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

Sani, Muhamad Shirwan Abdullah; Ismail, Azilawati Mohd; Azid, Azman; Samsudin, Mohd Saiful

doi:10.1016/j.foodcont.2021.108350

Cited by 8 publications

(15 citation statements)

References 31 publications

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“…Based on these works, we used this less expensive method in our study, except that we detected the separated AAs with a diode array detector, which has been shown to authenticate skin gelatine sources. This method was validated and verified on marshmallows, with the results published by Sani et al (2021).…”

Section: Introductionmentioning

confidence: 82%

“…Since it is the most prevalent chemometrics classification technique, discriminant analysis (DA) is utilised extensively in food authentication. Sani et al (2021) also authenticated gelatine products using DA, whereas there are few reports of PLS-DA applications for authenticating gelatine sources. noted that PLS-DA characteristics such as Fisher statistics and p-value could serve as discriminatory indicators for authentication purposes.…”

Section: Halalsphere International Islamic University Malaysia -Inhartmentioning

confidence: 99%

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Incorporation of Partial Least Squares-Discriminant Analysis with Ultra-High-Performance Liquid Chromatography Diode-Array Detector for Authentication of Skin Gelatine Sources

Abdullah Sani,

Mohd Ismail,

Azid

et al. 2024

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This research seeks to (1) authenticate sources of skin gelatine by combining putative 17 aminoacids (AAs) analysis with chemometrics by Ultra-High-Performance Liquid ChromatographyDiode-Array Detector (UHPLC-DAD) and (2) create AA profiles in skin gelatines. Theclassification capability of partial least square-discriminant analysis (PLS-DA) models wasassessed to determine the most effective discriminant model. Principal component analysis(PCA) with quartimax rotation was utilised to accurately organise gelatine clusters and assign thesignificantly contributing AAs to each cluster. The PLS-DA model with 13 AAs (PLS-DAVIPAA)outperformed the PLS-DA model with 17 AAs (PLS-DAAA) because its R2Y (0.938), R2X (0.881),and Q2 (0.929) values were greater. With 13 significant AAs, the PLS-DAVIPAA model obtainedcluster classification accuracy of 100% on training and cross-validation datasets and 93.3% ontesting and verification datasets. The chemical structure of gelatines may shed light on theinteractions between AAs. Following six quartimax rotations, the gelatines were groupedcorrectly. The PCA showed the dominant presence of these AAs: L-Valine, L-Phenylalanine andL-Tyrosine in porcine gelatine; Glycine, L-Threonine, L-Arginine, L-Methionine, L-Histidine andL-Serine in fish gelatine; and L-Hydroxyproline, L-Leucine and L-Proline in bovine gelatine. Theauthority could use this technique to set a standard for authenticating skin gelatine samples.

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Section: Introductionmentioning

confidence: 82%

Section: Halalsphere International Islamic University Malaysia -Inhartmentioning

confidence: 99%

Incorporation of Partial Least Squares-Discriminant Analysis with Ultra-High-Performance Liquid Chromatography Diode-Array Detector for Authentication of Skin Gelatine Sources

Abdullah Sani,

Mohd Ismail,

Azid

et al. 2024

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“…Another verification dataset with 93 data points and 20 replicates for each unknown soap sample ( n = 5) was used to validate regression models on cosmetic soap. Next, regression analysis utilizing MLR, PLS‐R and PCR was performed on the validation dataset [24]. The formula for MLR, PLS‐R and PCR that have been used are as below: MLR: ŷ = b 0 + b 1 x …”

Section: Methodsmentioning

confidence: 99%

Discrimination and authentication of lard blending with palm oil in cosmetic soap formulations

Aziz

Sani

Zakaria

et al. 2023

Intern J of Cosmetic Sci

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Background The employment of Fourier transforms infrared (FT‐IR) spectroscopy combined with chemometrics for determination and quantification of lard in a binary blend with palm oil in a cosmetic soap formulations. Objective To determine and quantify lard as an adulterant in a binary blend with palm oil in a cosmetic soap formulations 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, and the 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 analyse the presence of lard and quantify its percentage in cosmetic soap formulations.

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“…To achieve relevant findings, pre-requisite MDA must be carried out [30], beginning with choosing the appropriate dataset for the study using the KMO test. For the 250 datasets, the KMO test produced a KMO score of 0.820 (Table 2).…”

Section: Validation and Verification Of The Da Model Between Oa And H...mentioning

confidence: 99%

Diagnosis of Osteoarthritis at an Early Stage via Infrared Spectroscopy Combined Chemometrics in Human Serum: A Pilot Study

et al. 2023

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Methods applied for early diagnosis of osteoarthritis (OA) are limited. Early prevention and treatment can effectively reduce the pain of OA patients and save costs. The present study aimed to develop a rapid non-destructive detection method for early diagnosis of OA by evaluating infrared (IR) spectroscopy combined chemometrics. Our cohort consisted of (a) 15 patients with osteoarthritis (OA) and (b) 10 without clinical signs of the disease and they were used as controls. Attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy was used to investigate serum samples (50 µL) collected from these patients. A supervised classification algorithm namely discriminant analysis (DA) was applied to evaluate the diagnostic accuracy spectral processing and chemometrics analysis allowed for detecting spectral biomarkers that discriminated the two cohorts. About 250 infrared spectra were statistically important for separating the groups. Peaks at 1000 cm−1 in OA serum were associated mainly with C–O stretching vibration associated with the changes in the proteoglycan contents previously reported in OA. A good overall classification accuracy of 74.47% was obtained from the DA model. Our findings indicated that this discriminating model, which incorporated the ATR-FTIR spectrum, could provide a rapid and cost-effective blood test, thus facilitating the early diagnosis of human OA.

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

Cited by 8 publications

References 31 publications

Incorporation of Partial Least Squares-Discriminant Analysis with Ultra-High-Performance Liquid Chromatography Diode-Array Detector for Authentication of Skin Gelatine Sources

Incorporation of Partial Least Squares-Discriminant Analysis with Ultra-High-Performance Liquid Chromatography Diode-Array Detector for Authentication of Skin Gelatine Sources

Discrimination and authentication of lard blending with palm oil in cosmetic soap formulations

Diagnosis of Osteoarthritis at an Early Stage via Infrared Spectroscopy Combined Chemometrics in Human Serum: A Pilot Study

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