Synchronous fluorescence detection of nitrite in meat products based on dual-emitting dye@MOF and its portable hydrogel test kit.

A novel ratiometric fluorescent nanoprobe (Rh6G@UIO-66-NH2) was fabricated for efficient nitrite (NO2-) detection in the present study. When NO2- was introduced, it interacted with the amino groups on the surface of Rh6G@UIO-66-NH2, forming diazonium salts that led to the quenching of blue fluorescence. With this strategy, a good linear relationship between NO2- concentration and the fluorescent intensity ratio of the nanoprobe in the range of 1-100 µM was established, with a detection limit of 0.021 µM. This dual-readout nanosensor was applied to analyze the concentration of NO2- in real meat samples, achieving satisfactory recovery rates of 94.72-104.52%, highlighting the practical potential of this method. Furthermore, a portable Gel/Rh6G@UIO-66-NH2 hydrogel test kit was constructed for on-spot dual-mode detection of NO2-. This kit allows for convenient colorimetric analysis and fluorometric detection when used in conjunction with a smartphone. All the photos taken with the portable kit was converted into digital information using ImageJ software. It provides colorimetric and fluorescent visual detection of NO2- over a range of 0.1-1.5 mM, achieving a direct quantitative tool for NO2- identification. This methodology presents a promising strategy for NO2- detection and expands the application prospects for on-spot monitoring of food safety assessment.

Lipid oxidation and flavor changes in saturated and unsaturated fat fractions from chicken fat during a thermal process.

Chicken fat, due to its rich fatty acids (FAs), is more prone to lipid oxidation and the production of volatile compounds. The aim of the present study was to investigate the oxidative characteristics and flavor changes of saturated (SFF) and unsaturated fat fractions (USFF) from chicken fat induced by heating (140 °C at 70 rpm min-1 for 1 h and 2 h: SFF1, USFF1, SFF2 and USFF2). The FAs and volatile compounds were analyzed by gas chromatography-mass spectrometry (GC-MS) and two-dimensional gas chromatography time of flight mass spectrometry (GC × GC-ToFMS), respectively. The results showed that higher contents of unsaturated fatty acids (UFAs) were found in USFF compared to that in SFF, whereas USFF showed lower levels of saturated fatty acids (SFAs). With the extension of heating time, the SFA/UFA ratio in USFF and SFF significantly increased (p < 0.05), and more aldehydes, alcohols, ketones, and lactones were formed. Moreover, the odor activity values of 23 important compounds in USFF1-2 were significantly higher (p < 0.05) than those in SFF1-2. As revealed by principal component analysis (PCA) and cluster analysis (CA), it was obviously observed that all samples were divided into four clusters (USFF-SFF, USFF1-SFF1, USFF2, and SFF2). According to correlation analysis between FAs and volatile compounds, C18:2 ω6, C18:3 ω6 and C18:3 ω3 were significantly associated with dodecanal, (Z)-3-hexenal, (E)-2-decenal, 2-undecenal, (E)-2-dodecenal, (E,E)-2,4-nonadienal, (E,E)-2,4-decadienal, 2-decanone, γ-octalactone and γ-nonalactone. Our data elucidated that fat fractions from chicken fat with varying degrees of saturation could impart different flavor characteristics during a thermal process.

Effect of plant polyphenols on the physicochemical properties, residual nitrites, and N-nitrosamine formation in dry-fried bacon.

Tea polyphenol (TP), apple polyphenol (AP), and cinnamon polyphenol (CP) are all enriched with antioxidant components, present enormous potential as natural antioxidants in meat products. The objective of this study was to evaluate the physicochemical properties, residual nitrites, and formation of N-nitrosamine (NA) in dry-fried bacons with three aforementioned plant polyphenols and ascorbic acid (AA). The results show that both plant polyphenols and AA significantly reduced pH, lipid oxidation and residual nitrite content when compared to the control (P < 0.05). Only AP exhibited a protective effect against protein oxidation-induced damage in bacon, and N-nitroso-methyl phenylamine (NMPhA) contents were significantly affected by plant polyphenols (P < 0.05). Bacon containing 300 mg/kg AP produced less thiobarbituric acid reactive substance (TBARS) (0.59 MDA/kg), carbonyl contents (2.30 nmol/mg protein) and NMPhA formation (1.211 ng/kg). In conclusion, plant polyphenols, particularly AP, have the potential to be used as natural antioxidants for reducing oxidation and nitrite application level while also improving the safety of bacon.

Changes in moisture, colour, residual nitrites and N-nitrosamine accumulation of bacon induced by nitrite levels and dry-frying temperatures.

The effects of different nitrite levels (50, 100, and 150 mg/kg meat) and dry-frying temperatures (100, 150, 200 and 250 °C) on the moisture movement, colour, sensory variables and residual nitrite and N-nitrosamine levels in smoked bacon were investigated. Increasing the dry-frying temperatures significantly increased the cooking loss and decreased the moisture content (P < 0.05). The bacon L*-values showed an increasing trend at first and then decreased, with the highest value of the bacon with 150 mg/kg nitrite was obtained at 100 °C and 150 °C. In addition, a*-values were significantly affected by the nitrite level and dry-frying temperature (P < 0.05), with the highest value of the bacon samples with 100 and 150 mg/kg nitrite observed at 250 °C. The residual nitrite content level initially increased (from unheated control to 150 °C) and then decreased (from 150 to 250 °C) sharply with increasing dry-frying temperatures in the bacon samples with the same sodium nitrite levels. N-methyl-N-nitrosoaniline (NMPhA) and N-nitrosomorpholine (NMOR) were measured in a number of smoked bacon samples, and a significant positive correlation (R2 = 0.772) was found for N-nitrosamines (NA) contents and nitrite levels (P < 0.05). The maximum levels of NMPhA and NMOR were detected when the bacon with 150 mg/kg sodium nitrite was pan-fried at 200 °C and 150 °C, respectively.

Evaluation of volatile flavor compounds in bacon made by different pig breeds during storage time.

The oxidation and volatile constituents of bacon (which made of white pig (Duroc × Landrace × Yorkshire) and black pig (Beijing Black × Yorkshire)) during refrigerated storage were analyzed by thiobarbituric acid reactive substances (TBARS), total thiol groups, gas chromatography-mass spectrometry (GC-MS) and gas chromatography coupling with ion mobility spectrometry (GC-IMS). The TBARS value of tested samples increased while the total thiol groups decreased during 60 days storage (P < 0.05). Volatile fingerprint results were obtained by GC-MS and GC-IMS detector, the classes and contents of volatile compounds detected in WP bacon were much abundant than BP bacon. Higher phenols and acids concentrations were observed in WP bacon, while alcohols, ketones, and nitrogen-containing compounds were more determined in BP bacon. Besides, WP bacon was more notably affected by storage rather than BP bacon, and the difference of raw material is the main reason for the flavor in WP and BP bacon comparing with the storage process.

Multiple graphs learning with a new weighted tensor nuclear norm.

As an effective convex relaxation of the rank minimization model, the tensor nuclear norm minimization based multi-view clustering methods have been attracting more and more interest in recent years. However, most existing clustering methods regularize each singular value equally, restricting their capability and flexibility in tackling many practical problems, where the singular values should be treated differently. To address this problem, we propose a novel weighted tensor nuclear norm minimization (WTNNM) based method for multi-view spectral clustering. Specifically, we firstly calculate a set of transition probability matrices from different views, and construct a 3-order tensor whose lateral slices are composed of probability matrices. Secondly, we learn a latent high-order transition probability matrix by using our proposed weighted tensor nuclear norm, which directly considers the prior knowledge of singular values. Finally, clustering is performed on the learned transition probability matrix, which well characterizes both the complementary information and high-order information embedded in multi-view data. An efficient optimization algorithm is designed to solve the optimal solution. Extensive experiments on five benchmarks demonstrate that our method outperforms the state-of-the-art methods.