University of Extremadura

About: University of Extremadura is a education organization based out in Badajoz, Spain. It is known for research contribution in the topics: Population & Hyperspectral imaging. The organization has 7856 authors who have published 18299 publications receiving 396126 citations. The organization is also known as: Universidad de Extremadura.

Plant functional traits and canopy structure control the relationship between photosynthetic CO2 uptake and far-red sun-induced fluorescence in a Mediterranean grassland under different nutrient availability

Abstract: Summary Sun-induced fluorescence (SIF) in the far-red region provides a new noninvasive measurement approach that has the potential to quantify dynamic changes in light-use efficiency and gross primary production (GPP). However, the mechanistic link between GPP and SIF is not completely understood. We analyzed the structural and functional factors controlling the emission of SIF at 760 nm (F760) in a Mediterranean grassland manipulated with nutrient addition of nitrogen (N), phosphorous (P) or nitrogen–phosphorous (NP). Using the soil–canopy observation of photosynthesis and energy (SCOPE) model, we investigated how nutrient-induced changes in canopy structure (i.e. changes in plant forms abundance that influence leaf inclination distribution function, LIDF) and functional traits (e.g. N content in dry mass of leaves, N%, Chlorophyll a+b concentration (Cab) and maximum carboxylation capacity (Vcmax)) affected the observed linear relationship between F760 and GPP. We conclude that the addition of nutrients imposed a change in the abundance of different plant forms and biochemistry of the canopy that controls F760. Changes in canopy structure mainly control the GPP–F760 relationship, with a secondary effect of Cab and Vcmax. In order to exploit F760 data to model GPP at the global/regional scale, canopy structural variability, biodiversity and functional traits are important factors that have to be considered.

Treatment of olive oil mill wastewater by Fenton's reagent.

Abstract: Wastewater from olive oil mills has been treated by means of the Fe(II)/H2O2 system (Fenton's reagent). Typical operating variables such as reagent concentration (CH2O2 = 1.0−0.2 M; CFe(II) = 0.01−0.1 M) and temperature (T = 293−323 K) exerted a positive influence on the chemical oxygen demand and total carbon removal. The optimum working pH was found to be in the range 2.5−3.0. The exothermic nature of the process involved a significant increase of the temperature of the reaction media. The process was well simulated by a semiempirical reaction mechanism based on the classic Fenton chemistry. From the model, the reaction between ferric iron and hydrogen peroxide [k = 1.8 × 1015 exp((−12577 ± 1248)/T)] was suggested to be the controlling step of the system. Also, the simultaneous inefficient decomposition of hydrogen peroxide [k = 6.3 × 1012 exp((−11987 ± 2414)/T)] into water and oxygen was believed to play an important role in the process. On the basis of stoichiometric calculations for hydrogen peroxide...

Parallel Hyperspectral Image and Signal Processing [Applications Corner]

Abstract: Remotely sensed hyperspectral imaging instruments are capable of collecting hundreds of images corresponding to different wave length channels for the same area on the surface of the Earth. For instance, NASA is continuously gathering high dimensional image data with instruments such as the Jet Propulsion Laboratory's Airborne Visible-Infrared Imaging Spectrometer (AVIRIS). This advanced sensor for Earth observation records the visible and near-infrared spectrum of the reflected light using more than 200 spectral bands, thus producing a stack of images in which each pixel (vector) is represented by a spectral signal that uniquely characterizes the underlying objects. The resulting data volume typically comprises several gigabytes per flight. In this article, we describe the state of the art in the devel opment and application of image and signal processing techniques for advanced information extraction from hyperspectral data. The article also describes new trends for efficient pro cessing of such data using parallel and distributed processing techniques in the context of time-critical applications.