Journal of Food Process Engineering最新文献

Polysaccharides, as important bioactive components in medicinal and functional food materials, are key indicators for quality evaluation. Conventional analytical methods for polysaccharides quantification often require laborious sample preparation and may cause irreversible damage to samples, which limits their suitability for routine quality control. To overcome these limitations, we developed a rapid and non-destructive detection approach by integrating hyperspectral imaging with an iteratively retained information variables-artificial neural network (IRIV-ANN) model. Spectral data (400–1000 nm) were processed using the IRIV algorithm, which classified variables into four categories-strong information, weak information, no information, and interference. The optimal subset was then used to construct an ANN model, and its performance was compared with models based on shuffled frog leaping algorithm (SFLA), successive projections algorithm (SPA), one-dimension convolutional neural network (1D-CNN), full-spectrum ANN, and multiple linear regression (MLR). The IRIV-ANN model successfully eliminated redundant variables, reduced model complexity, and improved predictive performance, achieving a coefficient of determination (R²) of 0.9301 and a root mean square error (RMSE) of 0.7348 for the prediction set. The characteristic wavelengths selected were closely associated with vibrational changes in O-H and C-H functional groups, providing chemical interpretability of the spectral features. This method provides an efficient and reliable analytical tool for rapid quantification of polysaccharides and has considerable potential for broader application in the quality control of functional foods, traditional medicines, and other plant-derived materials.

The fundamentals of value engineering are presented in this article and can be applied to any small-scale refrigeration water cooler manufacturing industry. Value engineering is a clever technical engineering approach that is also a cost-effective way to get the required product function at the lowest possible cost. A case study of a refrigeration water cooling system is conducted, where the value engineering method is used to modify the component design and material. According to the case study, the usage of different hardware components, expensive materials, excessive material size, etc., raises the cost needlessly. The compressor, condenser, condenser fan, evaporator, refrigeration control system, outer body, taps, drain tray, and other components of the water cooler have been chosen, and value engineering is applied to these components to cut costs. The functional coefficient, cost coefficient, and value coefficient are calculated to analyze the correlation between various functions and their associated cost. Through the use of value engineering techniques in refrigeration water cooling systems, cost savings are accomplished.

This study investigates the impact of production systems, including: (1) open production system (OP) and (2) vertical farm (VF) on lettuce quality. The study aligns with SDG 2 (Zero Hunger) and SDG 12 (Responsible Consumption and Production). Germination experiments were carried out inside a climate-controlled farm for 4 weeks with two varieties of lettuces: Ruby Sky Lettuce (LR) and Patrona Lettuce (LO). Then, seedlings were planted in two experimental settings: an open production system (OP) with a dripping irrigation system and a vertical farm treatment (VF) with an aero hydroponic irrigation system arrangement with a 200 L nutrient tank. A comparison test was carried out between Patrona Lettuce (LO) and Ruby Sky Lettuce (LR), which were harvested in two different production systems. The two lettuce varieties, Ruby Lettuce (RL) and Patrona Lettuce (PL), were sampled for microbiological analysis and counts using the following quality indicators: aerobic mesophilic microorganisms, coliforms, fungi, and yeast to compare the production systems. Microbial analysis revealed significantly lower counts of aerobic mesophilic microorganisms, coliforms, and fungi in vertical lettuce. For Ruby Sky, outdoor production resulted in 29-, 32-, and 37-times higher counts, respectively. Patrona exhibited similar trends. These findings suggest that vertical farming enhances food safety by minimizing microbial contamination. VF can empower small-scale farmers, improve agricultural productivity, and enhance food security, particularly in regions facing limited land and water resources, thus reaching towards SDG 2 and SDG 12.

This study examined the drying kinetics and quality of desiccated coconut through hot-air drying at varying temperatures of 80°C, 85°C, and 90°C, reducing moisture content from 48% ± 2% (w.b.) to 2% ± 1.1% (w.b.). Several physicochemical parameters were assessed, including color, water activity, energy consumption, oil characteristics, surface morphology, functional groups, and fatty acid profiles. The findings revealed that drying temperature significantly affected the color attributes of the coconut, primarily driven by the Maillard reaction and sugar concentration, with desiccated coconut at 85°C demonstrating optimal color properties. Water activity consistently decreased with increasing drying temperature. Higher drying temperatures resulted in a notable reduction of free fatty acids (FFAs); however, the peroxide value of the extracted oil displayed an inverse correlation. Microstructural observations indicated that extended drying resulted in pore formation due to moisture evaporation, with 90°C exhibiting an oily surface indicative of oil cell breakdown absent at 85°C. Additionally, lauric acid content increased with drying temperature. FTIR analysis revealed distinct O–H stretching vibrations, alongside C–H and C═O stretching bonds, confirming the presence of carbohydrates and ester groups in coconut fat. Thus, optimizing the drying process at 85°C is recommended for improving the quality of desiccated coconut, suitable for industrial applications.

Dough toughness and extensibility are key rheological properties directly linked to the quality of dough-based products. Thus, this research employed a custom-built device to inflate dough sheets into bubbles, with a 3D imaging system recording real-time point cloud data of these formations. The investigation specifically targeted point cloud imagery capturing both the frame displaying maximum spatial deformation height in dough bubbles and its subsequent frame. Four novel computational methods were developed to quantify four distinct deformation characteristics from the selected two-frame bubble point cloud images. These parameters were subsequently fed into three machine learning architectures for autonomous prediction of dough toughness and extensibility. Experimental findings revealed optimal detection accuracy when utilizing deformation feature n's immediate recovery index (E_n) with the ELM algorithm, attaining R_p coefficients of 0.882 and0.940 for extensibility and toughness assessments, respectively.

This study aims to develop a novel oil hydrogenation process using a solid polymer electrolyte (SPE) electrochemical reactor, focusing on optimizing the preparation of platinum nanowire (Pt-NWs) catalysts and their application in hydrogenation. By controlling the concentration of the reducing agent (a formic acid-to-water ratio of 7:600) and maintaining the reaction temperature at 20°C, a high-performance Pt-NWs/C catalyst was synthesized. Since the <111> crystal plane is considered the most active in the Pt catalyst, characterization showed that the Pt-NWs/C exhibited sharper x-ray diffraction peaks in that direction compared to commercial Pt/C, along with a more hydrophobic catalytic layer (contact angle of 135° ± 0.3°). In addition, the Pt-NWs catalyst also demonstrates superior performance in electrochemical stability (a 29.31% decrease). The catalyst was applied in an SPE hydrogenation reactor, and its performance in soybean oil hydrogenation was systematically evaluated. The results show that the hydrogenated oil containing Pt-NWs/C has good selectivity, while transfatty acid (TFA) content was about 13% lower than with commercial Pt/C. Electronic nose analysis confirmed that the hydrogenated oil retained favorable flavor characteristics. Polarized light microscopy showed that oil produced by Pt-NWs/C had a finer (approximately 20 nm) and more uniform crystal structure. The Pt-NWs/C catalyst exhibited excellent catalytic activity (ECSA value of 27.40 m² g⁻¹) and selectivity by the SPE reactor, offering a promising technological pathway for producing healthy hydrogenated oil with low TFA content.

In this study, carvacrol (CA)/thymol (TH) nanoemulsions (CT NEs) were first prepared by the ultrasonic emulsification method, and then the effects of various nanoemulsion concentrations on the physicochemical properties and biological activities of chitosan/pullulan (CS/PU) nanocomposite films were systematically evaluated. The CT NEs exhibited good stability with a high encapsulation efficiency of 90.29% ± 0.95%, and they were well integrated in the CS/PU matrix as confirmed by the microstructure characterization. The performances of the nanocomposite films were significantly enhanced by CT NEs, including the improvements of mechanical properties and barrier properties. The CS/PU-CT films exerted notable antioxidant and antibacterial activities. In the end, the CS/PU-3CT film (with 3.0% w/v CA and TH), with the best antioxidant and antibacterial performance, was applied to the preservation of pork, and its shelf life was extended for 10 days compared to the CK group. The film loaded with 3CT NEs exhibits outstanding performance and offers significant prospects for use in food packaging.

Engineering oxidative and structural stability in oil-enriched food systems remains a primary focus in food process engineering, particularly in polyunsaturated fatty acid (PUFA)-enriched food systems. The oxygen-vacancy-enriched cerium oxide nanoparticles (CeO₂ NPs) were synthesized by a controlled synthesis route optimizing the surface defect chemistry and antioxidant capability in the present study. Structural characteristics, including Ce³⁺/Ce⁴⁺ ratio and oxygen vacancy concentration, were established by XRD, XPS, DLS, and UV–Vis methods. Prepared nanoparticles were incorporated into edible oils (rice bran and sunflower), and storage challenges in a high-oil emulsion-based mayonnaise were performed in an effort to explore designed nanoparticles' function in stabilizing Pickering-type food systems. Oxidative stability was ascertained by peroxide and anisidine value, and characterization of emulsion by textural, interfacial, and sensory tests. Addition of the CeO₂ NPs into the edible oils significantly improved oxidative stability, as evidenced by lower peroxide and p-anisidine values after prolonged storage. The emulsions at final stage also showed improved interfacial stability, greater texture profile, and higher sensory acceptance during storage at low temperature, with retained resistance against oxidative as well as structural deterioration. Most importantly, traditional workflows on production of mayonnaise were perfectly compatible with the designed nano-process engineering methodology, involving no fundamental changes in formulations. These findings lay the foundation for oxygen-vacancy-engineered CeO₂ NPs as multifunctional process additives in the creation of next-generation emulsions with extended shelf life, improved functional efficacy, and clean label characterization. The research advances progress in the field of nano-enabled food process engineering and systematic characterization of structure–function–process relationships.

Accurate detection of hulling quality-efficiency is critical for optimizing buckwheat processing and product quality. Current reliance on manual visual inspection is inefficient and impedes industrial progress. To address this issue, an online intelligent detection system is proposed based on an improved YOLOv8 algorithm. The model incorporates three key modifications: (1) a Dual Attention mechanism within the C2f module; (2) the WIoUv3 loss function replacing CIoU; and (3) an expansion to four detection heads. This refined framework enables real-time detection of buckwheat hulling efficiency. The system consists of four core components: an image-based detection module, a 6QB-150 buckwheat huller, control actuators, and auxiliary subsystems. An image acquisition device captures real-time samples, and the improved model accurately distinguishes three hulling statuses: hulled kernels, broken kernels, and unhulled kernels. Detection results are transmitted to a host computer, which interfaces with a PLC to regulate a three-phase asynchronous motor, enabling adaptive control of grinding disc speed and equipment operation. Ablation experiments demonstrated substantial performance improvements over the baseline, with increases of 7.7% in precision, 8.1% in recall, 5.9% in mAP@50, and 4.2% in mAP@50–95. Comparative trials confirmed the model's superiority over YOLOv5, YOLOv6, YOLOv8n, and YOLOv10n, with negligible computational increase. In practical experiment, model-detected rates for broken, hulled, and unhulled kernels deviated by merely +0.13%, −0.71%, and +0.53%, respectively, from manual counts, attesting to its reliability. The deployment of this system significantly enhances operational efficiency, offering an effective solution for automated quality control in buckwheat processing and contributing to agricultural modernization.

This study established an optimized CTAB-based DNA extraction method for edible oils, which enables stable and reliable DNA recovery from commercially available edible oils for authenticity identification and adulteration detection. Real-time PCR was used to assess DNA precipitation time and organic solvent extraction, revealing that longer precipitation increased inhibitors, hindering PCR amplification, while organic solvents enhanced efficiency. The method was applied to detect adulteration in commercially available soybean and olive oils. A standard curve based on real-time PCR Ct values demonstrated the ability to detect as low as 10% soybean oil in olive oil, with recovery rates of 92% and 80% for samples spiked with 70% and 30% soybean oil, respectively. The coefficients of variation (CV) were 11% and 14%, within acceptable ranges. This reliable method provides a valuable tool for edible oil authentication and adulteration detection.