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.

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.

Quality assessment and chemometrics application on physicochemical characteristics, antioxidant properties, and 5-HMF content of Malaysian stingless bee honey from different topographical origins.

The popularity of Malaysian stingless bee honey is rising among health-conscious individuals; thus, chemical and physical evaluations of Malaysian stingless bee honey are vital to ensure the honey has achieved the optimum limits set by Malaysian and international regulatory standards so that it can be commercialized locally and internationally. Therefore, in the present study, the physicochemical characteristics (moisture content, total dissolved solids, pH, free acidity, electrical conductivity, and ash content), antioxidant properties (total phenolic and flavonoid contents), and 5-hydroxymethylfurfural (5-HMF) of Heterotrigona itama (H. itama) honey from different sites in Peninsular Malaysia were investigated. Subsequently, the correlation between these chemical and physical parameters was studied using Spearman correlation coefficients. The significant difference between H. itama honey from different topographical origins was studied using univariate analysis (one-way ANOVA followed by post hoc Tukey's test). The discrimination pattern of 45 honey samples based on their topographical origins was evaluated using cluster analysis (heatmap and dendrogram) and chemometrics analysis (partial least squares-discriminant analysis). Results showed that some samples of certain parameters (electrical conductivity, free acidity, and moisture content) have exceeded the limit set by the international regulatory standard. However, the 5-HMF content of all samples was within the allowed range. A statistically significant difference (p < 0.05) has been observed for all the parameters except electrical conductivity and ash content in terms of inter-topographical origins. Although the profiles of H. itama honey from different origins were close, most of them were separated according to their topographical origins and were validated using a permutation test.

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, ß-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.

Effect of Mobile Phase pH on the Electrospray Ionization Efficiency and Qualitative Analysis of Pharmaceuticals in ESI + LC-MS/MS.

The effect of mobile phase pH on positive ionization process and retention time of nine pharmaceuticals on ultra-performance liquid chromatography-electrospray-tandem mass spectrometry (LC-MS/MS) was discussed. The effective use of high and low mobile phase pH in LC-MS/MS qualitative analyses method was also evaluated by comparing the instrument detection limit, quantification limit, precision, linearity and signal to noise (S/N) under low and high mobile phase pH. In this work, six mobile phase pH that ranged between pH 2 and pH 10 were used to evaluate the effect of the mobile phase pH changes on the ionization process in electrospray ionization. Results revealed that high mobile phase pH ionized more pharmaceuticals molecules and gave a higher signal than low mobile phase pH in positive ionization mode. The results proved that ammonium ion was better as a proton donor in high pH mobile phase than the hydronium ion in acidic mobile phase. The results revealed that the qualitative LC-MS/MS analyses method by using high mobile phase pH has better performance for most analytes in terms of sensitivity, precision, linearity and S/N than the low mobile phase pH.

Disk solid-phase extraction of multi-class pharmaceutical residues in tap water and hospital wastewater, prior to ultra-performance liquid chromatographic-tandem mass spectrometry (UPLC-MS/MS) analyses.

In this work, a new clean-up and pre-concentration method based on disk solid-phase extraction (SPE) was developed to determine multi-class pharmaceutical residues covering a wide range of polarities (log K ow values from -0.5 to 5.1) in water systems, prior to ultra-performance liquid chromatographic-tandem mass spectrometry (UPLC-MS/MS) analyses. Electrospray ionisation in positive and negative modes was used for the simultaneous determination of both acidic and basic pharmaceuticals. The performances of disk SPE and cartridge SPE were compared. The targeted pharmaceutical compounds list included bronchodilators, antidiabetic drugs, antihypertensive drugs, a lipid-lowering agent, analgesics, and anti-inflammatory drugs. Based on our results, the disk SPE demonstrated a higher sensitivity and recovery value and less analysis time as compared to the cartridge SPE method. The limits of detection (LOD) for the new method ranged from 0.02-3.2 ng L-1, 0.02-3.1 ng L-1 and 0.02-4.7 ng L-1 for tap, effluent and influent wastewater, respectively. The method's absolute recovery values ranged from 70% to 122% for tap water, 62% to 121% for effluent wastewater and 62% to 121% for influent wastewater, except for metformin in which the absolute recovery value was approximately 48% for all samples. Intra-day precision for tap water, effluent and influent wastewater ranged from 3-12%, 4-9% and 2-8%, respectively. The method developed was applied for the determination of targeted pharmaceuticals in tap, effluent, and influent wastewater from one hospital treatment plant in Malaysia. The results revealed that the highest concentrations of certain pharmaceuticals were up to 49 424 ng L-1 (acetaminophen) and 1763 ng L-1 (caffeine) in the influent and effluent wastewater, respectively. The results also showed a variation in the treatment efficiencies for the hospital treatment plant from one compound to another. Nevertheless, the removal efficiencies ranged from 0-99%.

Chemometric approach to validating faecal sterols as source tracer for faecal contamination in water.

Faecal sterols detection is a promising method for identifying sources of faecal pollution. In this study, faecal contamination in water samples from point source (sewage treatment plants, chicken farms, quail farms and horse stables) was extracted using the solid phase extraction (SPE) technique. Faecal sterols (coprostanol, cholesterol, stigmasterol, beta-sitosterol and stigmastanol) were selected as parameters to differentiate the source of faecal pollution. The results indicated that coprostanol, cholesterol and beta-sitosterol were the most significant parameters that can be used as source tracers for faecal contamination. Chemometric techniques, such as cluster analysis, principal component analysis and discriminant analysis were applied to the data set on faecal contamination in water from various pollution sources in order to validate the faecal sterols' profiles. Cluster analysis generated three clusters: coprostanol was in cluster 1, cholesterol and beta-sitosterol formed cluster 2, while cluster 3 contained stigmasterol and stigmastanol. Discriminant analysis suggested that coprostanol, cholesterol and beta-sitosterol were the most significant parameters to discriminate between the faecal pollution source. The use of chemometric techniques provides useful and promising indicators in tracing the source of faecal contamination.