A novel fluorimetric method for glyphosate and AMPA determination with NBD-Cl and MCR-ALS.

We report the development of a new analytical method for the quantification of N-(phosphonomethyl)glycine (glyphosate) and (aminomethyl)phosphonic acid (AMPA) by combining spectrofluorimetry and multivariate calibration. In this study, fluorescence spectroscopy was used to quantify glyphosate and AMPA, which were previously derivatized with the fluorogenic reagent: 4-chloro-7-nitrobenzofurazan (NBD-Cl). Fluorescence excitation-emission matrices (EEM) were recorded by exciting between 400 and 500 nm, and measuring the emission between 500 and 610 nm.

Open-Source Assisted Laboratory Automation through Graphical User Interfaces and 3D Printers: Application to Equipment Hyphenation for Higher-Order Data Generation.

Higher-order data generation implies some automation challenges, which are mainly related to the hidden programming languages and electronic details of the equipment. When techniques and/or equipment hyphenation are the key to obtaining higher-order data, the required simultaneous control of them demands funds for new hardware, software, and licenses, in addition to very skilled operators. In this work, we present Design of Inputs-Outputs with Sikuli (DIOS), a free and open-source code program that provides a general framework for the design of automated experimental procedures without prior knowledge of programming or electronics.

Modeling four and three-way fast high-performance liquid chromatography with fluorescence detection data for quantitation of fluoroquinolones in water samples.

This paper presents a study regarding the acquisition and analytical utilization of four and three-way data, acquired by following the excitation-emission fluorescence matrices at different elution times, in a fast liquid chromatographic HPLC procedure. This kind of data were implemented for first time for quantitative purposes, and applied to the determination of two fluoroquinolones in tap water samples, as a model to show the potentiality of the proposed strategy of four-way data generation. The data were modeled with three well-known algorithms: PARAFAC, U-PLS/RTL and MCR-ALS, the latter conveniently adapted to model third-order data.

Multivariate curve resolution modeling of liquid chromatography-mass spectrometry data in a comparative study of the different endogenous metabolites behavior in two tomato cultivars treated with carbofuran pesticide.

A metabonomic study based on the application of multivariate curve resolution and alternating least squares (MCR-ALS) to three-way data sets obtained by liquid chromatography coupled to mass spectrometry detection (LC-MS) was carried out for Rambo and Raf tomato cultivars treated with carbofuran pesticide. Samples were picked up during a 21 days period after treatment and analyzed by LC-MS in scan mode, along with the corresponding blank samples. Then, MCR-ALS was applied to the three-way data sets using column wise augmented matrices, and the evolutionary profiles as a function of the time after treatment were estimated for the metabolites present in both cultivars, as well as their corresponding pure spectra estimations.

Detection of unintended stress effects based on a metabonomic study in tomato fruits after treatment with carbofuran pesticide. Capabilities of MCR-ALS applied to LC-MS three-way data arrays.

A chemometric strategy based on multivariate curve resolution and alternating least-squares (MCR-ALS) applied to LC-MS three-way data arrays has been developed to perform a metabonomic study in tomato (Lycopersicon esculentum) fruits (cultivar Rambo) following treatment with carbofuran. This methodology has proved to be adequate for the detection of unintended stress effects due to the previous treatment with this pesticide. MCR-ALS was performed on augmented matrices built with the LC-MS three-way data obtained from treated and nontreated samples through the sampling time.

Calibration maintenance and transfer using Tikhonov regularization approaches.

Maintaining multivariate calibrations is essential and involves keeping models developed on an instrument applicable to predicting new samples over time. Sometimes a primary instrument model is needed to predict samples measured on secondary instruments. This situation is referred to as calibration transfer.