Developing an Original Soil Health Assessment Tool for Tropical Smallholder Farming Systems Based on Minimum Data Sets Calibrated for Nigerian Conditions

This dissertation develops and validates an original soil health assessment tool specifically calibrated for tropical smallholder farming systems in Nigeria, filling the critical gap created by the absence of any nationally relevant, farmer-accessible soil health assessment framework capable of diagnosing soil health status and guiding management decisions across Nigeria's diverse agroecological and social contexts. Existing global soil health frameworks (Cornell Soil Health Assessment, SMAF) were developed for temperate mechanised agriculture and require expensive laboratory analysis, making them inapplicable to Nigerian smallholder contexts. This study develops a minimum data set (MDS) for soil health assessment through canonical discriminant analysis applied to a comprehensive 48-indicator characterisation dataset from 400 smallholder farm soils across all six geopolitical zones. Indicators in the MDS are evaluated for their sensitivity to management, relevance to crop performance, laboratory accessibility, and correlation with soil function outcomes. A composite Soil Health Index (SHI) is constructed from the MDS using a scoring function approach. Parallel development of a farmer-operable visual soil assessment (VSA) protocol, validated against laboratory SHI scores from 200 farms, provides a field screening tool. The dissertation proposes the Nigerian Smallholder Soil Health Assessment System (NSSHAS) as an original contribution, integrating the laboratory SHI, the VSA, and a digital app interface for result interpretation. The NSSHAS is validated by demonstrating significant positive correlation (r = 0.82) between SHI scores and three-year average crop yields across a 120-farm validation cohort. Keywords: soil health assessment, minimum data set, Nigerian smallholder, soil health index, agroecological calibration.