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Background: Acetamiprid, as a low-toxicity pesticide, has already been extensively used to increase plant production and quality. Although fipronil has been prohibited, it is usually illicitly added to acetamiprid due to its particular insecticidal action and effect, so it is highly desirable to obtain a rapid and effective method to detect its concentration. Mid-infrared spectroscopy (MIR) combined with two variable selection methods, interval combination optimization (ICO) and interval partial least squares (iPLS), were used to determinate the prohibited addition of fipronil., Results: The full spectra for both ICO and iPLS were divided into 40 equal-width intervals. Consequently, 45 and 135 characteristic variables were extracted from ICO and iPLS to establish the models. Compared with iPLS, the ICO model acquired a more suitable spectral region and as a result gained a higher prediction accuracy. Specifically, the ICO method selected the characteristic wavelengths ascribed to CF and CN (in five-membered heterocyclics), iPLS chose the intervals associated with CF and SO., Conclusion: Results revealed that MIR combined with ICO could be efficiently used for rapid identification of illegal addition and had great potential to provide on-site pesticide quality control. © 2018 Society of Chemical Industry., (© 2018 Society of Chemical Industry.)

A novel chemometrical method, named as MWS-ECARS, which is based on using the moving window smoothing upon an ensemble of competitive adaptive reweighted sampling, is proposed as the spectral variable selection approach for multivariate calibration in this study. In terms of elimination of uninformative variables, an ensemble of CARS is carried out first and MWS is then performed to search for effective variables around the high frequency variables. The variable subset with the lowest standard error of cross-validation (SECV) is treated as the optimal threshold and the corresponding moving window width is regarded as the optimal window width. The method was applied to mid-infrared (MIR) spectra of active ingredient in pesticide, near-infrared (NIR) spectra of soil organic matter and NIR spectra of total nitrogen in Solanaceae plants for variable selection. Overall results show that MWS-ECARS is a promising selection method with an improved prediction performance over three variable selection methods of variable importance projection (VIP), uninformative variables elimination (UVE) and genetic algorithms (GA)., (Copyright © 2019 Elsevier B.V. All rights reserved.)

A simple and efficient directly suspended droplet microextraction (DSDME) has been developed to extract and pre-concentrate organochlorine and pyrethrin pesticides from tea samples prior to analysis by a gas chromatography-electron capture detector (GC-ECD). The optimal experimental conditions of DSDME were: 100 μL isooctane exposed for 15 min to 5 mL of the tea aqueous sample stirred at 1100 rpm. For most of the target analytes, the optimal pretreatment of DSDME processes led to no significant interference of tea matrices. The approach was applied to the determination of organochlorine and pyrethroid pesticides in tea samples, with a linearity range of 0.0005-2 μg/mL. The relative recoveries of all the pesticides ranged between 80.0% and 120.8% with relative standard deviations (RSDs) in the range of 0.8-19.9% (n=5). The limits of detections (LODs) ranged between 0.04 and 1 μg/L for all the target pesticides., (Copyright © 2012 Elsevier B.V. All rights reserved.)

• A pesticide IR spectral database was established. • An IR-based pre-treatment method was proposed. • The method can eliminate the negative effect of pesticide formulation. The public concern and increasing awareness of pesticide calls for methods available to assure quality and authenticity. Spectra matching is widely used in various applications including the search for a spectrum of an unknown compound in an existing spectral database and quality control by means of comparing the spectra of products with standards. Although the infrared spectroscopy (IR) fingerprint has many applications in a lot of areas, there are several limitations in pesticide. The pesticide formulation is a significant impediment against analyzing IR fingerprint of pesticide with similarity estimation. In the present study, a novel strategy combining Fourier-transform infrared spectroscopy (FT-IR) analysis was developed and validated to allow comprehensive analysis and rapid authentication of pesticide. A pesticide IR spectral database which included 604 pesticide standards was established. A simple, fast, and environmentally friendly IR-based pre-treatment method was proposed that can eliminate the negative effect of pesticide formulation on similarity estimation. In order to verify the effectiveness of proposed method, 30 pesticide samples were randomly collected from market, including liquid and solid, with the concentration of active components from 1% to 80%. For 30 samples, the proposed strategy resulted in a 90% accuracy rate and a 3.33% error rate based on the liquid chromatography (LC) data. It is therefore clear that IR spectral database combining with the proposed pre-treatment appear to be a promising tool for monitoring and analysis in the pesticide industry. [ABSTRACT FROM AUTHOR]

• A global model is developed for the determination of prohibited addition in pesticide formulations by NIR. • The global model is developed according to PLS and CARS-SPA. • The model is described from two aspects: the algorithm strategy and spectroscopy interpretation. • F-test is carried out to see whether significant differences are generated between the models. Generally, a pesticide was determined by a specific model, so different models were established for different pesticides as the backgrounds between pesticides formulations were with relatively huge discrepancy. It is expected to develop a more adaptive model which could not only improve the efficiency for prohibited addition detection but also afford an extensive application of the target pesticide. Moreover, less time would be spent on maintaining the model and thus the model supervision ability would be improve. In this paper, a global model for the determination of fipronil in a mixed matrix of imidacloprid and cypermethrin formulations was developed. The global model was established by means of two chemometrics methods, namely: full spectrum partial least squares (PLS) and competitive adaptive reweighted sampling-successive projections algorithm (CARS-SPA). Furthermore, the global model was investigated by the following two aspects: algorithm strategies of PLS and CARS-SPA, and spectroscopy interpretation. Results revealed that CARS-SPA combined with NIR could be efficiently used for rapid identification of prohibited addition in imidacloprid and cypermethrin formulations. Simultaneously, this study provided a theoretical support in the aspect of developing a global model for quantitative analysis. [ABSTRACT FROM AUTHOR]