912 resultados para 2016 Crop Condition


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Over the past twenty years, new technologies have required an increasing use of mathematical models in order to understand better the structural behavior: finite element method is the one mostly used. However, the reliability of this method applied to different situations has to be tried each time. Since it is not possible to completely model the reality, different hypothesis must be done: these are the main problems of FE modeling. The following work deals with this problem and tries to figure out a way to identify some of the unknown main parameters of a structure. This main research focuses on a particular path of study and development, but the same concepts can be applied to other objects of research. The main purpose of this work is the identification of unknown boundary conditions of a bridge pier using the data acquired experimentally with field tests and a FEM modal updating process. This work doesn’t want to be new, neither innovative. A lot of work has been done during the past years on this main problem and many solutions have been shown and published. This thesis just want to rework some of the main aspects of the structural optimization process, using a real structure as fitting model.

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Crop models are simplified mathematical representations of the interacting biological and environmental components of the dynamic soil–plant–environment system. Sorghum crop modeling has evolved in parallel with crop modeling capability in general, since its origins in the 1960s and 1970s. Here we briefly review the trajectory in sorghum crop modeling leading to the development of advanced models. We then (i) overview the structure and function of the sorghum model in the Agricultural Production System sIMulator (APSIM) to exemplify advanced modeling concepts that suit both agronomic and breeding applications, (ii) review an example of use of sorghum modeling in supporting agronomic management decisions, (iii) review an example of the use of sorghum modeling in plant breeding, and (iv) consider implications for future roles of sorghum crop modeling. Modeling and simulation provide an avenue to explore consequences of crop management decision options in situations confronted with risks associated with seasonal climate uncertainties. Here we consider the possibility of manipulating planting configuration and density in sorghum as a means to manipulate the productivity–risk trade-off. A simulation analysis of decision options is presented and avenues for its use with decision-makers discussed. Modeling and simulation also provide opportunities to improve breeding efficiency by either dissecting complex traits to more amenable targets for genetics and breeding, or by trait evaluation via phenotypic prediction in target production regions to help prioritize effort and assess breeding strategies. Here we consider studies on the stay-green trait in sorghum, which confers yield advantage in water-limited situations, to exemplify both aspects. The possible future roles of sorghum modeling in agronomy and breeding are discussed as are opportunities related to their synergistic interaction. The potential to add significant value to the revolution in plant breeding associated with genomic technologies is identified as the new modeling frontier.

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O uso e manejo do solo e da cultura são importantes condicionadores da variabilidade de atributos do solo. O trabalho foi desenvolvido em Selvíria (MS), com o objetivo de avaliar a variabilidade espacial do pH, potássio (K), cálcio (Ca), magnésio (Mg) e saturação por bases (V) em Latossolo Vermelho sob diferentes usos e manejos. Os solos foram amostrados em malha, com intervalos regulares de 2 m, perfazendo o total de 64 pontos, nas profundidades de 0,0-0,1 e 0,1-0,2 m, nas seguintes áreas: vegetação natural (Cerrado), plantio direto, plantio convencional e pastagem. As maiores variabilidades, medidas por meio do coeficiente de variação, foram observadas para K, Mg e Ca; o pH apresentou o menor coeficiente de variação nos diferentes usos e manejo do solo, e o atributo V, coeficiente de variação médio. Os sistemas preparo convencional e pastagem apresentaram os menores alcances quando comparado aos sistemas Cerrado e plantio direto.

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Actualmente las organizaciones en su búsqueda por ser ecoeficientes y generar una mejor practica en sus procesos productivos, ha buscado generar herramientas y mediciones que le permitan llevar a cabo una producción más limpia. Es por ello que en su afán han buscado una manera óptima de abordar un tema de preocupación mundial; el manejo del agua. Esta investigación tiene como eje central aterrizar al idioma español, el mandato por el agua un documento dado a conocer por el pacto global, el cual contiene herramientas, métricas y guías sobre el manejo del agua en las organizaciones. Adicional a esto la presente investigación pretende ver su pertinencia al contexto colombiano mediante la aplicación en a una organización.

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Report produced by the The Department of Agriculture and Land Stewardship, Climatology Bureau. Weather report released by the USDA National Agricultural Statistical Service. The report is released weekly from April through October. Formally titled: Iowa Crop and Weather Report

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Report produced by the The Department of Agriculture and Land Stewardship, Climatology Bureau. Weather report released by the USDA National Agricultural Statistical Service. The report is released weekly from April through October. Formally titled: Iowa Crop and Weather Report

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Report produced by the The Department of Agriculture and Land Stewardship, Climatology Bureau. Weather report released by the USDA National Agricultural Statistical Service. The report is released weekly from April through October. Formally titled: Iowa Crop and Weather Report

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Report produced by the The Department of Agriculture and Land Stewardship, Climatology Bureau. Weather report released by the USDA National Agricultural Statistical Service. The report is released weekly from April through October. Formally titled: Iowa Crop and Weather Report

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Report produced by the The Department of Agriculture and Land Stewardship, Climatology Bureau. Weather report released by the USDA National Agricultural Statistical Service. The report is released weekly from April through October. Formally titled: Iowa Crop and Weather Report

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Report produced by the The Department of Agriculture and Land Stewardship, Climatology Bureau. Weather report released by the USDA National Agricultural Statistical Service. The report is released weekly from April through October. Formally titled: Iowa Crop and Weather Report

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Report produced by the The Department of Agriculture and Land Stewardship, Climatology Bureau. Weather report released by the USDA National Agricultural Statistical Service. The report is released weekly from April through October. Formally titled: Iowa Crop and Weather Report

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Report produced by the The Department of Agriculture and Land Stewardship, Climatology Bureau. Weather report released by the USDA National Agricultural Statistical Service. The report is released weekly from April through October. Formally titled: Iowa Crop and Weather Report

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Report produced by the The Department of Agriculture and Land Stewardship, Climatology Bureau. Weather report released by the USDA National Agricultural Statistical Service. The report is released weekly from April through October. Formally titled: Iowa Crop and Weather Report

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Report produced by the The Department of Agriculture and Land Stewardship, Climatology Bureau. Weather report released by the USDA National Agricultural Statistical Service. The report is released weekly from April through October. Formally titled: Iowa Crop and Weather Report