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)
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คณะสถาปัตยกรรม ศิลปะและการออกแบบ
This app encourages users to clean by turning it into a fun game. Users can choose cleaning tasks, track dust levels, and earn reward points, making the cleaning process more engaging and enjoyable.
คณะวิศวกรรมศาสตร์
This research suggested natural hemp fiber-reinforced ropes (FRR) polymer usage to reinforce recycled aggregate square concrete columns that contain fired-clay solid brick aggregates in order to reduce the high costs associated with synthetic fiber-reinforced polymers (FRPs). A total of 24 square columns of concrete were fabricated to conduct this study. The samples were tested under a monotonic axial compression load. The variables of interest were the strength of unconfined concrete and the number of FRRlayers. According to the results, the strengthened specimens demonstrated an increased compressive strength and ductility. Notably, the specimens with the smallest unconfined strength demonstrated the largest improvement in compressive strength and ductility. Particularly, the compressive strength and strain were enhanced by up to 181% and 564%, respectively. In order to predict the ultimate confined compressive stress and strain, this study investigated a number of analytical stress–strain models. A comparison of experimental and theoretical findings deduced that only a limited number of strength models resulted in close predictions, whereas an even larger scatter was observed for strain prediction. Machine learning was employed by using neural networks to predict the compressive strength. A dataset comprising 142 specimens strengthened with hemp FRP was extracted from the literature. The neural network was trained on the extracted dataset, and its performance was evaluated for the experimental results of this study, which demonstrated a close agreement.
คณะวิทยาศาสตร์
The development of a fruit spoilage detection system originates from the need to reduce agricultural product losses, a global issue affecting both the agricultural and food distribution industries. Spoiled fruit can negatively impact product quality and result in significant economic losses. The primary goal of this system is to assist in screening and removing unsuitable fruit from the supply chain, thereby preserving product quality and meeting consumer demands for fresh produce. The system was designed to simulate the sorting process by utilizing images as a key factor in detecting spoiled fruit. Experimental results demonstrated high efficiency and rapid prediction capabilities, highlighting the system’s potential for practical applications.