Norashikin Saim

Chemometric application in identifying sources of organic contaminants in Langat river basin

Increasing urbanization and changes in land use in Langat river basin lead to adverse impacts on the environment compartment. One of the major challenges is in identifying sources of organic contaminants. This study presented the application of selected chemometric techniques: cluster analysis (CA), discriminant analysis (DA), and principal component analysis (PCA) to classify the pollution sources in Langat river basin based on the analysis of water and sediment samples collected from 24 stations, monitored for 14 organic contaminants from polycyclic aromatic hydrocarbons (PAHs), sterols, and pesticides groups. The CA and DA enabled to group 24 monitoring sites into three groups of pollution source (industry and urban socioeconomic, agricultural activity, and urban/domestic sewage) with five major discriminating variables: naphthalene, pyrene, benzo[a]pyrene, coprostanol, and cholesterol. PCA analysis, applied to water data sets, resulted in four latent factors explaining 79.0% of the total variance while sediment samples gave five latent factors with 77.6% explained variance. The varifactors (VFs) obtained from PCA indicated that sterols (coprostanol, cholesterol, stigmasterol, β-sitosterol, and stigmastanol) are strongly correlated to domestic and urban sewage, PAHs (naphthalene, acenaphthene, pyrene, benzo[a]anthracene, and benzo[a]pyrene) from industrial and urban activities and chlorpyrifos correlated to samples nearby agricultural sites. The results demonstrated that chemometric techniques can be used for rapid assessment of water and sediment contaminations.

Two-phase electrodriven membrane extraction combined with liquid chromatography for the determination of tricyclic antidepressants in aqueous matrices

A two-phase low-voltage electrodriven membrane extraction (EME) method combined with high performance liquid chromatography (HPLC) was developed for the determination of tricyclic antidepressants (TCAs) in aqueous matrices. Three TCAs, namely imipramine (IMI), amitriptyline (AMI) and chlorpromazine (CHLO) were used as target analytes. The drugs were extracted from aqueous sample solutions through a porous polypropylene membrane filter impregnated with 2-nitrophenyl octyl ether (NPOE) that served as a supported liquid membrane (SLM), and into an acceptor phase with a potential difference of 10 V applied over the SLM. EME parameters such as the type of organic solvent, the pH of sample solution, the extraction voltage, extraction time and stirring rate were evaluated and optimized. Optimal extractions were accomplished using NPOE as the organic solvent, a sample solution of pH 6, an extraction time of 10 min, and 10 V as the driving force with the whole assembly agitated at 1200 rpm. Under the optimized extraction conditions, the method demonstrated good linearity with coefficients of determination, r2 ≥ 0.9987 in the concentration range of 0.5–1000 µg L−1 for water, and 1.0–1000 µg L−1 for urine and good limits of detection in the range of 0.05–0.08 µg L−1 and 0.1–0.3 µg L−1 in water and urine samples, respectively. The method showed high enrichment factors in the range of 91–128 and high relative recoveries in the range of 98.4–103.1% and 86.7–107.4%, for water and urine samples, respectively with RSDs of <9.0% (n = 3). This method was successfully applied to the determination of the drugs in water and human urine samples. The proposed method offered good features such as simplicity, easy handling, fast extraction time, low voltage and minimum organic solvent consumption which meet the green chemistry concept.

Determination of Phthalate Plasticisers in Palm Oil Using Online Solid Phase Extraction-Liquid Chromatography (SPE-LC)

Contamination of phthalates plasticisers to food has raised concern as some of the phthalates are suspected to be endocrine disruptors. The phthalates have high affinity with oily environment and analysing these chemicals in such matrices is difficult because of the trace amount of the analyte and interference from matrix. An online solid phase extraction (SPE) technique using a large volume (3.5 mL) injection was developed for the analysis of 6 common plasticisers in palm oil. A simple sample preparation involving alumina as a fat retainer and methanol : acetonitrile (1 : 1) as the extraction solvent was performed prior to the usage of online SPE-LC system. This system consists of two columns, C16 for the solid phase extraction (SPE) and C18 as the analytical column, and a photo diode array detector. The calibration curves were linear from 5 to 1000 g L−1, with correlation coefficients above 0.99. The instrumental limit of detection was 3 g L−1 and satisfactory recovery was obtained. A screening on a few samples in the retail market revealed the presence of dibutyl phthalate (DBP) and butylbenzylphthalate (BBP) in the palm oil, with concentration less than 1 mg L−1.

Selective Extraction of Organic Contaminants from Soil Using Pressurised Liquid Extraction

This study focuses on the application of sorbents in pressurised liquid extraction (PLE) cell to establish a selective extraction of a variety of organic contaminants (polycyclic aromatic hydrocarbons (PAHs), chlorpyrifos, phenol, pentachlorophenol, and sterols) from soil. The selectivity and efficiency of each sorbent depend on the properties of the material, extracting solvent, capacity factor, organic compounds of interest, and PLE operating parameters (temperature, pressure, and extraction time). Several sorbents (silica, alumina, and Florisil) were evaluated and with the proper choice of solvents, polar and nonpolar compounds were successfully separated in two fractions. Nonpolar compounds (PAHs, chlorpyrifos, and pentachlorophenol) were recovered in the first fraction using a polar sorbent such as Florisil or alumina, and n-hexane as eluting solvent, while more polar compounds (phenol and sterols) were recovered in the second fraction using methanol. Silica (5 g) was found to be effective for selective extraction with the satisfactory recoveries for all compounds (PAHs from 87.1–96.2%, chlorpyrifos 102.9%, sterols from 93.7–100.5%, phenol 91.9%, and pentachlorophenol 106.2%). The efficiency and precision of this extraction approach and the existing EPA Method 3545 were compared.

Development of Chromatographic Fingerprints of Eurycoma longifolia (Tongkat Ali) Roots Using Online Solid Phase Extraction-Liquid Chromatography (SPE-LC)

E. longifolia is attracting interest due to its pharmacological properties and pro-vitality effects. In this study, an online SPE-LC approach using polystyrene divinyl benzene (PSDVB) and C18 columns was developed in obtaining chromatographic fingerprints of E. longifolia. E. longifolia root samples were extracted using pressurized liquid extraction (PLE) technique prior to online SPE-LC. The effects of mobile phase compositions and column switching time on the chromatographic fingerprint were optimized. Validation of the developed method was studied based on eurycomanone. Linearity was in the range of 5 to 50 µg∙mL−1 (r2 = 0.997) with 3.2% relative standard deviation of peak area. The developed method was used to analyze 14 E. longifolia root samples and 10 products (capsules). Selected chemometric techniques: cluster analysis (CA), discriminant analysis (DA), and principal component analysis (PCA) were applied to the fingerprint datasets of 37 selected peaks to evaluate the ability of the chromatographic fingerprint in classifying quality of E. longifolia. Three groups were obtained using CA. DA yielded 100% correlation coefficient with 19 discriminant compounds. Using PCA, E. longifolia root samples were clearly discriminated from the products. This study showed that the developed online SPE-LC method was able to provide comprehensive evaluation of E. longifolia samples for quality control purposes.

Spatial Variation and Source Distribution of Organic Contaminants in Langat River Basin, Malaysia Using Chemometric Techniques

Monitoring organic contaminants is becoming an important feature in environmental forensic as they are potential chemical markers to pollution source identification. This study investigates the potential of using 13 selected organic contaminants (polycyclic aromatic hydrocarbons (PAHs), sterols, pesticides and phenol) to evaluate the spatial variation of 10 monitoring sites located along Langat River. Chemometric techniques namely, hierarchical agglomerative cluster analysis (HACA), discriminant analysis (DA), principal component analysis (PCA) and the factor analysis (FA) were used to assess the spatial variation of the selected organic contaminants and to relate them to their possible sources. HACA classified the sampling sites into three clusters, which can be correlated to the level of pollution. Forward and backward DA was able to discriminate two and seven organic contaminants variables, respectively, from the original 13 selected variables. PCA and FA (varimax functionality) were used to identify the possible sources of each organic contaminants based on inventory of local activities provided by the Department of Environment, Malaysia (DOE). Five principal components were obtained with 64.83 % of the total variation. Result from FA indicated that PAHs (pyrene, fluorene, acenaphthene, benzo[a]anthracene and benzo[a]pyrene) originated from industrial activity; while sterols (coprostanol, stigmastanol and β-sitosterol) were associated with domestic sewage and local socio-economic activities. The occurrence of phenol was correlated to industrial activities. This study shows that the application of chemometric techniques can reveal meaningful information on the spatial variability of a large and complex river water chemical data.

Nano Natural Dyes from Melastoma Malabathricum L.

In this study, natural colours were produced from Melastoma Malabathricum L.’s (Senduduk) plant. The dyes were extracted from the petal part of the plant using solvent extraction method of acidified methanol and methanol. The natural colours were then converted into powder form of nano size scale using a ball mill grinder. Silk fabrics were used as the substrate and dyed using several natural and synthetic mordant. The use of different solvents for extraction and mordant for dyeing resulted in different colour shades on the silk fabrics. The color fastness to washing tests revealed colour fastness to washing ranging from 3 – 4/5 and the change in color ranging from 3/4 – 4/5. The findings will benefit and promote the dyeing and printing industry such as batik manufacturers and local fashion industry in using natural dyes. On the other hand, dyes from plants can also be used as an alternative to synthetic dyes for dyeing natural silk fibers.

Ionic liquid-impregnated agarose film two-phase micro-electrodriven membrane extraction (IL-AF-μ-EME) for the analysis of antidepressants in water samples

The aim of this study was to investigate and apply supported ionic liquid membrane (SILM) in two-phase micro-electrodriven membrane extraction combined with high performance liquid chromatography-ultraviolet detection (HPLC-UV) for pre-concentration and determination of three selected antidepressant drugs in water samples. A thin agarose film impregnated with 1-hexyl-3-methylimidazolium hexafluorophosphate, [C6MIM] [PF6], was prepared and used as supported ionic liquid membrane between aqueous sample solution and acceptor phase for extraction of imipramine, amitriptyline and chlorpromazine. Under the optimized extraction conditions, the method provided good linearity in the range of 1.0-1000μgL-1, good coefficients of determination (r2=0.9974-0.9992) and low limits of detection (0.1-0.4μgL-1). The method showed high enrichment factors in the range of 110-150 and high relative recoveries in the range of 88.2-111.4% and 90.9-107.0%, for river water and tap water samples, respectively with RSDs of ≤7.6 (n=3). This method was successfully applied to the determination of the drugs in river and tap water samples. It is envisaged that the SILM improved the perm-selectivity by providing a pathway for targeted analytes which resulted in rapid extraction with high degree of selectivity and high enrichment factor.

Kaedah reka bentuk eksperimen bagi pengekstrakan eurikomanon daripada akar tongkat ali (Eurycoma longifolia) menggunakan pengekstrakan cecair tekanan tinggi

Pressurised liquid extraction (PLE) method was utilised to extract eurycomanone from Tongkat Ali root (Eurycoma longifolia) using water as extraction solvent. Optimisation of PLE operating parameters was conducted using three-factor response surface experimental design to evaluate the interactive effects of temperature (90 – 150 oC), extraction time (10 – 30 min) and pressure (850 – 1700 psi) on the yield of eurycomanone. Online solid phase extraction – high performance liquid chromatography (SPEHPLC) with a diode array detector (DAD) was used for the separation and detection of this compound. Extraction temperature was found significant in increasing the yield of eurycomanone. Based on maximum yield of eurycomanone, the optimum operating extraction conditions for PLE were set up at temperature (106 °C), pressure (870 psi) and static time (30 min). The amount of eurycomanone from Tongkat Ali root samples of various sources was analysed using the optimised PLE conditions.

Combination of Sensory, Chromatographic, and Chemometrics Analysis of Volatile Organic Compounds for the Discrimination of Authentic and Unauthentic Harumanis Mangoes

This study analyzed the volatile organic compounds (VOCs) of three mango varieties (Harumanis, Tong Dam and Susu) for the discrimination of authentic Harumanis from other mangoes. The VOCs of these mangoes were extracted and analysed nondestructively using Head Space-Solid Phase Micro Extraction (HS-SPME) coupled to Gas Chromatography-Mass Spectrometry (GC-MS). Prior to the analytical method, two simple sensory analyses were carried out to assess the ability of the consumers to differentiate between the Harumanis and Tong Dam mangoes as well as their preferences towards these mangoes. On the other hand, chemometrics techniques, such as principal components analysis (PCA), hierarchical clustering analysis (HCA), and discriminant analysis (DA), were used to visualise grouping tendencies of the volatile compounds detected. These techniques were successful in identifying the grouping tendencies of the mango samples according to the presence of their respective volatile compounds, thus enabling the identification of the groups of substances responsible for the discrimination between the authentic and unauthentic Harumanis mangoes. In addition, three ocimene compounds, namely beta-ocimene, trans beta-ocimene, and allo-ocimene, can be considered as chemical markers of the Harumanis mango, as these compounds exist in all Harumanis mango, regardless the different sources of the mangoes obtained.