Purity Analysis of Adulterated Vegetable Oils by Raman and FTIR Spectroscopy

Bhaskar, Shyju; Spandana, K U; Mahato, Krishna Kishore; Mazumder, Nirmal

doi:10.1364/fio.2018.jw4a.121

Cited by 2 publications

(2 citation statements)

References 5 publications

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“…These studies demonstrate the potential use of Raman and IR spectroscopy for the detection of various adulterants in marine oils. The use of Raman and IR spectroscopy has also been demonstrated for the detection of adulterants in edible oils (i.e., olive oil, coconut oil, sunflower oil) [26][27][28].Very few vibrational spectroscopic studies have focused on fish oil [25,29]; one of these is our recent study [30], where we investigated Raman and IR separately and as a fused dataset to quantify adulterants (PO, O3C and FO) in fish oil samples (cod liver oil and salmon oil). Our research concluded that the SVM classification analysis successfully classified the adulterants and the PLSR model quantified the amount of adulterant in the fish oil samples.…”

Section: Introductionmentioning

confidence: 99%

Detection and Quantification of Adulteration in Krill Oil with Raman and Infrared Spectroscopic Methods

et al. 2023

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Raman and infrared spectroscopy, used as individual and low-level fused datasets, were evaluated to identify and quantify the presence of adulterants (palm oil, PO; ω-3 concentrates in ethyl ester, O3C and fish oil, FO) in krill oil. These datasets were qualitatively analysed with principal component analysis (PCA) and classified as adulterated or unadulterated using support vector machines (SVM). Using partial least squares regression (PLSR), it was possible to identify and quantify the adulterant present in the KO mixture. Raman spectroscopy performed better (r2 = 0.98; RMSEP = 2.3%) than IR spectroscopy (r2 = 0.91; RMSEP = 4.2%) for quantification of O3C in KO. A data fusion approach further improved the analysis with model performance for quantification of PO (r2 = 0.98; RMSEP = 2.7%) and FO (r2 = 0.76; RMSEP = 9.1%). This study demonstrates the potential use of Raman and IR spectroscopy to quantify adulterants present in KO.

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Section: Introductionmentioning

confidence: 99%

Detection and Quantification of Adulteration in Krill Oil with Raman and Infrared Spectroscopic Methods

et al. 2023

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“…Using multiple linear regression (MLR), it was possible to determine FFA content in crude palm oil with a prediction error of 0.1, using NIR spectra as predictors (Man & Moh, 1998). In recent works, the application of FTIR spectroscopy was investigated for determination of adulterated oil samples (Bhaskar, Spandana, Mahato, & Mazumder, 2018), whereas a hand-held FTIR spectrophotometer was used as a screening technique for adulterated olive oils (Pan, Sun, Zhou, & Chen, 2018).…”

Section: Introductionmentioning

confidence: 99%

Portable NIR Spectrometer for Prediction of Palm Oil Acidity

Kaufmann

Favero

Vasconcelos

et al. 2019

Journal of Food Science

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Palm oil is widely used in the food industry, and its quality is associated with the free fatty acids (FFA) content. Determination of FFA in oil is time‐consuming, requires chemicals and generates residues. There is a trend of applying process analytical technologies (PAT) for fast and nondestructive determination of oil parameters. Portable near‐infrared (NIR) spectrometers are cheaper than bench top equipment, and have been used for several tasks in the food processing industry, as it provides fast and reliable data for inline measurements. This study investigated the use of NIR spectra using a portable equipment, combined with both unsupervised and supervised multivariate analyses for identification of palm oil samples with different levels of FFA. Soft independent modeling of class analogy , k‐Nearest Neighbors, and linear discriminant analysis models were able to correctly identify 100% of the studied samples with selected wavelengths from NIR spectra. Calibration models were performed for acidity prediction, achieving R2 = 0.97, with root mean square error of prediction = 4.37 for partial least squares model using most relevant wavelengths. These results demonstrate the feasibility of applying a low‐cost portable NIR spectrophotometer to predict quality parameters of palm oil. Practical Application This work presents results that show the feasibility of using a low‐cost portable near‐infrared spectrophotometer for the classification of raw palm oil samples according to free fatty acids contents. Regression models are presented as a fast and nondestructive alternative to classify samples for acidity, which is an important quality parameter and that directly affects the market value of crude palm oil.

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Purity Analysis of Adulterated Vegetable Oils by Raman and FTIR Spectroscopy

Cited by 2 publications

References 5 publications

Detection and Quantification of Adulteration in Krill Oil with Raman and Infrared Spectroscopic Methods

Detection and Quantification of Adulteration in Krill Oil with Raman and Infrared Spectroscopic Methods

Portable NIR Spectrometer for Prediction of Palm Oil Acidity

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