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Climatic risk for potato late blight occurrence in the Andes region, Venezuela Potato is one of the most importance crops for Venezuela ́s agriculture. However, low temperature and high humidity in the region where potatoes are growed are favorable to Late Blight (Phytophtora infestans) occurrence. Such disease limits the potato production in almost all regions of the country. Potato crop is growed in Venezuela at different altitudes, between 400 and 3000 msnm, being the Andes Region, which include the states of Táchira, Mérida, and Trujillo, the biggest producer. In this region, the existence of a weather database is of extreme importance, but the density of weather stations which measure air temperature is very low and the stations are not very well distributed. Another problem related to weather data is that daily rainfall measurements is not very reliable due to failures and missing data, which causes difficulties for agrometeorological studies associated to climatic risks of diseases occurrence. In function of what was mentioned above and taking into account the importance of potato crop to Venezuela, the objectives of the present study are: to generate models to estimate daily air temperature (average, maximum, and minimum) based on the multiple linear regression and geographical coordinates (latitude, longitude, and longitude); to fill in missing daily rainfall data through a proposed method of the nearest neighboor, which is determined by the cluster analysis (Ward Method, with Euclidean distance); and to characterize and spatialize the climatic risk of potato Late Blight occurrence in the Andes region of Venezuela, based on the forecast model proposed by Hyre (1954), which uses as input daily rainfall and daily average and minimum air temperature. Data used in this study were obtained from 106 weather stations, from the Ministry of Environment and Natural Resources of Venezuela, for a period of 31 years (1967-1997). The obtained models for estimating average, maximum, and minimum air temperatures showed on average determination coefficients (R) higher than 0.90 when tested with independent data and estimated values free of significant errors: d (agreement index) from 0.98 to 1.00 and average RMSE smaller than 2C. After to be organized, rainfall data presented a database with 17% of the missing data. Using the proposed method (the nearest neighboor) this percentage fell down to 2.5%. The statistical test of this method showed moderate errors, with MAE between 1.7 and 4.0 mmday and d from 0.57 (daily basis) to 0.83 (monthly basis). The interpolation of the potential maximum climatic risk for Late Blight occurrence was done by Geostatistics, (ordinary Kriging method), generating the map of risks for each sowing date.(20) of January 1 to October 15. The maximum and most likely risks were then defined. These indexes showed that the period with the highest risk for potato Late Blight occurrence is during the rainy season, mainly in the states of Táchira and Trujillo. Key-words: Geostatistics, SIG, Ward, multiple linear regression

Risco climático de ocorrência da requeima da batata na região dos Andes, Venezuela