This study aims to propose new grading standards that can be applied to AI-based automatic sorting machines, reflecting current distribution and consumption trends. The current domestic grading standards for onions in South Korea are based on the “Agricultural and Fishery Products Quality Control Act”. They classify onions based on criteria such as uniformity, shape, color, and the presence of foreign matter. Onion grading standards are divided into four categories based on bulb diameter and weight. However, in the actual domestic market, onions are distributed according to a five-grade classification based on bulb diameter. Therefore, this study classified onions into eight grades, reflecting current distribution and consumption trends in the domestic market. These grades are applicable to AI-based automatic sorting machines. Marketable onions were classified into A1 (extra large) to A5 (extra small) based on the diameter of a single bulb. Onions used for non-marketable purposes (processing) were classified as grade B. Additionally, grade C and grade D were designated for processing and disposal, respectively. By establishing quality grading classifications that align with current distribution and consumption market trends as well as the operational characteristics of AI-based automatic sorting machines, we can expect improvements in work efficiency and reductions in distribution costs. Following this study, it will be necessary to establish comprehensive quality grading standards that include both external criteria (such as bulb weight and size) and internal criteria (such as detection of internal decay and disease occurrence).

ABSTRACT
서 론
국내 양파 등급 규격
AI 기반 자동 선별기 적용 양파 품질 등급 기준 설정
결 론
ACKNOWLEDGMENTS
RERERENCES

• 김은지(국립목포대학교 일반대학원 생명자원개발이용학협동과정) | Eun Ji Kim (Interdisciplinary Program of Development and Utilization of Biological Resources, Graduate School pf Mokpo National University, Muan 58554, Korea)
• 주세훈(국립목포대학교 일반대학원 생명자원개발이용학협동과정) | Se Hun Ju (Interdisciplinary Program of Development and Utilization of Biological Resources, Graduate School pf Mokpo National University, Muan 58554, Korea)
• 고윤(국립목포대학교 일반대학원 원예학과) | Yoon Go (Department of Horticultural Science, Graduate School pf Mokpo National University, Muan 58554, Korea)
• 권영석(국립목포대학교 자연자원개발연구소) | Youngseok Kwon (Mokpo National University Nature Resource Institute, Muan 58554, Korea)
• 나해영(국립목포대학교 자연자원개발연구소, 국립목포대학교 원예산림학부) | Haeyoung Na (Mokpo National University Nature Resource Institute, Muan 58554, Korea, Department of Horticulture and Forestry, Mokpo National University, Muan 58554, Korea) Corresponding author