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Mother-Baby Trial Design×Agroecosystem Analysis×
분야Food Agriculture StudiesFood Agriculture Studies
계열Process / pipelineProcess / pipeline
기원 연도20021987
창시자Sieglinde SnappGordon R. Conway
유형Linked on-farm experimental design pairing replicated and dispersed trialsSystems-diagnosis pipeline for agroecosystem performance
원전Snapp, S. (2002). Quantifying Farmer Evaluation of Technologies: The Mother and Baby Trial Design. In M. R. Bellon & J. Reeves (Eds.), Quantitative Analysis of Data from Participatory Methods in Plant Breeding (pp. 9-17). Mexico, DF: CIMMYT. link ↗Conway, G. R. (1987). The properties of agroecosystems. Agricultural Systems, 24(2), 95-117. DOI ↗
별칭Mother and Baby Trial Design, MBT Design, Mother-Baby Trial Approach, Mother-Baby On-Farm TrialsAEA, Agroecosystem Properties Analysis, Conway Agroecosystem Analysis, Agroecosystem Diagnosis
관련44
요약The mother-baby trial design is an on-farm experimental architecture, formalized by Sieglinde Snapp in 2002, that resolves the long-standing tension between statistical rigor and wide farmer participation in agricultural research. A small number of replicated 'mother' trials carry the complete set of treatments under good management and provide the controlled, analyzable comparison; surrounding them, a large number of simple 'baby' trials, each on a farmer's own field and each testing only a subset of the treatments against the farmer's usual practice, sample the real variation in conditions and capture farmer evaluation at scale. Linking the two — the mother for precision, the babies for breadth and realism — yields both defensible treatment estimates and credible evidence about how technologies perform and are judged across many real farms.Agroecosystem analysis (AEA) is a systems-diagnosis framework, formalized by Gordon Conway in 1987, that characterizes any agricultural system through four properties: productivity, stability, sustainability, and equitability. Rather than judging a farming system by yield alone, AEA treats the agroecosystem as an ecological system shaped by human management and asks how much it produces, how reliably it produces it across seasons and shocks, whether it can maintain output over the long run, and how its benefits are distributed among the people who depend on it. The analyst bounds a system at an appropriate hierarchical level — plot, field, farm, watershed, or region — and uses interdisciplinary teams, ranked questions, and simple structured diagrams to surface the key relationships and the trade-offs among the four properties that drive design and policy choices.
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