METHODS: An Agilent 1200 series high-performance liquid chromatography (HPLC) unit using a diode-array detector (DAD) has been employed and optimized to detect IPTS in cosmetic products. For the separation, a reverse-phase Hypersil Gold C8 column (5 μm, 4.6 mm i.d. 250 mm) 5 mM tetrabutylammonium phosphate buffer 50 : 50, (v/v) solution in acetonitrile as mobile phase, in isocratic mode and a flow rate of 0.8 mL min(-1) were used. A second method using a gas chromatography/mass selective detector GC-MSD was also developed to confirm the IPTS identity in the cosmetic products.
RESULTS: Recoveries of IPTS from cosmetic matrices such as a lotion, cleansing milk and a cream ranged from 94.0% to 101.1% with <5% relative standard deviation (%RSD) showing good accuracy and repeatability of the method. The six-point calibration curves (determined over the range 0.5-50 μg mL(-1) ) have a correlation coefficient of 0.9999 (based on HPLC peak area) and 0.9998 (based on HPLC peak height). The intra- and interday precisions (measured by the %RSD) of the method were <2% and <5%, respectively, indicating that the developed method is reliable, precise and reproducible. The detection and quantification limit of the method were found to be 0.5 μg mL(-1) and 1.6 μg mL(-1) , respectively. Analyses of 83 commercial cosmetics showed no presence of IPTS.
CONCLUSIONS: The validation data indicated that this method was suitable for the quantitative analysis of IPTS in commercial cosmetics. This method is applicable for analyses of trace levels of IPTS in cosmetics and has the advantage of using only simple sample preparation steps.
OBJECTIVE: To determine and quantify lard as an adulterant in a binary blend with palm oil in a cosmetic soap formulation by FT-IR and multivariate analysis.
METHODS: Fatty acids in lard, palm oil, and binary blends were extracted via liquid-liquid extraction and were subjected to FTIR spectrometry, combined with principal component analysis (PCA) and discriminant analysis (DA) for the classification of lard in cosmetic soap formulations via two DA models: Model A (percentage of lard in cosmetic soap) and Model B (porcine and non-porcine cosmetic soap). Linear regression (MLR), partial least square regression (PLS-R), and principal components regression (PCR) were used to assess the degree of adulteration of lard in the cosmetic soap.
FINDINGS: The FTIR spectrum of palm oil slightly differed from that of lard at the wavenumber range of 1453 cm-1 and 1415 cm-1 in palm oil and lard, respectively, indicating the bending vibrations of CH2 and CH3 aliphatic groups and OH carboxyl group, respectively. Both of the DA models could accurately classify 100% of cosmetic soap formulations. Nevertheless, less than 100% of verification value was obtained when it was further used to predict the unknown cosmetic soap sample suspected of containing lard or a different percentage of lard. The PCA for Model A and Model B explained a similar cumulative variability (CV) of 92.86% for the whole dataset. MLR and PCR showed the highest determination coefficient (R2) of 0.996, lowest relative standard error (RSE), and mean square error (MSE), indicating that both regression models were effective in quantifying the lard adulterant in cosmetic soap.
CONCLUSION: FTIR spectroscopy coupled with chemometrics with DA, PCA, and MLR or PCR can be used to analyze the presence of lard and quantify its percentage in cosmetic soap formulations.
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