Characterisation of table olive cultivar by NIR spectroscopy

Casale, Monica; Zunin, Paola; Cosulich, Maria Elisabetta; Pistarino, Erika; Perego, Patrizia; Lanteri, Silvia

doi:10.1016/j.foodchem.2010.03.080

Cited by 37 publications

(13 citation statements)

References 11 publications

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“…Furthermore, a repeated K-fold-CV procedure was also applied for comparison purposes with the LOO-CV technique results, to ensure that there were no overfitting issues, since satisfactory results were obtained in both cross-validation techniques. It should be remarked that although the number of different independent samples studied is similar to those usually used in the literature regarding table olive analysis (Casale et al 2010;Cano-Lamadrid et al 2017;Cortés-Delgado et al 2016;Galán-Soldevilla et al 2013;Lanza and Amoruso 2016;Marx et al 2017a, b;Panagou et al 2008;Ramírez et al 2016;Sousa et al 2011), it does not allow the establishment of a representative external dataset, which justifies use of this cross-validation variant.…”

Section: Discussionmentioning

confidence: 99%

Assessment of Table Olives’ Organoleptic Defect Intensities Based on the Potentiometric Fingerprint Recorded by an Electronic Tongue

Marx

Rodrigues

Dias

et al. 2017

Food Bioprocess Technol

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Table olives are prone to the appearance of sensory defects that decrease their quality and in some cases result in olives unsuitable for consumption. The evaluation of the type and intensity of the sensory negative attributes of table olives is recommended by the International Olive Council, although not being legally required for commercialization. However, the accomplishment of this task requires the training and implementation of sensory panels according to strict directives, turning out in a time-consuming and expensive procedure that involves a degree of subjectivity. In this work, an electronic tongue is proposed as a taste sensor device for evaluating the intensity of sensory defects of table olives. The potentiometric signal profiles gathered allowed establishing multiple linear regression models, based on the most informative subsets of signals (from 24 to 29 recorded during the analysis of olive aqueous pastes and brine solutions) selected using a simulated annealing meta-heuristic algorithm. The models enabled the prediction of the median intensities (R 2 ≥ 0.942 and RMSE ≤ 0.356, for leave-one-out or repeated K-fold cross-validation procedures) of butyric, musty, putrid, winey-vinegary, and zapateria negative sensations being, in general, the predicted intensities within the range of intensities perceived by the sensory panel. Indeed, based on the predicted mean intensities of the sensory defects, the electroche micalchemometric approach developed could correctly classify 86.4% of the table olive samples according to their trade category based on a sensory panel evaluation and following the International Olive Council regulations (i.e., extra, 1st choice, 2nd choice, and olives that may not be sold as table olives). So, the satisfactory overall predictions achieved demonstrate that the electronic tongue could be a complementary tool for assessing table olive defects, reducing the effort of trained panelists and minimizing the risk of subjective evaluations.

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Section: Discussionmentioning

confidence: 99%

Assessment of Table Olives’ Organoleptic Defect Intensities Based on the Potentiometric Fingerprint Recorded by an Electronic Tongue

Marx

Rodrigues

Dias

et al. 2017

Food Bioprocess Technol

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“…In addition, this technique achieves high analysis speed and requires little or no sampling preparation. Up-to date, much of the published studies on the use of near and mid FT-IR spectroscopy were focused on the authentication and the classification of many agro-foods, notably olive oils [11,12] and table olives [13] by multi-variant statistical analysis on spectral data. Moreover, FT-MIR has been applied to analyze extra virgin olive oil adulterated with palm oil [14] and the determination of quality parameters of VOO [15].…”

Section: Please Scroll Down For Articlementioning

confidence: 99%

Prediction of Polyphenol Fraction in Virgin Olive Oil Using Mid-Infrared Attenuated Total Reflectance Attenuated Total Reflectance Accessory–Mid-Infrared Coupled With Partial Least Squares Regression

Hirri

Bassbasi

Souhassou

et al. 2015

International Journal of Food Properties

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“…The samples were stored in the original packaging, in dark at ambient temperature (~20°C) until analysis or after opened in the refrigerator at 4°C (being all of them analyzed before the end of the expiration date). It should be remarked that the number of different independent samples studied is of the same order of magnitude as those usually used in the literature regarding table olives analysis [17][18][19][20]22,[28][29][30].…”

Section: Introductionmentioning

confidence: 99%

Sensory classification of table olives using an electronic tongue: Analysis of aqueous pastes and brines

Marx

Rodrigues

Dias

et al. 2017

Talanta

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A B S T R A C T Table olives are highly appreciated and consumed worldwide. Different aspects are used for trade category classification being the sensory assessment of negative defects present in the olives and brines one of the most important. The trade category quality classification must follow the International Olive Council directives, requiring the organoleptic assessment of defects by a trained sensory panel. However, the training process is a hard, complex and sometimes subjective task, being the low number of samples that can be evaluated per day a major drawback considering the real needs of the olive industry. In this context, the development of electronic tongues as taste sensors for defects' sensory evaluation is of utmost relevance. So, an electronic tongue was used for table olives classification according to the presence and intensity of negative defects. Linear discrimination models were established based on sub-sets of sensor signals selected by a simulated annealing algorithm. The predictive potential of the novel approach was first demonstrated for standard solutions of chemical compounds that mimic butyric, putrid and zapateria defects (≥93% for cross-validation procedures). Then its applicability was verified; using reference table olives/brine solutions samples identified with a single intense negative attribute, namely butyric, musty, putrid, zapateria or winey-vinegary defects (≥93% cross-validation procedures). Finally, the E-tongue coupled with the same chemometric approach was applied to classify table olive samples according to the trade commercial categories (extra, 1 st choice, 2 nd choice and unsuitable for consumption) and an additional quality category (extra free of defects), established based on sensory analysis data. Despite the heterogeneity of the samples studied and number of different sensory defects perceived, the predictive linear discriminant model established showed sensitivities greater than 86%. So, the overall performance achieved showed that the electrochemical device could be used as a taste sensor for table olives organoleptic trade successful classification, allowing a preliminary quality assessment, which could facilitate, in the future, the complex task of sensory panelists.

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Characterisation of table olive cultivar by NIR spectroscopy

Cited by 37 publications

References 11 publications

Assessment of Table Olives’ Organoleptic Defect Intensities Based on the Potentiometric Fingerprint Recorded by an Electronic Tongue

Assessment of Table Olives’ Organoleptic Defect Intensities Based on the Potentiometric Fingerprint Recorded by an Electronic Tongue

Prediction of Polyphenol Fraction in Virgin Olive Oil Using Mid-Infrared Attenuated Total Reflectance Attenuated Total Reflectance Accessory–Mid-Infrared Coupled With Partial Least Squares Regression

Sensory classification of table olives using an electronic tongue: Analysis of aqueous pastes and brines

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