Analysis on non-destructive mango ripeness classification system

Malaysia is a country that receives enough sunlight and rain throughout the year forstrong fruit production, thus this unique property enables many fruits especially mangos to be cultivated. Mango obliges to be harvested at the best time to produce high quality of fruits and thus ripeness assessment are the most important aspects. However, with the increasing demand by consumers, the current way of mango ripeness assessment or classification is still prone to human error and sometimes damage the fruit because it is being done through manual processes. Therefore, the mango ripeness classification technique is required for replacing these traditional methods since this will improve the efficiency and accuracy. This research introduced a non-destructive system for mango ripeness classification by combining three techniques in a single system using image processing technique, odor sensing and capacitive sensing technique. The processes in this system are comprised with webcam camera for capturing the mango images forripeness classification through color based on the hue, saturation and value features through image processing technique. Besides that, eight different features were taken from Odor Gas Sensor (OGS) that are used to extract the smell data release from the mango, whereas as for capacitive sensing, parallel capacitive plate is used as an enhancement to the system for measuring the capacitive value features. The multiple technique is capable to tackle the problems arise as some mango has different ripeness properties such as color, odor and dielectric. Support Vector Machine (SVM) is used as classifier for this system to classify the mango ripeness and voting-based scoring approach is used to evaluate the overall performance score based on the three techniques. Based on the results and analysis, the mango ripeness classification system produces good results with a classification accuracy of 98.43% through image, odor and capacitive combination. The conducted research suggests that this system which are different from the existing system has the potential to implement for other types of fruits and can contribute to the improvement in the agriculture sector.