UNIVERSITI PUTRA MALAYSIA

OIL PALM FRUIT RIPENESS CLASSIFICATION USING OPTICAL-BASED COLOUR SENSOR

KIMIA SAADAT

FK 2016 125

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PMOIL PALM FRUIT RIPENESS CLASSIFICATION USING OPTICAL-BASED COLOUR SENSOR

By

KIMIA SAADAT

Thesis Submitted to the School of Graduate Studies, Universiti Putra Malaysia, in Fulfillment of the Requirements for the Degree of Master of Science

June 2016

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PMCOPYRIGHT

All materials contained within the thesis, including without limitation text, logos, icons, photographs and other artwork, is copyright material of Universiti Putra Malaysia unless otherwise stated. Use may be made of any material contained within the thesis for non- commercial purposes from copyright holder. Commercial use of material may only be made with the express prior, written permission of Universiti Putra Malaysia. Copyright © Universiti Putra Malaysia

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PMDEDICATIONS

This thesis work is dedicated to my parents, who have always loved me unconditionally and whose good examples have taught me to work hard for the things that I aspire to

achieve.

This work is also dedicated to my friend, Milad Faghihi, who has been a constant source of support and encouragement during the challenges of graduate school and

life.

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Abstract of thesis presented to the Senate of Universiti Putra Malaysia in Fulfillment of the requirement for the Degree of Master of Science

OIL PALM FRUIT RIPENESS CLASSIFICATION USING OPTICAL-BASED COLOUR SENSOR

By

KIMIA SAADAT

June 2016

Chairman Faculty

: Maryam Binti Mohd Isa, PhD : Engineering

Harvesting oil palm Fresh Fruit Bunches (FFB) at right stage of ripeness is critical to ensure optimum quality and quantity of oil production. Colour of these fruits can be used as an indicator to predict the level of fruits maturity. The manual grading system based on the colour of the fruits, which is currently used in oil palm mills may cause conflict and misconduct in fruits classification. Therefore, developing an automated fruit classification system is essential. A number of automated fruit sorting methods have been offered and tested for practical usage during the past few years but most of them are costly, bulky and time consuming.

In this study, a reflective colour sensor is used to determine the ripeness of the palm fruit. A portable optical-based sensor system to classify oil palm fruits based on fruits ripening stages has been designed. Several coloured papers were used to verify the effectiveness of the measurement. Analyses setup on distance, angle and position of the transmitter and receiver of the sensor were carried out. The best wavelength of the light source was chosen for the fruit classification system. All the measurements carried out are non-destructive and the oil palm fruit is possible to be measured on-site.

Results from the measurements set-up analyses show that 180º is the best angle between transmitter and receiver. The gap between transmitter and receiver and the gap between fruit and receiver are 1cm and 0.5cm-0.75cm respectively for high accuracy detection. The palm fruit is positioned vertically to the sensor for best detection. 1.5cm-2.3cm of fruit diameter range up to a week old fruit plugged ` the bunch in a dark room (LUX=0) is the best condition for oil palm fruit ripeness classification for this system.

The system is able to categorise the colour of different ripeness of oil palm fruit based on its colour reflection. The voltage ranges for unripe, ripe and overripe fruits are 0.478V to 0.511V, 0.674V to 0.714V and 1.22V to 1.24V respectively. The system also indicates the category of the fruit ripeness by displaying green, orange and red light for ripe unripe and overripe fruits respectively.

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Abstrak tesis yang dikemukakan kepada Senat Universiti Putra Malaysia sebagai memenuhi keperluan untuk Ijazah Master Sains

KELAPA SAWIT FRUITS KEMATANGAN KLASIFIKASI MENGGUNAKANOPTICAL BERASASKAN COLOR SENSOR

Oleh

KIMIA SAADAT

Jun 2016

Pengerusi Fakulti

: Maryam Binti Mohd Isa, PhD : Kejuruteraan

Penuaian Kelapa Sawit Buah Tandan Segar (FFB) pada peringkat awal kematangan adalah sangat penting bagi memastikan kualiti dan kuantiti pengeluaran minyak yang optimum. Warna buah kelapa sawit boleh digunakan sebagai indicator dalam meramalkan tahap kematangan buah tersebut.

Sistem penggredan manual adalah berdasarkan warna buah-buahan, yang kini digunakan di kilang-kilang kelapa sawit menyebabkan konflik dan salah laku dalam pengklasifikasian buah kelapa sawit. Oleh itu, pembangunan mengautomatikkan dalam sistem pengklasifisian buah-buahan adalah penting. Terdapat beberapa kaedah pengklasifisian buah kelapa sawit secara mengautomatikkan telah diuji dengan penggunaan praktikal sejak kebelakangan, tetapi kebanyakan ujian tersebut sangat mahal, mengambil ruang yang besar dan memakan masa yang panjang.

Dalam kajian ini, sensor warna reflektif digunakan bagi menentukan kematangan buah sawit. Oleh itu, sistem sensor yang berasaskan optik mudah alih digunakan bagi pengklasifian buah kelapa sawit mengikut tahap kematangan buah telah direka. Beberapa kertas warna telah digunakan bagi mengesahkan keberkesanan pengukuran. Persediaan analisis terhadap jarak, sudut dan kedudukan alat pemancar dan penerima sensor telah dijalankan. Limitasi terhadap saiz sampel, pengukuran masa dan cahaya ambien telah dikaji dalam projek ini bagi mencapai keputusan yang tepat. Penggunaan sumber cahaya yang terang daripada beberapa jalur spektrum telah diuji dalam pengklasifian buah. Kaedah ini tidak memudaratkan dan tahap kematangan buah kelapa sawit boleh diukur di tapak sebagai sistem penggredan kelapa sawit.

Sudut terbaik antara pemancar dan penerima telah dikenalpasti oleh sensor ini, keputusannya menunjukkan bahawa kedudukan sensor antara dengan jurang pemancar adalah 1cm manakala jurang penerima adalah jurang 0.5cm- 0.75cm dengan buah-buahan serta penerima sensor berada dalam kedudukan yang baik bagi mengesan hasil ketepatan yang tinggi. Selain itu, pengklasifikasian buah yang dibuat dalam kedudukan menegak adalah lebih tepat daripada dalam kedudukan mendatar. Selain daripada itu,

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faktor seperti saiz buah-buahan, cahaya ambien dan pengukuran masa yang memberi kesan kepada sensitiviti sensor dikaji dalam projek ini. Secara keseluruhan, sistem ini dapat mengkategorikan jenis warna buah kelapa sawit. Nilai sensor berada di dari 0.478V ke 0.511V bagi buah-buahan yang belum masak, dari 0.674V hingga 0.714V bagi buah-buahan yang sudah masak serta dari 1.22V hingga 1.24V bagi buah-buahan terlebih masak. Indikator warna hijau akan dihidupkan apabila buah masak. Indikator warna oren dan warna merah akan dihidupkan apabila buah-buahan yang belum masak atau masak mengikut kematangan buah tersebut.

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ACKNOWLEDGEMENTS

I praise God for all his mercy and grace, the beauties of the world and the chance that he has given us to discover its laws.

This dissertation would not have been possible without the guidance and help of several individuals who contributed their valuable assistance throughout this study.

Foremost, I would like to express my sincere appreciation to my supervisor Dr.Maryam Binti Mohd Isa for her patience, motivation and immense knowledge. Her guidance and support helped me throughout this research and the preparation of this thesis.

My special thanks also go to my Co-Supervisor Dr.Suhaidi Shafie for his support, motivation and knowledgeable guidance.

My sincere thanks also go to my friends in University Putra Malaysia: Sarah Rezaeien, Maral Faghani and Maryam Ehsani who always took the time to listen to me and share their knowledge.

Last but not the least; I would like to thank my parents, Kamran Saadat and Firouzeh Hatami, for their endless support and love they have provided me throughout my life. I would also like to thank them for encouraging and supporting me to pursue my Master’s study. My siblings, Kambiz Saadat, Kaveh Saadat, deserve my wholehearted thanks as well.

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This thesis was submitted to the Senate of the Universiti Putra Malaysia and has been accepted as fulfillment of the requirement for the degree of Master of Science.The members of the Supervisory Committee were as follows:

Maryam Binti Mohd Isa, PhD Senior Lecturer Faculty of Engineering Universiti Putra Malaysia (Chairman)

Suhaidi Bin Shafie, PhD Associate Professor Faculty of Engineering Universiti Putra Malaysia (Member)

BUJANG BIN KIM HUAT, PhD Professor and Dean School of Graduate Studies Universiti Putra Malaysia

Date:

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Declaration by graduate student

I hereby confirm that: this thesis is my original work; quotations, illustrations and citations have been duly referenced; this thesis has not been submitted previously or concurrently for any other degree at

any institutions; intellectual property from the thesis and copyright of thesis are fully-owned by

Universiti Putra Malaysia, as according to the Universiti Putra Malaysia (Research)Rules 2012;

written permission must be obtained from supervisor and the office of Deputy Vice-Chancellor (Research and innovation) before thesis is published (in the form ofwritten, printed or in electronic form) including books, journals, modules,proceedings, popular writings, seminar papers, manuscripts, posters, reports, lecturenotes, learning modules or any other materials as stated in the Universiti PutraMalaysia (Research) Rules 2012;

there is no plagiarism or data falsification/fabrication in the thesis, and scholarlyintegrity is upheld as according to the Universiti Putra Malaysia (Graduate Studies)Rules 2003 (Revision 2012-2013) and the Universiti Putra Malaysia (Research)Rules 2012. The thesis has undergone plagiarism detection software

Signature: ________________________________ Date: __________________

Name and Matric No.: Kimia Saadat , GS32050

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Declaration by Members of Supervisory Committee

This is to confirm that: the research conducted and the writing of this thesis was under our supervision; supervision responsibilities as stated in the Universiti Putra Malaysia (Graduate

Studies) Rules 2003 (Revision 2012-2013) were adhered to.

Signature: Name of Chairman of Supervisory Committee: Dr. Maryam Binti Mohd Isa

Signature: Name of Member of Supervisory Committee: Associate Professor Dr. Suhaidi Bin Shafie

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TABLE OF CONTENTS

Page

ABSTRACT i ABSTRAK ii ACKNOWLEDGEMENTS iv APPROVAL v DECLARATION vii LIST OF TABLES xi LIST OF FIGURES xii

CHAPTER

1 INTRODUCTION 1 1.1 Introduction 1 1.2 Background 1 1.3 Problem statement 2 1.4 Project objective 3 1.5 Project scope 3 1.6 Project significance 3 1.7 Organisation of the thesis 4

2 LITERATURE REVIEW 6 2.1 Introduction 6 2.2 Oil Palm: History 6 2.3 Formation of oil palm fruits 6 2.4 Ripening characteristics of oil palm fruits 8 2.5 Surface of oil palm fruit 9 2.6 Harvesting of oil palm fruits 9 2.7 Measurement of colour 10

2.7.1 Colour perception: Limitation 11 2.7.2 Spectrophotometry 12 2.7.3 Colorimetry 13 2.7.4 Optical reflective sensor 14

2.8 Grading of oil palm fresh fruit bunches 15 2.8.1 Manual grading system 15 2.8.2 Microwave sensors 16 2.8.3 Colour vision system 17 2.8.4 Magnetic resonance imaging (MRI) and bulk nuclear

magnetic resonance (NMR) 19

2.8.5 NIR spectroscopy 19 2.8.6 Optical sensor 20

2.9 Optical sensor applications 21 2.9.1 Opposed mode 21 2.9.2 Retro-reflective mode 22 2.9.3 Proximity mode 24

2.10 Summary 27

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3 METHODOLOGY 28 3.1 Introduction 28 3.2 Optical-based sensor circuit design 29

3.2.1 Light source 29 3.2.2 Detector 31

3.3 Sensor system initialization 34 3.3.1 Angle between light source and phototransistor 34 3.3.2 Distance between light source and phototransistor (D) 37 3.3.3 Distance between sensor and measurand (L) 39 3.3.4 Colour paper in different size 39

3.4 Sensor system test condition 40 3.4.1 Fruit positioning and orientation 40 3.4.2 Fruits in different sizes 41 3.4.3 Limitation on ambient light 42 3.4.4 Limitation on time of measurement 43 3.4.5 Light reflection measurement using different light

sources 43

3.5 System architecture 43 3.6 Software architecture 49

4 RESULTS 52 4.1 Introduction 52 4.2 Optical-based sensor circuit design 52 4.3 Sensor system initialization 52

4.3.1 Angle between light source and receiver (θ) 52 4.3.2 Distance between light source and receiver (D) 53 4.3.3 Distance between the sensor and measurand (L) 54 4.3.4 Colour paper in different size 55

4.4 Sensor system test condition 60 4.4.1 Distance between fruits and sensor 60 4.4.2 Fruits positioning and orientation 60 4.4.3 Fruits in different diameter size 63 4.4.4 Limitation on ambient light 64 4.4.5 Limitation on time of measurement 65 4.4.6 Light reflection measurement using different light

sources 66

4.5 Final sensor measurements 66 4.6 Reliability 67 4.7 Software development 67

5 CONCLUSION 69

70 75 92

REFERENCES APPENDICES BIODATA OF STUDENT PUBLICATION 93

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LIST OF TABLES

Table Page 2.1 Characteristics of Oil Palm Fruitlet 9 2.2 Grading of oil palm fruits by MPOB 15 3.1 Determination of reflected distance for different distance between

light source and detector 38

3.2 Location of fruits 41 3.3 Different categories of oil palm fruits based on their diameter size 42 3.4 PIC16F877A Microcontroller 45 3.5 Function of the labelled component of the reflective colour sensor

Box 49

4.1 Changes in percentage of the orange and red colour paper 59 4.2 Analysis for oil palm fruits reflectance at vertical mode 62 4.3 Analysis for oil palm fruits reflectance at horizontal mode 63

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LIST OF FUGURES

Figure Page

1.1 Five-year (2007–2011) palm oil average production by weight (USDA, 2012)

1

1.2 Work Flow of this Project 4

2.1 Structure of Oil Palm Fruit 6

2.2 Varieties of Oil Palm Fruit 7

2.3 Oil Palm fruit at different ripening stages 8

2.4 Electromagnetic spectrum 10

2.5 Operation of Spectrophotometer 12

2.6 Operation principles of a spectrometer and RGB colour sensor 12

2.7 Filter Arrangement in Colorimetry 13

2.8 Coaxial Sensor 16

2.9 Moisture Sensors 17

2.10 Colour sensor developed by Fadilah et al. (2012) 18

2.11 Portable 4-band sensor 20

2.12 Average Reflectance of 4- band sensor 20

2.13 Opposed Sensing Mode 21

2.14 Retro- reflective Mode 22

2.15 Effective beam in Retro- reflective mode 23

2.16 Specular sensor detects difference between dull and shiny surfaces 23

2.17 Diffused Mode Sensors 24

2.18 Divergent proximity sensing mode 25

2.19 Convergent Beam Sensing Mode 26

2.20 Fixed-field proximity sensing mode 26

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3.1 (a) Sensor system initialization parameter using coloured paper. (b) Sensor system test condition parameter using oil palm fruits

28

3.2 Light reflectance value from oil palm fruits at different light wavelengths (Saeed et al., 2012)

30

3.3 Circuit for the light source 30

3.4 Phototransistor structure 31

3.5 Basic Circuit for the detector 33

3.6 An amplifier added to the detector circuit 34

3.7 Phototransistor Spatial Distribution 35

3.8 System set up for measuring an optimal angle between red LED and phototransistor

35

3.9 Light source and receiver in direct incidence mode 36

3.10 Line of sight communication (LOS) block by an object 36

3.11 Light source and receiver in indirect incidence mode 37

3.12 Set up for measuring the best distance between light source and receiver (D). (a) Minimum distance. (b) Other conditions

38

3.13 Testing set up for measuring optimal distance between sensor and measurand

39

3.14 Measurements of the effects of paper width on sensor value 40

3.15 System set-up for measuring the optimal positioning and orientation of the fruits: (1) Fruit on horizontal direction. (2) Fruit on vertical direction

41

3.16 Determination of oil palm fruit diameter 42

3.17 Experiments set up in different ambient light (a) Dark room (b) Room with light (c) Outdoor

42

3.18 PCB Design and Connection for the optical-based colour sensor 44

3.19 Starter Kit SK40C 44

3.20 Top view of SK40C 45

3.21 Image of PIC16F877A 46

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3.22 Pin diagram of PIC16F877A 46

3.23 16x2 LCD Display 47

3.24 Circuit for PIC 16F877A with LED 47

3.25 Circuit for PIC 16F877A with LCD and 3 LEDs to display results 48

3.26 Internal (Left) and External (Right) Look of the sensor Box 48

3.27 Programming Work Flow 49

3.28 MikroC PRO for PIC 50

3.29 PICkit 2 Programmer 51

3.30 USB ICSP PIC Programmer UIC00B 51

4.1 Sensor output voltage VS Angle between LED and Phototransistor 53

4.2 Sensor output voltage vs. different distance between transmitter and receiver

54

4.3 Sensor Output Voltage VS different Distance between coloured paper and sensor

55

4.4 Reflected light from coloured paper with 1cm width size at different location in front of the sensor

56

4.5 Reflected light from coloured paper with 2cm width size at different location in front of the sensor

56

4.6 Reflected light from coloured paper with 3cm width size at different location in front of the sensor

57

4.7 Reflected light from coloured paper with 4cm width size at different location in front of the sensor

57

4.8 Reflected light from coloured paper with 5cm width size at different location in front of the sensor

58

4.9 Sensor Output voltage vs. different distance between oil palm fruits and sensor

60

4.10 Reflected light from oil palm fruits in vertical position at different location in front of the sensor

61

4.11 Reflected light from oil palm fruits in horizontal position at different location in front of the sensor

62

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4.12 Reflected light from unripe, ripe and overripe oil palm fruits with different diameter size

64

4.13 Reflected light from oil palm fruits in different ambient light 65

4.14 Reflected light from oil palm fruits during 1 week measurement 65

4.15 Comparison of reflected lights from oil palm fruits with different spectral bands

66

4.16 Box-and-Whisker plots representing sensor output value for unripe, ripe and overripe oil palm fruits

67

4.17 Programming flowchart 68

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CHAPTER I

INTRODUCTION

1.1 Introduction

In order to specify the ripeness of the fruit via colour distinction, a true method is

needed to be researched (MPOB, 1995). The colour presents very useful information

about the maturity and the freshness of the fruits and vegetables (Alfatni et al., 2008).

Therefore, colour can be used as one of the most significant factors for determining the

oil palm fruits grade and quality (Wan Ishak et al., 2000; Rashid et al., 2004).

1.2 Background

Dura, Pisifera and the Terena are the most prevalent types of the palm fruits. The

Terena palm has been used for this project because of its thick mesocarp and high

production of fruits in comparison with its parent palms.

Palm oil has a wide-ranging of usage; its plantation is extensively practiced by East

Asian farmers and organisations including Malaysia. Malaysia is one of the largest

exporters of palm oil in the world, contributing 3.2% to the country‘s real gross

domestic product (Basiron, 2007). It has an enormous contribution to the income of the

country. Malaysia is placed as the second highest producer of the oil palm with 39% of

the worldwide oil palm production (USDA, 2012).

Figure 1.1 : - – by weight

(USDA, 2012).

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To facilitate and maximise the production of the palm oil, it is necessary to harvest the

palm fruit at the right time (Wan Ishak et al., 2000). In case of an early harvest, the

bunch will be unripe and favourable amount of oil content might not be reached.

Whilst, an overripe fruit harvest results in extraction process issues since the quality

will be decreased by high acid existence (Ariffin, 1985). Therefore, harvesting the fruit

at the right time is needed.

Colour gives important information in evaluating the development and analysing the

ripeness of fruits. Colour also is one of the most important factors that presents the fruit

identification and is a good indicator for ripeness. This is also applicable for the oil

palm fruits where the fruit colour changes with its maturity, so it can be a good

parameter to estimate the fruits ripeness.

This research proposes a portable and cost effective grading system of an optical

technique by exploiting colour measurement to identify oil palm ripeness. This method

of optical technique will use reflected value, which sent back from oil palm fruits. This

system consists of a light source to illuminate the fruits and a photo detector to receive

and detect the reflected light from the fruits. Saeed O.M.B reported a comparison of

reflectance value from oil palm fruit bunches with four spectral bands 570nm, 670nm,

750nm, and 870nm; it is proved that there is a distinct difference between reflectance

values among different categories of oil palm fruits with 670nm spectral bands, which

is red light (Saeed et al., 2012). Thus, a red led has been selected as a light source in

this project and a phototransistor has been used as a light detector. Phototransistor

detects the reflected light from the fruits and the sensor system converts it to a specific

range of voltage for each group of the fruits based on the fruit surface colour. In this

project, the best physical positions and configuration of each element have been tested

in order to have an accurate and effective sensor to classify the fruits. Several LEDs

with different wavelengths have been tested for the best light source.

In this study, the right specification of the sensor have been analysed and the colour

range of the oil palm fruit have been determined.

1.3 Problem statement

There have been a few studies to investigate oil palm ripeness classification. In current

researches, the chemical analysis methodology is time and energy consuming which

are very crucial in industries. While the process of oil content determination in each

fresh fruit is costly and destructive. Hence, the physical scanning is highly

recommended since it is less time consuming with respect to the daily-required sample

quantity.

The major drawbacks in the manual grading system based on the surface colour of the

fruits are labour fee, slow and inaccurate. Therefore, developing an automated fruit

classification system is required.

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By employing the spectral reflectance of the oil palm fruits, the different fruit colour

can be identified. Some methods that are conducted for machine vision-based the fruits

categorising such as optical RGB cameras (Ismail et al., 2000; Abdullah et al., 2001;

2002; Devadas et al., 2009; Alfatni et al., 2007; 2008; Jamil et al., 2009), hyper

spectral imaging cameras (Junkwon et al., 2009), magnetic resonance imaging and bulk

nuclear magnetic resonance sensors (Shaarani et al., 2010). Shaarani et al. (2010) have

presented the capability of utilising optical sensors as a part of oil palm fruits

identification.

1.4 Project objective

The aim of the project is to develop a portable optical-based sensor system for

determining the oil palm fruit ripeness. The project objectives are:

1. To develop an optical-based sensor system.

2. To verify the performance of the developed sensor by detecting the ripeness

of randomly selected oil palm fruits.

1.5 Project scope

Three different coloured papers in black, red and orange colour have been used to

represent the colour of the fruit for unripe, ripe and overripe fruits respectively. If

actual fruits are being used, the fruits life time reduced the measurements process

speed. In addition, Terena type of fresh oil palm fruits was collected by farmers in

University Putra Malaysia (UPM). The farmers categorised fruits in three clusters

(unripe, ripe and over ripe) to measure the fruit surface colour. The measurements were

conducted in a dark room with fairly eminent room heat of about 25ºC and a light

meter employed to certify the absence of ambient light, which interferes the

experiments. The measurement also has been repeated in a room with lightning and

outdoor as well. The fruits have been tested after harvesting and then covered with

paper and kept in the fridge to prevent fruit evaporation. The samples were tested every

day within 1 week to reveal the fruit reliable time for measuring.

1.6 Project significance

This project significance is developing a new palm oil maturity grading method based

on the fruit colour. The mentioned method benefits the agriculture sector higher

performance achievement in term of palm oil production, which results in the Malaysia

economic development. This model benefits those students who have palm fruit oil

related assignments and help them finish their work easier and faster. This project

helps the researchers developing colour based identification methods.

The workflow of the study in Figure 1.2 shows the order of the tasks that have been

done in this project.

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Figure 1.2 : Work flow of this project

1.7 Organisation of the thesis

This report contains five chapters. The first chapter is an introduction; the literature review is included in the second chapter, the research methodology is described in the third section, fourth chapter includes findings and discussion and the conclusion and future studies are explained in the last chapter.

Chapter one will explain the background of palm oil, the problem statement, the project scope and significance of the study. The main objectives of the study are elaborated as well. At the end of the first chapter few points are highlighted as the benefits of the project.

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Chapter two reviews the technique and some of the existing similar projects as developing grading palm oil prototype guidance. The literature review is essential in this project as it provides evidence and a proven conclusion to support this project.

The research methodology, which is used in this research, is explained in chapter three. This chapter will describe the overall process of the project development. Chapter four discusses the results and findings of the project. Finally, chapter five divided into three main sections, which are the conclusion, the recommendation and the summary.

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REFERENCES Abbas, Z., 1994. A Microstrip Sensor for Determination of Harvesting Time for Oil Palm

Fruits, MSc Thesis. Malaysia: Universiti Putra. Abbas, Z.; Yeow, Y.K.; Shaari, A.H.; Khalid, K.; Hassan, J.; Saion, E, 2005. Complex

Permittivity and Moisture Measurements of Oil Palm Fruits Using an Open-Ended Coaxial Sensor. IEEE Sens. J. 5, 1281-1287.

Abdullah, M.Z., Guan, L.C. & Mohd, A.B., 2001. Stepwise Discriminant Analysis for

Colour Grading Of Oil Palm Using Machine Vision System. Institution of Chemical Engineers Trans Icheme (p.223- 231): 79 Part C.

Abdullah, M.Z., Lim, C.G., Abdul, M.D. & Mohd. A.M.N., 2002. Color Vision System

for Ripeness Inspection of Oil palm Elaeis Guineensis. Journal of Food Engineering Processing, 26 (1), pp.213-35.

Adedayo, O.O., Isa, M.M., Soh, A.C. and Abbas, Z. 2014. Comparison of feedforward

Neural Network training algorithms for intelligent modeling of dielectric properties of oil palm Fruitlets. International Journal of Engineering and Advanced Technology 3 (3): 38-42.

Alfatni MSM, Shariff ARM, Shafri HZM, Saaed OMB, Eshanta OM, 2008. Oil palm

fruit bunch grading system using red, green and blue digital number. J. Appl. Sci. 8(8):1444-1452.

Alfatni, M.S.M.; Shariff, A.R.M.; Shafri, H.Z.M.; Saaed, O.M.B.; Eshanta, O.M.;

Abuzaed, M., 2007. Automated oil palm fruit bunch grading system using density of color (RGB). In Proceedings of the 7th Saudi Engineering Conference. King Saud University, Riyadh, 2007.

Ali, A., 2007. A Study on Relationship between Reflection Coefficient and Moisture

Content in Oil Palm Fruits using Rectangular Waveguide, MSc Thesis. Malaysia: Universiti Putra.

Al-Maaitah, M.I., Al-Absi, K.M. & Al-Rawashdeh, A., 2009. Oil quality and quantity

of three olive ciltivars as influenced by harvesting date in the middle and southern parts of Jordan. Int. J. Agric. Biol., 11, pp.266–272.

Ariffin, A.A., 1985. The Biochemical Aspects of Ripeness Standard. In Proc. Of The

Symposium on Impact of the Pollinating Weevil on the Malaysian Oil Palm Industry. Kuala Lumpur.

Avago, 2007. Reflective Color Sensing with Avago Technologies’ RGB Color Sensor.

Unites States and other countries: Avago Technologies.

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Azis A.A., Mohamadiah Banjari, W Zailan Rosnah Mat Soom, W Omar and Chen Kin W., 1984. Ripeness Standard: Any sign of Loose Fruit and with One Loose Fruit per Bunch as the Minimum Standard. Proceeding Of The Symposium On Impact Of The Pollinating Weevil On The Malaysian Oil Palm Industry (pp. 165-176). Kuala Lumpur. Palm Oil Research Institute of Malaysia

Azis, A.A., 1990. A Simple Floatation Technique to Gauge Ripeness of Oil Palm Fruits and Their Maximum Oil Content. In proceedings of 1989 International Palm Oil Development Conference. Kuala Lumpur, 1990. PORIM.

Bafor, M.E. & Osagie, A.U., 1986. Changes in lipid class and fatty acid composition during maturation of mesocarp of oil palm (Elaeis guineensis) variety Dura. J. Sci. Food Agric., 37, pp.825–832.

Balasundram, S., Robert, P. and Mulla, D. 2006. Relationship between oil content and fruit surface colour in oil palm (Elaeis guineensis Jacq.). Journal of Plant Sciences 1 (3): 217-227.

Banner Engineering Corp., 1994. Handbook of Photoelectric Sensing. Minneapolis, MN: 9714 Tenth Ave. North.

Basiron, Y, 2007. Palm oil production through sustainable plantations. Eur. J. Lipid Sci. Technol. 109, 289–295.

Bonnie, T.Y.P. & Mohtar, Y., 2011. Determination of palm oil residue in palm kernel and palm oil methyl ester using near infrared spectroscopy. J. Oil Palm Res., pp.1055–59.

Cytron Technologies, 2011. UIC00B USB ICSP PIC Programmer User's Manual. Malaysia.

Devadas, R., Lamb, D.W., Simpfendorfer, S. & Backhouse, D., 2009. Evaluating ten spectral vegetation indices for identifying rust infection in individual wheat leaves. Precision Agriculture, 10, pp.459–70.

Fadilah, N., Mohamad-Saleh, J., Abdul Halim, Z., Ibrahim, H., & Syed Ali, S. S. (2012). Intelligent colour vision system for ripeness classification of oil palm fresh fruit bunch. Sensors (Basel, Switzerland), 12(10), 14179-95. http://dx.doi.org/10.3390/s121014179

Guan, L.C., 2005. Stepwise discriminant analysis on oil palm fruit’s hues for ripeness grading using machine vision system, Master’s thesis. Malaysia: School of Electrical and Electronic Engineering, Universiti Sains.

Hartley, C.W.S., 1977. The Oil Palm, 2nd edition. London: Longmans.

Hazir, M. H. M., Shariff, A. R. M., Amiruddin, M. D., Ramli, A. R., & Saripan, M. I. (2012). Oil palm bunch ripeness classification using fluorescence technique.Journal of Food Engineering, 113(4), 534-540.

© CO

PYRI

GHT U

PM

72

Hudzari, R., Ishak, W.W. & Norman, M., 2010. Parameter acceptance of software development for oil palm fruit maturity prediction. J. Softw. Eng., 4, pp.244–56.

Hunt, R.W.G., 2004. Reproduction of Color. England: John Wiley & Sons Ltd, 6 Ed. Ikemefuna, J. & Adamson, I., 1984. Chlorophyll and carotenoid changes in ripening

palm fruit, Elaeis guineensis. Phytochemistry, 23, pp.1413– 1415. Ishak, W.I.W. & Razali, M.H., 2010. Hue optical properties to model oil palm fresh fruit

bunches maturity index. In World Multi-Conference on Sys- temics, Cybernetics and Pattern Recognition., 2010.

Ismail, W.I.W., Bardaie, M.Z. & Hamid, A.M.A., 2000. Optical properties for

mechanical harvesting of oil palm FFB. Journal of Oil Palm Research, 12 (2), pp.38–45.

Jaffar, A., Jaafar, R., Jamil, N., Low, C. Y. and Abdullah, B. 2009. Photogrammetric

grading of oil palm fresh fruit bunches. International Journal of Mechanical and Materials Engineering 9 (10): 18-24.

Jamil, N., Mohamed, A. & Abdullah, S., 2009. Automated grading of palm oil fresh fruit

bunches (FFB) using neuro-fuzzy technique. In International Conference of Soft Computing and Pattern Recognition, SOCPAR' 09.

Junkwon P., Takigawa T., Okamoto H., Hasegawa H., Koike M., Sakai K., Siruntawineti

J., Chaeychomsri W., Sanevas N., Tittinuchanon P., et al. 2009. Potential application of colour and hyperspectral images for estimation of weight and ripeness of oil palm (Elaeis guineensis Jacq. Var. tenera) Agric. Inf. Res; 18:72–81.

Kaida, K. & Zulkifly, A., 1992. A Microstrip Sensor for Determination of Harvesting

Time for Oil Palm Fruits. Journal of Microwave Power and Electromagnetic Energy, 27 (1), pp.1-9.

Kasemsumran, S.; Thanapase, W.; Punsuvon, V.; Ozaki, Y, 2012. A feasibility study on

nondestructive determination of oil content in palm fruits by visible-near infrared spectroscopy. J. Near Infrared Spectrosc. 20, 687–694.

Lee, K.Y., 2004. Development of a 500 MHz Reflectometer using Stripline Coupler for

Moisture Measurement of Oil Palm Fruits, MSc Thesis. Malaysia: Universiti Putra.

Lötschert, W. & Beese, G., 1983. Collins Guide to Tropical Plants. London: Collins. M. C.-K. C. Albert H. Titus and V. P. Chodavarapu, “CMOS photodiode,” in

Photodiodes,World Activities in 2011, Rijeka, Croatia: InTech, 2011. May, Z. & Amaran, M.H., 2011. Automated oil palm fruit grading system using artificial

intelligence. Int. J. Eng. Sci., 11, pp.30–35.

© CO

PYRI

GHT U

PM

73

Mohd, H.M.H., Abdul, R.M.S. & Mohd, D.A., 2012. Determination of oil palm fresh fruit bunch ripeness—based on flavonoids and anthocyanin content. Ind. Crop. Prod., 36, pp.466–75.

Mokhtar, R., 2004. RDWG Technique for Determination of Complex Permittivity and

Moisture Content of Oil Palm Fruits, MSc Thesis. Malaysia: Universiti Putra. MPOB, 1995. Oil Palm Fruit Grading Manual. Malaysia: Malaysian Palm Oil Board. Ng, K.T. & Southworth, A., 1973. Optimum time of harvesting oil palm fruits. In

Proceedings of the International Oil Palm Conference, 16th-18th November 1972. Kuala Lumpur, Malaysia, 1973. Incorporated Society of Planters.

Norhisam, M., Qian, Y.L., Firdaus, R.N. & Norrimah, A., 2011. Effect of inductive coil

shape on sensing performance of linear displacement sensor using thin inductive coil and pattern guid. Sensors, 11, pp.10522–33.

Nureize, A. & Watada, J., 2009. Multi-criteria Fuzzy Regression Model for Evaluating

Oil Palm Grading. Japan: Graduate School of Information, Production and System, Waseda University.

Oo, K.C., Teh, S.K., Khor, H.T. & Augustine, S.H.O., 1985. Fatty acid synthesis in the

oil palm (Elaeis guineensis): incorporation of acetate by tissue slices of the developing fruits. Lipids, 20, pp.205–209.

Rajanaidu, N. & Tan, B.K., 1983. Variability of fatty acid composition (fac) within

bunches in the oil palm elaeis guineensis. Oleagineus, Vol.38 (1), pp.581-84. Rashid S, Nor A, Adnam RM, Shattri M, Rohaya H, Roop G, 2004. Correlation between

oil content and DN values, Department of Biological and Agriculture, Universiti Putra Malaysia, GISdevelopment.net.

Razali, M.H.; Wan, I.W.I.; Ramli, A.R.; Sulaiman, M.N.; Harun, M.H., 2011. Prediction

model for estimating optimum harvesting time of oil palm fresh fruit bunches. J. Food Agric. Environ.9, 570–575.

Saeed, O.M.B., Sankaran, S., Shariff, A.R.M., Shafri, H.Z.M., Ehsani, R., Alfatni, M.S.,

Hazir, M.H.M., 2012. Classification of oil palm fresh fruit bunches based on their maturity using portable four-band sensor system. Computers and Electronics in Agriculture 82, 55–60.

Sambanthamurthi, R., Sundram, K. & Tan, Y.A., 2000. Chemistry and biochemistry of

palm oil. Progress in Lipid Research, 39, pp.507-558, 553. Shaarani SMD, Cárdenas-Blanco A, Amin MHG, Soon NG, Hall LD, 2010. Monitoring

development and ripeness of oil palm fruit (Elaeis guneensis) by MRI and Bulk NMR. Int J Agric Biol 12:101–105

Southworth, A., Corley, R.H.V., Hardon, J.J. & Woods, B.J., 1976. Harvesting Oil Palm

Research (p. 469-477). Elsevier, Amsterdam, the Netherlands.

© CO

PYRI

GHT U

PM

74

Stevenson, T., 2006. Malaysia targets alternative fuels market. [Online] [Accessed 20 August 2015].

Tan, Y.A., Low, K.W., Lee, C.K. & Low, K.S., 2010. Imaging technique for quantification of oil palm fruit ripeness and oil content. Eur. J. Lipid Sci. Tech., pp.838–43.

Teoh, C.H. 2002. The palm oil industry in Malaysia - from seed to frying pan. A report prepared for WWF-Switzerland. Selangor, Malaysia. 1-59pp.

Teoh, L.H., 1997. Development of Conductor-Backed Coplanar Waveguide Moisture Sensor, MSc Thesis. Malaysia: Universiti Putra.

Turner, P.D. & Gillibanks, R.A., 1974. Oil Palm Cultivation and Management. Kuala Kumpur, Malaysia: United Selangor Press.

USDA (2012) Oilseeds: world markets and trade. Available at: http://apps. fas.usda.gov/psdonline/circulars/oilseeds.pdf (accessed 10 December 2014)

Wan Ishak, W.I., Mohd. Zohadie, B.A. & Malik, A.H., 2000. Optical Properties for Mechanical Harvesting of Oil Palm. Journal of Oil Palm Research, 11(2), pp.38-45.

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BIODATA OF STUDENT

Kimia Saadat was born on 23rd April 1988 in Tehran, Iran. She obtained her Bachelor of Engineering in Electrical and Electronics from Azad University of Kermanshah, Iran in 2010. She is now working toward the M.S. degree in University Putra Malaysia. Her area of research interest includes: electronics; circuit theory and applications; sensor design, fabrication and development; smart solutions for industrial applications; smart devices.

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PUBLICATION

K. Saadat, M. M. Isa, S. Shafie (2015), A portable reflective colour sensor for assessing oil palm fruits maturity. In: 7 th International Conference on Sustainable Agriculture for Food, Energy and Industry in Regional and Global Context 2015.

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UNIVERSITI PUTRA MALAYSIA

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OIL PALM FRUIT RIPENESS CLASSIFICATION USING OPTICAL-BASED COLOUR SENSOR

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