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Oil Plam Fruit Classification Using Spectrometer.


Mohamed Shariff, Abd Rashid and Mahmud, Ahmad Rodzi and Aouache, Mustapha (2013) Oil Plam Fruit Classification Using Spectrometer. Advanced Science Letters, 19 (9). pp. 2651-2653. ISSN 1936-6612


Artificial neural network and linear discriminant analysis were used to detect the ripeness of oil palm fruit bunches. The proposed classification scheme categorized the oil palm fruits into three classes, namely, overripe, ripe, and under-ripe. Fruit color, presumed to be an important indicator of the ripeness of oil palm fruits, was measured with the aid of a FieldSpec 3 Hi-Res spectroradiometer in the wavelength range of 400 nm to 1000 nm. The results were then compared with the classifications made by a trained human grader.

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Additional Metadata

Item Type: Article
Divisions: Faculty of Engineering
DOI Number: https://doi.org/10.1166/asl.2013.5004
Keywords: Spectrometer
Depositing User: Muizzudin Kaspol
Date Deposited: 04 Jul 2014 07:07
Last Modified: 08 Oct 2015 06:35
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1166/asl.2013.5004
URI: http://psasir.upm.edu.my/id/eprint/28408
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