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.
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.
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.
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.