Combination of soil classification and some selected soil properties to improve yield prediction: An experience from southwestern Nigeria
2000
Oluwatosin, G.A., Department of Agronomy, University of Ibadan, Ibadan, Nigeria (G. A. 0.'s present address: Soil Survey Unit, I. A. R. and T., P. M B. 5029, Ibadan, N!geria | Ogunkunle, A.0., Department of Agronomy, University of Ibadan, Ibadan, Nigeria
The advantage in the combined use of soil classification and top soil analysis for explaining crop yield variation was examined. Soil properties and yields of maize (Zea mays L.) on different soil types were measured on farmers' fields for 2 years. Yield prediction improved from 2 per cent at the Order and Association levels to 31 per cent at the Series level in the 1st year. The following year, it improved from 5-6 per cent (at the Order and Association levels) to 39 per cent (at the Series level). Regression of yield on soil properties showed that, with one soil property in the regression, yield prediction improved from 30 per cent at the Order level to 37 per cent at the Association level and 38 per cent at the Series level. With five properties in the regression, yield prediction improved trom 42 per cent at the Order level to 44 per cent at the Association level and 66 per cent at the Series level. With 10 properties in the regression, yield prediction improved from 50-51 per cent (Order and Association levels) to 84 per cent at the Series level.
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