Predicting fruit maturity stage dynamically based on fuzzy recognition and color feature

Developing and ripening fruit are often classified for vary purposes according to its maturity classes. We propose an approach that predicts tomato fruit maturity stage during development and ripening according to their surface color. Tomato fruit maturity is divided into four stages in which the ripening time is short. The purpose of this paper is forecasting tomato fruit surface color change process which is reflected in surface color during every maturity stage based on temperature conditions. Fruits' current status should be get using fuzzy recognition before forecasting their maturity stage. This approach allows user to input the forecasting short-term temperature so as to get the ripening process dynamically during every maturity stage. This can lead to a decision making for farmer to maximize the profit.