Olive Oil Quality Research Articles

Genome-Wide Analysis of the Polyphenol Oxidase Gene Family in Olea europaea Provides Insights into the Mechanism of Enzymatic Browning in Olive Fruit.

Browning of olive (Olea europaea L.) fruit reduces the sensory and nutritional qualities of olive oil, thereby increasing production costs. Polyphenol oxidases (PPOs) are the key enzymes that catalyze phenolic substance oxidation and mediate enzymatic browning in olive fruit, but the exact regulatory mechanism remains unclear. The main challenge is the lack of comprehensive information on OePPOs at the genome-wide level. In this study, 18 OePPO genes were identified. Subsequently, we performed a bioinformatic analysis on them. We also analyzed the expression patterns and determined the relationship among browning degree, PPO activity, and expression of OePPOs in the fruits of three olive varieties. Based on our analysis, we identified the four most conserved motifs. OePPOs were classified into two groups, with OePPOs from Group 1 showing only diphenolase activity and OePPOs from Group 2 exhibiting both mono-/diphenolase activities. Seven pairs of gene duplication events were identified, and purifying selection was found to have played a critical role in the evolution of the OePPO gene family. A positive correlation was observed between the browning degree of olive fruit and PPO activity across different olive varieties. Moreover, two important genes were found: OePPO-5 the main effector gene responsible for fruit browning, and OePPO-8, a key gene associated with specialized metabolite synthesis in the olive fruit. In short, our discoveries provide a basis for additional functional studies on OePPO genes and can help elucidate the mechanism of enzymatic browning in olive fruit in the future.

Combining remote sensing, SPAD readings, and laboratory analysis for monitoring olive groves and olive oil quality

Combining remote sensing, SPAD readings, and laboratory analysis for monitoring olive groves and olive oil quality

Potential of the Oxidized Form of the Oleuropein Aglycon to Monitor the Oil Quality Evolution of Commercial Extra-Virgin Olive Oils.

The quality of commercially available extra-virgin olive oils (VOOs) of different chemical compositions was evaluated as a function of storage (12 months), simulating market storage conditions, to find reliable and early markers of the virgin olive oil (VOOs) quality status in the market. By applying a D-optimal design using the Most Descriptive Compound (MDC) algorithm, 20 virgin olive oils were selected. The initial concentrations of oleic acid, hydrophilic phenols, and α-tocopherol in the 20 VOOs ranged from 58.2 to 80.5%, 186.7 to 1003.2 mg/kg, and 170.7-300.6 mg/kg, respectively. K270, ∆K, (E, E)-2.4-decadienal and (E)-2-decenal, and the oxidative form of the oleuropein aglycon (3,4-DHPEA-EA-OX) reflected the VOO quality status well, with 3,4-DHPEA-EA-OX being the most relevant and quick index for simple monitoring of the "extra-virgin" commercial shelf-life category. Its HPLC-DAD evaluation is easy because of the different wavelength absorbances of the oxidized and non-oxidized form (3,4-DHPEA-EA), respectively, at 347 and 278 nm.

Effects of Filtration Processes on the Quality of Extra-Virgin Olive Oil-Literature Update.

Filtration is a process that eliminates solid sediments and moisture in olive oil to maintain its shelf life during storage. The influence of filtration on the oil characteristics is linked to many parameters such as chemical and sensory traits, cultivars and filtration systems. After assessing the literature on filtration research, we observed that there are contrasting findings and it is complicated to answer the question of whether to filter or not. An analysis of the influence of different filtration technologies used in extra-virgin olive oil production on the phenolic compounds, volatile fractions, antioxidant activity and sensory characteristics is given in this review. The information compiled could help olive oil producers to enhance extra-virgin olive oil quality and maintain it during storage.

Assessment of extra virgin olive oil quality by miniaturized near infrared instruments in a rapid and non-destructive procedure

Food fraud in olive oil is a major concern for consumers and authorities due to the health risks and economic impacts. Common frauds include blending with other cheaper non-olive oils, or misleading labelling. The main issue is that legislation and methods presently used in routine laboratories are not always up to date with current fraudulent practices, making detection difficult, so new analytical methods development is required.This study focuses on developing an affordable and non-destructive analysis method based on NIR spectroscopy and chemometrics for EVOO quality assessment, specifically by monitoring 7 parameters of interest in EVOO measured by official methods and used to develop calibrations through NIR data. For this, two NIR low-cost portable instruments were employed, studied in-depth and compared with a NIR benchtop instrument. Calibration results enabled detection of atypical olive oils and excellent accuracy, especially for palmitic and oleic acid predictions, demonstrating the potential of the instruments.

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.

Olive Oil Quality of Cultivars Cultivated in Super-High-Density Orchard under Cold Weather Conditions

In this work, the quality parameters of the oils of seven different varieties of olives (Olea europaea cvs, “Arbequina”, “Arbosana”, “Cobrançosa”, “Cornicabra”, “Koroneiki”, “Cacereña”, and “Chiquitita”) grown in hedgerow under cold conditions during three consecutive seasons were analyzed in order to evaluate their adaptation to this growing system. For this purpose, virgin olive oils (VOOs) were extracted, and, in addition to evaluating the indices of hydrolytic, oxidative, and sensory deterioration of the oils, their content in photosynthetic pigments and their composition in fatty acids and phenolic compounds were determined. The correlation between oxidative stability and the parameters evaluated has been studied, with the highest correlation coefficients found for the ratio MUFA/PUFA (0.871) and the content of secoiridoid phenolic compounds (0.816). Furthermore, principal component analysis was performed with the phenolic composition data from each season, which demonstrated the major influence of genetic factors in the phenolic composition of VOO. None of the VOOs presented hydrolytic, oxidative, or sensory deterioration, so all of them remained in the “extra” category. However, it should be noted that the mean ultraviolet absorbance values were significantly higher in “Cornicabra” and significantly lower in “Cacereña” oils. In spite of this, the oxidative stability was significantly higher in “Cornicabra” oils (125 h), which also had the highest mean phenolic content (1035 mg kg−1 oil), while the lowest phenolic content values were found in “Arbequina” and “Chiquitita” (58 and 52 h, respectively).

EXTRA VIRGIN OLIVE OIL QUALITY INVESTIGATION OF DIFFERENT BRANDS ACQUIRED IN COMMERCE FROM RIO DE JANEIRO CITY, BRAZIL

Olive oil is obtained by physical means without the usage of solvents. Different than edible vegetable oils, it can be consumed in the virgin form, also being an oil of a better nutritional quality and stability, since it is mainly composed by monounsaturated fatty acids (oleic acid) as well as many antioxidant compounds. Having its greatest value in raw state, the extra virgin olive oil is the one with best quality in organoleptic aspect. As a result, this kind of oil is the one that shows biggest interest to the population and has the highest commercial value, therefore being more susceptible to adulterations. This paper aims to assess the chemical characteristics which define its classification, chemical quality and possible presence of adulterations in different brands commercialized in Brazil, applying methods described in accordance with identity and quality standards, in conformity with current legislation. This paper consists in bromatological analyzes of quality research related to classification, oxidative state, and adulteration, applying analyzes of acidity, peroxide and iodine. According to the results obtained related to classification and oxidative state, all samples were found within limits of tolerance prescribed by all legislations. Regarding adulterations, based on the iodine analyzes, two samples showed higher values determined by legislations and one showed lower value. Values higher than those determined by legislations may show mixtures with lower quality vegetable oils, and lower values may indicate mixture with fats that are rich in saturated fatty acids or a correlation with its oxidative state. Seeing that it is a kind of food that has become a major interest for investigation due to its nutritional benefits, particularly in the prevention of cardiovascular diseases, besides assuring safety to the consumer, this research shows the importance of physicochemical analyzes in the quality of extra virgin olive oils found in the market.

Potential Use of Olive Mill Wastewater Spreading in Olive Orchards for Improving Soil Fertility and Olive Oil Quality Under Semi-Arid Environment

ABSTRACT In Tunisia, olive growing and olive oil production represent a key element of the agricultural and economic sectors. Furthermore, olive producing areas are mostly located in semi-arid and arid regions with low water availability. On the other hand, olive oil industry generates high liquid effluent volumes (olive mill wastewater (OMW)) that represent a major environmental concern, and therefore must be appropriately managed. Accordingly, spreading OMW on agricultural lands in water scare areas may help to sustain dry lands productivity. In this study, we investigated the long-term effects of OMW spreading to an olive orchard in a semi-arid region. Physicochemical and biological properties of soil as well as olive oil quality were monitored. OMW was applied, after the end of the olive milling season, at annual dose of 50 m3 ha−1 y−1 every 2 years. The findings revealed that the OMW application increased soil water content. Moreover, OMW positively affected soil fertility, and increased, soil organic matter and biological activity. The overall results of this study indicate that OMW spreading at doses of 50 m3 ha−1 y−1 in a semi-arid region improves soil physicochemical properties and does not have a negative impact on olive oil quality. Additionally, direct spreading of OMW, if applied every 2 years, could be a sustainable practice in olive orchards under semi-arid environments.

Evolution of the quality and sensory characteristics of extra virgin olive oil as affected by phenolic content during long‐time storage at room temperature

AbstractBackgroundExtra Virgin olive oils are directly obtained from olives and their quality is influenced by the oxidative process during storage as consequence the category may be penalized. Sensory attributes are crucial parameter of olive oils quality and classifications. This study evaluated the main sensorial and volatile profile of three olive oils with high medium and low content of initial total phenolic compounds (from ‘Koroneiki’ Blend of varieties and ‘Arbequina’ respectively) including quality parameters up to 15 months of storage.ResultsA significant increase of peroxide index value (around 50%) and reduction of phenolic compounds level (around 60%) were observed. The sensory attributes of sweet herbaceous almond and fruity notes decreased and the majority of volatile compounds found in all olive oils were (E)‐2‐hexenal (Z)‐3‐hexen‐1‐ol 1‐penten‐3‐one and hexanal even after 15 months. The reductions of different parameters are related to initial phenolic level and samples are classified as Virgin after seven (low phenolics) nine (medium phenolics) and 11 (high phenolics) months displaying defect of rancid in distinct intensities.ConclusionsThis investigation provided detailed about Brazilian olive oils useful in a global context moreover modifications of sensory and volatile compounds profile and its evolution according to the long‐time storage were established.

The effect of data fusion on improving the accuracy of olive oil quality measurement.

Olive oil is one of the healthiest and most nutritious edible oils, and it has a great potential to be adulterated. In this research, fraud samples of olive oil were detected with six different classification models by fusion of two methods of E-nose and ultrasound. The samples were prepared in six categories of adulteration. The E-nose system included eight various sensors. 2MHz probes were used in through transmission ultrasound system. Principal Component Analysis method was used to reduce features and six classification models were used for classification. Feature with the greatest influence in the classification was "percentage of ultrasonic amplitude loss." It was found that the ultrasound system's data had worked more effectively than the E-nose system. Results showed that the ANN method was recognized as the most effective classifier with the highest accuracy (95.51%). The accuracy of classification in all the classification models significantly increased with data fusion.

Influence of geographical locations on yield, oil productivity and fatty acid profiling in four olive cultivars

Olives and its oil are considered an imperative element of diet due to their excellent nutritional quality. Geographical factors (i.e., geology, slope, elevation and temperature) and genetic variability in different olive cultivars influence plant growth, yield, oil and profiling of fatty acids. The prime objective of this investigation was to demonstrate the prodigious consequences of high temperature on the growth, production, and fatty acid composition of four olive cultivars (Coratina, Frantoio, Ottobratica and Leccino) at three different geographical locations (BARI, IOF, HRS) with the range of 460-751 m altitude during the year 2017 and 2018. The study has been carried out to investigate different parameters such as climatic conditions (rainfall and temperature), phenological attribute and yield traits (fruit set, fruit weight, yield, and oil content), and oil quality and profiling of fatty acids (free fatty acid contents, peroxide, palmitic acid, palmitoleic acid, oleic acid, linoleic acid, and linolenic acid). The results indicated a positive correlation of yield with rainfall and negative with the temperature was observed among olive cultivars. The results showed higher rainfall (1189 mm) and temperature (37.51 °C) at location-1 and lower rainfall (525 mm) and temperature (36.05 °C) at location-3. Coratina and Frantoio depicted significantly higher fruit set and yield in warmer climatic regions (Location-1 and Location-2) while Leccino and Ottobratica showed better results in the cooler region. Higher oil content was found in Frantoio and Coratina at location-3 among other locations and other cultivars. Overall, the lowest free fatty acid value was exhibited in Coratina and the highest in Ottobratica at all locations in both seasons. The contents of peroxide were observed higher in Leccino and lower in Coratina at all locations. The results revealed less variation among fatty acid composition in cultivars and seasons, however, palmitic acid, palmitoleic acid and oleic acid contents were found higher at location-2, linoleic acid at location-3, and linolenic acid at location-2 in all four olive cultivars. Custer analysis revealed two main groups and group-I contained two subgroups (A and B) while group-II contained three subgroups (C, D and E). In principal component analysis (PCA), PC1 axis had Leccino-L3, Leccino-L1, Frantoio-L1, Ottobratica-L1, Coratina-L1, and Leccino-L3 and explained 91.99% of the total variation. Therefore, geographic location influence growth, yield and olive oil quality attributes. Keywords: Climatic conditions; Acid value; High temperature; Free fatty acids;· Oleic acid;· Olive cultivars; Pothwar-Pakistan

Endogenous n-Alkanes in Vegetable Oils: Validation of a Rapid Offline SPE-GC-FID Method, Comparison with Online LC-GC-FID and Potential for Olive Oil Quality Control.

The potential of endogenous n-alkane profiling for the assessment of extra virgin olive oils (EVOO) adulteration (blends with cheaper vegetable oils) has been studied by relatively few authors. Analytical methods used for this purpose often involve tedious and solvent-intensive sample preparation prior to analytical determination, making them unattractive. A rapid and solvent-sparing offline solid phase extraction (SPE) gas chromatography (GC) flame ionization detection (FID) method for the determination of endogenous n-alkanes in vegetable oils was, therefore, optimized and validated. The optimized method demonstrated good performance characteristics in terms of linearity (R2 > 0.999), recovery (on average 94%), and repeatability (residual standard deviation, RSD < 11.9%). The results were comparable to those obtained with online high-performance liquid chromatography (HPLC)-GC- FID ( RSD < 5.1%). As an example of an application to prove the potentiality of endogenous n-alkanes in revealing frauds, the data set obtained from 16 EVOO, 9 avocado oils (AVO), and 13 sunflower oils (SFO), purchased from the market, was subjected to statistical analysis and principal component analysis. Two powerful indices, namely (n-C29 + n-C31)/(n-C25 + n-C26) and n-C29/n-C25, were found to reveal the addition of 2% SFO in EVOO and 5% AVO in EVOO, respectively. Further studies are needed to confirm the validity of these promising indices.

Application of a Cold-Pressing Treatment to Improve Virgin Olive Oil Production and the Antioxidant Phenolic Profile of Its by-Products.

The olive oil sector is continuously evolving in order to improve the quality of olive oil and its by-products. In fact, the trend is to use increasingly greener olives to improve quality by decreasing the extraction yield, thus obtaining a higher content of antioxidant phenolics. The application of a cold-pressing system to the olive before the extraction of oil was tested with three varieties: picual at three different stages of maturity and arbequina and hojiblanca at early stages of maturity. The Abencor system was used for the extraction of virgin olive oil and its by-products. For the quantification of phenols and total sugars for all phases, organic solvent extractions and colorimetric measurements and high-performance liquid chromatography (HPLC) with a UV detector were used. The results show that the new treatment significantly improved the amount of oil extracted by between 1 and 2% and even increased its concentration of total phenols by up to 33%. Regarding the by-products, the concentrations of the main phenols, such as hydroxytyrosol, increased by almost 50%, as did the glycoside. The treatment also facilitated the separation of phases in by-products and improved the phenolic profile, although not in terms of total phenols, but individual phenols with higher antioxidant activity were obtained.

Whole genome scanning of a Mediterranean basin hotspot collection provide new insights into olive tree biodiversity and biology.

Olive tree (Olea europaea L. subsp. europaea var. europaea) is one of the most important species of the Mediterranean region and one of the most ancient species domesticated. Τhe availability of whole genome assemblies and annotations of olive tree cultivars and oleasters have contributed to a better understanding of genetic and genomic differences between olive tree cultivars. However, compared to other plant species there is still a lack of genomic resources with olive tree populations that span across the entire Mediterranean region. This study has developed the most complete genomic variation map and comprehensive catalogue/resource of molecular variation to date for 89 olive tree genotypes originating from the entire Mediterranean basin, revealing the genetic diversity of this commercially significant crop tree and explaining the divergence/similarity among different variants. Additionally, the monumental ancient tree "Throuba Naxos" was studied to characterize the potential origin or routes of olive tree domestication. Several candidate genes, known to be associated with key agronomic traits, including olive oil quality and fruit yield, were uncovered by selective sweep scan to be under selection pressure on all olive tree chromosomes. To exploit further the genomic and phenotypic resources obtained from the current work, Genome Wide Association Analyses were performed for twenty-three morphological and two agronomic traits. Significant associations were detected for eight traits that provide valuable candidates for fruit tree breeding and for deeper understanding of the olive tree biology.

Miniature spectrometer data analytics for food fraud

Machine learning has been extensively used for analyzing spectral data in food quality management. However, collecting high-quality spectral data from miniature spectrometers outside the laboratory is challenging due to various factors such as distortions, noise, high dimensionality, and collinearity. This paper presents an in-depth analysis of food datasets collected from miniature spectrometers to evaluate the data quality and characteristics, by focusing on a case study of olive oil quality check, where various machine learning models were applied to differentiate pure and adulterated olive oil. Furthermore, the impact of pre-processing techniques on data distortions was studied. It presents a comprehensive pipeline, including data pre-processing, dimension reduction, classification, and regression analysis, and deploys different algorithms for comparative classification and regression analysis. The model performances were assessed using 2 separate methods: tenfold cross-validation on an entire dataset with 10% random testing, and an entire test set collected in different environments (multi-session validation). The first validation approach reached classification rates of up to 96.73%, while the second achieved 83.32%. These results demonstrate that cost-effective miniature spectrometers augmented with a suitable machine learning pipeline could execute classification tasks on par with non-portable and more expensive spectrometers. Furthermore, the study highlights the requirement of specialized algorithms to handle different ambient conditions affecting data acquisition and to eliminate performance gaps, making miniature spectrometers suitable for in situ scenarios. This work extends previous research to enable consumers becoming the first line in the defense against food fraud.

Effect of pedoclimatic variables on analytical and organoleptic characteristics in olive fruit and virgin olive oil

Due to the expansion of olive oil cultivation around the world and the increasing effects of climate change, Olea europaea (L:) cultivation must deal with ever higher temperatures and drought conditions, with productivity and virgin olive oil (VOO) quality issues. At the same time the demand for premium quality products with high nutraceutical value, chemical and organoleptic characteristics related to specific areas of cultivation is steadily rising. Within this framework a deep knowledge of the olive variety with regards to environment interaction is necessary to achieve VOO production and qualitative standards required by the market. Rainfed adult olives (cv Bosana) cultivated in five typical areas of north and central Sardinia (Italy) were the subject of a three-year study, with the aim to investigate the influence of pedoclimatic variability on olive and olive oil characteristics. Physical and chemical attributes of fruits (morphometric features, firmness, pH, titratable acidity, sugar content, moisture, and oil yield) and VOO (fatty acid and sensory profile) were analysed at harvest and related to monthly weather data (precipitation, maximum, average, and minimum temperatures) of the whole fruit development period and soil composition. Monthly maximum temperatures were the most relevant variables. However, the role of each meteorologic variable was specific per olive and olive oil parameters and their relevance varied according to the period of the season. An emblematic example is that the maximum temperatures during summer months reduced oil yield and improved oleic acid concentration, but during the following months, the same variable exerted an opposite effect. This suggests the presence of a maximum temperature threshold in the olive fruits, for lipogenesis processes. Meteoclimatic conditions during maturation were the principal element responsible for VOO sensory profile: high precipitation and low thermal amplitude promoted an attribute’s intensities.

Quality of Olive Oil Obtained by Regulated Deficit Irrigation

Olive oil is one of the basic products in the Mediterranean diet, and, due to its nutritional value, it is becoming more and more widespread in the world. Even though it has traditionally been a rainfed crop, farmers are currently transforming their plantations into super-high-density orchards to increase production. However, the increasingly acute drought in Mediterranean countries forces the establishment of water control mechanisms that allow restriction the contribution of water without undermining the properties of the products obtained. Under this concept, hydroSOS crops and products arose. This study aims to analyze the influence of the application of deficit irrigation on the olive oil obtained from the Arbequina and Arbosana varieties. The sensory parameters descriptive profile and consumers satisfaction degree were measured using trained and consumers’ panels, and the chemical parameters peroxide index, fatty acids, and volatile profile were analyzed using the methods from the International Olive Oil Council and gas chromatography. The experimental results showed that applying this type of irrigation leads to an oil that is more valued by consumers, with a higher concentration of aromatic compounds related with a greener aroma (hexanol, trans-2-hexen-1-ol, hexanal), a higher content of polyunsaturated fatty acids, and greater antioxidant capacity. Deficit irrigation strategies led to environmentally friendly olive oil with high acceptance by Spanish consumers.

Effect of Various Agro-Climatic Conditions on the Quality and Quantity of Olive Oil

Effect of Various Agro-Climatic Conditions on the Quality and Quantity of Olive Oil

Effect of enzymatic and talc treatment on olive oil extraction process at the industrial scale

Technological coadjuvants were applied at the beginning of the malaxation phase of the olive oil mechanical extraction process at the industrial scale. An enzymatic formulation consisting of 35% pectinase, 28% pectinmethylesterase and 7% polygalacturonase % (v/v/v) and talc was added during the kneading of olive paste to evaluate its impact on oil extractability and on olive oil quality characteristics. Quantitative and qualitative evaluation of hydrophilic phenols and volatile compounds involved in the main health and sensory properties of high-quality olive oil was carried out. The addition of a combination of enzymatic complex and talc, for the first time at industrial scale, increased the oil extractability by 5.6% (absolute value), improving the degradation of the cell wall structure of olive paste and breaking down the oil-in-water emulsions with a more efficient separation of the oil during the extraction process. The use of the enzymatic complex and talc leads to a percentage increase in the phenolic content in the range of 12%–16% without altering the legal quality parameters and volatile profile of the final product.