Abstractbook SCIfair 2021_No3

SCIFA R 2021
Production of binderless particleboard from rice straw mixed with
banana pseudostem

Nutnaree Saropas 1, Prapaporn Huijisut 1, Sorada Noratad 1, Panitarn Wanakamol 1,
Sureepan Supansomboon 2 and Supitcha Supansomboon 1*
1 Department of Materials Science, Faculty of Science, Srinakharinwirot University,

Bangkok, 10110
2 Faculty of Architecture Urban Design and Creative Arts, Mahasarakham University,

Mahasarakham, 44150
* Project Advisor Email: [email protected]

Abstract
The particleboards currently used are manufactured with synthetic adhesives
containing formaldehyde. It is a substance that is harmful to health and has a
negative impact on environment. Therefore, the development of a binderless
particleboard is interesting. The adhesion properties of the lignocellulose material
present in agricultural waste have been used to develop products that are
environmentally friendly. This research aims to develop binderless particleboard
using agricultural waste materials such as rice straw and banana psuedostem.
These raw materials are abundant, easy to grow and fast growing. This research
explored the feasibility of using rice straw and banana psuedostem to produce
binderless particleboards. The proper preparation conditions for production and
the mechanical-physical properties of the particleboard samples were investigated.
Mechanical tests were performed to obtain modulus of rupture (MOR), modulus
of elasticity ( MOE) . Physical tests including density, moisture content and
thickness swelling (TS) were also examined.

Keywords: Banana pseudostem, Binderless particleboard, Lignocellulose materials,
Rice straw

84

SCIFA R 2021
The influence of supplements on the production of bacterial
cellulose by Komagataeibacter nataicola TISTR 975

Pranatda Taiwongyoi 1, Pasinee Songin 1, Onanong Pringdulka 2 and Akarin Boonsombuti 1*
1 Department of Materials, Faculty of Science, Srinakharinwirot University, Bangkok, 10110
2 Department of Microbiology, Faculty of Science, Srinakharinwirot University, Bangkok, 10110
* Project Advisor Email: [email protected]

Abstract
Bacterial cellulose (BC) is a high purity polymer composed of a mere glucose
molecule since it lacks lignin, pectin, and hemicellulose. It also has many
dominant properties. Then, BC is used in a variety of applications such as the
food industry, the pharmaceutical industry and the medical industry. However,
the yield of cellulose from bacteria is tremendously low. Therefore, the
enhancement of cellulose production is vastly studied. In this work, the influence
of the addition of 5 types of supplements on the production of bacterial cellulose,
Komagataeibacter nataicola TISTR 975, was studied. The supplements are
composed of Arabica and Robusta spent coffee grounds, ethanol, PEG 6000, and
lignin which have previously been reported that they can elevate the production
of bacterial cellulose. After incubated at 30°C for 9 days with the addition of each
5 supplements, it was found that all supplements affected cellulose yield and
water holding activity. Moreover, the results from XRD and SEM indicated that
the quality of cellulose was altered after the supplements were added to the
fermentation medium. The results suggested that unvalued spent coffee ground
and lignin can be utilized as a supplement for bacteria like commercial supplements,
ethanol, or PEG 6000 since they contained essential nutrition that may be lacking
in a common culture medium.

Keywords: Bacterial cellulose, Komagataeibacter nataicola TISTR 975,
Supplements, Spent coffee ground

85

SCIFA R 2021
The production of particleboard from oil palm fiber using lignin
formaldehyde synthesized from oil palm kernel shell

Suchanan Suksri and Akarin Boonsombuti *
Department of Materials Science, Faculty of Science, Srinakharinwirot University,
Bangkok,10110
* Project Advisor Email: [email protected]

Abstract
Palm trees are economic crops that are widely utilized in Thailand as palm oil in
both industry and households. The processing of palm oil generates by-products
including palm leaves, palm trunk, palm empty fruit bunch, palm fiber and palm
kernel shells. These biomass cause PM2.5 when they were burnt as fuel. This
research aims to develop particleboard made from palm fibers as a filler and
lignin extracted from palm kernel shells as an adhesive synthesized with
formaldehyde, namely lignin formaldehyde. The fiber and adhesive were evenly
mixed, followed by the hot press at the temperature of 180°C, the pressure of 10
MPa, and 8 minutes pressing time. The produced particleboards are tested
according to TIS 876-2547 standard. The results demonstrated an enhancement
in the mechanical properties (Modulus of rupture, Modulus of elasticity, thickness
swelling) compared with the traditional adhesive of phenol-formaldehyde. This
may be due to the extracted lignin from kernel shell composed of free hydroxyl
more than phenol. This research shows that biomass from the oil palm industry,
oil palm fiber, and kernel shell can be used to produce eco-friendly particleboard.
Keyword : Formaldehyde, Lignin, Oil palm kernel shell, Oil palm mesocarp fiber

86

SCIFA R 2021
Fabrication of silk fibroin and silk fibroin fluorescent nanofibers
via electrospinning

Aueakan Boonkacha, Chutimol Pongsiri, Pimtawan Sangjantip, Supitcha Supansomboon
and Panitarn Wanakamol *
Department of Materials Science, Faculty of Science, Srinakharinwirot University, Bangkok,
10110
* Project Advisor Email: [email protected]

Abstract
Fibroin, derived from cocoon, is a natural polymer used widely and increasingly
in various fields. In recent years, the development of fluorescent fibroin has
gained attention in the field of tissue engineering because of its biocompatibility,
oxygen/water vapor permeability, adaptive biodegradability, and ability to be
tested non-invasively. In this work, silk fibroin and fluorescent silk fibroin fibers
were fabricated via electrospinning, a simple process through which continuous
submicron fibers can be produced. Degummed fibroin was extracted by
dissolving in a calcium chloride solution. The fibroin powder was dissolved in
98% formic acid to form 10, 12 and 14 wt.% solutions. Fluorescent fibroin
solutions were achieved with addition of fluoresceine sodium (FS) as fluorescent
dye. The fluorescent solutions were prepared at 10 wt.% fibroin with varying FS
concentration at 0.1, 0.3 and 0.5 wt.% and at varying 0.5wt.% FS with fibroin
concentration at 10, 12, 14 wt.%. The fibroin solutions were fabricated into fibers
via electrospinning. The applied voltage was varied at 10, 15 and 20 kV. The
surface morphology of silk fibroin fibers and fluorescent fibroin fibers, observed
by scanning electron microscope (SEM), showed long continuous fibers. The
average fiber diameter, in sub-micron range, was found to increase with fibroin
concentration. The fluorescence effect observed by fluorescence spectrophotometer
was found to vary with concentration of fluorescent dye. The functional groups
and chemical structure of silk fibroin fibers analyzed by infrared spectroscopy
(IR) were not affected by the addition of fluorescent dye.

Keywords: Electrospinning, Fibroin, Fluorescent dye, Silk

87

SCIFA R 2021
Face, age and gender identification system for application

Kannicha Khamjring, Pacharasiri Siriyom, Panida Jitviriyavasin and Sirisup Laohakiat *
Department of Computer Science, Faculty of Science, Srinakharinwirot University, Bangkok,
10110
* Project Advisor Email: [email protected]

Abstract
Currently, automatic age and gender predictions based on face detection draw a
lot of attention due to their wide areas of applications. In this study, we try to
build a system that consists of age, gender and emotion prediction models. Based
on deep convolutional neural network architecture, age and gender models are
trained by public dataset with 14,000 data instances. After implementing the
primary models using Keras, we convert the model using TFLiteConverter, so
that the model can be deployed as a mobile application. The performance of the
three models are found as follow: using MAE as the evaluation index, the age
model yields MAE of 0.1668; the gender model yields the accuracy of 0.95 and
the emotion prediction model yield the accuracy of 0.62. We found that the causes
of models inaccuracy included the images with some nonstandard poses, for
example, skewed faces, distant faces, makeup on the faces, light, and shadow of
the image, etc. By reducing these factors, the accuracy of the models can improve.
Keywords: Age detection, Face detection, Gender detection, Keras, Tensorflow

88

SCIFA R 2021
Text sentiment analysis from GoEmotions

Nithiwat Thanasrisawat, Pawarit Sripiboon, Piyathida Thainguan and
Werayuth Charoenruengkit *
Department of Computer Science, Faculty of Science, Srinakharinwirot University, Bangkok,
10110
* Project Advisor Email: [email protected]

Abstract
Text emotion recognition is a challenging topic for research in natural language
processing. The research in this field often creates recognition models based
on data collected from social media or open datasets. This research investigates
the new Google developed dataset "GoEmotions: A Dataset of Fine-Grained
Emotions", which is made up of text from subreddits that has been labeled into
28 emotional categories. The dataset is grouped into 3 classes: positive emotion
class, negative emotion class, and ambiguous emotion class. The goal is to
classify an unknown emotional text into one of these classes. Our study suggests
that combining unsupervised learning LDA with popular text feature vectors
like TF-IDF and Word2Vec can improve the emotion recognition accuracy.
The experiment demonstrates the learning curves and model tuning techniques,
as well as the results from various feature vectors and models. According to the
experiment results, using XGBoost with Word2Vec gives the best performance
with 64 percent accuracy. We also created a chatbot to show how the algorithm
can be used in practice.
Keyword: Chatbot, Sentiment analysis, Text emotion recognition

89

SCIFA R 2021
Improving digestive organ classification from wireless capsule
endoscopy images using deep learning

Supakorn Taweechainaruemitr 1, Padipon Thongjumruin 1, Nuttiwut Ektarawong 1,
Kawee Numpacharoen 2, Amporn Atsawarungruangkit 2 and Nuwee Wiwatwattana 1*
1 Department of Computer Science, Faculty of Science, Srinakharinwirot University,
Bangkok, 10110
2 Brown University / Rhode Island Hospital, United States of America
* Project Advisor Email: [email protected]

Abstract
The location of a lesion is crucial information that Gastroenterologists must report
using capsule endoscopy images. There have not been many studies that employ
deep learning to automatically classify the location of the gastrointestinal tract.
In this work, we created a deep learning model for identifying the organs of the
gastrointestinal system (esophagus, stomach, small bowel and colon) using
images from capsule endoscopy. The capsule endoscopies train set (670,051
images), validation set (411,702 images), and test set (216,978 images) are
employ. The deep learning architecture is comprised of an InceptionResnetV2
Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM).
On average, the accuracy is 92 percent, the precision is 89 percent, the recall
(sensitivity) is 86 percent, the specificity is 96 percent, and the f1-score is 86
percent.
Keywords: Capsule endoscopy, Convolutional Neural Network, Deep learning,
Gastroenterologists, Long Short-Term Memory

90

SCIFA R 2021
Development of a flood forecasting system in the lower Chao Phraya
River area

Amita Roma, Aunchittha Hongthong, Jirapa Thongdaeng and Sasivimon Sukaphat *
Department of Computer Science, Faculty of Science, Srinakharinwirot University, Bangkok,
10110
* Project Advisor Email: [email protected]

Abstract
The objective of this research was to analyze flood trends in the lower Chao
Phraya River in 10 provinces, Phra Nakhon Si Ayutthaya, Nonthaburi, Pathum
Thani, Lop Buri, Chai Nat, Sing Buri, Uthai Thani, Saraburi, Suphan Buri, and
Ang Thong. The flooding problem in these areas was a catastrophic impact that
causes damage to the country, human life, property, agriculture, etc. Therefore,
we proposed the flood forecasting system which applied Geographic Information
Systems (GIS) methods, including Machine Learning algorithms in the prediction
process and used the ArcGIS Pro for visualizing the results in mobile
applications. We conducted the experiments by using six factors: elevation, water
content in dams, rainfall, land use, soil type, and flood history. We compared the
prediction accuracy of three algorithms: Model Logistic Regression (0.95
accuracy), Model Random Forest (0.99 accuracy) and Model Long Short-Term
Memory (0.42 accuracy). According to the results in the lower Chao Phraya River
flood forecasting system, we can predict the flood in the next three days by the
Model Random Forest to analyze flooding in our system with high accuracy and
help reduce the damage that will occur to people in those areas.

Keywords: Chao Phraya River, Flood, GIS, Machine learning

91

SCIFA R 2021
Autonomous simulated vehicles for steering angle prediction

Supavit Jaraspornsrivong, Kantivit Suwattnamala and Vera Sa-ing *
Department of Computer Science, Faculty of Science, Srinakharinwirot University, Bangkok,
10110
* Project Advisor Email: [email protected]

Abstract
At present, vehicles have many advantages for transporting people to communicate
and travel to other places. However, many statistical reports represent over 80%
of accidents mostly occur from human error. In addition, the increasing cases of
accidents were found from the missing control of the steering wheel. Therefore,
this research will develop a new system to reduce human error to decrease the
accident case from transporting by suggesting a suitable steering angle. This
research proposes a new convolutional neural network (CNN) model for
predicting the efficient steering angle based on the imaging view of the vehicle.
In the first step, our research gathers the training, validation and testing data from
the driving simulation of the Udacity platform that consists of the sequence of
driving images, steering angles, speed numbers and others. Then, we convert all
gathered data of driving images by reducing the image size to 320x160 pixels and
the colour channel from reg-green-blue (RGB) to hue-saturation-value (HSV). In
the third step, this research uses the prepared data to train the CNN system for
making the prediction model of a suitable steering angle. In the experimental
results, this CNN model was evaluated by using the Root Mean Squared Error
(RMSE) and R-square value. In addition, we evaluate the percentage accuracy of
correcting angles between predicted and gathered steering angles by using the
Ground truth degree formula. From the experimental result, this proposed CNN
model represents the corrected accuracy of the predicted steering angle of more
than 80%. Therefore, this CNN model can use the suggestion of a suitable
steering angle based on the real vehicle view for decreasing the human error.

Keywords: Autonomous vehicles, Convolutional neural network, Steering angle
prediction

92

SCIFA R 2021
Development of mobile application for daily air quality assessment
in Bangkok

Rattanaporn Roekphodee, Surirat Yutthasuntorn, Thitiya and Sasivimon Sukaphat *
Department of Computer Science, Faculty of Science, Srinakharinwirot University, Bangkok,
10110
* Project Advisor Email: [email protected]

Abstract
Air is an important resource for all living things to live for survival. However,
in some area, especially in the capital we have found that the air quality is
contaminated with pollution which affects people’s health. Unfortunately, there
is still no proper way to deal with the problem of fine dust PM2.5 and this
problem becomes a major source of severe environmental air pollution both
domestically and internationally. The objective of this research is to propose the
fine-tune machine learning models which is able to forecast 7-Day PM2.5 in
Bangkok. The model could determine appropriate measures to cope with the haze
problem in the future. The Long Short-Term Memory models (LSTM), one of
the Deep Learning models, was trained using hourly air pollution data from the
Pollution Control Department, Thailand, and The Meteorological Department,
Thailand. the experiment results shown that Long Short-Term Memory (LSTM)
had the best performance in predictions of PM 2.5 in 7 days. The best results
included PM2.5, PM10, Wind Speed, Pressure, Humidity, and Temperature. The
model performance values were RMSE 8.47, MAE 6.37 and MAPE 25.19%. This
research has improved the efficiency of the model to forecast more accurately by
choosing Adam Optimizer.

Keywords: AQI, GIS, LSTM, PM2.5

93

SCIFA R 2021
2D environment mapping and self-position estimation with
ultrasonic range sensor array

Kompich Sophat, Patikorn Kliangsanmuang, Warakon Santang and Sophon Mongkolluksamee *
Department of Computer Science, Faculty of Science, Srinakharinwirot University, Bangkok,
10110
* Project Advisor Email: [email protected]

Abstract
Currently, modern robots use information from a Light Detection and Ranging
(LiDAR) module sensor to build a map of the surrounding environment and
simultaneously determine its location within the map. The map information is
crucial for many tasks, such as path planning and obstacle avoidance. However,
the LiDAR Module is expensive compared to other distance sensors, such as
ultrasonic sensors. Therefore, this project will use low-cost ultrasonic sensors
installed on the two-wheel-drive education-grade robot to build map. Then, the
odometer data from the robot’s wheels and distance data from ultrasonic sensors
are passed to the Particle Filter (PF) -based SLAM algorithms to precisely specify
the robot’s position. The imprecise map created from running the robot in an L-
shape map reveals that using inaccurate information from the low-cost sensors
and education-grade robot directly affects the quality of the created map.
Therefore, morphological image processing is applied to the created map to
improve the map quality. As a result, the similarity is increased to approximately
70% compared to the ground truth map. We need to control the robot precisely in
different positions to get quality results. Nevertheless, it is hard to do by using
educational grade robots. Accordingly, we push the robot by hand in our
experiments instead of controlling the motor.

Keywords: Occupancy grid, Robot odometry, SLAM, Ultrasonic sensor

94

SCIFA R 2021
Vacant parking slots detection using deep learning

Pariwat Rattanaprarom, Worawit Naknawa, Kanchanit Photisuwan and Waraporn Viyanon *
Department of Computer Science, Faculty of Science, Srinakharinwirot University, Bangkok,
10110
* Project Advisor Email: [email protected]

Abstract
Using sensors to detect the status of a parking space requires a large budget to
install sensors in the parking space. Most of the parking spaces in densely
populated areas have CCTVs for security reasons. The CCTV system can be
further developed to detect the number of available parking slots and the location
of vacant spaces. Our objective is to create a deep learning model for parking lot
occupancy detection. This research used image datasets from PKLot and CNRPark.
The data were divided into 2 sets with a ratio of 80:20, 1) a training dataset of
522,182 images, and 2) a test dataset of 130,519 images. The architectures chosen
for modeling were Alexnet, VGG16, and RestNet50. The models’ performance
was measured using the test dataset in order to select the best architecture to
implement further. The best result is the Alexnet architecture achieved an
accuracy of 99.20%, precision of 98.40%, recall of 98.60%, and an F1 score of
99.10%. The selected model was developed into a web application called
ParkHere!, using React Js, Fast API, and PostgreSQL technologies to simulate
the system of parking lot occupancy detection from CCTV images.
Keywords: Alexnet, Deep learning, Parking occupancy detection, ResNet50,
VGG16

95

SCIFA R 2021
Thai music mood analysis

Natdanai Veerathavorn, Paris Aungkanapanich and Subhorn Khonthapagdee *
Department of Computer Science, Faculty of Science, Srinakharinwirot University, Bangkok,
10110
* Project Advisor Email: [email protected]

Abstract
The emotion or mood of music affects the listener in various ways. Nowadays
people listen to music on streaming services like Spotify. On streaming services,
a playlist is a selection of similar songs customized based on listener preferences.
Often, those playlist’ s names contain words or phrases that express the emotion
of music. In this work, we collected 200 songs from 10 different playlists created
by Spotify. It is worth noting that these playlists' names convey a variety of
emotions such as sad, crying, discourage, feeling love, tired, missed, chill-out etc,
which was used as the emotion label for each song in those playlists. Using audio
data collected from Spotify web API, we developed music emotion classification
models using various machine learning techniques. Random Forest yielded 0.81
accuracy as the best performance. Moreover, we noticed that Random Forest
worked best with only 3 or 4 emotion labels. Later, we also noticed similar results
by using K Mean clustering technique. We conclude that based on audio data,
those 10 playlists have similar pattern and can be grouped into only 3 or 4
collections.
Keywords: Clustering analysis, Machine learning, Music emotion classification

96

SCIFA R 2021
READ2U: A text-to-speech mobile application for visually impaired
people

Jedsadaporn Puttakosai, Tuanahlam Tuansani and Supphachai Thaicharoen *
Department of Computer Science, Faculty of Science, Srinakharinwirot University, Bangkok,
10110
* Project Advisor Email: [email protected]

Abstract
Visually impaired people typically use Braille reading and writing system to
access information. However, most textual knowledge and information are not
built for Braille. To help those with visual disabilities be able to access non-
Braille information, particularly in a physical format, this project presents a text-
to-speech mobile application, named READ2U, which can be used to read
hardcopy text to users. With this application, after a user takes a picture of a text
document, the application utilizes Tesseract OCR library to analyze and extract
text from the image into individual words. Then, it sends the extracted words to
Text-to-Speech (TTS) system for reading them up to the user. According to the
experimental results on 30 textual paragraphs with 100 words each, the accuracy
of extracted Thai-only text is 73.87%, English-only text 81.27%, and Thai-
English text 78.27%, respectively.
Keywords: Optical Character Recognition (OCR), Tesseract OCR, Text-to-
speech (TTS), Visually impaired people.

97

SCIFA R 2021
Trashy : A smart chatbot for sustainable trash management

Pattamas Wiratchanee, Wutthipong Ranmeechai, Suwikan Wongwean and Chantri Polprasert *
Department of Computer Science, Faculty of Science, Srinakharinwirot University, Bangkok,
10110
* Project Advisor Email: [email protected]

Abstract
Recently, waste management is one of the biggest problems encountered by many
countries. Improper waste management leads to many ensuing problems for
society such as health issues due to germs and global warming since many people
destroy waste by burning. One possible solution to alleviate this problem is to
properly classify the type of garbage and handle each type efficiently. For
example, some organic waste could be fermented to be used as fertilizer or recycle
waste for sale to reuse for maximum benefit. However, waste classification in
many countries is neglected due to many factors such as incompetent authority or
lack of waste management awareness leading to inefficient waste management
system. In this project, we propose "Trashy”, a smart chatbot for sustainable trash
management. Trashy is an intelligent software chatbot that gives suggestions to
users on how to responsibly manage waste. Trashy employs a deep learning
model called resnet50 to analyze a picture of garbage and classify them into 7
types: glass, plastic, metal, paper, general waste, food waste and hazardous waste.
Once the garbage has been classified, Trashy advises users on how to properly
take care of the garbage such as identifying the proper type of bin to dispose of
the trash or notifying suitable places and time to sell recycled waste. Preliminary
results show that our trash classification model yields 98% classification accuracy
where each image takes approximately 4 seconds to process. In addition, Trashy
uses a deep learning model called LSTM to predict trash price with root mean
square error (RMSE) equal to 0.07 baht/kg based on the past waste price.

Keywords: Chatbot, Classification, Deep learning, Image Processing, Long
Short Term Memory

98

SCIFA R 2021
Performance evaluation of face encoding techniques: a case study
on the Asian population

Jirayu Pornsirianun, Phuripakorn Sriyod, Chinatan Sukjam and Napa Sae-bae *
Department of Computer Science, Faculty of Science, Srinakharinwirot University, Bangkok,
10110
* Project Advisor Email: [email protected]

Abstract
The purpose of this study was to compare the performance of facial recognition
systems in terms of recognition performance, the bias of gender on a face
recognition system, and the effectiveness of facial recognition attacks using
dictionary attack methods on the Asian population datasets. Typically, the face
recognition system consists of three main components: the face detection module,
the face embedding module, and the face matching module. The process starts by
detecting the face region from the face image. Then, the face region image is
converted to a vector (embedding) representation. Lastly, the distance between a
test image and a template (an enrolled face image) is computed by calculating the
vector similarity and the decision to accept or reject the test image depends on
the computed similarity score. The biometrics system performance is then
evaluated based on False Acceptance Rate and False Rejection Rate. The models
used in this research were 3 pre-trained models: ResNet50, SeNet50, and
FaceNet. The systems were evaluated based on an Asian face database
comprising 1819 images of 107 individuals. The result indicated no bias in system
performance when tested against a facial image with different gender attributes.
The model with the best recognition performance was SeNet50. Lastly, using a
dictionary attack, researchers examined the attack performance of facial
recognition systems, it found that the attack has a high success rate of 22.94%,
21.5%, and 22.72% when 5 photos were used on ResNet50, SeNet50, and
FaceNet models, respectively.

Keywords: Dictionary attack, Face detection, Face embedding, Face encryption

99

SCIFA R 2021
Certificate verification using Ethereum blockchain system

Chayanan Wongthongveskul, Teejutar Itsuwarn, Norawit Aumpansaeng, and
Supphachai Thaicharoen *
Department of Computer Science, Faculty of Science, Srinakharinwirot University, Bangkok,
10110
* Project Advisor Email: [email protected]

Abstract
Students must present the certificates to institutions or companies. Manual verification
becomes a tedious task.The absence of an appropriate anti-counterfeiting system
leads to situations where graduation certificates are found to be forged. To make
data safer and more secure everything needs to be digitized with the principle of
confidentiality, credibility and availability. All of these can be done with
Blockchain-based technology. Our system consists of a certificate authority that
will generate certificates and those certificates will be reviewed by a committee
within that organization before it was sent to students via Ethereum Network.
Each certificate has a unique hash key and can be used to verify the validity of a
certificate by any organization. The benefits of system are that students don't have
to worry about their graduation certificates being lost or damaged and verifying
the validity of certificates is quite easy.
Keywords: Blockchain, Certificates, Ethereum network, Unique hash key

100

SCIFA R 2021
Creation of a regression equation for predicting a change in coastal
area in Samut Prakan

Nonthaworn Sathapornpitak, Thanaporn Kunlayasinlapin, Narissara Poungsawat, Suchada Toyai,
Noppadon Wichitsongkram and Khawn Piasai *
Department of Mathematics, Faculty of Science, Srinakharinwirot University, Bangkok, 10110
* Project Advisor Email: [email protected]

Abstract
The coastal area in Laem Fhapa Subdistrict, Phra Samut Chedi District, Samut
Prakan had eroded at a rate of more than 25 meters per year. The coastline erosion
was about 12.5 kilometers long. Originally, there were more than 200 houses in
the area. However, there were only about 70 houses left in 2020. This mathematics
project aims to create an equation to predict a change in the coastal area at a
certain year after the year of 2000. In this study, data was collected over 21 years
(2000 - 2020) based on satellite observations in Google Earth. The observations
cover the coastline from longitude 100°28'29.76" east to longitude 100°30'15.07
east, which is about 2.25 kilometers long. The process begins with creating a line
along the coastal area in each year. Next, a linear equation that contains two points
on the line was determined and integrated to find the coastal area in that particular
year. Then, the coastal area in that particular year was compared with the coastal
area in 2000 to determine the change. Finally, the changes in the coastal areas in
each of 21 years and the coastal area in 2000 were plotted to determine a
distribution. By using regression analysis, we obtain a regression equation for
predicting the difference between the coastal area at a certain year and the coastal
area in 2000 in Laem Fhapa Subdistrict, Samut Prakan. The results showed that
the regression equation is y = 130351.882228346 ln(x) + 3970.7537211664
where x represents the number of years after 2000.

Keywords: Coastal area, Integration, Regression equation, Regression analysis

101

SCIFA R 2021
The relationships between the weight of the egg and the volume of
the albumen and the yolk

Kanokpon Nueamun, Pornthipa Kongngern, Papatsara Buaboonnark, Supitchaya Santivachratsamee,
Noppadon Wichitsongkram, Anek Janjaroon, Sukanya Hajisalah and Khawn Piasai *
Department of Mathematics, Faculty of Science, Srinakharinwirot University, Bangkok, 10110
* Project Advisor Email: [email protected]

Abstract
The objectives of this Mathematical project were to find 1) the relationship
between the weight of the egg and the volume of its albumen and 2) the
relationship between the weight of the egg and the volume of its yolk. The data
was carried out from No.0 and No.1 eggs. The number of eggs in each group is
30 equally so there were 60 eggs in total. The process started by weighing No.0
and No.1 eggs to determine the weight of each egg and record the data. After
cracking an egg, we separated the yolk and the albumen of it. Then we used a
syringe to find the volume of the albumen and the yolk and recorded the data. To
obtain the relationships between the weight of the egg and the volume of the
albumen and the yolk, we applied simple linear regression and the method of
least-squares. We found that 1) The relationship between the weight of the egg



and the volume of the albumen is y = 0.7374x −11.9573 and the average relative
error is 2.7042 percent, and the correlation coefficient is 0.8441 where y is the
volume of the albumen, and x is the weight of the egg. 2) The relationship



between the weight of the egg and the volume of the yolk is y = 0.0903x + 9.1325 , and
the average relative error is 4.6704 percent, and the correlation coefficient is
0.2568 where y is the volume of the yolk, and x is the weight of the egg.

Keywords: Method of least-squares, Simple linear regression, Volume of the
albumen, Volume of the yolk, Weight of the egg

102

SCIFA R 2021
The mathematical model for determination of an appropriate
number of cars on each road lines at Srinakharinwirot University,
Prasarnmit campus

Kewalee Chaiwut, Kodchaphan Riyaphan, Jiratchaya Maneerat, Prarthana Osatanon and
Khawn Piasai *
Department of Mathematics, Faculty of Science, Srinakharinwirot University, Bangkok, 10110
* Project Advisor Email: [email protected]

Abstract
This math project has the purpose to create a mathematical model that determines
the appropriate number of cars on each road. The operation began by drawing a
car traffic map at Srinakharinwirot University in Prasarnmit Campus, except for
basement parking, Defining variables related to the number of cars entering and
exiting intersections within the University, then, creating a system of equations
that showed the relationship between the number of cars entering and leaving the
intersection. By applying matrix knowledge to a system of linear equations and
solving the system of equations with the Minimum Norm Solutions of
Underdetermined System method, the results of using MATLAB program are as
follows: From the data collection on April 7th -9th 2021, the number of cars
entering and leaving the intersections within Srinakhinwirot University in Prasarnmit
Campus, except for basement parking related to Tˆ = 86.97802 + 1.296703T ,where T

2 11

and T2 have a high level of linear relationships, and Tˆ4 = 50.70983 − 0.1259T3 where
T3 and T4 have a medium level of linear relationships.

Keywords: Cars, Intersection, Mathematical model, System of linear equation

103

SCIFA R 2021
The relationship between the-15 puzzle and the permutation group

Apiwat Kadmanee, Kritsada Prathum, Worraprat Nunthaphodech, Sahapol Vachiraprasit and
Thitarie Rungratgasame *
Department of Mathematics, Faculty of Science, Srinakharinwirot University, Bangkok, 10110
* Project Advisor Email: [email protected]

Abstract
The objective of this mathematical project was to find the conditions allowing us
to arrange the numbered pads in the - 15 puzzle from a given arrangement pattern
to be a preferred arrangement pattern. The project started from sliding numbered
pads in the given arrangement pattern. After observing and analyzing the
movement pattern of sliding numbered pads caused by arranging the numbered
pads in the identity pattern and non-identity patterns, the conjecture was obtained
regarding the conditions allowing to order the numbered pads in the - 15 puzzle
from a given arrangement pattern to be a preferred arrangement pattern. The proof
of the conjecture utilized the permutation group theory. The findings indicated
that the given numbered pads can be reordered to be the preferred numbered pads
if the given numbered pads are even permutations and the shortest distance from
the blank (the pad no.16) is even or the given numbered pads are odd
permutations and the shortest distance from the blank (the pad no.16) is odd. If
both the given arrangement pattern and preferred arrangement pattern cannot be
rearranged to be the identity pattern, then we can arrange the numbered pads from
the given arrangement pattern to be preferred arrangement pattern.
Keywords: Identity pattern, Permutation group, The – 15 puzzle

104

SCIFA R 2021
Geometric shapes obtained from swinging a simple pendulum

Padoungkiet Punjakhun, Pipatphong phuatana, Putanon Bordeeasanut, Rittiporn Kaewjun and
Khawn Piasai *

Department of Mathematics, Faculty of Science, Srinakarinwirot University, Bangkok, 10110
* Project Advisor Email: [email protected]

Abstract

The purpose of this mathematical project was to study the equations of the

geometric shapes obtained from swinging a simple pendulum with and without

damping. The process started from creating a mathematical model from a simple

pendulum swing that was nearly the reality on GeoGebra program. Then, we did

some simple pendulum experiments with and without damping. In the meantime,

we observed the movement of an object which created a geometric trace. After

that, we predicted the equations of these traces, and then proved the predictions

by using the concept of Oscillation in Physics. As a result, the equation of the

geometric shape obtained from a simple pendulum swinging without damping

was (R )2 (R )2 = 1 + ççèççæ2ARxxARyy - cos(d)÷÷÷÷÷øöcos(d) when R = A sin(wt + a ) ,
x+ y xx x
A2
A2 y
x

R = A sin(wt + a ) , d = a - a and the equation of the geometric shape, obtained
yy y xy

from a simple pendulum swinging with damping, was dx = dq = y and dy = - by .
dt dt dt

Keywords: GeoGebra program, Geometric shape, Oscillation, Simple pendulum

105

SCIFA R 2021
A mathematical model for COVID-19 pandemic controls

Patpaphoom Chuyong, Chanoknan Boonsing, Nitchakamon Ulitphon, Tuandaria Sureng and
Khawn Piasai *

Department of Mathematics, Faculty of Science, Srinakharinwirot University, Bangkok, 10110
* Project Advisor Email: [email protected]

Abstract

This mathematics initiative is designed to develop a mathematical model for
limiting the COVID-19 outbreak via education campaigns. The population used

in the study was 2020 residents of Bangkok, which was divided into three

subgroups: the at-risk population (S), the infected and infectious population (I),

and the recovered population (R). The study's parameters were the population's

immigration and migration rates. Through an educational effort, this initiative

selects a mathematical model to be used in developing a SIR model. The
mathematical model for COVID-19 pandemic control that was developed

consists of the following equations:

dS =  N − (1− p) SI − S (1)
dt

dI = (1− p) SI − ( + )I (2)
dt

dR =  I − R (3)
dt

By S + I + R = N

The results showed that the infection level was calculated by the Next Generation

method which equals R0 = (1− p)  N , which R0 is equal to 0.82606 and 2.47818
 ( + )

when education campaigns is p = 0.7 , and p = 0.1 As shown, increasing the

number of campaigns results in a decrease in the number of infected people. Thus,
if an optimal campaign value for a given time can be identified, the number of
future instances may be predicted. This will aid in the design of disease preventive
and control measures.

Keywords: Education campaign, Infection level, SIR model

106

SCIFA R 2021
Study of parabolic chute propeller turbines

Thanadol Sintuurai, Pollakorn Saichalard, Supakit Lapsuwanwong and Witchapol Chaisutti *
Department of Mathematics, Faculty of Science, Srinakharinwirot University, Bangkok, 10110
* Project Advisor Email: [email protected]

Abstract
The goals of this mathematics project were to 1) find the range of values that
increased the volume of the parabolic displacement of the turbine and 2)
determine the value of one that caused the parabolic displacement of the turbine.
The volume of the water turbine is the greatest. This project was based on the
equation for the impeller of a parabolic chute turbine y = ax2 created from the
program Photoshop CS6 by specifying 0 < a < 1 using the program Geogebra to
calculate the volume V of a three-dimensional geometric figure with a parabolic
cross-section. Then use Python 3.0 Jupiter to analyze the possible values and then
create a graph showing the relationship between the volume V and the value in
Excel to determine the value as mentioned above. The results showed that 1) the
parabolic displacement blades of the forging turbine had an increase in volume V
when 0.01< a < 0.24 and the parabolic-rail blades of the bellows had decreased
when a > 0.24, and 2) the parabolic-rail blades of the bellows had the volume V
most when a = 0.24 .
Keywords: Parabolic-rail blades, Volume of the parabolic

107

SCIFA R 2021
Investigating well-known football players’ foot placement angles for
taking free kicks

Supharat Chomood, Hadsadin Saleelad, Attapol Kanapang, Assadang Luangmantana and
Anek Janjaroon *
Department of Mathematics, Faculty of Science, Srinakharinwirot University, Bangkok, 10110
* Project Advisor Email: [email protected]

Abstract
The objective of this mathematics project is to determine an average angle among
angles formed by several well-known football players’ foot placements and
imaginary straight lines from their free kick points to particular areas between
two goalposts where the balls enter. The project considered three different areas
(i.e., Area 1, Area 2, and Area 3) between two goalposts. That is, Area 1, Area 2,
and Area 3 cover any place from 0 to 2 yards, from 2 to 6 yards, and from 6 to 8
yards, respectively, away from the right goalpost. To collect data, 30 YouTube
video clips of well-known football players were viewed to search for their free
kick moments. These moments were snipped. In total, there were 55 photographs
of free kick moments. There were 20 photographs, 8 photographs, and 27
photographs of the moments that the balls entered the goals within Area 1, Area
2, and Area 3, respectively. All photographs were analyzed by using Geogebra
and Microsoft Excel to determine angles formed by the football players’ foot
placements and imaginary straight lines from the free kick points to the places
where the balls entered the goals. Then, an average angle of each group was
calculated. The results showed that the average angles formed by the well-known
football players’ foot placements and imaginary straight lines from the free kick
points to the places where the balls entered the goals within Area 1, Area 2, and
Area 3 are 56.84 degrees, 62.97 degrees, and 64.30 degrees, respectively.

Keywords: Average angle, Football, Foot placement, Free kick, GeoGebra

108

SCIFA R 2021
Learning about COVID-19 with “Defense against COVID-19”
board game

Intupa Chansawang, Patcharapa Nuansuwan and Panarat Arunrattiyakorn *
Department of Chemistry, Faculty of Science, Srinakharinwirot University, Bangkok, 10110
* Project Advisor Email: [email protected]

Abstract
This research presents the design of the science board game “Defense Against
COVID-19: DAC” to learn about viral infections and immune response to
SARS-CoV-2 during the COVID-19 pandemic. The DAC was designed to help
students understand the SARS-CoV-2 infection process through facing serious
situations at high risk of COVID-19 infection and controlling the spread of
COVID-19 under the policies of the government based on real events. In
addition to learning about the process of how SARS-CoV-2 infects the host and
immune response, the students are also learning about the importance of
vaccinations. The game is designed for 2-4 players and is suitable for students
aged 17 and above. The research methodology consists of: The first phase is to
design a science board game “Defense Against COVID-19: DAC” and the DAC
has been field-tested with a group of undergraduate students of the chemistry
department, SWU, to evaluate its applicability in the second phase.
Keywords: COVID-19, COVID-19 vaccine, Immune response, Science board
game, Serious game

109

SCIFA R 2021
Mangiferin structure improvement to increase the efficiency of
water solubility for reducing blood sugar levels

Natchaphon Phuphakaphanphong, Thanchanok Thepphichai, Kulvadee Dolsophon and
Nuttapon Apiratikul *
Department of Chemistry, Faculty of Science, Srinakarinwirot University, Bangkok, 10110
* Project Advisor Email: [email protected], [email protected]

Abstract
The population of Thailand tends to increase in patients with diabetes continuously.
There are approximately 300,000 new cases per year. In 2021, there were around
3.2 million people with diabetes in the system. Many research studies have shown
that mangiferin was a substance found in the mango plant family (Mangifera
indica), which could reduce blood sugar levels and showed anti-diabetic activity.
Because mangiferin has low water solubility, it was difficult to be absorbed in
body. This research aimed to study the extraction and isolation of mangiferin
from mango leaves, modification of the structure and comparison of water
solubility of mangiferin, mangiferin sodium salt, and mangiferin potassium salt.
Dried mango leaves were extracted in 95% ethanol to obtain crude extract in 12.9
% by mass. Mangiferin was then precipitated using ethanol. The structures of
mangiferin and its salt were confirmed by Nuclear magnetic resonance (NMR)
techniques.
Keywords: Anti-Diabetes, Mangiferin, Mangiferin potassium salt, Mangiferin
sodium salt, Solubility

110

SCIFA R 2021
Development of paper-based colorimetric device for detection of
proline content in honey

Mutita Jokkaeo, Vichaya Wuttipek and Weena Siangproh *
Department of Chemistry, Faculty of Science, Srinakharinwirot University, Bangkok, 10110
* Project Advisor Email: [email protected]

Abstract
Proline is a predominant free amino acid found in honey that can be used as a
quality indicator to evaluate the authentication and detect sugar adulteration.
Many analytical methods have been used to determine proline content, such as
paper chromatography, high-performance liquid chromatography (HPLC), gas
chromatography, and capillary electrophoresis (CE). However, those methods
necessitate a long analysis time, sample pretreatment, large quantities of reagents,
and expensive instruments. Thus, this work aims to develop a rapid and simple
method for detection of the proline content. Paper-based colorimetric device
could be used for the determination of proline content due to its simplicity, cost-
effective, portable platforms and disposability. Proline was reacted with Isatin
reagent, resulted in a color change from yellow to blue on paper-based analytical
device (PAD). It could be easily observed with the naked eye. Under optimal
conditions (Isatin concentration 0.066 M, Isatin:Proline 1.4:0.7 uL, temperature
120 oC, 5 min), the proposed PAD was successfully quantified the proline content
from the color intensity that measured by an ImageJ software in RGB color. The
good linearity of this method was obtained in the range of 0.1-0.5 ppm (R2 =
0.9951). The limit of detection (LOD) and limit of quantification (LOQ) were
found to be 0.023 ppm and 0.077 ppm, respectively. Therefore, this developed
PAD could be applied for the determination of proline content in honey samples.
Moreover, this PAD provides a low-cost, simple, sensitive, and promising tool
for estimating the quality of honey as well as being suitable for on-field analysis.

Keywords: Honey, Isatin reagent, Paper-based colorimetric device, Proline

111

SCIFA R 2021
Effect of herbal plant extracts and plant growth regulators on the
growth and development of Caladium bicolor Vent.

Natnicha Kanyala, Sasitorn Khaimook and Wiphusinee Worrachottiyanon *
Department of Biology, Faculty of Science, Srinakharinwirot University, Bangkok, 10110
* Project Advisor Email: [email protected]

Abstract
Caladium bicolor Vent. are annual crops with colorful leaves and storage tubers.
They are famous ornamental plants and are important for the economy.
This study aims to examine the effects of herbal plant extracts (Piper betle, Piper
sarmentosum and Curcuma longa) and plant growth regulators on the growth and
development of C. bicolor ‘Kai-Rachawadee’ and ‘Kai-Sudsanguan’. The results
showed C. longa extract added with root supplement presented the maximum
survival rate (100%), shoot numbers (1.67 shoots) and shoot length (1.60 cm) of
Kai-Rachawadee tubers. The highest root numbers (3.67 roots) and root length
(2.50 cm) were recorded on the C. longa extract. In addition, Kai-Sudsanguan
tubers were induced to have the maximum survival rate (100%), root length (5.23
cm), shoot numbers (1.67 shoots) and shoot length (7.36 cm) on C. longa extract
added with root supplement. While P. betle extract was treated in combination
with the root supplement, it exhibited the highest root numbers (6.33 roots).
Moreover, plantlets were subsequently treated with different concentrations of
Benzyladenine (BA) and Gibberellic acid (GA3) and results showed that BA (200
ppm) solution and GA3 (200 ppm) combination with BA (200 ppm) solution were
the most effective plant growth regulators for inducing leaflets from Kai-
Rachawadee plantlets, showing the highest number of leaves 3.13 leaves per
shoot. In Kai-Sudsanguan plantlets, the highest root numbers (6.13 roots), root
length (5.90 cm) and petiole length (16.03 cm) were observed on GA3 (100 ppm)
combination with BA (200 ppm) solution.

Keywords: Benzyladenine, Caladium bicolor, Gibberellic acid, Herbal plant
extracts

112

SCIFA R 2021
Development of a simple PCR-RFLP technique to determine
genetic relationship of some plants in Lamiaceae

Nuti Ngamphen, Assadawut Khunla, Kopchapan Jitturongaporn, Wuttipong Tongbai and
Rakchanok Koto *
Department of Biology, Faculty of Science, Srinakharinwirot University, Bangkok, 10110
* Project Advisor Email: [email protected]

Abstract
Lamiaceae is a family of plants comprising several species reported in Thailand.
It is widely used in households, for instance, using it as cooking ingredient.
Member of this family has morphological similarities, causing errors in
classification based only on morphology. Therefore, using molecular biology
techniques such as Polymerase Chain Reaction and Restriction Fragment Length
Polymorphisms (PCR-RFLP), the genetic relationship of Lamiaceae was
examined and studied. Six plants were selected, Ocimum tenuiflorum, O.
gratissimum, O. basilicum, O. americanum, Mentha cordifolia, and M. piperita.
In this study, PCR was used to amplify the internal transcribed spacer (ITS)
region. All PCR products were digested with the same restriction enzyme. The
DNA band characteristics were obtained by agarose gel electrophoresis. The
results showed that only Ocimum basilicum, Ocimum americanum, and Mentha
cordifolia were successfully amplified. The reason why the remaining three
plants could not be amplified is the family contains secondary metabolites which
interfere with the PCR process. The plants were found to be genetically different
after PCR products were digested with the restriction enzyme, EcoRV.
Consequently, the PCR-RFLP technique can be used to classify Lamiaceae,
which can be applied in breeding selection when utilized appropriately.

Keywords: ITS region, Lamiaceae, PCR-RFLP, Restriction enzyme, Secondary
metabolite

113

SCIFA R 2021
Transcribing lab-modified DENV2 genome-mimicking construct
via in vitro transcription

Nutthapat Bumrungdee, Thanyathip Chaikhampha and Nopnithi Thonghin *
Department of Biology, Faculty of Science, Srinakharinwirot University, Bangkok, 10110
* Project Advisor Email: [email protected]

Abstract
Dengue virus (DENV) causes dengue fever (DF) that is widespread in tropical
countries. However, there is no vaccine for DF prevention because scientists
have insufficient knowledge of DENV translation and the recognition site of
ribosomes on DENV genome is unclear. Therefore, the aim of this project is to
obtain appropriate conditions for transcribing lab-modified DENV genome-
mimicking constructs by in vitro transcription, where RNA product will be
further investigated using cryo-EM. We initially compared the efficiency of T7
RNA polymerase obtained from a commercial kit and lab preparation. In
addition, relevant factors were optimized, including the concentration of the
DNA template (500 ng and 1 µg), reaction duration (2 and 4 hours), and the
amount of enzyme used in the reactions (0.5, 0.75, 1.25, 1.5, and 1.75 µg). The
yield of the reaction that was examined by denaturing agarose gel
electrophoresis showed that both T7 RNA polymerase samples were able to
perform the reaction under the recommended condition. However, lab-prepared
T7 RNA polymerase continued to yield even the reaction duration was halved
from the aforementioned condition, while the kit enzyme did not yield any
products. The researchers are currently in the process of interpreting the results
of the enzymatic dosage alteration experiment of lab-prepared T7 RNA
polymerase to figure out conditions for RNA production for further studies.

Keywords: Dengue virus, DENV genome, In vitro transcription, T7 RNA
polymerase, Viral RNA

114

SCIFA R 2021
Designing and synthesizing molecular constructs to mimic dengue
viral genome

Kornkanok Yusuk, Supitsara promsuwon and Nopnithi Thonghin *
Department of Biology, Faculty of Science, Srinakharinwirot University, Bangkok, 10110
* Project Advisor Email: [email protected]

Abstract
Dengue virus (DENV) is a virus that causes dengue fever (DF), a common
disease found in Southeast Asian countries. Scientists today still cannot
completely explain how the virus translates its genome in the host cell.
Knowledge on viral translation is crucial and will lead to an understanding on
how the disease begins. However, since a specific Internal Ribosome Entry Site
(IRES) of DENV has not been discovered, applying existing knowledge
regarding translation from other viruses is very limited. This research, therefore,
focuses on designing and synthesizing molecular constructs to mimic DENV
genome. The construct is expected to be capable of synthesizing viral RNA,
which will be subjected to further investigation via cryo-electron microscopy.
In this study, we designed a construct that possesses 5´ untranslated region
(5´ UTR), enhanced green fluorescent protein gene (eGFP) with the FLAG tag
sequence, 3´ untranslated region (3´ UTR) and restriction sites of restriction
enzymes HindIII, PstI, SpeI and XbaI. We have successfully synthesized separate
DNA fragments required for the construct using PCR. Each fragment was
subsequently prepared by digesting with corresponding restriction enzymes as
designed. Currently, ligation trials are being conducted expecting all fragments
to be ligated into pUC19 plasmid. Transformation and plasmid verification will
be performed to ensure the correctness of the construct.

Keyword: Dengue viral genome-mimicking construct, Dengue virus, Enhanced
green fluorescent protein (eGFP) gene, 3´ untranslated region, 5´ untranslated
region

115

SCIFA R 2021
DNA fingerprints of myotoxin-containing mushrooms in the
genus Russula

Penpicha Roiampang 1, Benyapa Srilachai 1, Sittiporn Parnmen 2 and Achariya Rangsiruji 1*
1 Department of Biology, Faculty of Science, Srinakharinwirot University, Bangkok, 10110
2 National Institute of Health, Department of Medical Sciences, Ministry of Public Health,

Nonthaburi 11000
* Project Advisor Email: [email protected]

Abstract
The genus Russula is a large group of mushrooms in the phylum Basidiomycota.
Russula subnigricans contains a toxic substance (cycloprop-2-ene carboxylic
acid) which can cause severe rhabdomyolysis. Due to its morphological
resemblance to other wild edible species, including R. nigricans and R.
densifolia, R. subnigricans is often mistaken for edible species. In the present
study, six samples of Russula were obtained from the Ministry of Public Health.
Molecular identification revealed by NCBI BLAST search analysis of 28S
rRNA gene sequence data of all samples confirmed the presence of R.
subnigricans, R. nigricans and R. densifolia with 100%, 98% and 100%,
respectively. The samples were used to analyze DNA fingerprints based on high
annealing temperature-random amplified polymorphic DNA (HAT-RAPD).
From 10 random primers used, 7 primers produced a total of 39 PCR bands.
These bands were scored as 19 monomorphic and 20 polymorphic. The overall
percentage of polymorphism (51.28%) indicates a moderate genetic diversity
among these three species of Russula.

Keywords: DNA fingerprint, HAT-RAPD, Rhabdomyolysis, Russula

116

SCIFA R 2021
Anatomical and histological studies of the sand worm Perinereis
nuntia (Phyllodocida: Nereididae)

Boriphat Phonchai, Nutchayaporn Kongsanan, Suchanun Sophak and Thanit Siriboon *
Department of Biology, Faculty of Science, Srinakharinwirot University, Bangkok, 10110
* Project Advisor Email: [email protected]

Abstract
The sand worm ( Perinereis nuntia) is characterized by having a long, slender, and
slightly flattened body with parapodia on body segments. It is important as feed for
aquaculture- livestock farming due to its high nutrition, particularly protein and
unsaturated fatty acids. The anatomy of the sand worms is described with gross
dissection of organ systems. However, some structures are complicated to describe
and cannot be separated by anatomical technique. This research aimed to identify
organs using anatomical and histological methods. The result shows the epidermis
and cuticle represents mucus channel with secretory cells secreting viscous
mucus. Neuron, glia cells and giant nerve fibers were found in the suprapharyngeal
ganglia. Photoreceptor cells were found in the retina of the eyes with clearly visible
dark pigments. Numerous neurons were found in the suprapharyngeal ganglia, palp
and tentacle, mostly in the peristomium and prostomium regions. The muscular
system consists of longitudinal, circular, and parapodial muscles. The digestive tract
consisted of a pharynx, esophagus, and intestine. Columnar epithelia, mucous and
serous cells were found in the pharyngeal lining of the pharynx. The esophagus was
shaped like papillae with columnar epithelia, mucous and serous cells.The esophageal
glands were found on both sides of the esophagus. The gland was divided into two
parts which are the duct with simple cuboidal epithelium and glandular part having
columnar epithelium. The pharynx, esophagus, and esophageal glands play the key
role for digestion. The intestine was shaped like typhlosole to increase surface area
for absorption with columnar epithelia and serous cells. The information obtained
from this research could be applied to improve the explanation of physiological
mechanisms of the sand worm.

Keywords: Anatomy, Histology, Sand worm

117

SCIFA R 2021
Comparative anatomy of leaf blade, petiole and wood of some
species of Bignoniaceae in Thailand

Prakaypetch Chanthateero, Aphichai Phupiam, Azhar Waedueramae and Anitthan Srinual *
Department of Biology, Faculty of Science, Srinakharinwirot University, Bangkok, 10110
* Project Advisor Email: [email protected]

Abstract
The anatomical characteristics of leaf blade, petiole, and wood of the family
Bignoniaceae in Thailand were determined. In this study, the leaf epidermis was
investigated by peeling and clearing methods, and stained with 1% safranin in
70% ethanol. The transverse sections of the leaf blade and petiole were prepared
in terms of their anatomical structures by the paraffin method, stained with 1%
safranin in 70% ethanol and 1% fast green in 95% ethanol. The wood anatomy
was stained with 1% safranin in 70% ethanol. The results indicated the
characteristics of the leaf blade, petiole and wood can be used for the
identification of the genus and species, including the ornamentations of cuticle,
the shapes of epidermal cells, the types of trichomes, the types of stomata and the
presence or absence of inclusions in the epidermis, the presence or absence of
cuticle layers, the shapes of the margin, the types of trichomes on the leaf blade
and petiole, the shapes of petiole, the shapes of the vascular bundle and
the presence or absence of inclusions in the leaf, the types of ray parenchyma,
the types of axial parenchyma and the presence or absence of inclusions in wood.
Keywords: Anatomy, Bignoniaceae, Thailand

118

SCIFA R 2021
Comparative anatomy of some medicinal plants of the family
Sapindaceae in Thailand

Jakkawan Chotawan, Pattarapon Yeephadung and Anitthan Srinual *
Department of Biology, Faculty of Science, Srinakharinwirot University, Bangkok, 10110
* Project Advisor Email: [email protected]

Abstract
The anatomical characteristics of leaf blade of 14 species of medicinal plants of
family Sapindaceae occurring in Thailand were described and assigned to
construct the species identification keys. Leaf epidermis was prepared by
epidermal peeling and clearing methods while transverse section of leaf blade
was examined by paraffin method. The results in this study indicated that the
anatomical characteristics could be used to identify the species of plant, attribute
the aspects occurring together to create a dichotomous identification keys, as
follows: 1) the patterns of cuticle; 2) the shapes of epidermal cells; 3) the types
of stomata; 4) the types of trichomes; and 5) the types of inclusions and secretory
cavities.The above mentioned of features were the significant characteristics for
encouraging species identification and as a database.
Keywords: Anatomy, Identification, Medicinal plant, Sapindaceae, Thailand

119

SCIFA R 2021
Comparison of protease reaction efficiency from fruits and
vegetables affecting meat tenderness

Teerapat Weerachartyanukool and Somkiat Phornpisutthimas *
Department of Biology, Faculty of Science, Srinakharinwirot University, Bangkok, 10110
* Project Advisor Email: [email protected]

Abstract
Protease is an enzyme group that catalyzes the hydrolysis of proteins by breaking
polypeptides into shorter peptide fragments. Meat tenderizing using proteases in
the food industry and households is mainly based on meat tenderizer chemicals.
The meat-marinating chemicals may result in an unpleasant taste for the meat that
is used in various types of cooking. The smell of that food was lost, resulting from
the chemical residues changing in food, which may have caused the meat
degradation. The purpose of this study was to compare the activity of proteases
extracted from vegetables and fruits by using a simple screening enzyme test. The
most effective fruit and vegetable extracts were then selected for tenderness
testing of pork using the texture analysis test. Forty-seven types of fruits and
vegetables were primary screened and compared with combizym as a positive
control. To compare among the extracts, a completely randomized design (CRD)
was analyzed, and Duncan’s new multiple range test was used for the pos hoc
test. The results indicated that the extracts from goji berries, strawberry,
pineapple, mango, and red pepper showed a significant difference (p < 0.05) and
they can give the pork tenderness, respectively.
Keywords: Fruit, Meat tenderness, Protease, Vegetable

120

SCIFA R 2021
Molecular identification and cluster analysis of edible boletes in
Ubon Ratchathani Province

Pornpimon Dechsorn 1, Suprakit Wathaeow 1, Sapitchaya Khamkhom 1, Sittiporn Parnmen 2
and Achariya Rangsiruji 1*
1 Department of Biology, Faculty of Science, Srinakharinwirot University, Bangkok, 10110
2 National Institute of Health, Department of Medical Sciences, Ministry of Public Health,

Nonthaburi 11000
* Project Advisor Email: [email protected]

Abstract
Boletaceae is a large family of fungi in the order Boletales, in which the fruiting
structures bear pores rather than gills. Many genera contain highly priced edible
mushrooms which are an important source of functional foods. The members of
this family (boletes) are diverse, but some are hard to be distinguished
morphologically. Hence, this study focused on molecular systematics of some
wild edible boletes based on sequence data of the internal transcribed spacer (ITS)
regions and nuclear-encoded large subunit ribosomal DNA (LSU). The resulting
neighbor-joining tree revealed that the bolete samples obtained from Ubon
Ratchathani Province were classified into four genera, including Phlebopus,
Tylopilus, Boletus and Leccinum with high bootstrap values. The richness of these
ectomycorrhizal boletes can be used as a bio-indicator of the high diversity of
host plants in tropical forests.
Keywords: Bio-indicator, Bolete, Ectomycorrhiza, ITS, LSU, Neighbor-joining
method

121

SCIFA R 2021
Anatomical studies on selected Annonaceae medicinal plants in
Thailand

Thanaporn Sungsorn, Ratchada Chanakaree and Anitthan Srinual *
Department of Biology, Faculty of Science, Srinakharinwirot University, Bangkok, 10110
* Project Advisor Email: [email protected]

Abstract
Anatomical investigation of some medicinal plants of the Family Annonaceae in
Thailand. The leaf epidermis was examined using peeling and clearing methods.
The transverse sections of the leaf blades and petioles were prepared using the
paraffin method. The wood specimens were also sections in three planes
including transverse, radial and tangential sections by a sliding microtome.
The anatomical characteristics were useful for the identification are as follows:
1) the ornamentation of cuticle; 2) the shapes of epidermal cell; 3) the outlines of
cell wall; 4) the types of trichome; 5) the types of inclusion and secretory structure
in epidermis; 6) the types and shapes of vascular bundle in midrib; 7) the positions
of palisade; 8) the shapes of leaf margin; 9) the structures of petiole, 10) the types
of trichome and secretory structure; 11) the compositions of ray parenchyma;
12) the porosity of vessels; 13) the arrangements of vessel; 14) the outlines of
vessel; 15) the types of perforation plate; 16) the presence or absence and
positions of gelatinous fibre; 17) the thickness of fibre wall; 18) the presence or
absence of septate fibers and 19) the types of axial parenchyma.
Keywords: Annonaceae, Medicinal plant, Thailand

122

SCIFA R 2021
Development of a simple PCR-RFLP marker technique to determine
the genetic relationship of some species in Cucurbitaceae

Panida Yimchoy, Kamonchanok Kongthong, Chayada Uyanontharuk, Wuttipong Tongbai and
Somkiat Phornphisutthimas*
Department of Biology, Faculty of Science, Srinakharinwirot University, Bangkok, 10110
* Project Advisor Email: [email protected]

Abstract
Cucurbitaceae is an economic crop cultivated in Thailand and various countries.
Many species are similar in morphology and are difficult to be identified.
Therefore, the researchers used molecular biology technique to distinguish
between species of Cucurbitaceae. This research involved the extraction process
of plant genetic material and simple polymerase chain reaction. Based on the
Cucurbitaceae nucleotide sequences obtained from GenBank, a molecular marker
for PCR-Restriction Fragment Length Polymorphism (PCR-RFLP) technique
was designed for analyzing the genetic relationship of eight species of
Cucurbitaceae including watermelon (Citrullus lanatus Mats. & Nakai),
Muskmelon (Cucumis melo L. var. conomon), Cantaloupe (Cucumis melo L. var.
cantaloupes), Melon (Cucumis melo L. var. cantalpensis), Wax gourd (Benincasa
hispida Cogn.) cucumber (Cucumis sativus L.) Chayote (Sechium edule Sm.) and
Bitter gourd (Momordica charantia L.). A pair of primers derived from the DNA
sequences of non-coding region between internal transcribed spacer 1 (ITS1) and
internal transcribed spacer 2 (ITS2) was used for PCR amplification. The
restriction sites on the DNA sequences were analyzed by using the website
https://molbiotools.com/restrictionanalyzer.php. The results indicated that two
restriction enzymes, ClaI and EcoRV, are suitable for classifying eight species of
Cucurbitaceae.

Keywords: Cucurbitaceae, DNA sequence, ITS1, ITS 2, PCR–RELP, Restriction
enzyme

123

SCIFA R 2021
Anatomy of leaf blade and stem of the genus Trapa, Ammannia and
Rotala in Thailand

Kongphol Chamnan1, Phongsak Phonsena2 and Anitthan Srinual 1*
1 Department of Biology, Faculty of Science, Srinakharinwirot University, Bangkok, 10110
2 Forest and Plant Conservation Research Office, Wildlife and Plant Conservation, Bangkok,

10900
* Project Advisor Email: [email protected]

Abstract
The anatomical characteristics of leaf blade and stem in three genera including
Ammannia, Rotala and Trapa which are belonging to the family Lythraceae were
determined. Peeling method was used for epidermal study, and paraffin method
was used for leaf blade and stem transverse sections. The results indicated that
the significant characteristics of epidermis for identification were comprised of
the ornamentation of cuticle, the presence or absence of stomata, the presence or
absence of trichomes and inclusions. The characteristics in transverse section of
leaf blade and stem also provided informative data which can be used for species
identification, including the presence or absence of cuticle layers on leaf margin,
the shapes of leaf margin, the types of inclusions in the leaf margin, the number
of the palisade layers, the shapes of the midrib, the shapes of vascular bundles in
the midrib, the types of inclusions in the midrib, the shapes of the stem, the
number of aerenchyma layers in the stem and the types of inclusions in the stem.
Keywords: Anatomy, Ammannia, Rotala, Trapa, Thailand

124

SCIFA R 2021
Molecular identification of myotoxin-containing mushrooms

Sanupong Kimakhom 1, Sittiporn Parnmen 2 and Achariya Rangsiruji 1*
1 Department of Biology, Faculty of Science, Srinakharinwirot University, Bangkok, 10110
2 National Institute of Health, Department of Medical Sciences, Ministry of Public Health,

Nonthaburi 11000
* Project Advisor Email: [email protected]

Abstract
Myotoxin-containing mushrooms include the genus Russula which contains 450
species distributed throughout the world. Russula subnigricans is the major cause
of several fatal cases of rhabdomyolysis in Thailand. Morphologically, it
resembles other wild edible species, including R. nigricans and R. densifolia.
Therefore, R. subnigricans is often misidentified as edible. In the present study,
ribosomal DNA sequences from the internal transcribed spacer (ITS) regions and
nuclear-encoded large subunit ribosomal DNA (LSU) were assessed to determine
phylogenetic positions of 10 unknown samples of Russula. Based on neighbor-
joining analysis these samples were distinguished into four groups of R. nigricans
(5 samples), R. subnigricans (2 samples), and R. densifolia (3 samples). Hence,
the ITS and LSU loci can be used as DNA barcodes for species identification of
mushrooms.
Keywords: ITS, LSU, Myotoxin-containing mushroom, Phylogenetics, Russula

125

SCIFA R 2021
Diversity of MSDIN family members in a hepatotoxic mushroom
(Amanita brunneitoxicaria)

Punnapron Ieadmun 1, Jaraswadee Prasertprom 1, Sittiporn Parnmen 2 and Achariya Rangsiruji 1*
1 Department of Biology, Faculty of Science, Srinakharinwirot University, Bangkok, 10110
2 National Institute of Health, Department of Medical Sciences, Ministry of Public Health,

Nonthaburi 11000
* Project Advisor Email: [email protected]

Abstract
Amanita brunneitoxicaria, a hepatotoxic mushroom, is the causative agent of
fatal mushroom poisoning in Thailand. This species contains lethal toxins
known as cyclopeptides, including amatoxins and phallotoxins, which are
encoded by short nucleotide sequences of the MSDIN family. Hence, the aim of
this study was to investigate the diversity of toxin-associated genes in the
MSDIN family in A. brunneitoxicaria. A 300-bp PCR product specific to the
MSDIN family was derived from a sample of A. brunneitoxicaria, and used for
DNA cloning. Ten white colonies were selected for Sanger sequencing. Two
types of gene sequences were obtained and phylogenetic analysis revealed the
classification of these sequences as amatoxins (α-amanitin and β-amanitin).
Keywords: Amanita, Amatoxin, Cyclopeptide, DNA cloning, MSDIN family

126

SCIFA R 2021
Comparative relation between reproductive success and rarity of
orchids in Khao Soi Dao Wildlife Sanctuary

Peerada Lhapawong, Nichagan Pongchey and Wittaya Pakum *
Department of Biology, Faculty of Science, Srinakharinwirot University, Bangkok, 10110
* Project Advisor Email: [email protected]

Abstract
Recently, populations of wild orchids in Thailand have been depleted and many
species are threatened with extinction. Therefore, this research aims to assess
the reproductive success and rarity of orchids in the Khao Soi Dao Wildlife
Sanctuary. The study sites were plotted into 3 natural study trail: Khao Soi Dao
Waterfall, Pha Hin Koob and Huai Hin Dad. In field observation, 45 species were
found. During the flowering period, 11 of 45 species were monitored. In a
20x20 m2 transect line plot, plant individuals, flower buds, and fruits of each
species were counted and recorded. Reproductive success and rarity were
assessed by the percentage of natural fruit set and the frequency of individuals,
respectively. The highest reproductive success was found on Habenaria gibsonii
Hook.f. (92.20%), while the lowest reproductive success was found on Phalaenopsis
cornucervi (Breda) Blume & Rchb. f. (2.18%). The rarest species (low frequency)
were found on 6 species. The most common species was Cymbidium aloifolium
(L.) Sw. The correlation between the number of flowers and fruit set depends on
species. There were only two species where more flowers per inflorescence
enhanced more fruit setting. Reproductive success did not depend on individual
numbers or rarity.
Keywords: Khao Soi Dao, Orchid, Rarity, Reproductive success

127

SCIFA R 2021
Comparison of leaf and wood anatomical characteristics of some
species of the tribe Uvarieae in Thailand

Sutthathip Inchan, Tevich Khemayan, Sitapat Keitbunjong and Anitthan Srinual *
Department of Biology, Faculty of Science, Srinakharinwirot University, Bangkok, 10110
* Project Advisor Email: [email protected]

Abstract
The anatomical investigations of leaf blade, petiole, and wood of 10 species of
the tribe Uvarieae (Annonaceae) in Thailand. The purpose of present study was
to examine anatomical characteristics which can be used for species identification.
The epidermal features of leaf were prepared by peeling and clearing methods
and stained with safranin. The transverse sections of leaf blade and petiole were
studied by paraffin method, then double stained in safranin and fast green. The
transverse and longitudinal sections of wood were cut by sliding microtome and
stained with safranin. The results indicated that the anatomical characteristics
including types of stomata, types of crystals, types of trichomes, the outlines of
the apex of leaf margin, shapes of petiole, the presence or absence of the septate
in fibre and the compositions of ray parenchyma are useful for species
identification.
Keywords: Annonaceae, Plant anatomy, Thailand, Uvarieae

128

SCIFA R 2021
Anatomical investigation of vegetative parts of the tribe Miliuseae
(Annonaceae) in Thailand

Supagorn Changjeen, Sottivat Tongampai, Ananda Chantakat and Anitthan Srinual *
Department of Biology, Faculty of Science, Srinakharinwirot University, Bangkok, 10110
* Project Advisor Email: [email protected]

Abstract
Leaf blade, petiole and wood anatomy of the tribe Miliuseae (Annonaceae)
were examined by leaf peeling and clearing methods, transverse section of leaf
blade and petiole, and transverse, tangential and radial sections of wood. The
anatomical characteristics, e.g., the shapes of cells in leaf blade, the types of
stomata, the types of trichome, the shapes of vascular bundle in petiole, the types
of axial parenchyma in wood, the presence or absence of crystals and inclusions
which were able to be used for genus and species idenfication. The results showed
that types of stomata can be used to identify the genus Mitrephora, the presence
of paracytic stomata only on the lower epidermis were found in M. alba and
M. tomentosa, whereas the presence of paracytic stomata on the lower epidermis
and the low density of anomocytic stomata on the upper epidermis were found in
M. winitii. Therefore, the significant anatomical features can fulfill the anatomical
database and can be used to construct keys for species identification.
Keywords: Anatomy, Annonaceae, Tribe Miliuseae

129

SCIFA R 2021
Comparative in vitro seed germination and seedling development
of orchids in Khao Soi Dao Wildlife Sanctuary

Yanisa Yingyongyuth, Dudphet Keawmanee, Kanokpohn Thongwattana and
Wittaya Pakum *
Department of Biology, Faculty of Science, Srinakharinwirot University, Bangkok, 10110
* Project Advisor Email: [email protected]

Abstract
Soi Dao Wildlife Sanctuary (SDWS) is a place of wild orchid diversity. Recently,
populations of many species are dramatically depleted. To compare seed number
per fruit, seed germination and seedling development of six orchid species
(Coelogyne filipeda Gagnep., Habenaria gibsonii Hook.f., Phalaenopsis deliciosa
Rchb.f., Pholidota imbricata Hook., Vanilla siamensis Rolfe ex Downie and
Phalaenopsis difformis (Wall. ex Lindl.) Kocyan & Schuit.) were collected from
SDWS. The seeds were counted and then cultured on varied culture media (VW,
MS, and ½MS) for 12 weeks. There were two species that seed germination was
found. In C. filipeda, VW could induce the highest percentage of germination
(45.3%) and induce seedlings into stage 5. In Pha. difformis, VW could induce
the highest percentage of germination (9.0%) and induce seedlings into stage 3.
The result showed that the culture medium should be screened for orchid
conservation via seed propagation in vitro.
Keywords: Orchid, Plant tissue culture, Seed germination, Seed per pod, Seedling
development

130

SCIFA R 2021
Verification of somaclonal variation by RAPD marker and SCoT
marker of Dendrobium draconis Rchb.f. from tissue culture

Polathip Boonma, and Rakchanok Koto *
Department of Biology, Faculty of Science, Srinakharinwirot University, Bangkok, 10110
* Project Advisor Email: [email protected]

Abstract
The objective of this research was to verify the somaclonal variation by RAPD
marker and SCoT marker of Dendrobium draconis Rchb.f. from tissue culture.
Ten tissuecultured orchid leaves were sampled for DNA extraction by the CTAB
method, and DNA amplification was performed using the PCR technique. It uses
the RAPD molecular marker and the ScoT molecular marker. The DNA
fingerprinting was then tested by the gel electrophoresis technique on a 1%(w/v)
agarose gel. Four RAPD primers yielded clear results: OPA11, OPA13, OPH19,
and OPK1, which yielded a total of 19 specific DNA bands without pattern
differences (monomorphic). As for using ScoT primers, it was found that there
were 12 ScoT primers with clear results: ME2, ME8, S4, S5, S7, S9, S10, S12,
S17, S33, S34, S35, yielding a total of 49 specific DNA bands, with no difference
in DNA patterns (monomorphic). Therefore, it concludes that there was no
somaclonal variation in the tissue culture of Dendrobium draconis Rchb.f.
Keywords: Dendrobium draconis, RAPD marker, SCoT marker, Somaclonal
variation, Tissue culture

131

SCIFA R 2021
Wireless-power transfer experimental kit for undergraduate Physics
laboratory

Papavee Kaewtun, Rawiporn Somsai and Surawut Wicharn *
Department of Physics, Faculty of Science, Srinakharinwirot University, Bangkok, 10110
* Project Advisor Email: [email protected]

Abstract
Currently, wireless-power transfer technology has been widely used in our daily
lives. Especially, almost wearable and portable devices such as smartphones,
tablets, smartwatches, and earphones are available for wireless charging.
Consequently, the basic principle of this technology can be made understandable
even for undergraduate students. In this work, a wireless-power transfer
experimental kit was designed and constructed with basic electronic components.
The designed kit is user-friendly, simple, and easy to assemble for freshmen and
sophomore students. The physics behind the experimental kit is based on strongly
coupled magnetic resonances between transmitter and receiver. Both systems
were made of tank circuits consisting of resistors, capacitors, and inductors
(transmitting and receiving coils) connected in series. By following experimental
procedures, the students will be learned why they have to adjust the input ac
signal to resonant frequencies (around 1.0 – 1.7 kHz), which causes the maximum
power transfer between transmitter and receiver. They will be also learned why
the number of coil turns, the diameter of coils, and the distance between two coils
affect the efficiency of a wireless power transfer system.

Keywords: Coupled magnetic resonance, Power transfer efficiency, Resonant
frequency, Wireless-power transfer

132

SCIFA R 2021
The study of simple harmonic motion and damped oscillation by
using Phyphox application

Phitchakon Thongsri, Panadda Sinthuchai and Surawut wicharn *
Department of Physics, Faculty of Science, Srinakharinwirot University, Bangkok, 10110
* Project Advisor Email: [email protected]

Abstract
The objective of this project is to study the motion of a simple pendulum and of
damping oscillation by using Phyphox application. In the first experiment, the
pendulum length is varied to 0.30 m, 0.35 m, 0.40 m, 0.45 m, 0.50 m, 0.55 m, and
0.60 m and the initial angles of the pendulum arm are set at 10° and 25°,
respectively. After releasing the pendulum ball, the time-dependent motion of the
pendulum system was tracked by Phyphox application. The measured results
from application provided periodic motion of the pendulum system. Then, the
square of the period and the pendulum length are linearly fitted in Microsoft Excel
for calculating the slope of the graph. The average calculated slope is 9.78 m/s2,
which is the gravitational acceleration of the earth at the considered position
(Bangkok). In the last experiment, the center punched cardboard was attached to
the ball bottom to create the damping oscillation. The pendulum length and initial
angle are set at 0.50 m and 25°. The time-dependent damping oscillation was also
tracked by Phyphox application. After that, the measured results were different
from the case of the simple pendulum. The results showed periodic motion with
exponentially decreasing amplitudes due to air resistance.
Keywords: Simple harmonic oscillation, Damping oscillation, Phyphox

133