This study aims to develop alginate-based hydrogels reinforced with carrageenan and gellan gum as composite materials for oral drug delivery. Alginate, a naturally derived polymer from brown algae, forms a gel upon exposure to cations such as calcium ions, enhancing the hydrogel’s structural integrity. Carrageenan and gellan gum, both polysaccharides, further improve stability and encapsulation efficiency. This research investigates the physical properties, mechanical strength, encapsulation capacity, and swelling behavior of hydrogel beads under simulated gastrointestinal conditions. The findings are expected to demonstrate that incorporating carrageenan and gellan gum enhances the durability and stability of hydrogel beads while enabling controlled release of active compounds in the gastrointestinal tract. These advanced hydrogel beads hold significant potential for applications in the food and pharmaceutical industries as effective oral delivery systems for bioactive substances.
ในงานวิจัยนี้มีจุดมุ่งหมายเพื่อพัฒนาไฮโดรเจลบีดส์จากอัลจิเนตที่เสริมด้วยคาร์ราจีแนนและเจลแลนกัม โดยมีคุณสมบัติที่ช่วยเสริมความแข็งแรงและความยืดหยุ่นให้กับโครงสร้างของไฮโดรเจลบีดส์ เพื่อเพิ่มความทนทานและเสถียรภาพมากขึ้น ซึ่งสามารถนำมาใช้ในการห่อหุ้มและปกป้องสารสำคัญ โดยมุ่งเน้นการควบคุมการปลดปล่อยสารสำคัญไปยังจุดเป้าหมาย การศึกษานี้จะครอบคลุมถึงลักษณะทางกายภาพ ความแข็งแรงของไฮโดรเจลบีดส์ และความสามารถในการกักเก็บสารสำคัญ ลักษณะทางกายภาพและการบวม (Swelling) ภายใต้สภาวะจำลองทางเดินอาหาร โดยใช้สารจำลองน้ำย่อยทั้งในกระเพาะอาหารและลำไส้ การพัฒนาไฮโดรเจลบีดส์จากอัลจิเนตที่เสริมด้วยคาร์ราจีแนนและเจลแลนกัมมีศักยภาพในการนำไปใช้งานในอุตสาหกรรมเภสัชกรรมและอาหารที่ต้องการห่อหุ้มสารสำคัญที่มีประสิทธิภาพสูงในอนาคต
คณะเทคโนโลยีการเกษตร
This study examines the effects of chemical mutagens, ethyl methane sulfonate (EMS) and colchicine in inducing mutations in Chrysanthemum spp. through tissue culture techniques. In vitro cultures of Chrysanthemum were treated with various concentrations of EMS and colchicine to assess their impact on shoot regeneration and mutation frequency. Results indicated that EMS significantly increased phenotypic variability, leading to enhanced flower color and size, while colchicine treatment effectively induced polyploidy, resulting in plants with greater flower size and overall vigor. Morphological assessments, along with genetic analyses using molecular markers, confirmed the mutations associated with these treatments. The integration of chemical mutagenesis with tissue culture presents a promising approach for developing novel Chrysanthemum varieties with improved ornamental traits.
คณะอุตสาหกรรมอาหาร
This research aims to optimize the production process of gamma-aminobutyric acid (GABA) in fermented pineapple juice using probiotics and acetic acid bacteria (AAB), which are microorganisms with the potential to enhance GABA levels. This process has been developed to improve the nutritional value of fermented pineapple juice and to increase the economic value of Thai pineapples, which have long suffered from low market prices. This study focuses on determining the optimal conditions for GABA production by examining factors such as sugar content, pH levels, fermentation duration, and L-glutamate concentration, as well as the co-cultivation of probiotics and acetic acid bacteria. The experiments are conducted using controlled fermentation techniques, and the bioactive components of the fermented juice are analyzed with advanced instruments such as HPLC and GC-MS. The findings of this research are expected to contribute to the development of formulations and production processes for a high-GABA pineapple-based functional beverage. This product could offer health benefits such as stress reduction, cognitive function enhancement, and relaxation while also strengthening the potential of Thailand’s fermented food and beverage industry.
คณะวิศวกรรมศาสตร์
Jaundice, a common condition in infants that results from high bilirubin levels in the blood, often requires early diagnosis and monitoring to prevent severe complications, especially in newborns. Traditional diagnostic methods can be time-consuming and subject to human error. This study proposes an approach for real-time jaundice detection using advanced image processing techniques and machine learning algorithms. By analyzing images captured in RGB color spaces, pixel values are extracted and processed through Otsu’s thresholding and morphological operations to detect color patterns indicative of jaundice. A classifier model is then trained to distinguish between normal and jaundiced conditions, offering an automated, accurate, and efficient diagnostic tool. The system’s potential to operate in real-time makes it particularly suited for clinical settings, providing healthcare professionals with timely insights to improve patient outcomes. The proposed method represents a significant innovation in healthcare, combining artificial intelligence and medical imaging to enhance the early detection and management of jaundice, reducing reliance on manual interventions and improving overall healthcare delivery.