KMITL Expo 2026 LogoKMITL 66th Anniversary Logo

Designed Quality coffee from fermentation

Designed Quality coffee from fermentation

Abstract

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)

Objective

-

Other Innovations

Effect of Sorbitol Concentration as Plasticizer in Capsicum Oleoresin-Loadded Oral Disintegrating Film

คณะอุตสาหกรรมอาหาร

Effect of Sorbitol Concentration as Plasticizer in Capsicum Oleoresin-Loadded Oral Disintegrating Film

Oral disintegrating films (ODFs) can dissolve in the mouth instantly upon contact with saliva, without the need for water. This study aimed to investigate the effect of sorbitol concentration on the properties of oral disintegrating films containing Capsicum Oleoresin extract, which has properties that stimulate saliva secretion, making swallowing easier. The film was developed to address difficulties in swallowing, especially for individuals with dysphagia. The films were prepared using different concentrations of sorbitol and tested for rheological properties, mechanical properties, moisture content, free water content, thickness, disintegration time, contact angle, color, and antioxidant activity. The results indicated that sorbitol played a key role in increasing the flexibility and reducing the brittleness of the films. Additionally, an optimal concentration of sorbitol helped maintain the stability of the Capsicum extract and enhanced its efficacy in stimulating saliva secretion, thereby making swallowing more convenient and reducing oral friction. The films developed in this study demonstrate potential as an alternative for individuals with swallowing difficulties.

Read more
Safety Improvement Lifter

คณะวิศวกรรมศาสตร์

Safety Improvement Lifter

Mitsubishi Motors (Thailand) Co.,Ltd. This company has a zero-risk, zero-accident safety policy, and it has maintained records of all accidents that happened inside the factory in 2024.There have been 5 accidents to date, one of them was an accident that happened on the production line while the Production Engineer Assembly Department had control of it. I got this issue to be resolved as a result. by identifying issues, classifying them, and choosing solutions to address them. D using CCTV and AI cameras to identify behavior to prevent risky events from occurring by training AI with images or Equipment malfunctions, including pallets,X-Lifters, and conveyor Including designing the Concept Improvement of the software so that CCTV+AI Camera can detect it. Outcome following installation That area was accident-free after that. Avoid accidents Cut down on the losses that will happen Whether it be the costs incurred because of the accident Training new hires Resources for work or a variety of other purposes.

Read more
A Comparison of The Performance of Machine Learning Methods on Time Series Data Using Lagged Time Intervals

คณะวิทยาศาสตร์

A Comparison of The Performance of Machine Learning Methods on Time Series Data Using Lagged Time Intervals

This special problem aims to compare the performance of machine learning methods in time series forecasting using lagged time periods as independent variables. The lagged periods are categorized into three groups: lagged by 10 units, lagged by 15 units, and lagged by 20 units. The study employs four machine learning methods: Decision Tree (DT), Random Forest (RF), K-Nearest Neighbors (KNN), and Support Vector Machine (SVM). The time series data simulated as independent variables diverse including characteristics: Random Walk data, Trending data, and Non-Linear data, with sample sizes of 100, 300, 500, and 700. The research methodology involves splitting the data into 90% for training and 10% for testing. Simulations and analysis are performed using the R programming language, with 1,000 iterations conducted. The results are evaluated based on the average mean squared error (AMSE) and the average mean absolute percentage error (AMAPE) are calculated to identify the best performing method. The research findings revealed that for Random Walk data, the best performing methods are Random Forest and Support Vector Machine. For Trend data, the best performing methods are Random Forest. For Non-Linear data, the best performing methods are Support Vector Machine. When tested with real-world data, the results show that for the Euro-to-Thai Baht exchange rate, the best methods are Random Forest and Support Vector Machine. For the S&P 500 Index in USD, the best performing methods are Random Forest. For the Bank of America Corp Index in USD, the best performing methods are Support Vector Machine.

Read more