2015_Hasinah_fyp2_2806 (2)

DESIGN AND DEVELOPMENT OF A PORTABLE NEAR INFRARED SPECTROSCOPY
NUR HASINAH BINTI HANIS
UNIVERSITI TUN HUSSEIN ONN MALAYSIA

DESIGN AND DEVELOPMENT OF A PORTABLE NEAR INFRARED
SPECTROSCOPY
(AE110106)
A thesis submitted in fulfilment of the requirement for the award of the
Degree in Bachelor Electronic Engineering with Honours
Faculty of Electric and Electronic Engineering
Universiti Tun Hussein Onn Malaysia
JUNE 2015

UNIVERSITI TUN HUSSEIN ONN MALAYSIA
STATUS CONFIRMATION FOR UNDERGRADUATE PROJECT REPORT
DESIGN AND DEVELOPMENT OF A PORTABLE NEAR – INFRARED
SPECTROSCOPY (NIRS)
ACADEMIC SESSION: 2014/2015
I, NUR HASINAH BINTI HANIS, agree to allow this Undergraduate Project Report to be kept at the
library under the following terms:
1. This Undergraduate Project Report is the property of the Universiti Tun Hussein Onn Malaysia.
2. The library has the right to make copies for educational purpose only.
3. The library is allowed to make copies of this report for educational exchange between higher
educational institution.
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to Malaysia as STIPULATED under the OFFICIAL SECRET
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FREE ACCESS
Approved by,
___________________________ __________________________
(WRITER’S SIGNITURE) (SUPERVISOR’S SIGNITURE)
NUR HASINAH BINTI HANIS DR CHIA KIM SENG
Permanent Address:
NO 7A, LOT 55
KM1 JLN BESAR PUSA
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94950 PUSA
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please attach the letter from the relevant authority/organization stating reasons and duration for such
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DECLARATION
I hereby declared that the work in this thesis is my own except for quotation and
summarize which have been duly acknowledged
Student : ………………………………………
Date : ………………………………………
Supervisor : ………………………………………
DR CHIA KIM SENG

ACKNOWLEDGEMENT
I am greatly indebted to many people for their support and encouragement during the
period this work was done.
I sincerely thank my supervisor Dr. Chia Kim Seng because guides me in this
period to make sure my project is done. He has been very helpful and was always ready
whenever I faced troubles regarding the project. He had given some excellent ideas
and without his guidance, this work would have been incomplete.
Deep thanks to my parents for their solicitude and helps especially in project
funding. I am grateful for all the help and kindness that I got from all my PSM section
members. I am also grateful to both of my panels Associate Prof. Ir. Dr. Babul Salam
and Dr. Rosli Omar because give some comment during the presentation to improve
my project.
Furthermore, my sincere thanks go to all faculties and staffs for their constant
support and help in the department and their suggestions.
Finally yet importantly, I would like to thank all of my colleagues for their
support and kindness during my study, backed me up with their moral support and
always motivated me throughout the project

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ABSTRACT
Near-Infrared Spectroscopy (NIRS) is one of non-destructive measurement
techniques. Most of the existing NIR Spectroscopy equipment is non-portable. Thus,
the sample must first be brought to the laboratory for testing and take some time to
know the result. By design and develop the portable NIR Spectroscopy, the user do
not need to bring the sample to the laboratory to see the result. OPT101 was selected
as the optical sensor to build up the IR circuit while 850nm and 940nm of the LED
were selected as the source to combine with optical sensor in the IR circuit. There a
three parameters will affect the reading of fruits; size, moisture and ripeness. Ten
samples for each of Japanese Apple Pear, Granny Smith Green Apple, Royal Gala Red
Apple, and Rose Apple were taken to get a ratio value based on the 850nm and 940nm
LEDs. From the average of the fruits, Royal Gala Red Apple shows the high ratio value
of 3.13 while Rose Apple has a ratio of 1.31. Therefore, from the whole analysis after
process properly, different ratio of the Royal Gala Red Apple and Rose Apple have
been proven. The different size of fruits also gives the different ratio of the fruits like
Sample 6 in Japanese Apple Pear.

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ABSTRAK
Near Infrared Spectroscopy (NIRS) ialah salah satu teknik pengukuran bukan
pemusnah. Kebanyakan peralatan NIR Spectroscopy yang sedia ada adalah jenis yang
tidak mudah alih. Oleh itu, sampel mesti dibawa ke makmal untuk diuji dan akan
mengambil sedikit masa untuk mengetahui keputusan ujian. Dengan reka bentuk dan
penambahbaikan NIR Spectroscopy yang sedia ada kepada peralatan mudah alih,
pengguna tidak perlu membawa sampel ke makmal untuk melihat hasilnya. OPT101
telah dipilih sebagai sensor optik untuk membina litar IR manakala 850nm dan 940nm
LED telah dipilih sebagai sumber untuk bergabung dengan sensor optik dalam litar IR.
Terdapat tiga parameter yang akan mempengaruhi bacaan buah-buahan; saiz,
kelembapan dan kematangan. Sepuluh sampel bagi setiap Lai, Granny Smith Apple
Green, Royal Gala Red Apple, dan Jambu Air telah diambil untuk mendapatkan nilai
nisbah daripada LED 850nm dan 940nm. Dari purata buah-buahan, Royal Gala Red
Apple menunjukkan nilai nisbah yang tinggi 3.13 manakala Jambu Air mempunyai
nisbah 1.31. Oleh itu, daripada keseluruhan analisis selepas proses yang betul, nisbah
yang berbeza diperolehi daripada Royal Gala Red Apple dan Jambu Air telah terbukti.
Saiz buah-buahan yang berbeza juga memberi nisbah yang berbeza kepada buah-
buahan seperti Sample 6 untuk Lai.

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TABLE OF CONTENTS
ACKNOWLEDGEMENT......................................................................................................I
ABSTRACT........................................................................................................................... II
ABSTRAK ............................................................................................................................III
TABLE OF CONTENTS ....................................................................................................IV
LIST OF TABLES...............................................................................................................VI
LIST OF FIGURES........................................................................................................... VII
LIST OF APPENDIXS........................................................................................................IX
LIST OF SYMBOLS AND ABBREVIATIONS ................................................................ X
CHAPTER 1 INTRODUCTION.......................................................................................... 1
1.1 BACKGROUND OF STUDY .................................................................................... 1
1.2 PROBLEM STATEMENTS....................................................................................... 2
1.3 OBJECTIVES............................................................................................................. 2
1.4 SCOPE OF PROJECT ................................................................................................ 3
CHAPTER 2 LITERATURE REVIEW.............................................................................. 4
2.1 INTRODUCTION ...................................................................................................... 4
2.1.2 Characteristics of NIR........................................................................................ 6
2.2 EXISTING RELATED WORKS................................................................................ 7
2.2.1 Summary of the Existing Related Works........................................................... 7
2.3 DESIGN AND CONCEPT SELECTION................................................................. 10
2.3.1 Case Study I: SLIM Spectrometer ................................................................... 10
2.3.2 Case Study II: Spectuino.................................................................................. 14
2.3.3 Case Study III: Monolithic Photodiode............................................................ 15
2.4 SUMMARY.............................................................................................................. 16
CHAPTER 3 RESEARCH METHODOLOGY................................................................ 17

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3.1 PROJECT OVERVIEW ........................................................................................... 17
3.2 SYSTEM OPERATIONAL...................................................................................... 19
3.2.1 METHODS ...................................................................................................... 22
3.3 SYSTEM ARCHITECTURE.................................................................................... 23
3.3.1 HARDWARE................................................................................................... 23
3.3.1.1 OPT101............................................................................................................... 23
3.3.2 SOFTWARE .................................................................................................... 24
3.3.2.1 Schematic Design ............................................................................................... 24
3.3.2.2 PCB Layout ........................................................................................................ 25
CHAPTER 4 RESULT AND DISCUSSION..................................................................... 29
4.2 RESULT TAKEN..................................................................................................... 31
4.3 DISCUSSION RESULT........................................................................................... 33
4.3.1 JAPANESE APPLE PEAR.............................................................................. 34
3.2 GRANNY SMITH GREEN APPLE .................................................................... 37
4.3.3 ROYAL GALA RED APPLE.......................................................................... 40
4.3.4 ROSE APPLE .................................................................................................. 42
4.3.4 RATIO OF THE DIFFERENT FRUITS ......................................................... 45
CHAPTER 5 CONCLUSION............................................................................................. 49
5.1 CONCLUSION......................................................................................................... 49
5.2 FUTURE RECOMMENDATION............................................................................ 50
PROJECT PLAN................................................................................................................. 51
REFERENCES..................................................................................................................... 52
APPENDIX.......................................................................................................APPENDIX A

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LIST OF TABLES
TABLE 2.1: THE PROS AND CON BETWEEN THE DEVICES ........................................ 8
TABLE 2.2: CHARACTERISTIC OF THE DETECTORS.................................................... 9
TABLE 2.3: ELEMENTS OF CONVENTIONAL AND SLIM SPECTROMETERS......... 13

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LIST OF FIGURES
FIGURE 1.1: THE ELECTROMAGNETIC SPECTRUM [7]................................................ 2
FIGURE 2.1: SETUP FOR THE ACQUISITION OF (A) REFLECTANCE, (B)
TRANSMITTANCE, AND (C) INTERACTANCE SPECTRA, WITH (I) THE LIGHT
SOURCE, (II) FRUIT, (III) MONOCHROMATOR/DETECTOR, (IV) LIGHT BARRIER,
AND (V) SUPPORT. [10]....................................................................................................... 6
FIGURE 2.2: THE LAYOUT OF THE BASIC COMPONENTS OF THE SOLID-STATE
SPECTROMETER [14]......................................................................................................... 10
FIGURE 2.3: SCHEMATIC OF THE SLIM SPECTROPHOTOMETER [14].................... 11
FIGURE 2.4: FLOW DIAGRAM OF THE STEPS IN THE MCU PROGRAM [14]......... 13
FIGURE 2.5: SCHEMATIC OF THE SPECTRUINO SPECTROPHOTOMETER [15]..... 14
FIGURE 2.6: SCHEMATIC OF THE INSTRUMENT ANALOG ELECTRONICS [17]... 15
FIGURE 2.7: SPECTRAL RESPONSITIVITY OF OPT101 V/S WAVELENGTH OF
INCIDENT LIGHT [17]........................................................................................................ 16
FIGURE 3.1: FLOWCHART OF OVERALL PROJECT..................................................... 18
FIGURE 3.2: BLOCK DIAGRAM OF NIR SPECTROMETER ......................................... 19
FIGURE 3.3: REFLECTANCE MODE OF NIR SPECTROMETER.................................. 20
FIGURE 3.4: FLOWCHART OF THE NIR SPECTROMETER ......................................... 21
FIGURE 3.5: CIRCUIT OF OPT101 CHIP [17]................................................................... 23
FIGURE 3.6: OUTPUT CONNECTION OF OPT101 [17].................................................. 24
FIGURE 3.7: 850NM LEDS CONNECTION....................................................................... 25
FIGURE 3.8: 940NM LEDS CONNECTION....................................................................... 25
FIGURE 3.9: MULTI LEDS CONNECTION ...................................................................... 26
FIGURE 3.10: PCB LAYOUT.............................................................................................. 27

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FIGURE 3.11: MULTI LEDS CONNECTION .................................................................... 27
FIGURE 3.12: DISTANCE BETWEEN LEDS AND OPT101............................................ 28
FIGURE 4.1: FROM TOP..................................................................................................... 29
FIGURE 4.2: FROM FRONT................................................................................................ 30
FIGURE 4.3: FROM SIDE EDGE ........................................................................................ 30
FIGURE 4.4: SENSOR CALIBRATION.............................................................................. 31
FIGURE 4.5: CALIBRATION READING........................................................................... 32
FIGURE 4.6: CALIBRATION READING FOR 850NM..................................................... 32
FIGURE 4.7: CALIBRATION READING FOR 940NM..................................................... 33
FIGURE 4.8: VOLTAGE VALUE AT 850NM.................................................................... 34
FIGURE 4.9: VOLTAGE VALUE AT 940NM.................................................................... 35
FIGURE 4.10: AVERAGE OF VOLTAGE VALUE AT 850NM AND 940NM................. 36
FIGURE 4.11: RATIO OF THE 10 SAMPLES.................................................................... 36
FIGURE 4.12: VOLTAGE VALUE AT 850NM.................................................................. 37
FIGURE 4.18: AVERAGE VOLTAGE VALUE AT 850NM AND 940NM....................... 41
FIGURE 4.19: SPECTRA INTENSITY OF THE 10 SAMPLES......................................... 42
FIGURE 4.24: VOLTAGE VALUE OF THE DIFFERENT FRUIT TYPES....................... 46
FIGURE 4.25: RATIO OF THE DIFFERENT FRUITS....................................................... 47
FIGURE 4.26: AVERAGE RATIO INTENSITY OF THE DIFFERENT FRUITS............. 48

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LIST OF APPENDIXS
CHARACTERISTICS OF RAMAN, MIR, AND NIR SPECTROSCOPIES [11] ...................
............................................................................................................................APPENDIX A
SOURCE CODE.................................................................................................APPENDIX C
JAPANESE APPLE PEAR (LAI) ......................................................................APPENDIX D
GRANNY SMITH GREEN APPLE...................................................................APPENDIX G
ROYAL GALA RED APPLE .............................................................................APPENDIX J
ROSE APPLE (JAMBU AIR)...........................................................................APPENDIX M

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LIST OF SYMBOLS AND ABBREVIATIONS
IR Infrared
NIR Near Infrared
UV Ultra-Violet
Vis Visible
MIR Middle – Infrared
ATR Attenuated Total Reflection
LED Light emitted diode
ADC Analog to Digital Converter
IC Integrated Circuit
TIA Transimpedence Amplifier
BJT Biased Junction Transistor
A Attenuation of light
I Intensity of transmitted light
Io Intensity of incident light
C Concentration of light
d Direct path length of photon
EEPROM Electrically Erasable Programmable Read-Only Memory
RISC Reduced Instruction Set Computer
PC Personal Computer

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RAM Random Access Memory
MCU Multipoint Control Unit
PbS Plumbous Sulfide/Lead Sulfide
PbSe Lead (II) Selenide
InGaAs Indium Gallium Arsenide
InSb/InAs Indium Antimonide/Indium Arsenide
CCD Charge Coupled Device

CHAPTER 1
INTRODUCTION
1.1 BACKGROUND OF STUDY
Spectroscopy is a scientific discipline studying interactions of light with matter. The
electromagnetic spectrum represented the light of different wavelengths. The IR region
is generally divided into three intervals; near, mid and far-IR. The near-IR (NIR)
region covers the wavelength range 750 to 2500 nm [1]. Figure 1.1 shows the
electromagnetic spectrum.
Near infrared spectroscopy (NIRS) a sensor that can be used to study a non-
destructive technique. Non-destructive technique is one of the technique to evaluate
the properties of a material, component or system without causing damage. The
potential applications of NIRS technology have been already glorious and have open
doors for a spread of analysis investigations of applied science and human factors [2].
The examples of the application are predicting soluble solids content of pineapple [3],
predicting soluble solids content of pears [4] and sugar measuring in mango [5].
Portable analytical instruments have become more and more useful in a wide
variety of fields related to environmental and process monitoring, medical diagnosis,
explosives detection, chemical emergencies and so forth. With LEDs and sensors that
will be developed, it is possible to construct small, portable and low cost NIR

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Spectroscopy instruments that can analysis the chemical compounds relevant for
diagnosis and monitoring [6].
Figure 1.1: The electromagnetic spectrum [7]
1.2 PROBLEM STATEMENTS
Most of the users want to know the result of sample without bringing the sample back
to the laboratory to the analysis, however, most of the equipment are not portable and
difficult to use on the field. The sample must first be brought to the laboratory for
testing and take some time to know the result.
1.3 OBJECTIVES
The objectives of this project are:
i. To develop a prototype of a portable NIR Spectroscopy
ii. To measure the ratio for different fruits

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1.4 SCOPE OF PROJECT
The scopes of this project are:
i. The wavelength of IR LEDs was selected; 850nm and 940nm
ii. Photodiode OPT101 was selected as a sensor
iii. 9V battery was used as a power supply
iv. Four different fruits were selected as a sample
a. Japanese Apple Pear (Lai)
b. Granny Smith Green Apple
c. Royal Gala Red Apple
d. Rose Apple (Jambu Air)

CHAPTER 2
LITERATURE REVIEW
2.1 INTRODUCTION
NIR Spectroscopy is a spectroscopic technique based on molecular overtones and
combination vibration of a particular atom [2, 8]. Vibration spectroscopic technique
belongs to the IR light spectrum from regarding 750 to 2500 nm [1] and known as
Near-Infrared spectrum. In IR region, the molar absorption factor is incredibly small.
The wavelength about 718nm, 768nm and 856nm have a prestigious wavelength as
the predictors of prophetical models achieved higher prophetical accuracy, compared
to that used either the complete spectrum or the chosen spectral segments in solid
sample [3].
NIR spectra only have a few significant peaks, but they are exceptionally
information-rich due to the number of overlapping absorption bands. Thus,
interpretation of NIR spectra is usually combined with mathematical and statistical
methods (Chemometric methods) in order to extract the necessary information
There are three physical principles of NIR Spectroscopy; light absorption, light
scattering and light attenuation [6]. Absorption of light happens to specific
wavelengths. It determined by the molecular properties of the materials within the light
path. At a similar time, scattered photon travel direction relies upon the wavelength.
Light attenuation represented as a formula.

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𝐴 = log
𝐼
𝐼 𝑂
= 𝜀0 𝐶. 𝑑
Where,
A is an Attenuation of light
I is an Intensity of transmitted light
Io is an Intensity of incident light
C is a concentration of light
d is a direct path length of photon
Some important chemical quality features like the total sugar content,
scattering is related to the microstructure of the tissue and the macroscopic texture
properties of the fruit is related in Vis/NIR range of absorption [9].
Figure 2.1 shows the three different types of acquisition mode to collect the
spectra intensity from the fruit. The Vis/NIR reflectance, interactance or transmittance
spectrum of the fruit is typically set based on a large calibration dataset using
chemometrical techniques to estimate the quality features.
In reflectance mode, light source and detector are mounted under a specific
angle mostly about 45º to avoid specular reflection. The light source is in the opposite
position of the detector in transmittance mode, while in interactance mode the light
source and detector are positioned parallel to each other in such a way that light due to
specular reflection cannot directly enter the detector.

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Figure 2.1: Setup for the acquisition of (a) reflectance, (b) transmittance, and (c) interactance spectra,
with (i) the light source, (ii) fruit, (iii) monochromator/detector, (iv) light barrier, and (v) support. [10]
2.1.2 Characteristics of NIR
Table 2.1 shows the three different spectroscopic techniques that are possible to gain
rapid and accurate information of solid and liquid sample from the high – resolution
spectra. All of the techniques are economic and enable qualitative and quantitative as
well as non-invasive and non-destructive analysis.
The most flexible technique is NIRS [11] because it allow the determination of
multiple values in a single determination by using the chemometric evaluation tools
and light-fibre optics. NIRS ideally suited for quality control of raw materials because
it can analyse through some translucent packaging materials. Besides that, the spectra
are impacted by physical parameters like particle size, density, and moisture content.

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2.2 EXISTING RELATED WORKS
A. Spectrophotometer built in Nicaragua [8].
The device was constructed for less than $100, which provides a frame of
reference to from device cost.
B. DIY Spectro II
Simple spectrophotometer made with Arduino microcontroller. The
architecture was similar like Spectuino.
C. A Low cost LED based Spectrophotometer [12].
Helped to determine LED as a light source to help eliminate a diffraction
grating. It has the option of 10 hours powered up battery.
D. Camera Phone used as a spectrophotometer.
While an interesting option, due to phones being readily available in the target
country [13]. The design is not well packaged or durable.
2.2.1 Summary of the Existing Related Works
Table 2.1 shows the advantages and disadvantages of the existing related works of the
spectroscopy. This related works will be use as references to design a portable NIR
spectroscopy.

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TABLE 2.1: THE PROS AND CON BETWEEN THE DEVICES
Devices/Equipment Advantages Disadvantages
Spectrophotometer built in
Nicaragua
Affordable price Not portable
DIY Spectro II
Suitable for visible
wavelength
Not suitable for NIR
wavelength
A Low cost LED based
Spectrophotometer
Affordable price
Using grating, difficult to get
NIR wavelength
Camera Phone used as a
spectrophotometer
Portable devices Not durable
2.2.2 The Main Materials to Develop NIR Spectroscopy
A. Optical Components
i. Mirror
ii. Lens
iii. Fibre Optics
a. Bevelled single fibre
b. Bevelled fibre including sending and receiving fibre
c. Bevelled fibre bundle
d. Banded fibre bundle
B. Light Sources
i. LED
ii. Bulb (tungsten lamp)
C. Collimator [2]
i. Light diode array
ii. Filter
iii. Acousto-optical tuneable filter
iv. Grating
v. Interferometer
vi. Hadamard mask

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D. Detector
TABLE 2.2: CHARACTERISTIC OF THE DETECTORS
Detector
Wavelength
Range (nm)
Region Responsivity/Detectivity Remark
PbS
1100-2500
400-2600
1100-4500
NIR
UV-NIR
NIR-MIR
Intermediate
Pbs ‘sandwiched’
with silicon
photodiode, are
often used for VIS-
NIR
PbSe 1100-5000 NIR-MIR Fast/High
The detector must
be cooled with
liquid nitrogen
InGaAs 700-1700
NIR
NIR
Raman
Fast/Very high
Linear arrays high
sensitivity,
dynamic range,
SNR performance
and stability
FT-NIR
Diode arrays
spectrometers
InSb/InAs 1000-5500
NIR
MIR
IR
Fast/Very high
High quality
detector
Detector
photodiodes
CCD 800-2200 NIR Fast/High
High performance
detector
Applied in cameras
Diode arrays
spectrometers
Most of the conventional design uses an optical component to determine the spectral
resolution. The new design will propose to use only LED because the LED was filtered
and already have its own wavelength. The LED was chosen to design this project
because it has a low cost and low power consumption. Thus, with the filtered LED
there is no need to use optical component and collimator in the design.

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2.3 DESIGN AND CONCEPT SELECTION
2.3.1 Case Study I: SLIM Spectrometer
A new spectrometer, here delineated the SLIM spectrometer, was developed that
exploits the tiny size and low price of solid-state electronic devices. An acronym SLIM
know as a Simple, Low-power, Inexpensive and Microcontroller-based.
In this device, configured with a flow-cell, LED, single-chip integrated circuit
Photodetector, embedded microcontrollers, and batteries replace traditional
optoelectronic components, computer, and power supplies [8, 14].
Figure 2.2: The layout of the basic components of the solid-state spectrometer [14]
The SLIM design replaced components in traditional designs with alternatives
and appears feasible can be used in resource-limited settings. Their concern of SLIM
design that has utilized are noisier and has lower resolution than standard models [8].

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Figure 2.3: Schematic of the SLIM Spectrophotometer [14]
The electronic parts were chosen to match the low cost and low power consumption
of the LED. The duty cycle of the LED can determine the lifetime of the battery. An
alkaline 9V battery will power a LED with 10 mAs of currents for about 60 hours [8].
The IC chosen to serve as the embedded microcontroller in these devices is the
PIC-16F84 that has an 8-bit MCU with 1K of program memory and 68 bytes of data
RAM. It is a RISC (reduced instruction set computer) paradigm chips, thus there are
only 35 assembly language instructions. An 8-bit MCU was chosen because its cost,

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size, power consumption, and computational power are well suited to this particular
application.
The photodetector is the TSL230 programmable light-to-frequency converter
manufactured. This IC a configurable grid of photodiodes and a current-to-frequency
converter in a single package. This photodetector is ideals of this application because
no separate ADC chip or domain converters are required. TSL230 is the best
photodetector for ultraviolet-to-visible-light in the range of 300 nm to 700 nm.
A DS1307 serial real clock were used as the timekeeping device. This IC a
38.768 kHz crystal to keep track a time of seconds, minutes, hours, day, month and
year [8].
The memory of this device is an X24 128 128K-bit serial EEPROM that is
organized in a 16K x 8-bit. It is accustomed stores the timestamp data together with
light intensity data into a formatted data block. Both read and write operations are
controlled via the same bus used for communication with the real time clock. It
provides a functional amount of storage with a minimum of hardware lines and
software overhead for non-volatile data storage and retrieval. The storage capacity of
those constantly being increased and space for storing is not a problem in the future
because the memory may be simply expanded upon adding many EEPROM chips.
In this new design the small size, low power consumption, and simplicity of
the LED light source is well matched to the other components of the spectrometer.
This design most suitable for visible light spectrometer because TSL 230 is the best
photodetector in range of 300nm to 700nm.
Based on Figure 2.4, the decision point "Acquire new data?" is decided in
favour of the state of the push button switch. The Sequence of events on the right is
executed whenever the spectrometer measures an intensity. The current data will be
reset to acquire new data. Before the samples were measured, the dark will be
measured first to calibrate the device.

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Figure 2.4: Flow diagram of the steps in the MCU program [14]
Table 2.3 shows the comparison between conventional and SLIM spectrometers.
SLIM spectrometer is the best spectrometers because it have characteristics to be a
portable device if acrylic flow cell can be replace with other portable component that
has the same function.
Conventional spectrometer can detected two different range of wavelength
simultaneously while SLIM spectrometer only detect visible wavelength.
TABLE 2.3: ELEMENTS OF CONVENTIONAL AND SLIM SPECTROMETERS
COMPONENT CONVENTIONAL SLIM
Light Source Tungsten lamp LED
Sample Delivery Cuvette Acrylic flow cell
Detector Photodiode, PMT, Diode Array Photodiode IC
Data Storage Computer Disk EEPROM
Control Unit PC Microcontroller
Wavelength
250nm to 700nm
450nm to 800nm
300nm to 700nm

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2.3.2 Case Study II: Spectuino
The Spectruino replaces standard elements with more refined equipment to resist harsh
environments. The Spectruino is easy to use with design of two buttons and easy
instructions should be no trouble for anyone to operate.
The monochromator and costly light source is replaced with a microcontroller
and LED. The cost that is faced much from the case and serial display used. The
programming of the Arduino may make this device as accurate as any
spectrophotometer in the market [8]. Two simple buttons to choose from the “learning”
and “identify” mode make it user-friendly.
The learn mode a better-known sample is tested and its values are kept within
the database of the Arduino. In the identify mode, the five led are shone at the sample
and an algorithmic program identifies the liquid. Figure 2.5 shows the Spectruino’s
schematic.
Figure 2.5: Schematic of the Spectruino spectrophotometer [15]

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2.3.3 Case Study III: Monolithic Photodiode
The emitted optical intensities were adjusted by controlling currents through the LED
that might be between 10 to 50mA [16]. Received light is converted into a voltage
signal using an OPT101 photodiode with an integrated transimpedence amplifier
(TIA).
Figure 2.6 shows the schematic of the instrument Analog electronics. A
narrowly targeted beam falling on only the photodiode can provide improved settling
times compared to a source that uniformly illuminates the full area of the die. If a
narrowly targeted light source were to miss the photodiode area and fall only on the
op amp circuitry, the OPT101 would not perform properly [17].
Figure 2.6: Schematic of the Instrument Analog Electronics [17].
A photo-detector is used to convert the light signal into electrical signals. The
electrical signal's amplitude is very low. Thus, to detect the signal, an amplifier is
added directly after the photo-detector. This amplifier is known as a transimpedence
amplifier (TIA) which may be used not only to amplify however also to convert the
current into voltage.

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IC OPT101 includes both of the photo-detectors and of TIA together [17].
Using this IC chip, build the TIA is unnecessary. This chip will provide a sensible
performance output signal [18]. The used of OPT101 combines a photodiode and the
transimpedence amplifier in the same chip may reduce some drawbacks like overflow
currents, interferences, and parasitic capacitances [19]. The design shown in Figure
2.6 created a versatile system capable of measuring absorbency in a wide range given
the configurable optical power-to-voltage gain.
Figure 2.7: Spectral Responsitivity of OPT101 v/s Wavelength of Incident Light [17]
The wavelength of Infrared light varies from 700nm to 1100nm and generally, IR LED
are available with 880nm. Based on Figure 2.7, OPT101 gives very good spectral
responsitivity for IR from 800nm to 950nm [20].
2.4 SUMMARY
Thus, for this project the best choice to design portable NIR spectroscopy is by using
specific wavelengths of IR LED in between 750nm to 950nm because the photodiode
OPT101 will give a good result of detecting spectra in that range of the spectrum. An
Arduino UNO will be used to connect the IR circuit with the PC to display the output
on the serial monitor.

CHAPTER 3
RESEARCH METHODOLOGY
3.1 PROJECT OVERVIEW
Figure 3.1 shows a flowchart of methodology implemented during this project. NIR
spectroscopy has a varies in different ways of design and development like the size,
shape and mode that will be depends on the aim, objectives and applications.
Nowadays, there are plenty of research, tests and trials being conducted to discover
the most effective, simplest and cost effective ways of NIR spectroscopy. Generally,
NIR spectroscopy consists of different design options, various types of sensors and so
on. Each design component has its own specific functions, advantages and
disadvantages compared to others design. Therefore, the purpose of this chapter is to
deliver the first hand conceptual ideas of the vital criteria such as the most suitable,
user-friendly, low cost and commercially available for this project.
In this chapter, a brief introduction of the selected component that has use will
be described. For the hardware section, the selected component and tools used in this
design will be listed clearly regarding their specification and characteristics. Next, the
procedures of setting up the software are included in the software section.

18
START
RESEARCH
SENSOR SELECTION
CIRCUIT
CONSTRUCT ON
BREADBOARD WITH
ARDUINO UNO
PROGRAMMING USING
SKICH (ARDUINO
SOFTWARE)
RESULT TAKEN
DOCUMENTATION
END
Troubleshooting
Figure 3.1: Flowchart of Overall Project

19
3.2 SYSTEM OPERATIONAL
The methodology for the implementation of this proposed analysing intensity of
different fruit based on two different wavelengths refer to Figure 3.2.
IR SENSOR
ARDUINO
UNO
SERIAL
MONITOR
ARDUINO
PROGRAM
DIGITAL CONTROL
OUTPUT DISPLAY
Figure 3.2: Block diagram of NIR Spectrometer
According to the suggested model, the experimental system is fabricated as
shown in Figure 3.2. The IR sensor consists of IR LED and OPT101 optical sensor.
An IR sensor will sense the spectral intensity of a fruit and OPT101 will give a voltage
as an output. Arduino UNO Board process the voltage and transfer to a PC using the
Arduino software for the display analogue value of the wavelength intensity. The
voltage value will be displayed on the serial monitor.
IR sensor will detect the spectrum on fruit tissue based on reflectance was
shown in Figure 3.3. In the reflectance mode, a higher probability is given to the
incident beam to interact with the sample. Hence, the emerging beam contains more
information on the sample constituents and reflects better the actual composition of
the sample.

20
Figure 3.3: Reflectance mode of NIR Spectrometer
Figure 3.4 shows the flowchart of the spectrometer. The sample is detected by
the light source that consist of IR LEDs that will emit the light to the spectrometer to
detect the intensity of the sample. The microcontroller will interfaced the result than
display it on serial monitor.
The LED with 850nm wavelength will be switched ON first to take a reading
on the five parts of each sample. During the reading taken, the 850nm LED will switch
OFF then 940nm LED will switch ON to take a reading at the sample by parts
alternatingly. Means, when Part 1 was taken on 850nm LEDs then 940nm LED will
switch ON while 850nm LED is switched OFF and that goes on with the Part 2 to Part
5 continuously.

21
START
INTENSITY
SPECTRUM
DETECTED
BY IR
SENSOR
WAVELENGTH
(850nm & 940nm)
DISPLAY ON
SERIAL
MONITOR
END
Figure 3.4: Flowchart of the NIR Spectrometer
To get a spectra intensity ratio, the value from a wavelength of 850nm and
940nm will be taken separated. At the end, the voltage value of the each sample of the
fruit will be divided to get a ratio as:
𝑉850𝑛𝑚
𝑉940𝑛𝑚
= Ratio

22
3.2.1 METHODS
i. Stick the masking tape on the sample’s surface to write down the samples
number.
ii. The sample will be placed at the top of the tube to take the reading.
a. Each samples will have five part to take the reading
b. Each of Part 1 to Part 3 is 1/3 of the body sample, while Part 4 is top of
the sample and Part 5 is at the bottom.
iii. To take Part 1 reading, place the Part 1 region facing in the tube.
a. Switch ON the 850nm LEDs’, take the reading
b. Do not rotate the sample until both of reading for 850nm and 940nm
were taken.
c. Switch OFF the 850nm LEDs and switch ON the 940nm LEDs, take
the reading of 940nm.
d. These steps (a – c) will continuous until all the five part were done.
iv. Change the Sample 1 to Sample 2 until Sample 10
a. Repeat step iii(a) until iii(d)
v. After all the parts of the sample were taken, get the average for each samples
simply using this equation :
𝑃𝑎𝑟𝑡 1+𝑃𝑎𝑟𝑡 2+𝑃𝑎𝑟𝑡 3+𝑃𝑎𝑟𝑡 4+𝑃𝑎𝑟𝑡 5
5
= 𝑎𝑣𝑒𝑟𝑎𝑔𝑒
a. This equation will used on reading for 850nm and 940nm separately.
vi. When the average of a sample was calculated for 850nm and 940nm, then
calculate the ratio simply using :
𝑉850𝑛𝑚
𝑉940𝑛𝑚
= 𝑅𝑎𝑡𝑖𝑜
a. Calculate the ratio for all the samples (Sample 1 – Sample 10)
vii. Repeat step i to vi for the different types of fruit.

23
3.3 SYSTEM ARCHITECTURE
There are two parts on system architectures will be explained here. There are hardware
and software part.
3.3.1 HARDWARE
3.3.1.1 OPT101
Figure 3.5 shows the IC chip known as OPT101. This IC chip has 1MΩ internal
resistance and up to 14 kHz bandwidth. The open loop gain is 90 dB, causative a low
offset voltage about 0.5 V. The minimum operating a power supply is 2.7 V,
consuming a relatively low power [17]. Using this IC chip, there is no need to build
TIA. This chip will give a good performance output signal.
Figure 3.5: Circuit of OPT101 Chip [17]
The IR LED is driven by a constant current source created using an NPN BJT. Figure
3.6 shows the connected of BJT and biased at 5V to provide a current of 10mA.
The OPT101 is sensitive to IR LED; however, it can be used without too many
problems occur. The OPT101 can obtain any IR at low frequencies, but high

24
frequencies the interference is an amplitude modulation of the present signal may
easily be filtered out. Figure 3.6 shows the basic connection of the output pin of
OPT101. MPSA12 is a Darlington Transistors consists of a pair of bipolar transistors
that are connected to provide a very high-current gain from a low-base current. The
input transistor’s emitter is connected to the output transistor’s base and their collectors
are tied together at 5V. Therefore, the output transistor amplifies the current that is
amplified by the input transistor even further.
Figure 3.6: Output connection of OPT101 [17]
3.3.2 SOFTWARE
3.3.2.1 Schematic Design
The circuit of IR sensor that was designed using LED and OPT101. The function of
the potentiometer is to adjust LED sensitivity. The incident angle between LED and
OPT101 should be ±200
[17] to give a sensor good response. Vs of OPT101 is 1.3V,
while set value is 5V. Therefore, the Vo is 3.7V.
To choose the design of LED whether it in series or parallel, the LED
Calculator – Online [21] software was used. The calculation for 850nm LEDs was
shows in Figure 3.7 and for 940nm was shows on Figure 3.8.

25
Figure 3.7: 850nm LEDs connection
Figure 3.8: 940nm LEDs connection
3.3.2.2 PCB Layout
Figure 3.9 shows the design of multi LED with photodiode OPT101. The LEDs were
arranged around the OPT101 to ensure the OPT101 can absorb the spectral intensity
when infrared is emitted. The design used two LEDs for 940nm and four LEDs for
850nm is to make sure the intensity is enough to emit. 9V battery is used as the power

26
source for the LEDs. The sensor and LEDs were mounted on the printed circuit board
(PCB) by designing the circuit using Fritzing software.
The LEDs is connected in series circuit to make sure there is only one path
from the source through all of the LEDs and back to the source. This means that all of
the current in the circuit must flow through all of the LEDs. Series connection do not
overheat easily do not blow out very fast while in parallel connection, there are lot of
wire will be used and the inner resistance will increases. Parallel circuit is suitable to
use in house design because it provide more current than one source can produce.
Unless all in parallel have the same voltage, current would flow from one source into
the other and will result in loss of power.
Figure 3.9: Multi LEDs connection
The arrangement of LED and the OPT101 is placed near to each other to maximum
light passes through the measurement site and has a high probability of coming out
near the photo sensor. Figure 3.10 and Figure 3.11 shows the desire circuit design.

27
Figure 3.10: PCB layout
Figure 3.11: Multi LEDs connection
Figure 3.12 shows the actual distances between LEDs and OPT101. The distance was
selected is 1.5cm. To get 45º in reflectance mode, the height between sample and
OPT101 is about 1.5cm. This calculation is based on Trigonometric Theory of Right
Angle Triangle.

28
Figure 3.12: Distance between LEDs and OPT101
Calculation:
𝑡𝑎𝑛 45º =
150
𝑥
𝑥 =
150
tan 45
= 150
= 1.50 cm

29
CHAPTER 4
RESULT AND DISCUSSION
4.1 HARDWARE DESIGN
Figure 4.1 until Figure 4.3 shows the hardware design from the top side, front side and
backside.
Figure 4.1: From Top
850nm Switch 940nm Switch

30
Figure 4.2: From Front
Figure 4.3: From side edge

31
Figure 4.4: Sensor Calibration
When the battery switch ‘ON’, the IR LED will light. The LEDs and sensor was
designed to place in a dark area to make sure the sensor will detect the light intensity.
The sample will be placed in the top of the tube to make sure sample in reflectance
mode.
4.2 RESULT TAKEN
The serial monitor will shows the ±0. 00 value when both of 850nm and 940nm LEDs
were switched OFF was shown in Figure 4.5. This calibration to make sure there is no
reading taken when the switch is in OFF mode.
The ratio intensity is come from the ratio of 850nm/940nm. The ratio between
the two LEDs will shows the ratio intensity value.

32
Figure 4.5: Calibration reading
Figure 4.6 shows the reading for 850nm LEDs when its switch ON. The voltage
reading at 850nm LED will be ±0.17V, while Figure 4.7 shows the 940nm LED
calibration reading. The voltage at 940nm LED will be ±0.06V.
Figure 4.6: Calibration reading for 850nm

33
Figure 4.7: Calibration reading for 940nm
Therefore, the spectral intensity of calibration is:
𝑉850𝑛𝑚
𝑉940𝑛𝑚
=
0.17
0.06
= 2.83
4.3 DISCUSSION RESULT
There are four types of fruits were used to compare the ratio at the 850nm and 940nm
wavelength. There are Japanese Apple Pear, Granny Smith Green Apple, Royal Gala
Red Apple, and Rose Apple. These four types of fruits were randomly chosen to
compare they ratio because there is no information regarding the fruit’s ratio based on
the wavelength.
Each fruit will have 10 samples that are in different of size and quality. To take
the reading, each sample will be rotated at five different parts to assume it read the
whole sample. The step will repeat for 10 samples for four different fruits.

34
4.3.1 JAPANESE APPLE PEAR
Figure 4.8 shows the voltage value of the sample at 850nm wavelength. From the
graph, Sample 6 shows the lowest of voltage of 0.36V to 0.43V. The highest reading
of the Japanese Apple Pear is Sample 1 with a voltage value of 0.84V to 0.85V.
There are several factors affecting the reading of the voltage during conduct
the experiment. One of them is the fruit quality. Sample 6 has a lower voltage value
because this sample is not yet ripe and the size is smaller compared to the other
samples.
Figure 4.8: Voltage value at 850nm
From the Figure 4.9, the voltage reading of the sample at a 940nm wavelength is on
average about 0.44V to 0.54V.
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
1 2 3 4 5 6 7 8 9 10
VOLTAGE(V)
SAMPLE NUMBER
SAMPLE'S VOLTAGE AT 850NM
READING 1 READING 2 READING 3 READING 4 READING 5

35
To compare the voltage value between wavelengths of 850nm and 940nm, Figure 4.10
shows the average value of the voltage for Sample 1 to Sample 10 for both of the
wavelength. In summary, the wavelength 840nm emit more spectra compare than the
wavelength 940nm because the voltage value at 840nm higher than at 940nm. Means,
wavelength 840nm can detect more acidic concentration compare than wavelength
940nm.
Figure 4.11 shows the ratio of ten samples of Japanese Apple Pear. The reading
that was shows has a different ratio value. Sample 6 is farthest from the trend line with
the value of 0.86. The value is due to the voltage reading at the 850nm wavelength.
Thus, the different size of the sample will affect the ratio of the fruits.
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
1 2 3 4 5 6 7 8 9 10
VOLTAGE(V)
SAMPLE NUMBER
SAMPLE'S VOLTAGE AT 940nm

36
Figure 4.10: Average of voltage value at 850nm and 940nm
Figure 4.11: Ratio of the 10 samples
0.84
0.48
0.78
0.56
0.71
0.56
0.76
0.54
0.77
0.48
0.38
0.44
0.73
0.48
0.69
0.46
0.55
0.43
0.64
0.44
0.00
0.20
0.40
0.60
0.80
1.00
850nm 940nm
VOLTAGE(V)
WAVELENGTH(nm)
AVERAGE OF VOLTAGE VALUE FOR EACH JAPANESE APPLE
PEAR
SAMPLE 1 SAMPLE 2 SAMPLE 3 SAMPLE 4 SAMPLE 5
1.75
1.39
1.27
1.41
1.60
0.86
1.52 1.50
1.28
1.45
0.20
0.40
0.60
0.80
1.00
1.20
1.40
1.60
1.80
0 1 2 3 4 5 6 7 8 9 10
RATIO
SAMPLE NUMBER
RATIO OF THE 10 SAMPLES FOR JAPANESE APPLE PEAR

37
3.2 GRANNY SMITH GREEN APPLE
The reading for Granny Smith Green Apple is not stable at the 840nm wavelength.
Figure 4.12 shows the voltage value of the ten samples at a wavelength of 850nm. The
highest voltage value is Sample 6 with 0.71V and the lowest voltage value is Sample
5 and Sample 10 with 0.67V.
Figure 4.13 shows the voltage value of the ten samples at wavelengths at
940nm. The voltage looks stable at this wavelength. The voltage value is in average of
0.37V to 0.52V. Sample 5 shows the lowest voltage about 0.37V while Sample 2 has
the highest voltage value about 0.52V.
At Sample 5, there are two different parts have a lower voltage. This
phenomena occur because of the parts have some bruise on it. Thus, the reading will
differ with the other party that does not have bruises.
0.63
0.64
0.65
0.66
0.67
0.68
0.69
0.70
0.71
0.72
1 2 3 4 5 6 7 8 9 10
VOLTAGE(V)
SAMPLE NUMBER
VOLTAGE VALUE AT 850nm

38
Figure 4.13: Voltage Value at 940nm
Figure 4.14 shows the average voltage value of the ten samples at 8.50nm and 940nm
wavelengths. The voltage value at 850nm is high compared than at 940nm. To get a
spectra intensity ratio, the sample's value of the 850nm wavelength will be divided by
the value at 940nm wavelength.
The result of the spectra intensity ratio for Granny Smith Green Apple was
shows in Figure 4.15. Sample 2 shows the lower ratio value while Sample 5 has a large
ratio value with 1.33 and 1.81 respectively.
0.00
0.10
0.20
0.30
0.40
0.50
0.60
1 2 3 4 5 6 7 8 9 10
VOLTAGE(V)
SAMPLE NUMBER
READING 1 READING READING 3 READING 4 READING 5

39
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
850nm 940nm
VOLTAGE(V)
WAVELENGTH
AVERAGE OF VOLTAGE VALUE FOR EACH GRANNY SMITH
GREEN APPLE
1.49
1.33
1.50
1.60
1.81
1.67
1.60 1.58
1.55
1.68
1.20
1.30
1.40
1.50
1.60
1.70
1.80
1.90
0 1 2 3 4 5 6 7 8 9 10
RATIO
SAMPLE NUMBER
RATIO OF 10 SAMPLES FORGRANNY SMITH GREEN
APPLE

40
4.3.3 ROYAL GALA RED APPLE
Figure 4.16 shows the voltage value of the samples at 840nm wavelength. The voltage
of each sample looks more stable. The high voltage is about 0.80V and the lowest is
0.72V at the Sample 3 and Sample 2 respectively.
Figure 4.17 shows the voltage value of the samples at 940nm wavelength. At this
wavelength, the reading of the voltage is too far from the average value. The lowest
value is about 0.16V while the highest is 0.47V.
0.68
0.70
0.72
0.74
0.76
0.78
0.80
0.82
1 2 3 4 5 6 7 8 9 10
VOLTAGE(V)
SAMPLE NUMBER

41
The average voltage value for each of the samples was shown on Figure 4.18.
Wavelength 840nm shows the highest voltage value, compare than 940nm.
Figure 4.18: Average voltage value at 850nm and 940nm
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0.45
0.50
1 2 3 4 5 6 7 8 9 10
VOLTAGE(V)
SAMPLE NUMBER
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
850nm 940nm
VOLTAEG(V)
WAVELENGTH
AVERAGE VOLTAGE VALUE FOR EACH ROYAL GALA RED APPLE

42
Based on the Figure 4.19, most of the sample has a closed ratio value. Sample 4 until
Sample 8 has a ratio in between 3.70 to 3.85. Thus, four of the ten samples are in
average ratio.
Figure 4.19: Spectra intensity of the 10 samples
4.3.4 ROSE APPLE
Figure 4.20 and Figure 4.21 shows the voltage value of the ten samples of the Rose
Apple with the wavelength 850nm and 940nm respectively.
The highest reading of the voltage at wavelength 850nm and 940nm is 0.58V
and 0.45V respectively. While the lowest reading is 0.50V and 0.38V for wavelength
850nm and 940nm.
Therefore, at wavelength 850nm, the voltage shows the high reading compared
than at 940nm wavelength.
1.74
1.59
3.48
3.85
3.70 3.75 3.79 3.79
4.22
4.63
1.00
1.50
2.00
2.50
3.00
3.50
4.00
4.50
5.00
0 1 2 3 4 5 6 7 8 9 10
RATIO
SAMPLE NUMBER
RATIO OF 10 SAMPLES FOR ROYAL GALA RED APPLE

43
Average of voltage value of the ten samples of 850nm and 940nm wavelength was
shown on Figure 4.22. Both of the wavelength shows the stable voltage reading, but at
the wavelength of 850nm, the reading is higher compared than the reading at the
940nm.
0.46
0.48
0.50
0.52
0.54
0.56
0.58
0.60
1 2 3 4 5 6 7 8 9 10
VOLTAGE(V)
SAMPLE NUMBER
0.34
0.36
0.38
0.40
0.42
0.44
0.46
1 2 3 4 5 6 7 8 9 10
VOLTAGE(V)
SAMPLE NUMBER

44
From the Figure 4.23, the trend line is close to most of the samples. Sample 1, Sample
2, Sample 3, Sample 6, Sample 7, and Sample 9 have a ratio value of 1.26, 1.29, 1.30,
1.29, 1.31, and 1.27 respectively.
Therefore, six of ten samples have a close value of the ratio. Thus, the ratio
value of Rose Apple can be used as a reference if the technical error is eliminated, the
reading is more accurate.
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
850nm 940nm
VOLTAGE(V)
WAVELENGHT
AVERAGE VOLTAGE VALUE FOR EACH ROSE APPLE

45
4.3.4 RATIO OF THE DIFFERENT FRUITS
Figure 4.24 shows the voltage value of the different fruit types based on two different
wavelengths. From the graph, the higher voltage value of the 850nm wavelength is
Red Apple with 0.75V and the lower value is Rose Apple with 0.56V. Apple Pear and
Green Apple have the same voltage value of 0.69V.
At the 940nm wavelength, the top voltage value is Apple Pear with 0.49V
while Red Apple with 0.24V is on the bottom. The average for all the fruits will be
used to get the average ratio and will be used to compare the ratio intensity of the fruits.
1.26
1.29 1.30
1.40
1.59
1.29 1.31
1.20
1.27
1.41
1.00
1.10
1.20
1.30
1.40
1.50
1.60
1.70
0 1 2 3 4 5 6 7 8 9 10
RATIO
SAMPLE NUMBER
RATIO OF 10 SAMPLES FOR ROSE APPLE

46
Figure 4.24: Voltage value of the different fruit types
From the Figure 4.25, Royal Gala (R.G) Red Apple shows the highest ratio value. That
means, R.G Red Apple absorb more light from IR compare than the other fruits.
Japanese Apple Pear shows the sarcastic value of the ratio. Each sample does
not have a close ratio value, thus the ratio can not be used as a reference to make a
comparison. Several factors affect the sarcastic value such as fruit quality for each fruit
may be different. More than that, the fruit size, moisture and its ripeness also can affect
these results.
Granny Smith Green Apple and Rose Apple show the stable value of the ratio.
Both of them have a low value of the ratio.
The ratio between Granny Smith Green Apple is almost same with the Japanese
Apple Pear. Thus, the ratio’s comparison should not be taken from this two type of
fruits. The best comparison is between Royal Gala Red Apple and Rose Apple,
because both of them have a value ratio that is different from other types of fruit.
0.69 0.69
0.75
0.56
0.49
0.44
0.24
0.42
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
APPLE PEAR GREEN APPLE RED APPLE ROSE APPLE
VOLTAGE(V)
SAMPLE TYPES
VOLTAGE VALUE OF THE DIFFERENT
FRUITS
850nm 940nm

47
Figure 4.25: Ratio of the different fruits
The average ratio of each fruit was shown in Figure4.26. From the graph, Red Apple
shows the highest value of ratio with 3.13. The value is quite high due to spectra
absorbed at a 940nm wavelength is too low compare to spectra absorbed at 850nm.
This is due to the number of LEDs on the devices.
Rose Apple shows the lowest value of the ratio intensity with 1.31. The voltage
value from spectra absorbed at 850nm and 940nm wavelengths is close to each other
and can get an acceptable ratio value.
Based on the average ratio, the type of fruits can be can be distinguished from
each other using NIR – spectroscopy because all of them have its own intensity. The
different intensity is based on its parameter like size, moisture and ripeness.
0.50
1.00
1.50
2.00
2.50
3.00
3.50
4.00
4.50
5.00
J. APPLE PEAR G.S GREEN APPLE R.G RED APPLE ROSE APPLE
RATIO OF THE DIFFERENT FRUITS
RATIO OF THE DIFFERENT FRUITS

48
Figure 4.26: Average ratio intensity of the different fruits
1.41
1.57
3.13
1.33
1.00
1.50
2.00
2.50
3.00
3.50
J. APPLE PEAR G.S GREEN APPLE R.G RED APPLE ROSE APPLE
RATIO
FRUIT TYPES
AVERAGE RATIO INTENSITY FOR THE
DIFFERANT FRUITS

CHAPTER 5
CONCLUSION
5.1 CONCLUSION
To give proper light intensity, LEDs should be connected to resistor to control the
LEDs intensity. The OPT101 IC chip was selected because that IC has both of
photodetector and of transimpedence amplifier (TIA). The purpose of TIA is to convert
the current signal from the photodiode to voltage signal.
The design of a portable NIR – spectroscopy can measure the voltage of the
fruits. This prototype can measure the voltage and get the ratio to differentiate the types
of fruit even though there are no information or data about the fruit’s ratio.
Ten samples of Japanese Apple Pear, Granny Smith Green Apple, Royal Gala
Red Apple, and Rose Apple were taken to get a ratio value based on the 850nm and
940nm wavelength. From the average of the fruits, Royal Gala Red Apple shows the
high ratio value of 3.13 while Rose Apple has a ratio of 1.31.
Therefore, from the whole analysis after process properly, different ratio of the
Royal Gala Red Apple and Rose Apple have been proven. The different size of fruits
also gives the different ratio of the fruits like Sample 5 in Japanese Apple Pear.

50
5.2 FUTURE RECOMMENDATION
To get an accurate value of the spectra ratio, acquisition mode to absorb the NIR
spectra should be chosen based on fruit feature. Different mode will give the different
reading.
To improve the NIR Spectroscopy design to make it more efficient, a LCD
should be added to display the result. More LED of the different wavelength should
be added to make sure the ratio of the spectral intensity of the different fruit is more
accurate. The number of each LED should be equal to make sure emitted light is same.
In the current design of the portable NIR – spectroscopy, there are manual
switch to change the LED wavelength. Thus, to improve this design to make it more
efficient, the automatic switch is needed.
Proper method needs to improve the reading of the ratio to make sure the ratio
can differentiate the fruit based on the intensity. By doing this, this device can actually
can make a differentiation between good and poor quality of fruits.

51
PROJECT PLAN
NO Task Name Start Finish Duration
Mar 2015 Apr 2015 May 2015 Jun 2015 Jul 2015
22/2 1/3 8/3 15/3 22/3 29/3 5/4 12/4 19/4 26/4 3/5 10/5 17/5 24/5 31/5 7/6 14/6 21/6 28/6 5/7
1 13.4w26/5/201523/2/2015Hardware Development and Testing
2 .2w16/4/201516/4/2015Submit 1st Draft of PSM Reportto SV
3 7.8w10/6/201517/4/2015Repair PSM Report
4 1w20/5/201514/5/2015SubmitDraft PSM Reportto SV for approval
5 .2w21/5/201521/5/2015
Submitthe approvalDraftPSM Report to PSM 2
Seminar Panels
6 .2w28/5/201528/5/2015PSM 2 Power Exhibition with Industrial Panels
7 .2w11/6/201511/6/2015
Submitthe Full PSM Report (Ring Binding), Log
Book & Proceeding Paper to SVto Evaluation
9 .2w2/7/20152/7/2015
Submission of Hard Covered PSM Report to Pusat
Sumber FKEE (CD, Softcopies & Research
Materials)
.2w18/6/201518/6/2015
SubmitPSM 2 SVEvaluation Form to the Respective
Department Coordinator
8

52
REFERENCES
[1] J. D. Jonckheere and F. Narbonneau, "Report on the design of a fiber sensor
based on NIRS," Optical Fiber Sensors Embedded into technical Textile for
Healthcare (OFSETH), 2007.
[2] H. P. R. Aenugu, D. Kumar, Srisudharson, N. Parthiban, S. S. Ghosh and D.
Banji, "Near Infra Red Spectroscopy- An Overview," International Journal of
ChemTech Research, vol. 3, no. 2, pp. 825-836, 2011.
[3] H. A. RAHIM, C. K. SENG and R. A. RAHIM, "Prediction of Soluble Solid
Content in Pineapple Using Adaptive Linear Neuron," Sensors & Transducers,
vol. 168, no. 4, pp. 243-248, 2014.
[4] Y. Liu, W. Liu, X. Sun, R. Gao, Y. Pan and A. Ouyang, "Potable NIR
spectroscopy predicting soluble solids content of pears based on LEDs," Journal
of Physics: Conference Series, vol. 277, no. 1, 2011.
[5] S. R. Delwiche, W. Mekwatanakarn and C. Y. Wang, "Soluble Solids and Simple
Sugars Measurement in Intact Mango Using Near Infrared Spectroscopy,"
HerTechnology, vol. 3, no. 18, pp. 410-416, 2008 .
[6] A. Bakker, B. Smith, P. Ainslie and K. Smith, "Near Infrared Spectroscopy," in
Applied Aspects of Ultrasonography in Human, The Nerherlands, InTech, 2012,
pp. 65-88.
[7] C. R. Haynes, "Digital Infrared Capture & Workflow," 23 September 2014.
[Online]. Available: http://www.crhfoto.co.uk/. [Accessed 24 February 2015].
[8] C. Kalkbrenner, A. Van, T. Smith and D. Charles, "Low-Cost
Spectrophotometer," Dwight Look College of Engineering, Texas A&M
University, Texas, 2013.
[9] W. Saeys, M. Velazco-Roa, S. Thennadil, B. M. Nicolai and H. Ramon, Optical
properties of apple skin and flesh in the wavelength range from 350 to 2200 nm,
United Kingdom: Optical Society of America, 2008.
[10] B. M. Nicola, K. Beullens, E. Bobelyn, A. Peirs, W. Saeys, K. I. Theron and J.
Lammertyna, "Nondestructive measurement of fruit and vegetable quality by

53
means of NIR spectroscopy: A review," Postharvest Biology and Technology,
vol. 46, no. 2, p. 99–118, 2007.
[11] Metrohm Monograph, NIR Spectroscopy : A guide to near-infrared
spectroscopic analysis of industrial manufacturing processes, Herisau: Metrohm
AG, 2013.
[12] P. Rolfe, G. Mondo, F. Bottini, D. Repetto and C. Ruggiero, "Near Infra-Red
Spectroscopy: a low cost device," in Proceedings of the 23rd Annual EMBS
International Conference, Istanbul, Italy, 2001.
[13] A. Scheeline, "Chemical Science Lesson Plan: Cellphone Spectrometer,"
EnLIST Chemistry Workshop, University of Illinois, 2010. [Online]. Available:
http://butane.chem.uiuc.edu. [Accessed 4 October 2014].
[14] K. Cantrell, "The Development and Characterization of Miniture Spectrometers
for Measuring the Redox Status of Enviromental Sample," Oregon State
University, Corvallis, 2002.
[15] E. Rosenthal, Portable Spectrometer, New York: Creative Technology, LLC
(CTech), 2007.
[16] N. H. Berivanlou, S. k. Setarehdan and H. A. noubari, "A multi-channel fNIRS
brain imagery based on Arduino microcontroller," in fNIRS 2014 Abstracts,
Canada, 2014, p. 14.
[17] Texas Instruments Incorporated, "MONOLITHIC PHOTODIODE AND
SINGLE-SUPPLY TRANSIMPEDANCE AMPLIFIER," Texas Instruments
Inc., 2003.
[18] F. Kong, Y. Qin, Z. Yang and Z. Lin, A Wearable Pulse Oximeter, Piscataway,
New Jersey, 2014.
[19] P. AJ, O. JM, L.-F. A, F.-R. MD, C. MA and C.-V. LF, "Portable light-emitting
diode-based photometer with one-shot optochemical sensors for measurement in
the field," REVIEW OF SCIENTIFIC INSTRUMENTS, vol. 79, no. 10, 2008.
[20] S. Goynar, Shalini, S. Goel and D. V. Gadre, "Health Walker - Six Minute Walk
Testing Unit," Netaji Subhas Institute of Technology, Dwarka, 2014.
[21] ledcalculator.net, "LED Calculator," 2011. [Online]. Available:
http://ledcalculator.net/. [Accessed 2 May 2015].
[22] G. Reich, "Near-infrared spectroscopy and imaging: Basic principles and
pharmaceutical applications," ELSEVIER, pp. 1109-1143, 2005.
[23] J. Lammertyn, A. Peirs, J. D. Baerdemaker and B. Nicolai, "Light penetration
properties on NIR radiation in fruit with respect to non-destructive quality
assessment," Postharvest Biology and Technology, vol. 18, pp. 121-132, 1991.

54
[24] N. Abu-Khalaf, SENSING TASTE OF FRUITS AND VEGETABLES USING
NEAR INFRARED (NIR) TECHNOLOGY, Taastrup: The Royal Veterinary and
Agricultural University (KVL), 2001.

APPENDIX A
APPENDIX
CHARACTERISTICS OF RAMAN, MIR, AND NIR SPECTROSCOPIES [11]
Raman MIR NIR
Wavenumber(cm-
1
)
50 - 4000 200 -4000 4000 - 12500
Bonds
Homonuclear bonds such
as C–C, C=C, S–S
Polar bonds such as
C=O, C–O, C–F
H-containing bonds
such as
C–H, O–H, N–H, S–H
Absorption bands
due to
Scattered radiation
Absorbed radiation
(basic vibration)
Absorbed radiation
(overtones and
combination)
Absorption Strong Weak Weak
Absorption bands
Well-resolved,
assignable to specific
chemical groups
Well-resolved,
assignable to specific
chemical groups
Series of overlapping
bands
Signal intensity Poor Good Good
Quantification
Intensity (I) ¬
concentration
log I0/I ¬
concentration
(Lambert-Beer law)
log I0/I ¬
concentration
(Lambert-Beer law)
Excitation
conditions
change of polarizability

change of dipole
moment µ
change of dipole
moment µ
Selectivity High High
Low, requires
calibration and
chemometrics
Interference
Broad fluorescence
baseline
Water
Water, physical
attributes
Particle size Independent Dependent Dependent
Applicability for
atline, online,
inline
Good Poor Good

APPENDIX B
Radiation source
Monochromatic
(laser VIS/NIR region)
Polychromatic by
globar tungsten
Polychromatic by
globar tungsten
Sample
preparation
None
Reduced
(except ATR*)
None

APPENDIX C
SOURCE CODE
void setup() {
// initialize serial communication at 9600 bits per second:
Serial.begin(9600);
Serial.println("Near-IR Spectroscopy");
Serial.println("Sample Setup...");
Serial.println("...Ready for read...");
Serial.println("Intensity reading...");
Serial.println(" ");
delay(10);
}
// the loop routine runs over and over again forever:
void loop() {
// read the input on analog pin 0:
int sensorValue = analogRead(A0);
// Convert the analog reading (which goes from 0 - 1023) to a voltage (0 - 5V):
float voltage = sensorValue * (5.0 / 1023.0);
// print out the value you read:
Serial.println("Value = ");
Serial.println(voltage);
delay(1500);
}

APPENDIX D
JAPANESE APPLE PEAR (LAI)
Sample 1
850nm 940nm
Sample 2
Sample 3

APPENDIX E
Sample 4
Sample 5
Sample 6
Sample 7

APPENDIX F
Sample 8
Sample 9
Sample 10

APPENDIX G
GRANNY SMITH GREEN APPLE
Sample 1
850nm 940nm
Sample 2
Sample 3

APPENDIX H
Sample 4
Sample 5
Sample 6
Sample 7

APPENDIX I
Sample 8
Sample 9
Sample 10

APPENDIX J
ROYAL GALA RED APPLE
Sample 1
850nm 940nm
Sample 2
Sample 3

APPENDIX K
Sample 4
Sample 5
Sample 6
Sample 7

APPENDIX L
Sample 8
Sample 9
Sample 10

APPENDIX M
ROSE APPLE (JAMBU AIR)
Sample 1
850nm 940nm
Sample 2
Sample 3

APPENDIX N
Sample 4
Sample 5
Sample 6
Sample 7

APPENDIX O
Sample 8
Sample 9
Sample 10

2015_Hasinah_fyp2_2806 (2)

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