Statistical and chemometric view of the variation in the concentration of selected organophosphates in peeled unwashed and unpeeled washed fruits and vegetables.

Fruits and vegetables play an important role in human nutrition. Study of the contamination sources which result from farming activities is of importance. For this reason, a chitosan-graphene oxide nanocomposite film was prepared and implemented as the extractive phase in thin film microextraction of six organophosphate residues (OPPs) in the samples using high-performance liquid chromatography. The optimized method was validated and the limits of detection (0.7-1.2 µg l-1), limits of quantification (2.3-4.0 µg l-1) and linear dynamic range (2.0-1000.0 µg l-1) were obtained. Principal component analysis revealed clustering of the fruit and vegetable samples based on the selected (OPPs) into two groups of unwashed-unpeeled and peeled-washed. This mapping was further investigated using descriptive method of boxplot. Washing and peeling of the samples, reduced the presence of OPPs to half or one third of interquartile range found in the unpeeled and unwashed samples.

Classification of cow milk using artificial neural network developed from the spectral data of single- and three-detector spectrophotometers.

Spectra data from two instruments (UV-Vis/NIR and FT-NIR) consisting of three and one detectors, respectively, were employed in order to discriminate the geographical origin of milk as a way to detect adulteration. Initially, principal component analysis (PCA) was used to see if clusters of milk from different origins are formed. Separation between samples of different origins were not observed with PCA, hence, feed-forward multi-layer perceptron artificial neural network (MLP-ANN) models were designed. ANN models were developed by changing the number of input variables and the best models were chosen based on high values of generalized R-square and entropy R-square, as well as small values of root mean square error (RMSE), mean absolute deviation (Mean Abs. Dev), and -loglikelihood while considering 100% classification rate. Based on the results, whether the spectra data was collected from a single or three detector instrument the same clustering was observed based on geographical origin.

Graphene oxide-starch-based micro-solid phase extraction of antibiotic residues from milk samples.

In this study, a method was described for the extraction of three antibiotic residues from cow milk samples using a graphene oxide-starch-based nanocomposite. The prepared nanocomposites were employed as an extractive phase for micro-solid phase extraction of antibiotics from cow milk samples. The extracted antibiotics, i.e. amoxicillin, ampicillin and cloxacillin, were subsequently analyzed by high-performance liquid chromatography-ultraviolet detection (HPLC-UV). Important variables associated with the extraction and desorption efficiency were optimized. High extraction efficiencies for the selected antibiotics were conveniently achieved using the starch-based nanocomposite as the extractive phase. The developed method was validated according to the European Commission Decision 2002/657/EC by spiking the selected antibiotics to the blank milk samples. The limits of quantitation (2.7-5.0 µg kg-1) were calculated for the selected penicillin group in milk samples and their quantities are lower than the maximum residue limits (MRLs). The obtained results indicate the remarkable efficiency of the graphene oxide-starch-based nanocomposite performance toward the selected antibiotics. The relative standard deviations of intra and inter-day analysis are less than 3.3 and 6.1%, respectively. Moreover, trueness of method was successfully accomplished via the recovery assays (88-102%) in the fortified blank milk samples with three different concentration levels (MRL, 1.5 MRL and 3 MRL µg kg-1). In overall, the proposed method was a promising alternative for analysis of selected three antibiotics in variety milk samples, due to the effective and easy-to-perform method and acceptable relative recovery in the range 83-105%.

Porous eco-friendly fibers for on-line micro solid-phase extraction of nonsteroidal anti-inflammatory drugs from urine and plasma samples.

In this study, cellulose acetate (CA) fibers were prepared using different solvent systems in electrospinning. The recorded scanning electron microscopy micrographs indicated that the morphology of the prepared fibers is closely associated with the type of electrospinning solvents. The prepared CA fibers were used as an extractive phase for on-line micro-solid phase extraction (µ-SPE) of nonsteroidal-inflammatory drugs (NSAIDs) in biological samples pursued by HPLC-UV determination. Work conducted on this research ascertained that the use of dichloromethane:acetone (3:1, v/v) solvent system in the CA dissolution for electrospinning, leads to the formation of porous ribbon-like fibers and subsequent excellent extraction efficiencies for the selected drugs. Moreover, the effects of diverse parameters on the extraction efficiency were surveyed and optimized. The proposed method was used for determination of naproxen, diclofenac and mefenamic acid in human urine and plasma samples. The optimized method was validated and the limits of detection (1.0-2.4 µg L-1), limits of quantification (3.3-8.0 µg L-1) and linear dynamic range (4.0-1000.0 µg L-1) were obtained. The reproducibility (relative standard deviation: 2.6-7.9%) was in an acceptable range. Trueness of the procedure was accomplished through recovery assays in urine (94-105%) and plasma (85-102%) samples, indicating the minor contribution from the sample matrix. Finally, the CA porous fibers within the framework of the µ-SPE method were found to be appropriate for the separation and determination of the selected drugs in urine and plasma samples collected from treated patients. Also, the adsorption behavior of the porous fibers was well described by Freundlich isotherm and porous fibers showed acceptable adsorption capacity.

Geochemical characteristics of rare earth elements in different types of soil: A chemometric approach.

Rare earth elements (REEs) are becoming significant due to their huge applications in many industries, large-scale mining and refining activities. Increasing usage of such metals pose negative environmental impacts. In this research ICP-MS has been used to analyze soil samples collected from former ex-mining areas in the depths of 0-20 cm, 21-40 cm, and 41-60 cm of residential, mining, natural, and industrial areas of Perak. Principal component analysis (PCA) revealed that soil samples taken from different mining, industrial, residential, and natural areas are separated into four clusters. It was observed that REEs were abundant in most of the samples from mining areas. Concentration of the rare elements decrease in general as we move from surface soil to deeper soils.

Isotopic ratio analysis of cattle tail hair: A potential tool in building the database for cow milk geographical traceability.

The potential for the isotopic ratio analysis of cattle tail hair in determining the geographical origin of raw cow milk in Peninsular Malaysia had been investigated in this research using exploratory visualization. A significant positive correlation (p<0.0001) (n=54) was noticed between δ(13)C and δ(15)N in milk with that of hair which indicated that these matrices could be used in tracing the geographical origin of animal produce and tissues, and there is a possibility that hair could be used as a substitute in building the database for the geographical traceability of milk. It was also observed that both hair and milk isotopic ratio correlations exhibited separation between the northern and southern regions. The accuracy of using isotopic ratio in determining geographical discrimination had been clearly demonstrated when several commercial milk samples from the same regions under the study were correctly assigned to the appropriate geographical clusters.

A simple design for microwave assisted digestion vessel with low reagent consumption suitable for food and environmental samples.

The objective of this work is to prepare a cost-effective, low reagent consumption and high performance polytetrafluoroethylene (PTFE) vessel that is capable to work in domestic microwave for digesting food and environmental samples. The designed vessel has a relatively thicker wall compared to that of commercial vessels. In this design, eight vessels are placed in an acrylonitrile butadiene styrene (ABS) holder to keep them safe and stable. This vessel needs only 2.0 mL of HNO3 and 1.0 mL H2O2 to digest 100 mg of biological sample. The performance of this design is then evaluated with an ICP-MS instrument in the analysis of the several NIST standard reference material of milk 1849a, rice flour 1568b, spinach leave 1570a and Peach Leaves 1547 in a domestic microwave oven with inverter technology. Outstanding agreement to (SRM) values are observed by using the suggested power to time microwave program, which simulates the reflux action occurring in this closed vessel. Taking into account the high cost of commercial microwave vessels and the volume of chemicals needed for various experiments (8-10 mL), this simple vessel is cost effective and suitable for digesting food and environmental samples.