Energy supply, even if modest and close to resting energy requirements appears to be positively associated with hospital discharge. However, disease severity was the main negative factor on outcome and also had a negative effect on energy intake, making it difficult to separate the effects of both factors when interpreting hospital discharge. Thin animals with low BCS had greater mortality.
Two experiments were conducted to develop and evaluate a model to estimate ME requirements and determine Gompertz growth parameters for broilers. The first experiment was conducted to determine maintenance energy requirements and the efficiencies of energy utilization for fat and protein deposition. Maintenance ME (MEm) requirements were estimated to be 157.8, 112.1, and 127.2 kcal of ME/kg(0.75) per day for broilers at 13, 23, and 32 degrees C, respectively. Environmental temperature (T) had a quadratic effect on maintenance requirements (MEm = 307.87 - 15.63T + 0.3105T(2); r2= 0.93). Energy requirements for fat and protein deposition were estimated to be 13.52 and 12.59 kcal of ME/g, respectively. Based on these coefficients, a model was developed to calculate daily ME requirements: ME = BW(0.75) (307.87 - 15.63T + 0.3105 T2) + 13.52 Gf + 12.59 Gp. This model considers live BW, the effects of environmental temperature, and fractional fat (Gf) and protein (Gp) deposition. The second experiment was carried out to estimate the growth parameters of Ross broilers and to collect data to evaluate the ME requirement model proposed. Live BW, empty feather-free carcass, weight of the feathers, and carcass chemical compositions were analyzed until 16 wk of age. Parameters of Gompertz curves for each component were estimated. Males had higher growth potential and higher capacity to deposit nutrients than females, except for fat deposition. Data of BW and body composition collected in this experiment were fitted into the energy model proposed herein and the equations described by Emmans (1989) and Chwalibog (1991). The daily ME requirements estimated by the model determined in this study were closer to the ME intake observed in this trial compared with other models.
RESUMOO objetivo deste trabalho é dar uma contribuição ao estudo das condições climáticas do Estado do Rio de Janeiro, visando a uma melhor Classificação Climática por meio da identificação de regiões homogêneas em precipitação. Para isto foram utilizadas médias mensais da precipitação de 48 estações meteorológicas, em um período de 30 anos . A análise hierárquica de agrupamento, a orografia e a proximidade do mar, mostraram que o Estado do Rio de Janeiro pode ser dividido, quanto à precipitação, em seis regiões pluviometricamente homogêneas o que possibilitou classificar as estações meteorológicas pelo método de classificação não hierárquica k-means. A região norte do Estado, com precipitações anuais em torno de 870 mm é a mais seca, e a região da encosta sul da Serra do Mar, com 2020 mm, é a mais chuvosa. Mas, em ambas as regiões, os valores da precipitação da estação chuvosa representam em torno de 70% dos totais anuais. Palavras-chave: regiões homogêneas, análise de agrupamento, precipitação mensal ABSTRACT: IDENTIFICATION OF HOMOGENEOUS PRECIPITATION REGIONS IN THE STATE OF RIO DE JANEIRO USING MONTHLY MEANS.The aim of this work is to give a contribution to the study of climatic conditions for Rio de Janeiro State towards a better Climatic Classification by identifying homogeneous precipitation regions. Monthly mean rainfall for a period of thirty years , from 48 meteorological stations, were used. Cluster hierarchical analysis, orography and proximity to the ocean showed that Rio de Janeiro State could be divided into six homogeneous regions according to its rainfall distribution, which allowed the classification of meteorological stations by nonhierarchical K-means method. The north region of the State is the driest one, with annual rainfall around 870 mm. The south hillside of Serra do Mar is the wettest. In both regions, the precipitation during the rainy season represents around 70% of the total annual rainfall. Keywords: homogeneous regions, cluster analysis, monthly rainfall INTRODUÇÃOO Estado do Rio de Janeiro, com cerca de 40 mil quilômetros quadrados, embora se situe na orla litorânea da costa leste do território brasileiro, apresenta diferentes padrões climáticos. A disposição das serras do Mar e da Mantiqueira apresenta-se quase perpendicular ao escoamento médio da baixa troposfera, que associado às perturbações extratropicais, provoca um aumento considerável da precipitação a barlavento das montanhas, quando comparado com as mesmas situações atmosféricas nas regiões do Vale do Paraíba e da baixada litorânea. O conhecimento dos elementos de clima dessas regiões é uma importante ferramenta para a previsão de tempo em mesoescala e para auxiliar projetos agrícolas e industriais. Portanto, faz-se necessária a realização de estudos que visem à adoção de uma nova classificação climática, que leve em conta a variabilidade dos diversos elementos de clima ocorrida nos últimos anos. Para a compreensão dos processos climatológicos de uma região torna-se necessário um prévio conhecimento de seus diversos fa...
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