Chromatographic quantification of seven pesticide residues in vegetable: Univariate and multiway calibration comparison

Chromatographic Applications in the Multi-Way Calibration Field

In this review, recent advances and applications using multi-way calibration protocols based on the processing of multi-dimensional chromatographic data are discussed. We first describe the various modes in which multi-way chromatographic data sets can be generated, including some important characteristics that should be taken into account for the selection of an adequate data processing model. We then discuss the different manners in which the collected instrumental data can be arranged, and the most usually applied models and algorithms for the decomposition of the data arrays. The latter activity leads to the estimation of surrogate variables (scores), useful for analyte quantitation in the presence of uncalibrated interferences, achieving the second-order advantage. Recent experimental reports based on multi-way liquid and gas chromatographic data are then reviewed. Finally, analytical figures of merit that should always accompany quantitative calibration reports are described.

A Review on Prediction Models for Pesticide Use, Transmission, and Its Impacts

The lure of increased productivity and crop yield has caused the imprudent use of pesticides in great quantity that has unfavorably affected environmental health. Pesticides are chemicals intended for avoiding, eliminating, and mitigating any pests that affect the crop. Lack of awareness, improper management, and negligent disposal of pesticide containers have led to the permeation of pesticide residues into the food chain and other environmental pathways, leading to environmental degradation. Sufficient steps must be undertaken at various levels to monitor and ensure judicious use of pesticides. Development of prediction models for optimum use of pesticides, pesticide management, and their impact would be of great help in monitoring and controlling the ill effects of excessive use of pesticides. This paper aims to present an exhaustive review of the prediction models developed and modeling strategies used to optimize the use of pesticides.

Chromatographic Methods for Detection and Quantification of Carbendazim in Food

Carbendazim (CBZ), which is a fungicide widely used for the management of plant diseases, has been detected in a number of food products. The negative effects of CBZ to human health have stimulated the reduction of the maximum residue limits (MRLs), and subsequently the development of reliable and sensitive detection methods. Here, we are reviewing for the first time all reported chromatographic methods for the detection and quantification of CBZ in food. Several techniques, including liquid chromatography (LC), thin layer chromatography (TLC), micellar electrokinetic chromatography (MEKC), and supercritical fluid chromatography (SFC), were used for the separation and detection of CBZ, showing diverse characteristics and sensitivity. Some methods allowed the specific determination of CBZ, whereas other methods were successfully applied for the simultaneous quantification of a huge number of pesticides. Most reported methods showed limits of detection (LOD) and quantification (LOQ) lower than the MRLs. Relevant efforts in the field have been directed toward the simplification and optimization of the extraction steps prior to the chromatographic separation to increase the recovery and reduce the matrix effects. In this Review, the matrices, extraction procedures, and separation and detection parameters are detailed and compared in order to provide new insights on the development of new reliable methods for the detection of CBZ in food.

Multiblock modelling on the study of the kinetic degradation of rosuvastatin calcium in the presence of retention time shifts and rank deficiency

In pharmaceutical development, forced degradation studies are mandatory before the commercialization of any drug product. They aim at identifying the possible degradation routes and the potential products that may be formed during drug product shelf life. The most widely used techniques for monitoring this in the pharmaceutical industry are hyphenated techniques such as Liquid Chromatography coupled to ultraviolet diode array detector (LC-DAD). There are however some drawbacks, such as long analysis times required for the elution of all compounds and coelution, which is not easily detected since degradation products usually have spectra very similar to that of the drug. Chemometrics methods applied to LC-DAD data are capable of solving this issue, but the approaches described in the literature first require peak alignment to solve the rank deficiency problem, which is a delicate preprocessing method for high order data. The present work describes another approach where extra information - the kinetic degradation profiles - is included for the modelling, generating a third-order data set for each sample, resulting in a four-way array (sample x retention times x spectra x degradation profile). This approach has the advantage of using the information in the third mode to solve the peak co-elution problem without the need for peak alignment among samples. With the proposed approach, it was possible to study the degradation of calcium rosuvastatin, a modern cholesterol lowering drug, using a 2 min-run, despite all the challenges in the modelling of this data. The proposed strategy was compared to an approach based on augmenting the matrix in the spectral/kinetic modes (second order modelling strategy).