On overview of PCA application strategy in processing high dimensionality forensic data

Establishing forensic food models for authentication and quantification of porcine adulterant in gelatine and marshmallow

Discriminant-type analyses arise from the need to classify samples based on their measured characteristics (variables), usually with respect to some observable property. In the case of samples that are difficult to obtain, or using advanced instrumentation, it is very common to encounter situations with many more measured characteristics than samples. The method of Partial Least Squares Regression (PLS-R), and its variant for discriminant-type analyses (PLS-DA) are among the most ubiquitous of these tools. PLS utilises a rank-deficient method to solve the inverse least-squares problem in a way that maximises the co-variance between the known properties of the samples (commonly referred to as the Y-Block), and their measured characteristics (the X-block). A relatively small subset of highly co-variate variables are weighted more strongly than those that are poorly co-variate, in such a way that an ill-posed matrix inverse problem is circumvented. Feature selection is another common way of reducing the dimensionality of the data to a relatively small, robust subset of variables for use in subsequent modelling. The utility of these features can be inferred and tested any number of ways, this are the subject of this review.

Review of Variable Selection Methods for Discriminant-Type Problems in Chemometrics

The aim of this study is to determine the alcohol residue in perfumery products claimed to be alcohol-free using the automated headspace gas chromatography-mass spectrometry (HS-GC-MS) method. This method successfully determined the residual ethanol in 26 perfumery products to be in the range of 7.31- 611.64 µg/mL. The linear concentration range is 0.2-1000 ppm and the correlation coefficient is relatively good (R =0.998). The results show that the method has an excellent measurement precision (RSD < 3.8%) and 2 accuracy recovery of 97.3 ± 3.7%. The analysis requires no sample pre-treatment and the method is very simple, reliable and rapid. This method provides an invaluable analytical tool for the quality control of perfumery products and can be used in routine analysis.

http://www.idosi.org/mejsr/mejsr22(3)14/17.pdf

Rapid Determination of Residual Ethanol in Perfumery Products Using Headspace Gas Chromatography-Mass Spectrometry

ABSTRACT Halal food products are requisite to be consumed by Muslim communities in the world. The standard methods capable of quantifying non-halal components are very urgent. This review highlights the chromatographic methods and chemometric or multivariate data analysis that offer reliable techniques to provide the separation capacity in halal authentication analysis. This review article was written from reputable worldwide databases including Web of Science, Scopus, and PubMed, between January and February 2022. The keywords were “halal research,” “food analysis,” “chromatography,” “chemometrics” and “authentication.” Chromatographic-based techniques in combination with chemometrics of multivariate analysis, a powerful statistical analysis to manage huge data generated from analytical measurement, could be used to identify potential markers to differentiate halal and non-halal samples. Chromatogram and peak separation profiles resulted as the instrument responses can be further evaluated for determination as well as quantification of halal and non-halal components in food products. Combination of chromatographic-based method and chemometrics techniques with some scenarios can be applied for halal research on food products.

https://www.tandfonline.com/doi/pdf/10.1080/10942912.2022.2082468?needAccess=true

Use of chromatographic-based techniques and chemometrics for halal authentication of food products: A review

This study provided a step-by-step procedure to investigate the distribution of 17 amino acids (AAs) in 50 fish, 50 bovine and 54 porcine gelatines using Ultra-High-Performance Liquid Chromatography Diode-Array Detector (UHPLC–DAD) with the incorporation of principal component analysis (PCA). Dataset pre-processing step, including outlier removal, analysis of variance (ANOVA), dataset adequacy test, dataset transformation and correlation test was performed before the PCA. The method rendered linearity range of 37.5–1000 pmol/µL and accuracy of 85–111% recovery. The bovine and porcine gelatines showed a similar ranking while the l-Alanine (Ala), l-Arginine (Arg) and l-Glutamic acid (Glu) concentrations had differed the fish gelatine from the bovine and porcine gelatines. The PCA, which explained 77.013% cumulative variability at eigenvalue of 5.436, showed AAs with strong FL in PC1 had polar and nonpolar side chains while AAs with strong FL in PC2 had polar side chain. The AAs with moderate and weak FL in PC1 had a nonpolar side chain. The AAs with strong FL of in PC1 were also the same AAs with 7, 6 and 5 strong CMs as determined in the correlation test. The second PCA showed that the l-Serine (Ser), Arg, Glycine (Gly), l-Threonine (Thr), l-Methionine (Met), l-Histidine (His) and L-Hydroxyproline (Hyp) were significant in fish gelatine; Hyp, Met, Thr, Ser, His, Gly, and Arg in bovine gelatine; and l-Proline (Pro), l-Tyrosine (Tyr), l-Valine (Val), l-Leucine (Leu), and l-Phenylalanine (Phe) in porcine gelatine. The 100% fish, bovine and porcine gelatines accommodated grouping 1, 2 and 3, respectively, which proved that AAs with strong FL (Hyp, His, Ser, Arg, Gly, Thr, Pro, Tyr, Met, Val, Leu and Phe) were the significant AAs and becomes the biomarkers to identify the gelatine source. From this study, the PCA was a useful tool to analyse a multivariate dataset that could provide an in-depth understanding of AA distributions as compared to ANOVA and correlation test.

/pdf/food-forensics-on-gelatine-source-via-ultra-high-performance-214hqiknya.pdf

Food forensics on gelatine source via ultra-high-performance liquid chromatography diode-array detector and principal component analysis

Lard adulteration in food products is undesirable particularly among people with certain diet preference or religious restrictions. Previous attempts on detecting lard in wheat-based biscuits using PCR-based method were inconsistent due to the minute amount of DNA present in lard and entrapment of DNA in the starch matrix. Hence, alternative method using fatty acid–based approach is necessary. The present study aimed to detect lard adulterated in wheat biscuit using chemometrics and machine learning–assisted GCMS. Oil was extracted from the laboratory-prepared wheat biscuits using Soxhlet extraction method, converted to fatty acid methyl ester and analysed using GCMS. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) were able to cluster lard, wheat biscuits and lard-adulterated samples based on their fatty acid distribution. Random forest outperformed partial least squares-discriminant analysis (PLS-DA) in sample classification. Feature selection using random forest identified two fatty acids as potential biomarkers. C18:3n6 is proposed as the potential biomarker in discriminating pure wheat biscuits and lard-adulterated biscuits due to its dose-dependent composition with lard addition.

Detection of Lard Adulteration in Wheat Biscuits Using Chemometrics-Assisted GCMS and Random Forest

Alcohol is an organic solvent that is widely used in the manufacturing industry, especially in food and beverage products. It is also widely used in cosmetic industries to produce products such as perfume, moisturizer and other personal care products. Despite its widespread application,  discussions regarding the use of alcohol in cosmetics from the Shariah and scientific perspectives are still very limited. Thus, the main focus of the present study is to consider the halal status of alcohol as an ingredient in Shariah-based cosmetic products in Malaysia. The analysis focuses on different aspects of Shariah law and also draws on scientific findings from previous studies. Opinion from scholars in Shariah and scientific field are examined in this articles, and the different types of alcohol found in cosmetic products are also discussed.
Keyword: alcohol, cosmetic products, Shariah

/pdf/a-study-of-literatures-status-of-alcohol-in-cosmetics-3t6a14i0sm.pdf

Syariena Arshad

Papers

Food forensics on gelatine source via ultra-high-performance liquid chromatography diode-array detector and principal component analysis

Detection of Lard Adulteration in Wheat Biscuits Using Chemometrics-Assisted GCMS and Random Forest

A Study of Literatures: Status of Alcohol in Cosmetics Products from Shariah Views in Malaysia