Quality Parameters Of Olive Oil Research Articles

Bioactive Compounds in the Oils of the Autochthonous Slovenian Olive Varieties ‘Buga’, ‘Črnica’ and ‘Drobnica’

The adaptation of autochthonous olive varieties to local soil and climatic conditions can lead to a unique chemical composition and characteristics of olive oils that may differ from the generally accepted quality standards set out in the International Olive Oil Council strategy documents and EU regulations. Therefore, the fatty acid composition, biophenol, tocopherol, sterol and triterpenic dialcohol content and composition of the autochthonous Slovenian olive varieties ‘Buga’, ‘Črnica’ and ‘Drobnica’ were studied for a three-year period with the aim of valorising the characteristics of the three olive varieties. Standardised and accredited analytical methods in accordance with SIST EN ISO/IEC 17025:2017 were applied. The results of the investigation showed that the highest average amount of oleic acid (75.75%) was found in the oils of the ‘Črnica’ variety, followed by the ‘Drobnica’ (72.06%) and the ‘Buga’ (68.73%). All three varieties are a good source of total biophenols (‘Buga’ 616 mg/kg, ‘Drobnica’ 569 mg/kg and ‘Črnica’ 427 mg/kg) and α-tocopherol (‘Buga’ 378 mg/kg, ‘Drobnica’ 279 mg/kg, and ‘Črnica’ 243 mg/kg). ‘Buga’ and ‘Drobnica’ are characterised by high amounts of total sterols, 2468 mg/kg and 2391 mg/kg, respectively, while ‘Črnica’ oils, in comparison, showed a lower average value of total sterols (1351 mg/kg). Due to their exceptional chemical composition, ‘Buga’, ‘Črnica’ and ‘Drobnica’ show great potential for the further cultivation and valorisation of traditional olive oil production in the region, thus contributing to the preservation of biodiversity and local traditions. The quality parameters of olive oil from the autochthonous Slovenian olive varieties ‘Buga’, ‘Črnica’ and ‘Drobnica’ also fulfil the limits for extra virgin olive oil according to the Commission Delegated Regulation (EU) 2022/2104, despite local climatic influences. However, accelerated growth due to climatic changes affecting early harvest can lead to them falling outside these limits, which was observed in particular for the ‘Buga’ variety in terms of the linoleic acid content. This study emphasises the importance of timing the harvest to achieve optimum maturity and meet EU quality standards, taking into account the genetic makeup of the varieties and their response to the current climatic conditions.

Challenges and Opportunities for Pilot Scaling-Up Extraction of Olive Oil Assisted by Pulsed Electric Fields: Process, Product, and Economic Evaluation

This study aimed to investigate the impact of Pulsed Electric Fields (PEF) technology in the extraction of olive oil on a pilot scale, using the “Galega Vulgar” olive variety as raw material. The extraction assisted by PEF had a malaxation time of 30 min and was compared with the traditional process of 45 min of malaxation. The main quality parameters of olive oil and the PEF’s cost-benefit assessment were performed. The incorporation of PEF in olive oil production reduced the malaxation stage by 33% without compromising the yield or extra-virgin classification. This efficiency leads to a potential 12.3% increase in annual olive oil production, with a 12.3% and 36.8% rise in revenue and gross profit, respectively. For small-scale production, the considerable upfront investment required for PEF equipment may be a challenge in terms of return on investment. In this scenario, opting for a renting scheme is the best economic solution, especially given the seasonal nature of olive oil production. In medium- to large-scale production, the investment in PEF is a sound investment since it is possible to achieve, with an equipment cost of EUR 450,000 and a production output of 5 tons per hour, an annual ROI of 20%.

Detection and quantification of olive oil adulteration using fluorescence spectroscopy and chemometric tools

The increasing incidence of fraud in the olive oil market, particularly through adulteration with cheaper oils, poses a major challenge for the industry. This study examines the effectiveness of fluorescence spectroscopy combined with chemometric tools as a method to detect and quantify olive oil adulteration. Chemical analyses were used to measure parameters such as specific absorption coefficients K232 and K270, peroxide value, and acidity, in accordance with International Olive Council (IOC) standards. These measurements were conducted on samples of olive oil blended with varying percentages of adulterating oils. 3D fluorescence spectra were analyzed to examine the changes induced by adulteration. The results show that free acidity and peroxide value decrease with increasing adulteration degree, while the parameters K232 and K270 increase with the degree of adulteration. Principal component analysis (PCA) was effectively used to differentiate samples based on the percentage of adulterant. A partial least squares (PLS) regression model was developed, achieving a correlation coefficient of 0.999 for predicting the percentage of adulterant in olive oil. This PLS model also proved effective in predicting oil quality parameters such as free acidity and K232 and K270 indices. The results of this study demonstrate the significant potential of fluorescence spectroscopy as a rapid and non-destructive method for olive oil authentication. PCA emerges as a powerful tool for characterizing pure oils without requiring sample preparation or destruction. Furthermore, PLS models provide accurate means to predict both the presence of adulterants and olive oil quality parameters. This approach offers a promising solution to combat fraud in the olive oil industry, ensuring product integrity and quality.

Optimized variable selection and machine learning models for olive oil quality assessment using portable near infrared spectroscopy

Olive oil is a key component of the Mediterranean diet, rich in antioxidants and beneficial monounsaturated fatty acids. As a result, high-quality olive oil is in great demand, with its price varying depending on its quality. Traditional chemical tests for assessing olive oil quality are expensive and time-consuming. To address these limitations, this study explores the use of near infrared spectroscopy (NIRS) in predicting key quality parameters of olive oil, including acidity, K232, and K270. To this end, a set of 200 olive oil samples was collected from various agricultural regions of Morocco, covering all three quality categories (extra virgin, virgin, and ordinary virgin). The findings of this study have implications for reducing analysis time and costs associated with olive oil quality assessment. To predict olive oil quality parameters, chemical analysis was conducted in accordance with international standards, while the spectra were obtained using a portable NIR spectrometer. Partial least squares regression (PLSR) was employed along with various variable selection algorithms to establish the relationship between wavelengths and chemical data in order to accurately predict the quality parameters. Through this approach, the study aimed to enhance the efficiency and accuracy of olive oil quality assessment. The obtained results show that NIRS combined with machine learning accurately predicted the acidity using iPLS methods for variable selection, it generates a PLSR with coefficients of determination R2 = 0.94, root mean square error RMSE = 0.32 and ratios of standard error of performance to standard deviation RPD = 4.2 for the validation set. Also, the use of variable selection methods improves the quality of the prediction. For K232 and K270 the NIRS shows moderate prediction performance, it gave an R2 between 0.60 and 0.75. Generally, the results showed that it was possible to predict acidity K232, and K270 parameters with excellent to moderate accuracy for the two last parameters. Moreover, it was also possible to distinguish between different quality groups of olive oil using the principal component analysis PCA, and the use of variable selection helps to use the useful wavelength for the prediction olive oil using a portable NIR spectrometer.

Quality parameters of olive oils at different ripening periods as affected by olive fruit fly infestation and olive anthracnose

Olive pests and diseases influence olive oil quality. Ayvalik olive cultivar is important between local cultivars grown in Turkey. This study aimed to monitor the effects of olive pests and diseases (olive fruit fly attack and olive anthracnose) on Ayvalik olive oil quality parameters such as free fatty acids (FFA), peroxide value (PV), specific extinction coefficients (K232, K270, and ΔK). Besides, Ayvalik olive fruits were collected at six harvest times, and the level of ripening with olive pests was also evaluated. Results showed that the FFA level influenced negatively by olive pests, mainly olive anthracnose. At the end of harvesting, FFA of oils from damaged olive anthracnose reached up to 5.42 (% oleic acid). Except for the first harvest period, the other quality parameters remained between limit values, and slight differences were observed between healthy and damaged olives. At the first harvest period, PV and K232 (7.02 mEq O2/kg, 2.22) of olive oil from fly-infected olive had higher values than the other samples. The stage of ripening, healthy, and damaged olives affected slightly certain fatty acids of the oils. Total phenolics, o-diphenol, and α-tocopherol content of oils from healthy fruits had higher values than oils from damaged olives. Besides, the antioxidant activity of oils obtained from healthy olives showed higher values compared to the oils from infected olive fruits.

The Introduction of Allochthonous Olive Variety and Super High-Density System in the Abruzzo Region: A Study on Olive Oil Quality

The transition to a sustainable economic and environmental management of olive oil sector needs to be implemented in both national and regional territories through the introduction and development of innovative growing systems and variety. In this study, the olive oil quality parameters of local and allochthonous varieties cultivated in different orchards located in the Abruzzo region (Italy), using traditional and super high-density systems, were analyzed. Frantene, Lecciana, Koroneiki, and a mix of Arbequina and Lecciana provided olive oils rich in flavonoids and secoiridoids compounds with respect to the local varieties Frantoio, Leccino, and a mix of Dritta, Leccino, and Pendolino. Oleic/linoleic ratio was influenced by cultivar and training systems with super high-density olive oils rich in oleic acid. Frantene showed a peculiar fatty acid profile different from cultivars grown in the same location; moreover, interesting similarities were found between Frantene and the mix of Dritta, Leccino, and Pendolino in terms of health-related compounds. The potential development of innovative sustainable training system to improve olive oil quality was highlighted. The study's results identify olive varieties suitable for super high-density systems spread in the Abruzzo region, representing a valid alternative for the olive growers to improve both the quality of the olive oil, as well as the company's income.

Non-destructive Fluorescence Spectroscopy as a Tool for Discriminating Between Olive Oils According to Agronomic Practices and for Assessing Quality Parameters

A non-destructive fluorescence method combined with chemometric algorithms has been developed for discriminating between olive oils. The excitation-emission matrices (EEMs) of two olive oil varieties (Arbosana and Oliana) from two crop seasons, which had undergone two different irrigation treatments (control irrigation strategy and regulated deficit irrigation (RDI)), were recorded. EEMs were analysed using parallel factor analysis (PARAFAC), followed by linear discriminant analysis (LDA) incorporating three PARAFAC components. This analysis was able to discriminate between olive oils according to crop season (100% of predictions in the validation set were correct) and variety (100% of predictions were correct). Moreover, good discrimination (80% of correct predictions) was also achieved when examining olive oils belonging to the same variety but submitted to two different irrigation treatments. Further, the olive oil quality parameters obtained using conventional methods were compared with those obtained using unfolded partial least squares (U-PLS). Good correlation coefficients were obtained for Rancimat hours (r = 0.87), K270 (r = 0.75) and total polyphenol content (r = 0.94).

Identification and Quantification of Olive Oil Quality Parameters Using an Electronic Nose

An electronic nose (EN), which is a kind of chemical sensors, was employed to check olive oil quality parameters. Fifty samples of olive oil, covering the four quality categories extra virgin, virgin, ordinary virgin and lampante, were gathered from different Palestinian cities. The samples were analysed chemically using routine tests and signals for each chemical were obtained using EN. Each signal acquisition represents the concentration of certain chemical constituents. Partial least squares (PLS) models were used to analyse both chemical and EN data. The results demonstrate that the EN was capable of modelling the acidity parameter with a good performance. The correlation coefficients of the PLS-1 model for acidity were 0.87 and 0.88 for calibration and validation sets, respectively. Furthermore, the values of the standard error of performance to standard deviation (RPD) for acidity were 2.61 and 2.68 for the calibration and the validation sets, respectively. It was found that two principal components (PCs) in the PLS-1 scores plot model explained 86% and 5% of EN and acidity variance, respectively. PLS-1 scores plot showed a high performance in classifying olive oil samples according to quality categories. The results demonstrated that EN can predict/model acidity with good precision. Additionally, EN was able to discriminate between diverse olive oil quality categories.

Therapeutical effect of olive oil aggregate to 4-methoxycinnamic acid diester obtained from carnauba (Copernicia prunifera) wax (PCO–C) on dyslipidemia, hyperglycemia, and oxidative stress

Olive oil is an important food with interesting functional properties and is widely indicated as a hypolipidemic, oxidative stress reliever and hypolipidemic agent due to its chemical structures and biological functions. The present study analyzed the hypoglycaemic, hypolipidemic, technological, and sensory potential of 4-methoxycinnamic acid (PCO–C) diester aggregate olive oil, obtained from the wax powder from carnauba (Copernicia prunifera). Zebrafish was used as an experimental obesity model. After developing obesity, with hyperglycemia and hyperlipidemia, fishes were submitted to extra virgin olive oil aggregated to 4-methoxycinnamic acid diester (PCO–C + AZ) or not, for 4 days. Also, the product PCO–C + AZ was submitted to rheological and sensory analysis. The PCO–C + AZ shown a 43% reduction (p < 0.01) in blood glucose and the rheological findings did not show any change in the quality parameters of olive oil due to the aggregation to PCO–C. Oil + PCO–C (100 mg/kg) was able to reduce (***p < 0.001) cholesterol and triacylglycerol levels of animals in the treatment group when compared to animals in the control group. In addition, all the treatments used were able to significantly reduce the hepatic levels of reactive oxygen species ((**p < 0.01 vs. Control). Additionally, the acceptability of the product shown all acceptability index (IA%) parameters above 70%. Thus, we concluded that the product PCO–C + AZ has a hypoglycaemic effect, presenting quality parameters very similar to the original extra virgin olive oil.

From olive to olive oil: a general approach

This study aimed to carry out a systematic literature review about olives, extraction methods, physical and chemical characterization and identity and quality parameters of olive oils, as well as technological alternatives for using by-products. Olive oil is the oil extracted from the ripe fruits of the olive tree (Olea europaea L.). Trees have been cultivated in the Mediterranean Region for several centuries and thousands of cultivars differ by weight, size and chemical characteristics of the fruits. Currently, olive oil is produced worldwide and the olive plant was recently introduced in the city of Diamantina, Minas Gerais. The lipid content is mostly composed of oleic acid and smaller fractions of phenolic compounds, phytosterols and pigments, substances with antioxidant and bioactive activities that promote oxidative stability of the oil and beneficial effects on human health. The main extraction of olive oil consists of crushing, pressing and centrifuging, generating by-products that can be reused for recovery of compounds or generation of new products in the food industry. After extraction, the oil is submitted to several physical and chemical analyzes to define the identity and quality parameters, according to international standards. The main characteristics that define the quality of olive oil are free acidity, peroxide index, specific extinction index, instrumental color and fatty acids profile.

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.

Determination of Moisture in Olive Oil: Rapid FT-NIR Spectroscopic Procedure Based on the Karl-Fischer Reference Method.

According to CODEX, moisture and volatile matter are olive oil quality parameters and the development of a rapid screening method for the determination of moisture is of interest. We recently demonstrated for the first time that the weak near-infrared (NIR) band near 5260 cm-1 is primarily attributed to a water O-H combination band. To determine the intensity of this band, we measured the peak-to-peak (p-p) height of its first derivative and generated exponential calibration curves for p-p height versus gravimetrically determined concentrations of spiked water in olive oils that had been purged of their initial moisture contents. To further optimize this univariate calibration method, calibration curves were generated in the present study based on plotting the moisture band first derivative p-p heights for neat olive oils (that were neither purged nor spiked) versus the moisture concentrations obtained by the Karl-Fischer (KF) primary reference method. To enhance the speed of FT-NIR data collection, measurements were carried in the transmission mode using disposable glass tubes. We also developed and compared a multivariate partial least squares approach to the univariate one. All the spectra were collected in two separate laboratories using two FT-NIR spectrometers of the same brand and model and no significant difference (p > 0.05) was found between the two laboratory determinations and the KF reference values at a 95% confidence interval. High accuracies were found with the two FT-NIR instruments used, as indicated by the low root mean squared error (RMSE, %) for predicted values obtained with the univariate procedure (RMSE = 0.008% and 0.010%) and the multivariate one, which yielded an even lower value (RMSE= 0.007% for both instruments). These results suggest that, once validated, the FT-NIR approach could potentially be a rapid substitute for the KF method.

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Visible Near Infrared Spectroscopy as a Green Technology: An Environmental Impact Comparative Study on Olive Oil Analyses

The olive oil industry is a significant productive sector in the European Union and the related production process is characterised by practices and techniques associated with several adverse effects on the environment. In the literature, many works on the environmental impact assessment of the olive oil chain have been carried out but the effects of the analytical analyses procedures were considered to be negligible. Currently, the reduction of solvents and of energy consumption in the laboratory has become a crucial aspect to be investigated. In this scenario, non-destructive optical methods based on visible/near-infrared (vis/NIR) spectroscopy represent a simple, rapid, and easy-to-use method to predict olive and olive oil quality parameters. Therefore, the aim of the work was to evaluate the environmental impact of the use of optical vis/NIR technologies for analytical assessment in comparison to chemical analyses on olive oil. The life cycle assessment method (LCA) was used. The functional unit defined for this study was the analysis and a “from cradle to grave” approach was applied. The vis/NIR technology results were distinctly better, by 36 times on average, than the chemical methods. Attention must be paid to the calibration phase of the vis/NIR instrumentation: In this case, the two methods must coexist for this initial procedure to obtain the required reference data for a reliable chemometric model. In conclusion, the vis/NIR spectroscopy gives very reliable results and can be considered a green technology, representing a choice among applications of low environmental impact analytical technologies.

Application of an electronic tongue as a single-run tool for olive oils’ physicochemical and sensory simultaneous assessment

Olive oil is highly appreciated due to its nutritional and organoleptic characteristics. However, a huge compositional variation is observed between olive oils, requiring the use of diverse analytical techniques for its classification including titration, spectrophotometry and chromatography, as well as sensory analysis. Chemical analysis is usually time-consuming, expensive and require skilled technicians, while the sensorial ones are dependent upon individual subjective evaluations, even if performed by trained panellists. This work evaluated and demonstrated the feasibility of using a potentiometric electronic tongue, comprising non-specific lipid polymeric and cross-sensitive sensor membranes, coupled with chemometric tools based on different sub-sets of sensors (from 11 to 14 sensors), to predict key quality parameters of olive oils based on single-run assays. The multivariate linear models established for 23 centenarian olive trees from different cultivars allowed predicting peroxide value, oxidative stability, total phenols and tocopherols contents, CIELAB scale parameters (L*, a* and b* values), as well as 11 gustatory-retronasal positive attributes (green, sweet, bitter, pungent, tomato and tomato leaves, apple, banana, cabbage, fresh herbs and dry fruits) with satisfactory accuracy (0.90 ± 0.07 ≤ R2 ≤ 0.98 ± 0.02 for the repeated K-fold-CV procedure, which ensured that 25% of the data was used for internal-validation purposes). The electronic tongue device had an accuracy statistically similar to that achieved with standard analytical techniques, pointing out the versatility of the device for the fast and simultaneous chemical and sensory analysis of olive oil.

A Rapid, Univariate FT-NIR Procedure to Determine Moisture Concentration in Olive Oil.

We recently observed that the weak near-infrared (NIR) band near 5260 cm-1 was relatively more intense for extra virgin olive oil (EVOO) than for refined olive oil (ROO). We also observed that its intensity was diminished upon heating and erroneously presumed that it may be attributed to volatile carbonyl components in EVOO. In the present study we demonstrate for the first time that this band is primarily attributed to a water O-H combination band. To accurately determine the intensity of this weak band, observed on a shifted and sloping baseline, we measured the peak-to-peak (p-p) height of its first derivative. An exponential calibration curve for p-p height versus gravimetrically-determined concentration of spiked water was satisfactorily generated. The calibration curve was first evaluated by using independent sets of gravimetrically prepared test samples. Subsequently, it was used to determine the moisture content, a quality parameter, for a limited set of authenticated reference olive oils whose quality and purity were confirmed by official methods. These concentrations, 0.098-0.12% H2O (w/w) for EVOO, 0.022-0.030% H2O (w/w) for ROO, and 0.028-0.054% H2O (w/w) for pomace olive oil (POO), were consistent with those reported in the literature. For 88 commercial products investigated, the moisture levels fell in the range from 0.026% to 0.13% (w/w). The correlation between moisture content and other olive oil quality parameters has been reported in the literature and has yet to be further investigated.

Investigation of combined ultrasound and microwave pretreatments and enzyme addition on the main phenolics and some quality parameters of olive oil

Olive oil was obtained by applying laboratory scale microwave (MW) and ultrasound (US) technologies and enzymes (E) after olive crushing and malaxation. The effects of these technologies on some physical and chemical properties of olive oil have been examined with focus on phenolics in olive oil. The aim was to evaluate the combined effect of MW and US applications and E to olive paste by comparing with conventional production. The secoiridoids were present with lower values in US applied samples; as an example, the amount of 3-4-DHPEA-EDA in US treated sample was 59.36 mg kg–1 oil, whereas its amount was 92.36 mg kg–1 in the sample of conventional extraction. US resulted in the highest decrease (62%), and MW+US condition resulted in the lowest decrease (25.7%) in terms of total phenolics content. The US and MW pretreatments resulted in more advantageous properties in terms of free acidity, peroxides, and phenolics when applied together than their single applications.

Isıtma İşleminin Çekişte Zeytinyağının Kalite, Oksidatif Stabilite ve Yağ Asidi Bileşimine Etkisi

Çalışmanın amacı Çekişte çeşidi zeytinlerden elde edilen zeytinyağlarının ısıtma işlemi sırasında temel kalite kriterleri, oksidatif stabilite ve yağ asidi bileşiminde meydana gelen değişimlerin belirlenmesidir. Bu amaçla Aydın ilinden 2017 yılında hasat edilmiş olan Çekişte çeşidi zeytinlerden elde edilmiş olan zeytinyağı, 100°C sıcaklıkta ve 20 L/saat hava akışı altında toplamda 50 saat süreyle ısıtılmıştır ve 10 saatlik aralıklarla serbest yağ asidi oranı, peroksit sayısı, dien ve trien (K232 ve K270) değerleri, toplam fenol miktarı, antioksidan aktivite, klorofil ve karotenoid miktarları ile yağ asidi kompozisyonları yönünden analiz edilmiştir. Ayrıca örneklerin indüksiyon periyodu olarak ifade edilen oksidatif stabiliteleri belirlenmiştir. Çalışma sonunda temel kalite parametrelerinden serbest yağ asidi miktarı, peroksit sayısı, dien ve trien (K232 ve K270) değerlerinin ısıtma işlemi ile birlikte artış gösterdiği saptanmıştır. Örneklerin toplam fenol, antioksidan aktivite, klorofil ve karotenoid miktarları ise ısıtma süresinin artmasıyla birlikte kademeli olarak azalmıştır. Benzer şekilde indüksiyon periyodunun da işlem süresinin artmasıyla birlikte azaldığı tespit edilmiştir. Zeytinyağı örneklerinde tespit edilen yağ asitlerinden linolenik asit miktarının ise işlem sonunda önemli düzeyde arttığı, oleik asit miktarının ise işlem öncesine göre azalma eğiliminde olduğu saptanmıştır.

Characterization of aroma, aroma-active compounds and fatty acids profiles of cv. Nizip Yaglik oils as affected by three maturity periods of olives.

The present study aimed to investigate how olive maturity indices (MI) (2.5, 3.5 and 4.5 MI) affect the aroma, aroma-active compounds, fatty acid profiles and color properties of cv. Nizip Yaglik olive oils. Various techniques for extracting volatiles from oil materials are available in the literature. Aroma compounds were extracted by the solvent-assisted flavor evaporation extraction method for the first time in olive oil. The type and number of aroma-active compounds varied according to maturity periods of olives. A total of 22, 21 and 20 different key odorants were found in aromatic extracts of samples with 2.5, 3.5 and 4.5 MI, respectively. The most potent aroma-active compounds based on flavor dilution (FD) factor values were hexanal (green) for 2.5 MI (FD: 1024) and 3.5 MI (FD: 512), as well as 1-penten-3-ol (green-leafy) for 4.5 MI (FD: 512). Overall, olive oils obtained from unripe and medium-ripe olives had stronger green and fruity odours compared to ripe olives. Principal component analysis demonstrated that oils were clearly discriminated according to their general physicochemical analysis, fatty acids, aroma profiles and key odorants. The results of the present study show that the olive maturity period has a significant influence on the quality parameters of olive oil. © 2018 Society of Chemical Industry.

Multicommuted Flow Injection Analysis Using Chemiluminescence Detection (MCFIA-CL) for Olive Oil Analysis

This article describes the applicability of multicommuted chemiluminescence flow injection analysis (MCFIA-CL) to the determination of olive oil quality parameters. Two automated MCFIA methods were developed and validated for the determination of peroxide value (PV) and phenolic compounds in commercial extra virgin olive oil samples. The PV method proposed is based on the chemiluminescent (CL) signal produced from luminol oxidation by the olive oil hydroperoxides in basic conditions using Co(II) as catalyst, while the determination of phenolic compounds is based on CL emission generated from permanganate reduction in acidic media by hydroalcoholic extracts of olive oil. The flow assemblies for automated liquid handling consisted, respectively, of 2 and 3 three-way solenoid valves, which were controlled by a homemade electronic interface and Java-written software together with a CL detector. The signals obtained correlated well against the PV and total phenolic contents measured by the official and the Folin-Ciocalteu methods, respectively. The linear response range observed for PV allows checking whether the samples are in compliance with European Union regulations. On the other hand, the phenolic compounds content also correlated well with data reported by the well-known FC method across the entire typical concentration range of these compounds in virgin olive oils. The proposed methods are faster, safer, and more environmentally friendly than the respective official or classical ones involving lower consumption of solvents, reagents, and sample, as well as less waste generation together with a high sample throughput. Moreover, they are straightforward and cost-effective to implement in routine analysis, and can be regarded as a feasible alternative to the official or classic methods.