Published Researches

6 May 2019

Modeling Ripeness Grading of Palm Oil Fresh Fruit Bunches through Image Processing using Artificial Neural Network

Modeling Ripeness Grading of Palm Oil Fresh Fruit Bunches through Image Processing using Artificial Neural Network

Osama M. Ben Saaed1, Meftah Salem M Alfatni1,2*, Abdul Rashid Mohamed Shariff3 and Hadya S Hawedi1

1Faculty of Information Technology, Al-Asmarya Islamic University, Zliten, Libya,

2Faculty of Information Technology, Elmergib University, AL-Khomes, Libya,

3Faculty of Engineering, Universiti Putra Malaysia, 43400, Serdang, Selangor, Malaysia.

Faculty of Information Technology, Al-Asmarya Islamic University, Zliten, Libya;

Abstract

This research introduces the use of a hyperspectral based system to detect the ripeness of oil palm fruit bunches (FFB). FFB are scanned by a hyperspectral device and the reflectance recorded for different wavelengths. A sample of 209 fruits from one type of oil palm fresh fruit bunches (Nigrescens) iscollected for categorization using the over-ripe, ripe and under-ripe categories. Attribute of the fruit in the visible and near-infrared (400–1000 nm) wavelength range regions is measured. An artificial neural network(ANN)classified the different wavelength regions on oil palm fruit by pixel-wise processing. ANN is employed, and the trained network is integrated back into the system to allow oil palm fruit ripeness differentiation. The results are then compared to classifications made by a trained human grader. The developed ANN model successfully classifies oil palm fruits into three ripeness categories. A comparison of the accuracy of results between ANN approach and the conventional system that applies a manual classification is made. The results show that ANN approach yields more than 90% classification accuracyfor all three categories. The findings of this research will help increase the efficiency of quality harvesting and grading of fresh fruit bunches (FFB).

Keywords: hyperspectral, ripeness, oil palm fresh fruit bunches, color, visibility, near infrared, classification.






 
 

 
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Reducing Total Freshwater Use in the Gold Processing Industry Using Linear Programming

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by Lamouchi Helmi
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Control of a Hybrid Wind-PV and Energy Storage System

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DETECTIONS OF BUILDINGSDIGITAL SURFACE MODELS DEFORMATIONS GENERATED FROM DRONES NADIR IMAGES

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Precision Technologies Role in the Study of Climate Change Impact

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5th International Conference on Water, Energy, Food and Agricultural Technology Istanbul, Turkey, 22-25 January 2019

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Drone base multiscale Digital Surface Models to planar areas.

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10th edition of the International Congress & technologies dedicated to geospatial applications

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Bluesky’s LiDAR experts educate Mouchel’s water industry professionals

The Mouchel Urban Drainage Academy (MUDA) trains water industry professionals Aerial mapping company Bluesky is helping water industry professionals understand the potential of laser captured height models. Following a request ...
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