Author : Ojo O. Adedayo, John O. Famoriji and Gbadamosi S. Lekan

User-friendliness and ease-of-usage are two of the important qualities of a good measurement and characterization system. This work attempts to bring these qualities into the characterization of oil palm fruitlets for easier grading. Measurement of microwave energy parameters was first carried out on clean and ripe samples of oil palm fruitlets within the frequency range of 2-4GHz. The dielectric properties of the fruitlets were extracted from the values of the measured parameters and an intelligent Artificial Neural Network was designed and trained for prediction of the percentage oil content of the fruitlets. This network was linked to a carefully designed Graphical User Interface (GUI) written on MATLAB platform. Results of this work established that the prediction accuracy of the Neural Network-linked GUI is high and serves as a reliable tool for rapid determination of the quality of oil palm fruitlets. Additionally, the GUI served as a tool which helps users to efficiently characterize oil palm fruitlets with particular application in research and quality control.

Keywords: Graphical User Interface (GUI), Artificial Neural Network, oil content, oil palm fruitlets, dielectric properties

Article published in International Journal of Current Engineering and Technology, Vol.5, No.3 (June-2015)