UV-MALDI mass spectrometric quantitation of uracil based pesticides in fruit soft drinks along with matrix effects evaluation

3-Cyclohexyl-6-phenyl-1-(p-tolyl)pyrimidine-2,4(1H,3H)-dione

The synthesis of a novel uracil derivative, 3-cyclohexyl-6-phenyl-1-(p-tolyl)pyrimidine-2,4(1H,3H)-dione (4), is reported via a four-component reaction involving an α-chloroketone (1), an aliphatic isocyanate (2), a primary aromatic amine (3) and carbon monoxide. The proposed reaction mechanism involves a Pd-catalyzed carbonylation of 2-chloro-1-phenylethan-1-one (1), leading to a β-ketoacylpalladium key intermediate, and, at the same time, in situ formation of non-symmetrical urea deriving from cyclohexyl isocyanate (2) and p-toluidine (3). After a chemo-selective acylation of the non-symmetrical urea and the subsequent cyclization of the acylated intermediate, 3-cyclohexyl-6-phenyl-1-(p-tolyl)pyrimidine-2,4(1H,3H)-dione (4) is formed. Uracil derivative 4 was isolated in good yield (73%) and fully characterized by 1H, 13C, 2D 1H-13C HSQC and 2D 1H-13C HMBC NMR, FT-IR spectroscopy and GC-MS spectrometry.

High-throughput screening and spatial profiling of low-mass pesticides using a novel Ti3C2 MXene nanowire (TMN) as MALDI MS matrix

Pesticides play critical roles in agricultural fields; however, pesticide residues can cause serious damage to human health and the ecological environment; therefore, developing a rapid and sensitive method for pesticide detection is urgently needed. Nanostructure-assisted matrix laser desorption/ionization (MALDI) mass spectrometry (MS) has great potential for the detection of low-mass pesticides. In this study, a novel Ti₃C₂ MXene nanowire (TMN) was prepared by a facile sol-gel method and served as a matrix to enhance MALDI MS performance in the analysis of pesticides in positive ion mode. The TMN showed superior performance in the high-throughput detection of six kinds of pesticides (organophosphorus, organochlorine, carbamate, neonicotinoids, triazole, and oxadiazines), with ultrahigh sensitivity (detection limits at sub-ppt levels), remarkable repeatability, excellent salt tolerance, and extremely low background compared to traditional organic matrices due to the specific polyaromatic structure and the doping of nitrogen. Furthermore, this matrix was successfully employed for the analysis of residual pesticides in traditional Chinese herbs, and the level of diniconazole was quantified with a linear range of 0-50 ng/mL (R² > 0.99). More importantly, the spatial distribution of various endogenous compounds (e.g., amino acids and saccharides, fatty acids, alkaloids, and plant hormones) and xenobiotic pesticides from the intact root of the medicinal plant P. quinquefolium was clearly visualized using the TMN self-assembly film as a matrix for MALDI imaging mass spectrometry (IMS). With superior advantages such as sensitivity, simplicity, rapidness, and minimal sample requirement, TMN as a matrix-assisted MALDI MS shows great promise for various applications.

Worldwide survey of pesticide residues in citrus-flavored soft drinks

After more than ten years since pesticide residues were detected in citrus-flavored soft drinks, this study reveals that the situation has not changed. A new sensitive multiresidue UHPLC-MS/MS method has been validated for 88 pesticides, which was used to analyze 200 samples manufactured in 67 countries, 80% corresponding to fruit-based soft drinks. The results show that 98% of the samples collected worldwide contained at least one pesticide, and 85% of them contained more than 4 pesticides. 40 out of 88 target compounds were quantified among the screened samples. Europe was the world region with the highest total amount of pesticides, probably due to the higher content of juice concentrate in samples, which may be the main source of the pesticide residues. Nevertheless, residues were also found in samples with no juice, so water quality also plays an important role as the main ingredient of citrus-flavored soft drinks.

Nanoplasmonic sensor array for the detection and discrimination of pesticide residues in citrus fruits

Great attention has been directed towards developing rapid and straightforward methods for the identification of various pesticides that are usually used simultaneously in citrus fruits. The extensive use of diverse classes of pesticides in citrus fruits and their high toxicity may cause serious diseases in the human body. In the current study, a non-enzymatic sensor array has been developed for the identification and discrimination of five different pesticides belonging to diverse classes, including organophosphate, carbamate, and bipyridylium. For this aim, two gold nanoparticles (AuNPs) with different capping agents, citrate and borohydride, were used as sensing elements. The aggregation-induced spectra alterations of AuNPs were utilized to identify the pesticides in a wide range of concentrations (20-5000 ng mL-1). We have employed data visualization methods (i.e., heat maps, bar plots, and color difference maps), a supervised pattern recognition method (i.e., linear discrimination analysis), and partial least squares regression to qualitatively and quantitatively determine the pesticides. Finally, the practical applicability of the developed sensor array was evaluated for the identification of target pesticides in lime peel. The outcomes revealed that the probe could accurately verify the absence or presence of the pesticides in lime fruit.

Matrix Effects and Interferences of Different Citrus Fruit Coextractives in Pesticide Residue Analysis Using Ultrahigh-Performance Liquid Chromatography-High-Resolution Mass Spectrometry

The matrix effects of ethyl acetate extracts from seven different citrus fruits on the determination of 80 pesticide residues using liquid chromatography coupled to high-resolution time-of-flight mass spectrometry (UHPLC-(ESI)-HR-TOF) at 4 GHz resolution mode were studied. Only 20% of the evaluated pesticides showed noticeable matrix effects (ME) due to coelution with natural products between t_R = 3 and 11 min. Principal component analysis (PCA) of the detected coextractives grouped the mandarins and the orange varieties, but separated lemon, oranges, and mandarins from each other. Matrix effects were different among species but similar between varieties, forcing the determination of pesticide residues through matrix-matched calibration curves with the same fruit. Twenty-three natural products (synephrine, naringin, poncirin, glycosides of hesperitin, limonin, nomilin, and a few fatty acids, among others) were identified in the analyzed extracts. Twelve of the identified compounds coeluted with 28 of the pesticides under study, causing different matrix effects.