Journal of Food Process Engineering最新文献

Breaks or cracks in eggshells offer substantial food safety issues. Bacteria and viruses, in particular, are more likely to enter the egg through breaks and cracks, increasing the risk of food poisoning. Furthermore, deformations in the shell may compromise the integrity of the protective shell, exposing the egg to more external variables and causing it to lose freshness and decay faster. To reduce such hazards, this research created an innovative crack detection system based on an autoencoder (AE) that uses acoustic signals from eggshells. A system that creates an acoustic effect by hitting the eggshell without damaging it was designed, and these effects were recorded through a microphone. Acoustic signal data of size 1 × 1000 was fed into k nearest neighbor (kNN), decision tree (DT), and support vector machine (SVM) classifiers. AE was employed to reduce data size in order to accommodate the raw data's unique features. This AE model, which reduces data size, was used with many classifiers and was able to accurately distinguish between intact and cracked eggs. The built AE-based classifier model completed the classification procedure with 100% accuracy, including microcracks that are invisible to the naked eye.

In view of the low bract removal and high corn ear damage in the operation of the current peeling device, this work aimed to accurately measure the coefficients of friction (COFs) involved between peeling rollers and corn ears during the corn peeling. Consequently, the movement state of corn ear in a peeling device and the friction behavior involved were analyzed, and the mechanical model was established. Friction tests were conducted by using the modified tilting table, the modified direct shear apparatus, and the self-built rolling friction apparatus. The value range and change rule of the COFs between corn ears and peeling rollers were obtained. Linear regression models were described for the COFs depending on moisture content. The results show that the coefficient of static friction (COSF) was 0.391–1.396, the coefficient of sliding friction (CODF) was 0.398–1.318, and the coefficient of rolling friction (CORF) was 0.119–0.377. All COFs were positively correlated with moisture content. Besides, the COFs of two rubber rollers were significantly larger than that of the steel roller. Among the two rubber rollers, the COFs were higher between the fish scale rubber roller and bare corn ears and were lower between the fish scale rubber roller and corn ears with bracts. This meant that the fish scale rubber roller was more likely to cause seed damage under the same conditions. Knowledge concerning these coefficients is believed to provide data support for the improvement and optimization of corn peeling devices.

Kadamb (Neolamarckia cadamba) is an underutilized fruit which has many nutritional and medicinal properties. The literature availability on utilization of kadamb as food is scarce. The present work was carried out to find the effect of vacuum impregnation during osmotic dehydration on the quality of kadamb fruit (Neolamarckia cadamba) candy (KC). The vacuum impregnation at 100 mbar for 15 min, brix value of hypertonic solution at 60°, 65°, 70°, and 75°, and time of osmotic dehydration 24, 36, 48, and 72 h were taken as variables in the process. Mass transfer parameters like water loss, solute gain, and weight reduction for all samples were calculated. The treatment with 75° Brix, 48 h, 100 mbar vacuum for 15 min got best results with more water loss (67.48% ± 1.11%), solute gain (19.63% ± 0.32%), and less weight reduction (40.51% ± 0.39%), respectively. No microbial load was found in the developed candy. Infrared (IR) spectrum, texture profile analysis, and field emission scanning electron microscopy tests revealed the availability of compounds, textural and microstructure of KC, respectively. The candy prepared from 75° Brix, 48 h, 100 mbar vacuum for 15 min has the highest organoleptic scores. The prepared candy cubes were packed into low-density polyethylene (LDPE) pouches and stored under ambient conditions, and the quality changes during storage were studied.

Ensuring efficient grading of guavas is crucial for timely postharvest storage and maximizing profits. Currently, the subjective nature of manual grading underscores the need for more sophisticated methodologies. However, employing machine vision for intelligent grading faces hurdles due to the diverse characteristics of guavas and the high development costs. This research targets the limitations in the guava grading process and introduces an intelligent system to overcome them. The system's structure and operational procedures were outlined, establishing diverse standards encompassing guava color, shape, size, and integrity. Image capture and preprocessing of guavas are completed. Employing the RGB model, the study performed color feature extraction and guava recognition, alongside diameter and integrity assessment through edge detection. Following a thorough analysis of various models, ResNet50 emerged as the preferred choice for guava image evaluation and depth recognition. Subsequently, an intelligent guava grading system was developed using Microsoft Visual Studio 2017. Experimental results demonstrated outstanding grading accuracy of 98.05%, with grading speed averaging 5.47 times faster than manual methods. Compared to traditional manual grading techniques, the system excelled in work efficiency, speed, reliability, and robustness.

Using variable temperature and relative humidity of natural air based on local climatic conditions for natural drying aeration of grain is an energy-saving and efficient method. The study of heat and moisture transfer within grain piles during natural air and low-temperature air drying aeration of bulk corn in low-humidity areas, which can provide theoretical support for selecting efficient and low-consumption grain drying processes and practical applications. In this study, the mathematical model of the coupled heat and moisture transfer dynamics in the dry silo was verified using experimental datum of grain storage drying aeration experiment, and the relative error was less than 5% between the simulated and the experimental datum. Based on this validated model, the temperature and moisture content variations of in-silo bulk corn drying were simulated by computational fluid dynamics (CFD) numerical simulation techniques. The simulations included continuous drying aeration with daily average, hourly average temperature and relative humidity of the local natural air, and low-temperature air drying aeration with heated up to 3°C over the ambient temperature, as well as intermittent drying aeration. Drying effectiveness and economic efficiency were also analyzed and evaluated. The costs for continuous drying aeration with hourly average of natural air and low-temperature, intermittent drying aeration with hourly average of natural air are 0.032, 0.042, and 0.016 CNY/kg, respectively. Compared to traditional high-temperature hot air drying, the costs of these methods were reduced by 0.048, 0.038, and 0.064 CNY/kg, respectively.

Turmeric is a medicinal herb that can be used in a wide range of applications, such as food ingredients, cosmetics, and traditional medicine. The active ingredients found in turmeric are curcumin (CUR), desmethoxycurcumin (DMC), and bisdesmethoxycurcumin (BMDC). The aim of this research was to precipitate the active ingredients from a turmeric extract using the gas anti-solvent process with carbon dioxide as the anti-solvent. The effects of solvent type (ethanol, methanol, and acetonitrile), precipitation temperature (25°C–45°C), and CO₂ flow rate (4–12 mL/min) on the amount of precipitates were investigated using the Box–Behnken design of experiments. The precipitates were analyzed for curcuminoids and CUR content using HPLC and were tested for antioxidant activity. It was found that solvent type and temperature were significant variables at a 5% significance level on the amount of precipitates. Using a mixture of ethanol and methanol (77.5% v/v ethanol) with a polarity index of 4.48 as the solvent, a precipitation temperature of 25.40°C, and a CO₂ flow rate of 7.56 mL/min was found to be the optimal conditions for achieving the highest amount of precipitates. At the optimal conditions, the amounts of curcuminoids and CUR precipitates were found to be 27.33 ± 0.23 and 13.30 ± 0.12 mg/5 mL of extracted solution, respectively. In the antioxidant studies, the Trolox equivalents found in the products at the optimal conditions using DPPH and ABTS assays were 38.19 ± 0.17 and 65.96 ± 2.36 mg/5 mL of extracted solution, respectively. The total phenolic content was found to be 30.84 ± 1.80 mg/5 mL of extracted solution.

The research aimed to study how different drying methods (spray and freeze drying) affect the release kinetics of microencapsulated astaxanthin in various environmental conditions. Shrimp shell extract containing astaxanthin was encapsulated using different wall components (maltodextrin with different dextrose equivalents and modified starch) via a simplex lattice mixture design. The encapsulated extract was then subjected to storage at different temperatures (25°C ± 2°C and 2°C ± 4°C) and humidity conditions (52% ± 2% and 75% ± 2%), as well as exposure to UV light (four 15 W lamps, 254 nm, for 10 h). The release kinetics of astaxanthin were analyzed using various models (page, Newton Korsmeyer–Peppas model, Modified Henderson and Pabis, Diffusion approach, and Two-term exponential). The evaluation results of correlation coefficient (R²), root mean square deviation (RMSE), and mean absolute percentage error (MAPE) values of different models showed that the astaxanthin degradation followed a two-term exponential kinetics in both types of microcapsules. Astaxanthin degradation increased with higher temperatures, humidity, and UV light exposure. However, microcapsules with equal wall compound ratios exhibited better preservation of astaxanthin. The study also emphasized the significance of optimizing storage conditions and wall materials for microencapsulated astaxanthin, as well as the utility of the two-term exponential model in enhancing stability and shelf life.