No abstract

Resumo -O objetivo deste trabalho foi avaliar tendências das temperaturas mínimas e máximas no Estado de Minas Gerais. Foram avaliados dados de 43 municípios, tendo-se considerado as escalas anual e sazonal -janeiro, abril, julho e outubro, que representam os meses centrais de verão, outono, inverno e primavera, respectivamente. Séries históricas de temperaturas mínimas e máximas do ar diárias, com extensão mínima de 30 anos, foram analisadas com base no teste de Mann-Kendall e no uso de regressão linear simples. As tendências foram consideradas significativas somente quando ambas as avaliações foram significativas; neste caso, determinaram-se as taxas de alteração das temperaturas. Houve boa concordância entre os testes de significância para a detecção de tendências nas séries históricas, na maioria dos municípios. Observou-se tendência de elevação das temperaturas mínimas em julho de até 1,5ºC por década, com tendências generalizadas de aumento na maior parte do estado, em outubro e janeiro, e também na escala anual. Exceções foram verificadas especialmente em municípios de maiores altitudes, em que as temperaturas mínimas diminuíram no inverno. Há predominância de municípios com tendência significativa de aumento de temperaturas, independentemente da escala de avaliação. Tendências de aumento nas temperaturas são esperadas mais comumente no sentido sul-norte do Estado de Minas Gerais.Termos para indexação: agrometeorologia, aquecimento global, mudanças climáticas, teste de Mann-Kendall, variabilidade climática. Trends of minimum and maximum air temperatures in the state of Minas Gerais, BrazilAbstract -The objective of this work was to evaluate the trends in minimum and maximum air temperatures in the state of Minas Gerais, Brazil. Data from 43 municipalities were analyzed, considering annual and seasonal scales -January, April, July, and October, which represent the middle months of summer, autumn, winter, and spring, respectively. Historical series of minimum and maximum daily air temperatures, from at least 30 year, were analyzed by the Mann-Kendall test and linear regressions. Trends were considered significant only if both evaluations were significant; in this case, the rates of temperature shift were determined. There was good agreement between the statistical tests for detecting trends in the historical series, for most municipalities. An increasing temperature trend of up to 1.5 o C per decade was observed for minimum temperatures in July, with generalized increasing trends in the greatest part of the state in January and October, and also in the annual scale. Exceptions were verified mainly in municipalities at higher altitudes, in which minimum air temperatures decreased in winter. There is a predominance of municipalities with significant increasing temperature trend, regardless of the evaluation scale. Increasing temperature trends are expected to be more common in the south to north direction, in the state of Minas Gerais.

Broiler chickens are classified as homoeothermic animals and require a production environment within well-defined thermal comfort intervals. Therefore, the development of algorithms (mathematical models) to control the environment that can be embedded in microcontrollers becomes necessary. Hence, this work aimed to develop a fuzzy model for predicting the productive performance of broiler chickens as a function of the thermal environment during the various breeding phases. The Mamdani inference and defuzzification methods were used, by means of the gravity center, to develop the fuzzy model. Two hundred and forty-three rules with weighting factors of 1.0 each were elaborated. Three commercial warehouses (conventional system, wind tunnel with negative pressure and dark house) were evaluated for testing of the model. We recorded the thermal environment (dry bulb temperature-tdb and relative humidity-RH) and productivity data (feed intake-FI, weight gain-WG, feed conversion-FC and productive efficiency index-PEI) over six lots in each aviary. The resulting fuzzy model was capable of forecasting FI, WG, FC, and PEI, with standard deviations and mean percentage errors of 4.16 g and 5.05%, 146.53 g and 8.04%, 0.06 g g-1 and 4.96%, and 24.51 g and 12.29%, respectively.

Understanding hydrologic behavior in forested areas, not least the Brazilian Atlantic Forest, is of fundamental importance for environmental modeling. This work aimed to estimate evapotranspiration values in Atlantic Forest remnants of Mantiqueira Range region using water balance calculations, and to estimate parameters (stomatal and aerodynamic conductances) for this vegetation cover using the Penman-Monteith model. In terms of water balance, evapotranspiration accounted for 89% of total precipitation, deep percolation accounted for 13.6% and storage variation was slightly negative over the analysis period.

No abstract