0000000000012406

AUTHOR

S. Del Valle-tascon

showing 8 related works from this author

Impact of Ozone on Crops

2004

Tropospheric O3 has a negative impact on growth, development, and productivity of crops. Effects of O3 have been observed in a wide range of physiological characteristics, such as accelerated senescence, decreased photosynthetic assimilation, decreased productivity, and reduced carbon allocation to roots. Different responses to O3 have been observed in related species and, hence, it is thought that the initial mechanism of O3-induced stress on crops is uniform. A better understanding of the effect of O3 and O3-generated reactive oxygen species is necessary for an insight into the impact of O3 in crops. A great effort must be made in order to decrease the concentrations of O3 air pollution. …

OzoneCrop yieldAir pollutionfood and beveragesAssimilation (biology)medicine.disease_causePhotosynthesisSignal pathwayCropchemistry.chemical_compoundchemistryAgronomymedicineEnvironmental scienceOzone exposure
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Evaluation of remote sensing of vegetation fluorescence by the analysis of diurnal cycles

2008

Chlorophyll fluorescence (ChF) emission is a direct indicator of the photosynthetic activity of vegetation, which is a key parameter of the carbon cycle. This paper analyses chlorophyll fluorescence evolution at leaf level during a complete diurnal cycle in simulated and natural conditions, for two species under different stress conditions. Absolute spectral radiance of the ChF emission is obtained allowing a quantitative derivation of the fluorescence yield of the ChF, which correlates well with established fluorescence instruments. The studied cases show that the ChF emission is mainly driven by the photosynthetic active radiation during the whole cycle, but the fluorescence yield is seve…

chemistry.chemical_compoundchemistryPhotosynthetically active radiationDiurnal cycleChlorophyllRadianceGeneral Earth and Planetary SciencesEnvironmental scienceVegetationPhotosynthesisFluorescenceChlorophyll fluorescenceRemote sensingInternational Journal of Remote Sensing
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Chlorophyll A Fluorescence and Chlorophyll Content in Parmelia Quercina Thalli from a Polluted Region of Northern Castellon (Spain)

1996

AbstractMeasurements of modulated chlorophyll a fluorescence emission and chlorophyll content were made in thalli of Parmelia quercina collected from northern Castellon(Spain). Althoug high air pollution concentrations have been measured in this area, the ratio of variable to maximal fluorescence is unaffected. Following dark-adaptation, the response to irradiance of chlorophyll fluorescence was examined. With respect to control samples, thalli collected in northern Castellon consistently showed differences in fluorescence quenching, the efficiency of excitation energy capture and quenching of basal fluorescence. However, the quantum ield of photochemistry and non-cyclic electron flow were …

Chlorophyll aQuenching (fluorescence)ParmeliabiologyChlorophyll cQuantum yieldbiology.organism_classificationFluorescenceThalluschemistry.chemical_compoundchemistryEnvironmental chemistryBotanyChlorophyll fluorescenceEcology Evolution Behavior and SystematicsThe Lichenologist
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Effective 1-day ahead prediction of hourly surface ozone concentrations in eastern Spain using linear models and neural networks

2002

The aim of this research was to develop pure predictive models in order to provide 24 h advance forecasts of the hourly ozone concentration for the rural site of Carcagente (Valencia, Spain) and the urban sites of Paterna (Valencia, Spain) and Alcoy (Alicante, Spain) over 4 years from 1996 to 1999. The peculiarity of the model presented here is that it uses past and previously predicted information of inputs exclusively, thus being this is the first genuine 24 h advance O3 predictive model with neural networks. We used autoregressive-moving average with exogenous inputs (ARMAX), multilayer perceptrons and FIR neural networks. Five performance measures yield reasonably good results in the th…

Public informationSurface ozoneArtificial neural networkEcological ModelingStatisticsLinear modelEnvironmental scienceSampling (statistics)PerceptronAir quality indexNetwork analysisEcological Modelling
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Biophysical parameter estimation with adaptive Gaussian Processes

2009

We evaluate Gaussian Processes (GPs) for the estimation of biophysical parameters from acquired multispectral data. The standard GP formulation is used, and all hyperparameters (kernel parameters and noise variance) are optimized by maximizing the marginal likelihood. This gives rise to a fully-adaptive GP to data characteristics, both in terms of signal and noise properties. The good numerical results in the estimation of oceanic chlorophyll concentration and leaf membrane state confirm GPs as adequate, alternative non-parametric methods for biophysical parameter estimation. GPs are also analyzed by scrutinizing the predictive variance, the estimated noise variance, and the relevance of ea…

Hyperparameterbusiness.industryEstimation theoryNoise (signal processing)Pattern recognitionVariance (accounting)Marginal likelihoodsymbols.namesakeKernel methodKernel (statistics)symbolsArtificial intelligencebusinessGaussian processAlgorithmMathematics2009 IEEE International Geoscience and Remote Sensing Symposium
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Relationship between Auxin-Dependent Proton Extrusion and Plasmalemma Redox System in Maize Coleoptile Segments

1988

Abraded coleoptile segments reduce ferricyanide utilizing endogenous substrates. The kinetics of ferricyanide reduction shows an initial rapid rate followed by a slow rate of reduction. The duration of the initial phase is about 5 minutes. The slow phase is observed for more than 30 minutes. A Lineweaver-Burk plot of the slow phase was linear and revealed maximum velocity of the reaction of 42 nmols ferricyanide reduced/hour*coleoptile segment and an apparent Km (ferri) of 2.25mM.

chemistry.chemical_classificationchemistry.chemical_compoundColeoptileBiochemistryProtonChemistryAuxinPhase (matter)KineticsBiophysicsExtrusionFerricyanideRedox
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Hexacyanoferrate (III) stimulation of elongation in coleoptile segments fromZea mays L.

1995

The influence of exogenous potassium hexacyanoferrate (III) (HCF III) on elongation of maize (Zea mays L.) coleoptile segments was investigated. Addition of HCF III led to a strong stimulation of growth both in the presence and absence of indole-3-acetic acid (IAA). The magnitude of growth stimulation was dependent on the presence of IAA, HCF III concentration, incubation time, and phase growth. The reduced form, potassium hexacyanoferrate (II), was without effect on growth. In the presence of HCF III, elongation was suppressed when coleoptile segments were treated with N,N′-dicyclohexylcarbodiimide, cycloheximide or atebrine (quinacrine). The addition of HCF III stimulated the IAA-induced …

biologyATPasePotassiumfood and beverageschemistry.chemical_elementStimulationCell BiologyPlant ScienceGeneral MedicineCycloheximideHypocotylchemistry.chemical_compoundColeoptileBiochemistrychemistrybiology.proteinBiophysicsElongationIndole-3-acetic acidProtoplasma
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Unbiased sensitivity analysis and pruning techniques in neural networks for surface ozone modelling

2005

Abstract This paper presents the use of artificial neural networks (ANNs) for surface ozone modelling. Due to the usual non-linear nature of problems in ecology, the use of ANNs has proven to be a common practice in this field. Nevertheless, few efforts have been made to acquire knowledge about the problems by analysing the useful, but often complex, input–output mapping performed by these models. In fact, researchers are not only interested in accurate methods but also in understandable models. In the present paper, we propose a methodology to extract the governing rules of trained ANN which, in turn, yields simplified models by using unbiased sensitivity and pruning techniques. Our propos…

Artificial neural networkOperations researchComputer sciencebusiness.industryEcological ModelingNon linear modelMachine learningcomputer.software_genreField (computer science)chemistry.chemical_compoundSurface ozonechemistrySensitivity (control systems)Tropospheric ozoneArtificial intelligencePruning (decision trees)businesscomputerInterpretabilityEcological Modelling
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