Digital image colorimetric analysis for evaluating lipid oxidation in oils and its emulsion

Development of an Open Droplet Microchannel-Based Magnetosensor for Immunofluorometric Assay of Trimethoprim in Chicken and Pork Samples with a Wide Linear Range

Trimethoprim (TMP), functioning as a synergistic antibacterial agent, is utilized in diagnosing and treating diseases affecting livestock and poultry. Human consumption of the medication indirectly may lead to its drug accumulation in the body and increase drug resistance due to its prolonged metabolic duration in livestock and poultry, presenting significant health hazards. Most reported immunoassay techniques, such as ELISA and immunochromatographic assay (ICA), find it challenging to achieve the dual advantages of high sensitivity, simplicity of operation, and a wide detection range. Consequently, an open droplet microchannel-based magnetosensor for immunofluorometric assay (OMM-IFA) of trimethoprim was created, featuring a gel imager to provide a signal output derived from the highly specific antibody (Ab) targeting trimethoprim. The method exhibited high sensitivity in chicken and pork samples, with LODs of 0.300 and 0.017 ng/mL, respectively, and a wide linear range, covering trimethoprim's total maximum residue limits (MRLs). Additionally, the spiked recoveries in chicken and pork specimens varied between 81.6% and 107.9%, maintaining an acceptable variation coefficient below 15%, aligning well with the findings from the ultraperformance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) technique. The developed method achieved a much wider linear range of about 5 orders of magnitude of 10-2-103 levels with grayscale signals as the output signal, which exhibited high sensitivity, excellent applicability and simple operability based on magnetic automation.

A low-toxic, robust, and sensitive colorimetric sensor for the peroxide value of edible oils with CsPbBr3 NCs in ethyl acetate

Sensitively, accurately, and rapidly evaluating edible oils' peroxide value (PV) is significant for safeguarding food quality and safety. However, the conventional detection methods are challenging to meet the above demands due to their complex operation, poor reproducibility, and professional personnel. The colorimetric method is an emerging technique to rapidly and on-site determine the PV of edible oils. CsPbBr3 NCs, as a novel fluorescent-sensing material, have been applied in the chemical colorimetric analysis. However, the heavy use of high-toxic solvents (toluene, chloroform) in the CsPbBr3 NCs colorimetric system significant-negatively influences the environment. This study evaluated the performances of CsPbBr3 NCs in nine low-toxic solvents and investigated the potential response mechanism to PV. The results presented that CsPbBr3 NCs in ethyl acetate displayed the highest photoluminescent intensity and the most uniform distribution. The results performed that the micro-morphology and crystal structure of CsPbBr3 NCs in ethyl acetate were similar to that in toluene, demonstrating the potential excellent performance. Under optimum conditions, three methods, including photoluminescence (PL)-decreased, wavelength-shifted, and phone-based colorimetric methods, were established to evaluate PV with the LOD of 0.0034 g/100 g. The PV recovery rates in Soybean oil, Camellia oil, Linseed oil, and Olive oil were from 75.0% to 100.0%, with a relative error below 25%. Furthermore, it was believed that the decreased PL and shifted wavelength originated from the halogen substitution with the crystal-structure destructions and the surface-defect formations. Thus, developing the low-toxic colorimetric CsPbBr3 NCs system with ethyl acetate could reduce the environmental influence and even enlighten the rise of other green detection methods for PV in edible oils.

A colorimetric sensor array for rapid discrimination of edible oil species based on a halogen ion exchange reaction between CsPbBr3 and iodide

Halogen exchange of iodides with CsPbBr3 NCs generates CsPbI3, which differs in its content and directly causes different photoluminescence responses.

Mechanism, indexes, methods, challenges, and perspectives of edible oil oxidation analysis

Edible oils are indispensable food components, because they are used for cooking or frying. However, during processing, transport, storage, and consumption, edible oils are susceptible to oxidation, during which various primary and secondary oxidative products are generated. These products may reduce the nutritional value and safety of edible oils and even harm human health. Therefore, analyzing the oxidation of edible oil is essential to ensure the quality and safety of oil. Oxidation is a complex process with various oxidative products, and the content of these products can be evaluated by corresponding indexes. According to the structure and properties of the oxidative products, analytical methods have been employed to quantify these products to analyze the oxidation of oil. Combined with proper chemometric analytical methods, qualitative identification has been performed to discriminate oxidized and nonoxidized oils. Oxidative products are complex and diverse. Thus, proper indexes and analytical methods should be selected depending on specific research objectives. Expanding the mechanism of the correspondence between oxidative products and analytical methods is crucial. The underlying mechanism, conventional indexes, and applications of analytical methods are summarized in this review. The challenges and perspectives for future applications of several methods in determining oxidation are also discussed. This review may serve as a reference in the selection, establishment, and improvement of methods for analyzing the oxidation of edible oil. HighlightsThe mechanism of edible oil oxidation analysis was elaborated.Conventional oxidation indexes and their limited values were discussed.Analytical methods for the determination of oxidative products and qualitative identification of oxidized and non-oxidized oils were reviewed.

Application of Artificial Neural Network Based on Traditional Detection and GC-MS in Prediction of Free Radicals in Thermal Oxidation of Vegetable Oil

In this study, electron paramagnetic resonance (EPR) and gas chromatography-mass spectrometry (GC-MS) techniques were applied to reveal the variation of lipid free radicals and oxidized volatile products of four oils in the thermal process. The EPR results showed the signal intensities of linseed oil (LO) were the highest, followed by sunflower oil (SO), rapeseed oil (RO), and palm oil (PO). Moreover, the signal intensities of the four oils increased with heating time. GC-MS results showed that (E)-2-decenal, (E,E)-2,4-decadienal, and 2-undecenal were the main volatile compounds of oxidized oil. Besides, the oxidized PO and LO contained the highest and lowest contents of volatiles, respectively. According to the oil characteristics, an artificial neural network (ANN) intelligent evaluation model of free radicals was established. The coefficients of determination (R2) of ANN models were more than 0.97, and the difference between the true and predicted values was small, which indicated that oil profiles combined with chemometrics can accurately predict the free radical of thermal oxidized oil.

A color reaction for the determination of Cu2+ in distilled beverages employing digital imaging

In this work, we describe for the first time the synthesis of a thiocarbazone for the selective determination of Cu²⁺ in distilled beverages. The method was based on the complexation reaction of Cu²⁺ with the thiocarbazone, and the colored product was analyzed using a smartphone application. The thiocarbazone reacts with Cu²⁺ to form a 1:1 (metal:ligand) complex. The Cu²⁺ complex was characterized by UV, IR and NMR spectral analyses. The proposed reaction yields a yellow color, and therefore, channel B of the RGB system was used in the analysis. After optimizing the reaction conditions, an analytical curve was obtained to determine Cu²⁺ concentrations ranging between 0.25 and 6.75 mg L^-1; the use of 400 μL sample volumes led to a relative standard deviation (n = 5) of 3.2% and a detection limit of 0.18 mg L^-1. Recovery experiments were performed with sugar cane spirits, whiskies and tequilas to evaluate the accuracy of the method, and the recovery obtained ranged from 80.5 to 112.2%.