Seasonal effects on flesh volatile concentrations and texture at harvest in a near-isogenic line of melon with introgression in LG X

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.This study was supported by Ministry of Innovation and Science (now, the Ministry of Economy and Competition) and European Union FEDER funds (AGL2010-20858) and the Fundación Séneca de la Región de Murcia (project 11784/PI/09)

Drivers of and barriers to energy renovation in residential buildings in Spain—the challenge of next generation EU funds for existing buildings

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.This research received no external funding

Vertical wind profile characterization and identification of patterns based on a shape clustering algorithm

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.The authors are grateful for the financial support from the Spanish Ministry of the Economy and Competitiveness and the European Union —ENE2016-78214-C2-2-R—and the Spanish Education, Culture and Sport Ministry —FPU16/042

Seasonal changes in antioxidative/oxidative profile of mining and non-mining populations of Syrian beancaper as determined by soil conditions

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 plasticity that allow it to successfully shift its metabolism to withstand the multiple stresses that plants must cope with in mine tailings piles under Mediterranean climatic conditions.This work was supported by the Ministerio de Ciencia e Innovación [grant number CTM2011-23958]; Ministerio de Ciencia y Tecnología [grant number CGL2006-11569]; and Fundación Séneca [grant number FB/23/FS/02]. AL-O holds a grant from the Ministerio de Educación Cultura y Deporte [grant number AP2012-2559]. Part of this work was carried out at the Instituto de Biotecnología Vegetal, UPCT

Spatio-temporal dynamic clustering modeling for solar irradiance resource assessment

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.These data were obtained from the NASA Langley Research Center (LaRC) POWER Project funded through the NASA Earth Science/Applied Science Program, United States. The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request. This work was partially funded by the research project PID2020–112754GB–I00, financially supported by the Ministerio de Ciencia e Innovación (Spain)

Differential aroma volatiles in non-climacteric near-isogenic lines of melon as biomarkers of differences of flesh firmness at harvest

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

Spatiotemporal sampling design adapted to heterogeneities and real-time observations. Poster

Entropy-based criteria for spatiotemporal sampling design naturally incorporate prior knowledge on structural heterogeneities of processes involved in environmental applications, an important aspect of variation to be considered for risk assessment purposes. Whenever possible, real-time observations must be also integrated for dynamic adaptation of the spatial sampling configurations, eventually under certain restrictions, to account for the actual evolution of the system. In this paper, such information is exploited to redefine, at each time, the region of interest in terms of local density. Procedures are applied to simulated examples where different ranges of memory and spatial dependence, as well as different levels of local variability (fractality), are specified to study the structural influence of the model in the entropy-based spatiotemporal sampling design.This work has been supported in part by projects P05-FQM-00990 of the Andalusian CICYE and MTM2005-08597 of the DGI, Spain

Characterization of vertical wind speed profiles based on Ward's agglomerative clustering algorithm

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.This work was supported in part by the Ministry of Science and Innovation (Spain) (No. PID2021-126082OB-C22)

A characterization of metrics for comparing satellite-based and ground-measured global horizontal irradiance data: a principal component analysis application

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.The paper includes results of activities conducted under the Research Program for Groups of Scientific Excellence at Region of Murcia (Spain), the Seneca Foundation, and the Agency for Science and Technology of the Region of Murcia (Spain). This work was also supported by the Spanish Ministry of Economy and Competitiveness and the European Union–FEDER Funds, ENE2016-78214–C2-1-R

Sensitive parameter analysis for solar irradiance short-term forecasting: application to LoRa-based monitoring technology

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.This research was funded by the Fondo Europeo de Desarrollo Regional/Ministerio de Ciencia e Innovación–Agencia Estatal de Investigación (FEDER/MICINN-AEI), project RTI2018–099139–B–C21