Economical Evaluation of Reduced Herbicide Doses Application Rates to Control Phalaris brachystachys (Short-Spiked Canary Grass) in a Biennial Wheat-Sunflower Rotation in Mediterranean Dryland: A Modelling Approach.

Phalaris brachystachys (short-spiked canary grass) is considered to be among the most troublesome cereal weeds in Mediterranean areas. A bioeconomic model, based on population dynamics, competition and economic sub-models, was developed to simulate the long-term economic consequence of using herbicide-based strategies: no herbicide application, full herbicide dose (standard rate) and two reduced dose rates (75 and 50% of the standard rate) to control P. brachystachys in a biennial wheat-sunflower rotation. Simulation results indicated that only herbicide application at a full dose (90% control) and 3/4 dose (80% control) produced positive economic results, with the full dose being the best strategy (EUR 98.65 ha-1 year-1). A sensitivity analysis showed that the economic outcome, in terms of annualized net return, was strongly influenced by changes in yield, price, and fixed costs. In addition, the annualized net return was more sensitive to parameter changes at reduced herbicide doses than at full rate. In the wheat-sunflower rotation system, the application of the full dose of herbicide was the most economical and stable strategy in the long-term. Reduced doses are not a recommended option from an economic point of view. Bioeconomic models provide practical insight into different management approaches for effective weed control.

Regions of homozygosity identified by oligonucleotide SNP arrays: evaluating the incidence and clinical utility.

Copy neutral segments with allelic homozygosity, also known as regions of homozygosity (ROHs), are frequently identified in cases interrogated by oligonucleotide single-nucleotide polymorphism (oligo-SNP) microarrays. Presence of ROHs may be because of parental relatedness, chromosomal recombination or rearrangements and provides important clues regarding ancestral homozygosity, consanguinity or uniparental disomy. In this study of 14 574 consecutive cases, 832 (6%) were found to harbor one or more ROHs over 10 Mb, of which 651 cases (78%) had multiple ROHs, likely because of identity by descent (IBD), and 181 cases (22%) with ROHs involving a single chromosome. Parental relatedness was predicted to be first degree or closer in 5%, second in 9% and third in 19%. Of the 181 cases, 19 had ROHs for a whole chromosome revealing uniparental isodisomy (isoUPD). In all, 25 cases had significant ROHs involving a single chromosome; 5 cases were molecularly confirmed to have a mixed iso- and heteroUPD15 and 1 case each with segmental UPD9pat and segmental UPD22mat; 17 cases were suspected to have a mixed iso- and heteroUPD including 2 cases with small supernumerary marker and 2 cases with mosaic trisomy. For chromosome 15, 12 (92%) of 13 molecularly studied cases had either Prader-Willi or Angelman syndrome. Autosomal recessive disorders were confirmed in seven of nine cases from eight families because of the finding of suspected gene within a ROH. This study demonstrates that ROHs are much more frequent than previously recognized and often reflect parental relatedness, ascertain autosomal recessive diseases or unravel UPD in many cases.

Clasificación orientada a objetos en fotografías aéreas digitales para la discriminación de usos del suelo / Object-based classification in aereal digital photography for land-use discrimination / Clasificação orientada a objetos em fotografias aéreas digitais para a discriminação de usos do solo

Las técnicas de clasificación tradicionales, basadas en rasgos de la imagen a nivel de píxel, presentan ciertas limitaciones, como lo son la aparición de un característico efecto "sal y pimienta" o su reducida capacidad para extraer objetos de interés. Éstas resultan especialmente problemáticas al aplicarse en imágenes de moderada o alta resolución. Una alternativa a dichos sistemas de clasificación pasa por un proceso previo de segmentación de la imagen. De esta forma se permite el trabajo con la imagen a nivel de objeto, lo cual amplía notablemente la cantidad de información que se puede extraer de la misma. En el presente estudio, el objetivo principal es obtener una clasificación digital de la interfase urbano forestal que pueda ser usada por los servicios contra incendios forestales. Para ello, se ha segmentado y clasificado una imagen aérea digital del sensor DMC, empleando el software eCognition, donde la formación de objetos tiene lugar de forma que la homogeneidad interna se mantiene constante. Los objetos resultantes sirven de base para la posterior clasificación. Se utilizaron fotografías aéreas digitales y datos de 350 parcelas en la provincia de Granada, España, para validar las clasificaciones, consiguiendo una precisión total del 90% y un excelente estadístico Kappa (85%) para la clasificación orientada a objetos.

Traditional classification techniques, basically pixel-based approaches, are limited. Typically, they produce a characteristic "salt and pepper" effect, and are unable to extract objects of interest. These techniques have considerable difficulties in dealing with the rich information content of medium and high-resolution images. One alternative to these classification systems can be a previous segmentation of the image to be classified. In this way, object-based classification can be performed so that a significant increase on the information that can be extracted is obtained. In the present work, the aim is to obtain a digital classification of wilderness-urban interface areas that can be used by fire management services. To this end, a digital aerial image provided by the DMC sensor was segmented and classified using eCognition software, which allows homogeneous image object extraction. The meaningful image objects obtained were then used for the classification. Segmentation before classification worked out as an efficient image analysis technique, overcoming traditional approaches limitations. Digital aerial photographs and data of 350 plots in Granada, Spain, were used to validate the classifications obtained; the overall classification accuracy of 90% and an excellent Kappa statistic (85%) for the object-based classification, proved the validity of this method.

As técnicas de clasificação tradicionais, baseadas em traços da imagen a nível de pixel, apresentam certas limitações, como são a aparição de um característico efeito "sal e pimenta" ou sua reduzida capacidade para extrair objetos de interesse. Estas resultam especialmente problemáticas ao serem aplicadas em imagens de moderada ou alta resolução. Uma alternativa a ditos sistemas de clasificação passa por um processo prévio de segmentação da imagem. Desta forma se permite o trabalho com a imagem a nível de objeto, o qual amplia notavelmente a quantidade de informação que pode ser extraida da mesma. No presente estudo, o objetivo principal é o de obter uma classificação digital da interfase urbano- florestal que possa ser usada pelos serviços contra incêndios florestais. Para isto, tem sido segmentada e classificada uma imagem aérea digital do sensor DMC, empregando o software eCognition, onde a formação de objetos tem lugar de forma que a homogeneidade interna se mantêm constante. Os objetos resultantes servem de base para posterior classificação. Utilizaram-se fotografias aéreas digitais e dados de 350 lotes na província de Granada, Espanha, para validar as classificações, conseguindo uma precisão total de 90% e uma excelente estatística Kappa (85%) para a classificação orientada a objetos.