Search

The effect of the QTL involved in climacteric ripening ETHQB3.5 on the fruit VOC composition was studied using a set of Near-Isogenic Lines (NILs) containing overlapping introgressions from the Korean accession PI 16375 on the chromosome 3 in the climacteric ‘Piel de Sapo’ (PS) genetic background. ETHQB3.5 was mapped in an interval of 1.24 Mb that contained a NAC transcription factor. NIL fruits also showed differences in VOC composition belonging to acetate esters, non-acetate esters, and sulfur-derived families. Cosegregation of VOC composition (23 out of 48 total QTLs were mapped) and climacteric ripening was observed, suggesting a pleiotropic effect of ETHQB3.5. On the other hand, other VOCs (mainly alkanes, aldehydes, and ketones) showed a pattern of variation independent of ETHQB3.5 effects, indicating the presence of other genes controlling non-climacteric ripening VOCs. Network correlation analysis and hierarchical clustering found groups of highly correlated compounds and confirmed the involvement of the climacteric differences in compound classes and VOC differences. The modification of melon VOCs may be achieved with or without interfering with its physiological behavior, but it is likely that high relative concentrations of some type of ethylene-dependent esters could be achieved in climacteric cultivars.

Wind turbine blades have been constantly increasing since wind energy becomes a popular renewable energy source to generate electricity. Therefore, the wind sector requires a more efficient and representative characterization of vertical wind speed profiles to assess the potential for a wind power plant site. This paper proposes an alternative characterization of vertical wind speed profiles based on Ward's agglomerative clustering algorithm, including both wind speed module and direction data. This approach gives a more accurate incoming wind speed variation around the rotor swept area, and subsequently, provides a more realistic and complete wind speed vector characterization for vertical profiles. Real wind database collected for 2018 in the Forschungsplattformen in Nordund Ostsee (FINO) research platform is used to assess the methodology. A preliminary pre-processing stage is proposed to select the appropriated number of heights and remove missing or incomplete data. Finally, two locations and four heights are selected, and 561588 wind data are characterized. Results and discussion are also included in this paper. The methodology can be applied to other wind database and locations to characterize vertical wind speed profiles and identify the most likely wind data vector patterns.

The aim of this research was to analyze the drivers and barriers facing the agents involved in the energy renovation process and the effective use of existing subsidies for this purpose. The drive for energy renovation in buildings is undeniable. European policies aiming to completely decarbonize the economy by 2050 will give an important boost to the building sector in Europe by improving comfort conditions in renovated homes. In this study, a questionnaire was developed using the free software LimeSurvey, which was then evaluated by experts. The questionnaire included representative indicators of energy refurbishment and was segmented into the intervening groups to highlight their differences. The results were analyzed using the Mann–Whitney test for group comparisons and Pearson’s correlation coefficient to assess the relationships between the responses. This analysis reveals the complexity of a process, in which excessive bureaucratic requirements to obtain Next Generation EU funds, economic aspects (80%) and owners’ lack of awareness are the barriers that were most highlighted by those surveyed (77%). In terms of motivation, we found that, apart from economic savings (88%), the most valued aspect for users was noise insulation (93%), which is not directly related to energy improvement. This study highlights the lack of knowledge and information that the agents responsible for this change have about energy improvement and their differences in opinions on motivations and barriers.

[SPA] La problemática respecto a la variabilidad de las series temporales, junto con la creciente preocupación sobre el estado del Mar Menor, ha impulsado la necesidad de desarrollar una metodología efectiva para el análisis y pronóstico de datos temporales. En este Trabajo de Fin de Estudios (TFE), se ha seguido una metodología sistemática que abarca desde la exploración y clasificación de la serie temporal hasta la selección del modelo más adecuado para su predicción. Mediante la aplicación de esta metodología a datos reales del Mar Menor, se ha validado su eficacia y precisión en el análisis de series temporales complejas. Se destacó que los modelos estadísticos son idóneos para predicciones a corto plazo, mientras que los modelos de inteligencia artificial son más apropiados para proyecciones futuras. Los resultados obtenidos ofrecen un enfoque sólido para la comprensión y gestión de datos temporales, contribuyendo al avance en la toma de decisiones en el contexto del Mar Menor y en otros ámbitos que enfrentan desafíos similares. [ENG] The growing concern about the state of the Mar Menor and the problem of the variability of the time series, has driven the need to develop an effective methodology for the analysis and forecasting of time series data. In this TFE, a systematic methodology has been proposed, ranging from the exploration and classification of the time series to the selection of the most appropriate model for its prediction. By applying this methodology to real data from the Mar Menor, its effectiveness and accuracy in the analysis of complex time series has been validated. It was highlighted that statistical models are suitable for short-term predictions, while artificial intelligence models are more appropriate for future projections. The results obtained provide a robust approach to understanding and managing temporal data, contributing to the advancement of decision making in Mar Menor context and other areas facing similar challenges.

The management of the COVID-19 pandemic, which required global lockdowns and mobility restrictions, positively impacted air quality (especially the concentrations of primary pollutants). With the progressive return to normal activity during the last few months of 2020 and 2021, air pollutant concentrations were expected to rise again. In this work, together with meteorological conditions and traffic intensity, the concentrations of NO, NO2, O3, PM10, and SO2 measured at three different locations (urban, industrial, and rural) in southeast Spain, from January 2016 to December 2021, were analyzed. For the three locations, PM10 concentrations did not change significantly in 2020 or 2021. SO2 concentrations did not experience changes at the industrial site in 2020 or 2021, but SO2 concentrations did slightly increase in five months of 2021 in the urban location (with a maximum monthly average concentration of 11 g·m-3). In 2020, NO and NO2 concentrations were, in general, lower than those measured in previous years (2016–2019). Interestingly, at the urban site (San Basilio), the levels of NO and NO2 were significantly lower in 2021 than in 2020 despite the higher traffic intensity in 2021. While the concentrations of NO and NO2 decreased, in VOC-limited areas, O3 concentrations increased. This was clearly observed at the industrial and the urban sites. Despite the increase, O3 concentrations were still below the European O3 target value for the protection of human health. An analysis of new registrations of EVs and HEVs in the latter years and their impact on the vehicle fleet of Murcia and, subsequently, on road emissions was carried out. Regardless of the steep increase in environmentally friendly vehicles in 2021, their share of the vehicle fleet is still negligible; thus, the lower concentrations of NO and NO2 are likely due to more favorable weather conditions in 2021 than in 2020.

Nowadays, with the development of international policies and agreements to promote the integration of renewable energy sources, mainly solar and wind, modeling the solar resource by including the spatio-temporal variability is crucial to determine future PV power plant locations and estimate potential power generation performances. However, contributions involving long-term periods and different time windows to explore such potential solar resource variability are generally scarce. Under this framework, the present paper proposes a methodology focused on characterizing and clustering the spatio-temporal solar resource variability through the global horizontal irradiance analysis. Hierarchical clustering technique is firstly used to classify the spatial data. Different time windows — from short-term to long-term data — can be subsequently evaluated by using various sources of information. The Spanish territory is selected as case study, considering 22-year period data (1999–2020) and 1,936,917 observations from online satellite database. Spatial variability and geographical clustering differences are discussed and compared depending on the selected time windows, identifying relevant spatial variations for some specific months. Additionally, some years present more variability as well, in line with the sunspot peak of the solar cycles. The proposed approach gives an alternative comprehensive spatio-temporal clustering and characterization of GHI evolution, providing a suitable methodology to help the current European sustainable energy transition.

Due to the relevant penetration of solar PV power plants, an accurate power generation forecasting of these installations is crucial to provide both reliability and stability of current grids. At the same time, PV monitoring requirements are more and more demanded by different agents to provide reliable information regarding performances, efficiencies, and possible predictive maintenance tasks. Under this framework, this paper proposes a methodology to evaluate different LoRa-based PV monitoring architectures and node layouts in terms of short-term solar power generation forecasting. A random forest model is proposed as forecasting method, simplifying the forecasting problem especially when the time series exhibits heteroscedasticity, nonstationarity, and multiple seasonal cycles. This approach provides a sensitive analysis of LoRa parameters in terms of node layout, loss of data, spreading factor and short time intervals to evaluate their influence on PV forecasting accuracy. A case example located in the southeast of Spain is included in the paper to evaluate the proposed analysis. This methodology is applicable to other locations, as well as different LoRa configurations, parameters, and networks structures; providing detailed analysis regarding PV monitoring performances and short-term PV generation forecasting discrepancies.

[SPA] Esta tesis doctoral se presenta bajo la modalidad de compendio de publicaciones. La necesidad de lograr una economía descarbonizada para evitar los efectos del cambio climático ha derivado en una serie de compromisos internacionales que obligan a España y Europa a reducir paulatinamente sus emisiones de gases de efecto invernadero hasta alcanzar la neutralidad climática en 2050. Este objetivo solo se puede alcanzar con un nuevo modelo energético basado en una integración masiva de energías renovables. Entre las tecnologías llamadas a convertirse en uno de los pilares de esta descarbonización de la economía se encuentra la energía solar fotovoltaica como consecuencia de su propia madurez tecnológica y la significativa reducción de costes que ha experimentado en los últimos años. Dentro de las instalaciones fotovoltaicas, una de las tipologías que ha recibido un mayor impulso son las instalaciones de autoconsumo ubicadas cerca de los puntos de demanda eléctrica gestionadas por los consumidores que pasan a ser también proveedores de energía y servicios a la red convirtiéndose en los denominados “prosumers“. Esta integración masiva de nuevas plantas de generación distribuida supone un desafío para la gestión de la red eléctrica que, tradicionalmente, ha respondido a un modelo de flujo de potencias unidireccional donde la potencia fluye desde grandes unidades de generación hacia los puntos de consumo, ajustando en todo momento la generación a la demanda y consiguiendo un balance de potencias que permitiese regular y controlar de manera efectiva los valores de tensión y frecuencia dentro de rangos admisibles. El nuevo modelo de generación distribuida basada en renovables requiere de nuevas herramientas y estrategias de gestión para hacer frente a la variabilidad que presentan estas energías renovables por su propia naturaleza y el gran número y dispersión geográfica de instalaciones que requieren una mayor flexibilidad ante nuevos retos en forma de flujo bidireccion, [ENG] This doctoral dissertation has been presented in the form of thesis by publication. The need to achieve a decarbonized economy to fight climate change has prompted several international commitments that oblige Spain and Europe to progressively reduce their greenhouse gas emissions until reaching climate neutrality in 2050. This goal can only be reached with a new energy model based on a massive integration of renewable energies. Among these technologies, photovoltaic solar energy is called to become one of the pillars to decarbonize the economy decarbonization thanks to its own technological maturity and the significant cost reduction, it has experienced in recent years. Within the different types of photovoltaic installations, one of the fastest growing is that of self-consumption, which are installations located near the points of electricity demand managed by the consumers themselves who also become providers of energy and services to the network, becoming the so-called prosumers.This massive integration of new distributed generation plants poses a challenge for the management of the electricity grid, which has traditionally responded to a unidirectional power flow model. In this unidirectional model, the power flows from the large generation units to the consumption points, adjusting the generation to achieve a power balance that allows effective regulation and control of the voltage and frequency values within the admissible ranges. The new decentralized distributed model requires new tools and management strategies to deal with the variability that renewable energies present due to their very nature and the large number and the geographical dispersion of installations that require greater flexibility to ensure a constant supply to cover demand and meet new challenges in the form of bidirectional flow of power These new management strategies are supported by the great advances made by information and communication technologies (ICTs) that have been gradua

Phosphoric fertiliser has enormously contributed to agriculture; however, it generates five tonnes of phosphogypsum per ton of phosphoric acid synthesised. Phosphogypsum houses heavy metals and long-lived radioactive elements that represents an environmental issue requiring remediation. This paper presents a methodology for characterising phosphogypsum deposits using geophysical, geochemical, and statistical tools. Gamma-ray probes determined the abnormal radioactive zones within the phosphogypsum deposits while electrical resistivity tomography provided the geometry and distribution of the phosphogypsum deposits. Chemical results confirmed the high presence of heavy metals in the waste determining chromium as the most concentrated metal. Radiological measures indicate that the effective ambient dose equivalent average in the study area surface is approximately 8.5 times higher than the average for Europe. While at 1.0 m depth, in the phosphogypsum layer, the ambient dose equivalent average surpasses approximately 27 times the European average. Statistical correlation analysis supports that the radiation increases due to the uranium presence. This methodology might reduce time and cost avoiding the use of expensive traditional methods, and it is exportable to any deposit.

[SPA] En este trabajo se presenta un estudio estadístico sobre los niveles de concentración de ciertos contaminantes en el aire ambiente de la Región de Murcia durante el periodo 2016-2020. En primer lugar, se ha realizado una introducción teórica con el fin de introducir conceptos destacados, así como comprender la legislación en materia de calidad del aire en España. Posteriormente, se han analizado datos de calidad del aire, obtenidos en ocho estaciones de medición fija distribuidas por toda la Región e información sobre la intensidad de tráfico en distintas carreteras. Se han obtenido una serie de representaciones gráficas y resúmenes numéricos a partir de los cuales se han extraído las conclusiones apropiadas sobre el dióxido de azufre (SO2), dióxido de nitrogeno (NO2), ozono (O3) y materia particulada (PM10). Tras analizar los resultados, se observa una clara disminución de los contaminantes PM10 y NO2 durante el 2020 como consecuencia de las restricciones aplicadas por el gobierno, concretamente aquellas relacionadas con el transporte. El ozono también sigue este comportamiento debido a las relaciones de dependencia que presenta con ciertos contaminantes. Por su parte, el SO2 se presenta como un contaminante no influenciado por la pandemia, aunque se observan distintas variaciones en función de la estación considerada. Finalmente, se confirma una clara influencia de la pandemia en la calidad del aire, lo que pone de manifiesto una estrecha relación entre actividad humana y contaminación atmosférica y con ello, la necesidad de cambiar nuestra forma de actuar. [ENG] This project presentes a statistical study on the concentration levels of certain pollutants in the ambient air of the Region of Murcia during the period 2016-2020. First, a theoretical introduction has been made in order to introduce important concepts, as well as to understand the legislation on air quality in Spain. Subsequently, air quality data analized from eight fixed measurement stations dis

This study presents the results of a physical-chemical characterisation of phosphogypsum deposits generated with hydrochloric and sulphuric acid during the wet acid process. The paper aims to establish an efficient methodology based on electrical resistivity tomography (ERT), chemical analysis and multivariate analysis identifying the areas most contaminated by heavy metals in an abandoned factory where fertiliser was derived from phosphoric rock. This fertiliser has provided many benefits to agriculture; however, it generates a vast amount of waste (5 tonnes phosphoric rock/1 tonne fertiliser). The chemical composition of this by-product varies according to the industrial process performed. Hydrochloric acid (HCl) recovers more than 90% of phosphorus, while sulphuric acid (H2SO4) recovers around 30%. Therefore, a chemical assessment of the remaining waste is a necessary step prior to initiating any remediation process. ERT provided the geometry of the deposits and the distribution of the phosphogypsum. The chemical analyses consistently validated the electrical contrast found within the deposits. We employed a correlation analysis combined with multivariate analysis to identify the relationships among the metal concentrations and resistivity. Principal component analysis (PCA) reduced the information contained in all the variables to a few principal components. The first three principal components accounted for 74% of the variability of all the studied variables. Partial least squares-discriminant analysis (PLS-DA) for classification allowed the discrimination of the two populations. Electrical resistivity was the most influential variable for separating HCl waste from that of H2SO4. The use of ERT saves time and reduces costs yielding a methodology which facilitates the environmental assessment of large areas.

BACKGROUND. A near-isogenic line (NIL) of melon (SC10-2) with introgression in linkage group X was studied from harvest (at firm-ripe stage of maturity) until day 18 of postharvest storage at 20.5 °C together with its parental control (‘Piel de Sapo’, PS). RESULTS. SC10-2 showed higher flesh firmness and whole fruit hardness but lower juiciness than its parental. SC10-2 showed a decrease in respiration rate accompanied by a decrease in ethylene production during ripening, both of which fell to a greater extent than in PS. The introgression affected 11 volatile organic compounds (VOCs), the levels of which during ripening were generally higher in SC10-2 than in PS. Transcriptomic analysis from RNA-Seq revealed differentially expressed genes (DEGs) associated with the effects studied. For example, 909 DEGs were exclusive to the introgression, and only 23 DEGs were exclusive to postharvest ripening time. Major functions of the DEGs associated with introgression or ripening time were identified by cluster analysis. About 37 genes directly and/or indirectly affected the delay in ripening of SC10-2 compared with PS in general and, more particularly, the physiological and quality traits measured and, probably, the differential non-climacteric response. Of the former genes, we studied in more detail at least five that mapped in the introgression in linkage group (LG) X, and 32 outside it. CONCLUSION. There is an apparent control of textural changes, VOCs and fruit ripening by an expression quantitative trait locus located in LG X together with a direct control on them due to genes presented in the introgression (CmTrpD, CmNADH1, CmTCP15, CmGDSL esterase/lipase, and CmHK4-like) and CmNAC18.

[ESP]En el año 2020, la pandemia derivada del virus de la COVID-19 repercutió a nivel mundial sobre las actividades de la población, con restricciones tales como confinamiento domiciliario y limitaciones del tráfico rodado. Como consecuencia de ello, se han obtenido unas condiciones únicas para poder realizar estudios sobre cómo afectan a la contaminación atmosférica y a la calidad del aire las restricciones del tráfico y la actividad industrial a consecuencia del confinamiento. En este trabajo, se evalúa el efecto de las restricciones para contener la pandemia por COVID-19 en los niveles de contaminación atmosférica de la Región de Murcia. Para ello, se han estudiado las concentraciones en aire de los contaminantes atmosféricos NO2, PM10, SO2 y O3, registradas en las estaciones fijas de vigilancia de la calidad del aire (Alcantarilla, La Aljorra, Alumbres, Caravaca de la Cruz, Lorca, Mompeán, San Basilio y el Valle de Escombreras). El estudio ha consistido en comparar las concentraciones registradas durante 2020, dividido en tramos según las restricciones vigentes en cada periodo del año, con las obtenidas en los años anteriores (de 2016 a 2019). Tras el análisis de los datos, se concluye que ha habido una disminución generalizada en el aire de la Región de las concentraciones de NO2 y PM10, que son los dos contaminantes atmosféricos más problemáticos en la actualidad. Respecto al SO2 se observan comportamientos diferentes en función de la localización de la estación de medida. Por último, las concentraciones de ozono disminuyeron en todas las estaciones con excepción de la del Valle de Escombreras. Los resultados ponen de manifiesto el vínculo entre actividad industrial, económica y social y los niveles de contaminación atmosférica, así como la necesidad de cambiar patrones de comportamiento en beneficio de una atmósfera más limpia[ENG]In 2020, the pandemic derived from the COVID-19 virus had a worldwide impact on the activities of the population, with restriction

The rapid evolution of wind energy in reducing CO2 emissions worldwide is undeniable, which is, in fact, expected to continue or even increase its impressive yearly capacity growth. In this regard, optimizing operations and maintenance of wind turbines (WTs) and farms is considered to be one of the options for reducing the levelized cost of electricity of wind energy. This can be achieved by developing innovative condition monitoring methods. To this end, the use of the windowed scalogram difference (WSD) algorithm, based on wavelets, is proposed as an alternative solution, combined with current signature analysis (CSA). The electric generator is one of the major contributors to WT failure rates and downtime, and doubly-fed induction generators (DFIGs) are the dominant technology in variable-speed WTs. In the present work, operational data on an in-service WT DFIG are analyzed over a period of eight months, in contrast to the majority of the studies in this field, which rely on laboratory or simulated data. The evolution of the fault, namely rotor mechanical asymmetry, at an early stage, is analyzed and quantified implementing WSD to the stator current signals, supported by the previous diagnosis achieved through CSA. The combination of CSA and WSD shows strong potential for diagnosing and tracking, respectively, incipient faults in in-service WT DFIGs.

A melon non-climacteric near-isogenic line (NIL) SC10-2 and its parental ‘Piel de Sapo’ (PS) line were studied in two different seasons to analyse the seasonal effects of an introgression (located in LG X) on texture and aroma volatiles at harvest. Several univariate and multivariate statistical techniques were used to determine the association between the aroma volatile levels and differences in melon texture. Three methodologies involving different treatments of null values were applied to analyse the effects of introgression on volatile organic compounds (VOCs). Substitution of the zeros with the minimum value of the same VOC variable per season and line is proposed for the analysis of VOC data. SC10-2 showed higher whole fruit hardness, flesh firmness, and fibrousness, but lower juiciness than PS. One hundred sixteen VOCs were identified to evaluate the introgression effect, in which 60 VOCs were detected in two seasons with very different climatic conditions during fruit set and ripening; twenty-eight VOCs were involved in the differences on aroma production in the comparison of the NIL SC10-2 with PS. The environmental effects were more significant than the introgression effect. The environment particularly affected VOCs rather than textural traits, and at least one potential VOC quantitative trait locus (QTL) located in LG X alone and another interacting with the environment are proposed to affect VOC fruit metabolism.

[SPA] Con el fin de comparar la expresión génica de un melón cerca de la línea isogénica (NIL) SC10-2 y su parental Piel de Sapo (PS) durante la maduración y para comprender los mecanismos de diferenciación, se realizó una secuenciación transcriptoma. Dos genes de CmGGP (GDP-L-galactosa fosforilasa 1) y CmRAP2-11 (factor de transcripción sensible al etileno RAP2-11) mostraron menor expresión relativa en la NIL SC10 -2 versus PS debido a la introgresión en LG X. Sin embargo, no existieron diferencias en expresión de CmAP2-like X1 (factor de transcripción sensible al etileno, similar a AP2 TOE3 isoforma X1). En consecuencia, la expresión de genes que mapearon en el grupo de ligamiento X como un factor de transcripción de respuesta a etileno o del metabolismo del ácido ascórbico estuvieron probablemente asociados con el retraso de maduración. [ENG] The expression of selected genes during ripening was studied considering a melon Near-isogenic Line (NIL) SC10-2 and its parental “Piel de Sapo” (PS). The expression of CmGGP (GDP-L-galactose phosphorylase 1), CmAP2-like X1 (AP2-like ethylene-responsive transcription factor TOE3 isoform X1) and CmRAP2-11 (ethylene-responsive transcription factor RAP2-11) were differentially expressed in the NIL SC10-2 compared with PS. Consequently, expression of genes that mapped in LG X such as one ethylene response transcription factors or ascorbic acid metabolism gene were probably associated with delayed ripening.

The legacy of the mining industry has left a large number of tailing ponds in the Cartagena–La Unión mining district exposed to water and wind erosion, which causes serious environmental and health problems and requires remediation. Before applying any remediation technique, an intensive sampling of the materials infilling the pond is required to determine the geochemistry of the pond, which will condition the remediation process. However, sampling the large number of tailing ponds that compose the district could be expensive. Thus, the main objective of this study is to evaluate the usefulness of electrical resistivity tomography (ERT) as a non-invasive tool to provide an image of spatial subsurface resistivity distribution and its relation to the physicochemical composition of near-surface mine wastes. To achieve this objective, three short ERT profiles were conducted, and 12 samples in each profile were collected at different depths for its geochemical characterization. Several non-linear regression models were fitted to predict physicochemical properties and metal concentrations from electrical resistivity measures. As a result, a high resistivity area was depicted in the ERT profiles G2 and G3, while the low resistivity ERT profile G1 was also obtained in accordance with the site’s surficial characteristics. Relationships among low resistivity values and high salinity, clay content, high metal concentrations, and mobility were established. Specifically, calibrated models were obtained for electrical conductivity, particle sizes of 0.02–50 µm and 50–2000 µm, total Zn and Cd concentration, and bioavailable Ni, Cd, and Fe. The ERT technique was shown to be a useful tool for the approximation of the location and distribution of the highest ranges of fine particle sizes, moisture, and, to a lesser extent, metal accumulation in the near-surface waste materials.

Quality in melons (Cucumis melo L.) is an important criterion for consumer’s acceptance. Like any other fruit, melons development and ripening process are linked to a series of biochemical and physiological changes. The goal of these researches has been focused on determination of the global quality and aroma profile of a non-climacteric near-isogenic line (NIL) SC10-2 of melon developed from the Spanish cultivar T111 (ssp. melo) of the ‘Piel de Sapo’ type (PS) and the Korean accession PI 161375 Songwhan Charmi (ssp. agrestis) (SC), with different texture than its non-climacteric parental PS, in order to map QTLs associated with fruit quality and, particularly, aroma volatiles. A methodology for a consistent study of outliers of non-climacteric melon volatile organic compounds at harvest was reported. For extreme outliers, we proposed the study of compound classes in percentage of total area counts by principal component analysis followed by a further verification with box-whisker plot. The presence of esters usually at higher proportions than expected, or an excess of minority compounds such as ketones, alcohols, terpenes or others are usually a sign of volatile results that can be considered outliers. A comparison was performed in two seasons between the melon near-isogenic line SC10-2 and its parental PS in order to identify the most discriminant flesh aroma volatiles at harvest as potential biomarkers of textural differences (especially flesh firmness) due to introgressions in melon chromosome X, examining seasonal effects on these the former traits. Several univariate and multivariate statistical techniques were used to determine the association between the aroma volatile levels and differences in melon texture. Three methodologies involving different treatments of null values were applied to analyse the effects of introgression on volatile organic compounds (VOCs). Substitution of the zeros with the minimum value of the same VOC variable per season and line is

The increasing integration of photovoltaic (PV) power plants into power systems demands a high accuracy of yield prediction and measurement. With this aim, different global horizontal irradiance (GHI) estimations based on new-generation geostationary satellites have been recently proposed, providing a growing number of solutions and databases, mostly available online, in addition to the many ground-based irradiance data installations currently available. According to the specific literature, there is a lack of agreement in validation strategies for a bankable, satellite-derived irradiance dataset. Moreover, different irradiance data sources are compared in recent contributions based on a diversity of arbitrary metrics. Under this framework, this paper describes a characterization of metrics based on a principal component analysis (PCA) application to classify such metrics, aiming to provide non-redundant and complementary information. Therefore, different groups of metrics are identified by applying the PCA process, allowing us to compare, in a more extensive way, different irradiance data sources and exploring and identifying their differences. The methodology has been evaluated using satellite-based and ground-measured GHI data collected for one year in seven different Spanish locations, with a one-hour sample time. Data characterization, results, and a discussion about the suitability of the proposed methodology are also included in the paper.

Wind power plants are becoming a generally accepted resource in the generation mix of many utilities. At the same time, the size and the power rating of individual wind turbines have increased considerably. Under these circumstances, the sector is increasingly demanding an accurate characterization of vertical wind speed profiles to estimate properly the incoming wind speed at the rotor swept area and, consequently, assess the potential for a wind power plant site. The present paper describes a shape-based clustering characterization and visualization of real vertical wind speed data. The proposed solution allows us to identify the most likely vertical wind speed patterns for a specific location based on real wind speed measurements. Moreover, this clustering approach also provides characterization and classification of such vertical wind profiles. This solution is highly suitable for a large amount of data collected by remote sensing equipment, where wind speed values at different heights within the rotor swept area are available for subsequent analysis. The methodology is based on z-normalization, shape-based distance metric solution and the Ward-hierarchical clustering method. Real vertical wind speed profile data corresponding to a Spanish wind power plant and collected by using a commercialWindcube equipment during several months are used to assess the proposed characterization and clustering process, involving more than 100000 wind speed data values. All analyses have been implemented using open-source R-software. From the results, at least four different vertical wind speed patterns are identified to characterize properly over 90% of the collected wind speed data along the day. Therefore, alternative analytical function criteria should be subsequently proposed for vertical wind speed characterization purposes.

Aleppo pine is the most abundant conifer species in Mediterranean basin. Knowledge of adaptive mechanisms to cope with different environmental stresses simultaneously is necessary to improve its resilience to the predicted climatic changes and anthropogenic stressors, such as heavy metal/metal(loid)s (HMMs) pollution. Here, one year-old needles and rhizosphere soil samples from five mining and non-mining (NM) populations of Aleppo pines grown spontaneously in SE Spain were sampled in two consecutive years during spring and summer. Quantitative determination of a wide suite of edaphic, biochemical, and physiological parameters was performed, including soil physicochemical properties, ionome profile, foliar redox components, primary and secondary metabolites. Mining rhizosphere soils were characterized by elevated contents of HMMs, particularly lead and zinc, and low carbon, nitrogen and potassium levels. Multivariate data analysis based on needle ionome and antioxidative/oxidative parameters revealed a clear distinction between seasons irrespective of the population considered. Spring needles were characterized by higher levels of HMMs, sulfur, glutathione (GSH), proanthocyanidins (PAs), and soluble phenols (TPC), whereas reduced chlorophylls and increased levels of carotenoids, relative water content and K+, Na+ and Cl− typified summer needles. In general mining populations had higher levels of ascorbate, and TPC, and exhibited higher antioxidant activities than the NM population. This could contribute to prevent oxidative injury induced by HMMs. Taken together, results suggest that seasonal factors have a more marked effect on the metabolism of the Aleppo pine populations studied than that exerted by soil conditions. This effect could be mediated by water availability in surface soil layers. If this conclusion is right, predicted rainfall reduction and temperature increase in the Mediterranean basin associated to global climate change would lead to pine needle meta

El principal objetivo de este trabajo es el desarrollo de una metodología para el Diseño Óptimo de Experimentos para experimentos de inactivación isoterma. Para ello, se han definido los siguientes hitos: · Determinación analítica de las funciones de sensibilidad locales para el modelo de Bigelow. · Planteamiento del Diseño Óptimo de Experimentos como un problema de optimización. · Resolución del problema de optimización, evaluando la factibilidad del diseño experimental obtenido. · Definición de restricciones en el problema, de manera que sea realizable en el laboratorio. · Comparación teórica del diseño experimental propuesto con respecto al diseño “clásico” equiespaciado. Se trata de implementar algoritmos matemáticos de diseño óptimo de experimentos dinámicos. Crear una herramienta computacional para llevar a cabo el diseño óptimo de distintos procesos. Aplicar los puntos anteriores a procesos de inactivación microbiana en alimentos. Cuantificar las diferencias entre el enfoque de diseño óptimo y el enfoque tradicional en procesos de seguridad alimentaria.

A methodology for making consistent studies of outliers of non-climacteric melon volatile organic compounds at harvest is reported. The juice was squeezed from the fruit of the ‘Piel de sapo’ cultivar harvested during two consecutive seasons and the aroma volatiles were extracted by headspace solid phase microextraction and measured by gas chromatography coupled to mass-spectrometry. A deconvolution analysis was performed to obtain volatile organic compounds. For multivariate the reliable identification of outliers, compound classes were studied as a percentage of total area counts of the melon compounds identified in the chromatogram by principal component analysis and partial least-squares discriminant analysis, and then verified by correlation analysis, box-whisker plot, and formal tests for univariate outliers. Principal component analysis was the key methodology for selecting outliers in variables that mostly did not follow a normal distribution. The presence of an excess in terms of relative percentage of area and the diversity of minor compounds such as alcohols, terpenes, acids, among others, are usually a sign of anomalous data that can be considered outliers in the aroma of this non-climacteric cultivar. This multivariate approach removed outliers, but kept the variability of aroma among the samples of every cultivar.

The integration of renewables into power systems has led to multiple studies and analysis in terms of grid-power quality, reliability, and/or feasibility. Among different resources to be considered as alternative energy systems, wind and solar emerge as the most mature technologies. With regard to photovoltaic (PV) installations, monitoring problems requires detailed analysis, since solar-radiation fluctuations, soiling on solar panels, or deficiency of PV-panel performance can involve unexpected power-output oscillations and, subsequently, undesirable power-generation oscillations. Under this framework, this paper describes and assesses a wireless low-cost PV-module monitoring system based on open-source solutions. Our proposal allows us to monitor installations at the PV-module level, giving detailed information regarding PV power-plant performance. The proposed monitoring system is based on the IEC-61724 standard requirements, as a flexible and ad hoc solution with relevant connectivity options. Meteorological and electrical data are collected from the developed nodes and available for subsequent analysis. Detailed information of the solution, as well as extensive results collected in Spanish PV power plants connected to the grid, are also included in the paper.

Environmental contamination by hazardous heavy metals/metalloids (metal(loid)s) is growing worldwide. To restrict the migration of toxic contaminants, the establishment of a self-sustainable plant cover is required. Plant growth in multi-polluted soils is a challenging issue not only by metal(loid) toxicities, but also by the co-occurrence of other stressors. Dittrichia viscosa is a pioneer Mediterranean species able to thrive in metal(loid)-enriched tailings in semi-arid areas. The aim of the present work was to examine the metabolic adjustments involved in the acclimation responses of this plant to conditions prevailing in mine-tailings during Mediterranean spring and summer. For this purpose, fully-expanded leaves, and rhizosphere soil of both mining and non-mining populations of D. viscosa grown spontaneously in south-eastern Spain were sampled in two consecutive years. Quantitative analysis of > 50 biochemical, physiological and edaphic parameters were performed, including nutrient status, metal(loid) contents, leaf redox components, primary and secondary metabolites, salicylic acid levels, and soil physicochemical properties. Results showed that mining plants exhibited high foliar Zn/Pb co-accumulation capacity, without substantially affecting their photosynthetic metabolism or nutritional status even in the driest summer period. The comparison of the antioxidative/oxidative profile between mining and non-mining D. viscosa populations revealed no major seasonal changes in the content of primary antioxidants (ascorbate and GSH), or in the levels of ROS. Multivariate analysis showed that phenylalanine ammonia-lyase (PAL) and peroxidase (PRX) activities and soluble and cell wall-bound phenols were potential biomarkers for discriminating between both populations. During the dry season, a marked enhancement in the activity of both PAL and soluble PRX resulted in both a drop in the accumulation of soluble phenols and an increase of the strong metal chelator caffeic

Soil pollution by heavy metals/metalloids (HMMs) is a problem worldwide. To prevent dispersion of contaminated particles by erosion, the maintenance of a vegetative cover is needed. Successful plant establishment in multi-polluted soils can be hampered not only by HMM toxicities, but also by soil nutrient deficiencies and the co-occurrence of abiotic stresses. Some plant species are able to thrive under these multi-stress scenarios often linked to marked fluctuations in environmental factors. This study aimed to investigate the metabolic adjustments involved in Zygophyllum fabago acclimative responses to conditions prevailing in HMM-enriched mine-tailings piles, during Mediterranean spring and summer. To this end, fully expanded leaves, and rhizosphere soil, of three contrasting mining and non-mining populations of Z. fabago grown spontaneously in south-eastern Spain were sampled in two consecutive years. Approximately 50 biochemical, physiological and edaphic parameters were examined, including leaf redox components, primary and secondary metabolites, endogenous levels of salicylic acid, and physicochemical properties of soil (fertility parameters and total concentration of HMMs). Multivariate data analysis showed a clear distinction in antioxidative/oxidative profiles between and within the populations studied. Levels of chlorophylls, proteins and proline characterized control plants whereas antioxidant capacity and C- and S-based antioxidant compounds were biomarkers of mining plants. Seasonal variations were characterized by higher levels of alkaloids and PAL and soluble peroxidase activities in summer, and by soluble sugars and hydroxycinnamic acids in spring irrespective of the population considered. Although the antioxidant systems are subjected to seasonal variations, the way and the intensity with which every population changes its antioxidative/oxidative profile seem to be determined by soil conditions. In short, Z. fabago displays a high physiological pla

Two non-climacteric near-isogenic lines (NILs) of melon (Cucumis melo L.), SC10-2 and SC7-1, containing introgressions of the Korean cultivar \'\'Shongwan Charmi\'\' accession PI161375 (SC) into the Spanish cultivar \'\'Piel de Sapo\'\' (PS) were studied. Data were analysed by different supervised and unsupervised multivariate statistical techniques in order to determine the most discriminant aroma volatiles analyzed by constant flow gas-chromatography mass-spectrometry that could be associated with differences in ripening and flesh firmness in non-climacteric melons. The NILs and the parental showed non-climacteric behaviour during ripening. SC10-2 was harvested at least 7 days later than the control. At harvest, only the NIL SC10-2 showed 65% higher flesh firmness than PS. Whole fruit hardness of SC7-1 was 34% lower than PS. The results obtained by the partial-least square discriminant analysis showed that the aroma better discriminated SC10-2 than SC7-1 from the control, with scarce differences between SC7-1 and PS. The aldehydes (Propanal, 2-methyl-) and the ketones (2-3 Pentanedione) were the most discriminating volatile groups among the NILs studied and PS. Higher levels of several aldehydes (Propanal, 2-methyl-, Benzaldehyde, 2,4-dimethyl-/Benzaldehyde, 3,4-dimethyl-, Butanal, 2-methyl-), not present in PS line, discriminated the NIL SC10-2 from the control PS. Also, SC10-2 displayed lack of some ketones (Acetophenone) and very low presence of alcohols (as for example, Cyclohexanol, 3,5-dimethyl-) compared with PS. The NIL SC7-1 was highlighted by higher relative content in alcohols (1-Octanol, 3-Ethyl-2-heptanol) and one acetate ester (Acetic acid, phenylmethyl ester) than PS and presence of ketones (2-3 Pentanedione, 2-Cyclopenten-1-one, 3,5,5-trimethyl-) that were absent in PS. The results are discussed in terms of the aroma biosynthesis pathways that could be affected by the introgressions.