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Oil Palm Fruit Classification Using Spectrometer

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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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Document Type: Research Article

Publication date: September 1, 2013

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  • ADVANCED SCIENCE LETTERS is an international peer-reviewed journal with a very wide-ranging coverage, consolidates research activities in all areas of (1) Physical Sciences, (2) Biological Sciences, (3) Mathematical Sciences, (4) Engineering, (5) Computer and Information Sciences, and (6) Geosciences to publish original short communications, full research papers and timely brief (mini) reviews with authors photo and biography encompassing the basic and applied research and current developments in educational aspects of these scientific areas.
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