Evapotranspiration can be sufficiently estimated when meteorological data are available to implement robust models such as Penman-Monteith (PM). However, due to data scarcity, alternative approaches are necessary. In this context, this study aims to compare the reference evapotranspiration (ETo) obtained from the PM standard method with eight empirical equations to identify the simplest method that can be alternative to the reference method (Penman Monteith method) for ten places in state of Goiás (located in west-central Brazil, Brazilian Savanna). To estimate the ETo, air temperature and relative humidity air, wind speed, sunshine and solar radiation data, which were obtained from the data platform National Institute of Meteorology and the Meteorological and Hydrological System of the State of Goiás, were used. For comparison of empirical methods with PM standard method, we used the following statistical indicators: slope and intercept coefficients (β0 and β1) of regressions equations, the coefficient of determination (r²), Pearson's correlation (r), mean bias error (MBE), root mean square error (RMSE) concordance index refined (dr) and performance index (Pi). Our results indicated that the Turc method is the best option for the state of Goiás when meteorological data are not suffeciently available to use the standard PM method. On the other hand, the method of Romanenko did not present acceptable performance in nine of the ten studied localities. Therefore, its use is advised only in the municipality of the Itumbiara. Among evaluated methods the Hargreaves-Samani method is the best alternative, when there is only air temperature data.

RESUMOA estimativa de dados meteorológicos é imprescindível quando não se dispõe de dados observacionais. No entanto, a confiabilidade no uso destes, está condicionada a existência de concordância entre os dados preditos e os observados. Particularmente para a variável temperatura do ar, sendo uma das mais importantes para o planejamento das atividades agrícolas. Diante disso, objetivou-se com este trabalho, estimar os valores máximos, mínimos e médios da tempetura do ar, na escala decendial, a partir de coordenadas geográficas e altitude para o estado de Goiás. Para tanto, foram consideradas séries históricas de dados (1987-2017) oriundas de 27 municípios goianos. Para as estimativas consideradas neste estudo utilizou-se técnicas de análise de regressão múltipla, onde foi verificada a significância dos modelos preditores. Os coeficientes de determinação ajustados resultantes do modelo encontrado variaram de 0,66 a 0,82 para Tmax, de 0,56 a 0,72 para Tmin e de 0,66 a 0,74 para Tmed. Com este resultado, as médias das temperaturas máximas e médias decendiais, podem ser estimadas satisfatoriamente nos municípios goianos por meio da altitude, latitude e longitude.Palavras-chave: modelo matemático, temperatura do ar, regressão múltipla GEOGRAPHICAL COORDINATES AND ALTITUDE IN AIR TEMPERATURE ESTIMATION IN THE STATE OF GOIÁS ABSTRACTThe estimation of meteorological data is essential when observational data are not available. However, the reliability in its use, is conditioned by the existence of agreement between the predicted and observed data. Particularly for the variable air temperature, one of the most important for the planning of agricultural activities, this type of information has a strategic character. The objective of this work was to estimate the air temperature, maximum, minimum and mean values of air temperature, in the decendial scale, from geographic coordinates and altitude for the state of Goiás (Brazil). Historical data series from 27 municipalities in the state of Goiás were considered. For the estimates considered in this study multiple regression analysis techniques were used, where the significance of the predictive models was verified. The adjusted coefficients of determination resulting from the model found ranged from 0.66 to 0.82 for Tmax, from 0.56 to 0.72 for Tmin and from 0.66 to 0.74 for Tmed. With this result, mean maximum and average decendial temperatures can be estimated satisfactorily in the municipalities of Goiás by means of altitude, latitude and longitude.

Ponkan is one of the most popular freshly consumed tangerines in Brazil. Thus, postharvest technologies that prolong the shelf life of this fruit, such as drying, are desired and widely studied, promoting the preservation of fruit quality, resulting in long storage periods. The aim of thus study was to determine and model the drying kinetics of the Ponkan tangerine at temperatures of 60, 70 and 80 °C, and fit the best mathematical model that represents the behavior of experimental data. The experiment used a completely randomized design, where treatments were drying temperatures of 60, 70 and 80 ºC, with four repetitions. The mathematical models diffusion approximation, two terms, two-term exponential, Henderson and Pabis, modified Henderson and Pabis, logarithmic, Midilli, Newton, Page, and Thompson and Verma were fit to experimental data. Mathematical modeling was developed in Statistica 12.0 software. Drying time was found to be inversely proportional to temperature. Page's mathematical model fit satisfactorily to experimental data for drying at 60 and 70 ºC. For a temperature of 80 ºC, the Midilli mathematical model best fit drying kinetics.