0000000000012404

AUTHOR

J. L. Carrasco-rodriguez

showing 5 related works from this author

Long-term ozone exposure of potato: Free radical content and leaf injury analysed by Q-band ESR spectroscopy and image analysis

2008

This paper presents Q-band electron spin resonance (ESR) studies on free radicals (FR) generated in potato leaves exposed to different O(3) levels in open-top chambers (OTC), together with a quantitative study of the relationship between FR signal intensity and area of potato leaf damage. The advantages of Q-band when compared to X-band ESR spectroscopy are analysed, the main advantage being an absence of overlapping between Mn(II) and FR signals, allowing a quantitative study of FR signal intensity. This study also reports on a graphical method developed to quantitatively measure the damaged area on leaves caused by ozone exposure. Results indicate a direct relationship between FR signal i…

OzoneFree RadicalsChemistryAirRadicalElectron Spin Resonance SpectroscopyAnalytical chemistryGeneral MedicineBiochemistrySignallaw.inventionPlant Leaveschemistry.chemical_compoundOzoneQ bandNuclear magnetic resonancelawContent (measure theory)Image Processing Computer-AssistedOzone exposureSpectroscopyElectron paramagnetic resonanceSolanum tuberosumFree Radical Research
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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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Impact of elevated ozone on chlorophyll a fluorescence in field-grown oat (Avena sativa).

2001

Oat (Avena sativa) plants were grown in the field near the urban area of Valencia, Eastern Spain. The data on air quality showed that ozone was the main phytotoxic pollutant present in ambient air reaching a 7-h mean of 46 nl l(-1) and a maximum hourly peak of 322 nl l(-1). The effect of ambient ozone on PSII activity was examined by measurements of chlorophyll (Chl) a fluorescence. In leaves with visible symptoms, the function of PSII was changed at high actinic irradiances. Nonphotochemical quenching (NPQ) was higher and quantum efficiency of PSII (Phi(PSII)), photochemical quenching (q(p)), quantum efficiency of excitation capture and PSII electron flow (F(v)'/F(m)') were lower. An enhan…

Chlorophyll aOzonePhotoinhibitionPhotosystem IIPlant SciencePhotosynthetic efficiencyPhotosynthesischemistry.chemical_compoundHorticulturechemistryChlorophyllBotanyAgronomy and Crop ScienceChlorophyll fluorescenceEcology Evolution Behavior and SystematicsEnvironmental and experimental botany
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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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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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