Selection of calibration set samples in determination of olive oil acidity by partial least squares–attenuated total reflectance–Fourier transform infrared spectroscopy

Iñón, Fernando A.; Garrigues, Jose M; Garrigues, Salvador; Molina, Antonio; Guárdia, Miguel de la

doi:10.1016/s0003-2670(03)00711-6

Cited by 94 publications

(33 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…So, there exist studies involving the use of FT-IR with chemometrics for the determination of analytical parameters such as peroxide value and free fatty acidity value [13,14]. Another analytically determined parameter, fatty acids are one of the major ingredients that olive oil contains in its chemical structure.…”

Section: Introductionmentioning

confidence: 99%

Comparison of fatty acid profiles and mid‐infrared spectral data for classification of olive oils

Gürdeniz

Özen

Tokatlı

2010

Euro J Lipid Sci & Tech

View full text Add to dashboard Cite

The composition of olive oils may vary depending on environmental and technological factors. Fatty acid profiles and Fourier‐transform infrared (FT‐IR) spectroscopy data in combination with chemometric methods were used to classify extra‐virgin olive oils according to geographical origin and harvest year. Oils were obtained from 30 different areas of northern and southern parts of the Aegean Region of Turkey for two consecutive harvest years. Fatty acid composition data analyzed with principal component analysis was more successful in distinguishing northern olive oil samples from southern samples compared to spectral data. Both methods have the ability to differentiate olive oil samples with respect to harvest year. Partial least squares (PLS) analysis was also applied to detect a correlation between fatty acid profile and spectral data. Correlation coefficients (R2) of a calibration set for stearic, oleic, linoleic, arachidic and linolenic acids were determined as 0.83, 0.97, 0.97, 0.83 and 0.69, respectively. Fatty acid profiles were very effective in classification of oils with respect to geographic origin and harvest year. On the other hand, FT‐IR spectra in combination with PLS could be a useful and rapid tool for the determination of some of the fatty acids of olive oils.

show abstract

Section: Introductionmentioning

confidence: 99%

Comparison of fatty acid profiles and mid‐infrared spectral data for classification of olive oils

Gürdeniz

Özen

Tokatlı

2010

Euro J Lipid Sci & Tech

View full text Add to dashboard Cite

show abstract

“…Figure 1 shows the FTIR mean spectra of the three citrus cultivars. In consideration of the high signal contribution due to H 2 O and CO 2 in the juice samples, the spectral regions 4000-3030, 1900-1500, and 2400-2200 cm -1 were respectively removed because they are rich in instrumental noise and bring useless information (Iñón et al 2003).…”

Section: Methodsmentioning

confidence: 99%

“…On the native data, Multiplicative Scatter Correction (MSC), Standard Normal Variate (SNV), and Derivative data pre-treatments were applied (Iñón et al 2003;Maggio et al 2009). The classification algorithm PLS-DA (Kowalski 1984) performs a PCA in both X and Y matrices.…”

Section: Methodsmentioning

confidence: 99%

Chemometric classification of citrus juices of Moroccan cultivars by infrared spectroscopy

et al. 2015

View full text Add to dashboard Cite

Hirri A., De Luca M., Ioele G., Balouki A., Bassbasi M., Kzaiber F., Oussama A., Ragno G. (2015): Chemometric classification of citrus juices of Moroccan cultivars by infrared spectroscopy. Czech J. Food Sci., 33: 137-142.Fourier transform -infrared (FTIR) spectroscopy in connection with chemometric methodologies was used as a fast and direct analytical approach to classify citrus cultivars by the measurements on their juice. Modern multivariate analysis responds to the current needs for economic, simple, and fast methods able to classify new unknown samples with great accuracy. A set of 135 samples of citrus juice, representative of three cultivars (Hamlin, Muska, and Valencia), all picked in the same geographical area of Morocco, were analysed. Chemometric discrimination of the juice samples was achieved by principal component analysis (PCA) performed on the FTIR spectral data from the juice samples, showing an explained variance of 97.84% by considering only 2 PCs. A fully correct classification of the three Moroccan cultivars was then obtained by using Partial Least Square-Discriminant Analysis (PLS-DA) modelling procedure.

show abstract

“…Near infrared spectroscopy has been valuable for the assessment of physicochemical parameters of vegetable oils (Sato 1994;Hourant et al 2000;Takamura et al 1995;Franco et al 2006). Infrared spectroscopy (NIR and MID), has also been applied successfully for olive oil evaluation and geographical origin determination using chemometric approaches (Tapp et al 2003;Iñón et al 2003;Galtier et al 2007). In addition, NIR technique was employed to detect fraudulent addition of other vegetable oils and olive pomace oil, to virgin olive oil (Wesley et al 1995;Yang & Irudayaraj 2001;Doweny et al 2002;Vlachos et al 2006); and for olive oil authentication (Bertran et al 2000;Downey et al 2003;Woodcock et al 2008).…”

Section: Quantification Of Chemical Parameters In Olive Oilmentioning

confidence: 99%

Quality Evaluation of Olives, Olive Pomace and Olive Oil by Infrared Spectroscopy

Delgadillo¹,

Barros²,

Nunes³

2012

Olive Oil - Constituents, Quality, Health Properties and Bioconversions

View full text Add to dashboard Cite

Selection of calibration set samples in determination of olive oil acidity by partial least squares–attenuated total reflectance–Fourier transform infrared spectroscopy

Cited by 94 publications

References 21 publications

Comparison of fatty acid profiles and mid‐infrared spectral data for classification of olive oils

Comparison of fatty acid profiles and mid‐infrared spectral data for classification of olive oils

Chemometric classification of citrus juices of Moroccan cultivars by infrared spectroscopy

Quality Evaluation of Olives, Olive Pomace and Olive Oil by Infrared Spectroscopy

Contact Info

Product

Resources

About