Journal of Food Measurement and Characterization最新文献

Black rice, referred as “forbidden rice,” is a rich source of essential micronutrients and bioactive compounds known for its distinctive color, aroma, and superior health benefits compared to conventional varieties. This review provides a comprehensive exploration of the genetic and biochemical pathways of its unique traits. We delve into the anthocyanin biosynthesis pathway, responsible for the characteristic pigmentation, and the role of key genes like Kala4, whose promoter rearrangement drives this trait, a significant evolutionary development of this cultivar. The synthesis of the aromatic compound 2-acetyl-1-pyrroline (2-AP) is also detailed. Beyond genetics, the review details the rich profile of bioactive compounds, including flavonoids, phenolics, and γ-oryzanol, which contribute to potent antioxidant, anti-inflammatory, and anti-carcinogenic properties. The novelty of this review lies in its integrated synthesis of the molecular genetics underlying pigmentation and aroma with the demonstrated health-promoting chemical properties. The significant potential of black rice as a functional food and natural alternative to synthetic additives is often overlooked, despite its promise for enhancing global food security and public health.

Graphical Abstract

3D food printing offers opportunities to design customized, plant-based snacks, but little is known about their oral processing behavior and sensory perception. This study examined the effects of formulation and frying methods on the dynamic texture perception of 3D-printed soy-based snacks. Four formulations varying in tofu, soy yogurt, and starch content were printed and fried using air- and deep-fat methods. Physicochemical properties (moisture, oil content, hardness), oral processing parameters (bolus formation, particle size, chewing/swallowing behavior), and sensory characteristics were evaluated using Temporal Dominance of Sensations (TDS). Deep-fat frying produced significantly higher oil content (36.6–46.8% (w/w)) than air frying (1.6–2.3% (w/w), p < 0.05), whereas air-fried snacks were harder (up to 25% higher, p < 0.05), yielded finer bolus particles (76.9–84.6% < 3 mm, p < 0.05), and required approximately twice as much time before the first swallow (29.1 s vs. 14.3 s, p < 0.05). Snacks with the highest soy yogurt content showed the lowest bolus adhesiveness and strongest dominance of softness in TDS (up to 70%), while starch-rich formulations were harder and crispier, with dominance values above 75% for hardness. These results demonstrate that formulation and frying method strongly influence fragmentation, bolus properties, and texture perception, providing insights for designing innovative, health-conscious 3D-printed snacks.

This study aimed to develop an efficient and green novel process for the extraction and separation of flavonoids from the non-medicinal parts of Paeonia lactiflora Pall. Box-Behnken experimental design was employed, with the total flavonoid extraction yield as the optimization index, to optimize the parameters of ultrasound-assisted extraction using choline chloride-malic acid (molar ratio 1:1) as the extraction solvent. The parameters optimized included solid–liquid ratio, water content, and ultrasonic time. Ultra-High Performance Liquid Chromatography-High Resolution Mass Spectrometry (UHPLC-HRMS) was utilized for the qualitative and quantitative analysis of flavonoid components in the extract. A three-compartment electrodialysis technique was applied to separate flavonoids from the extract while simultaneously recovering choline chloride and malic acid. A total of 1.4718 mg of total flavonoids was extracted and isolated from per gram of P. lactiflora stems and leaves, among which 14 flavonoid compounds were identified. The recovery rates of choline chloride and malic acid reached 87.0% and 93.0%, respectively. This study developed an efficient, recyclable, and environmentally friendly method for total flavonoid extraction. This method provides technical support for the reuse of non-medicinal parts of P. lactiflora and offers a new approach for the recovery and recycling of green deep eutectic solvents.

Blueberries are rich in anthocyanins and vitamins but highly susceptible to surface defects such as desiccation, bruising, and decay, which compromise quality and safety. This study proposes an integrated hyperspectral reflectance imaging and intelligent algorithm approach for automated detection and classification of blueberry surface defects. Vis-NIR images (398–1016 nm) were analyzed using PCA combined with band ratio imaging (W_{691.44/819.31}), and a two-dimensional Otsu threshold algorithm achieved 94.0% defect detection accuracy. Key wavelengths were extracted via CARS, SPA, and UVE methods, and classification models—including PLSR, BPNN, and LS-SVM—were developed to categorize blueberries as normal, dried, bruised, or decayed. The UVE-PLSR model achieved the highest accuracy (98.5%) with 119 wavelengths, while SPA-based models required only 5.68% of features yet maintained 97% accuracy, demonstrating a favorable balance between precision and efficiency. These results highlight the method’s robustness and practicality for large-scale industrial inspection, providing a valuable framework for enhancing quality control and reducing post-harvest losses in blueberry production.

Packaging is used to protect food and extend its shelf life. The widespread use of plastic in food and beverage packaging has led to visible environmental consequences, now affecting communities. Alternative packaging is required to replace plastic, one of which is to adapt the edible film technology. Natural biopolymers, such as starch and chitosan, have been widely researched as edible films; however, this packaging still has many shortcomings, one of which is that it can be used by decaying microorganisms. The addition of ingredients to film composites, such as bacteriocins, essential oils from spices, such as ginger, galangal, garlic, turmeric, and oregano, as well as different types of nanoparticles, is necessary to inhibit the growth of decaying microorganisms. This systematic review was conducted to analyze the effectiveness of biofilms and edible films containing antimicrobial substances in inhibiting the growth of target microorganisms. Bacteriocins added to the composite film showed relatively large inhibitory effects against mold-type microorganisms. Some essential oils also show considerable inhibitory effects on some gram-negative and gram-positive bacterial microorganisms. Ginger extract incorporation into edible films significantly increased inhibition zones, attributable to polymerization-derived antibacterial functional groups and enhanced bioavailability of modified gingerol/shogaol compounds. The results of this systematic review can be used as a reference for further research on the effectiveness of film inhibition against target microorganisms that can be directly applied to the food matrix.

Potato protein is an ideal carrier for the delivery of hydrophobic nutrients due to its unique molecular structure and rich functional properties. In this study, a linseed oil emulsion cold gel (tPLG) based on TGase-modified potato protein was developed by the induction of gluconate-delta-lactone (GDL). Results indicated that 2.0% GDL led to the effectively improved gel strength of 114.32 g×mm with the highest WHC of 43.65%. SEM also showed that the surface of tPLG was smooth, and the network structure was uniform and tight. Strong evidence was found from the significantly increased disulfide bond (0.995 mmol/mg) at 2.0% GDL, as well as the reinforced secondary and tertiary structures of protein. Finally, tPLG induced by 2% GDL facilitated the formation of potato protein emulsion cold gel with excellent appearance, superior mechanical properties and water holding capacity. Therefore, the produced tPLG could be served as an effective way of embedding linseed oil, providing more possibilities for the high-value utilization of potato protein, and thereby alleviating the problems of environmental pollution and resource waste.

Yoghurt fermentation is a complex biochemical process governed by microbial activity and acidification dynamics, directly influencing product quality. Traditionally, monitoring this process relies on invasive sampling and pH measurement, which are labour-intensive, pose contamination risks, and hinder continuous quality control. Currently, no established non-invasive system exists which integrates deep learning models for real-time prediction of key fermentation parameters such as pH and time. Addressing this gap, the present study introduces a computer vision system employing deep learning to non-destructively assess yoghurt fermentation quality using surface chromatic features (L*, a*, b*). Comprehensive modeling was conducted using multiple deep learning architectures like Feed forward neural network, Long short-term memory, Gated recurrent unit and Transformer with FFNN4 (256, 128, 64) emerging as the most accurate model. It achieved high prediction accuracy for fermentation time (R²: 0.993 ± 0.004, RMSE: 8.03 ± 1.85, MAE: 6.54 ± 1.75 and MBE: 0.11 ± 0.55) and pH (R²: 0.996 ± 0.001, RMSE: 0.06 ± 0.01, MAE: 0.04 ± 0.005 and MBE: − 0.001 ± 0.01). A Python-based framework was developed using FFNN4 for real-time prediction, integrating a GUI, live camera feed, ROI-based image capture, and data logging. Calibration analysis showed excellent agreement with actual standards (R²: 0.9998, RMSE: 0.5799 and MAE: 0.4527), validating chromatic data reliability. The experimental yoghurt conformed to the commercial samples in physicochemical, sensory, texture, and microbiological properties, with no significant differences (p > 0.05). This non-invasive monitoring framework can be effectively deployed for industrial purpose, enhancing microbial safety, enabling continuous quality control, and reducing manual dependency, thereby supporting scalable, automated yoghurt production in smart dairy environments.

Phenolics are bioactive compounds known for their health-promoting properties, including antioxidant, anti-inflammatory, and potential protective effects against chronic diseases. They are also valued in the food industry for their role in enhancing nutritional quality and shelf life. This study aimed to evaluate the physicochemical properties, phenolic and volatile profiles, and antioxidant capacities of five pine cone powders (Pinus sylvestris, Pinus nigra, Pinus pinea, Pinus halepensis, and Pinus brutia) and their decoctions, as well as to investigate the changes in bioactive compounds during in vitrogastrointestinal digestion. The predominant volatile compounds in the decoctions were α-pinene, limonene, and pinocarveol. Total phenolic content (TPC) varied from 14.10 to 83.03 mg GAE/g dry weight, with P. halepensis decoction exhibiting the highest levels, followed by P. sylvestris. Quercetin emerged as the principal phenolic compound, along with caffeic acid, kaempferol, gallic acid, protocatechuic acid, and catechin. While P. halepensis showed high TPC and antioxidant capacity, its bioaccessibility index (BI %) was not consistently the highest. Notably, all decoctions except P. pinea maintained higher TPC and antioxidant levels throughout the intestinal phase, retaining 26.20%–37.47% of their initial phenolic content. These findings highlight the potential of pine cone decoctions as functional ingredients rich in phenolic and volatile compounds, suggesting applications in health-promoting foods and nutraceuticals.

Honey is an excellent source of a variety of chemical compounds and elements vital for human consumption. But changes in environmental conditions, anthropogenic pollution as well as deliberative adulteration practices might be altering the properties and thereby degrading the quality of honey. This study focuses on 72 mangrove honey samples collected from various coastal regions of the Indian Sundarbans to assess their physicochemical and biochemical parameters, and multi-elemental contents to determine their quality in the context of suitability for human consumption. Only 28% of wild honey samples (n = 35) and 11% of apiary honey samples (n = 37) were able to meet the honey specification made by food safety standards. Generalised Linear Model (GLM) showed a significant difference in overall quality between the wild and apiary honey samples. The Principal Component Analysis (PCA) suggested that the physical characteristics of the honey samples were mostly preserved while the concentrations of the essential elements were mostly responsible for variation between the samples. Macro and micro essential elements in all mangrove honey samples were within the limit made by food safety standards. This study found only 18% of total honey samples (n = 72) collected from Indian Sundarbans are suitable for human consumption. This study suggest that the honey collection methodology should be standardized and ecologically sustainable. To verify that the harvested honey is safe for human consumption or not, rigorous testing is required.

Moringa oleifera, often referred to as “Miracle Tree” has drawn increasing interest due to its seed oil with rich nutritional profile, therapeutic potential, and stability compared to conventional vegetable oils. In this study, Moringa oleifera seeds were processed through hot pressing and solvent extraction, yielding moringa oleifera seed oil (MSO). Comprehensive physical, chemical, and fatty acid analyses were conducted, followed by evaluation of lipid stability under microwave, electric stove, deep-frying, and incubation treatments, as well as application in mayonnaise formulation. The extracted oil exhibited a melting point of 19.2 °C, specific gravity value of 0.9082 and 1.4584 for the refractive index. Chemical analysis revealed low free fatty acids (0.1548%) with peroxide levels of 1.53 meq/kg while the saponification value was 184.19 mg KOH/g and iodine value 67.468 g I₂/100 g, indicating superior freshness and stability. Fatty acid profiling confirmed oleic acid dominance (71.01%), alongside palmitic (11.18%) and stearic (4.04%) acids, with Trans fats at just 0.15%. Across heat treatments, MSO demonstrated resilience, with peroxide values rising modestly (4.44–7.37 meq/kg) compared to other vegetable oils. Mayonnaise prepared using MSO showed high sensory acceptability (appearance: 7.87; overall acceptability: 7.20 on a 9-point hedonic scale), though texture scored lower (6.73). Overall, MSO exhibited strong oxidative stability, nutritional benefits, and consumer acceptability, establishing it as a promising alternative to conventional edible oils. Future research could focus on exploring the industrial applications of MSO in functional foods and nutraceuticals.