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Cereals are globally consumed as staple food, providing essential nutrients to the consumers. The emerging problems associated with cereals are mycotoxin outbreaks and adulteration in both the cereals and their products. Both classical and emerging techniques are extensively exploited to tackle such problems. However classical methods still face more limitations as compared to emerging nondestructive methods. High-performance liquid chromatography, gas chromatography and enzyme-linked immunosorbent assays, are classical methods employed for assessing the quality and safety parameters of cereal foods, with limitations of offline, time consuming and destructiveness. On the other hand, emerging nondestructive methodologies like hyperspectral imaging, fluorescence spectroscopy, near infrared spectroscopy and Fourier transform infrared spectroscopy have been introduced as promising techniques for the assessment of fungal contamination, quality discrimination and adulteration detection in cereals and cereal products. This review highlights the most recent applications of enlisted classical and emerging approaches, their working principles and advances in determining various safety and quality attributes of cereals and their products. Besides, challenges and future trends, their advantages and limitations are also elucidated. Classical methods have been exploited for safety and quality measurement of cereal foods with relatively low efficiency, as compared to emerging nondestructive techniques. Classical methods suffer from disadvantages of destructiveness, thus they cannot be used for on-line monitoring, detection and evaluation. Emerging approaches are reliable with accurate, fast and non-invasive nature of investigations for the authentication of safety and quality attributes of cereal grains and their products during storage and processing. These innovative technologies can overcome the complexity, troubles, destructibility and slowness associated with classical analytical tools. • Cereal and their products are important staple foods with essential nutrients. • Fungal Infections reduce nutritional value and production of grains. • Both conventional and novel methods are applied for quality monitoring of grains. • Working principles, limitations and strengths of both methods are presented. [ABSTRACT FROM AUTHOR]

Fresh fruit are important for a healthy diet, however, their shelf-life can be shortened because of ethylene, a key phytohormone associated with the ripening process. Therefore, detecting ethylene concentration on trace level and regulating its activity by safe and effective approaches are of paramount importance in extending postharvest shelf-life and controlling maturity of fruit. In this review, ethylene detection technologies as well as ethylene regulating strategies are discussed, aiming to develop more innovative and effective approaches. Effects of ethylene on quality and shelf-life of fruit are presented. Ethylene detection and monitoring technologies available such as gas chromatography, electrochemical, optical, chemical methods, especially novel methods such as those based on colorimetric, luminescence, metal-organic frameworks, organic field effect transistors and surface enhanced Raman spectroscopy are described. In addition, shelf-life extending technologies for ethylene control, removal or inhibition such as suppressing ethylene synthesis, scavenging or oxidizing or adsorbing ethylene, and blocking ethylene receptor are summarized. Finally, future perspectives on developing strategies that can simultaneously satisfy the requirements of sensitivity, rapidness and on-line for wide utilization in ethylene monitoring of fresh products are also given. It is expected that miniature and sensitive ethylene detection techniques combined with feasible ethylene control methods should be an effective solution for fruit quality maintenance and shelf-life extension. However, each type of sensors and ethylene control strategies currently available has their own advantages and limitations. Therefore, attempts should be made to exploit more effective ethylene detection and controlling technologies. • Ethylene concentration affects postharvest shelf-life and maturity of fruit. • Detecting and regulating C 2 H 4 is important in fruit postharvest management. • Commercially available C 2 H 4 detection methods have specific application fields. • Nanotechnology should be employed to achieve in-situ and rapid C 2 H 4 detection. • Dynamic controlled atmospheres can be refined to avoid CO 2 and low O 2 injury. [ABSTRACT FROM AUTHOR]

Button mushroom (Agaricus bisporus) is widely used on the world market. Browning of mushroom surface is the most intuitive factor affecting consumer purchase. Developments of browning during postharvest are related to the flush number, mechanical damage, polyphenol oxidase, phenolic compounds, pathogens and postharvest environment. Many techniques such as cooling, modified atmosphere packaging (MAP) and coating are developed to control button mushroom browning. In this review, the main factors involved in mushroom browning including mushroom tyrosinase, postharvest factors and pathogen are discussed, and some detection methods for mushroom surface color are introduced. Furthermore, different methods for controlling browning including MAP, polyphenol oxidase (PPO) inhibitors, edible coating, irradiation, cooling and other emerging techniques are reviewed and compared. Internal factors of button mushroom browning include subtracts, enzyme and mushroom cellular integrity, which are affected by postharvest factors such as mechanical damage, temperature, relative humidity, and atmosphere gas. Imaging or computer vision and hyperspectral imaging are emerging methods for the detection of mushroom color and can be used to analyze each pixel of the entire surface of mushrooms. In order to control mushroom browning, preservation methods including MAP, coating, PPO inhibitors and irradiation are extensively studied. In addition, thermally buffered package, commercial film materials and gas composition of MAP, natural coating and PPO inhibitor materials should be investigated in future. • Button mushroom browning is affected by postharvest factors. • Modified atmosphere packaging is often used among all the control methods. • Tendency of inhibitory rate for L* during storage varies with control methods. • Computer vision is a rapid and reliable method for detecting mushroom color. [ABSTRACT FROM AUTHOR]

• Discovery of oxidase-like activity and degradable property of γ-MnOOH nanowires. • Understanding of the degradation-activity correlation of γ-MnOOH nanozymes. • Designing a colorimetric platform for POC detection of OPs and AChE activity. • Low LODs, high selectivity, anti-interfere capacity, and workable in real samples. • This portable detection platform possessing great ecological sustainability. Despite the tremendous achievements of existing sensing techniques, sensitive and portable sensing of organophosphorus pesticides (OPs) in a non-polluting manner remains a challenging issue. This work proposed a facile colorimetric paper sensor using γ-MnOOH nanowires (NWs) as a degradable nanozyme and 3,3′,5,5′-tetramethylbenzidine (TMB) as a chromogenic indicator for rapid and sensitive screening of OPs and acetylcholinesterase (AChE) activity. The sensing mechanism was based on the easy disintegration of the oxidase-like γ-MnOOH NWs into invalid Mn2+ ions by the selective reaction with thiocholine (TCh) produced by AChE and acetylthiocholine iodide (ATCh), triggering a remarkable activity loss of MnOOH nanozymes towards TMB oxidation. The concentration of OPs, as an AChE inhibitor, was measured by the changes in absorbance at 652 nm or blue color of oxTMB products. Such detection platform in solution state achieved relatively low limits of detection (LODs) for AChE activity (0.007 mU mL−1), and for two typical OPs, i.e., omethoate (0.35 ng mL−1) and dichlorvos (0.14 ng mL−1), respectively. Further, the portable assembly of such AChE-nanozyme tandem reaction on test paper performed well, reaching LODs of 0.1 mU mL−1 for AChE, 10 ng mL−1 for omethoate, and 3 ng mL−1 for dichlorvos, respectively. Meanwhile, this sensing system showed great selectivity and anti-interfering capacity in both solution and solid states, and worked well in real serum and vegetable samples. The abovementioned results, along with evidence of its good ecological sustainability, demonstrated the superiority of this well-performing platform for application in the food, environmental, and medical fields. [ABSTRACT FROM AUTHOR]

Cheese is produced around the world in a wide range of flavours, varieties, textures, and shapes, which can be used as a final product in human diet, and as an important ingredient in various foods. With consumer's continuing demand for quality cheese as well as increasing challenge from production facing the industry, nondestructive techniques are increasingly used to evaluate cheese quality. Considering the rapid development of novel nondestructive techniques, relevant literatures in the past 15 years (2004–2018) are reviewed in this paper. The main quality attributes of cheese and the importance of evaluating these attributes are discussed. The principles, developments and applications of computer vision (CV), computed tomography (CT), X-ray system, magnetic resonance imaging (MRI), fluorescence spectroscopy, near-infrared (NIR) spectroscopy, Fourier transform infrared (FTIR) spectroscopy, hyperspectral imaging (HSI), Raman imaging, ultrasonic and acoustic sensing and other nondestructive techniques are discussed in this review. Among all nondestructive techniques used for cheese quality evaluation, fluorescence spectroscopy is the most used method for classification, NIR spectroscopy is mainly used for predicting chemical components, FTIR spectroscopy shows the greatest scope of applications, while CV, X-ray and MRI are only used for monitoring eye growth. HSI and Raman imaging begins to attract research interest, and synchronous fluorescence spectroscopy gradually replaces front-face fluorescence spectroscopy, whereas CV is no longer applied to cheese evaluation and literatures about NIR spectroscopy also becomes less in recent years. It is hoped that this review should provide information on current research gaps and set some directions for future studies. • Nondestructive techniques for cheese quality evaluation are reviewed. • Cheese attributes and their importance are presented. • Applicability and the pros and cons of nondestructive techniques are discussed. • Future research directions are suggested. [ABSTRACT FROM AUTHOR]

Abstract Secondary structure of proteins is closely related to the overall quality of meat. The sequence of the changes in chemical bonds caused by secondary structure modification and rapid detection method of secondary structure fractions was investigated by near-infrared hyperspectral imaging combined with generalized (G2D-CS) and heterospectral (H2D-CS) two-dimensional correlation analysis in this study. Synchronous and asynchronous spectral results from G2D-CS analysis indicated that, as α-helix fraction decreasing, the spectral intensity of N H stretching changed before that of the C H and O H, and the spectral fluctuation of O H stretching occurred after the carbonyl related C H band and before those aliphatic and aromatic C H band. Feature wavebands identified by H2D-CS analysis obtained good results with R2 CV of 0.836 in predicting α-helix fractions. The results of this study are useful for interpreting the secondary structure modification process of proteins during frozen storage and monitoring the secondary structure fraction in a rapid way. Highlights • NIR HSI was employed by the first time to monitor α-helix fraction of actomyosin. • G2D-CS was used for understanding the process of secondary structure modification. • H2D-CS was applied for identifying α-helix related NIR wavebands. • PLSR model built by the selected wavebands showed good results. [ABSTRACT FROM AUTHOR]

Abstract Protein is an important nutrient for people diet, and protein content is one of the most vital properties in quality assessment of pork meat. The potential of line-scanning based hyperspectral imaging (HSI) has been proved to be able to assess the protein content of meat, however quality of images obtained from line-scanning HSI is affected by sample transformation conditions. A novel single shot (snapshot) HSI sensor was employed to evaluate the protein content of numerous processed pork meat by using back propagation - neural network (BP-NN) and partial least squares regression (PLSR) predictive models. The results of BP-NN were better than that of PLSR. The best spectral profile was selected from reflectance, absorbance, and Kubelka–Munk (K–M) spectra by comparing the performances of their BP-NN models. The BP-NN model combined with absorbance spectra showed the best performance for evaluating the protein content of various processed pork meats with determination coefficient of cross-validation set (R2 CV) = 0.8318, and root mean square error of cross-validation set (RMSECV) = 8.38 mg/g, respectively. Results indicated the feasibility of determining the protein content of pork meats by means of single shot HSI. Highlights • The single shot hyperspectral imaging (HSI) could capture an image in 1/150 s. • Protein content of pork decreased after wet salting – dehydrating. • Absorbance spectra provided better accuracy. • BP-NN model was used to predict protein contents of pork by snapshot HSI. • Protein contents distribution of processed pork were showed by snapshot HSI. [ABSTRACT FROM AUTHOR]

Abstract The residual of pesticides in fruit and vegetables is one of the major food safety concerns for consumers. There is a demand for easy and rapid analytical methods to sense pesticide residues in foods. In this study, a core-shell Au@Ag nanoparticles aggregates (Au@AgNAs) based surface-enhanced Raman scattering (SERS) method was developed to detect trace amount of difenoconazole. Results suggested that by targeting the characteristic peaks at 700 and 808 cm−1, the logarithmic SERS signal intensities and logarithmic difenoconazole concentrations in the range from 5 × 10−7 to 2.5 × 10−5 M showed linear relationship with the coefficient of determination (R 2 ) of 0.990 and 0.985, and limit of detection (LOD) values of 5.01 × 10−8 and 2.8 × 10−8 M, respectively. The Quick Easy Cheap Effective Rugged and Safe (QuEChERS) sample preparation method was used to extract difenoconazole in grapes for SERS measurements. The LOD of difenoconazole in grapes using this developed method was as low as 48 μg/kg, which was significantly lower than the maximum residue limit (MRL) values prescribed by European Union and China. This study demonstrated that the Au@AgNAs-based SERS method can be used as a simple, rapid and sensitive approach for sensing trace contaminants in food. Graphical abstract fx1 Highlights • SERS is an alternative method for rapidly detecting trace contaminants. • Au@Ag nanowire aggregates was used as SERS substrate for detecting pesticide. • The developed SERS method can detect as low as 48 μg/kg difenoconazole in grapes. • The entire analysis can be achieved within 25 min. [ABSTRACT FROM AUTHOR]

Highlights • A multispectral model was built for DHA and EPA prediction. • A novel PN-GA algorithm was used to select the key variables. • MLR models showed better results for DHA and EPA in two fish fillets. • The dynamic changes of DHA and EPA were visualized. Abstract A multispectral model for the detection of docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA) changes in grass carp and salmon fillet was developed using physarum network and genetic algorithm (PN-GA) method for the first time. Partial least-squares regression (PLSR), multiple linear regressions (MLR), and principal component regression (PCR) algorithms were used to predict the DHA and EPA using optimal wavelengths selected by PN-GA. The MLR models showed the best DHA prediction results for both grass carp and salmon fillets, and also showed good prediction for EPA in grass carp fillet but poor prediction in salmon fillet. The MLR models were then applied for visualizing the spatial distribution of DHA and EPA changes in two fish fillets. The current results demonstrated that a developed multispectral imaging system could be feasibly constructed for DHA and EPA measurement in fish species with the optimal wavelengths selected by PN-GA method. [ABSTRACT FROM AUTHOR]

• A dual-mode freshness indicator based on DPA-Au/CuNCs was fabricated. • Simultaneous monitoring of ammonia and temperature was achieved for the first time. • Applications for in-situ and visual monitoring the seafood freshness. Seafood is highly perishable and monitoring its freshness this thus an important issue. For the first time, the current study developed a dual-mode freshness indicator based on d -penicillamine capped bimetallic gold/copper nanoclusters (DPA-Au/CuNCs) as a response probe for simultaneous monitoring of ammonia and temperatures to assess seafood freshness. Results indicated that the prepared DPA-Au/CuNCs have good sensitivity toward ammonia, with a limit of detection of 0.14 ppm. The indicator as a gas sensor for ammonia vapour detection exhibited highly recognizable fluorescence colour changes and the variations from white to yellow were observed with increasing storage temperature under natural light. For confirming its practical applications, the indicator was used to simultaneously monitor ammonia and temperatures during the storage of shrimp and fish, showing good potential for practical applications in evaluating seafood freshness for the food industry. [ABSTRACT FROM AUTHOR]

Near-infrared (NIR) spectra contain abundant data, heterospectral two-dimensional correlation (H2D-CS) analysis offers a good way to interpret these data. For the first time, H2D-CS was used to correlate the NIR hyperspectral imaging (HSI) data with mid-infrared spectra and to identify feature-related wavebands for developing models for monitoring the oxidative damage of pork myofibrils during frozen storage. The HSI images were acquired at frozen state without thawing and the oxidative damage of myofibrils was assessed by carbonyl content. Results showed that the simplified PLSR model based on H2D-CS identified feature wavebands obtained determination coefficient in prediction (R 2 P ) of 0.896 and root mean square error in prediction (RMSEP) of 0.177 nmol/mg protein, which was better than the partial least square regression (PLSR) model based on full wavebands (R 2 P  = 0.856, RMSEP = 0.209 nmol/mg protein). Therefore, H2D-CS was effective in selecting feature-related wavebands of NIR HSI. [ABSTRACT FROM AUTHOR]

Background The irrational usage of chemical substances including pesticides and drugs in agricultural and food production is a significant food safety issue due to its residues. Therefore, the detection of harmful residues in foods is an indispensable step for guaranteeing the consumer's health. Conventional methods, such as HPLC, GC-MS and LC-MS are accurate enough, but they fail to meet the requirements of the modern industry for rapid and on-line detection. Novel reliable techniques should thus be developed as alternatives. Scope and approach In this review, fundamentals of surface-enhanced Raman spectroscopy (SERS) is introduced. Recent advances in its usage for detecting harmful chemical residues in agricultural products including pesticides, antibiotics and β 2 -adrenergic agonists are discussed by two typical ways of detection improvement, and the advantages of SERS are addressed. Finally, future trends to routine use of SERS applications in harmful residues are presented. Key findings and conclusions SERS is a promising detection technique for the detection of common harmful chemical residues with merits of simple sampling, rapid data collection and non-destructiveness. Despite rapid developments in the technology, there is much studies should be done before SERS could be used as a daily tool for the industry. [ABSTRACT FROM AUTHOR]

Background Frozen dough technology could effectively extend the shelf life of bread to ensure the freshness, which is widely used and gradually replace the traditional bread production. However, during the production and storage of frozen dough, a series of problems could take place, such as inhibition of yeast activity, damage of the structure of the dough, leading to the deterioration of dough quality. Scope and approach This review summarizes the factors that affect the final quality of frozen dough, including yeast activity, dough structure and dough properties. Some effective methods for improving freeze tolerance of yeast, dough structure and dough properties are discussed, including addition of various additives, use of genetic engineering technique, optimization of freezing and storage conditions, and employment of novel freezing technology. Key findings and conclusions The addition of additives can not only improve the freeze tolerance of yeast but also maintain the rheological and thermophysical properties of dough. Through the modification of gene, freeze tolerance and fermentation ability of yeast can be improved. Optimizing freezing and storage conditions ensures the activity of yeast as well as dough network structure so that freezing damage due to ice crystals can be minimized. In addition, novel freezing technology such as ultrasound-assisted freezing can simultaneously accelerate the freezing process as well as generate fine and uniform ice crystals, thus protecting dough network structure. [ABSTRACT FROM AUTHOR]

The study investigated the possibility of using hyperspectral imaging (HSI) in the spectral range of 1000–2200 nm to characterize myofibrils cold structural deformation degrees of frozen pork samples. The HSI images of pork samples frozen under different freezing rates were acquired in the frozen state without thawing. The myofibrils cold structural deformation degrees were evaluated by surface hydrophobicity (S 0 ANS) and Ca 2+ -ATPase activity. Spectral angle mapping (SAM) algorithm was used for the first time to extract the spectral information for regression. Compared with the optimized partial least square regression (PLSR) models based on selected wavebands by successive projections algorithm (SPA), the optimized PLSR models developed based on the spectral angles calculated by the SAM algorithm achieved comparable or even better performance with R 2 P of 0.896 for S 0 ANS and 0.879 for Ca 2+ -ATPase activity, respectively. The implications of the frozen meat spectrum were also analyzed in the current study. [ABSTRACT FROM AUTHOR]

In this work, a rapid and accurate surface-enhanced Raman spectroscopy (SERS) based on silver nanodots (AgNDs) array substrate method was used to detect Alternaria alternata ( A. alternata ) in both sterile water and pear juice (an example of complex food matrix). The substrate fabrication conditions were firstly optimized to obtain the maximal SERS enhancement. SERS and Raman mapping methods were then used to scan the A. alternata adsorbed on the surface of the substrate, and the intrinsic and distinct SERS signals of A. alternata were used as the basis for detection. It was found that using A. alternata in sterile water as a model sample, the method was able to detect the A. alternata with a limit of detection (LOD) as low as 1.0 × 10 3 cfu/mL. Moreover, the newly developed method could also realize rapid detection of A. alternata in pear juice, and the lowest detectable A. alternata concentration was less than 1.0 × 10 4 cfu/mL. In addition, the A. alternata concentration range from 1.0 × 10 4 cfu/mL to 1.0 × 10 6 cfu/mL could be detected by SERS mapping. This study provides a convenient method for the detection of low-level A. alternata in complex food matrix, and further information and guidance for the design of a SERS-based detection. [ABSTRACT FROM AUTHOR]

Background Cold plasma (CP) is an emerging technology, which has attracted the attention of scientists globally. It was originally developed for ameliorating the printing and adhesion properties of polymers plus a variety of usage domains in electronics. In the last decade, its applications were extended into the food industry as a powerful tool for non-thermal processing, with diverse forms for utilization. Scope and approach This review presents an overview of recent studies on the application of cold plasma in the food industry. Specific areas discussed include microbial decontamination of food products, packaging material processing, functionality modification of food materials and dissipation of agrochemical residues. The application of CP has also been expanded into areas, such as hydrogenation of edible oils, mitigation of food allergy, inactivation of anti-nutritional factors, tailoring of seed germination performance and effluent management. In addition, the paper provides a summary of plasma chemistry and sources, factors influencing plasma efficiency and strategies for augmentation. Furthermore, key areas for future research are highlighted and salient drawbacks are discussed. Key findings and conclusions The recent studies conducted on the interaction of reactive species with food contact surfaces establish plasma processing as an eco-friendly technique with minimal changes to food products, making it a befitting alternative to traditional techniques. Active researches focused on up-scaling for commercial applications are urgently required. [ABSTRACT FROM AUTHOR]

• A high-sensitivity, stable and uniform Au@Ag NRs-CMC SERS chip was fabricated. • CMC hydrogel was used for Au@Ag NRs stabilization, homodisperse and protection. • Negatively-charged CMC hydrogel and Au@Ag NRs repel each other to form NRs arrays. • Au@Ag NRs-CMC chip has high SERS activity, reproducibility and long-term stability. • Au@Ag NRs-CMC chip achieves sensitive detection of pesticide residue in fruits. Cellulose material holds considerable promise for effective surface-enhanced Raman scattering (SERS) substrate construction due to its extensive availability, chemically modifying capacity, ease of manufacture, high flexibility and low optical activity. A large-area, high-sensitivity, stable and uniform Au@Ag nanorods (NRs)-CMC substrate was successfully developed via electrostatic repulsion by using negatively-charged core–shell Au@Ag NRs as SERS active plasmonic nanomaterial, combined with negatively-charged carboxymethylcellulose (CMC) hydrogel for nanoparticles stabilization, homodisperse and protection. The obtained Au@Ag NRs-CMC substrate showed excellent sensitivity for the detection of thiram residues in fruits containing low and abundant pigment interferents, such as apples and blueberries, with detection limits of 58 and 78 ppb, respectively. Additionally, it retained more than 80% SERS performance after storage for 9 months under ambient conditions, demonstrating its great potential in facilitating the commercialization of cellulose-based SERS technology for cost-effective detection of food contaminants with advantages of facile preparation procedure, uniformity, reproducibility and long-term stability. [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 The safety and quality of agri-food products is a critical public concern over the years. In order to guarantee human heath, it is essential to develop a rapid and non-destructive tool for assuring high-quality agri-food products in the market. Terahertz (THz) spectroscopic imaging is an emerging non-destructive technique. THz wave with the frequency range between the infrared and the microwave can penetrate many commonly used nonpolar dielectric materials and indicate vibrational modes of many biomolecules, which make it an extremely attractive tool for agri-food products inspection. Scope and approach This current paper presents the THz sources and fundamentals of THz spectroscopic imaging technique and discusses chemometric methods applied in THz spectra for qualitative and quantitative analysis. In addition, recent advances in its applications for the safety and quality control of agri-food products over the years 2012–2017 are reviewed. Finally, some perspectives on the current situation and future trends of using THz technique are addressed. Key findings and conclusions It is expected that THz technique combined with chemometric methods has great potential for agri-food products evaluation, and continuous wave THz imaging performs better for identifying low-density foreign bodies embedded in foodstuffs as compared to X-ray imaging. Additionally, THz technique shows the ability to detect packaged agri-food products. The future development of cost-effective and portable THz spectrometer with high sensitivity will make this technique in practical applications. [ABSTRACT FROM AUTHOR]

Background Microwave processing techniques have been extensively used in the food industry due to its significant reduction in cooking time and energy consumption. Microwave processing technologies such as microwave drying, heating and sterilizing play a significant role in food quality and safety control. However, few reviews have been published in recent years summarizing the latest developments in the application of microwave technology in the food industry. Scope and approach This review focuses on recent applications of microwave processing technologies including microwave drying, heating, and sterilizing in fruit (banana, apple, olive, sour cherries, pomegranate arils, blueberries, kiwifruit, aronia, strawberry, and grape tomato), vegetables (potato, bamboo shoot, purslane leaves, onion, green bean, pumpkin, eggplant, edamame, sea tangle, garlic, kale, red cabbage, tomato, cassava, lentils, chickpea, broccoli, Brussels sprouts, cauliflower, jalapeño peppers, and coriander foliage), and meat products (sardine fish, restructured silver carp slices, sea cucumber, beef semitendinosus muscle, bovine supraspinatus muscle, camel longissimus dorsi muscle, foal meat, bovine gluteus medium muscle, chicken steak, mature cows semimembranosus and semitendinosus muscles, kavurma (a ready-to-eat meat product), salmon, cod, drumettes, and beef slices), changes in product quality as affected with microwave processing are discussed in details, and future directions of research are presented. Key findings and conclusions Microwave drying has the advantages of low energy consumption and high efficiency as compared to conventional drying, while producing more porous structure of foods. Microwave drying usually combines with other conventional drying to enhance the quality of a food product. Compared with the traditional method, microwave heating or cooking can generally retain higher levels of bioactive components, antioxidant activity and attractive color of vegetables, while microwave cooking with water can cause a serious drop in nutrients due to leaching and thermal liability. Microwave sterilization has the capacity to completely inactivate microorganisms and effectively destroy enzyme activity, and less effect on antioxidant activity, texture and color of food products compared with conventional pasteurization. [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]

Effects of protein denaturation caused by high pressure freezing, involving Pressure-Factors (pressure, time) and Freezing-Factors (temperature, phase transition, recrystallization, ice crystal types), are complicated. In the current study, the conformation and functional changes of natural actomyosin (NAM) under pressure assisted freezing (PAF, 100,150,300,400,500 MPa P −20 °C/25 min ), pressure shift freezing (PSF, 200 MPa P −20 °C/25 min ), and immersion freezing ( 0.1MPa P −20 °C/5 min ) after pressure was released to 0.1 MPa, as compared to normal immersion freezing process (IF, 0.1 MPa P −20 °C/30 min ). Results indicated that PSF ( 200 MPa P −20 °C/30 min ) could reduce the denaturation of frozen NAM and a pressure of 300 MPa was the critical point to induce such a denaturation. During the periods of B → D in PSF or B → C → D in PAF, the generation and growth of ice crystals played an important role on changing the secondary and tertiary structure of the treated NAM. [ABSTRACT FROM AUTHOR]

Background Thermal processing has been widely employed in the food industry for food safety assurance. However, thermal processing may cause some undesirable changes or form by-products that negatively affect the nutritional value, flavor, color and texture of the final product. With increasing awareness of food and health, consumers prefer more naturally and minimally processed foods. Therefore, investigation of nonthermal processing technologies is important and necessary not only for its minimal impact on food but also for its extension of product shelf-life by inhibiting or inactivating microorganisms. Scope and approach This review presents a general perspective of nonthermal inactivation technologies based on electromagnetic fields, including pulsed electric fields, high voltage arc discharge, pulsed light, ionizing radiation, microwave and cold plasma. The inactivation mechanisms, characteristics and research progress, as well as the limitations of these technologies, are also discussed. Key findings and conclusions Compared to thermal treatments, nonthermal inactivation technologies have shown significant advantages with great potential. Hybrid technologies based on these methods should play a significant role in enhancing inactivation efficiency. In addition, combination of these methods with thermal treatment can lower the treatment temperature and achieve high reductions of microorganisms in foods. Despite various degrees of success in these technologies, their widespread applications in the food industry are yet to flourish. Further studies are still needed to understand these processes to provide a platform by which their limitations can be overcome. [ABSTRACT FROM AUTHOR]

When considering food security and huge market interest, a high-efficiency method to ensure the authenticity of the food product is necessary. For this goal, spectral imaging was explored for quantitative detection of Irish organic wheat flour (OWF) adulterated with common wheat flour (WF), cassava flour (CaF) and corn flour (CoF). Hyperspectral images (900–1700 nm) of OWF samples with a series of adulteration percentages were collected. The acquired spectra were pre-processed by second derivative (2nd Der) and standard normal variate (SNV) before modelling. Then partial least squares regression (PLSR) and principal component regression (PCR) were employed for quantitative analysis of adulteration proportion of CoF, CaF and WF in OWF. To develop more effective simplified models, three groups of feature wavelengths were selected from the loading plots of principal component analysis (PCA), and first-derivative and mean centering iteration algorithm (FMCIA). The models developed using FMCIA were better than PCA. After, the corresponding feature wavelengths were further reduced based on model regression coefficients (RC). The optimal result of admixture detection was emerged by the RC-FMCIA-PLSR model, with a determination coefficient of prediction ( R 2 P ) of 0.973 and a root mean square error of prediction (RMSEP) of 0.036 for OWF adulterated with CoF, R 2 P of 0.986 and RMSEP of 0.026 for OWF adulterated with CaF, and R 2 P of 0.971 and RMSEP of 0.038 for OWF adulterated with WF. Visualization maps were generated by calculating the spectral response of each pixel on flour samples. This result indicates that spectral imaging integrated with multivariate analysis has the potential to authenticate the admixtures in specific wheat flour in the range of 3–75% (w/w). [ABSTRACT FROM AUTHOR]

The feasibility of hyperspectral imaging (HSI) (400–1000 nm) for tracing the chemical spoilage extent of the raw meat used for two kinds of processed meats was investigated. Calibration models established separately for salted and cooked meats using full wavebands showed good results with the determination coefficient in prediction (R 2 P ) of 0.887 and 0.832, respectively. For simplifying the calibration models, two variable selection methods were used and compared. The results showed that genetic algorithm-partial least squares (GA-PLS) with as much continuous wavebands selected as possible always had better performance. The potential of HSI to develop one multispectral system for simultaneously tracing the chemical spoilage extent of the two kinds of processed meats was also studied. Good result with an R 2 P of 0.854 was obtained using GA-PLS as the dimension reduction method, which was thus used to visualize total volatile base nitrogen (TVB-N) contents corresponding to each pixel of the image. [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]

This study aimed to rapidly and nondestructively monitor 1-methylcyclopropene (1-MCP)-induced modulation of sugars accumulation in ripening ‘Hayward’ kiwifruit by hyperspectral imaging (HSI). Kiwifruit ( Actinidia deliciosa var. Hayward ) were treated with 0.5 μL L −1 1-MCP for 24 h at 23 °C and then stored for 20 d at room temperature for ripening. Hyperspectral images of 1-MCP treated and control fruit were recorded using a visible/near infrared (Vis/NIR) HSI system (400–1000 nm). The mean reflectance spectra of the inner cortex and the core were combined together to build a robust model for sugar contents in sliced samples. The best prediction accuracy for glucose, fructose, and sucrose in control fruit based on less than 10 selected features were: R 2 P of 0.934, 0.867, and 0.705, respectively. Moreover, the visualization maps showed a different sugar accumulation between treated and control fruit, with the sugar contents in the 1-MCP treated kiwifruit being significantly inhibited and the inhibitions were more effective in inner cortex than the core. The current study presented a rapid method for glucose, fructose, and sucrose detection in intact and fresh-cut kiwifruit as well as provided some insights for the effects of 1-MCP action on sugar accumulation through visualizing their distributions. [ABSTRACT FROM AUTHOR]

This study investigated the feasibility of hyperspectral imaging (HSI) to predict moisture content (MC) values in heated - dehydrated (H-D) and cool - air - dehydrated (C-A-D) pork samples using the calibrated models established based on fresh (F), frozen - thawed (F-T), dry - salting - dehydrated (D-S-D) and wet - salting - dehydrated (W-S-D) pork samples. The full spectra were extracted from the region of interests (ROIs) in the spectral range of 400–1000 nm and the textural variables were extracted by gray-level gradient co-occurrence matrix (GLGCM) method from the first two PC images accounting for 98.73% of the total variance. Moreover, the optimal wavelengths were selected by regression coefficients (RC). Partial least-squares regression (PLSR) predictive model was developed based on the above extracted data and their mutual combination, in which the changes can be correlated with MC - related attributes. The results demonstrated that the PLSR model based on the incorporation of the optimal wavelengths and the textures (OW-T) from F, F-T, D- S -D and W-S-D samples were the best to predict MC in H-D and C-A-D samples with R p 2 of 0.9489 and RMSEP of 1.4736. Moreover, the generated visualization maps provided a rapid way to screen the MC values unequally distributed in the whole pork samples after diverse processing conditions. Therefore, it is feasible and promising to improve the applicability of the existing MC predictive models for MC prediction in the pork samples by supplementing more samples under different treatments as another prediction sets. [ABSTRACT FROM AUTHOR]

Surface-enhanced Raman scattering (SERS) imaging coupling with multivariate analysis in spectral region of 200 to 1800 cm −1 was developed to quantify and visualize thiophanate-methyl (TM) and its metabolite carbendazim residues in red bell pepper ( Capsicum annuum L.). Least squares support vector machines (LS-SVM) and support vector machines (SVM) models based on seven optimized characteristic peaks that showed SERS effects of TM and its metabolite carbendazim residues were employed to establish prediction models. SERS spectra with first derivative (1st) and second derivative (2nd) method were subsequently compared and the optimized model of 1st-LS-SVM acquired showed the best performance (RPD = 6.08, R 2 P = 0.986 and RMSEP = 0.473). The results demonstrated that SERS imaging with multivariate analysis had the potential for rapid determination and visualization of the trace TM and its metabolite carbendazim residues in complex food matrices. [ABSTRACT FROM AUTHOR]

This study explored the potential of computer vision system (CVS) and hyperspectral imaging (HSI) technique covering spectral range of 900–1700 nm for identifying freezer burnt salmon fillets after frozen storage. Local binary pattern (LBP) descriptor was applied for the RGB image classification. Reflectance spectra were obtained from various positions surface and pretreated using the standard normal variate (SNV) transformation. TreeBagger classifier was used to build classification models for recognition and authentication of the freezer burnt flesh. The results suggested that hyperspectral discrimination performed much better than CVS with the correct classification rate (CCR) of 0.905 in validation and CCR of 0.945 in cross-validation. The effective wavelengths were selected based upon the feature importance in the TreeBagger model and the corresponding optimized model yielded CCR of 0.914 in validation and 0.978 in cross-validation. Overall, the outcome suggested the capability of HSI for rapid categorization of damaged regions on frozen salmon. [ABSTRACT FROM AUTHOR]

This study aimed to develop simplified models for rapid and nondestructive monitoring TVB-N contents during drying of cured meats based on a hyperspectral imaging system (HSI) in the spectral range of 400–1000 nm. Multivariate calibration models were first developed using partial least-squares regression (PLSR) and least-squares support vector machines (LS-SVM) in the full spectral range. In order to simplify the calibration model, a set of 9 feature wavelengths was then selected using the regression coefficient and two simplified models using PLSR and multiple linear regression (MLR) were subsequently established. The best simplified model obtained was based on MLR, with an R 2 p of 0.861 and RMSEP of 4.73. Mapping of TVB-N contents was realized by transferring the quantitative model to each pixel in the image to display protein degradation in cured pork slices at different drying periods. The results provided a possibility of realizing a multispectral imaging technique for on-line monitoring the TVB-N contents of cured meats during drying processes. [ABSTRACT FROM AUTHOR]

• Effects of isochoric freezing on quality attributes of chicken meat were studied. • Samples frozen in pure water and 1.5% NaCl solution were significantly affected. • Samples frozen in 2.5% NaCl solution at −4 and −8 °C had no significant change. • Pressure negative effect was minimized with increasing NaCl concentration. This study investigated the potential of isochoric freezing for chicken breast meat for the first time. Chicken breast samples were immersed in isochoric NaCl solutions with various concentrations of 0 (pure water, PW), 1.5 and 2.5 % at −4 and −8 °C, respectively, and effects of process parameters such as temperature, pressure, and solution concentration on quality characteristics of the sample including colour, water holding capacity, weight loss, texture, microstructure, and water mobility were evaluated. Results showed that increasing NaCl concentrations depressed freezing temperature and pressure and samples treated in PW and 1.5 % NaCl solution at −4 and −8 °C exhibited a significant decrease (P < 0.05) in the quality characteristics, while those treated in 2.5 % solution at −4 and −8 °C showed no significant difference compared with the control. These results indicated the potential for enhancing the quality of meats preserved in isochoric systems. [ABSTRACT FROM AUTHOR]

The growing concerns about microbial food safety and environmental contamination call for sustainable food active packaging materials and practices with high performance. This contribution proposed a biocatalytic spraying coating for fruit preservation using carboxymethyl cellulose nanofibers grafting enzyme-like metal-organic frameworks (CNF@Ce-MOF) with banana and mango as model fruits. The well-characterized biohybrid nanofibers were verified to simultaneously mimic good oxidase-like and apyrase-like activities, enabling effective enzyme-like sterilization against three typical foodborne pathogens, i.e. Escherichia coli O157: H7, Staphylococcus aureus , and methicillin-resistant Staphylococcus aureus , reaching killing rates as high as 90.46%. The biocidal •O 2 − generation and adenosine triphosphate depletion were the possible mechanisms causing the nonspecific bacteria death. Such antibacterial performance, as well as additional protective properties of CNF@Ce-MOF, facilitated the quality preservation during the 12-day storage of bananas and mangos by spray coating with the biomimetic CNF@Ce-MOF. It is expected that this work walks out the first step of nanozyme toward active packaging engineering for the fields of food, agriculture, and biomedicine. [Display omitted] • Biopolymeric nanozyme was created by biomineralizing in situ MOF on nanocellulose. • Dual enzyme biomimicry by CNF@MOF produced.•O 2 − species and depleted ATP • CNF@MOF possessed bacteriostatic activities, UV resistance and biocompatibility. • Pioneering research was conducted by introducing nanozyme into active packaging. • CNF@MOF coating improved quality and extended shelf life of banana and mango. [ABSTRACT FROM AUTHOR]

• Low frequency EMF changed Ca2+ATPase activity of grass carp in cold storage. • The EMF between 100 and 400 Hz inhibited protein oxidation during cold storage. • Lipid oxidation of grass carp was affected during low frequency EMF exposure. • Low frequency EMF reduced the relaxation of water molecules of grass carp. This work studied the effects of electromagnetic fields (EMF) with frequencies between 100 and 400 Hz and a fixed strength of 12 mT on cold storage of grass carp at 4 °C for 30 min, and Ca2+ATPase enzyme activities, and lipid and protein oxidations in samples were measured to assess changes in intracellular Ca2+ concentration and oxidative stability. Results showed higher Ca2+ATPase activities in samples treated with EMF frequencies. Significant (p < 0.05) decreases occurred in protein oxidation for samples treated between 100 and 300 Hz, but an increase was observed for treatment with 400 Hz. However, the lipid oxidation increased for samples treated up to 200 Hz and decreased with further increase in frequency to 300 and 400 Hz. Nuclear magnetic resonance analysis showed that exposure to different frequencies of EMF could reduce the association of water molecules with protein for both bound and immobilized water. Overall, treatments of EMF between 100 and 400 Hz could improve grass carp quality during cold storage. [ABSTRACT FROM AUTHOR]

This study investigated the feasibility of developing a multispectral imaging method using key wavelengths from hyperspectral images for modeling and simultaneously predicting total volatile basic nitrogen (TVB-N), thiobarbituric acid reactive substances (TBARS) and K value in grass carp fillet during chemical spoilage. The established least-squares support vector machine (LS-SVM) and multiple linear regression (MLR) models using five successive projection algorithm (SPA)-selected and six genetic algorithm (GA)-selected wavelengths showed excellent performances for predicting TVB-N and K value with R 2 P > 0.900 and RPD > 3.000, and poor results for TBARS value prediction. The LS-SVM model using six GA-selected wavelengths showed good reliability and was considered the best for simultaneous determination of TVB-N, TBARS and K value. The distribution maps of chemical spoilage changes were generated using image processing algorithms. The results demonstrated the feasibility of developing a rapid and on-line multispectral imaging system using the feature wavelengths and chemometrics analysis. [ABSTRACT FROM AUTHOR]

The potential use of feature wavelengths for predicting drip loss in grass carp fish, as affected by being frozen at −20 °C for 24 h and thawed at 4 °C for 1, 2, 4, and 6 days, was investigated. Hyperspectral images of frozen–thawed fish were obtained and their corresponding spectra were extracted. Least-squares support vector machine and multiple linear regression (MLR) models were established using five key wavelengths, selected by combining a genetic algorithm and successive projections algorithm, and this showed satisfactory performance in drip loss prediction. The MLR model with a determination coefficient of prediction ( R 2 P ) of 0.9258, and lower root mean square error estimated by a prediction (RMSEP) of 1.12%, was applied to transfer each pixel of the image and generate the distribution maps of exudation changes. The results confirmed that it is feasible to identify the feature wavelengths using variable selection methods and chemometric analysis for developing on-line multispectral imaging. [ABSTRACT FROM AUTHOR]

Spectral absorption index was proposed to extract the morphological features of the spectral curves in pork meat samples ( longissimus dorsi ) under the conditions including fresh, frozen–thawed, heated–dehydrated and brined–dehydrated. Savitzky–Golay (SG) smoothing and multiplicative scatter correction (MSC) were used for calibrating both the spectral reflectance and absorbance values. The absorption values were better than the reflectance values and the calibrated spectra by MSC were better than the raw and SG smoothing corrected spectra in building moisture content predictive models. The optimized partial least square regression (PLSR) model attained good results with the MSC calibrated spectral absorption values based on the spectral absorption index features ( R 2 P = 0.952, RMSEP = 1.396) and the optimal wavelengths selected by regression coefficients ( R 2 P = 0.966, RMSEP = 0.855), respectively. The models proved spectral absorption index was promising in spectral analysis to predict moisture content in pork samples using HSI techniques for the first time. [ABSTRACT FROM AUTHOR]

The influence of high hydrostatic pressure (HHP) processing in parallel with oak chip maceration on the physicochemical and sensory properties of a young red wine was investigated preliminarily. Wines were treated by HHP at 250, 450 and 650 MPa for up to 45 min and French oak chips (5 g/L) were added. HHP enhanced the extraction of phenolics from oak chips. The phenolic contents and antioxidant activity of the wine increased after HHP processing in the presence of oak chips. Meanwhile, the anthocyanin content and wine color intensity decreased in the first 5 min of pressure treatment and then increased gradually. The multivariate analysis revealed that “pressure holding time” was the key factor affecting wine physicochemical characteristics during HHP processing in the presence of oak chips. Furthermore, oak chip maceration with and without HHP processing weakened the intensities of several sensory attributes and provided the wine with an artificial taste. [ABSTRACT FROM AUTHOR]

The prediction of moisture content uniformity on mango slices as affected by four different shapes (square, rectangle, regular triangle, and round shape) during microwave-vacuum drying (MVD) was investigated using near-infrared hyperspectral imaging in combination with multivariate chemometric analysis. Applying spectral pretreatment of a 2nd derivative followed by mean-center to raw spectra was found to be greatly beneficial for the reduction of noise and scattering levels. Seven wavelengths (951, 977, 1138, 1362, 1386, 1420, and 1440 nm) with larger absolute values of regression coefficients derived from a partial least square regression model were identified as feature variables for moisture prediction. An optimized model based on the selected wavelengths was developed using multivariate linear regression, achieving a high prediction accuracy with R p 2 = 0.993 and RMSEP = 1.282%. From the moisture distribution map, a similar non-uniform drying pattern was found on square, rectangle and regular triangle-shaped samples, while round-shaped mango slices achieved better drying results. Industrial relevance The current study suggested that NIR hyperspectral imaging was a promising technique in predicting the moisture content of mango slices during MVD, and non-uniformity of moisture distribution and the effect of sample geometry should be taken into account when the microwave-vacuum method is implemented in drying. [ABSTRACT FROM AUTHOR]

Mango slices were dried by microwave-vacuum drying using a domestic microwave oven equipped with a vacuum desiccator inside. Two lab-scale hyperspectral imaging (HSI) systems were employed for moisture prediction. The Page and the Two-term thin-layer drying models were suitable to describe the current drying process with a fitting goodness of R 2 = 0.978. Partial least square (PLS) was applied to correlate the mean spectrum of each slice and reference moisture content. With three waveband selection strategies, optimal wavebands corresponding to moisture prediction were identified. The best model RC-PLS-2 ( R p 2 = 0.972 and RMSEP = 4.611%) was implemented into the moisture visualization procedure. Moisture distribution map clearly showed that the moisture content in the central part of the mango slices was lower than that of other parts. The present study demonstrated that hyperspectral imaging was a useful tool for non-destructively and rapidly measuring and visualizing the moisture content during drying process. [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]

Background Most contamination in agricultural and food products (AFP) is caused by undesirable microorganisms and how to detect microbial contaminants in a rapid and reliable way has always been a topic of great interest for researchers. By integrating traditional spectroscopy and digital imaging function into one system, hyperspectral imaging simultaneously providing spectral and spatial information is proposed and could be used as a smart and promising technology for microbial evaluation in AFP. Scope and approach In this review, we summarized the recent progresses and applications of hyperspectral imaging in replacing conventional time-consuming, tedious, labor-intensive and destructive techniques by providing a rapid, real-time, non-destructive and efficient alternative for detecting various microbial contaminants in raw and processed AFP. The great potential and importance of hyperspectral imaging is emphasized and approved with its satisfactory performance in microbial evaluation of various AFP. Key findings and conclusions Although hyperspectral imaging shows some obvious advantages, it still faces challenges in terms of accurate reference value measurement, fast data mining and advanced system development. With the further research and development of optics, it would be expected that efficient multispectral imaging systems would likely be developed and applied for online microbial evaluation in agricultural and 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]

• Combined ultrasound and plasma functionalized liquid (UPFL) treatment was studied. • UPFL treatments before vacuum packaging (VP) silver Pomfret showed best results. • Prevalent spoilage microbiota in VP silver Pomfret treated with UPFL was revealed. • Changes in myofibrillar protein structure were induced due to UPFL treatment. • Nutritional value and biomedical index of lipids and fatty acids were improved. The effects of the treatment (UPFL) combining ultrasound (US) with plasma functionalized liquids (PFL) were evaluated on the quality of vacuum-packaged silver Pomfret stored at 4 ℃ for 15 days. Conformational modifications in myofibrillar proteins, improvements in nutritional value and biomedical index of fatty acids and lipids, reduced pH of 5.70, increased K -value, TBARS, and TVB-N at values of 12.05%, 0.576 mg MDA/kg, and 9.15 mg N/100 g, respectively, and 1.99 log reductions in spoilage microorganisms were evident immediately after treatments. UPFL presented better quality preservative effects when compared with individual applications of US or PFL, and vacuum packaging ensured optimal quality enhancement effects such as stability of myofibril fragmentation, inhibition of physicochemical quality degradation, and microbial growth control. The results also revealed the predominant cultivable spoilage microbiota of vacuum-packaged silver Pomfret treated with UPFL, providing valuable information towards developing broad-spectrum sanitisers and hurdle technology for the seafood industry. [ABSTRACT FROM AUTHOR]

• HPUEH was evaluated by parametric screening and optimization. • Plasma voltage was the most significant variable in HPUEH. • Optimized HPUEH produced small sized peptides with increased surface area. • Optimized HPUEH accelerated hydrolysis, and improved bioactivity and amino acids. • Optimized HPUEH reduced emulsifying and foaming properties. Hybridising plasma functionalized water and ultrasound pretreatment for the enzymatic hydrolysis (HPUEH) of Larimichthys polyactis was evaluated by adopting Plackett-Burman design for parametric screening of six key variables, and Box-Behnken design for optimizing three most significant variables including plasma generating voltage (P V), ultrasound treatment time (U T), and enzyme concentration (E C). The models developed for predicting the degree of hydrolysis (DoH), protein recovery (PVY), and soluble protein content (SPC) were sufficiently fitted to the experimental data (R2 ≥ 0.966) with non-significant lack of fit and used for determining the optimum conditions as P V of 70 V, U T of 15 min, and E C of 1.787%, with predictive values of 27.74%, 85.62%, and 3.28 mg/mL for DoH, PVY, and SPC, respectively. HPUEH presented hydrolysates with smaller peptide sizes and molecular weights, enhanced DoH, PVY, SPC, amino acids and antioxidant activity, but reduced emulsifying and foaming properties when compared with conventional enzymatic hydrolysis. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The investigation of visible and near infrared hyperspectral imaging (400–1000 nm) coupled with classifiers and spectral pre-processing techniques was conducted to discriminate fresh from cold-stored (4 °C for 7 days) and frozen-thawed (−20 °C and −40 °C for 30 days) grass carp fish fillets. Four classifiers with four spectral pretreatment methods were applied to establish the classification models. Compared with the original models established using the full wavelengths, the classification models with three classifiers of soft independent modeling of class analogy (SIMCA), least squares-support vector machine (LS-SVM) and probabilistic neural network (PNN) in tandem with the first derivative pretreatment showed the best classification performance and the highest correct classification rate (CCR) of 94.29%. In addition, in order to reduce the high dimensionality of hyperspectral images, seven optimal wavelengths were selected by successive projections algorithm (SPA) and used to simplify the classification models. The simplified model obtained by the LS-SVM classifier coupled with the first derivative pre-processing method also presented good prediction accuracy with the CCR of 91.43%. The results demonstrated that the integration of hyperspectral imaging and classifiers analysis had a great potential for on-line detection and was feasible to rapidly and non-invasively discriminate fresh and frozen-thawed fish fillets. [ABSTRACT FROM AUTHOR]

This study examined the potential of hyperspectral imaging (HSI) for rapid prediction of 2-thiobarbituric acid reactive substances (TBARS) content in chicken meat during refrigerated storage. Using the spectral data and the reference values of TBARS, a partial least square regression (PLSR) model was established and yielded acceptable results with regression coefficients in prediction ( R p ) of 0.944 and root mean squared errors estimated by prediction (RMSEP) of 0.081. To simplify the calibration model, ten optimal wavelengths were selected by successive projections algorithm (SPA). Then, a new SPA–PLSR model based on the selected wavelengths was built and showed good results with R p of 0.801 and RMSEP of 0.157. Finally, an image algorithm was developed to achieve image visualization of TBARS values in some representative samples. The encouraging results of this study demonstrated that HSI is suitable for determination of TBARS values for freshness evaluation in chicken meat. [ABSTRACT FROM AUTHOR]

This study investigated the potential of hyperspectral imaging (HSI) for quantitative determination of total pigments in red meats, including beef, goose, and duck. Partial least squares regression (PLSR) was applied to correlate the spectral data with the reference values of total pigments measured by a traditional method. In order to simplify the PLSR model based on the full spectra, eleven optimal wavelengths were selected using successive projections algorithm (SPA). The new SPA-PLSR model yielded good results with the coefficient of determination ( R 2 p ) of 0.953, root mean square error (RMSEP) of 9.896, and ratio of prediction to deviation (RPD) of 4.628. Finally, distribution maps of total pigments in red meats were developed using an image processing algorithm. The overall results from this study indicated HSI had the capability for predicting total pigments in red meats. [ABSTRACT FROM AUTHOR]