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- W4322741306 abstract "In a response to the appeal for securing the rice production efficiency to achieve the United Nations Sustainable Development Goals, we adopted a geographic detector model to investigate the spatiotemporal evolution trajectory and driving forces of the rice production in the world’s largest rice-producing country, China. We have analyzed the spatiotemporal evolution features and aggregation patterns of county rice production efficiency based on panel data of 122 counties in Hunan Province, one of the main grain production provinces in China, from 2006 to 2018. Our findings indicate: (1) Hunan Province’s rice production in three counties (i.e., Taoyuan, Liling, and Anren) showed the highest efficiency; there were pronounced regional variances in rice productivity which results in a sharp and rapid shrink of the range of rice productivity, (2) financial investments in agriculture, forestry, and water resources, as well as per capita disposable income of farmers, were the main determinants of the spatiotemporal variation in rice production efficiency, (3) the spatiotemporal divergence of rice production efficiency at the province level was U-shapedly, influenced by the share of secondary industry in GDP; the southern Hunan region received the biggest contribution from farmers in terms of disposable income per person at the regional level. Overall, theoretically, this study offers fresh evidence for regional optimization of rice and other grain production from a novel integrative approach of the geospatial and the land resource preservation. Practically, it provides feasible guidance for the high-quality development of grain production in China, which may also help eradicate hunger and attain sustainable grain production all over the world." @default.
- W4322741306 created "2023-03-03" @default.
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- W4322741306 date "2023-03-01" @default.
- W4322741306 modified "2023-10-16" @default.
- W4322741306 title "Spatiotemporal Evolution and Antecedents of Rice Production Efficiency: From a Geospatial Approach" @default.
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- W4322741306 doi "https://doi.org/10.3390/systems11030131" @default.
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