Journal of Food Processing and Preservation最新文献

Introduction: Dragon fruit quality grading and maturity detection are crucial for ensuring market value and consumer satisfaction. The manual grading and maturity assessment of dragon fruit is a tedious, time-consuming task that often lacks consistency due to human subjectivity and environmental factors. Existing computer vision–based classification models rely on single deep learning architectures, which may not effectively capture the diverse features required for accurate quality assessment. Moreover, traditional machine learning classifiers struggle to generalize well when dealing with complex agricultural datasets containing variations in fruit texture, size, and lighting conditions.

Method: This paper presents a predictive classification model that integrates fused deep convolutional neural network (CNN) features with ensemble learning to achieve high-accuracy classification. The proposed model extracts deep features from multiple pretrained CNN architectures, including VGG16 and Inception-ResNet-v2, and fuses them to enhance feature representation. These fused deep features were then classified using an ensemble of machine learning algorithms, including random forest (RF), gradient boosting (GB), and AdaBoost (AB).

Findings: Experimental results on a benchmark dataset of dragon fruit images demonstrated that the proposed hybrid approach outperformed individual deep learning and machine learning models, achieving superior accuracy, precision, and recall in quality and maturity grade classification. RF achieved 99.99% accuracy in quality grading by classifying fresh versus defected fruits, while AB reached 99.69% accuracy in maturity detection, surpassing the performance of both RF and GB.

Conclusions: The model effectively distinguished different maturity levels and quality grades, offering a robust and automated solution for dragon fruit quality assessment. Its high accuracy and adaptability support real-world deployment in smart farming and processing units, including in automated sorting and grading systems. This enables real-time, consistent, and accurate fruit classification, thereby reducing labor, minimizing human error, and improving supply chain efficiency.

Conventional encapsulating materials like maltodextrin, gelatin, casein, and synthetic polymers face challenges such as instability in gastric conditions, high costs, and ethical concerns. As sustainable alternatives, starch-based polymers and protein isolates offer superior protection, biocompatibility, and eco-friendliness. This study is aimed at supporting Sustainable Development Goals by utilizing jackfruit seed starch (JSS) and protein isolate (JSPI) for the microencapsulation of Lactiplantibacillus plantarum. The encapsulation efficiency ranged from 82.87% to 96%, also enhancing cell viability to 10¹¹–10⁹ CFU/g. SEM analysis confirmed the formation of microcapsules (7–30 μm) without free cells. Thermal analysis showed endothermic peak temperatures of 78.4°C–87.5°C, indicating resilience to food processing conditions. Microencapsulation with JSS and JSPI improved probiotic survival up to 8 log CFU/g for 28 days and 7 log CFU/g in gastrointestinal conditions. These findings suggest that JSS and JSPI are promising, sustainable materials for probiotic microencapsulation in food applications.

Active plant extracts such as Heracleum persicum can be incorporated into food products and pharmaceutical formulations using advanced techniques such as nanoemulsion and nanoencapsulation. This study is aimed at determining the size and morphology of nanoemulsions (NEHP) and nanoencapsulations (NCHP) of H. persicum hydroethanolic extract (HP) and evaluating their antibacterial and anticancer properties. Additionally, the effects of these formulations on the qualitative properties of traditional cheese during refrigerated storage were assessed. Results from dynamic light scattering (DLS) and transmission electron microscopy (TEM) revealed consistent particle characteristics. FTIR analysis indicated the presence of various functional groups in the biomolecules surrounding the nanoparticles. After 48 h, NEHP and HP (500 mg/mL) reduced the viability of cancer and normal cells by approximately 80% and 75%, respectively. The minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) values ranged from 7.8 to 250 mg/mL and 15.6 to 500 mg/mL, respectively. At a 2× MIC concentration, NCHP exhibited the highest inhibition of biofilm formation by Listeria monocytogenes ATCC 7644 (LSTD) (72.5%) and a food isolate (LIFF) (70.3%). Incorporation of 2% NCHP into traditional cheese kept the total bacterial count (TBC) below 1.5 log CFU/g during storage. Furthermore, NCHP-coated samples exhibited the lowest levels of LSTD, LIFF, molds and yeasts, and coliforms. During storage, samples treated with 2% HP and 1% NEHP showed the lowest pH and titratable acidity (TA), respectively. The HP coating also improved the overall sensory acceptability of the cheese samples.

The quick spoilage of fish, particularly in developing countries, results in significant postharvest losses, underscoring the need for effective preservation strategies. This study was aimed at analyzing the drying kinetics and mass transfer characteristics of African catfish (Clarias gariepinus) using different drying methods. The catfish fillets were dried at temperatures of 60°C, 75°C, and 90°C, as well as with microwave power levels of 540, 700, and 800 W. The experimental data were evaluated using various thin-layer drying models to identify the best fit for predicting drying behavior. Results showed that hot air drying (HAD) followed a single-phase falling rate period, whereas microwave drying (MD) demonstrated three distinct phases. Higher temperatures and increased microwave power significantly boosted the drying rate, reducing drying time. Furthermore, MD displayed a higher effective moisture diffusivity compared to HAD, indicating faster moisture removal. The energy requirement for HAD was greater (18.74 kJ/mol) than for MD (4.84 W/g). Among the tested models, the modified Henderson and Pabis and Midilli models best described the drying of oven-dried catfish, while the Henderson and Pabis, Page, and Midilli models were most accurate for microwave-dried samples. This research provides valuable insights into how different drying methods influence the drying behavior and moisture transfer of catfish fillets.

Moringa oleifera, a medicinal tree native to Africa and Asia, has been utilized for centuries in traditional medicine to help treat a variety of diseases. This paper examines the optimization of the extraction process, characterization, and antioxidant activities of Moringa oleifera seeds. Using central composite design and response surface methodology, the study assessed temperature (25°C–60°C), extraction time (24–72 h), ethanol concentration (40%–80%), and yields (28%–39.4%). Optimal conditions were 42.5°C, 40% ethanol, and 35.5 h, yielding 35.2%. Additionally, physicochemical analysis revealed an acid value of 1.98 mg KOH/g and an iodine value of 83.02 mg/g. These values indicate low free fatty acid content and a high degree of unsaturation. The extracts also exhibited significant antioxidant activities compared to ascorbic acid, with an IC₅₀ of 15.80 mg/mL for the extract and 12.60 mg/mL for ascorbic acid, demonstrating strong reducing power. Fourier transform infrared spectroscopy identified key phytochemical functional groups, such as phenols, flavonoids, steroids, terpenoids, and polyphenols (tannins), all of which are linked to antioxidant activity. Gas chromatography–mass spectrometry analysis identified and quantified various bioactive compounds, including 9,12,15-octadecatrienoic acid, ethyl ester; n-hexadecanoic acid; hexadecanoic acid, ethyl ester; 2-hexadecen-1-ol, 3,7,11,15-tetramethyl-, acetate, [R-[R∗,R∗-(E)]]; 9,12,15-octadecatrienoic acid, ethyl ester, (Z,Z,Z); octadecanoic acid, ethyl ester; and oleic acid 3-(octadecyloxy) propyl ester. Additionally, the p value < 0.0001 indicates high significance (0.01% noise chance), with an adjusted R² at 0.9992 and predicted R² at 0.9986. These compounds all contribute to the antioxidant capacity. These findings suggest that Moringa oleifera seed extracts are potent natural antioxidants, indicating their potential for developing functional health products or natural antioxidant formulations.

This study is aimed at the comparison of the pectin-based edible films (2%), resulting from watermelon (WMPP), banana (BPP), and orange peel (OPP), in the shelf life enhancement of beef thigh meat at 4^°C ± 1^°C during 9 days of storage period. After extracting pectin from the watermelon, banana, and orange peel, FTIR analysis and scanning electron microscope (SEM) images were used to identify the obtained pectin. Tensile strength, Young’s modulus, and elongation at break of OPP (0.56, 19.67 MPa, and 2.99%), BPP (0.56, 14.19 MPa, and 4.01%), and WMPP (0.45, 17.41 MPa, and 4.50%) films were evaluated. Additionally, the highest and lowest thickness belonged to the BPP (0.21 mm) and OPP (0.04 mm) films, respectively. Total viable count (TVC) of the wrapped beef thigh meat by WMPP, BPP, and OPP films was 6.86, 6.59, and 6.03 log CFU/g, respectively, while the control group reached 8.01 log CFU/g at the end of the storage period. The populations of psychrotrophic bacteria, Enterobacteriaceae, molds, and yeasts in the OPP treatment were the lowest (6.18, 5, and 3 log CFU/g) and BPP (6.88, 6.32, and 4.44 log CFU/g) and WMPP (7.12, 6.94, and 4.96 log CFU/g) groups were in the next ranks, respectively, on the ninth day. The lowest pH and total volatile basic nitrogen (TVB-N) content of the samples was related to the OPP (5.81, 16.3 mg N/100 g) followed by BPP (5.98, 21.5 mg N/100 g) and WMPP (6.11, 22.3 mg N/100 g) treatments at the end of the storage period. The coated meat with OPP film registered acceptable sensory (odor, color, and overall acceptability) scores (≥ 3) during the entire storage period compared to the other treatments. It is concluded that OPP film, along with its more suitable mechanical properties, could enhance the shelf life of beef thigh meat compared to the BPP and WMPP treatments.

Research Background: Enrichment of fermented foods with γ-aminobutyric acid (GABA) is one of the recent strategies to obtain novel functional foods, and this fermentation process is led by GABA producer suitable lactic acid bacteria strains. Adaptation of high GABA-producing LAB strains to the fermentation environments is key, and boza, a cereal-based fermented beverage, might be a suitable environment to obtain physiologically relevant levels of GABA.

Experimental Approach: The objective of this study is to investigate the effect of monosodium glutamate (MSG)–induced in situ production of GABA on physicochemical, microbiological, viscoelastic, and sensory characteristics of boza at different fermentation (0, 24, 48, and 72 h) and storage (1, 3, 6, and 9 days) times, utilizing GABA-producing sourdough isolates: Lactiplantibacillus plantarum SD30 and Levilactobacillus brevis SD48 strains.

Results and Conclusions: Boza samples supplemented with MSG showed higher counts of lactic acid bacteria. MSG addition significantly induced GABA production in boza; moreover, the addition of MSG to boza, combined with fermentation by L. plantarum SD30, yielded the maximum amount of GABA, reaching 0.13 mg/mL. The MSG-induced production of GABA in boza significantly increased both elastic (G^′) and viscous (G^″) properties. Glucose and fructose amounts were lower in samples added with MSG, suggesting that MSG addition might have utilized glucose and fructose by the strains. Boza samples added with MSG received higher scores, which could be attributed to the impact of MSG on taste perception in boza.

Novelty and Scientific Contribution: This study highlights the potential of MSG-induced in situ GABA production by two LAB strains as starter cultures for the production of boza with improved viscoelastic and sensory properties.

Shallots are rich in bioactive compounds and antioxidants. They are, however, susceptible to quality loss during food pretreatments, thereby making careful selection of their pretreatment technique very imperative. This study investigated the influence of shallot powder pretreatment methods (blanching, soaking, and no treatment) on the functional properties of shallot–wheat flour blends and attributes of their biscuits. Pretreated and dried shallot powder was incorporated at 6 g per 100 g of wheat flour in the biscuit recipe. A control sample was prepared from 100% wheat flour. Functional properties (water absorption capacity [WAC], oil absorption capacity [OAC], swelling capacity [SC], and bulk density [BD]) of the flour blends were evaluated. Chemical and physicochemical characteristics of biscuits from various blends were determined using standard methods. A nine-point hedonic scale was used to evaluate the sensory properties of the biscuits using 50 panelists. Data were analyzed using ANOVA at α_0.05. Blanched shallot–wheat flour sample demonstrated the highest WAC (79.00%) and OAC (90.67%), indicating enhanced hydration and emulsification potential. Results of the proximate analysis showed that biscuits containing shallot powder, particularly those prepared with blanched pretreatment, exhibited increased levels of protein (15.67%), fat (10.33%), and ash (4.00%) compared to the control. Mineral analysis results revealed elevated concentrations of iron (10.60 mg/100 g), potassium (340.78 mg/100 g), and phosphorus (425.98 mg/100 g) in pretreated shallot-supplemented biscuits. Vitamins A, C, and E were also significantly improved, with the highest values in the samples supplemented with shallot pretreated by blanching and soaking. The highest antioxidant potentials of the biscuits, as measured by FRAP and total antioxidant capacity, were found in pretreated shallot-supplemented samples. Samples of biscuits supplemented with shallots were within acceptable ranges for taste, aroma, and crispiness, though the control biscuit received the highest overall sensory score. The findings indicate that shallot powder, particularly when blanched prior to application, can serve as a functional ingredient to improve the nutritional quality of baked products without adversely affecting consumer acceptability.

Aiming at the problems of poor imaging effect and low impurity classification accuracy of existing paddy quality detection systems, we propose a rapid paddy impurity detection system based on machine vision. The system consists of an image acquisition subsystem and an impurity classification subsystem, which aim to accurately evaluate the quality of paddy grains. The image acquisition subsystem is composed of a multi-degree-of-freedom manipulator, a flexible vibrating disc, an industrial camera, a light source, and an embedded computing platform. The multisensor fusion technology is used to realize the two-dimensional imaging of the target paddy. Moreover, the impurity classification subsystem innovatively adopts the feature extraction method based on convolutional neural network to realize the fast and accurate classification of paddy impurity images. To balance the classification accuracy and computational complexity, we use GhostNet as the backbone network for efficient high-dimensional semantic feature extraction from paddy images. Furthermore, the visual attention mechanism and multiscale feature aggregation strategy are introduced to enhance the extracted features and improve the accuracy of impurity classification. The image acquisition subsystem collects 256 raw images with a resolution of 5120 × 5120. After image preprocessing, a total of 5000 paddy image blocks are obtained, and each block has different resolutions. These image blocks include lesion paddy images, moldy paddy images, sprout paddy images, immature paddy images, and normal paddy images. The trained impurity classification model achieves 83.64% precision, 83.60% recall, 83.54% F1 score, and 93.44% accuracy. These results not only show the efficiency and accuracy of the system in practical applications but also provide important reference value for future research and application in a wider range of agricultural detection fields.

Food allergies are one of the globally recognized public health concerns due to developments in food production and processing technology. It is difficult to prevent the intake of food allergens due to the complex nature of food products. Food researchers are striving to find innovative techniques to remove allergy-causing agents and produce nonallergenic food products. The prime objective of this study was to assemble the latest information to produce hypoallergenic food with the help of emerging technologies including irradiation, high-pressure processing (HPP), pulsed ultraviolet light (PUL), pulsed electric fields (PEFs), cold plasma, ultrasound, and their combination. Classification of food allergy, epitope description, identification method, and clinical manifestations are also presented. Studies showed that processing technologies reduce allergenicity while retaining the sensory and nutritional integrity of food products. The effectiveness of each method appears to be highly dependent on the specific food matrix, the type of allergen, and the processing parameters used. Among the technologies discussed, cold plasma, HPP, and ultrasound demonstrated the most significant reduction in food allergenicity, while irradiation and PEF were less effective. Notably, combining multiple nonthermal technologies emerged as the most promising strategy to develop hypoallergenic foods with minimal compromise to quality. We anticipate that these findings will provide a thorough understanding of food allergy mechanisms in reducing food immunoreactivity and an approach for better industrial application.