Growing food demand, water shortage, increased concern about the environment and the search to increase profitability are factors that have stimulated the adoption of techniques to optimize the agricultural managementand are growing in importance. In this sense, technologies related to precision agriculture (PA) has led to the emergence of systems to support decision making in many areas, including, grape yards, almonds and apples orchards. In this work, a tool is presented that allows mapping apple quality indexes, such as firmness index and soluble sugars (Brix), georeferenced, and transform them into a graphic variable to serve as a support for orchard management. The system was developed in Java language, with PostgreSQL database and uses the geographical extension PostGIS.The system has been named "Apple Show" and has the ability to map the analyzed areas, mark the classified points and interpolate them using either the inverse distance weighting (IDW) or moving average (MA), presenting and classifying them in the form of thematic maps in order to facilitate the understanding and decision making during the productive cycle.To demonstrate the use of the system an area of 3.3 ha with 1600 trees located in Vacaria, RS, Brazil was evaluated. Fruit quality indexes were generated, with the normalization of quality indicators on a scale from 1 (worse situation) to 15 (better situation). This allowed the overlap, generating a resulting map from the empirical indexes of fruit quality with possible dimensionless values between 0 (very bad) and 15 (very good).The result obtained with this project was a computational tool that allows to gather, interpret and present information related to orchard agricultural production, so as to facilitate the understanding and decision making during the productive cycle in a facilitated way, through the use of thematic maps, replacing the various, commonly used, data sheets.