Evaluating drying feature differences between ginger slices and splits during microwave-vacuum drying by hyperspectral imaging technique

Exploring the moisture absorption behaviours of microwave-processed wheat starch-stearic acid complexes from a molecular view

The ambient humidity significantly affects the quality characteristics of starch-lipid complexes, and the moisture absorption behaviours remain further explored. In this study, microwave-processed wheat starch-stearic acid (WS-SA) complexes were prepared, of which the moisture absorption mechanism was investigated using experimental methods and molecular dynamics (MD) simulation. Results showed that the denser structure could endow the WS-SA complexes with lower equilibrium moisture (Me = 19.0 %) as compared with the pure WS (Me = 27.7 %), indicating their higher wetting resistance. MD simulation showed that the amylose-SA could effectively prevent water infiltration by the denser structures and the hydrophobicity of the non-complexed SA. This study reveals the moisture absorption behaviours of WS-SA complexes from a molecular view, embodying the theoretical and scientific significance of the current work. For future industrial reference, the current work can guide the development of humidity control strategies to mitigate the quality deterioration risks of starch-lipid complexes.

Effects of chain lengths and unsaturation degrees of fatty acids on microwave-processed wheat starch-fatty acid complexes: Structure, digestion, and storage stability

Wheat starch and fatty acid can combine as wheat starch-fatty acid (WS-FA) complexes playing crucial roles in health but are sensitive to ambient humidity. Therefore, microwave-processed WS-FA complexes incorporating fatty acids in different carbon chain lengths (C12 to C18) and unsaturation degrees (C18:0 to C18:3) were prepared, of which structural information, digestive characteristics and humidity-induced storage stability were investigated. Results showed that both chain lengths and unsaturation degrees of fatty acids affected the structural and digestive properties of WS-FA complexes. According to the moisture absorption behaviours, WS-FA complexes exhibited lower critical absorption relative humidities (CARH: 44 %-68 % RH) and equilibrium moisture values (Me: 17.7 %-20.5 %) than pure wheat starch (CARH: 72 % RH; Me: 27.7 %), indicating ambient humidity >44 % RH significantly impacts their storage stability. Beyond structural and digestive analysis, this study first investigates humidity-induced instability of WS-FA complexes for the first time, highlighting the need for customized standards for starch-lipid complex preservation.

Highly cost-effective wheat starch-stearic acid complexes enabled by microwave processing: Structural properties, anti-digestion, and molecular dynamics simulation

Microwave (MW) heating shows higher efficiency in preparing wheat starch-stearic acid (WS-SA) complexes than the traditional water bath (WB) heating method, while the detailed "time-energy-quality" evaluations and the potential anti-digestion mechanism of the MW-processed WS-SA remain further exploration. In this study, 95 % time cost and 73 % energy consumption were saved when using MW processing WS-SA, and the MW-processed complexes were verified to show significantly higher relative crystallinity, short-range ordered structure degree, thermal stability, complex index, and resistant starch content. Molecular dynamics (MD) simulation demonstrated that MW treatment notably facilitated the binding rate of amylose and SA molecules, generating a tight and stable helical structure through hydrogen bonds and van der Waals forces. Analyses of solvent-accessible surface area and water status cross-verified that the denser structure could endow the MW-processed complexes with higher resistance to water solvation effects and correspondingly reduce the water mobility for enzymatic hydrolysis reactions, ultimately making the MW-processed complexes more undigestible. This study provides a further understanding of the anti-digestion mechanisms of the MW-processed WS-SA from the molecular level, and it is expected that the current work could attract more concerns to the highly cost-effective MW heating method for processing starchy food.

Effects of freeze-hot air drying on physicochemical properties and anti-tyrosinase activity of quince peels

Xinjiang quince peels (XQP) are rich in bioactive compounds and have anti-tyrosinase potential. However, due to their short shelf life, effective preservation techniques are needed to retain their nutritional and medicinal properties. While freeze drying (FD) is effective, combining FD with hot air drying (HAD) offers greater efficiency. The study aimed to evaluate the effects of freeze-hot air drying on the physicochemical properties and anti-tyrosinase activity of XQP. The results showed that peels subjected to FD for 18 h followed by HAD for 0.3 h (FD18-HAD0.3) had the highest contents of total phenolics, total flavonoids, chlorogenic acid, rutin, and ascorbic acid, while reducing drying time by 25 % compared to FD alone. FD18-HAD0.3 peels also showed the highest anti-tyrosinase activity, with the smallest IC50 value (7.84 ± 0.03 mg/mL). The study concludes that FD18-HAD0.3 showed potential as the optimal drying process for XQP.

Digital model of biochemical reactions in lactic acid bacterial fermentation of simple glucose and biowaste substrates

As concerns about the environmental impacts of biowaste disposal increase, lactic acid bacterial fermentation is becoming increasingly popular. Current academic research is aimed at the process optimization by developing digital bioreactors. The primary focus is to develop a digital model mimicking the biochemical reactions. In the light of this, this paper intended to build a digital model of biochemical reactions during the fermentation process of both glucose and biowaste substrates, including white pasta and organic municipal waste. For this purpose, near-infrared (NIR) and mid-infrared (MIR) spectroscopy techniques were used to collect spectral information during the fermentation process. Next, the samples were analyzed by High Pressure Liquid Chromatography (HPLC) to measure their glucose, fructose, arabinose, xylose, disaccharide, lactic acid, and acetic acid contents. The results showed that learning algorithms trained on MIR spectra accurately estimated the biochemical reactions for both glucose and biowaste substrates. For the glucose substrate, the results showed R-squared of 0.97 and RMSE of 4.69 g/L for glucose, and R-squared of 0.98 and RMSE of 2.74 g/L for lactic acid. In the case of biowaste substrate, estimations included glucose (R-squared = 0.97, RMSE = 4.69 g/L), fructose (R-squared = 0.88, RMSE = 1.47 g/L), arabinose (R-squared = 0.98, RMSE = 0.55 g/L), xylose (R-squared = 0.93, RMSE = 1.11 g/L), disaccharide (R-squared = 0.90, RMSE = 0.55 g/L), total sugar (R-squared = 0.98, RMSE = 3.79 g/L), lactic acid (R-squared = 0.98, RMSE = 2.74 g/L), and acetic acid (R-squared = 0.97, RMSE = 0.36 g/L). Regarding NIR spectral data, the predictive models were accurate when the substrate was glucose, however, they failed to accurately estimate the chemical reactions in the case of biowaste substrate. The findings of this study can be used to fulfill the requirements for a continuous fermentation process with the objective of maximizing lactic acid production.

Quality Evaluation and Heat and Mass Transfer Mechanism of Microwave Vacuum Drying of Astragalus Roots

In this research, the objective was to optimize the drying process of Astragalus by investigating the effects of microwave vacuum drying parameters, including temperature (30, 35, 40, 45, and 50 °C) and slice thickness (2, 3, 4, 5, and 6 mm). In addition, utilizing COMSOL 6.0 finite element analysis software, we delved into the distribution of heat and moisture during the drying process. The results revealed that drying temperature played a significantly greater role than slice thickness in determining the drying dynamics. The thermal and mass transfer mechanism indicated that the whole drying process conforms to the microwave radiation mechanism and the basic principle of electromagnetic heating. In the case of low temperatures and thinner slice sizes, the more polysaccharide content was retained; The total phenol content peaked when the slice thickness was 5 mm; The increase of slice thickness was not conducive to the retention of total flavonoids content. The potent antioxidant capacity was detected at a temperature of 40 °C, with slice thickness having a negligible effect on this capacity; Low temperatures were beneficial for the preservation of active ingredients. Compared with the scanning electron microscope, the structure appeared more uniform at a temperature of 50 °C. Based on the analysis of the kinetic characteristics of microwave vacuum drying of Astragalus and the quality achieved under various drying conditions, the results of the study can provide valuable guidance for controlling the quality of microwave vacuum drying of Astragalus under different drying requirements.

Comparative elucidation of bioactive and antioxidant properties of red dragon fruit peel as affected by electromagnetic and conventional drying approaches

The effects of near-infrared (NIRD), mid-infrared (MIRD), far-infrared (FIRD), microwave (MWD), and hot air drying (HAD) on drying kinetic, colour, phytochemical composition, and antioxidant activity of red dragon fruit peel (RDFP) was evaluated. Results indicated that drying methods induced varying microstructural and chemical changes on RDFP, significantly influencing moisture removal rates and phytochemical retention. The lowest drying time was observed for MWD, while MIRD presented the highest drying time. FIRD drying was more favourable for retaining TPC, TFC, betacyanin and betaxanthin, while the ascorbic acid content was better retained during MIRD and NIRD. Enhancements in ABTS, CUPRAC and reducing power were associated with FIRD, and NIRD and MIRD enhanced DPPH and HRSA. Overall, chemical modifications induced by drying improved the phytochemical and antioxidant properties but presented adversative effects on ascorbic acid and DPPH. The study presented an essential background for the optimal drying of RDFP.

Predicting wheat gluten concentrations in potato starch using GPR and SVM models built by terahertz time-domain spectroscopy

The purpose of this study was for the first time to explore the feasibility of terahertz (THz) spectral imaging for the detection of gluten contents in food samples. Based on the obtained 80 THz spectrum data, Gaussian process regression (GPR) and support vector machine (SVM) models were established to predict wheat gluten concentrations in 40 potato starch mixture samples. The prediction performances of GPR and SVM obtained were R2 = 0.859 and RMSE = 0.070, and R2 = 0.715 and RMSE = 0.101 in the gluten concentration range of 1.3%-100%, respectively, showing that the linear SVM algorithm had better prediction performance. The results indicated that THz spectral imaging combined with GPR could be used to predict the gluten content in food samples. It is thus hoped that this research should provide a novel technique for gluten content detection to ensure gluten-free food samples.

Improving Ginger's Bioactive Composition by Combining Innovative Drying and Extraction Technologies

Ginger extracts (GEs) are antioxidant, antimicrobial, and anti-inflammatory. Their bioactivity can benefit foods and active packaging by extending shelf life, enhancing safety, and providing health benefits. Highly bioactive GEs are crucial to formulating potent active products and avoiding negative effects on their properties. Sesquiterpenes and phenolics are the main bioactives in ginger, but drying and extraction affect their composition. GEs are usually obtained from dry rhizomes; however, these operations have been studied independently. Therefore, a combined study of innovative drying and extraction technologies to evaluate their influence on extracts' composition will bring knowledge on how to increase the bioactivity of GEs. The effects of an emergent drying (vacuum microwave, VMD) followed by an emergent extraction (ultrasound, UAE, 20 or 80 °C) were investigated in this work. Microwave extraction (MAE) of fresh ginger was also studied. Convective oven drying and Soxhlet extraction were the references. Drying kinetics, powder color, extract composition, and antioxidant activity were studied. While MAE preserved the original composition profile, VMD combined with UAE (20 °C) produced extracts richer in phenolics (387.6 mg.GAE/g) and antioxidant activity (2100.7 mmol.Trolox/mL), with low impact in the sesquiterpenes. VMD generated shogaols by its high temperatures and facilitated extracting bioactives by destroying cellular structures and forming pores. UAE extracted these compounds selectively, released them from cell structures, and avoided losses caused by volatilization and thermal degradation. These findings have significant implications, as they provide an opportunity to obtain GE with tailored compositions that can enhance the formulation of food, active packaging, and pharmacological products.

Analyzing the effects of nonthermal pretreatments on the quality of microwave vacuum dehydrated beef using terahertz time-domain spectroscopy and near-infrared hyperspectral imaging

Both nonthermal pretreatment and nondestructive analysis are effective technologies in improving drying processes. This study evaluated the effects of different pretreatment methods on the quality of beef dehydrated by microwave vacuum drying (MVD) and compared the MVD process performance comprising real-time moisture content (MC), MC loss, colour content, and shrinkage rate using different optical sensing methods including terahertz time-domain spectroscopy (THz-TDS) and near-infrared hyperspectral imaging (NIR-HSI). Results indicated that osmotic pretreatment improved the drying rate of MVD beef with lower changes in colour and shrinkage rate. Both THz-TDS-based and NIR-HSI-based on-site direct scanning and in-situ in-direct sensing showed accurate prediction results, with best R²_p of 0.9646 and 0.9463 for MC and R²_p of 0.9817 and 0.9563 for MC loss prediction, respectively. NIR-HSI visualisation of MC results showed that ultrasound pretreatment curbed but osmotic pretreatment promoted nonuniform distribution during MVD. This research should guide improving the industrial MVD drying process.

Non-destructive monitoring of quality attributes kinetics during the drying process: A case study of celeriac slices and the model generalisation in selected commodities

The potential of Visual-NIR hyperspectral imaging (VNIR-HSI, 425-1700 nm) to predict celeriac quality attributes during the drying process was investigated. The HSI-Gaussian Process Regression (GPR) fusion method excellently predicted moisture content (MC, R² ≈ 1.00, RMSE = 0.77 g_w 100 g_s^-1) and water activity (a_w, R² = 0.98, RMSE = 0.04). Moreover, the rehydration ratio (RR, R² = 0.89, RMSE = 0.04) and colour indices (R² = 0.80-0.93, RMSE = 0.17-1.45) were reasonably predicted. However, antioxidant activity (AA) and total phenolic compounds (TPC) were poorly predicted. These results are potentially due to MC variations dominating the NIR region, masking phenolic compounds. Finally, the celeriac-based-trained model was assessed by predicting the MC of apple, cocoyam, and carrot slices. The results were encouraging; however, a GPR model trained on the data of all four commodities was more robust (R² ≈ 1.00, RMSE = 1-2 g_w 100 g_s^-1).

The Application of Hyperspectral Imaging Technologies for the Prediction and Measurement of the Moisture Content of Various Agricultural Crops during the Drying Process

Drying is one of the common procedures in the food processing steps. The moisture content (MC) is also of crucial significance in the evaluation of the drying technique and quality of the final product. However, conventional MC evaluation methods suffer from several drawbacks, such as long processing time, destruction of the sample and the inability to determine the moisture of single grain samples. In this regard, the technology and knowledge of hyperspectral imaging (HSI) were addressed first. Then, the reports on the use of this technology as a rapid, non-destructive, and precise method were explored for the prediction and detection of the MC of crops during their drying process. After spectrometry, researchers have employed various pre-processing and merging data techniques to decrease and eliminate spectral noise. Then, diverse methods such as linear and multiple regressions and machine learning were used to model and predict the MC. Finally, the best wavelength capable of precise estimation of the MC was reported. Investigation of the previous studies revealed that HSI technology could be employed as a valuable technique to precisely control the drying process. Smart dryers are expected to be commercialised and industrialised soon by the development of portable systems capable of an online MC measurement.

Novel sequential and simultaneous infrared-accelerated drying technologies for the food industry: Principles, applications and challenges

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.

Applications of machine learning techniques for enhancing nondestructive food quality and safety detection

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.

Recent advances in muscle food safety evaluation: Hyperspectral imaging analyses and applications

As there is growing interest in process control for quality and safety in the meat industry, by integrating spectroscopy and imaging technologies into one system, hyperspectral imaging, or chemical or spectroscopic imaging has become an alternative analytical technique that can provide the spatial distribution of spectrum for fast and nondestructive detection of meat safety. This review addresses the configuration of the hyperspectral imaging system and safety indicators of muscle foods involving biological, chemical, and physical attributes and other associated hazards or poisons, which could cause safety problems. The emphasis focuses on applications of hyperspectral imaging techniques in the safety evaluation of muscle foods, including pork, beef, lamb, chicken, fish and other meat products. Although HSI can provide the spatial distribution of spectrum, characterized by overtones and combinations of the C-H, N-H, and O-H groups using different combinations of a light source, imaging spectrograph and camera, there still needs improvement to overcome the disadvantages of HSI technology for further applications at the industrial level.

Effects of cutting and drying method (vacuum freezing, catalytic infrared, and hot air drying) on rehydration kinetics and physicochemical characteristics of ginger (Zingiber officinale Roscoe)

The purpose of this study was to discuss the effects of cutting methods (transverse cutting [TC] and longitudinal cutting [LC]) and drying methods (vacuum freeze-drying [FD], hot air drying [HD], catalytic infrared drying [CID]) on rehydration kinetics and physical and chemical characteristics of rehydrated ginger. The research results showed that the rehydration rate and equilibrium moisture content increased with an increase in temperature. LC samples had a higher rehydration rate, while TC samples showed higher equilibrium moisture. Peleg model can fit the rehydration curve of the sample well. The highest coefficient of determination (R2 ) was 0.99, while the sum of squares error and lowest chi-square (χ2 ) was close to zero. Compared with fresh samples, the rehydrated ginger slices had lower gingerol content, total phenol content (TPC), total flavonoid content (TFC), and higher antioxidant activity. The different cutting methods had no significant effect on the physical and chemical properties of rehydrated ginger. In conclusion, TC-CID rehydrated products have better retention of gingerol, TPC, TFC, and antioxidant properties, which was similar to the principal component analysis. PRACTICAL APPLICATION: The results of this study show that transverse cutting combined with catalytic infrared drying is a unique processing technology. Due to the short xylem of transverse cutting ginger, the xylem diameter can be restored during rehydration, the balanced water content was high, and the quality of dried ginger can be restored to the greatest extent. This makes food processors competitive in the operation process and provides better services to consumers.

A Rapid Non-Destructive Hyperspectral Imaging Data Model for the Prediction of Pungent Constituents in Dried Ginger

Ginger is best known for its aromatic odour, spicy flavour and health-benefiting properties. Its flavour is derived primarily from two compound classes (gingerols and shogaols), with the overall quality of the product depending on the interaction between these compounds. Consequently, a robust method for determining the ratio of these compounds would be beneficial for quality control purposes. This study investigated the feasibility of using hyperspectral imaging to rapidly determine the ratio of 6-gingerol to 6-shogoal in dried ginger powder. Furthermore, the performance of several pre-processing methods and two multivariate models was explored. The best-performing models used partial least squares regression (PSLR) and least absolute shrinkage and selection operator (LASSO), using multiplicative scatter correction (MSC) and second derivative Savitzky–Golay (2D-SG) pre-processing. Using the full range of wavelengths (~400–1000 nm), the performance was similar for PLSR (R² ≥ 0.73, RMSE ≤ 0.29, and RPD ≥ 1.92) and LASSO models (R² ≥ 0.73, RMSE ≤ 0.29, and RPD ≥ 1.94). These results suggest that hyperspectral imaging combined with chemometric modelling may potentially be used as a rapid, non-destructive method for the prediction of gingerol-to-shogaol ratios in powdered ginger samples.

A dual AE-GAN guided THz spectral dehulling model for mapping energy and moisture distribution on sunflower seed kernels

Energy and moisture contents are important food chemical attributes. In the current study, a nondestructive Terahertz (THz) time-domain imaging system was first time used for evaluating the energy and moisture distributions of sunflower seed kernels inside shells. For this task, a dual autoencoders (AE)-generative adversarial nets (GAN) spectral dehulling semi-supervised model was developed. The model could automatically learn the kernel information from the latent representations of the spectra of the intact seeds through adversarial learning to achieve feature disentanglement. Results indicated that the generated kernel images had similar features to the original kernel images and high-quality chemical distribution maps for energy and moisture contents of sunflower seed kernels inside shells were successfully obtained. As the current method took the advantage of the characteristics of THz imaging and selected a suitable deep learning algorithm, it has the potential to generalize for imaging other chemical substances of other dry shelled seeds or biological samples (moisture content and thickness below 15% and 5 mm, respectively).

Improving drying kinetics, physicochemical properties and bioactive compounds of red dragon fruit (Hylocereus species) by novel infrared drying

Effects of tray rotation speeds (TRS: 0, 20, 40 rpm), temperatures (50, 60, 70 °C) and wavelength spectra (mid and near-infrared) were comparatively evaluated on improving drying kinetics, physicochemical properties and bioactive content of red dragon fruits. Results indicated that successive increases in TRS and temperature led to significant reductions in drying time and increases in drying rates and moisture diffusivity. High TRS (40 rpm) and lower temperatures (50, 60 °C) also improved colour, total soluble solids, rehydration ratio, total phenolics and flavonoid contents, betalain content and antioxidant activity. Meanwhile, NIR drying presented a more energy-efficient approach, but with substantial reductions in quality properties compared with MIR drying. Overall, the results suggested the importance of wavelength absorption properties of plant tissues and potential avoidance of localized overheating for enhanced efficiency during infrared drying and prompted the development of suitable approaches and optimization studies for improving efficiency.

A terahertz time-domain super-resolution imaging method using a local-pixel graph neural network for biological products

The low image acquisition speed of terahertz (THz) time-domain imaging systems limits their application in biological products analysis. In the current study, a local pixel graph neural network was built for THz time-domain imaging super-resolution. The method could be applied to the analysis of any heterogeneous biological products as it only required a small number of sample images for training and particularly it focused on THz feature frequencies. The graph network applied the Fourier transform to graphs extracted from low-resolution (LR) images bringing an invariance of rotation and flip for local pixels, and the network then learnt the relationship between the state of graphs and the corresponding pixels to be reconstructed. With wood cores and seeds as examples, the images of these samples were captured by a THz time-domain imaging system for training and analysed by the method, achieving the root mean square error (RMSE) of pixels of 0.0957 and 0.1061 for the wood core and seed images, respectively. In addition, the reconstructed high-resolution (HR) images, LR images and true HR images at several feature frequencies were also compared in the current study. Results indicated that the method could not only reconstruct the spatial details and the useful signals from high noise signals at high feature frequencies but could also operate super-resolution in both spatial and spectral aspects.

Effect of processing technologies on the digestibility of egg proteins

Egg and egg products are a rich source of highly bioavailable animal proteins. Several processing technologies can affect the structural and functional properties of these proteins differently and can influence their fate inside the gastrointestinal tract. The present review examines some of the processing technologies for improving egg protein digestibility and discusses how different processing conditions affect the digestibility of egg proteins under gastrointestinal digestion environments. To provide up-to-date information, most of the studies included in this review have been published in the last 5 years on different aspects of egg protein digestibility. Digestibility of egg proteins can be improved by employing some processing technologies that are able to improve the susceptibility of egg proteins to gastrointestinal proteases. Processing technologies, such as pulsed electric field, high-pressure, and ultrasound, can induce conformational and microstructural changes that lead to unfolding of the polypeptides and expose active sites for further interactions. These changes can enhance the accessibility of digestive proteases to cleavage sites. Some of these technologies may inactivate some egg proteins that are enzyme inhibitors, such as trypsin inhibitors. The underlying mechanisms of how different technologies mediate the egg protein digestibility have been discussed in detail. The proteolysis patterns and digestibility of the processed egg proteins are not always predictable and depends on the processing conditions. Empirical input is required to tailor the optimization of processing conditions for favorable effects on protein digestibility.

Effects of dielectric properties and microstructures on microwave-vacuum drying of mushroom (Agaricus bisporus) caps and stipes evaluated by non-destructive techniques

This research work aimed to investigate the effects of microstructures, dielectric property and temperature distributions on drying feature difference between the mushroom cap and stipe during the microwave-vacuum drying (MVD) process. Near-infrared hyperspectral imaging (NIR HSI) was employed to visualize distribution maps for moisture content (MC), dielectric constant ε' and dielectric loss factor ε'' of mushroom slices during the MVD process. Infrared (IR) thermal imaging was used to evaluate the temperature distribution of the mushroom slices. Results demonstrated higher MC, ε' and ε'' values in MVD mushroom stipes. Nevertheless, the centre area of the mushroom slice showed the highest temperature, while the MVD mushroom cap displayed a more porous structure. The effect of microstructure could encounter effects of dielectric properties and temperature to cause higher water evaporation in the MVD cap. This work highlights the novelty to combine different detection techniques to investigate the effects of microstructures, dielectric property and temperature distributions on drying patterns of mushroom slices.

Recent developments in vibrational spectral analyses for dynamically assessing and monitoring food dehydration processes

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.

Application and interpretation of deep learning methods for the geographical origin identification of Radix Glycyrrhizae using hyperspectral imaging

Radix Glycyrrhizae is used as a functional food and traditional medicine. The geographical origin of Radix Glycyrrhizae is a determinant factor influencing the chemical and physical properties as well as its medicinal and health effects. The visible/near-infrared (Vis/NIR) (376–1044 nm) and near-infrared (NIR) hyperspectral imaging (915–1699 nm) were used to identify the geographical origin of Radix Glycyrrhizae. Convolutional neural network (CNN) and recurrent neural network (RNN) models in deep learning methods were built using extracted spectra, with logistic regression (LR) and support vector machine (SVM) models as comparisons. For both spectral ranges, the deep learning methods, LR and SVM all exhibited good results. The classification accuracy was over 90% for the calibration, validation, and prediction sets by the LR, CNN, and RNN models. Slight differences in classification performances existed between the two spectral ranges. Further, interpretation of the CNN model was conducted to identify the important wavelengths, and the wavelengths with high contribution rates that affected the discriminant analysis were consistent with the spectral differences. Thus, the overall results illustrate that hyperspectral imaging with deep learning methods can be used to identify the geographical origin of Radix Glycyrrhizae, which provides a new basis for related research.

Hyperspectral imaging provides an effective way to identify the geographical origin of Radix Glycyrrhizae to assess its quality.

Effects of constant power microwave on the adsorption behaviour of myofibril protein to aldehyde flavour compounds

This study explored the influence of constant power microwave on the adsorption ability of myofibril protein from beef to typical aldehyde flavour compounds. Results showed that there was a significant increasing trend in surface hydrophobicity and reactive sulfhydryls content of myofibril protein with an increase in microwave power and treatment time. The adsorption ability of myofibril protein to aldehyde flavour compounds increased with increasing microwave power and time. The percentage of free aldehyde flavour compounds was related to the content of surface hydrophobicity, and reactive and total sulfhydryls of myofibril protein under microwave conditions, which could be fitted according to the multilevel relational (MLR) model. Furthermore, the reduced interface energy was probably the driving force for myofibril protein-flavour compounds adsorption behaviour at the gas-liquid interface.