Aplicação de Sistema de Informações Geográficas na análise espacial de doenças do milho no Brasil.

This study presents an application of the geographical information system technology on plant disease involving a multidisciplinary teamwork of geoprocessing and physiopathology specialists. The spatial analysis tools in a GIS were used to evaluate the spatial distribution of two diseases of maize in Brazil: polysora rusl caused by Puccinia polysora and tropical rust caused by Physopella zeae. A database of cIimate variables (mean temperature. relative humidity. and leaf wetness duration) of cIimatological normal from 1961-1990 was obtained and then related it to a mathematical model of disease development (polysora rust) and to the cIimate intervals (tropical rust) in order to obtain the maps. The choice of the model or the favorable climate interval is the important chalIenge of the method because the difficulty of adequacy to the spatial and temporal scales for the specific application. The major incidence of both disease occurred in almost alI the North region from January to June. although this region has traditionalIy a low production of maize. Considering the biggest producers regions. for both the diseases, favorable areas are located in part of Mato Grosso, Tocanlins. Minas Gerais; Mato Grosso do Sul. and coastal areas of São Paulo, Paraná, and Santa Catarina. varying among the dilferent months from January to June. The method allowed making an adequate distinction of the states and the months considered.

Método de elaboração de mapas dos cenários climáticos futuros para o Brasil.

Human activities are altering greenhouse gas concentrations in the atmosphere and causing global climate change. The issue of impacts of human-induced climate change has become increasingly important in recent years. The objective of this work was to develop a database of climate information of the future scenarios using a Geographic Information System (GIS) tools. Future scenarios focused on the decades of the 2020?s, 2050?s, and 2080?s (scenarios A2 and B2) were obtained from the General Circulation Models (GCM) available on Data Distribution Centre from the Third Assessment Report (TAR) of Intergovernmental Panel on Climate Change (IPCC). The TAR is compounded by six GCM with different spatial resolutions (ECHAM4:2.8125×2.8125º, HadCM3: 3.75×2.5º, CGCM2: 3.75×3.75º, CSIROMk2b: 5.625×3.214º, and CCSR/NIES: 5.625×5.625º). The mean monthly of the climate variables was obtained by the average from the available models using the GIS spatial analysis tools (arithmetic operation). Maps of mean monthly variables of mean temperature, minimum temperature, maximum temperature, rainfall, relative humidity, and solar radiation were elaborated adopting the spatial resolution of 0.5° X 0.5° latitude and longitude. The method of elaborating maps using GIS tools allowed to evaluate the spatial and distribution of future climate assessments. Nowadays, this database is being used in studies of impacts of climate change on plant disease of Embrapa projects.

Dinâmica do desflorestamento e uso das terras na região dos formadores do rio Xingu.

Because of the occupation occurred in the last thirty years at Xingu river basin, this region has been suffering a large deforestation pressure, especially on its headwaters areas. This study aims to apply GIS techniques to evaluate how land use change has influenced the deforestation dynamics of Xingu water basin in Mato Grosso State. For that, a GIS based study was carried out were the deforestation data for the period between 2000 and 2005 was spatially integrated with settlement areas, indigenous lands, sites of mineral deposits and prospect areas. From this spatially integration, it was possible to analyze statistically how the deforestation has manifested on each kind of occupation, considering the original forest area. The techniques used, including inventory and database organization on GIS environment, and spatial analysis tools made it possible to analyze the deforestation in the Xingu basin in Mato Grosso State between the period of 2000 and 2005, and identify the most affected areas, considering different land uses.

Genetic structure and mating type analysis of the Pyricularia oryzae population causing widespread epidemics in southern Brazil.

Blast is a major disease of rice in Brazil, the largest rice-producing country outside Asia. This study aimed to assess the genetic structure and mating-type frequency in a contemporary Pyricularia oryzae population, which caused widespread epidemics during the 2012/13 season in the Brazilian lowland subtropical region. Symptomatic leaves and panicles were sampled at flooded rice fields in the states of Rio Grande do Sul (RS, 34 fields) and Santa Catarina (SC, 21 fields). The polymorphism at ten simple sequence repeats (SSR or microsatellite) loci and the presence of MAT1-1 or MAT1-2 idiomorphs were assessed in a population comprised of 187 isolates. Only the MAT1-2 idiomorph was found and 162 genotypes were identified by the SSR analysis. A discriminant analysis of principal components (DAPC) of SSR data resolved four genetic groups, which were strongly associated with the cultivar of origin of the isolates. There was high level of genotypic diversity and moderate level of gene diversity regardless whether isolates were grouped in subpopulations based on geographic region, cultivar host or cultivar within region. While regional subpopulations were weakly differentiated, high genetic differentiation was found among subpopulations comprised of isolates from different cultivars. The data suggest that the rice blast pathogen population in southern Brazil is comprised of clonal lineages that are adapting to specific cultivar hosts. Farmers should avoid the use of susceptible cultivars over large areas and breeders should focus at enlarging the genetic basis of new cultivars.

Analysis of spatial variation of tree heights in an urban area using LiDAR data.

Estimating with greater precision and accuracy the height of plants has been a challenge for the scientific community. The objective this study is to evaluate the spatial variation of tree heights at different spatial scales in areas of the city of Recife, Brazil, using LiDAR remote sensing data. The LiDAR data were processed in the QT Modeler (Quick Terrain Modeler v. 8.0.2) software from Applied Imagery. The TreeVaW software was utilized to estimate the heights and crown diameters of trees. The results obtained for tree height were consistent with field measurements.