The profitability of precision agriculture in the Bothaville district

[摘要] English: Variable-rate application technology based on soil potential and other field attributes is gradually replacing the standard rates of fertilizer application for individual cropping systems. In South Africa, differential application of inputs in cash crop production is mainly concerned with fertilizer and lime, and this indicates the importance of these inputs. This study evaluates the maize yield response to variable-rate (VR) application of nitrogen (N), and estimates the profitability of VR application of N relative to single-rate (SR) application under South African conditions.Data was collected from an experimental field of 104 ha on a farm in the Bothaville district. A strip-plot design consisting of 180 strips was used for this on-farm research experiment. This design involved treatments that ran in the same direction across the field as planting and harvesting. The objectives were to determine the maize crop response functions under different N rates, to estimate optimal N rates for different management zones in different years, and to assess profit estimates using ordinary least squares (OLS) and spatial error (SER) models. The methodology involves modelling maize yield response functions for N. A Baseline regression model that analyses variable-rate technology as a package was used, while three sensitivity tests were used to determine the consistency of the estimates.The results of this study indicate that there is a significant variation in maize yield response to the applied N on the basis of the application method used. Profit analysis resulting from the application strategies indicates that, in general, VR results in higher farming profits than SR. The analysis indicates that yield obtained from VR strategy can compensate additional costs incurred with the investment in VR technology. This finding is consistent in all the models. It has been established that yield response to fertilizer depends on soil conditions such as the effective soil depth, which has a positive effect on yield. Yield response also differs among management zones.Differences were observed between the results obtained from the OLS models and the results obtained with the SER models, and this has an impact on decision-making. The importance of taking spatial effects into account came to the fore, as inaccurate results can be obtained with methodologies that ignore the spatial dependencies in the analysis of yield monitor data.

[发布机构] University of the Free State