Agroecology as technoscience: knowledge, power, and Sino–American exchange in reform-era China

Agroecology has often been conceptualized as a bottom-up alternative to industrial agriculture, closely associated with peasant movements, food sovereignty, and grassroots resistance, particularly in Latin America. This article challenges that singular framing by examining the emergence of agroecology in China between the early 1970s and the early 1990s, with particular attention to Sino–American scientific exchange. Drawing on archival materials from South China Agricultural University, institutional and FAO documents, the published writings of key scientific actors, and oral history interviews, the study analyzes how agroecological knowledge was produced, translated, and institutionalized across two phases: an early period of “academic imagination and informal exchange” (1972–1978), in which American ecologists reflecting on the failures of the Green Revolution cast Chinese traditional farming as an ecological model, and a later period of “institutionalization and local reconstruction” (1978 onward), in which Chinese scientists reorganized indigenous agricultural experience through systems theory and computer modeling. The article argues that agroecology in China did not develop as a counter-hegemonic movement but as a form of state-aligned technoscience. Influenced by systems ecology, cybernetics, and socialist planning, and articulated by scientists within state institutions, agroecological ideas were incorporated into research and policy as tools for improving efficiency, managing ecological complexity, and advancing modernization. By situating the Chinese case within debates on knowledge co-production and the institutionalization of agroecology, the study demonstrates that agroecology cannot be understood as a singular or universally progressive model, but instead takes shape through specific political, institutional, and epistemic contexts, offering a more historically grounded understanding of agroecology’s diverse global trajectories.