Scale or technology? Infrastructure configuration pathways toward low-carbon food systems in China

Introduction Food production systems are a significant source of carbon emissions, and optimizing agricultural infrastructure is crucial for advancing low-carbon food systems. This study investigates how different configurations of agricultural infrastructure contribute to lower carbon intensity in 30 Chinese provinces between 2013 and 2022. Methods We employ fuzzy-set Qualitative Comparative Analysis (fsQCA) to analyze the combined effects of farmland water conservancy, rural transportation, digital infrastructure, agricultural electrification, cultivation scale, and technological progress on agricultural carbon emissions. Results Our findings reveal that no single infrastructure type is necessary for emission reduction. Instead, two dominant pathways emerge. The scale expansion pathway involves the joint presence of farmland water conservancy, rural transportation, and large-scale grain cultivation. The technological progress pathway combines digital infrastructure, farmland water conservancy, and advances in grain production technology. The technological progress pathway demonstrates slightly stronger consistency (0.9813) than the scale expansion pathway (0.9674). Discussion Regional analysis shows that scale-driven pathways are more common in southeastern coastal provinces, whereas technology-driven pathways dominate in northwestern and southwestern regions. These findings provide actionable guidance for region-specific, policy-driven low-carbon transitions in Chinese agriculture.

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Publication Details

Journal
Frontiers in Sustainable Food Systems
Published
2026-04-22
DOI
https://doi.org/10.3389/fsufs.2026.1775669
Primary Topic
Qualitative Comparative Analysis Research
Type
article
Field-Weighted Citation Impact
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article

Scale or technology? Infrastructure configuration pathways toward low-carbon food systems in China

Mingtao Gao, Shadab Ahmad, Hawasli Ghalia, Ziang Chen et al.
Frontiers in Sustainable Food Systems
Qualitative Comparative Analysis Research
article

Scale or technology? Infrastructure configuration pathways toward low-carbon food systems in China

Mingtao Gao, Shadab Ahmad, Hawasli Ghalia, Ziang Chen, Ubair Nisar, Cheng Li
article en

Abstract

Introduction Food production systems are a significant source of carbon emissions, and optimizing agricultural infrastructure is crucial for advancing low-carbon food systems. This study investigates how different configurations of agricultural infrastructure contribute to lower carbon intensity in 30 Chinese provinces between 2013 and 2022. Methods We employ fuzzy-set Qualitative Comparative Analysis (fsQCA) to analyze the combined effects of farmland water conservancy, rural transportation, digital infrastructure, agricultural electrification, cultivation scale, and technological progress on agricultural carbon emissions. Results Our findings reveal that no single infrastructure type is necessary for emission reduction. Instead, two dominant pathways emerge. The scale expansion pathway involves the joint presence of farmland water conservancy, rural transportation, and large-scale grain cultivation. The technological progress pathway combines digital infrastructure, farmland water conservancy, and advances in grain production technology. The technological progress pathway demonstrates slightly stronger consistency (0.9813) than the scale expansion pathway (0.9674). Discussion Regional analysis shows that scale-driven pathways are more common in southeastern coastal provinces, whereas technology-driven pathways dominate in northwestern and southwestern regions. These findings provide actionable guidance for region-specific, policy-driven low-carbon transitions in Chinese agriculture.

Frontiers in Sustainable Food SystemsVol. 10
Shandong University of Technology (CN), SK Group (South Korea) (KR), Wenzhou University (CN), Nanjing Forestry University (CN), Yunnan University (CN), People's Government of Yunnan Province (CN), Chitkara University (IN), National University of Malaysia (MY)
Openalex Percentile: Top 12%
Qualitative Comparative Analysis Research
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