• Title/Summary/Keyword: cold and frozen food storage warehouse

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Sanitary Conditions for Cold and Frozen Food Storage Warehouses in Korea (국내 식품 냉장.냉동 창고 위생관리 수준 분석)

  • Choi, Eun-Ji;Kim, Mee-Hye;Bahk, Gyung-Jin
    • Journal of Food Hygiene and Safety
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    • v.26 no.4
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    • pp.283-288
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    • 2011
  • We surveyed the sanitary conditions for 17 cold and frozen food storage warehouses in Korea, using the following 5 inspections items: "putting into warehouse (A)", "prevention of cross-contamination (B)", "storage management (C)", "temperature control (D)", and "management of records and documents (E)", We included 20 detailed items. The results of distribution for frequency by five major inspection items showed that "(E)" was the highest, the next "(D)", "(C)"; and "(B)" was the lowest. In the correlation of inspection scores between total scores, "(B)" and "(C)" were highly related to the total score, therefore, the higher score of "(B)" or "(C)", the higher for the total score. In details of inspection items, "the management of cross-contamination upon taking product out of the warehouse" had the lowest score with a mean, of $2.67{\pm}1.80$, and also ranked as first of the 20 items.

Analysis of Temperature and Probability Distribution Model of Frozen Storage Warehouses in South Korea (국내 식품냉동창고 온도분포 실태 및 확률분포모델 분석)

  • Park, Myoung-Su;Kim, Ga-Ram;Bahk, Gyung-Jin
    • Journal of Food Hygiene and Safety
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    • v.34 no.2
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    • pp.199-204
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    • 2019
  • This study aimed to generate a probability distribution model based on temperature data of frozen food storage facility as input variables for microbial risk assessment (MRA). We visited 8 food-handling businesses to collect temperature data from their cold storage warehouses. The overall mean temperature inside the storage facilities was $-20.48{\pm}3.08^{\circ}C$, with 20.4% of the facilities having above $-18^{\circ}C$, with minimum and maximum temperature values of -10.3 and $-25.80^{\circ}C$ respectively. Temperature distributions by space locations of natural and forced convection were $-22.57{\pm}0.84$ and $-17.81{\pm}1.47^{\circ}C$, $-22.49{\pm}1.05$ and $-17.94{\pm}1.44^{\circ}C$, and $-22.68{\pm}1.03$ and $-18.08{\pm}1.42^{\circ}C$ in the upper (2.4~4 m), middle (1.5~2.4 m), and lower (0.7~1.5 m) shelves, respectively. Probability distributions from the temperature data were obtained using the program @RISK. Statistical ranking was determined using goodness of fit to determine the probability distribution model. Our results show that a log-normal distribution [5.9731, 3.3483, shift (-26.4281)] is most appropriate for relative MRA conduction.

An Evaluation of Cold Chain Cluster Competitiveness in the Metropolitan Area (수도권 콜드체인 클러스터 경쟁력 평가에 관한 연구)

  • Ahn, Kil-Seob;Park, Sung-Hoon;Lee, Hae-Chan;Yeo, Gi-Tae
    • Journal of Digital Convergence
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    • v.18 no.10
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    • pp.181-194
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    • 2020
  • Due to the changes in the distribution market, issues related to storage and distribution of agricultural, aquatic and livestock products, and storage and transportation of processed and fresh food are rapidly emerging, and as a result, Cold Chain is naturally receiving attention as one of the logistics services. The purpose of this study is to evaluate the competitiveness of location in the construction of a cold chain cluster centered on the metropolitan area, which has attracted attention in relation to the distribution of cold chains, such as recently refrigerated frozen foods. To this end, this study evaluated the competitiveness of cold chain cluster candidates in the metropolitan area by utilizing the CFPR (Consistent Fuzzy Preference Relations) method that can efficiently extract and quantify expert knowledge. As a result, the location competitiveness was found to be superior to Incheon New Port's hinterland, Gyeonggi South Area (Yongin), Gyeonggi West Area (Gimpo Logistics Complex), and Pyeongtaek Oseong Logistics Complex. In particular, this study extracted the knowledge of refrigerated and refrigerated logistics warehouse operation experts, and conducted detailed competitiveness assessments for cold chain cluster candidates in the metropolitan area, and suggested the optimal cluster candidates. In the future research, it is necessary to classify the questionnaire into the owner, large business group, and public business group, etc., who have the right to purchase and build to secure ownership of the fresh food distribution center.