Crataegus azarolus (Hawthorn) serves as a novel, untapped botanical source for pectin extraction, offering a valuable approach to valorize underutilized wild fruits. This study optimized pectin extraction yield and quality using 0.1 M citric acid by varying pH and temperature, and comprehensively evaluated physicochemical, functional, and structural properties to assess its preliminary potential for preparing eco-friendly packaging films. Extractions were performed across pH levels of 1.5, 2.5, and 3.5, and temperatures of 70, 80, and 90 °C. Results showed that optimal extraction conditions yielded a maximum (8.43
The adulteration of extra virgin olive oil remains a major problem for the food industry. This practice has both health and economic consequences. In countries which import extra virgin olive oil, the problem is even more serious. The objective of this study was to use a laboratory assembled fluorometer to detect the presence of refined palm oil in extra virgin olive oil commercialized in Cameroon. The fluorescence spectra obtained with an excitation wavelength of 380 nm reveal two principal emission peaks: one at 497.18 nm, attributed to oxidation products in refined palm oil, and another at 673.75 nm, attributed to chlorophylls in extra virgin olive oil. The fluorescence intensities of the adulterated samples increased with the concentration of refined palm oil in extra virgin olive oil. Principal component analysis, employing two principal components that accounted for 95
The colloidal properties of Salmonella promote its adhesion to the oil–water interface in fatty food emulsions, hindering separation from the aqueous phase and reducing the sensitivity of rapid detection assays. There have been studies that utilized α-amylase to hydrolyze starch to enhance the detection of Salmonella in ground beef. However, the interfacial behavior of enzyme-modified starch and its relationship with bacterial distribution in oil–water systems is unclear. Based on this background, an enzyme-modified soluble starch (E-SS) was prepared that can effectively recover Salmonella from meat samples. Furthermore, this study examined the molecular structure of E-SS and its regulatory effect on Salmonella distribution in oil–water systems. Compared with native soluble starch (SS), E-SS exhibited a smaller molecular weight distribution (Mw = 3.184 × 103 ± 5.776
The present study investigates a novel electric field and pressure assisted extraction (EF PAE) technique for the recovery of rice bran oil (RBO) from the geographically indicated Mushkbudji rice (Oryza sativa L) compared to conventional Soxhlet extraction. Process variables like electric field strength (10–30 V/cm), positive pressure (0–10 kg/cm2), and temperature (10–20 ℃) were evaluated for their effect on the efficiency of extraction. The maximum oil recovery (16.01 g/100 g) was achieved at 30 V/cm, 10 kg/cm2, and 20 ℃, representing a 33.4
Melamine (MA) detection in milk and milk products has attracted much attention since the discovery that MA-adulterated food causes serious damage to the kidney, leading to urinary calculus, acute kidney failure, and bladder cancer. Most methods measure MA through various chromatographic techniques, which require skill, time consuming, tedious, expensive instrumentation and preprocessing of samples. Aptamer-based biosensors are a promising choice for MA analysis due to their advantages over instrumental analysis and immunoassays. Thymine (T) in single-stranded DNA can specifically bind to MA through a T-MA-T triple hydrogen bonding (NH⋯O and NH⋯N) motif, which serves as the fundamental recognition principle for many DNA-based biosensors. In this review, we aim to report the latest research progress in the field of aptasensors based on different sensing technologies (including colorimetric, fluorescence, surface enhanced Raman scattering (SERS), resonance Rayleigh scattering (RRS), and electrochemical) for rapid detection of MA in milk products. While these sensing techniques enable accurate and rapid detection, portable, high sensitivity, high efficiency, and simple operation, they are constrained by matrix interference, limited stability, poor reproducibility, and insufficient standardization. Overcoming these hurdles to achieve large-scale implementation requires future research to enhance device robustness, selectivity, and data-processing capabilities. This review will inspire future research on aptamer-based biosensing for real time monitoring of MA adulteration in order to safeguard human health and food safety.
Lavatera cretica leaves were traditionally used as a medicinal and food plant, particularly in rural communities. This study aimed to optimize extraction conditions for phenolic compounds from Lavatera cretica leaves and to evaluate their antioxidant and anti-hemolytic activities. The Box-Behnken model was used to optimize maceration time, solid-to-liquid ratio, and ethanol concentration. High-performance liquid chromatography with ultraviolet detection (HPLC–UV) was used to analyze the bioactive compounds in the extract. In vitro antioxidant and anti-hemolytic assays were also conducted. The optimal extraction conditions were 46.18
This study explores the design and application of red cabbage-derived DIY sensors as low-cost, eco-friendly analytical tools for monitoring quality parameters in food safety, personal health, and environmental diagnostics. Red cabbage (Brassica oleracea var. capitata f. rubra) is a rich source of anthocyanins, naturally occurring pH-sensitive pigments that undergo distinct, reversible color transitions across a pH range of 2–10. Leveraging these chromogenic shifts, we developed biodegradable sensors for monitoring sweat pH, exhaled breath gas, and food quality, fabricated from household materials such as filter paper, gelatin, and vinegar. These sensors demonstrated high visual contrast and functional reliability when exposed to bio-mimicking stimuli. To assess the pedagogical utility of these sensors, interactive sessions were conducted with high school and undergraduate students (n = 30), integrating sensor fabrication, calibration, and smartphone-assisted RGB analysis. Pre- and post-session assessments revealed a 38–86
Daqu is a key fermentation starter for Baijiu production, whose acidity is a core indicator for evaluating its quality. This study aimed to propose a method for Daqu acidity soft sensing and time series prediction based on environmental response so as to address the issues of complexity, destructiveness, and lag associated with traditional detection methods. The environmental parameters employed during Daqu fermentation were recorded and preprocessed. A stacking ensemble soft sensing model based on gradient boosting decision tree, random forest, extreme gradient boosting (XGBoost), and ridge regression was constructed to achieve rapid, nondestructive, and real-time estimation of Daqu acidity. The hourly acidity estimates output by the soft sensing model were then used as input features, besides environmental parameters, to construct a hybrid XGBoost–LSTM time series prediction model for predicting future acidity values. The experimental results showed that the stacking soft sensing model achieved the best performance, with a coefficient of determination (R2) of 0.9409. Compared with a single XGBoost model, the XGBoost–LSTM time series model improved R2 by more than 5
On-site detection of heavy metal ions remains challenging, especially for environmental monitoring and food safety. Herein, we present a paper-based microfluidic coordination array for the portable detection of Hg2⁺, Pb2⁺, Cd2⁺, and Cu2⁺. The device requires only 20 µL of sample solution to completely fill six channel reservoirs, and color changes are produced by coordination of heavy metal ions with chelating ligands. The color responses were captured using a smartphone under controlled LED illumination and converted into digital red–green–blue (RGB) signals. The device distinguished Hg2⁺, Pb2⁺, Cd2⁺, and Cu2⁺ in spiked water and canned juice at 2 µM; linear discriminant analysis (LDA) achieved 100
Widespread use of disposable plastic food containers has raised concerns regarding the migration of trace metals and metalloids into foods. This study developed and applied analytical methods for the determination of nine metals and metalloids (Pb, Sb, Cd, Ge, Co, Mn, Sn, As, Hg) released from polypropylene (PP), polyethylene terephthalate (PET), and polystyrene (PS) food containers commonly used in South Korea. Migration tests were conducted using 4
Monitoring toxic nitrite (NO2−) depletion in complex food matrices is crucial for food safety, yet challenging due to interfering matrices. Herein, we report a high-performance electrochemical sensor fabricated by decorating a highly conductive MXene (Ti3C2Tx) nanomaterial with a newly synthesized polymer-supported peroxomolybdate (PMo) composite. Structural and morphological properties of the PDDA@PMo/MXene composite were systematically validated using FTIR, XRD, SEM, TEM, and EDX. The modified sensor exhibited exceptional electrocatalytic activity, enabling simultaneous and sensitive quantification of both NO2− and ascorbic acid (AA). The same sensor was successfully applied to monitor nitrate (NO3−) levels following its chemical reduction to NO2− using a spongy Zn@Cd catalyst. Specifically, NO2− was detected across two wide linear ranges (2.0–100 μM and 100–1000 μM) with a low detection limit (LOD) of 0.39 μM, while AA quantification spanned 10–1200 μM with an LOD of 2.0 μM. Furthermore, the sensor effectively monitored NO2− depletion in cured meat samples containing nitrates and AA. The results demonstrated a strong correlation with standard laboratory methods, underscoring the robust practical applicability of the PDDA@PMo/MXene platform for advanced food safety monitoring.
Rapid and accurate identification of tea species and grade classification are crucial for regulating tea market transactions and advancing the standardized and intelligent development of the tea industry. This study innovatively achieves efficient classification and detection of tea species and grades through a self-developed portable electronic nose technology, combined with data preprocessing methods and multiple optimized pattern recognition algorithms. Firstly, four representative varieties of black tea and green tea, covering 26 grades, are selected as research objects. Volatile aroma characteristic signals of tea are collected using an electronic nose sensor array, and the differences in these signals originate from variations in sensory evaluation, which lays a feasible foundation for the classification tasks in this study. Subsequently, multiple classification models are compared. Results demonstrate that the AW-FA-SVM model exhibits the optimal performance, effectively resolving the identification dilemma caused by overlapping features of adjacent grade teas. The technical scheme proposed herein realizes the standardization, automation, and rapidity of the classification process, efficiently overcoming the shortcomings of strong subjectivity in traditional sensory evaluation and time-consuming complexity in physicochemical analysis. It provides new insights and practical basis for the future development of intelligent and portable online detection platforms for tea quality.
Chloramphenicol is a broad-spectrum antibiotic that poses a significant risk to public health and the environment. Exposure to this compound has been associated with serious adverse effects, including aplastic anemia and genotoxic/carcinogenic concerns. Therefore, the development of a reliable method to detect chloramphenicol in food samples is essential. However, its determination in complex food matrices remains challenging because of possible matrix effects, low analyte concentration, and the need for sensitive and selective methods. To this end, we developed a highly sensitive electrochemical sensor to detect chloramphenicol in milk samples. The sensor was based on the modification of a glassy carbon electrode surface with carbon black. Electroanalytical analyses were performed using cyclic voltammetry and differential pulse voltammetry, and the results revealed that the sensor has high sensitivity for chloramphenicol determination. Under optimal conditions, the sensor showed a linear response over the range of 0.05 to 87.0 μmol L⁻1, with a detection limit of 0.0012 μmol L⁻1 and a sensitivity of 0.07 μA L μmol⁻1 for chloramphenicol detection in Britton–Robinson buffer (0.04 mol L⁻1, pH 7.00). The recovery rates in milk samples ranged from 91.7
To address the limitations of conventional aflatoxin B1 (AFB1) detection methods, including high-performance liquid chromatography (HPLC) and enzyme-linked immunosorbent assay (ELISA), which are characterized by complex operation and high cost, this study proposes a dual-mode aptasensor constructed on MnO2 nanoflowers (MnO2 NFs). This sensor integrates colorimetric and fluorescent detection strategies, leveraging the high catalytic activity and fluorescence quenching properties of MnO₂ NFs to enhance detection sensitivity. Key assay parameters, including MnO2 NFs concentration, aptamer concentration, pH, and incubation time, were optimized to improve analytical performance. The method eliminates the need for complex nanomaterials or DNA amplification, offering operational simplicity and low cost. The proposed strategy was demonstrated to be effective for food safety monitoring, while also highlighting the potential of MnO2 nanomaterials in advanced biosensing applications.
The kernels of Litsea cubeba seeds are the primary byproduct after essential oil extraction, rich in oils. Their efficient utilization and quality enhancement are crucial to achieving comprehensive, high-value development of all Litsea cubeba components. The objective of this study is to investigate the effects of traditional methods (Cold Pressing (CP), Hot Pressing (HP), Soxhlet Extraction (SE)) and a novel method (Ultrasonic-Assisted Extraction (UAE)) on the oil yield, physicochemical properties, active components, antioxidant capacity, and volatile constituents of Litsea cubeba kernel oil (LCKO). Results indicate that the fatty acid composition of LCKO after steam distillation is dominated by linoleic acid and lauric acid, with unsaturated fatty acids accounting for over 50
The objective of this work was to streamline and optimize the method for quantifying acrylamide in wheat-based baked goods. Especially, because the presence of acrylamide in high-temperature-baked products is undesirable, as the International Agency for Research on Cancer (IARC) classifies it as a Group 2 potential carcinogen. We provide a GC–MS method for determining acrylamide following a multistage acrylamide extraction and cleanup process, and xanthydrol derivatization. The results showed that the optimized method achieved high recovery rates, precision, specificity, robustness, repeatability, and reproducibility. The method performance met EU guidelines for selecting a method for quantifying acrylamide in foods. Therefore, the optimized method may provide an analytical framework for comparing acrylamide concentrations in wheat-based products worldwide.
In this study, a model was utilized employing headspace-solid phase microextraction-gas chromatography-mass spectrometry, headspace-gas chromatography-ion mobility spectrometry, electronic nose, and electronic tongue technologies integrated with the random forest method to identify and analyze the flavor characteristics of seven different varieties of honeysuckle. The results indicated that there are significant differences in the types and concentrations of volatile compounds among different varieties of honeysuckle. Except for the overlap between Little Maohua and Leaf Qi samples, the other samples could be effectively distinguished. Combined analysis using headspace-solid phase microextraction-gas chromatography-mass spectrometry and headspace-gas chromatography-ion mobility spectrometry identified linalool as a key compound significantly contributing to the characteristic aroma of honeysuckle. Additionally, the content of amino acids and sugars showed a positive correlation with the taste characteristics of honeysuckle. This study not only provides a multi-dimensional analysis method for the quality evaluation of honeysuckle but also offers a solid foundation for variety identification and quality control, which is of great significance for the development and utilization of honeysuckle resources.
Dendrobium officinale is a renowned medicinal and edible plant, and its market value is closely related to its growth years. In this study, a nano-electrospray ionization mass spectrometry (Nano-ESI-MS) was established to rapidly obtain the chemical profiling and identify D. officinale with different growth years. The proposed method demonstrated high linearity (R2 > 0.9979), low LODs (0.03–0.26 mg·L−1) and LOQs (0.09–0.77 mg·L−1), high precision (RSD < 10
Bread is one of the most widely consumed staple foods worldwide, and the use of chemical additives during its production represents a significant concern due to potential health risks. Among these additives, potassium bromate (KBrO3) is classified as a possible carcinogen and is banned in many countries, including Brazil. In addition, sugars (glucose and fructose) are commonly added to enhance the flavor, texture, and shelf life. These additives, in some cases, exceed recommended dietary limits, and analytical methods are used to monitor the regulatory levels of these compounds. To achieve this goal, traditional methods, although efficient, are mostly expensive and time-consuming. Thus, we developed a rapid, low-cost, and environmentally friendly methods based on smartphone-assisted digital image analysis (DIA) for the quantification of KBrO3, glucose, and fructose in 22 commercial bread samples. After optimizing the DIA parameters, we have determined saturation and red as the best-performing channels for KBrO3 and sugars, respectively. The DIA methods were validated against UV–Vis spectrophotometry, showing no statistically significant differences. KBrO3 was detected in ten samples (from 4.03 to 31.69 µg g⁻1), indicating regulatory non-compliance. Glucose was the predominant sugar, indicating nutritional variability and the need for monitoring. The DIA methods enabled rapid, eco-friendly routine quality control.
The realization of sensitive detection of ofloxacin (OFL) residues is a key measure to prevent environmental risks caused by improper use of antibiotics, ensure food safety and promote public health security. Utilizing split crRNA with CRISPR/Cas12a (SCas12a)-powered cascade strand displacement amplification (C-SDA) and using phosphorothioate-modified G-quadruplex/triplex (psG43) concatemer fluorescence probe, a strategy named SCCA was devised for OFL detection. Target OFL triggers the SCas12a-driven C-SDA, and then activates SCas12a’s trans-cleavage activity. The activated SCas12a system cleaves reporter probe and then releases the psG43 sequence, which then combines with thioflavin T (ThT) to emit a fluorescence signal. The SCCA strategy not only avoids the design of PAM required by traditional C-SDA, but also can specifically detect OFL as low as 0.1 pM. The anti-interference advantage of psG43 enables the utilization of the SCCA strategy for OFL detection in milk samples.
