: Green bean (Phaseolus vulgaris L.) was stored under controlled freezing-point condition (0°C) as compared with room-temperature (25°C) and cold (8°C) storages for up to 18 days. Results showed that the peak rate of respiration was 109.2CO2 mg/kgh after storage at 0°C for 12 days, which was significantly lower than those with the other two storage temperatures. Weight loss increased significantly with increasing storage temperature. Measurements on other parameters such as soluble solid and surface colour also indicated that controlled freezing-point storage at 0°C could maintain better product quality. [Copyright &y& Elsevier]

Real-time temperature monitoring during cold chain logistics is critical because refrigerated foods are sensitive to temperature fluctuations. Time-temperature indicators (TTIs) are effective tools for monitoring the temperature history of food products in real-time. These technologies have been widely used in fresh food management, showing great potential to reduce food waste, ensure food safety, and achieve realistic control of the cold chain and cold storage of foods. This review presents commonly used modelling methods for TTIs establishment, including reaction rate constant (k) and activation energy (E a) determination and E a matching. Through mathematical modelling, shelf-life of TTIs can be matched with shelf-life of target foods, making response changes of TTIs reflect food quality. For the first time, different apparent response types of TTIs are summarized, covering colour-based, acidity-based, diffusion length-based, and other responses-based TTIs. Besides, TTIs applications in cold chain management of fresh foods are also highlighted concerning dairy, meat and aquatic products, and vegetables. TTIs are effective temperature-sensitive monitoring tools and have been studied for monitoring various refrigerated fresh food products, especially for meat and aquatic products. Arrhenius equation is the most widely used mathematical modelling for matching kinetics of the food products and the TTI responses. Colour-based responses increasingly become the most popular response types of TTIs for the advantages of convenient and direct observation. The future trends of TTIs development should mainly focus on the integration of multiple quality indicators, constituent simplification, cost reduction, and modelling optimization. Image 1 • Overview concerning time-temperature indicators (TTIs) has been presented. • Modeling covers getting rate constant and activation energy (E a), and matching E a. • Color/acidity/diffusion length-based responses and other responses are summarized. • The merits and drawbacks of each response types are discussed. • Applicability, commercialization and future trends of TTIs are evaluated. [ABSTRACT FROM AUTHOR]

• Tomato slices were pretreated by plasma functionalized water (PW) before drying. • PW accelerated moisture transfer and shortened drying time. • PW was combined with osmotic dehydration liquid as a hurdle pretreatment technique. • The hurdle technique improved drying and bioactive compound retention. The effects of pretreatments using plasma functionalized water (PW), osmodehydration (OD), and combined plasma functionalized water and osmodehydration (PO) on the drying characteristics, physicochemical and bioactive components of tomato slices during hot air drying at an air temperature of 55 °C and velocity of 1.5 m/s were evaluated. Results revealed that PW pretreatment led to an increase in lycopene compared to fresh samples, and shortened drying time, improved ascorbic acids, TPC, TFC, acidity, rehydration, porosity and hue, but reduced TSS, compared to dried control samples, while OD resulted in lycopene degradation during pretreatment, and prolonged drying time, increased TSS, but lowered acidity, rehydration, porosity and hue, compared to dried control samples. On the other hand, PO was found to overcome the shortcomings of OD with enhancement in the lycopene during pretreatment, and showed accelerated moisture transfer, improved bioactive, acidity, porosity, rehydration, hue and texture, but decreased TSS, when compared to dried control samples. Overall, the results showed the promising potential of PW and PO pretreatments for enhancing drying efficiency and product quality for the food industry. [ABSTRACT FROM AUTHOR]