A dataset of interprovincial food trade flows in China

Abstract Understanding the food trading network is crucial for optimizing resource allocation, maintaining stability in the food system, and safeguarding food security. However, as one of the world’s largest agricultural producers, there is a dearth of publicly available data sources pertaining to C...

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Main Authors: Lan Luo, Zhencheng Xing, Yifan Liu, Xiang Liu, Lingling Jiang, Yi Peng, Haibo Zhang, Haikun Wang
Format: Article
Language:English
Published: Nature Portfolio 2025-06-01
Series:Scientific Data
Online Access:https://doi.org/10.1038/s41597-025-05290-4
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author Lan Luo
Zhencheng Xing
Yifan Liu
Xiang Liu
Lingling Jiang
Yi Peng
Haibo Zhang
Haikun Wang
author_facet Lan Luo
Zhencheng Xing
Yifan Liu
Xiang Liu
Lingling Jiang
Yi Peng
Haibo Zhang
Haikun Wang
author_sort Lan Luo
collection DOAJ
description Abstract Understanding the food trading network is crucial for optimizing resource allocation, maintaining stability in the food system, and safeguarding food security. However, as one of the world’s largest agricultural producers, there is a dearth of publicly available data sources pertaining to China’s interprovincial physical food trade. Here, we developed a dataset of interprovincial physical food flows in Chinese mainland for the period 2000–2022, using the trade gravity model with the integration of food supply, food demand, and transportation data. This dataset includes 15 key types of plant-based and animal-based food products and represents the longest time series covering the most extensive variety of food products to date on China’s food trade patterns. The dataset reveals changes in dietary structures and trade patterns across regions within China since the 21st century. This work provides a methodological framework and dataset that could support studies on virtual resources flow, agri-environmental impact assessment, and food policy formulation across various food categories and regions.
format Article
id doaj-art-d4e181c321c74bb68cf187a6b84228e1
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issn 2052-4463
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publishDate 2025-06-01
publisher Nature Portfolio
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series Scientific Data
spelling doaj-art-d4e181c321c74bb68cf187a6b84228e12025-08-20T02:05:49ZengNature PortfolioScientific Data2052-44632025-06-0112111210.1038/s41597-025-05290-4A dataset of interprovincial food trade flows in ChinaLan Luo0Zhencheng Xing1Yifan Liu2Xiang Liu3Lingling Jiang4Yi Peng5Haibo Zhang6Haikun Wang7School of Government, Nanjing UniversitySchool of Government, Nanjing UniversityState Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing UniversityDepartment of Earth and Planetary Sciences, Harvard UniversityJoint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing UniversitySchool of Government, Nanjing UniversitySchool of Government, Nanjing UniversityJoint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing UniversityAbstract Understanding the food trading network is crucial for optimizing resource allocation, maintaining stability in the food system, and safeguarding food security. However, as one of the world’s largest agricultural producers, there is a dearth of publicly available data sources pertaining to China’s interprovincial physical food trade. Here, we developed a dataset of interprovincial physical food flows in Chinese mainland for the period 2000–2022, using the trade gravity model with the integration of food supply, food demand, and transportation data. This dataset includes 15 key types of plant-based and animal-based food products and represents the longest time series covering the most extensive variety of food products to date on China’s food trade patterns. The dataset reveals changes in dietary structures and trade patterns across regions within China since the 21st century. This work provides a methodological framework and dataset that could support studies on virtual resources flow, agri-environmental impact assessment, and food policy formulation across various food categories and regions.https://doi.org/10.1038/s41597-025-05290-4
spellingShingle Lan Luo
Zhencheng Xing
Yifan Liu
Xiang Liu
Lingling Jiang
Yi Peng
Haibo Zhang
Haikun Wang
A dataset of interprovincial food trade flows in China
Scientific Data
title A dataset of interprovincial food trade flows in China
title_full A dataset of interprovincial food trade flows in China
title_fullStr A dataset of interprovincial food trade flows in China
title_full_unstemmed A dataset of interprovincial food trade flows in China
title_short A dataset of interprovincial food trade flows in China
title_sort dataset of interprovincial food trade flows in china
url https://doi.org/10.1038/s41597-025-05290-4
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