Best fit model selection for spatial differences (regression) in the profitability analysis of precision phosphate (P) application to winter cereals in Precision Agriculture (PA)

Phosphates (P) are an important nutrient required by every living plant and animal cell, and deficiencies in soils could cause limited crop production, thereby reducing profitability. Phosphates are also a primary nutrient essential for root development and crop production, and are needed in the tissues of a plant where cells rapidly divide and enlarge. Precision agriculture (PA) could assist the farmer in applying the correct amount of P to the part of the field where it is required most. Variable rate technology (VRT) is a potential tool that can help with the development of strategies for phosphate fertilizer management. On-field trials were conducted on a commercial farm in the Western Cape Province; As many as five soil types occur on each field studied, and three crops – wheat, canola and barley - are grown in rotation. One half of each field was planted using VRT (PA), while constant application (SR) was used on the other half. The objective was to determine whether spatial econometric models are more accurate than traditional ordinary least squares (OLS) models in predicting the profitability impact of P on PA. There are significant differences to be observed between the results obtained with the OLS, Spatial Error (SER) and restricted maximum-likelihood (REML) models. All the measures of goodness of fit indicated an increase in fit from the OLS to the SER model, with the best fit being achieved with the REML model, implying that the use of this model resulted in more accurate estimates.

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 Record created 2017-04-01, last modified 2017-08-25

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