Classification of moroccan olive cultivars by linear discriminant analysis applied to ATR–FTIR spectra of endocarps

Abstract

Summary The potential of FTIR combined with chemometrics was studied to classify five Moroccan varieties of olives by analysis on the endocarps. Attenuated total reflectance (ATR) enabled the samples to be examined directly in the solid state. The spectral data were subjected to a preliminary derivative elaboration based on the Norris gap algorithm to reduce the noise and extract larger analytical information. Linear discriminant analysis (LDA) was adopted as classification method, and Principle component analysis (PCA) was employed to compress the original data set into a reduced new set of variables before LDA. The calibration set was built by using the IR data from seventy‐five samples scanned in reflectance mode, and the ranges 3000–2400 and 2300–600 cm−1 were selected because furnishing the most useful analytical information. PCA allowed clustering the samples in five classes by using the first two principal components with an explained variance of 98.16%. Application of LDA on an external test set of twenty‐five samples enabled to classify them into five variety groups with a correct classification of 92.0%.

Synthesis and photodegradation studies of analogues of muscle relaxant 1,4-dihydropyridine compounds

“…According to our previous work (14), the residual concentration of the target compounds was determined by applying the MCR algorithm to the spectral data. This chemometric procedure was adopted for its ability to determine, during the entire photodegradation process, the number of involved species and their concentration and at the same time to plot their absorbance spectra (20)(21)(22). All tested compounds were confi rmed to be sensitive to light, showing 10 % degradation in less than twenty minutes of irradiation.…”

“…Due to the well-known photo-lability of DHPs (15)(16)(17)(18), the synthesized compounds were subjected to photodegradation tests (19). Concentration of parent compounds and by-products was calculated by multivariate curve resolution-alternating least squares (MCR-ALS) applied to the spectral data (20)(21)(22).…”

Cultivar discrimination of Spanish olives by using direct FTIR data combined with linear discriminant analysis

“…In addition, IR data have been often treated with multivariate chemometric techniques to develop methods of classification and characterization . Thus, IR (near and medium, and mostly Fourier‐transform infrared spectroscopy, FTIR) has been effectively employed to predict quality parameters of both olives and VOOs , and also to classify them according to their genetic variety , geographical origin , to detect VOO adulteration , to evaluate VOO freshness , and early stages of VOO autoxidation .…”

Neural network models to classify olive oils within the protected denomination of origin framework

“…Cosio et al, (2006Cosio et al, ( , 2007 applied an electronic nose, an electronic tongue and neural networks (NNs) to classify EVOO samples from the lake of Garda in the north of Italy. Luca et al, (2011Luca et al, ( , 2012 have applied a series of analytical and mathematical techniques to classify Moroccan olive cultivar. Similarly, the combination of electronic noses with other techniques for the identification of the geographical origin of olive oil samples has also been studied (Rodr ıguez-M endez et al, 2008;Casale et al, 2010;Haddi et al, 2011).…”