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
This project focuses on developing a test device for an AC charger for electric vehicles according to the IEC 61851-1 Annex A standard by simulating the test circuit inside an electric vehicle according to the standard to test the operation of the AC charger. The test topic is related to the communication between the electric vehicle and the charger via a Pulse Width Modulation (PWM) control circuit system and creating an operation manual (WI) to prepare for testing in accordance with ISO/IEC 17025 standards, which are general requirements for laboratory capabilities in conducting tests and/or calibrations. The overall picture of this project is to develop test equipment and create an operation manual by collecting knowledge and various devices and then comparing the data to meet the abovementioned standards to test the Type II AC charger in each state. The test equipment consists of a communication part between the test equipment and the AC charger using a PLC S7-1200 and an HMI to control the operation of the switches in the test equipment circuit, including controlling parameters and displaying results. The equipment used to measure values is an oscilloscope and a multimeter that have undergone a calibration process to comply with the specified standards.
คณะอุตสาหกรรมอาหาร
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)
วิทยาลัยอุตสาหกรรมการบินนานาชาติ
The capture of a target spacecraft by a chaser is an on-orbit docking operation that requires an accurate, reliable, and robust object recognition algorithm. Vision-based guided spacecraft relative motion during close-proximity maneuvers has been consecutively applied using dynamic modeling as a spacecraft on-orbit service system. This research constructs a vision-based pose estimation model that performs image processing via a deep convolutional neural network. The pose estimation model was constructed by repurposing a modified pretrained GoogLeNet model with the available Unreal Engine 4 rendered dataset of the Soyuz spacecraft. In the implementation, the convolutional neural network learns from the data samples to create correlations between the images and the spacecraft’s six degrees-of-freedom parameters. The experiment has compared an exponential-based loss function and a weighted Euclidean-based loss function. Using the weighted Euclidean-based loss function, the implemented pose estimation model achieved moderately high performance with a position accuracy of 92.53 percent and an error of 1.2 m. The in-attitude prediction accuracy can reach 87.93 percent, and the errors in the three Euler angles do not exceed 7.6 degrees. This research can contribute to spacecraft detection and tracking problems. Although the finished vision-based model is specific to the environment of synthetic dataset, the model could be trained further to address actual docking operations in the future.