The study investigated the extraction of astaxanthin-rich oil from shrimp waste biomass, a valuable byproduct rich in functional lipids and proteins. Wet rendering has long been an inexpensive method to extract oil, however the high temperatures and long cooking times negatively affect the amount of astaxanthin. On the other hand, the study looked into employing deep eutectic solvent as a green solvent and combining a wet rendering process with high-shear homogenization and high-frequency ultrasound-assisted extractions. DES-UAE at 60% amplitude and wet rendering at 60 °C were found to be the ideal conditions, as were DES-HAE at 13,000 rpm and wet rendering at 60 °C. With a notable increase in oil yields of 16.80% and 20.12%, respectively, and improved oil quality (lower acid and peroxide values) in comparison to the conventional wet rendering, experimental validation validated the effectiveness of the DES-HAE and DES-UAE procedures. DES-UAE notably raised the amount of astaxanthin. This study demonstrates that DES-HAE and DES-UAE are quicker, lower-temperature substitutes for obtaining premium, astaxanthin-rich shrimp oil, resulting in more effective use of this priceless byproduct.
Sustainability and Waste Utilization: Upcycling shrimp byproducts into valuable oil helps ensure that seafood manufacturing is waste-free. Potential for Nutraceutical & Functional Food Applications
วิทยาเขตชุมพรเขตรอุดมศักดิ์
This project aims to design and develop a propulsion system for agricultural equipment using RFID technology and evaluate its movement performance on different surfaces, including concrete and grass. The experiment focuses on examining the tag detection range under transmission power levels of 20 dBm, 23 dBm, and 26 dBm, as well as the impact of antenna angles on detection efficiency. Additionally, the system was tested in three movement scenarios: straight path, left turn, and right turn, at distances of 2 meters, 4 meters, and 6 meters. The results indicate that the system achieved the highest average speed of 0.4736 m/s and an average turning angle of 91.6° when moving in a straight path on a concrete surface at a distance of 4 meters. On a grass surface at the same distance, the average speed was 0.4483 m/s, with an average turning angle of 91.1°. For left and right turns, the movement on the concrete surface generally exhibited a higher average speed than on grass, particularly at a distance of 4 meters, where differences in turning angles were observed. This study provides insights into the factors affecting the movement of agricultural mowing equipment and serves as a foundation for enhancing the efficiency of propulsion systems in future developments.
คณะเทคโนโลยีการเกษตร
Public Park Project: Coastal folk Park is a design park in the area of Ang Sila Subdistrict, Chonburi Province. In an area of 22 acre, it is intended to be a place of rest, recreation, and also a source of learning and conservation of the seashore and the traditional way of life of the area.
คณะเทคโนโลยีสารสนเทศ
This report is part of applying the knowledge gained from studying machine learning models and methods for developing a predictive model to identify customers likely to cancel their credit card services with a bank. The project was carried out during an internship at a financial institution, where the creator developed a model to predict customers likely to churn from their credit card services using real customer data through the organization's system. The focus was on building a model that can accurately predict customer churn by selecting features that are appropriate for the prediction model and the unique characteristics of the credit card industry data to ensure the highest possible accuracy and efficiency. This report also covers the integration of the model into the development of a website, which allows related departments to conveniently use the prediction model. Users can upload data for prediction and receive model results instantly. In addition, a dashboard has been created to present insights from the model's predictions, such as identifying high-risk customers likely to cancel services, as well as other important analytical information for strategic decision-making. This will help support more efficient marketing planning and customer retention efforts within the organization.