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Product development of fish ball from Blackchin tilapia (Sarotherodon melanotheron)

Abstract

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Objective

เนื่องจากปลาหมอคางดำมีการแพร่กระจายของประชากรได้อย่างรวดเร็ว จึงต้องมีการควบคุมประชากรของปลาหมอคางดำด้วยการนำไปใช้ประโยชน์ จึงมีการทดลองนำปลาหมอคางดำมาทำเป็นผลิตภัณฑ์ลูกชิ้นปลา เพราะลูกชิ้นปลาเป็นอาหารที่เข้าถึงได้ง่าย และโปรตีนสูงอีกทั้งยังเป็นอาหารที่เหมาะสมสำหรับทุกเพศทุกวัย

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“Equinest” Thai Fruit-Flavored Horse Treats to Enhance Equine Digestive Efficiency.

วิทยาลัยการจัดการนวัตกรรมและอุตสาหกรรม

“Equinest” Thai Fruit-Flavored Horse Treats to Enhance Equine Digestive Efficiency.

This research aims to develop a horse treat product that meets the nutritional and health needs of horses by using natural ingredients with beneficial properties, such as oats, wheat flour, corn flour, and organic molasses. These ingredients are rich in fiber, vitamins, and essential minerals for horses, while also enhancing digestive efficiency, reducing the risk of colic, and providing an appropriate energy source. The treat is designed with a shape suitable for a horse’s chewing behavior and is infused with Thai fruit flavors, such as pineapple and ripe mango, to attract horses and make consumption easier. The production process emphasizes cleanliness and safety by selecting organic ingredients and avoiding harmful preservatives. The packaging is designed to maintain product quality for an extended period, prevent moisture, and be convenient for horse owners to use. Additionally, the treat can be used as a reward during horse training, helping to strengthen the bond between the horse and its owner while reducing equine stress. This product serves as both a health-boosting snack and an effective training tool, making it suitable for horses that require highly nutritious supplements. It also provides a new option for horse owners seeking a safe and beneficial product for their horse’s overall well-being.

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OPTIMIZATION OF CONCENTRATED BUTTERFLY PEA EXTRACT PROCESS

คณะวิศวกรรมศาสตร์

OPTIMIZATION OF CONCENTRATED BUTTERFLY PEA EXTRACT PROCESS

This thesis project was conducted to identify the optimal conditions for producing concentrated butterfly pea juice using vacuum evaporation to preserve key compounds in butterfly pea flowers, such as anthocyanins—natural pigments with high antioxidant properties. The study applies a Box-Behnken Design, a statistical method that facilitates analysis of multiple factors. The research focuses on the ratio of dried butterfly pea flowers to water, extraction temperature, and evaporation temperature, each of which has a direct effect on the preservation of key compounds, color, aroma, and flavor. The results indicate that using a dried flower-to-water ratio of 1:15, an extraction temperature of 60°C, and an evaporation temperature of 40°C under low pressure can minimize the loss of essential compounds and best retain the properties of the concentrated butterfly pea juice. Findings from this research provide a foundation for developing an industrial production process for concentrated butterfly pea juice and enhance the potential for creating new products from butterfly pea flowers.

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Optimization Hydrogen Manufacturing (HMU-2) and Pressure Swing Adsorption (PSA-3) Unit

คณะวิศวกรรมศาสตร์

Optimization Hydrogen Manufacturing (HMU-2) and Pressure Swing Adsorption (PSA-3) Unit

This cooperative education project aims to enhance the efficiency of Hydrogen Manufacturing Unit 2 (HMU-2) and Pressure Swing Adsorption 3 (PSA-3) by using AVEVA Pro/II process modeling and a Machine Learning model for process simulation. The study found that the AVEVA Pro/II model predicted outcomes with deviations ranging from 0–35%, including a hydrogen flow rate deviation from the PSA unit of 12%, exceeding the company’s acceptable limit of 10%. To address this, a Machine Learning model based on the Random Forest algorithm was developed with hyperparameter tuning. The Machine Learning model demonstrated high accuracy, achieving Mean Squared Errors (MSE) of 8.48 and 0.18 for process and laboratory data, respectively, and R-squared values of 0.98 and 0.88 for the same datasets. It outperformed the AVEVA Pro/II model in predicting all variables and reduced the hydrogen flow rate deviation to 4.75% and 1.35% for production rates of 180 and 220 tons per day, respectively. Optimization using the model provided recommendations for process adjustments, increasing hydrogen production by 7.8 tons per day and generating an additional annual profit of 850,966.23 Baht.

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