Determination of propineb in vegetable samples after a coprecipitation strategy for its separation-preconcentration prior to its indirect determination by FAAS

Construction of a fluorescence switch sensor of Mn doped AgInS2 quantum dots for the detection of Fe (III) and ascorbic acid

The convenience and high efficiency of recently developed I-III-VI group AgInS2 (AIS) fluorescence sensors have garnered considerable attention. In this study, glutathione (GSH) was employed as a stabilizer to synthesize Mn doped AgInS2 quantum dots (Mn-AIS QDs) via a one-step hydrothermal method at a lower temperature. The resultant samples displayed favorable photoluminescent characteristics and excellent water dispersibility. The photoluminescence of Mn-AIS QDs is quenched by Fe (III) via a photo-induced electron transfer mechanism (PET), and this quenching can be reversed by ascorbic acid (AA) as a result of the redox reaction between the Mn-AIS-Fe (III) complex and AA. Utilizing the on-off-on fluorescence principle, a fluorescence switch sensor based on Mn-AIS QDs was developed for the detection of Fe (III) and AA. The linear range for the detection of Fe (III) using the Mn-AIS QDs sensor was established to be 0.03-120 µM, with a detection limit (LOD) of 0.16 nM. For the detection of AA within the Mn-AIS-Fe (III) system, the linear range spanned from 0.05 to 180 µM, with a LOD of 0.031 µM. Both Mn-AIS and Mn-AIS-Fe (III) demonstrated robust anti-interference properties, facilitating the accurate detection of Fe (III) in tap water and AA in vitamin C tablets. This approach is notable for its simplicity, cost-effectiveness, and considerable potential for application in the creation of innovative biological and environmental sensors.

Development of a novel HPLC-CDCL method utilizing nitrogen-doped carbon dots for sensitive and selective detection of dithiocarbamate pesticides in tea

In this study, S-methyl derivatives of dithiocarbamates (DTCs) were shown to significantly enhance chemiluminescence (CL) between Ce(IV) and efficient and environmentally friendly nitrogen-doped carbon dots (NCDs). Based on the elucidation of the CL mechanisms, an innovative approach involving high-performance liquid chromatography coupled with N-CDs and CL detection (HPLC-CDCL) was proposed. The developed method was successfully applied to the highly sensitive detection of three DTC fungicides (dimethyl dithiocarbamate, ethylene bisdithiocarbamate, and propylene bisdithiocarbamate) in tea. The recovery of the established method ranged 70.51-116.45%, with relative standard deviations (RSD) of <9.40%. The limit of detection (S/N = 3) was as low as 0.19 μg/L (as CS2), which is superior to the previous methods and comparable to UPLC-tandem mass spectrometry (MS/MS). Moreover, the proposed approach does not require solid-phase extraction and offers excellent selectivity. This study proposes a novel method for the detection of DTCs in the food safety and environmental fields.

Sample Preparation Methods for Metal Containing Pesticides in Food and Environmental Samples

Metal-containing pesticides are used in many areas for purposes such as harvest efficiency and keeping pests away from the vegetable environment. Metal-containing pesticides are in the form of dithiocarbamate complexes and are named differently according to the type of metal they contain and are used for different purposes. Since the presence of these pesticides even at residue level threatens human and environmental health, their determination at trace level is important. In this review, studies on the determination of metal-containing dithiocarbamate pesticides in different matrices are discussed. This review on the analysis of dithiocarbamate pesticides with different techniques will shed light on the studies to be carried out for the determination of these pesticides one by one in different matrices.

Rapid quantitative analysis of calcium in infant formula powder assisted by long short-term memory with variable importance using laser-induced breakdown spectroscopy

Calcium is the main mineral responsible for healthy bone growth in infants. Laser-induced breakdown spectroscopy (LIBS) was combined with a variable importance-based long short-term memory (VI-LSTM) for the quantitative analysis of calcium in infant formula powder. First, the full spectra were used to establish PLS (partial least squares) and LSTM models. The R2 and root-mean-square error (RMSE) of the test set (R P2 and R M S E _P) were 0.1460 and 0.0093 in the PLS method, respectively, and 0.1454 and 0.0091 in the LSTM model, respectively. To improve the quantitative performance, variable selection based on variable importance was introduced to evaluate the contribution of input variables. The variable importance-based PLS (VI-PLS) model had R P2 and R M S E _P of 0.1454 and 0.0091, respectively, whereas the VI-LSTM model had R P2 and R M S E _P of 0.9845 and 0.0037, respectively. Compared with the LSTM model, the number of input variables in the VI-LSTM model was reduced to 276, R P2 was improved by 114.63%, and R M S E _P was reduced by 46.38%. The mean relative error of the VI-LSTM model was 3.33%. We confirm the predictive ability of the VI-LSTM model for the calcium element in infant formula powder. Thus, combining VI-LSTM modeling and LIBS has great potential for the quantitative elemental analysis of dairy products.