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Quality Estimation of Net Packaged Onions during Storage Periods using Machine Learning Techniques

원문정보

Nandita Irsaulul Nurhisna, Sang-Yeon Kim, Seongmin Park, Suk-Ju Hong, Eungchan Kim, Chang-Hyup Lee, Sungjay Kim, Jiwon Ryu, Seungwoo Roh, Daeyoung Kim, Ghiseok Kim

한국포장학회 한국포장학회지 Vol. 28 No. 3 2022.12 pp.237-244
피인용수 : 0건 (자료제공 : 네이버학술정보)

초록

영어

Onions are a significant crop in Korea, and cultivation is increasing every year along with high demand. Onions are planted in the fall and mainly harvested in June, the rainy season, therefore, physiological changes in onion bulbs during long-term storage might have happened. Onions are stored in cold room and at adequate relative humidity to avoid quality loss. In this study, bio-yield stress and weight loss were measured as the quality parameters of net packaged onions during 10 weeks of storage, and the storage environmental conditions are monitored using sensor networks systems. Quality estimation of net packaged onion during storage was performed using the storage environmental condition data through machine learning approaches. Among the suggested estimation models, support vector regression method showed the best accuracy for the quality estimation of net packaged onions.

목차

Abstract
Introduction
Material and Method
1. Sample and Equipment
2. Quality Attributes measurement
3. Prediction Model
Result and Discussion
1. Onion Quality Analysis
2. Prediction Model
Conclusions
References

키워드

저자정보

  • Nandita Irsaulul Nurhisna Department of Biosystems Engineering, Seoul National University, Integrated Major in Global Smart Farm, Seoul National University
  • Sang-Yeon Kim Department of Biosystems Engineering, Seoul National University
  • Seongmin Park Department of Biosystems Engineering, Seoul National University, Research Institute of Agriculture and Life Science, Seoul National University
  • Suk-Ju Hong Department of Biosystems Engineering, Seoul National University, Integrated Major in Global Smart Farm, Seoul National University
  • Eungchan Kim Department of Biosystems Engineering, Seoul National University, Integrated Major in Global Smart Farm, Seoul National University
  • Chang-Hyup Lee Department of Biosystems Engineering, Seoul National University, Integrated Major in Global Smart Farm, Seoul National University
  • Sungjay Kim Department of Biosystems Engineering, Seoul National University, Integrated Major in Global Smart Farm, Seoul National University
  • Jiwon Ryu Department of Biosystems Engineering, Seoul National University, Integrated Major in Global Smart Farm, Seoul National University
  • Seungwoo Roh Department of Biosystems Engineering, Seoul National University, Integrated Major in Global Smart Farm, Seoul National University
  • Daeyoung Kim Department of Biosystems Engineering, Seoul National University, Integrated Major in Global Smart Farm, Seoul National University
  • Ghiseok Kim Department of Biosystems Engineering, Seoul National University, Integrated Major in Global Smart Farm, Seoul National University, Research Institute of Agriculture and Life Science, Seoul National University

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