A Fuzzy Logic Approach for the Determination of Cavendish Banana Shelf Life

Abstract

This is an automated system in determining shelf-life of a cavendish banana fruit using its ethylene gas content through fuzzy logic approach. One finger of banana is placed inside a chamber for experimentation. An MQ3 sensor is used to measure the ethylene gas emitted by the fruit and a DHT22 temperature sensor is also used to monitor the ambient temperature inside the chamber. Linear regression analysis statistics is being applied to show that adjusted R Square result is 0.94. Three temperature range were considered to differentiate the emission speed of ethylene gas for a certain temperature. The higher the temperature, the faster the ripening process. Moist also affects ethylene gas emission inside the chamber and is therefore, proper ventilation is essential during the ripening process. The system uses MATLAB to determine banana’s shelf-life using fuzzy logic toolbox and displayed in a graphical user interface. Ethylene gas content were also monitored for each classifications of banana, namely: unripe, ripe and overripe. With this, conventional way in determining ripeness will be minimized and shelf-life will also be easily identified. Consumers and farmers are the great beneficiaries of the system, as it is their way to monitor fruit ripening and its shelf-life.