Journal of Food Process Engineering最新文献

High sodium intake from processed foods has been linked to increased risks of hypertension and cardiovascular diseases, prompting the need for sodium reduction strategies in meat products. This study aims to investigate the influence of partially replacing salt (NaCl) with Salicornia herbacea L. in the formulation of meat chips on their yield, quality, and sensory characteristics. The main difference between control and experimental recipes lies in the substitution of part of the salt (NaCl) with S. herbacea L., known for its beneficial properties and lower sodium content. Beef, chicken breast, and horse meat were used for chip preparation. Control recipes contained 8% NaCl, whereas in experimental recipes, NaCl constituted 4%, and S. herbacea L. constituted 4%. The preparation process involved grinding the meat to a minced state, adding salt and spices, forming chips, a three-stage drying process, and subsequent cooling. The results indicated that the inclusion of S. herbacea L. reduces chip yield by 2%. Moisture, fat content, protein composition, and caloric content of the chips also slightly decreased in experimental recipes. Meanwhile, antioxidant activity and chip-shape stability increased. Experimental recipes also demonstrated improved sensory characteristics such as taste, aroma, and texture. Thus, despite a minor decrease in production yield the use of S. herbacea L. in meat chip formulations was justified. Simultaneously, alongside sodium reduction, there was an improvement in the product's antioxidant activity and sensory properties. The incorporation of S. herbacea L. makes meat chips more nutritious and appealing to health-conscious consumers.

Fruits and vegetable (F&V) account for a large proportion of the market output, and reducing mechanical damage can improve economic benefits. During harvesting and storage of F&V, visible mechanical damage and unseen bruises can result from external loads. However, there are relatively few studies on the micro-damage of F&V, and the micro-damage changes are reflected in the macro. Therefore, it is necessary to establish macroscopic, mesoscopic, and microscopic mechanical structure models. In this paper, the factors influencing the mechanics of F&V are analyzed, macroscopic, mesoscopic, and microscopic mechanical analysis methods of F&V are reviewed, multi-scale mechanical relationships are explored, and future research directions of multi-scale biomechanics of F&V are prospected. The results show that future research direction should mainly focus on the force analysis of microscopic single cell, as it is the basis of mechanical analysis of F&V.

This study comprehensively investigates the temperature dynamics, fluid flow patterns, and moisture distribution during solar drying of Stevia rebaudiana leaves. Drying experiments were conducted using an indirect mode solar dryer (ISD) and mixed-mode solar dryer (MSD), considering both natural convection mode (NCM) and forced convection mode (FCM). Results revealed that MSD dried the leaves 40.00%–44.44% faster than ISD. Additionally, the average effective moisture diffusivity was 26.73% higher in MSD under NCM, and 34.75%–36.67% higher under FCM compared to ISD. The average mass transfer coefficient in MSD was also significantly higher than in ISD (p < 0.05), ranging from 2.92 × 10⁻⁶ to 3.68 × 10⁻⁶ m/s, a 25.86%–37.31% increase. The experimental data were evaluated using nine thin-layer drying models, with the Page and Two-term exponential models emerging as the best fit based on Akaike increment criteria and Akaike weights. The total color change was significantly higher (p < 0.05) by 35.41% under NCM and 40.17%–76.10% under FCM in MSD compared to ISD, indicating substantial quality and microstructural alterations in stevia due to its interactions with high temperature airflow. The total phenolic content of leaves showed a significant (p < 0.05) increase, ranging from 63.65% to 71.99%, when dried using ISD compared to MSD. The 3D finite element modeling performed using COMSOL Multiphysics software showed strong agreement with the experimental data, offering valuable insights into stevia's drying kinetics and the airflow patterns inside the solar dryer. These observations strongly support the efficacy of the ISD for drying heat sensitive medicinal herb like stevia.

We investigated steady heat transfer in rice grains at various temperatures to evaluate the heat transfer properties of food solid–liquid dispersions and their particle size dependence. The two dispersion systems, comprising homogeneously dispersed and heterogeneously precipitated solutions with various volumetric solid–liquid fractions and diameters of rice grain particles, were prepared using media with different specific gravities. The thermal conductivity of both dispersion solutions depended on the solid–liquid fraction and particle diameter, and the effective interfacial area between the dispersion phase and the medium was suggested to contribute to thermal conductivity. That is, reducing the effective interfacial area was indicated to make heat transfer in the dispersion solution more efficient. In addition, the thermal conductivity of the dispersion phase was estimated using a model equation, and it was suggested that the thermal conductivity at the temperature above the gelatinization temperature might reflect the effect of water sorption by rice grains and gelatinization. The experimental and analytical methods used in this study could potentially provide useful information for simulations of thermal manipulation in the manufacturing and processing not only of rice grains but also other granular foods, especially food materials containing a large quantity of starch, such as beans.

This study explores the potential of fluorescence spectroscopy (FS), coupled with principal component analysis (PCA) and partial least square regression (PLSR), to detect meat adulteration rapidly and non-destructively in cooked minced beef. We aimed at evaluating FS as a simple and efficient tool for identifying cheaper meat species, that is chicken, used as adulterants in beef. Fluorescence spectra were collected at one fixed emission wavelength (410 nm) and three excitation wavelengths (290, 322, and 340 nm) from both pure and adulterated cooked meat samples. Adulteration levels ranging from 10% to 90% were assessed by mixing chicken meat with beef, followed by fluorescence analysis. The results indicated that the PCA model explained 100% of the variance, with 96% accounted for by the first principal component, showing clear discrimination between pure and adulterated samples. PLSR models demonstrated excellent predictive accuracy, with cross-validated coefficients of determination of 0.95, highlighting FS's capability in distinguishing between pure and adulterated meats even after cooking. The cross-validated grouping success rate was ~97%, reinforcing the reliability of the technique. This study represents the first investigation using FS to predict adulteration in cooked meat, providing a benchmark for future research. The findings suggest that FS, in combination with mathematical modeling, holds great promise as a rapid, cost-effective, and nondestructive method for detecting meat adulteration, with significant potential for practical application in food industry quality control.

This study has introduced a novel methodology for detecting brick powder (BP) adulteration in red chili powder (RCP; Variety: Bullet Lanka-5) by strengthening advanced digital image processing techniques. Specifically, this approach integrated color space histogram and texture features, subsequently refined through Z-score normalization and followed by the infinite latent feature selection (InLFS) method. By combining these innovative image-based techniques with machine learning (ML) algorithms, this research sets a standard for ensuring the safety and authenticity of RCP. The digital image-based dataset consisting of images of pure and adulterated RCP with BP at various concentrations, is used to extract the features for the evaluation of models. Three histograms (i.e., YCbCr, RGB, and Lab) and texture feature models (i.e., GLCM, GLDM, and GLRM) are extracted from each image. Subsequently, the InLFS model is employed to identify the most desirable features for the extracted histogram and texture features, which are further trained on the ML models to evaluate the existence and extent of BP adulteration in RCP. The regression model has given a higher coefficient of determination (R²) of 0.99 when using exponential Gaussian Process Regression (GPR) trained on Lab color space histogram features, with corresponding RMSE, MSE, and MAE values of 2.14, 12.21, and 1.08, respectively. Meanwhile, the subspace KNN classifier, with SF-C-Texture-Lab-hist, has achieved an accuracy of 99.31%. Therefore, the findings of this study underscore the potential applications of digital image-based feature extraction in combination with ML models to ensure the safety and authenticity of RCP.

Edible insects have gained increased attention as the important and sustainable source of nutrients for both human and animal consumption due to their rich content of protein, oil, fiber (as chitin), vitamins, and minerals. This study focuses on examining the effects of advanced pretreatments and oil extraction methods from prominent edible insect species commercially cultivated in Thailand, namely the house cricket (Acheta domesticus), black soldier fly larvae (Hermetia illucens), and silkworm (Bombxy mori). The raw insect samples underwent pretreatment using high pressure processing (HPP) at 200–600 MPa for 5 min or ultrasonication (UL) at 37 kHz for 5–15 min, followed by dehydration and extraction using supercritical carbon dioxide (SC-CO₂) or solvent extraction. The study revealed that HPP significantly reduced the initial microbial load of all edible insects by 6–8 log cycles, while UL showed a slight effect on microbial reduction. Additionally, pretreatments notably improved the oil extraction yield of most samples by disrupting the integrity of the cell membrane, facilitating the release of oils. The extracted edible insect oils were rich in unsaturated fatty acids, omega 3, 6, and 9, making them suitable for various applications such as cosmetics, food, and feed additives. Furthermore, the protein meals obtained as a residue after oil removal were identified as potential meat alternatives or replacements in food or feed formulations. This study provides valuable insights into the potential of edible insects as a sustainable source of oil and protein, highlighting the significance of pretreatments and extraction methods in maximizing their utility for various applications in the food, cosmetic, and feed industries.

Freezing pretreatment is one of the novel pretreatments for fruit and vegetable drying, and its treatment intensity has a direct impact on the effectiveness of color protection and drying promotion. However, there are major limitations on transformations of dynamic changes of and water status of material, which is crucial for judging processing intensity. Here a mathematical model was presented to characterize heat transfer in freezing pretreatment of carrot crisps. The model accounts for freezing phase change heat transfer. And a further analysis on the effect of freezing pretreatment on product quality was made according to experimental results. Results showed that the heat transfer process of freezing pretreatment is divided into four stages based on the temperature changes, namely fast cooling segment, phase transition segment, secondary cooling segment, constant temperature holding segment. In the phase transition segment, the presence of latent heat is the core element that the temperature of the material can be maintained constant. In the constant temperature holding segment, the effect of processing time on the material was significant. The optimal pre-freezing conditions for carrots was a temperature of −15°C for the duration of 45 min plus an additional 10 h, resulting in dried products with minimal color difference, maximum rehydration ratio, and optimal puffing degree.