Prediction of crude protein and classification of the growth stage of wheat plant samples from NIR spectra

Near-infrared spectroscopy (NIRS) was used to analyse the crude protein content of dried and milled samples of wheat and to discriminate samples according to their stage of growth. A calibration set of 72 samples from three growth stages of wheat (tillering, heading and harvest) and a validation set of 28 samples was collected for this purpose. Principal components analysis (PCA) of the calibration set discriminated groups of samples according to the growth stage of the wheat. Based on these differences, a classification procedure (SIMCA) showed a very accurate classification of the validation set samples : all of them were successfully classified in each group using this procedure when both the residual and the leverage were used in the classification criteria. Looking only at the residuals all the samples were also correctly classified except one of tillering stage that was assigned to both tillering and heading stages. Finally, the determination of the crude protein content of these samples was considered in two ways: building up a global model for all the growth stages, and building up local models for each stage, separately. The best prediction results for crude protein were obtained using a global model for samples in the two first growth stages (tillering and heading), and using a local model for the harvest stage samples.

Dynamic drag modeling of submerged aquatic vegetation canopy flows

Vegetation has a profound effect on flow and sediment transport processes in natural rivers, by increasing both skin friction and form drag. The increase in drag introduces a drag discontinuity between the in-canopy flow and the flow above, which leads to the development of an inflection point in the velocity profile, resembling a free shear layer. Therefore, drag acts as the primary driver for the entire canopy system. Most current numerical hydraulic models which incorporate vegetation rely either on simple, static plant forms, or canopy-scaled drag terms. However, it is suggested that these are insufficient as vegetation canopies represent complex, dynamic, porous blockages within the flow, which are subject to spatially and temporally dynamic drag forces. Here we present a dynamic drag methodology within a CFD framework. Preliminary results for a benchmark cylinder case highlight the accuracy of the method, and suggest its applicability to more complex cases.

Testing the influence of topography and material properties on catchment-scale soil moisture patterns using remotely sensed vegetation patterns in a humid temperate catchment, northern Britain

In order to evaluate the relationship between the apparent complexity of hillslope soil moisture and the emergent patterns of catchment hydrological behaviour and water quality, we need fine-resolution catchment-wide data on soil moisture characteristics. This study proposes a methodology whereby vegetation patterns obtained from high-resolution orthorectified aerial photographs are used as an indicator of soil moisture characteristics. This enables us to examine a set of hypotheses regarding what drives the spatial patterns of soil moisture at the catchment scale (material properties or topography). We find that the pattern of Juncus effusus vegetation is controlled largely by topography and mediated by the catchment's material properties. Characterizing topography using the topographic index adds value to the soil moisture predictions relative to slope or upslope contributing area (UCA). However, these predictions depart from the observed soil moisture patterns at very steep slopes or low UCAs. Copyright (c) 2012 John Wiley & Sons, Ltd.

Integrating defeasible argumentation with fuzzy ART neural networks for pattern classification

Many classification systems rely on clustering techniques in which a collection of training examples is provided as an input, and a number of clusters c1,...cm modelling some concept C results as an output, such that every cluster ci is labelled as positive or negative. Given a new, unlabelled instance enew, the above classification is used to determine to which particular cluster ci this new instance belongs. In such a setting clusters can overlap, and a new unlabelled instance can be assigned to more than one cluster with conflicting labels. In the literature, such a case is usually solved non-deterministically by making a random choice. This paper presents a novel, hybrid approach to solve this situation by combining a neural network for classification along with a defeasible argumentation framework which models preference criteria for performing clustering.

Aplicación de imágenes radar de satélite a la cartografía de la vegetación en zonas boreales

El presente estudio se enmarca en el proyecto europeo SIBERIA. Trata de explorar el uso de imágenes radar de satélite (ERS y JERS) para la actualización de la cartografía de vegetación de zonas boreales. Se dispone de 8 imágenes de amplitud y coherencia tomadas en 1998, así como de un inventario de vegetación georreferenciado de dos pequeñas zonas. Se proponen tres tipos de clasificaciones supervisadas por el método de máxima verosimilitud. La primera con las imágenes de satélite, la segunda añadiendo algunas imágenes texturales, y la tercera utilizando sólo las imágenes de los componentes principales más significativos. Se siguen los criterios establecidos en el proyecto SIBERIA para la obtención de áreas de entrenamiento. Se propone una doble validación, por una parte vía matrices de confusión a partir de áreas de verdad-terreno obtenidas por el mismo método que las áreas de entrenamiento, y por otra parte contrastando y correlacionando las clasificaciones con los parámetros de inventario disponibles para dos pequeñas áreas de verdad-terreno. Los resultados indican una sensible mejora en la clasificación con la incorporación de imágenes texturales (la precisión aumenta de un 66% a un 75%), y señalan el parámetro biomasa como el mejor correlacionado con las clasificaciones derivadas (coeficiente de correlación r de hasta 0,49). Diferentes fuentes de error permiten augurar un margen de mejora para posteriores estudios.

Protocolo para la zonificación intraparcelaria de la viña para vendimia selectiva a partir de imágenes multiespectratrales

En este trabajo se presenta un protocolo para la zonificación intraparcelaria de la viña con la finalidad de vendimia selectiva. Se basa en la adquisición de una imagen multiespectral detallada en el momento del envero, a partir de la cual se obtiene el índice de vegetación de la diferencia normalizada (NDVI). Este índice se clasifica en áreas de vigor alto y bajo mediante un proceso de clasificación no supervisada (algoritmo ISODATA). Las zonas resultantes se generalizan y se transfieren al monitor de cosecha de una máquina vendimiadora para realizar la recolección selectiva. La uva recolectada según este protocolo en parcelas control ha mostrado diferenciación en cuanto a parámetros de calidad como el pH, la acidez total, el contenido de polifenoles y el color. La imagen multiespectral utilizada fue adquirida por el satélite Quickbird-2. Los datos de calidad de la uva fueron muestreados según una malla regular de 5 filas por 10 cepas, procediendo a un test estadístico de rangos múltiples para analizar la separación de medias de las variables analizadas en cada zona de NDVI.

Evidence-based provisional clinical classification criteria for autoinflammatory periodic fevers.

The objective of this work was to develop and validate a set of clinical criteria for the classification of patients affected by periodic fevers. Patients with inherited periodic fevers (familial Mediterranean fever (FMF); mevalonate kinase deficiency (MKD); tumour necrosis factor receptor-associated periodic fever syndrome (TRAPS); cryopyrin-associated periodic syndromes (CAPS)) enrolled in the Eurofever Registry up until March 2013 were evaluated. Patients with periodic fever, aphthosis, pharyngitis and adenitis (PFAPA) syndrome were used as negative controls. For each genetic disease, patients were considered to be 'gold standard' on the basis of the presence of a confirmatory genetic analysis. Clinical criteria were formulated on the basis of univariate and multivariate analysis in an initial group of patients (training set) and validated in an independent set of patients (validation set). A total of 1215 consecutive patients with periodic fevers were identified, and 518 gold standard patients (291 FMF, 74 MKD, 86 TRAPS, 67 CAPS) and 199 patients with PFAPA as disease controls were evaluated. The univariate and multivariate analyses identified a number of clinical variables that correlated independently with each disease, and four provisional classification scores were created. Cut-off values of the classification scores were chosen using receiver operating characteristic curve analysis as those giving the highest sensitivity and specificity. The classification scores were then tested in an independent set of patients (validation set) with an area under the curve of 0.98 for FMF, 0.95 for TRAPS, 0.96 for MKD, and 0.99 for CAPS. In conclusion, evidence-based provisional clinical criteria with high sensitivity and specificity for the clinical classification of patients with inherited periodic fevers have been developed.

Using vegetation to characterize the avalanche to Canal del Roc Roig, Vall de Núria (Eastern Pyrenees, Spain)

Avalanche hazard maps of high accuracy are difficult to produce. For land-use planning and management purposes, a good knowledge of extreme run-out zones and frequencies of avalanches is required. In the present work, vegetation recognition (especially focused on Pinus uncinata trees) and dendrochronological techniques are used to characterize avalanches that have occurred in historical times, helping to determine both the extent of large or extreme avalanches and their occurrence in time. Vegetation was studied at the Canal del Roc Roig (eastern Pyrenees, Spain) avalanche path. The avalanches descending this path affect the railway that reaches the Vall de Núria resort and the run-up to the opposite slope. During winter 1996, two important avalanches affecting this path were well documented. These are compared with the results of the vegetation study, consisting of an inventory of flora, the recording of vegetation damages along eight transverse profiles at different altitudes on the path and a dendrochronological sampling campaign. The data obtained contributed to a characterization of the predominant snow accumulation in the starting zone, the 1996 avalanches and the range of frequencies of large avalanches. Also, traces of avalanches that increase the path mapped in the avalanche paths map published by the Institut Cartogràfic de Catalunya in 2000 were identified, improving the initial existing information.

Using vegetation to characterize the avalanche to Canal del Roc Roig, Vall de Núria (Eastern Pyrenees, Spain)

Avalanche hazard maps of high accuracy are difficult to produce. For land-use planning and management purposes, a good knowledge of extreme run-out zones and frequencies of avalanches is required. In the present work, vegetation recognition (especially focused on Pinus uncinata trees) and dendrochronological techniques are used to characterize avalanches that have occurred in historical times, helping to determine both the extent of large or extreme avalanches and their occurrence in time. Vegetation was studied at the Canal del Roc Roig (eastern Pyrenees, Spain) avalanche path. The avalanches descending this path affect the railway that reaches the Vall de Núria resort and the run-up to the opposite slope. During winter 1996, two important avalanches affecting this path were well documented. These are compared with the results of the vegetation study, consisting of an inventory of flora, the recording of vegetation damages along eight transverse profiles at different altitudes on the path and a dendrochronological sampling campaign. The data obtained contributed to a characterization of the predominant snow accumulation in the starting zone, the 1996 avalanches and the range of frequencies of large avalanches. Also, traces of avalanches that increase the path mapped in the avalanche paths map published by the Institut Cartogràfic de Catalunya in 2000 were identified, improving the initial existing information.