6 resultados para Agricultural Science
em University of Queensland eSpace - Australia
Resumo:
The challenge of Research, Development and Extension (R,D&E) is to apply agricultural science to serve the real needs of production systems. The ideal is to have community partnerships involving a variety of stakeholders with equal representation, and a sharing in the design of R, D&E actions. R,D&E policy in Australia is stressing the participation of industry in new projects. The Dairy Research and Development Corporation (DRDC) in Australia, and the Brazilian Agricultural Research Corporation for Dairy (Embrapa Dairy), have developed initiatives to identify priorities for R,D&E design with participation of the industry. However, weaknesses in the methods have been identified. The present study describes the results of a strategy to involve a broader range of stakeholders in the identification of regional dairy industry needs. The findings show that overall communication, finance and marketing as the three major priorities of three study regions, meaning that primary needs for the industry are not in production technologies. This is an apparent contradiction with what some stakeholders considered valuable for dairy farms, which are pasture, genetics and nutrition technologies. The results reflect the large amount of research activity into production technology, and the relative success of R,D&E. However, it is necessary to consider issues beyond production technologies before developing R,D&E projects or presenting technologies.
Resumo:
Allocations of research funds across programs are often made for efficiency reasons. Social science research is shown to have small, lagged but significant effects on U.S. agricultural efficiency when public agricultural R&D and extension are simultaneously taken into account. Farm management and marketing research variables are used to explain variations in estimates of allocative and technical efficiency using a Bayesian approach that incorporates stylized facts concerning lagged research impacts in a way that is less restrictive than popular polynomial distributed lags. Results are reported in terms of means and standard deviations of estimated probability distributions of parameters and long-run total multipliers. Extension is estimated to have a greater impact on both allocative and technical efficiency than either R&D or social science research.
Resumo:
An expanding human population and associated demands for goods and services continues to exert an increasing pressure on ecological systems. Although the rate of expansion of agricultural lands has slowed since 1960, rapid deforestation still occurs in many tropical countries, including Colombia. However, the location and extent of deforestation and associated ecological impacts within tropical countries is often not well known. The primary aim of this study was to obtain an understanding of the spatial patterns of forest conversion for agricultural land uses in Colombia. We modeled native forest conversion in Colombia at regional and national-levels using logistic regression and classification trees. We investigated the impact of ignoring the regional variability of model parameters, and identified biophysical and socioeconomic factors that best explain the current spatial pattern and inter-regional variation in forest cover. We validated our predictions for the Amazon region using MODIS satellite imagery. The regional-level classification tree that accounted for regional heterogeneity had the greatest discrimination ability. Factors related to accessibility (distance to roads and towns) were related to the presence of forest cover, although this relationship varied regionally. In order to identify areas with a high risk of deforestation, we used predictions from the best model, refined by areas with rural population growth rates of > 2%. We ranked forest ecosystem types in terms of levels of threat of conversion. Our results provide useful inputs to planning for biodiversity conservation in Colombia, by identifying areas and ecosystem types that are vulnerable to deforestation. Several of the predicted deforestation hotspots coincide with areas that are outstanding in terms of biodiversity value.