Olive Oil Quality Research Articles

The Influence of Standard and Freeze-Dried Tofu on the Phenols and Quality of Virgin Olive Oil Used as an Immersion Medium

Various protein-rich foods are traditionally immersed in virgin olive oil (VOO), a medium rich in phenols, which are health-promoting and sensorially important compounds. Immersing tofu in VOO may modify the sensory properties and nutritional value of both due to the oil’s hydrophilic phenol interactions with proteins and water. In this study, cubes of fresh tofu (T) (70% water) and freeze-dried tofu (FD-T) (5% water) were immersed in VOO for 7 days of cold storage. The changes in the phenolic compound content and standard quality parameters of the oil were noted after 1, 3, 5, and 7 days of contact with the tofu. The total phenols in the oil were determined using the Fast Blue BB assay, while single phenols were analyzed by HPLC-UV/VIS. During the 7 days, the total phenols in the oil decreased by up to 56% and 26% under the influence of fresh and freeze-dried tofu, respectively, including a significant decrease in hydroxytyrosol, oleacein, tyrosol, and oleocanthal. The water content and its release from fresh tofu significantly contributed to this decline. The degradation of the quality of the oil in contact with the fresh tofu was observed only in its sensory properties, with a marked reduction in the intensity of its fruitiness, bitterness and pungency.

Olive Oil Quality Produced Under Conventional and Organic Farming Systems in a Multisite Two-Year Evaluation in Greece

Six olive groves (three conventional and three organic) of “Koroneiki” olive cultivar were selected in two different provinces in southern Greece during a two-year trial (one province per year). At harvest, the oil was extracted from olive fruits using an Abenchor-type olive mill. Olive oil quality characteristics, including free acidity, ultraviolet absorbance indexes, peroxide value, free fatty acids, total and individual phenolic compounds, antioxidant capacity, and α-tocopherol content, were assessed. During the second year, olive oil samples were stored for 12 months, and their quality was re-evaluated. Few significant differences were observed between organically and conventionally produced olive oils, while the quality of both deteriorated significantly after storage (decrease in antioxidant capacity and major phenolic compounds, except for hydroxytyrosol and tyrosol, and increase in peroxide index value). Principal component analysis revealed that, during the first year, oils produced following organic and conventional practices could be distinguished; however, this distinction was not evident during the second year. Nevertheless, significant differentiation was found between oils produced under the same cultivation practice. In conclusion, the discrepancies found in the literature regarding organic versus conventional olive oil properties probably originate from the differences detected even among similar products (organic or conventional), including high-standard deviations.

Utilizing Olive Fly Ecology Towards Sustainable Pest Management

The olive fly (Bactrocera oleae, OLF) is a major pest of global significance that occurs in places where olive cultivation thrives. This paper highlights the economic and environmental damage caused by OLF infestations, including reduced olive oil yield and quality, disrupted supply chains, and ecosystem imbalances due to heavy insecticide use. Understanding olive fly ecology is crucial for developing effective control strategies. The review explores the fly’s life cycle, its relationship with olive trees, and how environmental factors like temperature and humidity influence population dynamics. Additionally, studying the role of natural enemies and agricultural practices can pave the way for sustainable control methods that minimize environmental harm. Climate change, intensive cultivation, and the development of resistance to insecticides necessitate a shift towards sustainable practices. This includes exploring alternative control methods like biological control with natural enemies and attract-and-kill strategies. Furthermore, a deeper understanding of OLF ecology, including its response to temperature and its ability to find refuge in diverse landscapes, is critical for predicting outbreaks and implementing effective protection strategies. By employing a holistic approach that integrates ecological knowledge with sustainable control methods, we can ensure the continued viability of olive cultivation, protect the environment, and produce high-quality olive oil.

Signal Preprocessing in Instrument-Based Electronic Noses Leads to Parsimonious Predictive Models: Application to Olive Oil Quality Control

Gas sensor-based electronic noses (e-noses) have gained considerable attention over the past thirty years, leading to the publication of numerous research studies focused on both the development of these instruments and their various applications. Nonetheless, the limited specificity of gas sensors, along with the common requirement for chemical identification, has led to the adaptation and incorporation of analytical chemistry instruments into the e-nose framework. Although instrument-based e-noses exhibit greater specificity to gasses than traditional ones, they still produce data that require correction in order to build reliable predictive models. In this work, we introduce the use of a multivariate signal processing workflow for datasets from a multi-capillary column ion mobility spectrometer-based e-nose. Adhering to the electronic nose philosophy, these workflows prioritized untargeted approaches, avoiding dependence on traditional peak integration techniques. A comprehensive validation process demonstrates that the application of this preprocessing strategy not only mitigates overfitting but also produces parsimonious models, where classification accuracy is maintained with simpler, more interpretable structures. This reduction in model complexity offers significant advantages, providing more efficient and robust models without compromising predictive performance. This strategy was successfully tested on an olive oil dataset, showcasing its capability to improve model parsimony and generalization performance.

The Effects of Storage and Maturity Index on the Quality of Virgin Olive Oil from “Pendolino” Cultivar Produced in Nowshera, Pakistan

The Effects of Storage and Maturity Index on the Quality of Virgin Olive Oil from “Pendolino” Cultivar Produced in Nowshera, Pakistan

The level of Farmers’ Knowledge and Implementation of Olive Oil Quality Improvement for Marketing Practices in the Village of Imatin, Qalqilya Governorate, Palestine

The level of Farmers’ Knowledge and Implementation of Olive Oil Quality Improvement for Marketing Practices in the Village of Imatin, Qalqilya Governorate, Palestine

Insecticidal Action of Local Isolates of Entomopathogenic Fungi Against Bactrocera oleae Pupae.

In this work, the ability of certain entomopathogenic fungi to control the olive fruit fly Bactrocera oleae (Diptera: Tephritidae), which significantly affects olive cultivation, was assessed. First, entomopathogenic fungi that often contribute to reducing pests, as well as B. oleae, were sought out. Puparia of B. oleae were collected from oil mills, and soil samples were collected from various olive grove regions of Greece. These soils were used as the substrate in which the effect of the entomopathogenic fungi on the B. oleae pupae was studied. In addition, the same treatments were studied in non-soil conditions. The results show that certain known entomopathogenic fungi are able, in their natural environment, to kill B. oleae pupae to a significant extent. The survival time for adults (days) was lower in the presence of Beauveria bassiana (Hypocreales: Cordycipitaceae), at 13.20 in the soil (5.56 ± 0.42) and non-soil (6.76 ± 0.46) conditions, compared to that of the control in soil (9.83 ± 083) and non-soil (9.90 ± 0.72) conditions. This is encouraging for Mediterranean regions where the presence of B. oleae significantly affects olive cultivation, while quality olive oil is in high demand.

Effects of Summer Water Deficit Stress on Olive Fruits and Oil Quality

The Mediterranean basin is the leading worldwide region for olive production. Extreme weather is increasingly frequent in this region, and how these climate extremes will affect olive products and quality remains unknown. We aim to study the effects of the water deficit stress, which occurred in the summer of 2017, on olive fruit and oil quality from a 30-year-old orchard. Fruits from olive trees standing on (i) one hydrated and (ii) one dry area of an orchard at the north of Portugal were harvested. Fruits’ water content, oil yield and quality, fruit carbohydrates, and fruit and oil phenolic metabolite profiles were analyzed. Fruits from the dry area presented low water availability and increased carbohydrates, oleuropein, oleoside, and elenolic acid glucoside abundance. Oil yield was lower in the dry area, but the abundance of oleacein increased, together with traits of some sensory sensations. Climate stress events can reduce oil yield but stimulate the accumulation of bioactive compounds that improve oil quality and nutritional value.

Cultivar-Dependent Effect of Silicon Foliar Application on Olive Fruit Yield, Morphology, and Olive Oil Quality Parameters

Silicon is one of the most abundant elements in the Earth’s crust and, although it is not an essential element for plant growth, it is considered beneficial as it can help in defense against biotic and abiotic stresses. Research on the effects of foliar sprays containing silicon has been well documented for different plants. However, in olive plants there is considerably less research focused on silicon soluble foliar formulations, which differs from the application of inert materials, like kaolin. The purpose of this study was to evaluate the effects of three increasing levels of foliar-applied soluble silicon on the characteristics of olive fruit and olive oil parameters. Fruit morphology, contents of multiple polyphenols, fatty acid profiles and mineral content in olive oil, olive oil quality parameters, fruit yield, and olive oil production parameters were assessed. Results show significant effects of silicon treatments on palmitic, palmitoleic, and linoleic acids and on the content of mono- and polyunsaturated fatty acids. Polyphenols were generally more influenced by the cultivar rather than by silicon. Apigenin, phenolic acids, and flavonoids were impacted by silicon treatments. Fruit morphology was affected by silicon treatment and, generally, parameters (fruit and seed length, width, and mass) increased at higher silicon application. This was concomitantly seen in both fruit and extra virgin olive oil (EVOO) yield increase, but only for the Leccino cultivar, suggesting specific cultivar x treatment interplay for those traits. Increases in mineral contents in olive oil due to Si treatments were not found, except for silicon, where Si2 and Si3 treatments yielded higher silicon content in olive oil compared to control. Results of this study indicate that Silicon Foliar Application could be used to enhance olive yield and only slightly modifies the fatty acid composition of olive oil and the content of some of the phenols. Although silicon application did affect several parameters, the effect of cultivar was more pronounced in affecting most of the parameters. Further research could be driven towards the effect of foliar silicon on these parameters under environmental stress factors.

Relationships Between Chemical Compounds and Sensory Properties of Virgin Olive Oil in the US and Israel: Development of a Prediction Model for Defects.

Virgin olive oil (VOO) quality is defined by both chemical and sensory parameters. While the chemical parameters are objective and measured using instrument-based methods, sensory quality evaluation is based upon human panels, which can be subjective, have less repeatability, suffer from fatigue, and require long and costly training. Tasting biases could be minimized by a trained panel, but using humans as a testing instrument is inevitably prone to various psychological biases, stimulus-related factors, and carry-over effects. The objectives of this study were to evaluate instrumental methodologies that will assist the existing human panel in assessing the sensory characteristics of VOO and to develop chemistry-based predicting models for sensory properties in the oil using VOO samples originating from the US and Israel. Our results indicated that oil rancidity highly correlated with the contents of chemical components contents; 1-penten-3-one, 3-hexen-1-ol, (E)-2-pentanal, and 1-octen-3-ol are the major volatiles associated with rancidity defects (low concentrations of these compounds). Positive sensory attributes, such as fruitiness, correlated with 1- acetoxypinoresinol and hexanal, while bitterness correlated with pinoresinol, the aldehydic form of oleuropein aglycones, and the dialdehydic form of oleuropein aglycone. The random forest model suggested that luteolin, (E)-2-hexenal, 1-penten-3-one, and C18:0 are the most useful measurements in predicting the occurrence of sensory defects in the olive oil samples included. In other words, when these compounds are below or above a certain threshold, a defect, such as rancidity, is more likely to be found by the sensory panel.

Bactrocera oleae Control and Smart Farming Technologies for Olive Orchards in the Context of Optimal Olive Oil Quality: A Review

Bactrocera oleae Control and Smart Farming Technologies for Olive Orchards in the Context of Optimal Olive Oil Quality: A Review

Assessing statistical neural networks potentiality to distinguish PDO Kalamata and Molaoi olive oil varieties

Several regional areas in Greece produce high quality olive oil by cultivating certain varieties. Olive oil varieties of Kalamata and Molaoi are of special interest, since they produce extra virgin olive oil. Concretely, Kalamata is a city located in southwestern Greece. Intuitively, Molaoi is a town located in southeastern Greece. Subsequently, both geographic locations are known for their famous olive oil quality. Continually, Protected Designation of Origin (PDO) Kalamata olive oil, established by Council regulation (EC) No 510/2006, is considered an exceptional extra virgin olive oil variety. Specifically, there is a need to distinguish PDO Kalamata olive oil from other olive oil varieties is Greece such as the Molaoi olive oil, since PDO Kalamata olive oil is the main variety exported in the global olive oil market. Distinguishing PDO Kalamata from Molaoi olive oil is possible by incorporating statistical neural networks. Concretely, applying neural network experimentation enables differentiation between variations of certain chemical characteristics observed in certain geographic locations of Greece. In this paper, we use statistical neural networks to distinguish the geographical origin of PDO Kalamata olive oil compared with Molaoi olive oil based on synchronous excitation−emission fluorescence spectroscopy of provided olive oils samples evaluated in the chemical laboratory. Evaluation based on certain experimentation phase and subsequent data visualization of the adopted statistical neural networks are promising for distinguishing the samples of PDO Kalamata olive oil with high values of prediction accuracy. Such ability enables olive oil industry to assess extra virgin olive oil profitable potentiality in global market.

Machine learning-aided microRNA discovery for olive oil quality.

MicroRNAs (miRNAs) are key regulators of gene expression in plants, influencing various biological processes such as oil quality and seed development. Although, our knowledge about miRNAs in olive (Olea europaea L.) is progressing, with several miRNAs being identified in previous studies, but most of these reported miRNAs have been predicted without the aid of a reference genome, primarily due to limited genome accessibility at the time. However, significant knowledge gaps still need to be improved in this area. This study addresses the complexities of miRNA detection in olive, using a high quality reference genome and a combination of genomics and machine learning-based methods. By leveraging random forest and support vector machine algorithms, we successfully identified 56 novel miRNAs in olive, surpassing the limitations of conventional homology-based methods. Our subsequent analysis revealed that some of these miRNAs are implicated in the regulation of key genes involved in oil quality. Within the context of oil biosynthesis pathways, the novel miRNA Oeu124369 regulates fatty acid biosynthesis by targeting acetyl-CoA acyltransferase 1 and palmitoyl-protein thioesterase, thereby influencing the production of acetyl-CoA and palmitic acid, respectively. These findings underscore the power of machine learning in unraveling the complex miRNA regulatory network in olive and provide a high quality miRNA resource for future research aimed at improving olive oil production by exploring the target genes of the identified miRNAs to understand their role and their biological processes.

Evaluation of phenolics in the analysis of virgin olive oil using near infrared spectroscopy

Olive oil is an indispensable part of the diet in Mediterranean regions, and is appreciated worldwide for its sensory characteristics, combining a fine aroma and pleasant flavor with the high nutritional value of specific chemical compounds. However, making rapid measurements of phenolic compounds is a major challenge for the olive oil sector. The development of a new method based on near infrared (NIR) spectroscopy may be considered an important advance for the sector, as it is rapid, low-cost, non-contaminant and non-destructive. In this study, three different NIR instruments – one FT-NIR benchtop instrument (671.82–2702.70 nm) and two low-cost portable devices (900–1700 nm and 1350–2150 nm) – were used to analyze a collection of virgin olive oil samples from various Mediterranean regions. To predict both the individual and total concentration of phenols in the olive oil, four signal pretreatment methods and modified partial least squares regression analyses were employed to develop the predictive models. The results showed that the benchtop FT-NIR instrument performed better than the other portable instruments when measuring the phenolic compounds in virgin olive oil. The best models of hydroxytyrosol derivatives, tyrosol derivatives, total phenols and “EFSA phenols” showed R2cv values of 0.84, 0.85, 0.88 and 0.89, while the RPDcv values were 2.51, 2.61, 2.93 and 2.95, respectively. Meanwhile, for the portable NIR instruments, the prediction models for hydroxytyrosol derivatives, total phenols and “EFSA phenols” (the sum of the hydroxityrosol and tyrosol derivatives) showed R2cv values ranging between 0.75 and 0.81 and an RPDcv between 2 and 2.5. These results indicate the great potential of NIR, both with benchtop and portable devices, to detect phenolic compounds in virgin olive oil, which can guarantee the quality of virgin olive oil and thus aid progress in the olive oil industry. Moreover, this is the first published work to determine phenolic compounds in virgin olive oil using portable NIR instruments.

Future aridity and drought risk for traditional and super-intensive olive orchards in Portugal

Portugal, a leading olive oil producer, boasts six Protected Denomination of Origin (PDO) regions, with distinct olive orchard (OR) densities (traditional rainfed to super-intensive irrigated). This study aimed to assess future drought and aridity conditions and the impacts on ORs located in the PDOs. Therefore, drought and aridity indicators were considered for the historical (ERA5: 1981–2000) and future periods (2041–2060; 2081–2100), and anthropogenic forcing scenarios (RCP4.5 and RCP8.5), using a 7-member ensemble of global climate models. From Spearman’s correlation analysis, Annual Mean Aridity (AIA) was selected as the most representative indicator of the climate conditions, to which the ORs were exposed. Readily Available Soil Water (RAW; mm) was considered to represent the available soil water reservoir for olive trees. Moreover, the Olive Drought and Aridity Risk Index (ODAR) was developed to determine each OR's future risks. This index considered that the AIA and RAW were weighted by OR density fractions. In the future, southern Portugal will be more arid (0.69) than northern and central (0.60). ORs soil shows lower RAW in southern PDOs (< 60 mm) than in central and northern regions (> 90 mm). These results suggest that the south of ORs will be more exposed to water stress than the northern regions. According to ODAR, the ORs exposed to low and high risk will be mainly located in the central parts of the PDOs. In northern ORs, moderate to high risk will predominate. In the south, however, the risk will be very high, which means that the olive tree growth, fruit development, and olive oil quality could be negatively affected. Implementation of tailored adaptation measures will be required to improve the climate resiliency of the sector.

Densimetric sorting of olives to control olive oil quality

AbstractExtra virgin is the most valuable commercial category among olive oils, and its quality is influenced by various factors, among which the olive fruit plays a fundamental role. The olives that enter the mill exhibit significant variability in physical and chemical characteristics, potentially impacting the quality of the extracted oil. Therefore, selecting the olives in post‐harvest could be a crucial step, especially for differentiating the final product and producing high‐quality oil. This work aimed to conduct post‐harvest densimetric sorting of the olives. For this purpose, a saline solution was used with different concentrations of salt over the 3 days of harvesting, which made it possible to divide the initial olive batch into two sub‐batches with different densities. The respective oil was extracted from each sub‐batch, called low‐ and high‐density oils, respectively, and then appropriate physical–chemical analyses were performed to characterize both the olives and the oils. Although both oils were classified as extra virgin, significant differences were observed, with higher concentrations of phenolic and volatile compounds associated with positive sensory attributes in the low‐density oils. Densimetric sorting of olives could represent a novel approach in the field of extra virgin olive oil production, enabling potential differentiation of the final product.Practical Applications: The results obtained in the study could be applied at an industrial level to classify olives in the post‐harvest phase. This could allow to produce extra virgin olive oils (EVOOs) with different chemical and sensory characteristics, particularly in terms of volatile and phenolic compounds. This would make it possible to diversify the production of EVOO, satisfy the diverse needs of consumers, allow producers to be more competitive in the market, and, in general, improve the overall quality of the final product.

Interplay of phenolic compounds and gene expression in phenylpropanoid and flavonoid pathways during olive (Olea europaea L.) ripening of ‘Leccino’ cultivar

This study presents a detailed analysis and interplay of the phenolics, relative gene expression and quality parameters during ripening of ‘Leccino’ olive fruit pulp and skin at seven maturity indexes, in the phenylpropanoid and flavonoid pathways. Tissue-specific gene expression analysis revealed statistically higher expression levels for eight genes in the skin. The only exception was anthocyanidin synthase (ANS), which expression level was statistically higher in the pulp. Our results confirm that the important role in olives of the anthocyanin composition have flavonoid 3′-hydroxylase (F3′H) and flavonoid-3′,5′-hydroxylase (F3′5′H) in both tissues. The phenolic content was mostly statistically higher in the skin than in the pulp and generally increased in both tissues during ripening. A notable shift in phenolic compounds occurs between maturity index 3 and 4, when the skin of the fruit turns completely purple. Results from this study highlight the intricate dynamics of physiological processes and biochemical mechanisms in the phenylpropanoid and flavonoid pathways in olive fruit. The findings also underscore the relationship between phenolic content, relative gene expression, and quality parameters, particularly in relation to color development during ripening in different olive fruit tissues. Our conclusions can be used by growers to improve the quality of fruit and consequently the quality of olive oil or other final products.

Physicochemical Characteristics and Antioxidant Activity of Some Algerian Extra Virgin Olive Oils (Olea europaea L.)

Background:: The present work was conducted to investigate the quality and antioxidant properties of some Algerian extra virgin olive oils (EVOOs). Objective:: In this paper, the physicochemical characteristics and antioxidant properties of four EVOOs of monovarietal samples (Chemlal) from East Algeria were studied. Methods:: Physicochemical characteristics, which include free acidity, peroxide index, saponification index, specific extinction coefficients, water content, refractive index, relative density, and chemical composition, in addition to their antioxidant activity, were investigated based on DPPH free radical-scavenging activity (DPPH-SA). Results:: The results of physicochemical and quality parameters proved that all samples are EVOOs with highly nutritious and health benefits for the consumer, as per the recommendation of the International Olive Council (IOC). The results showed that the olive oils from the southern arid region of Algeria (Sahara), have a high antioxidant activity than the samples from the Northern regions. Conclusion:: These findings revealed a significant influence of geographic location on the chemical characteristics and antioxidant activities of olive oil from the same cultivar (Chemlal). These olive oils from the arid Saharan region may be used as a functional food with great antioxidant potential.

Study of the quality of olive oils imported to Russia

Study of the quality of olive oils imported to Russia

Long-term stability of extra virgin olive oil: effects of filtration and refrigeration storage on the Kolovi variety.

The composition of extra virgin olive oil (EVOO) defines its sensory, nutritional, and human health benefits, and distinguishes it as a key component of the Mediterranean diet. Nevertheless, EVOO constituents are susceptible to degradation during processing and storage, which reduces the olive oil's quality and limits its shelf life. The present study investigated the effect of molecular filtration before storage and the effect of cool storage at 4 °C on the stability of 'Kolovi' EVOO, a variety originating from the Greek island of Lesvos, over a 24 month period. Storing EVOO at 4 °C positively affected free acidity, peroxide value, K268, fruity qualities, and concentrations of hydroxytyrosol, tyrosol, ligstroside aglycone, lutein, and squalene, in comparison with the control sample stored at room temperature, particularly after 1 year. Molecular filtration significantly affected the ratio of unsaturated fatty acids to saturated fatty acids (UFAs/SFAs). Optimal preservation of parameters such as acidity value and lutein content was achieved by combining molecular filtration with refrigeration. The present study recommends storing EVOO in the refrigerator for up to 18 months. Based on the regulatory limits of the quality characteristics of acidity, peroxide value, K232 value and fruity sensory attributes, the shelf-life of the protected geographical indication (PGI) 'Kolovi' EVOO can reach 2 years under cool storage (4 °C) and with molecular filtration before storage. © 2024 The Author(s). Journal of the Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.