Purpose: The flow of the Sino-Brazilian frozen beef trade has intensified. Thus, the purpose of this paper is to characterize the supply chain structure, and identify its major fragilities. Design/methodology/approach: Supply chain mapping was conducted based on the existing literature and primary data collection. Key stakeholders were detected and questioned through semi-structured interviews, which were later interpreted with content analysis. Findings: The results reveal a low degree of chain coordination from the Brazilian farm to the Chinese consumer, arising from an immature traceability mechanism, a limited flow of reliable information between the segments, and low trust between the stakeholders. Research limitations/implications: The infancy of the beef trade, the paucity of literature on the topic, and restricted accessibility to key governmental and official materials imposes limits on the available information. Language and cultural barriers might have also impacted the interviewees’ responses. However, the participation of Brazilian and Chinese academics in both the interview analysis and chain mapping mitigates these shortcomings. Practical implications: The Brazilian public and private sectors need to establish a reliable traceability system and information platform. This, together with investments in marketing and branding, would facilitate differential responses among traders and consumers, and, hence, improve supply chain sustainability. Originality/value: By adopting an inter-country approach and directly sourcing views from specific key figures in the supply chain this study offers some unique insights and contributes to the literature on the emergence of a multi-polar global food trade.

China’s agricultural transition toward low-carbon, high-quality development necessitates reducing greenhouse gas emissions. This study examines how agricultural production intensification (API) affects carbon emissions, incorporating technological innovation as a mediator. Using 2014–2023 panel data, fixed-effects, mediation, and threshold models reveal: (1) API significantly reduces emissions, validated by robustness tests. (2) Heterogeneity tests show a U-shaped relationship in major grain-producing regions but no significant effect elsewhere. (3) Technological innovation partially mediates API’s emission-reducing effect. (4) Threshold tests indicate nonlinear impacts: API suppresses emissions above a threshold of 0.60, but this weakens beyond 0.95.