Use of experimental designs for the optimization of stir bar sorptive extraction coupled to GC–MS/MS and comprehensive validation for the quantification of pesticides in freshwaters

Prediction of the accumulation behavior of pesticides in PDMS-coated stir bars used as passive samplers in freshwaters

Passive samplers accumulate organic contaminants at rates that depend on in-field exposure conditions such as freshwater flow velocity, water temperature and water quality. Time-weighted average concentrations can be determined by using a correction process such as the performance reference compound (PRC) method. This study presented a new approach to predict the accumulation behavior of pesticides in polydimethylsiloxane-coated stir bars under different exposure conditions and assign a specific PRC to each pesticide for quantitative purposes. We used an experimental design with eight simultaneous accumulation kinetics of 13 pesticides and elimination kinetics of three PRC candidates run in a flow-through system to determine the effects of flow velocity, water temperature and dissolved organic matter on the kinetic constants. We identified the parameters that had a significant effect on the accumulation of each pesticide and assigned a PRC candidate to each pesticide. We then used a discriminant function analysis to find the parameters that had a significant effect on accumulation of the 13 pesticides via their physical-chemical properties and to predict through a stochastic approach the parameters for seven other pesticides. This approach provides a better framework for identifying a PRC than conventional methods to determine unbiased concentrations in future monitoring efforts.

Optimizing Mass Spectrometry Analyses: A Tailored Review on the Utility of Design of Experiments

Mass spectrometry (MS) has emerged as a tool that can analyze nearly all classes of molecules, with its scope rapidly expanding in the areas of post-translational modifications, MS instrumentation, and many others. Yet integration of novel analyte preparatory and purification methods with existing or novel mass spectrometers can introduce new challenges for MS sensitivity. The mechanisms that govern detection by MS are particularly complex and interdependent, including ionization efficiency, ion suppression, and transmission. Performance of both off-line and MS methods can be optimized separately or, when appropriate, simultaneously through statistical designs, broadly referred to as "design of experiments" (DOE). The following review provides a tutorial-like guide into the selection of DOE for MS experiments, the practices for modeling and optimization of response variables, and the available software tools that support DOE implementation in any laboratory. This review comes 3 years after the latest DOE review (Hibbert DB, 2012), which provided a comprehensive overview on the types of designs available and their statistical construction. Since that time, new classes of DOE, such as the definitive screening design, have emerged and new calls have been made for mass spectrometrists to adopt the practice. Rather than exhaustively cover all possible designs, we have highlighted the three most practical DOE classes available to mass spectrometrists. This review further differentiates itself by providing expert recommendations for experimental setup and defining DOE entirely in the context of three case-studies that highlight the utility of different designs to achieve different goals. A step-by-step tutorial is also provided.

Optimization of ultrasonic-assisted extraction for determination of polycyclic aromatic hydrocarbons in biochar-based fertilizer by gas chromatography-mass spectrometry

Application of biochar-based fertilizers is increasingly being considered for its potential agronomic and environmental benefits. However, biochar may contain residues of polycyclic aromatic hydrocarbons (PAHs) as a result of its production by pyrolysis. The strong adsorption of PAHs to biochar makes extraction and analysis of biochar-based fertilizers difficult. This study optimizes the extraction of PAHs in biochar-based fertilizer samples by using an ultrasonic bath for quantification by gas chromatography-mass spectrometry. Among 12 solvents, acetone-cyclohexane (1:1) mixture was selected as the optimum solvent for extraction. Three variables affecting the extraction were studied by Box-Behnken design. The optimum conditions were 57 °C extraction temperature, 81 min extraction time, and two extraction cycles, which were validated by assessing the linearity of analysis, LOD, LOQ, recovery, and levels of PAHs in real biochar-based fertilizer samples. Results revealed that the 16 U.S. EPA PAHs had good linearity, with squared correlation coefficients greater than 0.99. LODs were low, ranging from 2.2 ng g(-1) (acenaphthene) to 23.55 ng g(-1) (indeno[1,2,3-cd]perylene), and LOQs varied from 7.51 ng g(-1) to 78.49 ng g(-1). The recoveries of 16 individual PAHs from the three biochar-based fertilizer samples were 81.8-109.4 %. Graphical Abstract Use of RSM to optimize UAE for extraction of the PAHs in biochar-based fertilizer.

Determination of Nicotine in Tobacco by Chemometric Optimization and Cation-Selective Exhaustive Injection in Combination with Sweeping-Micellar Electrokinetic Chromatography

Nicotine is a potent chemical that excites the central nervous system and refreshes people. It is also physically addictive and causes dependence. To reduce the harm of tobacco products for smokers, a law was introduced that requires tobacco product containers to be marked with the amount of nicotine as well as tar. In this paper, an online stacking capillary electrophoresis (CE) method with cation-selective exhaustive injection sweeping-micellar electrokinetic chromatography (CSEI-sweeping-MEKC) is proposed for the optimized analysis of nicotine in tobacco. A higher conductivity buffer (160 mM phosphate buffer (pH 3)) zone was injected into the capillary, allowing for the analytes to be electrokinetically injected at a voltage of 15 kV for 15 min. Using 50 mM sodium dodecyl sulfate and 25% methanol in the sweeping buffer, nicotine was detected with high sensitivity. Thus, optimized conditions adapted from a chemometric approach provided a 6000-fold increase in the nicotine detection sensitivity using the CSEI-sweeping-MEKC method in comparison to normal CZE. The limits of detection were 0.5 nM for nicotine. The stacking method in combination with direct injection which matrix components would not interfere with assay performance was successfully applied to the detection of nicotine in tobacco samples.