39 resultados para Technical translation

em CentAUR: Central Archive University of Reading - UK


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Tremendous progress in plant proteomics driven by mass spectrometry (MS) techniques has been made since 2000 when few proteomics reports were published and plant proteomics was in its infancy. These achievements include the refinement of existing techniques and the search for new techniques to address food security, safety, and health issues. It is projected that in 2050, the world’s population will reach 9–12 billion people demanding a food production increase of 34–70% (FAO, 2009) from today’s food production. Provision of food in a sustainable and environmentally committed manner for such a demand without threatening natural resources, requires that agricultural production increases significantly and that postharvest handling and food manufacturing systems become more efficient requiring lower energy expenditure, a decrease in postharvest losses, less waste generation and food with longer shelf life. There is also a need to look for alternative protein sources to animal based (i.e., plant based) to be able to fulfill the increase in protein demands by 2050. Thus, plant biology has a critical role to play as a science capable of addressing such challenges. In this review, we discuss proteomics especially MS, as a platform, being utilized in plant biology research for the past 10 years having the potential to expedite the process of understanding plant biology for human benefits. The increasing application of proteomics technologies in food security, analysis, and safety is emphasized in this review. But, we are aware that no unique approach/technology is capable to address the global food issues. Proteomics-generated information/resources must be integrated and correlated with other omics-based approaches, information, and conventional programs to ensure sufficient food and resources for human development now and in the future.

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A method is proposed to determine the extent of degradation in the rumen involving a two-stage mathematical modeling process. In the first stage, a statistical model shifts (or maps) the gas accumulation profile obtained using a fecal inoculum to a ruminal gas profile. Then, a kinetic model determines the extent of degradation in the rumen from the shifted profile. The kinetic model is presented as a generalized mathematical function, allowing any one of a number of alternative equation forms to be selected. This method might allow the gas production technique to become an approach for determining extent of degradation in the rumen, decreasing the need for surgically modified animals while still maintaining the link with the animal. Further research is needed before the proposed methodology can be used as a standard method across a range of feeds.

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Technical efficiency is estimated and examined for a cross-section of Australian dairy farms using various frontier methodologies; Bayesian and Classical stochastic frontiers, and Data Envelopment Analysis. The results indicate technical inefficiency is present in the sample data. Also identified are statistical differences between the point estimates of technical efficiency generated by the various methodologies. However, the rank of farm level technical efficiency is statistically invariant to the estimation technique employed. Finally, when confidence/credible intervals of technical efficiency are compared significant overlap is found for many of the farms' intervals for all frontier methods employed. The results indicate that the choice of estimation methodology may matter, but the explanatory power of all frontier methods is significantly weaker when interval estimate of technical efficiency is examined.

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Despite record national output in the early years of this decade there is widespread concern that rice yields in Bangladesh are below those attainable, and that given future population growth this may constrain achievement of food security and poverty reduction objectives. A frequent response to this problem is that farmers could close the gap between actual farm yields and potential yields identified in field trials if farmers who are technically inefficient could improve their current farming practices. This paper estimates and explains technical efficiency for a sample of rice farmers in Bangladesh employing Bayesian methods. The results provide insights into the distribution of technical efficiency and identify important influences on rice growing.

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We evaluate the profitability and technical efficiency of aquaculture in the Philippines. Farm-level data are used to compare two production systems corresponding to the intensive monoculture of tilapia in freshwater ponds and the extensive polyculture of shrimps and fish in brackish water ponds. Both activities are very lucrative, with brackish water aquaculture achieving the higher level of profit per farm. Stochastic frontier production functions reveal that technical efficiency is low in brackish water aquaculture, with a mean of 53%, explained primarily by the operator's experience and by the frequency of his visits to the farm. In freshwater aquaculture, the farms achieve a mean efficiency level of 83%. The results suggest that the provision of extension services to brackish water fish farms might be a cost-effective way of increasing production and productivity in that sector. By contrast, technological change will have to be the driving force of future productivity growth in freshwater aquaculture.

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The paper provides one of the first applications of the double bootstrap procedure (Simar and Wilson 2007) in a two-stage estimation of the effect of environmental variables on non-parametric estimates of technical efficiency. This procedure enables consistent inference within models explaining efficiency scores, while simultaneously producing standard errors and confidence intervals for these efficiency scores. The application is to 88 livestock and 256 crop farms in the Czech Republic, split into individual and corporate.

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The paper provides one of the first applications of the double bootstrap procedure (Simar and Wilson 2007) in a two-stage estimation of the effect of environmental variables on non-parametric estimates of technical efficiency. This procedure enables consistent inference within models explaining efficiency scores, while simultaneously producing standard errors and confidence intervals for these efficiency scores. The application is to 88 livestock and 256 crop farms in the Czech Republic, split into individual and corporate.