-The citriculture consists in several environmental risks, as weather changes and pests, and also consists in considerable financial risk, mainly due to the period of return on the initial investment. This study was motivated by the need to assess the risks of a business activity such as citriculture. Our objective was to build a stochastic simulation model to achieve the economic and financial analysis of an orange producer in the Midwest region of the state of Sao Paulo, under conditions of uncertainty. The parameters used were the Net Present Value (NPV), the Modified Internal Rate of Return (MIRR), and the Discounted Payback. To evaluate the risk conditions we built a probabilistic model of pseudorandom numbers generated with Monte Carlo method. The results showed that the activity analyzed provides a risk of 42.8% to reach a NPV negative; however, the yield assessed by MIRR was 7.7%, higher than the yield from the reapplication of the positive cash flows. The financial investment pays itself after the fourteenth year of activity.

RESUMO: Diversos fatores afetam a indústria canavieira do Brasil, como a baixa taxa de utilização da capacidade industrial e redução dos rendimentos dos processos agrícolas mecanizados, principalmente na colheita da cana-de-açúcar. O objetivo deste estudo foi utilizar metodologias de autores da área de mecanização agrícola para a estimativa de indicadores de desempenho operacional das operações de colheita mecanizada de cana-de-açúcar. Os dados foram coletados por meio de pesquisa documental realizada numa propriedade pertencente a uma usina sucroenergética situada na cidade de São Manuel-SP. A análise desta proposta metodológica foi realizada por meio de um estudo de caso, com a obtenção de informações sobre a área colhida, na safra 2010/2011. De acordo com os resultados obtidos neste trabalho, pode-se concluir que os métodos utilizados para estimar os indicadores de desempenho operacional auxiliam no planejamento das operações de colheita, tanto para o dimensionamento do número de máquinas e implementos necessários, como para a determinação de indicadores que contribuem para o controle das operações. PALAVRAS-CHAVE:Colheita mecanizada, indicadores, metodologia. OPERATIONAL PERFORMANCE EVALUATION OF SUGARCANE (Saccharum spp.) HARVESTING AND LOADING MECHANICAL OPERATIONSSUMMARY: Several factors have affected the sugarcane industry in Brazil lately, the low rate of industrial capacity utilization and the decrease agricultural processes efficiency, especially in harvesting process. The objective of this study was to estimate operational performance indicators for mechanical harvesting of sugarcane operations based on methodologies described by researchers in the field of agricultural mechanization. Data were collected through desk research conducted in a sugarcane plant located in Sao Manuel, Sao Paulo State. The analysis of this proposed methodology was carried out through a study case with collected information on the harvesting area in 2010/2011. According to the present results, it was concluded that the methodologies used to estimate the operational performance indicators help planning harvesting operations, both for determining the number of machines and equipment needed, and identifying the indicators that contribute to control this operations.

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Several factors may contribute to changes in monitoring parameters of drinking water quality, especially climatic characteristics. Behavioral studies of these characteristics are relevant to the rational and sustainable use of water resources and better monitoring of the quality of water available for the population. To assess the association between water quality and climate, this research explored physical-chemical and microbiological characteristics considered important for the monitoring of water quality, analyzed in casual samples collected daily from the distribution system of a city, and considered monthly data of climatic characteristics from 2007 to 2011. The associations between these two sets of variables were assessed by the multivariate procedure of the canonical correlation analysis. The results indicate a positive correlation between the canonical variable formed by the linear combination of climatic variables and the canonical variable formed by the linear combination of water quality variables.

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