Analysis of plot diagnostics as a decision-support tool in CIMMYT Innovation Hubs - Fonteyne, Simon (CIMMYT, 2025)
CIMMYT’s Innovation Hubs are a key methodology for scaling sustainable farming practices in Latin America through locally adapted solutions. Plot diagnostics are a foundational component of this approach, guiding the design of innovation modules and extension areas by identifying farmer objectives, field-level constraints, and context-specific opportunities. While diagnostics are primarily used for plot-level planning, they have generated a large body of information that has not yet been fully leveraged for program-level learning and decision-making. This report analyzes 438 plot diagnostics conducted between 2015 and 2025 across three Innovation Hubs in Mexico: Pacífico Sur (Oaxaca), Chiapas, and the Peninsula de Yucatán. Due to variation in diagnostic formats and documentation, a qualitative analysis was conducted to identify common patterns in diagnosed constraints, proposed innovations, and opportunities to strengthen the diagnostic methodology. Across hubs and years, diagnostics consistently identify recurring challenges, including soil degradation, limited residue cover and diversification, inefficient nutrient and crop management, weed, pest, and disease pressure, labor and mechanization constraints, and exposure to climate and environmental risks. Farm advisors frequently recommend practices aligned with conservation agriculture, crop diversification and rotations (often with legumes), improved planting arrangements and densities, seed quality and seed treatment, and the use of biological inputs to enhance soil function and system resilience. The alignment between diagnosed problems and proposed solutions indicates a shared technical framework across Innovation Hubs and highlights a core set of practices with high potential for scaling. However, the lack of standardized diagnostic formats, centralized data storage, and integration with digital platforms limits comparability, follow-up, and learning across hubs and over time. Strengthening plot diagnostics through standardization of core elements, integration into e-Agrology, improved question design, basic quality assurance, and the development of simple indicators would allow CIMMYT to better leverage field-level knowledge. These improvements would support evidence-based prioritization of technologies, stronger alignment between research, training, and farmer needs, and more effective scaling of sustainable agricultural innovations within Innovation Hubs.