Optimized Supply Chain Management of Rice in South Korea: Location–Allocation Model of Rice Production

An, Kyunam and Kim, Sumin and Shin, Seoho and Min, Hyunkyoung and Kim, Sojung (2021) Optimized Supply Chain Management of Rice in South Korea: Location–Allocation Model of Rice Production. Agronomy, 11 (2). p. 270. ISSN 2073-4395

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Abstract

Planning for optimized farming with the aim of providing ideal site and cultivar selection is critical for a stable and sustainable supply of rice with sufficient quantity and quality to customers. In this study, a range of morphological characteristics and yield of eight rice cultivars that are commonly cultivated in Korea were investigated from 2005 to 2020. All morphological characteristics were significantly different among the eight rice cultivars. The dataset of morphological characteristics and yield was used to isolate groups of similar rice cultivars. The k-means clustering method was used to group the rice cultivars. Three groups (Group 1, Group 2, and Group 3) were created. Most cultivars were in Group 1. High-yielding rice cultivars were in Group 2, while the rice cultivars in Group 3 had the lowest rice grain yield. After grouping these rice cultivars, ideal farming locations for all three rice cultivar groups were identified to reduce transportation cost using an optimized location–allocation model. Simulation results suggested the following: (1) Group 1 should be produced in Jellanam-do (south west region), (2) Group 2 should be produced in Chungcheongnam-do (central west region), and (3) Group 3 should be mainly produced in the central west region of South Korea. Simulation results showed the potential to reduce transportation cost by around 0.014%. This can also reduce 21.04 tons of CO2 emission from a freight truck. Because these eight cultivars only make up 19.76% of the total rice production in South Korea, the cost reduction proportion was only 0.014% of total revenue. In future studies, more rice cultivars should be investigated to increase the efficiency of the model performance.

Item Type: Article
Subjects: Apsci Archives > Agricultural and Food Science
Depositing User: Unnamed user with email support@apsciarchives.com
Date Deposited: 16 Jan 2023 08:51
Last Modified: 03 Jan 2024 06:49
URI: http://eprints.go2submission.com/id/eprint/224

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