In the current agricultural model, it is essential for farmers to know the real time available for the execution of agricultural operations throughout the crop cycle. This is the first step to plan and achieve greater efficiency in these operations, which are subject to climate changes. Meteorological variables in a certain region directly influence the number of days available to work with farm machinery. The objective of this study was to estimate the probabilities of favorable workdays for farm machinery, using meteorological information from the municipality of Santa Maria, RS, Brazil. The conditions to be considered as a favorable working day with machinery were: precipitation <5 mm and soil water storage between 40 and 90% of the available water capacity. The first order Markov chain was used to estimate the conditional probabilities of favorable days to work with machines. Results indicate that the methodology used to estimate the probabilities of favorable working days for agricultural machinery was feasible, showing the most appropriate times to execution of mechanized farming operations in the field, in the municipality of Santa Maria, RS.
agricultural machinery management; probability of wet days; markov chain
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