Coffee is a critical agricultural commodity to be used to produce a premium beverage to serve people worldwide. Coffee microbiome turned to be an essential tool to improve the bean quality through the natural fermentation. Therefore, understanding the microbial diversities could create the final product's better quality. This study investigated the natural microbial consortium during the wet process fermentation of coffee onsite in Thailand to characterize the microorganisms involved in correlation toward the biochemical characteristics and metabolic attributes. Roasting is another important step in developing the complex flavor/ aroma that make coffee to be enjoyable. During the roasting process, the beans undergo many complex and alternatively change in the physicochemical properties from the gained substances in the fermentation process. The changing in the formation of the substances responsible for the sensory qualities, physicochemical/ aroma attributes as well as the health benefits of the final product. Using the starter culture could also develop the distinguished characteristics of coffee (Research collaboration with Van Hart company)
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คณะเทคโนโลยีการเกษตร
Dwarf whipray (Brevitrygon heterura) is a common species found in a local market in the Gulf of Thailand. However, like many other species of stingrays, it is threatened by overfishing and habitat destruction. Therefore, an accurate species identification is crucial because conservation efforts may vary depending on the species. This study aims to understand morphological variation of B. heterura in the Gulf of Thailand by morphometric study and genetic analysis. During October 2022 and February 2023, we obtained 49 samples from research vessels fish landing ports and local fish markets. We observed two distinct groups based on 43 morphological variables/ratios. B. heterura samples from Chanthaburi, Rayong, Chonburi, Samut Sakhon, Nakhon Si Thammarat and Songkla provinces, called “group A," typically have longer snout length than those from Prachuap Khiri Khan provinces, called “group B" according to external morphological characters for species identification. Three morphological variables/ratios were significantly different between groups A and B. Main characters to explain intraspecific variations between group A and group B are further discussed. DNA barcoding based on a fragment of the cytochrome c oxidase subunit I (COI) gene were obtain from eight samples of group A and eight samples from group B. Pairwise percent sequence divergence (p-distance) for COI between group A and group B were 0.0-2.5. This study contributes to the understanding of variations of morphology and genetics of B. heterura in the Gulf of Thailand.
คณะวิทยาศาสตร์
In today’s rapidly expanding e-commerce environment, the massive volume of product reviews makes it crucial to summarize user opinions in a way that is both comprehensible and practically applicable. This research presents a system for analyzing product reviews using Aspect-Based Sentiment Analysis (ABSA), a Natural Language Processing (NLP) technique that identifies key aspects of a review (such as shipping, product quality, and packaging) and evaluates the sentiment (positive, negative, or neutral) associated with each aspect, allowing both consumers and merchants to gain more efficient access to in-depth insights. This project focuses on developing AI for Thai-language ABSA by utilizing WangchanBERTa, a model trained on Thai data, and comparing it with various standard approaches such as TF-IDF + Logistic Regression, Word2Vec + BiLSTM, and Multilingual BERT (mBERT/XLM-R) to assess their performance in terms of accuracy, speed, and resource usage. Additionally, a dashboard visualization is provided to help users quickly grasp review trends. The expected outcome is to create an AI tool that can be practically employed in the e-commerce industry, enabling consumers to make easier purchasing decisions and assisting merchants in effectively improving their products and services.
คณะวิทยาศาสตร์
This project presents the development of a "Smart Cat House" using Internet of Things (IoT) and image processing technology to facilitate and enhance the safety of cat care for owners. The infrastructure of the smart cat house consists of an ESP8266 board connected to an ESP32 CAM camera for cat monitoring, and an Arduino board that controls various sensors such as a motion sensor in the litter box, a DHT22 temperature and humidity sensor, an ultrasonic water and food level sensor, including a water supply system for cats, an automatic feeding system, and a ventilation system controlled by a DC FAN that adjusts its operation according to the measured temperature to maintain a suitable environment. There is also an IR sensor to detect the cat's entry into the litter box and an automatic sand changing system with a SERVO MOTOR. All systems are connected and controlled through the Blynk application, which can be used on mobile phones, allowing owners to monitor and care for their pets remotely. Cat detection and identification uses image processing technology from the ESP32 CAM camera in conjunction with YOLO (You Only Look Once), a high-performance object detection algorithm, to detect and distinguish between cats and people. Data from various sensors are sent to the Arduino board to control the operation of various devices in the smart cat house, such as turning lights on and off, automatically changing sand, adjusting temperature and humidity, feeding food and water at scheduled times, or ventilation. The use of a connection system via ESP8266 and the Blynk application makes it easy and convenient to control various devices. Owners can monitor and control the operation of the entire system from anywhere with internet access.