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Cooling and freezing are two widely used methods for food preservation. Conventional cooling and freezing techniques are usually with low efficiency and prone to damage foodstuffs. In order to increase cooling and freezing efficiencies and ensure better food quality, many efforts have been performed. As effective solutions, pressure-related techniques such as vacuum cooling (VC), vacuum film cooling (VFC), vacuum spray cooling (VSC), pressure shift freezing (PSF) and isochoric freezing (ICF) have attracted a lot of interests. The current review intends to provide an overview of pressure-related cooling and freezing techniques for the food industry. In the review, the fundamentals including principles, experimental systems, thermodynamic and kinetic mechanisms and their relevant mathematical models are presented, latest applications of these techniques in the food industry are summarized, and future trends concerning technological development and industrialization are highlighted. Pressure plays an important role in improving the cooling and freezing processes and ensuring food qualities, and mathematical modeling is an effective tool for understanding the thermodynamic and kinetic mechanisms of these processes. However, the latest researches showed that despite many merits of these pressure-related processes, limitations still exist in applying some of the techniques in the food industry. For achieving technological development and industrialization of the pressure-related processes, further researches should focus on improving model performance, integrating multiple technologies, and cost control.

Milk is a complete nutrient source for humans. The quality and safety of milk are critical for both producers and consumers, thereby the dairy industry requires rapid and nondestructive methods to ensure milk quality and safety. However, conventional methods are time-consuming and laborious, and require complicated preparation procedures. Therefore, the exploration of new milk analytical methods is essential. This current review introduces the principles of Raman spectroscopy and presents recent advances since 2012 of Raman spectroscopic techniques mainly involving surface-enhanced Raman spectroscopy (SERS), fourier-transform (FT) Raman spectroscopy, near-infrared (NIR) Raman spectroscopy, and micro-Raman spectroscopy for milk analysis including milk compositions, microorganisms and antibiotic residues in milk, as well as milk adulterants. Additionally, some challenges and future outlooks are proposed. The current review shows that Raman spectroscopic techniques have the promising potential for providing rapid and nondestructive detection of milk parameters. However, the application of Raman spectroscopy on milk analysis is not common yet since some limitations of Raman spectroscopy need to be overcome before making it a routine tool for the dairy industry.

In the past ten years, as a novel and prospective nanomaterials, carbon dots have acquired tremendous attention for their unique optical and physicochemical properties, high compatibility and low cost, as well as great potential in sensing area. This review aims to present the current detecting principles based on carbon dots and other nano biological technologies, involving fluorescence quenching and recovery mechanisms. The synthetic and modificatory approaches in making carbon dots including top-down and bottom-up methods, as well as surface passivation and heteroatom doping ways are introduced. Their applications in food area, concerning detection of nutrients, restricted or banned substances as well as foodborne pathogenic bacteria and the toxins secreted are discussed. Finally, the difficulties to be overcome or problems to be solved are presented, and other novel techniques to combine with carbon dots to obtain more stable and specific nanosensors in various fields are proposed. Although carbon dots based sensors have shown the potential in sensing aspect of food area, as food samples are complex in compositions that may cause interferences, more novel techniques are needed to combine with carbon dots to develop sensitive and specific sensing probes.

Staple foods, including cereals, legumes, and root/tuber crops, dominate the daily diet of humans by providing valuable proteins, starch, oils, minerals, and vitamins. Quality evaluation of staple foods is primarily carried out on sensory (e.g. external defect, color), adulteration (e.g. species, origin), chemical (e.g. starch, proteins), mycotoxin (e.g. Fusarium toxin, aflatoxin), parasitic infection (e.g. weevil, beetle), and internal physiological (e.g. hollow heart, black heart) aspects. Conventional methods for the quality assessment of staple foods are always laborious, destructive, and time-consuming. Requirements for online monitoring of staple foods have been proposed to encourage the development of rapid, reagentless, and noninvasive techniques. Spectroscopic techniques, such as visible-infrared spectroscopy, Raman spectroscopy, nuclear magnetic resonance spectroscopy, and spectral imaging, have been introduced as promising analytical tools and applied for the quality evaluation of staple foods. This review summarizes the recent applications and progress of such spectroscopic techniques in determining various qualities of staple foods. Besides, challenges and future trends of these spectroscopic techniques are also presented.

Based on a new approach for wavelength selection, a multispectral real-time imaging system was proposed for the staple food industry to determine the fidelity of organic spelt flour (OSF) from three categories of adulterants including rye flour (RF), organic wheat flour (OWF) and spelt flour (SF). Calibration models were first built by partial least squares discriminant analysis (PLSDA) and partial least squares regression (PLSR) with spectral pretreatment for multivariate analysis of hyperspectral image in the spectral range of 900-1700nm. Instead of qualifying certain groups of characteristic wavelengths for RF, OWF, SF and OSF separately, a set of mutual wavelengths (1145, 1192, 1222, 1349, 1359, 1396, 1541, and 1567nm) was chosen by first-derivative and mean centring iteration algorithm (FMCIA) for all investigated flour samples. Then these selected feature wavelengths were utilized in PLSDA, PLSR and multiple linear regression (MLR) models to devise multispectral imaging system. Better performances for both qualitative discrimination of OSF and quantitative measure of adulterants were emerged in simplified PLSDA and PLSR models, with mean determination coefficients in cross validation (R(2)CV) of 0.958 and in prediction (R(2)P) of 0.957, respectively. To visualize the adulterants in OSF samples, the distribution maps were drawn by computing the spectral response of each pixel on corresponding spectral images at specific frequencies using a quantitative identification function. The results reveal that spectral imaging integrated with multivariate analysis has good potential for rapidly evaluating the purity of organic spelt flour., (Copyright © 2016 Elsevier B.V. All rights reserved.)

With consumer concerns increasing over food quality and safety, the food industry has begun to pay much more attention to the development of rapid and reliable food-evaluation systems over the years. As a result, there is a great need for manufacturers and retailers to operate effective real-time assessments for food quality and safety during food production and processing. Computer vision, comprising a nondestructive assessment approach, has the aptitude to estimate the characteristics of food products with its advantages of fast speed, ease of use, and minimal sample preparation. Specifically, computer vision systems are feasible for classifying food products into specific grades, detecting defects, and estimating properties such as color, shape, size, surface defects, and contamination. Therefore, in order to track the latest research developments of this technology in the agri-food industry, this review aims to present the fundamentals and instrumentation of computer vision systems with details of applications in quality assessment of agri-food products from 2007 to 2013 and also discuss its future trends in combination with spectroscopy.

K value is an important freshness index widely used for indication of nucleotide degradation and assessment of chemical spoilage. The feasibility of hyperspectral imaging (400-1000 nm) for determination of K value in grass carp and silver carp fillets was investigated. Partial least square (PLS) regression and least square support vector machines (LS-SVM) models established using full wavelengths showed excellent performances and the PLS model was better with higher determination coefficients of prediction (R(2)P = 0.936) and lower root mean square errors of prediction (RMSEP = 5.21%). The simplified PLS and LS-SVM models using the seven optimal wavelengths selected by successive projections algorithm (SPA) also presented good performances. The spatial distribution map of K value was generated by transferring the SPA-PLS model to each pixel of the images. The current study showed the suitability of using hyperspectral imaging to determine K value for evaluation of chemical spoilage and freshness of fish fillets., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

There is an increased interest in the applications of hyperspectral imaging (HSI) for assessing food quality, safety, and authenticity. HSI provides abundance of spatial and spectral information from foods by combining both spectroscopy and imaging, resulting in hundreds of contiguous wavebands for each spatial position of food samples, also known as the curse of dimensionality. It is desirable to employ feature selection algorithms for decreasing computation burden and increasing predicting accuracy, which are especially relevant in the development of online applications. Recently, a variety of feature selection algorithms have been proposed that can be categorized into three groups based on the searching strategy namely complete search, heuristic search and random search. This review mainly introduced the fundamental of each algorithm, illustrated its applications in hyperspectral data analysis in the food field, and discussed the advantages and disadvantages of these algorithms. It is hoped that this review should provide a guideline for feature selections and data processing in the future development of hyperspectral imaging technique in foods.

Food quality and safety is the foremost issue for consumers, retailers as well as regulatory authorities. Most quality parameters are assessed by traditional methods, which are time consuming, laborious, and associated with inconsistency and variability. Non-destructive methods have been developed to objectively measure quality attributes for various kinds of food. In recent years, hyperspectral imaging (HSI) has matured into one of the most powerful tools for quality evaluation of agricultural and food products. HSI allows characterization of a sample's chemical composition (spectroscopic component) and external features (imaging component) in each point of the image with full spectral information. In order to track the latest research developments of this technology, this paper gives a detailed overview of the theory and fundamentals behind this technology and discusses its applications in the field of quality evaluation of agricultural products. Additionally, future potentials of HSI are also reported.

The freshness quality of fish plays an important role in human health and the acceptance of consumers as well as in international fishery trade. Recently, with food safety becoming a critical issue of great concern in the world, determination and evaluation of fish freshness is much more significant in research and development. This review renovates and concentrates recent advances of evaluating methods for fish freshness as affected by preharvest and postharvest factors and highlights the determination methods for fish freshness including sensory evaluation, microbial inspection, chemical measurements of moisture content, volatile compounds, protein changes, lipid oxidation, and adenosine triphosphate (ATP) decomposition (K value), physical measurements, and foreign material contamination detection. Moreover, the advantages and disadvantages of these methods and techniques are compared and discussed and some viewpoints about the current work and future trends are also presented.

Nowadays, people have increasingly realized the importance of acquiring high quality and nutritional values of fish and fish products in their daily diet. Quality evaluation and assessment are always expected and conducted by using rapid and nondestructive methods in order to satisfy both producers and consumers. During the past two decades, spectroscopic and imaging techniques have been developed to nondestructively estimate and measure quality attributes of fish and fish products. Among these noninvasive methods, visible/near-infrared (VIS/NIR) spectroscopy, computer/machine vision, and hyperspectral imaging have been regarded as powerful and effective analytical tools for fish quality analysis and control. VIS/NIR spectroscopy has been widely applied to determine intrinsic quality characteristics of fish samples, such as moisture, protein, fat, and salt. Computer/machine vision on the other hand mainly focuses on the estimation of external features like color, weight, size, and surface defects. Recently, by incorporating both spectroscopy and imaging techniques in one system, hyperspectral imaging cannot only measure the contents of different quality attributes simultaneously, but also obtain the spatial distribution of such attributes when the quality of fish samples are evaluated and measured. This paper systematically reviews the research advances of these three nondestructive optical techniques in the application of fish quality evaluation and determination and discuss future trends in the developments of nondestructive technologies for further quality characterization in fish and fish products.

In considering the need of people all over the world for high-quality food, there has been a recent increase in interest in the role of nondestructive and rapid detection technologies in the food industry. Moreover, the analysis of data acquired by most nondestructive technologies is complex, time-consuming, and requires highly skilled operators. Meanwhile, the general applicability of various chemometric or statistical methods is affected by noise, sample, variability, and data complexity that vary under various testing conditions. Nowadays, machine learning (ML) techniques have a wide range of applications in the food industry, especially in nondestructive technology and equipment intelligence, due to their powerful ability in handling irrelevant information, extracting feature variables, and building calibration models. The review provides an introduction and comparison of machine learning techniques, and summarizes these algorithms as traditional machine learning (TML), and deep learning (DL). Moreover, several novel nondestructive technologies, namely acoustic analysis, machine vision (MV), electronic nose (E-nose), and spectral imaging, combined with different advanced ML techniques and their applications in food quality assessment such as variety identification and classification, safety inspection and processing control, are presented. In addition to this, the existing challenges and prospects are discussed. The result of this review indicates that nondestructive testing technologies combined with state-of-the-art machine learning techniques show great potential for monitoring the quality and safety of food products and different machine learning algorithms have their characteristics and applicability scenarios. Due to the nature of feature learning, DL is one of the most promising and powerful techniques for real-time applications, which needs further research for full and wide applications in the food industry. [ABSTRACT FROM AUTHOR]

Infrared drying (IRD) is considered an innovative drying solution for the food industry with advantages of energy-saving potentials, reduced drying time and production cost-effectiveness. However, IRD also suffers from drawbacks such as weak penetrative ability, and product overheating and burning. Therefore, over the years, significant progress has been made to overcome these shortcomings by developing infrared-accelerated drying (IRAD) technology based on the combination of IRD with other drying technologies. Although several reviews have been published on IRD, no review focusing on IRAD is yet available. The current review presents up-to-date knowledge and findings on the applications of IRAD technologies for enhancing the quality and safety of food. The fundamental principles and characteristics of IRAD, energy-saving potentials, simulation and optimization approaches for enhancing efficiency, and developments in various acceleration approaches by combining with other drying techniques for achieving better end-products are discussed, and challenges and future work for developing the novel accelerated drying technology are also presented. Due to the synergistic effects of sequential or simultaneous combined drying methods, the total drying time and energy required are drastically lowered with most IRAD technologies, and consequently there are significant improvements in the sensory, nutritional, and safety attributes of dried food products with better appearance and quality. The development of multi-wavelength IRAD systems based on infrared absorption bands, and the incorporation of novel sensing techniques for real-time monitoring during drying will further enhance process efficiency and food quality and safety. [ABSTRACT FROM AUTHOR]

Isochoric freezing is an emerging technique for preserving food at subfreezing temperatures under moderately high pressure. This study investigated the impact of isochoric frozen storage (IFS) of chicken breast for 0, 3, 6, 9, 12, and 15 days using 2.5% NaCl solution at −4 °C on qualities including physicochemical and microbial attributes, as compared with samples under conventional frozen storage (CFS) at the same temperature. Results showed IFS samples exhibited slight enhancements in various quality parameters, including pH, protein solubility, TBARS, drip loss, shear force, yellowness, cooking loss, and a slow decreasing rate in lightness, redness, Ca2+-ATPase activity, total viable count, and TVB-N, while substantial changes occurred in CFS samples for all quality parameters. This suggests that the impact of high pressure in isochoric freezing would be advantageous in terms of microbial destruction and enzymatic inhibition, potentially offering better long-term preservation techniques for the industry. • Isochoric frozen storage (IFS) at −4 °C of chicken breast meat was studied. • IFS slowly enhanced protein solubility, pH, and texture of the meat. • IFS significantly minimized TVB-N, drip loss, cooking loss, and lipid oxidation. • IFS also significantly inhibited Ca2+-ATPase activity and microbial viability. [ABSTRACT FROM AUTHOR]

Dehydration is one of the most widely used food processing techniques, which is sophisticated in nature. Rapid and accurate prediction of dehydration performance and its effects on product quality is still a difficult task. Traditional analytical methods for evaluating food dehydration processes are laborious, time-consuming and destructive, and they are not suitable for online applications. On the other hand, vibrational spectral techniques coupled with chemometrics have emerged as a rapid and noninvasive tool with excellent potential for online evaluation and control of the dehydration process to improve final dried food quality. In the current review, the fundamental of food dehydration and five types of vibrational spectral techniques, and spectral data processing methods are introduced. Critical overtones bands related to dehydration attributes in the near-infrared (NIR) region and the state-of-the-art applications of vibrational spectral analyses in evaluating food quality attributes as affected by dehydration processes are summarized. Research investigations since 2010 on using vibrational spectral technologies combined with chemometrics to continuously monitor food quality attributes during dehydration processes are also covered in this review. [ABSTRACT FROM AUTHOR]

Controlled release (CR) systems have become a powerful platform for accurate and effective delivery of bioactive compounds (BCs). Metal-organic frameworks (MOFs) are one of the best BCs-loaded carriers for CR systems. In the review, the principles and methods of the design and synthesis of MOFs-CR systems are summarized in detail, the encapsulation of BCs by MOFs and CR mechanisms are explored, and their biological toxicity and biocompatibility are highlighted and applications in the food industry are discussed. In addition, current challenges in this field and possible future development directions are also presented. MOFs have been proven to encapsulate BCs effectively, including gaseous and solid molecules, and control the release of BCs through spontaneous diffusion or stimulus-response. The solubility, stability and biocompatibility of BCs encapsulated by MOFs are greatly improved, which expands their applications in foods. The effective CR of BCs by MOFs-CR systems is beneficial to assist in maintaining or even improving the quality and safety of food, reduce the BCs usage while increasing the bioavailability. Low- or non-biotoxic MOFs, especially bio-MOFs, show greater application prospects in the food industry. [ABSTRACT FROM AUTHOR]

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]

Frozen foods are among the most popular food products and the development of techniques for the rapid detection of their structures and quality is important for the frozen food industry. In the current review, the principles and applications of Raman spectroscopic techniques in detecting and evaluating the structure changes and quality of frozen foods are discussed and merits and drawbacks of each Raman type are presented. These techniques include dispersive, Fourier transform, spatially offset, micro Raman spectroscopies. Raman spectroscopy can assess the compositional, physicochemical, and sensory characteristics of the frozen foods without any pretreatment. It can also be applied to investigate the structural alterations of protein, lipid, water and other components. Further trends of developing the Raman spectroscopy in monitoring the frozen foods should focus on reducing overlapping signals, achieving real noninvasive detection, eliminating misclassification and quantification errors, establishing standardized Raman database, and controlling cost. [ABSTRACT FROM AUTHOR]

The public concerns about agrifood safety call for innovative and reformative analytical techniques to meet the inspection requirements of high sensitivity, specificity, and reproducibility. Enzyme‐mimetic nanomaterials or nanozymes, which combine enzyme‐like properties with nanoscale features, emerge as an excellent tool for quality and safety detection in the agrifood sector, due to not only their robust capacity in detection but also their attraction in future‐oriented exploitations. However, in‐depth understanding about the fundamental principles of nanozymes for food quality and safety detection remains limited, which makes their applications largely empirical. This review provides a comprehensive overview of the principles, designs, and applications of nanozyme‐based detection technique in the agrifood industry. The discussion mainly involves three mimicking types, that is, peroxidase, oxidase, and catalase‐like nanozymes, capable of detecting major agrifood analytes. The current principles and strategies are classified and then discussed in details through discriminating the roles of nanozymes in diverse detection platforms. Thereafter, recent applications of nanozymes in detecting various endogenous ingredients and exogenous contaminants in foods are reviewed, and the outlook of profound developments are explained. Evidenced by the increasing publications, nanozyme‐based detection techniques are narrowing the gap to practical‐oriented food analytical methods, while some challenges in optimization of nanozymes, diversification of recognition‐to‐signal manners, and sustainability of methodology need to conquer in the future. [ABSTRACT FROM AUTHOR]

Hyperspectral imaging (HSI) techniques play an important role in the food industry for providing rapid, nondestructive, and chemical‐free detection method, whereas a microscope can provide detailed information about the microstructure of a food item. As an emerging imaging spectroscopy technique, hyperspectral microscope imaging (HMI) technique combines the advantages of HSI with microscopic imaging and has been gradually applied in the food industry. This review introduces the principles of different kinds of HMI techniques, such as fluorescence HMI, visible/near‐infrared HMI, Raman HMI, and infrared HMI. Moreover, detailed applications of HMI techniques are summarized, including evaluation of structures of nutrients, and detection of microorganisms and residues. On the other hand, some challenges and future trends in the applications of these techniques are also discussed. It is concluded that by integrating HSI with microscopy, HMI can not only provide both spectral and spatial information about food substances but also provide their chemical information at the molecular or cellular level. Therefore, HMI techniques have great potentials in nondestructive evaluation of structures of nutrients, and detection of microorganisms and residues for the food industry. [ABSTRACT FROM AUTHOR]

Hyperspectral techniques in terms of spectroscopy and hyperspectral imaging have become reliable analytical tools to effectively describe quality attributes of roots and tubers (such as potato, sweet potato, cassava, yam, taro, and sugar beet). In addition to the ability for obtaining rapid information about food external or internal defects including sprout, bruise, and hollow heart, and identifying different grades of food quality, such techniques have also been implemented to determine physical properties (such as color, texture, and specific gravity) and chemical constituents (such as protein, vitamins, and carotenoids) in root and tuber products with avoidance of extensive sample preparation. Developments of related quality evaluation systems based on hyperspectral data that determine food quality parameters would bring about economic and technical values to the food industry. Consequently, a comprehensive review of hyperspectral literature is carried out in this chapter. The spectral data acquired, the multivariate statistical methods used, and the main breakthroughs of recent studies on quality determinations of root and tuber products are discussed and summarized. The conclusion elaborates the promise of how hyperspectral techniques can be applied for non-invasive and rapid evaluations of tuber quality properties. [ABSTRACT FROM AUTHOR]

Freezing is one of the most widespread used preservation methods for meats including fish meat. Traditional freezing methods such as air blast freezing and cryogenic freezing could induce some quality deterioration such as damage to cell structure, increased drip loss, and poor sensory value. Therefore, novel freezing methods have been developed to minimize the disadvantages of traditional freezing methods. This review describes the enhancement of quality attributes of muscle tissues frozen by novel freezing technologies, including high pressure freezing, electrically and magnetically assisted freezing, ultrasound assisted freezing and antifreeze protein. These quality attributes include microstructure, moisture loss, color, tenderness, protein denaturation, lipid and protein oxidation, and microbial counts. In this review, the principles of these emerging freezing technologies are introduced, and the impacts of these technologies on controlling the formation and growth of ice crystals and on complex changes of protein are also discussed. The current review shows that the novel freezing methods have positive effects on promoting the quality of frozen muscle. At a micro level, the majority of the novel methods have some certain ability on controlling the formation and growth of ice crystals, thus creating smaller, and more homogeneous and regular distribution of ice crystals, leading to better microstructure and enhanced quality attributes of frozen meats. Meanwhile, complex changes of protein take place under some of these novel freezing processes, and therefore the possible negative effect of the changes of protein should also be considered for commercial applications of these technologies in the frozen food industry. [ABSTRACT FROM AUTHOR]

Freezing is an effective way of food preservation. However, traditional freezing methods have the disadvantages of low freezing efficiency and generation of large ice crystals, leading to possible damage of food quality. Power ultrasound assisted freezing as a novel technique can effectively reduce the adverse effects during freezing process. This paper gives an overview on recent researches of power ultrasound technique to accelerate the food freezing processes and illustrates the main principles of power ultrasound assisted freezing. The effects of power ultrasound on liquid food, model solid food as well as fruit and vegetables are discussed, respectively, from the aspects of increasing freezing rate and improving microstructure. It is shown that ultrasound assisted freezing can effectively improve the freezing efficiency and promote the formation of small and evenly distributed ice crystals, resulting in better food quality. Different inherent properties of food samples affect the effectiveness of ultrasound application and optimum ultrasound parameters depend on the nature of the samples. The application of ultrasound to the food industry is more likely on certain types of food products and more efforts are still needed to realize the industrial translation of laboratory results. [ABSTRACT FROM AUTHOR]

The ability to analyze food safety and quality in a quick, sensitive, and reliable manner is of high importance in food industry. Surface-enhanced Raman scattering (SERS), which is popular for its significant enhancement, excellent sensitivity, and the fingerprinting ability to identify special molecules, has shown vast potential for rapid detection of chemical constitutes, chemical contaminants, and pathogens in food sample. For SERS, the enhancement of Raman signals is related to not only the SERS-active substrates, but also the interactions between sample and substrates. In the current review, colloidal and solid surface-based substrates are briefly described, fabrication techniques for SERS substrates are presented, and applications of SERS for food matrixes, correlation between substrates and food samples are also introduced. Finally, some outlook on further developments is presented. The current review is therefore intended to provide a comprehensive overview on the nanofabrication of SERS substrates, and the potential of applying SERS as an important food analysis platform. [ABSTRACT FROM AUTHOR]

This study investigated the underlying mechanisms involved in moisture migration under three different isochoric treatment conditions, namely, direct immersion freezing (DIF), vacuum pack freezing (VPF), vacuum immersion pack freezing (VIPF), and their molecular interactions on the overall freshness of chicken breast meat using a 2.5 g/dL sodium chloride solution at −4 °C. Occurring mass transfer processes of moisture, including diffusion and infusion, led to changes in water distribution and mobility, which significantly (P < 0.05) affected various characteristics, such as colour, water holding capacity, pH, cooking loss, total volatile basic nitrogen, thiobarbituric acid reactive substances, solubility, and microstructural integrity of the DIF samples. Meanwhile, VIPF samples were slightly affected except for pH and WHC, while VPF samples did not significantly differ from fresh samples (P > 0.05). The study suggested that the isochoric protocol could be varied depending on the sample nature and desired outcomes, and could provide some theoretical and experimental basis for designing isochoric freezing protocols. • Isochoric freezing mechanism on moisture migration of chicken breast was studied. • Substantial moisture loss and high mass transfer occurred in DIF samples. • DIF samples showed increases in pH, cooking loss, protein, and lipid oxidation. • VIPF samples showed a slight significant decrease in protein solubility. • No observable changes occurred in VPF samples. [ABSTRACT FROM AUTHOR]

The role of packaging cannot be denied in the life cycle of any food product. Intelligent packaging is an emerging technology in the food packaging sector. Although it still needs its full emergence in the market, its importance has been proved for the maintenance of food quality and safety. The present review describes several aspects of intelligent packaging. It first highlights different tools used in intelligent packaging and elucidates the role of these packaging devices for maintaining the quality of different food items in terms of controlling microbial growth and gas concentration, and for providing convenience and easiness to its users in the form of time temperature indication. This review also discusses other intelligent packaging solutions in supply chain management of food products to control theft and counterfeiting conducts and broaden the image of the food companies in terms of branding and marketing. Overall, intelligent packaging can ensure food quality and safety in the food industry, however there are still some concerns over this emerging technology including high cost and legal aspects, and thus future work should be performed to overcome these problems for further promoting its applications in the food industry. Moreover, work should also be carried out to combine several single intelligent packaging devices into a single one, so that most of the benefits from this emerging technology can be achieved. [ABSTRACT FROM AUTHOR]

Voids, filled with air, in plant tissues, can attenuate ultrasound, resulting in weakening the effectiveness of ultrasound during immersion freezing. The effect of voids on ultrasound-assisted immersion freezing (UF) in selected plant tissues, apple, radish, and potato was investigated in the present study. The freezing time and quality attributes of firmness, drip loss, total calcium content, and total phenolic content were investigated in apple, radish, and potato samples treated by normal immersion freezing (IF) and UF. The results showed that the more the percentage voids in the plant tissues, the lower the effectiveness of the ultrasound treatment. The total freezing time reduction (%) due to UF was a power function of the volume of voids (%): y = 0.018x−1.057 (R2 = 0.994). Ultrasound at 0.62 W/cm2 (28 kHz) resulted in the best firmness and lowest drip loss in potato, while no significant (p > 0.05) differences in quality attributes were observed between IF and UF in apple samples. These findings indicated that UF was more effective in freezing fruit or vegetables with a highly dense structure. [ABSTRACT FROM AUTHOR]

Improvements in living standards result in a growing demand for food with high quality attributes including freshness, nutrition and safety. However, current industrial processing methods rely on traditional thermal and chemical methods, such as sterilization and solvent extraction, which could induce negative effects on food quality and safety. The electric fields (EFs) involving pulsed electric fields (PEFs) and high voltage electric fields (HVEFs) have been studied and developed for assisting and enhancing various food processes. In this review, the principles and applications of pulsed and high voltage electric fields are described in details for a range of food processes, including microbial inactivation, component extraction, and winemaking, thawing and drying, freezing and enzymatic inactivation. Moreover, the advantages and limitations of electric field related technologies are discussed to foresee future developments in the food industry. This review demonstrates that electric field technology has a great potential to enhance food processing by supplementing or replacing the conventional methods employed in different food manufacturing processes. Successful industrial applications of electric field treatments have been achieved in some areas such as microbial inactivation and extraction. However, investigations of HVEFs are still in an early stage and translating the technology into industrial applications need further research efforts. [ABSTRACT FROM AUTHOR]

Fourier transform infrared (FT-IR) and Raman and hyperspectral imaging (HSI) techniques have emerged as reliable analytical methods for effectively characterizing and quantifying quality attributes of different categories of powdery food products (such as milk powder, tea powder, cocoa powder, coffee powder, soybean flour, wheat flour, and chili powder). In addition to the ability for gaining rapid information about food chemical components (such as moisture, protein, and starch), and classifying food quality into different grades, such techniques have also been implemented to determine trace impurities in pure foods and other properties of particulate foods and ingredients with avoidance of extensive sample preparation. Developments of corresponding quality evaluation systems based on FT-IR, Raman, and HSI data that measure food quality parameters and ensure product authentication, would bring about technical and economic benefits to the food industry by enhancing consumer confidence in the quality of its products. Accordingly, a comprehensive review of the mushrooming spectroscopy-based FT-IR, Raman, and HSI literature is carried out in this article. The spectral data collected, the chemometric methods used, and the main findings of recent research studies on quality assessments of powdered materials are discussed and summarized. Providing a review in such a flourishing research field is relevant as a signpost for future study. The conclusion details the promise of how such noninvasive and powerful analytical techniques can be used for rapid and accurate determinations of powder quality attributes in both academical and industrial settings. [ABSTRACT FROM AUTHOR]

The multispectral imaging technique is considered a reformation of hyperspectral imaging. It can be employed to noninvasively and rapidly evaluate food quality. Even though several imaging or sensor-based techniques have been conducted for the quality assessment of various food products, the rise of multispectral imaging has been more promising. This paper presents a comprehensive review of the use of the multispectral sensor in the quality assessment of plant foods (such as cereals, legumes, tubers, fruits, and vegetables). Different quality parameters (such as physicochemical and microbiological aspects) of plant-based foods that were determined and visualized by the combination of modeling methods and feature wavelength selection approaches are summarized. Based on the literature, the most frequently used wavelength selection methods are the successive projection algorithm (SPA) and the regression coefficient (RC). The most effective models developed for analyzing plant food products are the partial least squares regression (PLSR), least square support vector machine (LS-SVM), support vector machine (SVM), partial least squares discriminant analysis (PLSDA), and multiple linear regression (MLR). This article concludes with a discussion of challenges, potential uses, and future trends of this flourishing technique that is now also being applied to plant foods. [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]

Nowadays, near-infrared spectroscopy (NIR) has become one of the most efficient and advanced techniques for analysis of food products. Many relevant researches have been conducted in this regard. However, no reviews about the applications of NIR for liquid food analysis are reported. Therefore, this review summarizes the recent research developments of NIR technology in the field of liquid foods, focusing on the detection of quality attributes of various liquid foods, including alcoholic beverages (red wines, rice wines, and beer), nonalcoholic beverages (juice, fruit vinegars, coffee beverages, and cola beverages), dairy products (milk and yogurt), and oils (vegetable, camellia, peanut, and virgin olive oils and frying oil). In addition, the classification and authentication detection of adulteration are also covered. It is hoped that the current paper can serve as a reference source for the future liquid food analysis by NIR techniques. [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]

Fish is highly perishable and frozen storage is normally used to maintain its quality. This study employed freezing-thawing (F-T) cycles to simulate the abuse in frozen storage conditions, and their effects on the quality changes of grass carp fillet were investigated. Results indicated that with the increase in F-T cycles, the hardness exhibited an increase during cycle 0 and cycle 1 and then decreased in the following two cycles. Measurement points had little influence on textural properties. Total volatile basic nitrogen (TVB-N) value showed an increase from 8.72 to 22.55 mg N/100 g during four F-T cycles, while thiobarbituric acid reactive substances (TBARS) exhibited gradual increase with the cycles and K value was also increased from 20.57 to 76.29% with the cycles. The results demonstrated that frozen storage condition abuse showed an important effect on textural properties and TVB-N, TBARS and K value of grass carp fillet. Practical Applications Investigations of fish and fish fillet freshness are much more significant in research and development for providing premium quality for the acceptance of consumers as well as international fishery trade. However, little work has been reported about the frozen storage condition abuse on textural and chemical properties of grass carp fillet. Therefore, in the current study, freezing-thawing cycles were used to simulate the temperature abuse during frozen storage, and their effects on the quality changes of grass carp fillet muscle based upon fish textural parameters were investigated. The results should provide practical guidance for the fish industry. [ABSTRACT FROM AUTHOR]

Hyperspectral imaging is built with the aggregation of imaging, spectroscopy and radiometric techniques. This technique observes the sample behaviour when it is exposed to light and interprets the properties of the biological samples. As hyperspectral imaging helps in interpreting the sample at the molecular level, it can distinguish very minute changes in the sample composition from its scatter properties. Hyperspectral data collection depends on several parameters such as electromagnetic spectrum wavelength range, imaging mode and imaging system. Spectral data acquired using a hyperspectral imaging system contain variations due to external factors and imaging components. Moreover, food samples are complex matrices with conditions of surface and internal heterogeneities, which may lead to variations in acquired data. Hence, before extracting information, these variations and noises must be reduced from the data using reference-dependent or reference-independent spectral pre-processing techniques. Using of the entire hyperspectral data for information extraction is tedious and time-consuming. In order to overcome this, exploratory data analysis techniques are used to select crucial wavelengths from the excessive hyperspectral data. Using appropriate chemometric techniques (supervised or unsupervised learning techniques) on this pre-processed hyperspectral data, qualitative or quantitative information from sample can be obtained. Qualitative information for analysing of the chemical composition, detecting of the defects and determining the purity of the food product can be extracted using discriminant analysis techniques. Quantitative information including variation in chemical constituents and contamination levels in food and agricultural sample can be extracted using categorical regression techniques. In combination with appropriate spectra pre-processing and chemometric technique, hyperspectral imaging stands out as an advanced quality evaluation system for food and agricultural products. [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]

Muscle food is one of the most perishable food products because of its vulnerability to microbial spoilage, which can result in critical food safety problems. Traditional techniques for detection and evaluation of microbial spoilage in muscle foods are tedious, laborious, destructive, and time-consuming. In recent years, spectroscopic and imaging technologies have shown great potentials for the assessment of food quality and safety due to their nondestructive, noninvasive, cost-effective, and rapid responsive nature. This review focuses on the applications of several valuable spectroscopic techniques including visible and near-infrared spectroscopy, Fourier transform infrared spectroscopy, fluorescence spectroscopy, Raman spectroscopy, and hyperspectral imaging for the rapid and nondestructive detection of microbial spoilage in common muscle foods such as meat, poultry, fish, and related products. Combined with chemometric analysis, such as spectral preprocessing and modeling methods, these potential technologies have been successfully developed for the determination of total viable count, aerobic plate count, Enterobacteriaceae, Pseudomonas, Escherichia coli, and lactic acid bacteria loads in muscle foods. Moreover, the advantages and disadvantages of these techniques are discussed and some perspectives about future trends are also presented. [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]

There is great interest in developing hyperspectral imaging (HSI) techniques for rapid and nondestructive inspection of food quality, safety, and authenticity. In recent years, image quality has been constantly improved through advances in instrumentation, particularly in more powerful detectors. Nevertheless, pretreatment of data by de-noising is a necessary step to insure clean HSI datasets for further analysis. This review first introduces the typical and commonly used de-noising methods in HSI that correct for undesirable variations and remove noisy variables. Their advantages, disadvantages, and implementation are also discussed by giving examples of recent applications in the food industry. Finally, some advice is given for selecting the de-noising methods that are best suited for a particular application. This review offers an overview of the most frequently applied methods and the latest progress made in HSI de-noising in food applications. It provides systematic insight into future trends for generating high-accuracy predictions regarding food safety and quality. [ABSTRACT FROM AUTHOR]

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]

AbstractFood quality and safety problems caused by inefficient control in the food chain have significant implications for human health, social stability, and economic progress and optical sensor arrays (OSAs) can effectively address these challenges. This review aims to summarize the recent applications of nanomaterials-based OSA for food quality and safety visual monitoring, including colourimetric sensor array (CSA) and fluorescent sensor array (FSA). First, the fundamental properties of various advanced nanomaterials, mainly including metal nanoparticles (MNPs) and nanoclusters (MNCs), quantum dots (QDs), upconversion nanoparticles (UCNPs), and others, were described. Besides, the diverse machine learning (ML) and deep learning (DL) methods of high-dimensional data obtained from the responses between different sensing elements and analytes were presented. Moreover, the recent and representative applications in pesticide residues, heavy metal ions, bacterial contamination, antioxidants, flavor matters, and food freshness detection were comprehensively summarized. Finally, the challenges and future perspectives for nanomaterials-based OSAs are discussed. It is believed that with the advancements in artificial intelligence (AI) techniques and integrated technology, nanomaterials-based OSAs are expected to be an intelligent, effective, and rapid tool for food quality assessment and safety control. [ABSTRACT FROM AUTHOR]

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]