Oil palm fruit classifications by using near infrared images

• Main Authors: Mohd Kassim, Muhamad Saufi, Wan Ismail, Wan Ishak, Lim, Ho Teik
• Format: Article
• Published: Maxwell Science Publication 2014
• Online Access: http://psasir.upm.edu.my/id/eprint/34715/; http://www.maxwellsci.com/jp/abstract.php?jid=RJASET&no=412&abs=05
• Institution: Universiti Putra Malaysia

Non-destructive assessment on oil palm Fresh Fruit Bunch (FFB) variability provides information for convenient oil palm field management practices. In this study a destructive assessment, using a microstrip sensor technique was firstly used to determine oil palm FFB maturity stages. A sample of FFB fruitlets was taken from 50 oil palm trees. The statistical data of insertion loss obtained from microstrip sensor was then been compared with moisture content in wet basis that was obtained from oven drying to correlate with the FFB maturity stages. The images of the above FFB samples were taken at the field by using multispectral camera. These images were processed and Near Infrared (NIR) hue value was extracted as the maturity feature. A relationship between images data of NIR and microstrip sensor data was developed to determine the maturity stages. The maturity stages data was plotted in the GIS map. Farmers will be able to go to specific location of FFB that has the optimum maturity and carried out the harvesting operation efficiently.