Quality Parameters Of Virgin Olive Oil Research Articles

A chemometric strategy to evaluate the comparability of PLS models obtained from quartz cuvettes and disposable glass vials in the determination of extra virgin olive oil quality parameters by NIR spectroscopy

In the present study, a chemometric strategy was deployed for comparing the analytical performances of quartz cuvettes and disposable glass vials in the analysis of olive oil by near infrared spectroscopy (NIRS). Nowadays, laboratories that perform ‘highly frequent’ analysis on extra virgin olive oil (EVOO) by NIRS usually employ quartz cuvettes. This results in time-consuming measurements, especially in the cleaning phase, and an increased cost for non-green cleaning solvents. The use of mono-use glass vials may reduce time and costs significantly, but their analytical performances in EVOO analysis, have not yet been investigated. In order to reach this goal, a set of 106 EVOO samples from different Italian olive-growing areas were collected and analysed using both quartz cuvettes and mono-use glass vials. From spectral data, multivariate calibration models were developed to estimate quality parameters of extra virgin olive oil: methyl esters of fatty acids (FAMEs) and triacylglycerols (TAGs) determined by a fast-GC approach and an UHPLC system, respectively. An optimisation procedure was performed in order to individuate the best pre-treatment and the optimal complexity for each model. The predictive ability of each PLS model was evaluated on an independent test set. The Passing-Bablok linear regression was lastly used to statistically compare the performances of the two different types of cuvettes. In light of the outcomes of the present study, analytical performances of quartz cuvettes and disposable glass vials were considered not significantly different in predicting the olive oil quality parameters taken into account.

Physicochemical characterization of virgin olive oil obtained using an ultrasound-assisted extraction at an industrial scale: Influence of olive maturity index and malaxation time

Ultrasound-assisted extraction is an innovative technique applied to the extraction process for virgin olive oil (VOO), which is generally employed to increase plant efficiency and improve product quality. A high-power ultrasound (US) device was introduced at an industrial plant that can process at 2 tons/h to evaluate the technique’s physicochemical impact on quality parameters of VOO that was caused by an intensive mass transfer induced by acoustic cavitation process and shockwaves. The impact on oil yield was also evaluated with respect to the ripening stage and malaxation time. No significant effects on the legal and commercial parameters of VOO (including quality indices, sterols, triterpene dialcohols, waxes and diacylglycerols) were found for olives at medium-early ripening stage. Significant physical changes, increased extraction yield (22.7%), enhanced phenol content (10.1%) were observed in US-VOO compared to control (C) oil extracted with a traditional process at an early maturity index.

How clarification systems can affect virgin olive oil composition and quality at industrial scale

The effect of two different clarification systems, vertical centrifugal separator (VCS) with minimal water addition, and conical bottom settling tank (CBST), on virgin olive oil (VOO) composition and quality was studied at industrial scale for three crop years. In general, for the studied clarification systems, higher clarification values were reached for horizontal screw solid bowl (HSSB) oils with higher moisture and solid content. VCS showed higher clarification efficiency for HSSB oils with higher moisture and solid content. No notable differences were observed on the quality indices between evaluated clarification systems. Phenolic compounds showed a significant decrease when the HSSB oils were clarified by CBST. In general, a better sensory score was observed when the oils were clarified by VCS.Practical applications: The VCS with a minimal water addition could result a better option to produce VOO of improved quality, since is an efficient and quick operation that reduces the contact between oil and the remaining water and impurities content during the storage stage. This leads to prolong VOO shelf‐life and conservation of positive sensory notes, due to preservation of the quality indexes and minor components. Besides, this clarification system reduces the water consumption and generated wastewater regarding to conventional vertical centrifugation, and therefore can be considered more environmentally friendly.Effect of two different clarification systems (vertical centrifugal separator with minimal water addition and conical bottom settling tanks) on the virgin olive oil quality parameters, composition, and sensory characteristics.

STORAGE OF OLIVES (OLEA EUROPAEA): EFFECT ON THE QUALITY PARAMETERS AND THE RADICAL SCAVENGING ACTIVITY OF THE TOTAL FRACTION, LIPIDIC AND METHANOLIC FRACTIONS OF THE VOO

ISHS International symposium on Medicinal and Aromatic Plants - SIPAM 2012 STORAGE OF OLIVES (OLEA EUROPAEA): EFFECT ON THE QUALITY PARAMETERS AND THE RADICAL SCAVENGING ACTIVITY OF THE TOTAL FRACTION, LIPIDIC AND METHANOLIC FRACTIONS OF THE VOO

NIR prediction of fruit moisture, free acidity and oil content in intact olives

In this work, the prediction of olive fruit and virgin olive oil quality parameters through the direct measuring of the fruit using near infrared spectrometry (NIRS) has been investigated and the effectiveness of a portable spectrometer has been assessed. Models and calibration tests were developed using both the hexane-isopropanol extraction of individual olive fruits, and the Soxhlet extraction of olive paste. The parameters analyzed were the free acidity in olive oil, oil yield from physical extraction, oil content referring to fresh weight, oil content referring to dry matter and fruit moisture. The results indicate a good predictive potential with both methodologies and serve to encourage improvement in the obtained models through the enlargement of the calibrations. Fruit moisture prediction models showed high accuracy.

Comparison of Fourier Transform near Infrared Spectroscopy Partial Least Square Regression Models for South African Extra Virgin Olive Oil Using Spectra Collected on Two Spectrophotometers at Different Resolutions and Path Lengths

Near infrared (NIR) partial least square (PLS) regression models for the determination of several extra virgin olive oil quality parameters (peroxide value, free fatty acid content, specific extinction coefficients K232 and K270, linoleic, oleic and saturated acid content, α:β ratios of linoleic and oleic acid, pigment and total polyphenol content, thiobarbituric acid reactive substances value) were developed from spectra collected on two different Fourier transform near infrared (FT-NIR) spectrophotometers using different sample holders, path lengths and resolutions. Spectra were recorded on the PerkinElmer IdentiCheck spectrophotometer (9091–4000 cm−1) in transmittance mode at resolutions of 64, 32, 16 and 8 cm−1 at each of two path lengths (0.2 and 0.5 mm) and on the Büchi NIRLab N-200 instrument (10 224–4000 cm−1) in transflectance mode at a fixed resolution of 8 cm−1 and a path length of 0.6 mm. The PLS regression models, for each respective parameter, were statistically compared to evaluate the effect of different sample scanning conditions on model performance. The comparison of the regression models developed from PerkinElmer spectra revealed that spectra recorded at the lowest resolution of 64 cm−1 produced equally accurate models when compared to higher resolution spectra and that the two path lengths resulted in no significant differences. Comparisons between PLS models developed from Büchi and PerkinElmer spectra, respectively, showed significant differences for only a few parameters. In general, reliable prediction results were obtained for the peroxide value [standard error of prediction ( SEP) = 4.15 meq O2 kg−1, r2 = 0.87], K232 ( SEP = 0.94, r2 = 0.94), linoleic acid ( SEP = 0.83%, r2 = 0.90) and saturated acid content ( SEP = 0.91%, r2 = 0.88) PLS regression models.