This study aims to investigate the co-fermentation process between lactic acid bacteria (LAB) and Saccharomyces cerevisiae in the production of sour beer, with a focus on its impact on product quality, including pH, organic acid content, sugar content, and sensory characteristics. In this experiment, selected LAB strains and S. cerevisiae were utilized under controlled fermentation conditions. The microbial ratio was optimized to enhance growth and the production of key compounds. The findings indicate that co-fermentation significantly reduces pH compared to fermentation with yeast alone. Furthermore, an increase in lactic acid was observed due to sugar consumption by LAB, contributing to the distinctive flavor profile of sour beer.
เบียร์เปรี้ยว (Sour Beer) เป็นเบียร์ประเภทหนึ่งที่มีรสเปรี้ยวเฉพาะตัว ซึ่งเกิดจากกระบวนการหมักที่ต่างจากเบียร์ทั่วไป ความเปรี้ยวของ เบียร์เปรี้ยวเกิดจากการใช้แบคทีเรียกรดแลกติก (Lactic acid bacteria) และยีสต์เช่น Lactobacillus และ Pediococcus,ในการหมักเพิ่มทางเลือกให้กับผู้บริโภค Sour Beer เป็นตัวเลือกที่น่าสนใจสำหรับคนที่ต้องการประสบการณ์รสชาติใหม่ๆ แตกต่างจากเบียร์รสขมทั่วไป โดยมีทั้งรสเปรี้ยวที่เบาและรสเข้มข้น การหมักและกระบวนการผลิตเฉพาะทาง การทำ Sour Beer ต้องใช้ความรู้และเทคนิคพิเศษทำให้ต้องมีการควบคุมกระบวนการหมักอย่างใกล้ชิดซึ่งส่งเสริมการพัฒนาทักษะและนวัตกรรมในอุตสาหกรรมการผลิตเบียร์ ผู้ผลิตต้องเข้าใจลักษณะของจุลินทรีย์ที่ใช้และรู้จักการควบคุมรสชาติ ทำให้ Sour Beerมีความสำคัญในการพัฒนาอุตสาหกรรมเบียร์ไปสู่ความสร้างสรรค์ใหม่ๆ
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.
คณะเทคโนโลยีสารสนเทศ
Traditional methods of public relations and learning often lack engagement and fail to provide users with a deep and immersive experience. Additionally, these methods struggle to reach a wide audience, especially those unable to visit the physical location. This project aims to solve the issues of accessibility and awareness regarding the institution’s Chalermphrakiat Hall and historical exhibition. Utilizing metaverse technology to simulate important locations allows users to explore the site and view key information in a virtual format, thereby enhancing the engagement of students staff alumni and the general public. The metaverse system is developed using Unity, a powerful game engine capable of supporting the creation of metaverse environments. This allows for the creation of an interactive and realistic virtual space. Unity also supports the management of physics, lighting, and sound, further enhancing realism. Additionally, the system is integrated with web browsers using WebGL technology, enabling the project developed in Unity to be accessed directly through a browser. Users can visit and interact with the metaverse environment from anywhere without the need to install additional software. The developers have thus created the metaverse system to provide a realistic and engaging learning experience, enhancing public relations efforts and fostering a strong connection with the institution efficiently.
คณะเทคโนโลยีการเกษตร
The objective of this experiment was to determine the effect of nitrogen and potassium concentration combination with photoperiod on the growth of Viola in a plant factory to increase the quality of the products, reduce the production time and increase the production cycle throughout the year. The experimental plan was 3x3 Factorial in CRD with nine treatments and three replications (six plants per replication). The factor of this study was two factors; the first factor was three different concentrations of nitrogen and potassium in ratios of 1:1, 1:2 and 2:1. The second factor was the application of different photoperiods. There were 1) 24-hours photoperiod, 2) 8-hours light/16-hours dark photoperiod (Induced flowering state: 13-hours light/11-hours dark photoperiod) and 3) 5-hours light/3-hours dark photoperiod. Controlled temperature at 25 °C, the EC=1.5-2.0 mS/cm and the pH=5.8-6.5 in all treatment. The result showed that the concentration of N: K in the ratio of 1:1 combined with 24-hour photoperiod was the most vegetative growth and also maximizes reproductive growth. The overall great sensory evaluation was an acceptable level and suitable for cooking or decorating dishes. Therefore, the concentration of N: K in the ratio of 1:1 combined with 24-hour photoperiod is the best treatment to increase the quality of the product, reduce the production time of viola flowers in each cycle from 90-100 days down to 43-45 days which is good for farmers.