11 resultados para plant disease loss
Resumo:
2008
Resumo:
2008
Resumo:
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.
Resumo:
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.
Resumo:
Risk assessment guidelines for the environmental release of microbial agents are performed in a tiered sequence which includes evaluation of exposure effects on non target organisms. However, it becomes important to verify whether environmental risk assessment from temperate studies is applicable to tropical countries, as Brazil. Pseudomonas putida is a bacteria showing potential to be used for environmental applications as bioremediation and plant disease control. This study investigates the effects of this bacteria exposure on rodents and aquatic organisms (Daphnia similes) that are recommended to be used as non-target organism in environmental risk assessments. Also, the microbial activity in three different soils under P. putida exposure was evaluated. Rats did not show clinical alterations, although the agent was recovered 16 h after the exposure in lung homogenates. The bacteria did not reduce significantly the reproduction and survival of D. similis. The soil enzymatic activities presented fluctuating values after inoculation with bacteria. The measurement of perturbations in soil biochemical characteristics is presented as an alternative way of monitoring the overall effects of the microbial agent to be introduced even in first stage (Tier I) of the risk assessment in tropical ecosystems.
Resumo:
2016
Resumo:
2016
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The aim of this study was to assess the organic matter changes in quantity and quality, particularly of the humic fraction in the surface layer (0?20 cm), of a Typic Plinthustalf soil under different management of plant mixtures used as green manure for mango (Mangifera indica L.) crops. The plant mixtures, which were seeded between rows of mango trees, were formed by two groups of leguminous and non -leguminous plants. Prior to sowing, seeds were combined in different proportions and compositions constituting the following treatments: 100% non-leguminous species (NL); 100% leguminous species (L); 75% L and 25% NL; 50% L and 50% NL; 25% L and 75% NL; and 100% spontaneous vegetation, considered a control. The plant mixtures that grew between rows of mango trees caused changes in the chemical composition of the soil organic matter, especially for the treatments 50% L and 50% NL and 25% L and 75% NL, which increased the content of humic substances in the soil organic matter. However, the treatment 25% L and 75% NL was best at minimising loss of total organic carbon from the soil. The humic acids studied have mostly aliphatic characteristics, showing large amounts of carboxylic and nitrogen groups and indicating that most of the organic carbon was formed by humic substances, with fulvic acid dominating among the alkali soluble fractions.
Resumo:
The common bean cultivar with carioca grain type, BRSMG Uai, is recommended for cultivation in Minas Gerais and stands out for its upright plant architecture, which facilitates cultivation and mechanical harvesting. This cultivar has high yield potential and is resistant to the major races of anthracnose that occur in region.
Resumo:
Dynamic global vegetation models (DGVMs) simulate surface processes such as the transfer of energy, water, CO2, and momentum between the terrestrial surface and the atmosphere, biogeochemical cycles, carbon assimilation by vegetation, phenology, and land use change in scenarios of varying atmospheric CO2 concentrations. DGVMs increase the complexity and the Earth system representation when they are coupled with atmospheric global circulation models (AGCMs) or climate models. However, plant physiological processes are still a major source of uncertainty in DGVMs. The maximum velocity of carboxylation (Vcmax), for example, has a direct impact over productivity in the models. This parameter is often underestimated or imprecisely defined for the various plant functional types (PFTs) and ecosystems. Vcmax is directly related to photosynthesis acclimation (loss of response to elevated CO2), a widely known phenomenon that usually occurs when plants are subjected to elevated atmospheric CO2 and might affect productivity estimation in DGVMs. Despite this, current models have improved substantially, compared to earlier models which had a rudimentary and very simple representation of vegetation?atmosphere interactions. In this paper, we describe this evolution through generations of models and the main events that contributed to their improvements until the current state-of-the-art class of models. Also, we describe some main challenges for further improvements to DGVMs.
Resumo:
2016