Fluorescence determination of cochineal in strawberry jam in the presence of carmoisine as a quencher by means of four-way PARAFAC decomposition

ZnO Hollow Quasi-Spheres Modified Screen-Printed Graphite Electrode for Determination of Carmoisine

Food colorants are important in food selection because they improve the gastronomic appeal of foods by improving their aesthetic appeal. However, after prolonged use, many colorants turn toxic and cause medical problems. A synthetic azo-class dye called carmoisine gives meals a red color. Therefore, the carmoisine determination in food samples is of great importance from the human health control. The current work was developed to synthesis ZnO hollow quasi-spheres (ZnO HQSs) to prepare a new electrochemical carmoisine sensor that is sensitive. Field emission-scanning electron microscopy (FE-SEM) and X-ray diffraction (XRD) have been used to analyze the properties of prepared ZnO HQSs. A screen-printed graphite electrode (SPGE) surface was modified with ZnO HQSs to prepare the ZnO HQSs-SPGE sensor. For carmoisine detection, the ZnO HQSs-SPGE demonstrated an appropriate response and notable electrocatalytic activities. The carmoisine electro-oxidation signal was significantly stronger on the ZnO HQSs-SPGE surface compared to the bare SPGE. Cyclic voltammetry (CV), linear sweep voltammetry (LSV), chronoamperometry (CHA), and differential pulse voltammetry (DPV) have been utilized to investigate the suggested protocol. The DPV results revealed an extensive linear association between variable carmoisine concentrations and peak current that ranged from 0.08 to 190.0 µM, with a limit of detection (LOD) as narrow as 0.02 µM. The ZnO HQSs-SPGE's ability to detect carmoisine in real samples proved the sensor's practical application.

Sensitive voltammetric quantification of carminic acid in candies using selenium dioxide nanoparticles based electrode

Carminic acid is a food colorant which concentration has to be controlled due to the possible negative health effects. Sensitive voltammetric method is developed for carminic acid determination using electrode modified with SeO₂ nanoparticles (SeO₂ NPs) and hexadecyltriphenylphosphonium bromide (HDTPPB) acting as dispersive agent for nanoparticles and electrode surface co-modifier. SeO₂ NPs of 37-45 nm are uniformly distributed at the electrode increasing its electroactive area (41 ± 2 vs. 8.9 ± 0.2 mm² for bare glassy carbon electrode (GCE)). Electrochemical impedance spectroscopy data confirm an 18.3-fold decrease of charge transfer resistance compared to GCE (12.7 ± 0.3 vs. 232 ± 7 kΩ, respectively). In differential pulse mode, the linear dynamic ranges of carminic acid are 0.010-2.5 and 2.5-10 μmol L^-1 with a detection limit of 3.4 nmol L^-1. The method is successfully employed in candies and lozenges for sore throat treatment. The approach is simple, reliable, and can be used as an alternative to chromatography in routine analysis.

Application of multivariate data analysis for food quality investigations: An example-based review

These days, large multivariate data sets are common in the food research area. This is not surprising as food quality, which is important for consumers, and its changes are the result of a complex interplay of multiple compounds and reactions. In order to comprehensively extract information from these data sets, proper data analysis tools should be applied. The application of multivariate data analysis (MVDA) is therefore highly recommended. However, at present the use of MVDA for food quality investigations is not yet fully explored. This paper focusses on a number of MVDA methods (PCA (Principal Component Analysis), PLS (Partial Least Squares Regression), PARAFAC (Parallel Factor Analysis) and ASCA (ANOVA Simultaneous Component Analysis)) useful for food quality investigations. The terminology, main steps and the theoretical basis of each method will be explained. As this is an example-based review, each method was applied on the same experimental data set to give the reader an idea about each selected MVDA method and to make a comparison between the outcomes. Numerous MVDA methods are available in literature. Which method to select depends on the data set and objective. PCA should be the first choice for data exploration of two-dimensional data. For predictive purposes, PLS is the most appropriate method. Given an underlying experimental design, ASCA takes into account both the relation between the different variables and the design factors. In case of a multi-way data set, PARAFAC can be used for data exploration. While these methods have already proven their value in research, there is a need to further explore their potential to investigate the complex interplay of compounds and reactions contributing to food quality. With this work we would like to encourage food scientists with no or limited knowledge of MVDA to get some first insights into the selected methods.

Determination of melamine in milk by fluorescence spectroscopy and second-order calibration

Melamine is a compound commonly used in the manufacturing of plastic and flame retardant products, but due to its solubility on water and high nitrogen content, it is also used to adulterate milk to mask adulteration by dilution in protein content tests. This work proposes a quick method using excitation-emission matrix (EEM) fluorescence spectroscopy and second-order calibration methods (PARAFAC and U-PLS/RBL) for the identification and quantification of melamine in milk. The proposed method uses a single clean-up step with acetic acid, resulting in a quick, low-cost, and environmentally friendly procedure, in agreement with green chemistry principles. Both PARAFAC and U-PLS/RBL were capable of detecting melamine in milk above 120.6 and 146.5 ppm respectively, adequate for adulterations above 2% in volume, with RMSEPs of 68.6 and 81.9 ppm, respectively.

Cobalt (II) complex as a fluorescent sensing platform for the selective and sensitive detection of triketone HPPD inhibitors

4-Hydroxyphenylpyruvatedioxygenase (HPPD) is a Fe(II)/Co(II)-dependent enzyme which has become one of the most effective herbicide targets. HPPD inhibitors have been developed as efficient herbicides for resistant weed control. Developing a method for efficient and rapid HPPD inhibitors detection is still challenging. N-n-butyl-4-methylhydrazinecarbothioamide-1,8-naphthalimide (NMN) was synthesized and used to detect Co²⁺ efficiently with the limit of detection (LOD) of 7.82 nM with a turn-on fluorescence. Herein a novel fluorescent complex, NMN‒Co²⁺ was employed to determine HPPD inhibitors which performed a turn-off effect in the sensing process based on the competitive coordination between the probe and HPPD with Co²⁺. The LODs for three commercial triketone HPPD inhibitors (mesotrione, tembotrione and NTBC) were 6.60 nM, 7.37 nM and 10.22 nM with good sensitivity and selectivity. Furthermore, the present probe has potentials to quantitatively detect mesotrione and tembotrione in real samples.

A novel and sensitive ratiometric fluorescence assay for carbendazim based on N-doped carbon quantum dots and gold nanocluster nanohybrid

A novel fluorescence "turn on" ratiometric fluorescent sensor was employed to determine carbendazim. The sensing process was achieved through the strong fluorescence resonance energy transfer (FRET) between nitrogen doped carbon quantum dots (N-CQDs) and gold nanocluster (AuNCs). The photoluminescence intensity of N-CQDs can be deactivated by AuNCs through FRET effect and recovered by the addition of carbendazim. The ratiometric detection of carbendazim is achieved by recording the photoluminescence and second-order Rayleigh scattering (SRS) signal of N-CQDs/AuNCs system. With the introduction of carbendazim to the sensing platform resulted in the photoluminescence and SRS signal of N-CQDS/AuNCs enhancing. UV-vis absorption, Zeta potential and fluorescence lifetime analyses indicate that the fluorescence turn on process can be attributed to the aggregation of AuNCs breaks the FRET process and increases SRS intensity. N-CQDs/AuNCs probe present a good sensitivity and selectivity for carbendazim detection, with two linear response ranges (1-100 μM, 150-1000 μM), low detection limit of 0.83 μM and 37.25 μM. Furthermore, real sample analyses indicate that the as-presented sensor has potentials in carbendazim determination in real sample analyses.