Hepatotoxicity assessment of innovative nutritional supplements based on olive-oil formulations enriched with natural antioxidants.

Introduction: This study focuses on the assessment of extra virgin olive-oil and olive fruit-based formulations enriched with natural antioxidants as potential nutritional supplements for alleviating symptoms and long-term consequences of illnesses whose molecular pathophysiology is affected by oxidative stress and inflammation, such as Alzheimer's disease (AD). Methods: Besides evaluating cell viability and proliferation capacity of human hepatocellular carcinoma HepG2 cells exposed to formulations in culture, hepatotoxicity was also considered as an additional safety measure using quantitative real-time PCR on RNA samples isolated from the cell cultures and applying approaches of targeted molecular analysis to uncover potential pathway effects through gene expression profiling. Furthermore, the formulations investigated in this work contrast the addition of natural extract with chemical forms and evaluate the antioxidant delivery mode on cell toxicity. Results: The results indicate minimal cellular toxicity and a significant beneficial impact on metabolic molecular pathways in HepG2 cell cultures, thus paving the way for innovative therapeutic strategies using olive-oil and antioxidants in dietary supplements to minimize the long-term effects of oxidative stress and inflammatory signals in individuals being suffered by disorders like AD. Discussion: Overall, the experimental design and the data obtained support the notion of applying innovative molecular methodologies and research techniques to evidently advance the delivery, as well as the scientific impact and validation of nutritional supplements and dietary products to improve public health and healthcare outcomes.

Measuring circular economy in olive oil mills: A review of circularity indicators and tools.

Circularity assessment and monitoring have become a core research topic in academic societies, as well as a basis for developing economic development measures. Despite the circular economy (CE) being a game-changer for the agro-food sector, little effort has been made to identify its level of circularity. In order to achieve the transition to a CE, stakeholders and industry professionals must be provided with appropriate indicators, tools and methods. Due to the complexity of CE measurement, it is necessary to devise indicators, methods and tools that are tailored to each industry. The objective of this review article is to identify the indicators and tools required for assessing the level of circularity in olive oil mills. This research collected data regarding available CE indicators at the company and product levels, as well as those applicable to the agro-food industry. As a result, a list of indicators appropriate to the needs of olive mills has been developed that could be used to measure the level of implementation of circular practices in this industry. The main conclusion reached is that once indicators are defined, they should be compared or combined with life cycle assessment methodologies to determine their applicability and effectiveness. There is no doubt that olive oil plays a significant economic, environmental and social role throughout the Mediterranean region. Hence, evaluating the CE is essential to demonstrate the effectiveness of current policies.

Monitoring of seven pesticide residues by LC-MS/MS in extra virgin olive oil samples and risk assessment for consumers.

Residue levels of seven pesticides were analyzed in thirty-five samples of Extra Virgin Olive Oil to assess the health risk of consuming Italian oils correlated with the presence of these pesticides. An in-house analytical procedure was developed and validated, consisting of a specific dispersive solid-phase extraction using the QuEChERS technique and a qualitative-quantitative analysis using liquid chromatography coupled with tandem mass spectrometry. Thirty-four percent of the samples were contaminated with pesticide residues; in the concentration range of 0.53-0.56 ng/mL for imazalil, 1.11-1.56 ng/mL for acetamiprid-N-desmethyl, 1.28-1.46 ng/mL for clothianidin, 0.94-1.49 ng/mL for thiacloprid, 1.08-4.64 ng/mL for dinotefuran, 0.42-1.47 ng/mL for thiamethoxam, 0.42-6.14 ng/mL for imidacloprid). Risk assessment was evaluated using the hazard quotient, hazard index, and Pesticide Residue Intake Model by EFSA. All hazard indices confirmed that the concentrations of pesticides detected in the oil samples did not represent a short or long-term risk for consumers' health.

Assessment of fruity aroma intensity in olive oils from different Spanish regions using a portable electronic nose.

BACKGROUND: The organoleptic profile of an olive oil is a fundamental quality parameter obtained by human sensory panels. In this work, a portable electronic nose was employed to predict the fruity aroma intensity of 199 olive oil samples from different Spanish regions and cultivar varieties ('Picual', 'Arbequina', and 'Cornicabra'), with special emphasis in testing the robustness of the predictions versus cultivar variety variability. The primary data given by the electronic nose were used to obtain two different feature vectors that were employed to fit ridge and lasso regressions models to two datasets: one consisting of all the samples and another just the cv. Picual samples. RESULTS: The results obtained showed mean average error (MAE) values below 0.88 in all cases, with an MAE of 0.67 for the 'Picual' model. These MAE values and the similarities in the model parameters fitted for the different data folds are in agreement with the results obtained in previous studies. CONCLUSION: The large number of samples analyzed and the results obtained show the robustness of the approach and the applicability of the methods. Also, the results suggest that better performance can be obtained when specific models are fitted for particular cultivars. Overall, the proposed methods are capable of providing useful information for a fast screening of the fruity aroma intensity of olive oils. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

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.

Potentiality Assessment of the Acetylcholinesterase-Inhibitory Activity of Olive Oil with an Additive Edible Insect Powder.

Edible insects (Alphitobius diaperinus Panzer, Gryllus campestris, Tenebrio molitor, Chorthippus biguttulus) are rich in nutrients that potentially inhibit acetylcholinesterase (AChE), but also improve cognition. The aim of this study was to evaluate four varied species of freeze-dried edible insects (purchased from a store); their nutrient composition, including fat, total phenolic compounds, vitamins, and antioxidant properties; and the potential inhibitory effect of AChE. An additional goal was to obtain olive oil with the addition of edible insects. Such oil was characterized by high oxidizing properties and showed high affinity to AChE. The results showed that mealworms and grasshoppers had the highest content of fats (PUFA/SFA) and phenolic compounds. These insects also showed a high content of vitamins, which correlated with the highest affinity for AChE. Therefore, they were added as a functional additive to olive oil. Olive oil with the addition of edible insects showed a higher affinity for AChE and enriched the olive oil with vitamin C and B vitamins.

Evaluation of Novel Rapid Analytical Methods to Categorize Extra Virgin Olive Oil Based on the Coulometrically Determined Antioxidant Capacity and on the Spectrophotometric Assessment of Phenolic Compounds.

The lack of a practical "fit for the purpose" analytical protocol is the main limitation that has hampered the exploitation of the EFSA analytical health claim on the extra virgin olive oil (EVOO) biophenols, more than ten years since its introduction. In this work, two analytical methods recently developed in our laboratories for categorizing EVOO have been evaluated on a set of 16 samples from Cilento (Campania Region, southern Italy) and compared to other commonly used quality indexes. The Coulometrically Determined Antioxidant Capacity (CDAC) is associated with the component responsible for the health-promoting properties and oxidative stability of EVOO. The Fast Blue BB (FBBB) assay consists of the spectrophotometric (420 nm) determination of biophenols-FBBB diazonium coupling products generated in unfractionated EVOO. The FBBB assay and HPLC-UV reference method provide values highly correlated to each other. Fourteen of sixteen EVOO samples with CDAC > 10 mmol kg-1 and FBBB absorbance > 0.5 had HPLC-determined biophenols > 250 mg kg-1, and therefore eligible for the EFSA health claim. Consistently, two EVOO samples with HPLC-determined biophenols < 250 mg kg-1 had CDAC values and FBBB absorbance below the respective thresholds. CDAC and FBBB assays are proposed individually or in combination as methods to categorize EVOO samples in alternative to HPLC-UV.

Chemical and sensory assessment of extra virgin olive oil blends with omega-3 polyunsaturated fatty acids from plant origin

Extra virgin olive oil (EVOO) is known for its health benefits, although it provides a minimum amount of n-3 polyunsaturated fatty acids (n-3 PUFA), which play an important role in the human organism. In this study, EVOO was blended with vegetable oils which are rich sources of n-3 PUFA alpha-linolenic acid (ALA) and/or stearidonic acid (SDA) (chia, walnut, linseed and viper's bugloss seed oils). Fatty acid profiles, induction time, and organoleptic characteristics of the resulting blends were assessed. The n-3 PUFA enrichment in the blends was proportional to the degree of blending. Sensory analysis carried out by a trained panel showed that it is possible to enrich EVOO with up to 20% chia, linseed and viper's bugloss seed oil without altering the original organoleptic characteristics of EVOO. However, the induction time of the blends was significantly reduced compared with EVOO even after adding n-3 PUFA in small proportions, meaning that shelf-life time of these blends is much lower than that of EVOO, which should be considered when preparing these products for commercial purposes.

El aceite de oliva extra virgen (AOEV) es ampliamente conocido por sus beneficios para la salud, aunque apenas aporta ácidos grasos poliinsaturados n-3 (AGPI n-3), los cuales juegan un papel importante en el organismo humano. En este estudio se elaboraron mezclas de AOEV con aceites vegetales ricos en ácido alfa-linolénico (ALA) y/o estearidónico (SDA) (chia, nuez, linaza y viborera). Se evaluaron los perfiles de ácidos grasos, tiempos de inducción y características organolépticas de las mezclas resultantes. El enriquecimiento en AGPI n-3 fue proporcional al grado de mezcla. El análisis sensorial llevado a cabo por un panel entrenado mostró que es posible enriquecer AOEV con hasta un 20% de aceite de chia, linaza o viborera sin alterar las características organolépticas originales del AOEV. Sin embargo, los tiempos de inducción de las mezclas fueron significativamente menores que el del AOEV, incluso tras añadir AGPI n-3 en pequeñas proporciones, lo que significa que el tiempo de vida media de las mezclas es mucho menor que el del AOEV. Este hecho debería tenerse en cuenta al preparar las mezclas con propósitos comerciales.

NMR-Based Metabolite Profiling and the Application of STOCSY toward the Quality and Authentication Assessment of European EVOOs.

Extra virgin olive oil (EVOO) possesses a high-value rank in the food industry, thus making it a common target for adulteration. Hence, several methods have been essentially made available over the years. However, the issue of authentication remains unresolved with national and food safety organizations globally struggling to regulate and control its market. Over the course of this study, the aim was to determine the origin of EVOOs suggesting a high-throughput, state-of-the-art method that could be easily adopted. A rapid, NMR-based untargeted metabolite profiling method was applied and complemented by multivariate analysis (MVA) and statistical total correlation spectroscopy (STOCSY). STOCSY is a valuable statistical tool contributing to the biomarker identification process and was employed for the first time in EVOO analysis. Market samples from three Mediterranean countries of Spain, Italy, and Greece, blended samples from these countries, as well as monocultivar samples from Greece were analyzed. The NMR spectra were collected, with the help of chemometrics acting as "fingerprints" leading to the discovery of certain chemical classes and single biomarkers that were related to the classification of the samples into groups based on their origin.

Concentration and probabilistic health risk assessment of benzo(a)pyrene in extra virgin olive oils supplied in Tehran, Iran.

One hundred and sixteen samples of extra virgin olive oils (VOOs) from markets of Tehran were analyzed by high-performance liquid chromatography (HPLC) to detect the amount of benzo (a)pyrene. The values of LOD and LOQ were calculated as 0.03 and 0.05 µg/kg, respectively. The concentration of benzo (a) pyrene was from 0.03 to 0.95 µg/kg. The results indicate that the levels of benzo (a) pyrene are lower than the limits approved. Target Hazard quotient (THQ) and Margin of Exposure (MOE) were estimated. The mean of THQ for adults and children was 0.0006 and 0.0028 and also mean of MOE for adults and children was 43,503 and 9438, respectively. The probabilistic health risk shows that THQ is less than 1 value; hence consumers are not at non-cancer risk. The mean of MOE value for adults was more than 10,000 but for children was less than 10,000. Hence, children are at health risk borderline.

A customized multi-cycle model for measuring the sustainability of circular pathways in agri-food supply chains.

Circular economy (CE) is claimed to be a promising pathway to achieve the Sustainable Development Goals (SDGs), but a reliable metric is needed to validate closed-loop strategies by measuring sustainability performances together with the degree of circularity. A significant contribution is offered by Life Cycle (LC) scholars in terms of methodological advances and operational tools for different sectors, also those more complex such as the agro-industrial systems that encompass biological and anthropogenic variables at different scales. However, to date, LC methodologies have not yet answered how to model the complexity of circular pathways. LC evaluations are often modelled for cradle-to-grave analyses, while a circularity evaluation would require an extension of the system boundaries to more interconnected life cycles, orienting towards a cradle-to-cradle perspective. This research gap led us to propose a multi-cycle approach with expanded assessment boundaries, including co-products, into a cradle-to-cradle perspective, in an attempt to internalize circularity impacts. The customized LC framework here proposed is based on the Life Cycle Assessment (LCA), the Environmental Life Cycle Costing (ELCC) in terms of internal and external costs, and the Social Life Cycle Assessment (SLCA) in terms of Psychosocial Risk Factor (PRF) impact pathway. The model is designed to be applied to the olive-oil sector, which commonly causes significant impacts by generating many by-products whose management is often problematic. Results are expected to show that the customized LC framework proposed can better highlight the environmental and socioeconomic performances of the system of cycles, allowing CE to deliver its promises of sustainability, as the circularity of materials per se is a means, not an end in itself.

The Status of Genetic Resources and Olive Breeding in Tunisia.

The olive tree, an iconic symbol of the Mediterranean basin, is the object of growing international interest in the production of olive oil for the world food market. In Tunisia, which is the fourth-largest producer of olive oil in the world, the production of olives and olive oil is of great socio-economic importance. Cultivation is widespread from north to south, but it is carried out using traditional techniques that results in extremely irregular production levels. To maintain their competitiveness on the international market, Tunisian producers must improve the quality of the oil through breeding plans that enhance the rich genetic heritage that is still not adequately exploited. The objective of this review is to present the state of olive breeding in Tunisia, illustrating the opportunities available for a better use of the rich Tunisian genetic heritage, the challenges it must face, and the need to multiply the efforts for sustainability, even in the light of the challenges posed by climate changes.

Optimization of preparation conditions of a novel low-cost natural bio-sorbent from olive pomace and column adsorption processes on the removal of phenolic compounds from olive oil mill wastewater.

Olive oil mill wastewater (OMWW) poses an undeniable environmental problem due to its high organic loads and phenolic compound (PC) content. This study determined the optimal conditions for preparing a new bio-sorbent from olive pomace (OP) and the adsorptive treatment of OMWW by this bio-sorbent. The activation reaction was performed with hydrogen peroxide. The results of the combination effect optimization of the three preparation variables, the activation temperature (°C) X1, the activation time (min) X2, and the impregnation ratio X3, are presented by the response surface methodology (RSM). The maximum adsorption capacity was obtained at an activation time of 240 min, a temperature of 80 °C, and a ratio equal to 6.2:1. The bio-sorbent was characterized by Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), and X-ray diffractometer (XRD). The adsorption process performance of this bio-sorbent was examined in batch (phenol solution) and fixed-bed columns (real effluent of OMWW). An adsorption capacity of 789.28 mg g-1 and 643.92 mg g-1 has been achieved for 4000 mg L-1 concentration of PCs, respectively, for batch and fixed-bed column essays. The adsorption isotherm and kinetics were consistent with the Langmuir and pseudo-second-order models. Therefore, the Thomas model best fits the fixed-bed column experimental data. The bio-sorbent gave a high desorption percentage of PCs, which was above 60% using HCl (0.1M).

Bay Laurel (Laurus nobilis L.) Essential Oil as a Food Preservative Source: Chemistry, Quality Control, Activity Assessment, and Applications to Olive Industry Products.

Essential oils (EOs) find application as flavoring agents in the food industry and are also desirable ingredients as they possess preservative properties. The Mediterranean diet involves the use of a lot of herbs and spices and their products (infusions, EOs) as condiments and for the preservation of foods. Application of EOs has the advantage of homogeneous dispersion in comparison with dry leaf use in small pieces or powder. Among them, Laurus nobilis (bay laurel) L. EO is an interesting source of volatiles, such as 1,8-cineole and eugenol, which are known for their preservative properties. Its flavor suits cooked red meat, poultry, and fish, as well as vegetarian dishes, according to Mediterranean recipes. The review is focused on its chemistry, quality control aspects, and recent trends in methods of analysis and activity assessment with a focus on potential antioxidant activity and applications to olive industry products. Findings indicate that this EO is not extensively studied in comparison with those from other Mediterranean plants, such as oregano EO. More work is needed to establish authenticity and activity methods, whereas the interest for using it for the preparation of flavored olive oil or for the aromatization and preservation of table oils must be further encouraged.

Low-Cost 3D Printer Drawn Optical Microfibers for Smartphone Colorimetric Detection.

A fused deposition modeling (FDM) 3D printer extruder was utilized as a micro-furnace draw tower for the direct fabrication of low-cost optical fibers. An air-clad multimode microfiber was drawn from optically transparent polyethylene terephthalate glycol (PETG) filament. A custom-made spooling collection allows for an automatic variation of fiber diameter between ϕ ∼ 72 to 397 µm by tuning the drawing speed. Microstructure imaging as well as the 3D beam profiling of the transmitted beam in the orthogonal axes was used to show good quality, functioning microfiber fabrication with uniform diameter and identical beam profiles for orthogonal axes. The drawn microfiber was used to demonstrate budget smartphone colorimetric-based absorption measurement to detect the degree of adulteration of olive oils with soybean oil.

Exploring multiple-cumulative trapping solid-phase microextraction coupled to gas chromatography-mass spectrometry for quality and authenticity assessment of olive oil.

This study explores the potential of an innovative multi-cumulative trapping headspace solid-phase microextraction approach coupled with untargeted data analysis to enhance the information provided by aroma profiling of virgin olive oil. Sixty-nine samples of different olive oil commercial categories (extra-virgin, virgin and lampante oil) and different geographical origins were analysed using this novel workflow. The results from each sample were aligned and compared using for the first time a tile-based approach to enable the mining of all of the raw data within the chemometrics platform without any pre-processing methods. The data matrix obtained allowed the extraction of multiple-level information from the volatile profile of the samples. Not only was it possible to classify the samples within the commercial category that they belonged to, but the same data also provided interesting information regarding the geographical origin of the extra-virgin olive oil.

Geographical Origin Assessment of Extra Virgin Olive Oil via NMR and MS Combined with Chemometrics as Analytical Approaches.

Geographical origin assessment of extra virgin olive oil (EVOO) is recognised worldwide as raising consumers' awareness of product authenticity and the need to protect top-quality products. The need for geographical origin assessment is also related to mandatory legislation and/or the obligations of true labelling in some countries. Nevertheless, official methods for such specific authentication of EVOOs are still missing. Among the analytical techniques useful for certification of geographical origin, nuclear magnetic resonance (NMR) and mass spectroscopy (MS), combined with chemometrics, have been widely used. This review considers published works describing the use of these analytical methods, supported by statistical protocols such as multivariate analysis (MVA), for EVOO origin assessment. The research has shown that some specific countries, generally corresponding to the main worldwide producers, are more interested than others in origin assessment and certification. Some specific producers such as Italian EVOO producers may have been focused on this area because of consumers' interest and/or intrinsic economical value, as testified also by the national concern on the topic. Both NMR- and MS-based approaches represent a mature field where a general validation method for EVOOs geographic origin assessment could be established as a reference recognised procedure.

Measurement Strategies for the Classification of Edible Oils Using Low-Cost Miniaturised Portable NIR Instruments.

Miniaturised near-infrared (NIR) instruments have been increasingly used in the last few years, and they have become useful tools for many applications on different types of samples. The market already offers a wide variety of these instruments, each one having specific requirements for the correct acquisition of the instrumental signal. This paper presents the development and optimisation of different measuring strategies for two miniaturised NIR instruments in order to find the best measuring conditions for the rapid and low-cost analysis of olive oils. The developed strategies have been applied to the classification of different samples of olive oils, obtaining good results in all cases.

Exploration of Spanish Olive Oil Quality with a Miniaturized Low-Cost Fluorescence Sensor and Machine Learning Techniques.

Extra virgin olive oil (EVOO) is the highest quality of olive oil and is characterized by highly beneficial nutritional properties. The large increase in both consumption and fraud, for example through adulteration, creates new challenges and an increasing demand for developing new quality assessment methodologies that are easier and cheaper to perform. As of today, the determination of olive oil quality is performed by producers through chemical analysis and organoleptic evaluation. The chemical analysis requires advanced equipment and chemical knowledge of certified laboratories, and has therefore limited accessibility. In this work a minimalist, portable, and low-cost sensor is presented, which can perform olive oil quality assessment using fluorescence spectroscopy. The potential of the proposed technology is explored by analyzing several olive oils of different quality levels, EVOO, virgin olive oil (VOO), and lampante olive oil (LOO). The spectral data were analyzed using a large number of machine learning methods, including artificial neural networks. The analysis performed in this work demonstrates the possibility of performing the classification of olive oil in the three mentioned classes with an accuracy of 100%. These results confirm that this minimalist low-cost sensor has the potential to substitute expensive and complex chemical analysis.

Life cycle assessment, C footprint and carbon balance of virgin olive oils production from traditional and intensive olive groves in southern Spain.

Olive oil production shapes the socio-economic and environmental life of many areas of the Mediterranean basin, especially southern Spain, the highest olive oil-producing region worldwide. Olive grove cultivation is tending to intensify from traditional low-density to intensive and high-density cropping systems, which might result in higher environmental impacts. The aim of this study is to estimate the environmental impacts, carbon (C) footprint and carbon balance of producing virgin origin olive oil in Spain from four traditional rainfed, four irrigated, and three intensive olive farms, including the processing phase. Environmental impacts of producing 1 kg of unpacked virgin olive oil at the farm and industrial phases were quantified with the Life Cycle Assessment (LCA) tool and a "cradle-to-gate" approach using data from surveys at these farms and 12 olive oil mills. On average, the farming phase accounted for 76.3% of the EIs. Therefore, to reduce the impact of the virgin olive oils production, most of the efforts should be made especially in the farming phase. Despite the high variability between seasons and between independent replicates of the same farming system, intensive farming had significant higher impacts on most environmental impact categories than traditional rainfed farming, mainly due to the application of nitrogen fertilizer, plant protection products and herbicides. In terms of climate change, the environmental impact of the functional unit is in the ranges of 1.80-2.41, 1.59-2.78 and 2.28-3.26 kg of CO2 eq. for traditional rainfed, irrigated and intensive, respectively. C footprint was negative and averaged -5.5, -4.3 and -2.7 kg CO2 eq. Olive groves are efficient atmospheric CO2 sinks mainly by fixing CO2 into permanent and non-permanent trees structures. The lower intensification of the traditional rainfed groves contributed more in mitigating the increase of atmospheric CO2. Finally, the C footprint and C balance are negative, especially in traditional irrigated and intensive farming. The application of organic sources of fertilizer and the implementation of temporary spontaneous cover crops, both technically and economically feasible, are sound strategies to achieve a positive carbon balance and reduce the impacts of olive cultivation.