Journal of Food Process Engineering最新文献

The study aimed to dehydrate beet microgreen foams using cast-tape drying and freeze-drying to obtain powder and characterize them in terms of physicochemical properties and betalain. Foam formulations were analyzed: F1 = 78.3% water + 13% microgreens + 6.5% Emustab + 2.2% pre-gelatinized starch; F2 = 78.3% water + 13% microgreens + 4.4% pre-gelatinized starch + 4.3% Emustab. The formulated foams were dried using cast-tape drying (CTD) (70°C and 2 mm spreading thickness) and freeze-dried (FD). The drying time for CTD was 12 min for CTDF1 and 24 min for CTDF2 (moisture of 0.1 g/g). The FD time was 14 h for FDF1 and 18 h for FDF2 (moisture of 0.02 g/g). The water activity and moisture content of the powder obtained by CTD were lower than that of the FD powder for both formulations, and the protein content in F2 (4%–4.6%) was lower than in F1 (5.2%–6.3%). The foam allows for the rapid drying of beet microgreens by CTD due to the high drying rate and moderate temperature. The CTDF2 powder has lower moisture and activity water, violet/red coloration, good flowability, and low cohesiveness compared to the other samples. Freeze-drying shows higher betalain retention (FDF1). Microgreens in powdered form constitute viable protein sources to be incorporated into plant-based products, while betalain allows using this powder as a natural dye. These potential applications demand further investigation, aiming at a potential introduction as a new product in the market.

Konjac glucomannan (KGm) has emerged as a promising candidate in the realm of sustainable packaging materials due to its biodegradability, biocompatibility, and unique chemical properties. Derived from the konjac plant tuber, KGm is primarily composed of glucose and mannose units linked by β-1,4 glycosidic bonds, which impart high molecular weight, acetylation levels, and functional characteristics such as viscosity, gel-forming ability, and water absorption capacity. In the food industry, KGm films serve as edible coatings on fruits and vegetables, extending shelf life by creating a protective barrier against moisture and oxygen. KGm-based films are used in controlled release formulations, wound healing dressings, and tissue engineering scaffolds. Various manufacturing techniques such as solvent casting, microfluidic spinning, and electrospinning are used to customize the mechanical properties and structure of KGm films for specific applications. Ongoing research aims to enhance water resistance and barrier properties through innovations such as composite formulations and cross-linking methods. Looking ahead, further developments in KGm-based edible films hold promise for addressing environmental concerns linked to traditional plastic packaging materials.

Persimmon is a soft fruit, which is why it is one of the horticultural products most prone to mechanical damage throughout the cold chain. Understanding the impact of this damage on the post-harvest quality of these fruits is extremely important to reduce losses that occur throughout the supply chain. This study used the finite element method (FEM) to predict the damage to persimmon during impact loading. The tensile and puncture tests were used to find mechanical properties, and the pendulum tests for three levels of impact. During simulation, persimmon was modeled as an elastic–plastic, and the problem was considered a non-linear explicit procedure. Two different force-time and initial velocity methods were used for simulation in Abaqus software. Results of the maximum von Mises stress, maximum contact force, deformation, bruise volume, and internal energy indicated that increasing the impact level in both methods resulted in a rise of stress, deformation, bruise volume, and absorbed energy. The average error in contact force in the force-time and initial velocity methods was 12% and 21%, respectively. Also, the average deformation error in the force-time and initial velocity methods was 10% and 52%, respectively. According to these results, the force-time method is more accurate, and the elastic–plastic model can properly represent the behavior of persimmon.

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.