Sangoh Kim

Prof. Dr. Sangoh Kim

Plant and food science and technology, Sangmyung University, Cheonan, Republic of Korea
orcid

Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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20 February 2022 in Food Science and Biotechnology
Verified
Journal Article
Closed access
PDF file
SKSang-Soon Kim
Sang-Soon Kim
SKSangoh Kim
Sangoh Kim

25 October 2022 in Food Science and Biotechnology
Verified
Journal Article
Closed access
PDF file
SKSangoh Kim
Sangoh Kim

20 May 2022 in Food Science and Biotechnology
Verified
Journal Article
Closed access
PDF file
EKEunghee Kim
Eunghee Kim
CBChoongjin Ban
Choongjin Ban
SKSangoh Kim
Sangoh Kim
SLSeokwon Lim
Seokwon Lim
YCYoung Jin Choi
Young Jin Choi

4 October 2021 in Foods
Verified
Journal Article
Open access
PDF file
YYYoungsang You
Youngsang You
MLMuci Li
Muci Li
TKTaiyoung Kang
Taiyoung Kang
YKYoungBok Ko
YoungBok Ko
SKSangoh Kim
Sangoh Kim
SJSoojin Jun
Soojin Jun
Freezing extends the shelf-life of food by slowing down the physical and biochemical reactions; however, ice crystal formation can result in irreversible damage to the cell’s structure and texture. Supercooling technology has the potential to preserve the original freshness of food without freezing damage. In this study, fresh asparagus was preserved in a supercooled state and its quality changes such as color, weight loss, texture, chlorophyll and anthocyanin content, and enzymatic activities (superoxide dismutase and catalase) were evaluated. The asparagus samples were successfully supercooled at −3 °C with the combination treatment of pulsed electric field (PEF) and oscillating magnetic field (OMF), and the supercooled state was maintained for up to 14 days. Asparagus spears preserved in the supercooled state exhibited lower weight loss and higher levels of quality factors in comparison to the frozen and refrigerated control samples.

11 November 2024 in Food Science and Biotechnology
Verified
Journal Article
Closed access
PDF file
JJJieun Jeong
Jieun Jeong
SKSangoh Kim
Sangoh Kim

27 November 2024 in Foods
Verified
Journal Article
Open access
PDF file
YKYoungjin Kim
Youngjin Kim
SKSangoh Kim
Sangoh Kim
The Food Process Robot Intelligent System (FPRIS) integrates a 3D-printed six-axis robotic arm with Artificial Intelligence (AI) and Computer Vision (CV) to optimize and automate the coffee roasting process. As an application of FPRIS coffee roasting, this system uses a Convolutional Neural Network (CNN) to classify coffee beans inside the roaster and control the roaster in real time, avoiding obstacles and empty spaces. This study demonstrates FPRIS’s capability to precisely control the Degree of Roasting (DoR) by combining gas and image sensor data to assess coffee bean quality. A comparative analysis between the Preliminary Coffee Sample (PCS) and Validation Coffee Sample (VCS) revealed that increasing roast intensity resulted in consistent trends for both samples, including an increase in weight loss and Gas sensor Initial Difference (GID) and a decrease in Sum of Pixel Grayscale Values (SPGVs). This study underscores the potential of FPRIS to enhance precision and efficiency in coffee roasting. Future studies will expand on these findings by testing FPRIS across various food processes, potentially establishing a universal automation system for the food industry.