RUJA: Repositorio Institucional de Producción Científica

 

DIEA-Artículos

URI permanente para esta colecciónhttps://hdl.handle.net/10953/234

Examinar

Envíos recientes

Mostrando 1 - 20 de 75
  • Ítem
    Power Gain and Daily Improvement Factor in Stand-Alone Photovoltaic Systems With Maximum Power Point Tracking Charge Regulators. Case of Study: South of Spain
    (American Society of Mechanical Engineers, 2013-11) Muñoz-Rodríguez, Francisco José; Jiménez-Castillo, Gabino; Fuentes-Conde, Manuel; Aguilar-Peña, Juan Domingo
    The performance reliability of a stand-alone photovoltaic system (SAPV) depends on the long-term performance of the batteries. In this way, a charge controller becomes an essential device which not only prevents the batteries from suffering deep discharges and overvoltages but also monitors the battery state of charge (SOC) in order to maximize charging efficiency and energy availability. At present, pulse width modulated (PWM) charge regulators dominate the market for this type of component in SAPV systems. However, in recent years, to improve energy management, more manufacturers have developed controllers with strategies for maximum power point tracking (MPPT). PWM charge controllers do not always make optimum use of the available power given by the maximum power point and this gives a loss of power. These power losses depend on battery voltage, irradiance and temperature. However, they can be avoided by using a MPPT charge controller which operates the array at its maximum power point under a range of operating conditions, as well as regulating battery charging. The advantage, in terms of energy gain, provided by this type of charge regulator depends on weather conditions. This paper will study the power gain provided by this type of charge controller, depending on the module temperature and the battery voltage. The paper will, additionally, provide a study of the gain in energy yield, also shown as improvement factor, F, for SAPV systems installed in Jaén (South of Spain). This study may illustrate the behavior of these two types of charge controllers in warm weathers, like Mediterranean climates. Furthermore, it will analyze the suitability of MPPT charge controllers and their benefits in this type of climate. It will be shown that MPPT charge regulator global efficiency constitutes a key issue in making a choice between MPPT and PWM charge regulators. The results given here may be not only of interest for SAPV systems with no access to the electricity grid but also for battery back-up PV grid-connected PV (GCPV) systems.
  • Ítem
    Distributed generation and photovoltaic selfconsumption. Energy potential for the olive mill industries in Spain
    (Publicaciones DYNA SL, 2020-09) Martínez-Calahorro, Antonio Javier; Jiménez-Castillo, Gabino; Rus-Casas, Catalina; Muñoz-Rodríguez, Francisco José
    The industrial sector faces a new paradigm of energy offshoring, where distributed generation can play a leading role in reducing energy costs in industries, as well as in its C02 emissions. This work shows the potential that photovoltaic self-consumption systems can present to face part of the consumption in the industries of the agri-food sector, specifically the oil mills. The electrical consumption of this type of industry for an oil mill is analyzed, as well as the level of coupling between the actual consumption profiles and the estimated photovoltaic generation profiles for a given range of powers of the photovoltaic generator. The analysis method is easily extrapolated to any mill located in Spain. Likewise, and given that this type of industry has a very characteristic consumption profile, the results obtained are easily transferable to other oil mills. For the mill analyzed, and from an annual perspective, a level of use of the generated photovoltaic energy of 75% with a self-sufficiency index of 20% has been estimated, highlighting the great potential of this technology, as an energy option in this type of industry, as well as in any other that presents a consumption with little variability.
  • Ítem
    Effects of smart meter time resolution when analyzing photovoltaic self-consumption system on a daily and annual basis
    (Elsevier, 2021-02) Jiménez-Castillo, Gabino; Rus-Casas, Catalina; Tina, Giuseppe Marco; Muñoz-Rodríguez, Francisco José
    The management of photovoltaic self-consumption systems is based mainly on updating energetic parameters such as generation and household power consumption connected via smart devices. The expected rapid increasing volume of data collected with different time resolutions is surely a topic that deserves great attention. The choice of a proper recording interval should balance the amount of monitored data and a proper energy analysis in order not only to take effective and timely decisions but also to help this technology to be more efficient. In the literature, only specific nominal array powers for annual reporting period or an array power range for daily reporting period have been considered. In this context, the error, when matching photovoltaic generation and household power consumption profiles considering different recording intervals (1, 10, 15, 30 and 60 min) and different reporting periods (daily and annual), will be estimated as a function of the array power (up to 10 kWp) for five households and a resident’s association. Results depend on the reporting periods and it may be advisable to use 1 min and 10 min of recording intervals in order to estimate performance metrics in this type of system for a daily and annual basis, respectively.
  • Ítem
    Performance analysis indices for Rooftop Solar Photovoltaic system
    (IEEE, 2023-07-09) Jiménez-Castillo, Gabino; Martínez-Calahorro, Antonio Javier; Rus-Casas, Catalina; Snytko, Anastasiia; Muñoz-Rodríguez, Francisco José
    The integration of rooftop solar photovoltaic systems into the electricity grid may be crucial in the current energy scenario. At present, this type of electricity generation is cost-competitive in many countries due to its modularity, the availability of the solar resource and the cost of the components, without the need for subsidies. Rooftop Solar Photovoltaic systems have the potential to cover 20-30% of electricity demand in Spain. In order to assess the potential of this technology and to facilitate the deployment of this type of systems, it is very important to provide a proper performance analysis of PV Rooftops systems from monitored data. In this way, self-consumption and self-sufficiency indices are commonly used, however they may not provide a complete assessment. Hence, indices such as the self-sufficiency index for sunshine hours, self-production index and grid-liability rate are also analyzed. These indices estimate the performance of rooftop solar PV systems and provide maximum and minimum values when estimated as a function of array peak power. Moreover, new indices such as the self-production index and the grid-liability rate for sunshine duration have been developed to estimate the system's performance during sunshine hours. These indices can complement the commonly used metrics and improve the performance analysis from monitored data. Moreover, they may also help determine the proper size of the array power of these systems in the industrial sector. The metrics are evaluated using data from four canning industries equipped with rooftop solar photovoltaic systems that have been monitored for a year.
  • Ítem
    A new approach based on economic profitability to sizing the photovoltaic generator in self-consumption systems without storage
    (Elsevier, 2020-04) Jiménez-Castillo, Gabino; Muñoz-Rodriguez, Francisco José; Rus-Casas, Catalina; López-Talavera, Diego
    A proper assessment of the cost-competitiveness and profitability of self-consumption systems is crucial to promoting the transition from grid-dependent to energy self-sufficient buildings. Most of the approaches found in the literature may not take into account economic parameters such as taxes, depreciation and the cost of financing, which have a significant effect on the economic profitability of an investment. Moreover, they only focus on discrete array powers and relatively high recording intervals when estimating the self-consumed energy. In order to manage the aforementioned challenges, a new method will be developed to size the PV generator in a PV self-consumption system which provides the NPV curve together with the self-consumption and self-sufficiency indices for a wide range of array powers which suits residential self-consumption systems. Two scenarios will be considered depending on whether the generated surplus electricity is wasted or it is remunerated from the grid operator. Results show that not only the chosen scenario but the electricity tariff may be key parameters when optimizing NPV. Furthermore, the impact of the recording interval may be significant when estimating NPV. Percentage errors of 11.4% and 33.6% may be reached when considering a recording interval of 15 and 60 min, respectively.
  • Ítem
    Monitoring PWM signals in stand-alone photovoltaic systems
    (Elsevier, 2019-02) Jiménez-Castillo, Gabino; Muñoz-Rodríguez, Francisco José; Rus-Casas , Catalina; Casa-Hernández, Jesús; Tina, Giuseppe Marco
    The performance of stand-alone photovoltaic (SAPV) systems can be evaluated by monitoring them in the field using data acquisition systems (DASs). Most SAPV systems use battery charge controllers with pulse width modulation (PWM) to regulate the current into the battery. The PWM signals generated by battery charge controllers imply monitoring challenges due to the complexity of this type of signal. In this sense, the aim of this paper is to develop a new and simple monitoring technique for SAPV systems which can estimate the signals provided by a PWM battery charge controller, thus avoiding expensive DASs, simultaneous sampling and the huge amount of collected data. The estimation of PWM signal parameters, such as the duty factor (df) or high and low states, shows high accuracy, with the mean absolute percentage error lower than 1.4%, a mean relative error within 1.4%, and the coefficient of determination higher than 0.9. Furthermore, the proposed technique may easily be used for other electrical devices where PWM is employed.
  • Ítem
    A new approach to sizing the photovoltaic generator in self-consumption systems based on cost–competitiveness, maximizing direct self-consumption
    (Elsevier, 2019-01) López-Talavera , Diego; Muñoz-Rodríguez , Francisco José; Jiménez-Castillo, Gabino; Rus-Casas, Catalina
    Applications for sizing Photovoltaic (PV) self-consumption systems have been studied over recent years in order to achieve either an optimization of the cost of energy, the investment cost or any economic profitability criteria. However, PV self-consumption systems at the residential or small business level can be designed with the aims of reducing the electricity consumption from the conventional local grid and achieving competitiveness with grid electricity prices. These criteria will provide not only greater environmental benefits, security and independence of the grid but it will make the cost of PV self-consumption electricity competitive with electricity prices from the power grid. In this sense, this paper proposes a method to size the generator for a PV self-consumption system based on cost-competitiveness, maximizing direct self-consumption. The method will be applied for three different households located in the south of Spain using the household daily consumption and generation profiles for a single year. However, the method here illustrated can be applied to other countries. The results obtained suggest that residential direct PV self-consumption systems with an annual global irradiation at the optimal tilt angle higher than 1000 kWh/(m2·year) may be a feasible investment to future owners of these systems.
  • Ítem
    Photovoltaic Self-Consumption in Industrial Cooling and Refrigeration
    (MDPI, 2020-12-21) Martínez-Calahorro, Antonio Javier; Jiménez-Castillo, Gabino; Rus-Casas, Catalina; Gómez-Vidal, Pedro; Muñoz-Rodríguez, Francisco José
    The industrial sector has a great opportunity to reduce its energy costs through distributed generation. In this sense, the potential of photovoltaic self-consumption systems in the industrial cooling and refrigeration sector is shown. Two industries with photovoltaic self-consumption installations are shown and the electricity consumption profile of this type of industry which has a remarkable basal electricity consumption during daytime is analyzed. The matching between consumption and photovoltaic generation profiles is provided through the self-consumption and self-sufficiency curves considering different reporting periods (monthly and annual). Moreover, a new index is presented: self-sufficiency index for sunshine hours, φSS,SH. This index evaluates the performance of the photovoltaic self-consumption system when facing the consumption only during sunshine hours. This index may complement the self-sufficiency index and may improve the analysis of this type of systems in the industrial sector. Self-consumption indices of 90% may be provided. Moreover, self-sufficiency indices for total (24 h) and for sunshine hours of 25% and 50%, respectively, for industry A, and 26% and 45% for industry B have been obtained. During daytime, half the load consumption in this type of industry may be covered by photovoltaics while achieving high levels of use of the photovoltaic energy generated.
  • Ítem
    Impacts of Array Orientation and Tilt Angles for Photovoltaic Self-Sufficiency and Self-Consumption Indices in Olive Mills in Spain
    (MDPI, 2020-02-18) Jiménez-Castillo, Gabino; Muñoz-Rodríguez, Francisco José; Martinez-Calahorro, Antonio Javier; Tina, Giuseppe Marco; Rus-Casas, Catalina
    Olive mills are extensive in the Mediterranean Basin, and Spain constitutes approximately 45% of global production. The industrial sector faces a new energetic paradigm where distributed generation provided by small renewable energy sources may reduce the dependence from fossil energy sources as well as avoid energy distribution losses. Photovoltaic self-consumption systems can play an important role in confronting this challenge due to their modularity and their decreasing cost. Most of self-sufficiency energy studies are focused on building sector and discussions about the idiosyncrasy of industrial load profiles, and their matching capability with photovoltaic generation profiles can be scarcely found. This work analyzes the potential of photovoltaic self-consumption systems as a function of the array power, array tilt, and orientation angles to face the electric consumption in olive mills. Different recording intervals and reporting periods are considered. Results show that a self-sufficiency index of 40% may be achieved on olive harvest basis. Moreover, due to the load profile particularities, percentage error lower than 1.6% has been found when considering a recording interval of 60 min when matching the olive load consumption and photovoltaic generation profiles. Chosen array tilt and orientation angles may be key parameters to maximize the self-sufficiency index.
  • Ítem
    Development of a Prototype for Monitoring Photovoltaic Self-Consumption Systems
    (MDPI, 2020-01-01) Rus-Casas, Catalina; Jiménez-Castillo, Gabino; Aguilar-Peña, Juan Domingo; Fernández-Carrasco, Juan Ignacio; Muñoz-Rodríguez, Francisco José
    Currently, the increasing energy consumption around the world and the environmental impact resulting from the use of fossil fuel-based energy have promoted the use of renewable energy sources such as photovoltaic solar energy. The main characteristic of this type of energy is its unpredictability, as it depends on meteorological conditions. In this sense, monitoring the power generation of photovoltaic systems (PVS) in order to analyze their performance is becoming crucial. The purpose of this paper is to design a monitoring system for a residential photovoltaic self-consumption system which employs an Internet of Things (IoT) platform to estimate the photovoltaic power generation according to solar radiation and temperature. The architecture of the developed prototype will be described and the benefits of providing the use of IoT for monitoring will be highlighted, since all data collected by the data acquisition system (DAS) may be stored in the Cloud. The comparison of the results with those of other monitoring systems was very positive, with an uncertainty that complies with the IEC61724 standard.
  • Ítem
    Improvements in Performance Analysis of Photovoltaic Systems: Array Power Monitoring in Pulse Width Modulation Charge Controllers
    (MDPI, 2019-05-09) Jiménez-Castillo, Gabino; Muñoz-Rodríguez, Francisco José; Rus-Casas, Catalina; Gómez-Vidal, Pedro
    Various challenges should be considered when measuring photovoltaic array power and energy in pulse width modulation (PWM) charge controllers. These controllers are frequently used not only in stand-alone photovoltaic (SAPV) systems, but may also be found in photovoltaic (PV) self-consumption systems with battery storage connected to the electricity grid. An acceptable solution may be reached using expensive data acquisition systems (DASs), although this could be generally disproportionate to the relatively low cost of SAPV systems. Therefore, the aim of this paper is to develop new and e ective monitoring techniques which will provide the PV array direct current (DC), output power (PA,dc), and PV array DC output energy (EA), thus avoiding the use of sophisticated DASs and providing high accuracy for the calculated parameters. Only transducers and electronic circuits that provide the average and true rms values of the PWM signals are needed. The estimation of these parameters through the aforementioned techniques showed high accuracy for both series and shunt PWM battery charge controllers. Normalized root mean square error (NRMSE) was lower than 2.4%, normalized mean bias error (NMBE) was between 􀀀1.5% and 1.1%, and mean absolute percentage error (MAPE) was within 1.6%.
  • Ítem
    Development of a Utility Model for the Measurement of Global Radiation in Photovoltaic Applications in the Internet of Things (IoT)
    (MDPI, 2019-03-08) Rus-Casas, Catalina; Hontoria, Leocadio; Fernández-Carrasco, Juan Ignacio; Jiménez-Castillo, Gabino; Muñoz-Rodríguez, Francisco José
    In order to develop future projects in the field of photovoltaic solar energy, it is essential to accurately know the potential solar resources. There are many methods to estimate the incident solar radiation in a certain place. However, most of them are very expensive or do not have the ideal characteristics for good monitoring of a particular photovoltaic installation. For these reasons, an electronic device connected to the internet of things (IoT) is presented in this paper which manages to measure global radiation in photovoltaic applications. The device developed has been patented in the Spanish Patent and Trademark Office. It presents some features that make it very suitable to measure photovoltaic installations with the advantage of being a low cost and very reliable device. The device has been tested to determine global horizontal irradiance obtaining a correlation coefficient R2 = 0.994.
  • Ítem
    Comparative analysis of direct inclined irradiance data soruces for micro-tracking concentrator photovoltaics
    (MDPI, 2025-06-05) Pérez-Higueras, Pedro; Ceballos, María Ángeles; Mouhib, Elmehdi; Bessa, Joao Gabriel; Montes-Romero, Jesús; Mata-Campos, Raul
    In recent years, the scientific community has intensified its efforts to develop a new type of concentrator photovoltaic module that is competitive with conventional modules. These modules are based on internal tracking systems, known as micro-tracking concentrator photovoltaic modules, which generate electrical energy proportional to the direct radiation on the inclined surface. There are several reviews, databases, and models for various components of solar radiation, particularly for global and direct normal radiation. However, readily available data on direct inclined irradiance remain scarce. This paper reviews several available sources of solar radiation data, finding that only the Photovoltaic Geographic Information System and Solar Radiation Database provide direct inclined irradiance data. A comparative statistical analysis was carried out, and a reasonable fit was obtained between both databases. In addition, direct inclined radiation data extracted from these databases were compared with the values calculated using a well-established mathematical model. In addition, worldwide maps were generated to determine areas of interest for this technology. Therefore, this paper presents an original comparative analysis of existing databases containing information on direct inclined irradiation. This information is of interest for the accurate design and performance analysis of micro-tracking concentrator modules.
  • Ítem
    A new approach to analyse from monitored data the performance, matching capability and grid usage of large Rooftop Photovoltaic systems. Case of study: Photovoltaic system of 1.05 MW installed at the campus of University of Jaén
    (Elsevier, 2025) Muñoz-Rodríguez, Francisco José; Gómez-Vidal, Pedro; Fernández-Carrasco, Juan Ignacio; Tina, Giuseppe Marco; Jiménez-Castillo, Gabino
    Rooftop photovoltaic installations highlight their potential to meet a significant portion of urban electricity demand. These systems range from a few kW in residential areas to hundreds of kW in large Rooftop PV systems in commercial and industrial settings. The latter, which may include several inverters or arrays with different orientations and inclinations, require a proper analysis to assess the potential of this technology and to ensure the design objectives. This paper presents a methodology for analysing from monitored data large Rooftop PV systems, focusing on performance, self-consumption and grid usage. The approach is scalable, applicable at the inverter, individual Rooftop PV and global system levels. New key parameters defined include weighted system irradiation (HI,weighted) and weighted system reference yield (Yr,weighted), which account for different array orientations and inclinations. The methodology is validated using a 1.05 MW system at the University of Jaén with monitored data over a year. Results indicate subsystem and system PR values above 0.83 and a system Capacity Factor of 0.19, confirming a proper performance. Annual self-consumption and self-sufficiency indices of 97.5 % and 17.7 %, respectively, and a solar hour self-sufficiency of 27.7 % reveal minimal energy export and substantial potential to meet the university’s electricity demand.
  • Ítem
    Effect of electrical operating conditions on thermal behavior of PV modules: Numerical and experimental analysis
    (Elsevier, 2025) Osama, Amr; Tina, Giuseppe Marco; Gagliano, Antonio; Jiménez-Castillo, Gabino; Muñoz-Rodríguez, Francisco José
    The rapid growth of photovoltaic (PV) energy has the potential to transform the global energy landscape. However, the intermittent nature of solar power presents significant challenges to grid integration, such as overgeneration and curtailment. Consequently, PV systems may operate at points other than the maximum power point (MPP). Monitoring the thermal behavior of photovoltaic systems is critical due to its impact on productivity and system health. Most studies focus on meteorological variables, often overlooking the influence of electrical operating states on thermal performance. Thus the objective is to evaluate the accuracy of existing thermal models from the literature and widely used specialized software tools—alongside their commonly cited coefficients against different electrical operating status (EOS). This study investigates the thermal behavior of PV modules under different EOS: short-circuited (PVset-1), open-circuited (PVset-2), and operating at MPP (PVset-3). The experiment was conducted over four months at Jaén University campus in Spain. Results showed the short-circuited module's temperature was 6.90 °C higher, and the open-circuited module's temperature was 3.67 °C higher than the MPP module. Thermographic investigations revealed multiple hotspots in the short-circuited set. These hotspots can severely impact the module's long-term reliability and efficiency. The analysis of thermal models considering these operating states indicated an overestimation of the MPP module's temperature. However, the Keddouda model demonstrated high accuracy potential, with an average deviation of less than 3.4 %, particularly at high irradiance levels. These findings highlight the necessity of considering EOS in thermal models to enhance the accuracy and reliability of PV system performance assessments.
  • Ítem
    3D object recognition for anthropomorphic robots performing tracking tasks
    (Springer, 2019-07-03) Satorres Martínez, Silvia; Sánchez García, Alejandro; Estévez Estévez, Elisabet; Gómez Ortega, Juan; Gámez García, Javier
    Object recognition is still a major research issue of particular relevance in robotics. The new trend in industrial and mainly in service robotics is to perform manipulation tasks in an unstructured environment working in synergy with humans. To perform tasks in an environment that is not perfectly controlled, robots need adequate perceptual capabilities. Among various types of sensors available for robotic systems, the time-of-flight (ToF) camera is one of the most utilized since it simultaneously provides intensity and depth data at a high frame rate. Our proposal makes use of this technology exploiting both, depth and grey-scale information. Therefore, intensity and geometric features are fused together to allow 3D object recognition in real scenes in presence of partial occlusions. As a case study, an object tracking task for an anthropomorphic robot is presented. Experimental results demonstrate the effectiveness of the proposed method, not only providing reliable visual information about the object to be tracked but also recognizing potential obstacles which should be avoided during the robot arm movement.
  • Ítem
    The Advantage of Multispectral Images in Fruit Quality Control for Extra Virgin Olive Oil Production
    (Springer, 2021-08-17) Martínez Gila, Diego M.; Navarro Soto, Javiera P.; Satorres Martínez, Silvia; Gómez Ortega, Juan; Gámez García, Javier
    The highest quality of extra virgin olive oil must be guaranteed to succeed in the competitive market of the industry. To fulfil this need, high standards of fruit quality are required. In recent years, this search has led to the development of computer vision systems for the automatic inspection of fruits. Skin damage, dirtiness, and external colour were the main features selected. However, no known report is related to the internal quality evaluation of olives. The present research explores the application of multispectral images (from 600 to 975 nm) to discriminate olive fruits by their firmness. To achieve this aim, 58 olives were classified as hard or soft by an expert and then measured by a penetrometer. Afterwards, 58 multispectral images were obtained, and 8352 pixels were randomly selected for feature extraction. The feature vector of each pixel was composed of 25 infrared absorption values. These data were input into three supervised classification algorithms: a naïve Bayes (NB) classifier, a multilayer perceptron (MLP), and a support vector machine variation (SMO). The highest performance was achieved by the MLP, with an accuracy of 95% for the firmness grading. Furthermore, the three algorithms were subjected to principal component analysis (PCA), by which the MLP was confirmed to be the best model and its results were improved. Moreover, according to the second principal component, the 675 nm and 855 nm band frequencies have the strongest weights. The overall results confirm the convenience of multispectral imaging in olive firmness inspection, with the advantage of being a non-invasive technology.
  • Ítem
    Application of a Lab-Made Voltametric Electronic Tongue to Identify Musty and Vinegary Defects in Olive Oils
    (Springer, 2022-11-25) Martínez Gila, Diego Manuel; Estévez Estévez, Elisabet; Gómez Ortega, Juan; Gámez García, Javier
    The olive oil sector is undergoing a technological transformation promoted by high international competitiveness. This transformation must be aligned with the concepts of industry 4.0 that are already well defined and implemented in other sectors. The integration of advanced sensorics in the process phase in which the quality of the manufactured product is inspected is key to responding in the shortest possible time to deviations in the desired quality. In this work, the results of the experimentation carried out with an e-tongue voltammetric sensor are presented to evaluate its potential in the detection of two of the organoleptic defects that appear more frequently in olive oil (musty and vinegary). This sensor has been built in the research group’s laboratory and is made up of three metals in the measurement probe (nickel, silver and copper). Three classification algorithms (Support Vector Machines, Naïve Bayes and Classification Trees) were used and musty-type defect was identified with a success rate of 72%, while the vinegary-type defect was detected with a success rate of 84%.
  • Ítem
    Olive fly sting detection based on computer vision
    (ELSEVIER, 2019-11-14) Beyaz, Abdullah; Martínez-Gila, Diego Manuel; Gómez-Ortega, Juan; Gámez-García, Javier
    Olive fly (Bactrocera oleae Rossi) is a parasite that infects olive fruit by stinging the fruit to deposit its eggs. The infection damages the fruit during its growth and affects the quality of the olive oil as a final product. Detection of olive fly stings in the virgin olive oil production process is therefore critical. This research aimed to develop automatic methodologies based on computer vision to detect fly stings in infected olive fruit samples. Different methodologies to detect defective areas on the surface of the fruit and classify them between stings and other bruises are described. The methodology to detect defective areas reached a success ratio of 93% and best classification algorithms reached a success ratio close to 80%. The proposed methodology could be applied at reception of fruit for input of the virgin olive oil production process.
  • Ítem
    Classification of olive fruits and oils based on their fatty acid ethyl esters content using electronic nose technology
    (SPRINGER, 2021-08-20) Martínez Gila, Diego Manuel; Sanmartin, Chiara; Navarro Soto, Javiera; Mencarelli, Fabio; Gómez Ortega, Juan; Gámez García, Javier
    Among several parameters defined for the commercial classes of virgins olive oils (VOOs), there is one, the fatty acid ethyl ester (FAEE), that is only define for the best quality (EVOO). Fruit condition mainly determine these compounds, although, extraction process or deplorable storage condition could rise them up. The FAEE oxidation compound are originated by adding an alcohol chain into the oil molecule. Therefore, the hypothesis of this study is that the inherent constitution of FAEE entails a modification of the volatile profile of oils and olives and this is significant enough to be detected using an electronic nose. With this aim, different samples of olives and oils were analyzed in an accredited laboratory. On the other hand, volatiles from the same samples were captured by an electronic nose. The classification problem was analyzed from two points of view or models. The first was to classify fruits and oils based on whether they are within or outside the legal limits. And the second problem was oriented to classify fruits and oils based on their high or low FAEE content but being within the legal limits. To solve this problem, three classification algorithms were evaluated: Naïve Bayes (NB), Multilayer Perceptron (MLP) and Sequential Minimal Optimization (SMO). For the first model, a well-classified sample rate of 80.3% was obtained for NB and 100% for SMO and MLP, for measurements on oils. The same model evaluated with measurements on olives yielded a success rate of 87.5% with NB, 87.7% with MLP and 82.1% with SMO. For the second model, the suc- cess rates remained within the same orders of magnitude. For measurements on oils, the results were 89.7% for NB, 92.5% for MLP and 100% for SMO. And for measurements on olives the results were 77.9% for NB, 88.6% for MLP and 90.9% for SMO. In all cases, the characteristics that worked best were those obtained from the first derivative of the electronic nose response. Based on these results, the e-nose demonstrate to be a non-invasive technology suitable for the classification of olive fruits and oils based on their FAEE content.