4 resultados para Cotton production

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


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An important feature in computer systems developed for the agricultural sector is to satisfy the heterogeneity of data generated in different processes. Most problems related with this heterogeneity arise from the lack of standard for different computing solutions proposed. An efficient solution for that is to create a single standard for data exchange. The study on the actual process involved in cotton production was based on a research developed by the Brazilian Agricultural Research Corporation (EMBRAPA) that reports all phases as a result of the compilation of several theoretical and practical researches related to cotton crop. The proposition of a standard starts with the identification of the most important classes of data involved in the process, and includes an ontology that is the systematization of concepts related to the production of cotton fiber and results in a set of classes, relations, functions and instances. The results are used as a reference for the development of computational tools, transforming implicit knowledge into applications that support the knowledge described. This research is based on data from the Midwest of Brazil. The choice of the cotton process as a study case comes from the fact that Brazil is one of the major players and there are several improvements required for system integration in this segment.

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Traceability is a concept that arose from the need for monitoring of production processes, this concept is usually used in sectors related to food production or activities involving some kind of direct risk to people. Agribusiness in the cotton industry does not have a comprehensive infrastructure for all stages of the processes involved in production. Map and define the data to enable traceability of products is synonymous to delegate responsibilities for all involved in the production, the collection of aggregate data on cotton production is done in stages and specific pre-defined since the choice of the variety through the processing, the scope of this article specifically addresses the production of lint cotton. The paper presents a proposal based on service oriented architecture (SOA) for data integration processes in the cotton industry, this proposal provide support for the implementation of platform independent solutions.

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The main objective of the present work was to study nutritive strategies for lessening the CH4 formation associated to ruminant tropical diets. In vitro gas production technique was used for evaluating the effect of tannin-rich plants, essential oils, and biodiesel co-products on CH4 formation in three individual studies and a small chamber system to measure CH4 released by sheep for in vivo studies was developed. Microbial rumen population diversity from in vitro assays was studied using qPCR. In vitro studies with tanniniferous plants, herbal plant essential oils derived from thyme, fennel, ginger, black seed, and Eucalyptus oil (EuO) added to the basal diet and cakes of oleaginous plants (cotton, palm, castor plant, turnip, and lupine), which were included in the basal diet to replace soybean meal, presented significant differences regarding fermentation gas production and CH4 formation. In vivo assays were performed according to the results of the in vitro assays. , when supplemented to a basal diet (Tifton-85 hay sp, corn grain, soybean meal, cotton seed meal, and mineral mixture) fed to adult Santa Ines sheep reduced enteric CH4 emission but the supplementation of the basal diet with EuO did not affect ( > 0.05) methane released. Regarding the microbial studies of rumen population diversity using qPCR with DNA samples collected from the in vitro trials, the results showed shifts in microbial communities of the tannin-rich plants in relation to control plant. This research demonstrated that tannin-rich , essential oil from eucalyptus, and biodiesel co-products either in vitro or in vivo assays showed potential to mitigate CH4 emission in ruminants. The microbial community study suggested that the reduction in CH4 production may be attributed to a decrease in fermentable substrate rather than to a direct effect on methanogenesis.

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The CHAINPlan method developed by Neves (2007) is a practical tool which can be used to construct strategic plans for production chains. A preliminary step in this process includes mapping and quantifying the production chain. We present the results of applying the method to one of the most important agribusiness chains in Brazil-the cotton sector. The Gross Domestic Product for the cotton sector in the 2010-2011 crop year was estimated at nearly $19.2 billion. We show the interconnections between the links in the chain and its ability to generate revenues, taxes and jobs.