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.
ระบบตรวจจับผลไม้เน่ามีที่มาจากความต้องการในการลดการสูญเสียผลผลิตทางการเกษตร ซึ่งเป็นปัญหาที่เกิดขึ้นทั่วโลกโดยเฉพาะในอุตสาหกรรมการเกษตรและการจัดจําหน่ายอาหาร ผลไม้ที่เน่าเสียจะส่งผลกระทบต่อคุณภาพของผลิตภัณฑ์และสามารถก่อให้เกิดความสูญเสียทางเศรษฐกิจได้อย่างมาก การพัฒนาระบบตรวจจับผลไม้เน่าจึงมีเป้าหมายเพื่อช่วยในการคัดกรองและแยกผลไม้ที่ไม่เหมาะสมออกจากกระบวนการจัดส่ง เพื่อรักษาคุณภาพของสินค้าและตอบสนองต่อความต้องการของผู้บริโภคที่ต้องการผลไม้สดใหม่
คณะอุตสาหกรรมอาหาร
Bio-calcium powders were extracted from Asian sea bass bone by heat-treated alkaline with fat removal and bleaching supplementary method. Cereal bars (CBs) were fortified with produced bio-calcium at 3 levels: (1) increased calcium (IS-Ca; calcium ≥10% Thai RDI), (2) good source of calcium (GS-Ca; calcium ≥15% Thai RDI), and (3) high calcium (H-Ca; calcium ≥30% Thai RDI) which were consistent with the notification of the Ministry of Public Health, Thailand: No. 445; Nutrition claim issued in B.E. 2023. Moisture content, water activity, color, calcium content and FTIR analysis of bio-calcium powders were measured. Dimension, color, water activity, pH and texture of fortified CBs were determined. Produced bio-calcium could be classified as a dried food with light yellow-white color. Calcium contents in bio-calcium powder was 23.4% (w/w). Dimension, weight and color except b* and ΔE* values of fortified CBs were not different (P > 0.05) from those of the control. Fortifying of bio-calcium resulted in harder texture CBs. An increase of fortified bio-calcium amounts decreased carbohydrate and fat but increased of protein, ash and calcium in the fortified CBs. Shelf life of CBs was to be shorten by fortification of bio-calcium powder because of the increment of moisture, water activity and pH. Yield of bio-calcium production was 40.30%. Production cost of bio-calcium was approximately 7,416 Bth/kg while cost of fortified CBs increased almost 2-3 times compared to the control. Calcium contents in IS-Ca (921.12 mg/100g), GS-Ca (1,287.10 mg/100g) and H-Ca (2,639.70 mg/100g) cereal bars could be claimed as increased calcium, good source of calcium and high calcium, respectively. In conclusion, production of cereal bar fortified with Asian sea bass bone bio-calcium powder as a fortified food was possible. However, checking the remained hazardous reagents in bio-calcium powder must be carried out before using in food products and analysis of calcium bioavailability, sensory acceptance and shelf life of the developed products should be determined in further studies.
คณะอุตสาหกรรมอาหาร
The activities of the project's operations consist of: checking microbe on sample food, hygienic condition of cooker, containers and materials, sanitation knowledge and private sanitation and food quality of canteen and cleaning of cooker. The Food Safety Management program collaborated with the Property Management office, planned the operations, and assessed food vendors based on the SAN 20 food safety standards requirements. Using A.13 testing kits, we conducted testing for coliform bacteria contamination in food, containers, equipment, and hand contact surfaces, collecting 6 samples. These included samples such as prepared food, areas in front of the store, and food handlers' hands. Additionally, we used A.11 testing kits to test for coliform bacteria contamination in water and ice. The analysis of results, including physical, microbiological, and chemical aspects, serve as a guideline for improving the quality and safety of food production and service in the institution's canteen.
คณะเทคโนโลยีสารสนเทศ
This research presents a deep learning method for generating automatic captions from the segmentation of car part damage. It analyzes car images using a Unified Framework to accurately and quickly identify and describe the damage. The development is based on the research "GRiT: A Generative Region-to-text Transformer for Object Understanding," which has been adapted for car image analysis. The improvement aims to make the model generate precise descriptions for different areas of the car, from damaged parts to identifying various components. The researchers focuses on developing deep learning techniques for automatic caption generation and damage segmentation in car damage analysis. The aim is to enable precise identification and description of damages on vehicles, there by increasing speed and reducing the work load of experts in damage assessment. Traditionally, damage assessment relies solely on expert evaluations, which are costly and time-consuming. To address this issue, we propose utilizing data generation for training, automatic caption creation, and damage segmentation using an integrated framework. The researchers created a new dataset from CarDD, which is specifically designed for cardamage detection. This dataset includes labeled damages on vehicles, and the researchers have used it to feed into models for segmenting car parts and accurately labeling each part and damage category. Preliminary results from the model demonstrate its capability in automatic caption generation and damage segmentation for car damage analysis to be satisfactory. With these results, the model serves as an essential foundation for future development. This advancement aims not only to enhance performance in damage segmentation and caption generation but also to improve the model’s adaptability to a diversity of damages occurring on various surfaces and parts of vehicles. This will allow the system to be applied more broadly to different vehicle types and conditions of damage inthe future