Comparing farmers’ soil fertility knowledge systems and scientific assessment in Upper Eastern Kenya

• Published in: Geoderma Vol. 396; p. 115090
• Main Authors: Wawire, Amos W., Csorba, Ádám, Kovács, Eszter, Mairura, Franklin S., Tóth, József A., Michéli, Erika
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 15.08.2021
• ISSN: 0016-7061; 1872-6259
• DOI: 10.1016/j.geoderma.2021.115090

•Farmers have a consistent soil fertility classification knowledge system.•Scientific and farmer soil fertility assessments are correlated.•Farmer-derived soil quality index (SQI) correlated better with Factor analysis SQI than with the simple additive SQI.•Indicators of soil quality can be used to guide land use practices.•Understanding farmer knowledge of soil fertility promotes better communication with soil specialists. Few soil quality studies have attempted to examine the relationship between farmer soil fertility classification indices along scientific measurements, thus calling for closer examination of this association using innovative, comprehensive and systematic approaches. This study was conducted in the upper Eastern Kenya, to compare farmers’ knowledge of soil quality and laboratory soil measurements that were undertaken in the same fields. Farmer-descriptive soil quality indicator (FD-SQI) was compared with two scientific indicators, including additive SQI (A-SQI) and Factor Analysis (FA-SQI). A total of 69 farm households were sampled and surveyed using a face to face questionnaire to collect socio-economic, agricultural and soil quality perception data. Farmers described fertile and infertile soils, using a set of 9 descriptive likert scale indicators. Further, farm fields were classified as high or low fertility based on the farmer’s soil quality rating indicators. Soil samples were georeferenced and collected from 69 farms at surface depth (0–20 cm), after which they were subjected to laboratory analyses using standard methods. Means of key soil properties were compared using ANOVAs, LSD tests and contrasts for both fertile and infertile plots while soil indices derived from farmer soil fertility measures and laboratory soil measurements were regressed using linear models. Farmer-descriptive soil quality indicators scored significantly higher in fertile fields, compared to infertile fields. There was a positive significant relationship between FD-SQI and the two scientific indices. The relationship was stronger between FD-SQI and FA-SQI. The regression of FD-SQI against A-SQI was higher in fertile plots compared to low fertility plots in the study areas. The stronger correlation between FA-SQI and FD-SQI could be attributed to the objectivity of the latter due to elimination of redundancy and bias through statistical procedures and thus greater responsiveness. The A-SQI, on the other hand, is considered subjective due to reliance on literature review and researcher’s point of view. The findings showed that there was a linkage between local and scientific soil fertility assessment paradigms. This implies that farmers’ knowledge of soil quality constituted a consistent and logical classification of soil quality. Local soil knowledge should be developed in conjunction with scientific soil methodologies to benefit resource-poor small-holder farmers in sub-Saharan Africa regions.