The efforts to increase soil productivity has been ?eld-based experiments with little information on farmers’ indigenous knowledge of soil quality acquired through experience. This study assessed farmers’ indigenous knowledge on soil quality and fertility management practices in the Ada West District of Ghana. Two hundred-and-twelve farmers from five communities were interviewed using pre-tested questionnaires. Fifteen farmers each from four communities identified and classified their soil into high, medium and low soil quality. Thirty-six soil samples were collected based on farmers’ categorization and analysed to determine some physicochemical properties to determine the differences in soil quality categories. The Principal Component Analysis (PCA) was used to select effective indicators as the Minimum Data Set (MDS). Results showed that 89% of farmers’ use soil amendments out of which 71.1% combined organic and inorganic fertilizer, 19.6% applied only organic and 9.3% applied only inorganic fertilizer. The soil quality indicators used by farmers were based on visually observable indicators such as soil colour, presence of living organism, soil moisture, vigour plant growth, crop yield, soil texture, presence of plants and weeds, erosion and thickness of topsoil. Farmers’ soil quality categorization was contrary to the laboratory reports although soils from perceived high quality were relatively higher than medium and low. In PC1 electrical conductivity, available phosphorus, organic carbon, organic matter, calcium, and magnesium had a higher positive loading. In PC2, sand and silt had the highest factor loading while clay and sodium had the highest factor loading for PC3 and PC4 respectively. Farmers have good knowledge on soil quality but did not know the rate of soil amendments to apply. Farmers’ indigenous knowledge should be supplemented with scientific soil information. There is need for more training and education on application rates of soil amendments.
Farmers, Farm management practices, Indigenous knowledge, Principal component analysis, Soil quality indicators
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