Discrimination and characterisation of extra virgin olive oils from three cultivars in different maturation stages using Fourier transform infrared spectroscopy in tandem with chemometrics. (1st May 2015)

• Record Type: Journal Article
• Authors: Gouvinhas, Irene; de Almeida, José M.M.M.; Carvalho, Teresa; Machado, Nelson; Barros, Ana I.R.N.A.
• Is Part Of: Food chemistry. Volume 174(2015)
• Page Start: 226
• Page End: 232
• Publication Date: 2015-05-01
• Subjects: FTIR Fourier transform infrared spectroscopy -- ATR Attenuated Total Reflectance -- PCA principal component analysis -- DA discriminant analysis -- PLS-R partial least squares regression -- PCR Principal Component Regression -- RI Ripening Index -- GAE gallic acid -- ABTS 2, 2-azino-bis(3-ethylbenzothiazoline)-6 sulphonic acid -- R2 multiple coefficient of determination -- RMSEC root mean square error of calibration -- RMSECV root mean square error of cross validation; Fourier transform infrared spectroscopy -- Extra virgin olive oil -- Maturation stages -- Cultivars -- Chemometrics -- Chemical parameters; Food -- Analysis -- Periodicals; Food -- Composition -- Periodicals; 664
• DOI: 10.1016/j.foodchem.2014.11.037
• Languages: English
• ISSNs: 0308-8146

Abstract

Highlights: We proved that it is possible to distinguish ripening stages and cultivars. We model that is possible to classify samples with different biochemical characteristics. Indirect quantification of chemical parameters of EVOO's was possible. Abstract: A methodology based on Fourier transform infrared (FTIR) spectroscopy, combined with multivariate analysis methods, was applied in order to monitor extra virgin olive oils produced from three distinct cultivars on different maturation stages. For the first time, this kind of methodology is used for the simultaneous discrimination of the maturation stage, and different cultivars. Principal component analysis and discriminant analysis were utilised to create a model for the discrimination of olive oil samples. Partial least squares regression was employed to design calibration models for the determination of chemical parameters. The performance of these models was based on the multiple coefficient of determination ( R 2 ), the root mean square error of calibration (RMSEC) and root mean square error of cross validation (RMSECV). The prediction models for the chemical parameters resulted in a R 2 ranged from 0.93 to 0.99, a RMSEC ranged from 1% to 4% and a RMSECV from 2% to 5%. It has been shown that this kind of approach allows to distinguish the different cultivars, and to clearly discern the different maturation stages, in each one of these distinct cultivars. Furthermore, the results demonstrated that FTIR spectroscopy in tandem with chemometric techniques allows the creation of viable and accurate models, suitable for correlating the data collected by FTIR spectroscopy, with the chemical composition of the EVOOs, obtained by standard methods.