Data mining model for early fruit diseases detection

Automatic methods for an early detection of plant diseases could be vital for precise fruit protection. Traditionally the agriculture expert's knowledge is descriptive and experiment based, therefore it is difficult to describe it mathematically and subsequently build decision system which can replace it. Key parameters of decision based fruit protection system could differ for classes of plants and diseases. However, such systems are very rare and very complex, and in many cases designed just for one plant class. For effective diseases protection of fruit, meteorological data and data about the disease appearance are the most important. In this paper authors propose one idea for data mining based system for detection of possible fruit infection. For this purpose, different types of data mining techniques were evaluated on unique data sets.