Abstract :
The first task to ensure quality in oil milling is to select a good quality Oil palm fresh fruit bunches (FFB) for processing which means the only right mature FFB should be harvested. Herewith the brief research carried on various techniques to gauge the ripeness of oil palm fruits. The techniques have been developed such as percentage or number of harvested fruits per bunch, floatation technique, percentage detached fruits from the bunch, correlation of microwave frequency with fruits moisture content and all methods were as destructive and not possible to be applied for old oil palm trees due to height concern. Using non-destructive technique such as vision to determine the oil palm ripeness is used to categorize ripeness of oil palm FFB and to model in order to inspect and grade the oil palm fresh fruit bunches. The camera vision also is used to investigate the relationship between oil content in oil palm fruit and its surface color distribution while the colorimeter is used and found a strong correlation between mesocarp oil content and color values of internal mesocarp surface. Advantages of using imaging technology for sensing are that it can be fairly accurate, nondestructive, and yields consistent results. This paper review the applications of machine vision technology for improving industryʹs productivity, thereby reducing costs and making agricultural operations and processing safer for farmers and processing-line workers. It holds great potential and benefits for the agricultural industry because of its simplicity, low cost, rapid inspection rate, and broad range of applications.
