Unexplored olive cultivars from the Valencian Community (Spain): some chemical characteristics as a valorization strategy

[EN] The olive processing industry has till date been dominated by a small group of cultivars, leading to the possibility of some olive cultivars becoming extinct in the near future. In this study, we determined the composition of some chemical components in the olive oils from 31 minor olive cultivars of the Valencian Community. Our main aim was to identify suitable cultivars, which could produce differentiated olive oils, thus aiming towards their valorization. The average oil content of minor olive cultivars was found to be good, with some of them reporting approximately 60% (dry basis). On average, the total phenolic content was 229mg kg(-1), with cv. Mas Blanc reporting the highest content (570mg kg(-1)). Among the various tocopherols found in olives, -tocopherol was the main constituent, with a maximum concentration of 290.6mg kg(-1). Linoleic acid was the main polyunsaturated fatty acid and varied between 3.4% (cv. Del Pomet) and 16.9% (cv. Blanqueta Enguera). Special attention needs to be paid to the composition of sterols, since some olive oils exceeded the limits established for some sterols by the current European legislation. Some of the cultivars studied were highly productive, and originated differentiated olive oils with a rich composition of antioxidants and essential fatty acids. In some cases, these beneficial compounds were higher than those of commercial oils obtained from the most common cultivars worldwide. These results could contribute to the commercial exploitation of some of the studied cultivars.Salazar-García, DC.; Malheiro, R.; Pereira, JA.; López- Cortés, I. (2019). Unexplored olive cultivars from the Valencian Community (Spain): some chemical characteristics as a valorization strategy. 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Application of an electronic tongue for Tunisian olive oils' classification according to olive cultivar or physicochemical parameters

Olive oil commercialization has a great impact on the economy of several countries, namely Tunisia, being prone to frauds. Therefore, it is important to establish analytical techniques to ensure labeling correctness concerning olive oil quality and olive cultivar. Traditional analytical techniques are quite expensive, time consuming and hardly applied in situ, considering the harsh environments of the olive industry. In this work, the feasibility of applying a potentiometric electronic tongue with cross-sensitivity lipid membranes to discriminate Tunisian olive oils according to their quality level (i.e., extra virgin, virgin or lampante olive oils) or autochthonous olive cultivar (i.e., cv Chétoui and cv Shali) was evaluated for the first time. Linear discrimination analysis coupled with the simulated annealing variable selection algorithm showed that the signal profiles of olive oils hydroethanolic extracts allowed olive oils discrimination according to physicochemical quality level (classification model based on 25 signals enabling 84 ± 9% correct classifications for repeated K-fold cross-validation), and olive cultivar (classification model based on 20 signals with an average sensitivity of 94 ± 6% for repeated K-fold cross-validation), regardless of the geographical origin and olive variety or the olive quality, respectively. The results confirmed, for the first time, the potential discrimination of the electronic tongue, attributed to the observed quantitative response (sensitivities ranging from 66.6 to +57.7 mV/decade) of the E-tongue multi-sensors towards standard solutions of polar compounds (aldehydes, esters and alcohols) usually found in olive oils and that are related to their sensory positive attributes like green and fruity.This work was financially supported by Project POCI-01–0145-FEDER-006984–Associate Laboratory LSRE-LCM and by Project UID/QUI/00616/2013–CQ-VR both funded by FEDER—Fundo Europeu de Desenvolvimento Regional through COMPETE2020-Programa Operacional Competitividade e Internacionalização (POCI)—and by national funds through FCTFundação para a Ciência e a Tecnologia, Portugal. Strategic funding of UID/BIO/04469/2013 unit is also acknowledged. Nuno Rodrigues thanks FCT, POPH-QREN and FSE for the Ph.D. Grant (SFRH/ BD/104038/2014).info:eu-repo/semantics/publishedVersio

Biodiversity of tunisian virgin olive oils : valorization through quality approach (Tunolival)

Dans un objectif de valorisation des huiles d’olive tunisiennes, les huiles de huit variétés autochtones : Chemchali, Chemlali Sfax, Chemlali Zarzis, Chétoui, Oueslati, Sayali, Zalmati et Zarrazi ont été étudiées et caractérisées par des techniques spectroscopique et chromatographique en tenant compte de leurs composés mineurs (acides gras mineurs, squalène, phénols totaux et α-, β- et γ-tocophérols). Une banque de données à été créé à partir des analyses de la composition en acides gras et des spectres proche infrarouge de 516 échantillons d’huiles d’olive vierges. Quatre outils d’authentification de l’origine variétale, basés sur l’utilisation des approches statistiques et chimiométriques associées aux données chromatographiques et spectrales, ont été élaborés.In order to valorize the Tunisian olive oil production, eight autochthonous oil varieties (Chemchali, Chemlali Sfax, Chemlali Zarzis, Chétoui, Oueslati, Sayali, Zalmati and Zarrazi) were characterized by chromatographic and vibrational spectroscopy approaches. Fatty acid, squalene and near infrared spectra were analyzed in 516 samples which were used to create the data bank. Four origin varietal authentication tools were established using statistic and chemometric fatty acid treatment, NIR Spectra and olive oil minor fraction (minor fatty acids, squalene, totals phenols and α, β and γ-tocopherols)

Multiblock chemometrics for the discrimination of three extra virgin olive oil varieties

International audienceTo discriminate samples from three varieties of Tunisian extra virgin olive oils, weighted and non-weighted multiblock partial least squares-discriminant analysis (MB-PLS1-DA) models were compared to PLS1-DA models using data obtained by gas chromatography (GC), or global composition through mid-infrared spectra (MIR). Models performances were determined using percentages of sensitivity, specificity and total correct classification. The choice of threshold level for the interpretation of PLS1-DA results was considered. PLS1-DA models using GC data gave better results than those using MIR data. Even with the most conservative threshold, PLS1-DA on GC data allowed very good predictions for Chemlali variety (99% correct classification), but had more difficulty to discriminate Chetoui and Oueslati samples (95% and 84% correct classification respectively). Non-weighted MB-PLS1-DA models benefiting from the synergy between the two sources of data were more discriminative than simple PLS1-DA, yielding better prediction for Chetoui and Oueslati varieties (98% and 90% correct classification respectively)

A new simplex chemometric approach to identify olive oil blends with potentially high traceability

International audienceOlive oil blends (OOBs) are complex matrices combining different cultivars at variable proportions. Although qualitative determinations of OOBs have been subjected to several chemometric works, quantitative evaluations of their contents remain poorly developed because of traceability difficulties concerning co-occurring cultivars. Around this question, we recently published an original simplex approach helping to develop predictive models of the proportions of co-occurring cultivars from chemical profiles of resulting blends (Semmar & Artaud, 2015). Beyond predictive model construction and validation, this paper presents an extension based on prediction errors' analysis to statistically define the blends with the highest predictability among all the possible ones that can be made by mixing cultivars at different proportions. This provides an interesting way to identify a priori labeled commercial products with potentially high traceability taking into account the natural chemical variability of different constitutive cultivars

Biodiversity of Tunisian virgin olive oils: varietal origin classification according to their minor compounds

International audienceThe analysis of minor compounds (minor fatty acids, squalene, phenols and tocopherols) of eight autochthonous Tunisian varieties of virgin olive oils (VOOs) (Chemchali, Chemlali Sfax, Chemlali Zarzis, Chetoui, Oueslati, Sayali, Zalmati and Zarrazi) allows for the varietal origin authentication. The compositions of minor ω9 and ω7 fatty acids, especially 16:1 and 18:1 isomers, are important criteria for distinction among eight varieties of VOOs. The squalene content was ranged between 1.39 and 5.37 g/kg. Total phenol and the sum of α-, β- and γ-tocopherol contents were, respectively, ranged between 81–691 and 147–585 mg/kg. This minor fraction is not only highly dependent on the variety, but also the maturity index. Chemchali, Zarrazi and Sayali are characterized by having high content in total phenols, whereas Chemlali Sfax, Chemlali Zarzis and Zalmati are rich in total tocopherols. The intervarietal variation in the studied minor compounds was confirmed by chemometric treatment through PCAs. The potential of using the minor compounds in the authentication of the Tunisian olive oil varietal origin was tested through PLS-DA performed for the two most representative varieties (Chemlali Sfax and Chetoui). The obtained percentages of correct classification (superior to 97 %) proved the potential of the used method in varietal origin authentication

Authentication of Tunisian virgin olive oils by chemometric analysis of fatty acid compositions and NIR spectra. Comparison with Maghrebian and French virgin olive oils

International audienceSix Tunisian virgin olive oil (VOO) varieties, Chemlali Sfax, Chetoui, Chemchali, Oueslati, Zarrazi and Zalmati, were characterised by two analytical methods. The gas chromatography allowed the determination of 14 fatty acids and squalene amounts. With fatty acids of each variety, a characteristic ''morphotypes'' for each oil variety was established. Chemlali Sfax and Zalmati showed strong similarities. Gas chromatography of fatty acid methyl esters (FAME) and near infrared (NIR) spectra of oils, associated to chemometric treatment, allowed the study of the inter-varietal variability and the verification of the variety origins of some Tunisian commercial VOOs. The specificity of Tunisian VOOs was evaluated by comparing the samples to Algerian, Moroccan and French Protected Designation of Origin VOOs. Classification in varietal origins by SIMCA used the FAME compositions and NIR spectra of the most represented varieties (Chemlali Sfax, Chetoui and Oueslati) showed a high potential to authenticate the varietal origin of Tunisian VOOs

Rapid Assessment of Monovarietal Portuguese Extra Virgin Olive Oil’s (EVOO’s) Fatty Acids by Fourier-Transform Near-Infrared Spectroscopy (FT-NIRS)

A rapid method for the evaluation of fatty acids (FA) of monovarietal Portuguese extra virgin olive oils (EVOOs) (n¼82) from Alentejo, southcentral region of Portugal, is developed based on Fourier-transform nearinfrared spectroscopy (FT-NIRS). The contents of FA-components (previously determined per conventional gas chromatography) are correlated with FTNIRS data (independent variable), by means of full cross-validation partial least squares regression (CVPLSR). CVPLSR is run using standard normal variate (SNV) data pre-processing and the nonlinear iterative partial least squares (NIPALS) algorithm. Obtained correlation models are characterized with good statistics: high correlation coefficients (R>0.85) and low root mean square errors (RMSE<2.04). Obtained values of the residual predictive deviation (RPD) of CVPLSR-model, higher than 5.0 (C18:1, C18:2, MUFA, PUFA) confirm the FT-NIRS as a potential method for rapid quality control of EVOO’s FA. Practical Applications: In this work for the first time, fatty acid (FA) profile of monovarietal extra virgin olive oil (EVOO) samples of the greatest olive region in Portugal—Alentejo—is analyzed by Fourier-transform near-infrared spectroscopy (FT-NIRS) and chemometrics. Obtained high-quality results allow one to recommend this technique from monitoring to quality control analysis of FA (in particular, of representative unsaturated FA), in a great number of olive oil samples, in near-real time