Fruit Disease Identification Using Feature Extraction and Data Mining

Abstract

Agriculture is one of the fields which produce data continually ensuring each of the four characteristics with fantastic development. There are various difficulties in preparing farming records which manages assortment of organized and unstructured configuration. One of the difficulties in farming industry involves fruit infection discovery and control. For this reason ranchers needed to screen fruits ceaselessly from collect till its development period. Yet, this errand is definitely not a simple one. Subsequently it requires proposing a proficient smart cultivating strategy which will help for better yield and development with less human endeavors. Data preprocessing is a procedure which will analyze and arrange outside disorder inside fruits through different pictures. In this paper we proposed feature selection algorithm based on association rules (ARFS), considering the way that the association rule can find the association between the features attributes and the classes in the dataset, it uses the most outrageous system to learn the certainty between feature attributes and classifications.