Doctoral Dissertations

Date of Award

8-1999

Degree Type

Dissertation

Degree Name

Doctor of Philosophy

Major

Agricultural Economics

Major Professor

Burton C. English

Committee Members

Donald Tyler, Daryll Ray

Abstract

This simulation study was conducted to investigate the role of within-field variability in realizing economic and environmental benefits from precision farming. The objectives of the study were to (i) illustrate analytically the influence of within-field variability on the economic outcomes of a given sampling intensity and therefore, the choice of the most economical sampling scheme, (ii) develop a method to determine the minimum spatial variability (distribution of land within a field with different production capabilities) needed so the additional returns from precision farming would at least cover the costs of using the technology, (iii) illustrate the role of weather expectations in precision farming, (iv) test the hypothesis that precision farming holds the promise of environmental benefits, and (v) examine policy options to motivate farmers to adopt precision farming, if the new technology is found to reduce environmental degradation.

The objectives were accomplished assuming that the farmers' main objective was profit maximization and that the technology was adopted by custom hiring the necessary services from the farm service sector.

The study created four hypothetical com fields with different degrees of within-field variability on which nitrogen (N) was applied at variable rates based on soil sample tests. The results suggested, for each sampling intensity considered, that the more variability, the higher the returns above N costs with Variable Rate Technology (VRT) than with Uniform Rate Technology (URT). Further, it was indicated by the results that higher sampling intensity was economically optimal for the fields with higher variability, over a range of sampling costs considered.

Precision farming need not necessarily imply grid sampling. The technology could be used to apply inputs at spatially variable rates on different land types (classified, for example, according to soil series, slopes, landscape positions, etc.) with their oAvn yield responses to applied inputs. Under such circumstances, economic feasibility of adopting VRT depends upon the existing land mix on the field. Given input and product prices, custom charges, and knowledge of yield response to applied inputs on two or more land types, the study developed a method to identify the required land proportions so the additional returns from VRT could at least cover custom charges. These proportions were referred to as spatial break-even variability proportions.

It is not just economic benefits that are claimed of precision farming. The new technology is also expected to benefit the environment by matching input application to plant and soil needs. The study investigated the potential of precision farming to reduce N loading into the environment. The Environmental Policy Integrated Climate (EPIC) crop growth model was used to estimate com yield responses to applied N and predict total N losses on different soils under different rainfall scenarios.

The results indicated potential of the new technology to help reduce environmental degradation. The analysis suggested increasing importance of well-informed and accurate weather expectations under precision farming. In the majority of cases examined, farmers' decisions to adopt VRT meant economic losses when their rainfall expectations went wrong. Given the evidence of environmental benefits from being precise in input application, the study analyzed policy options to motivate farmers to adopt VRT. Subsidizing custom charges and restricting N use were the two options analyzed and found to help reduce N loss. The results showed totally different effects on production and farm incomes of input use restriction with and without VRT. With farmers having access to VRT, the fall in returns due to N restriction was much less than the fall that would have occurred with the same N use restriction without precision technology. Interestingly, when N use was restricted and farmers were forced to adopt VRT, production actually increased compared to the amount produced with URT under conditions of unconstrained N supply.

To sum up the findings of this study, the economic benefits from grid sampling depend upon the extent of variability; highly intensive sampling is beneficial for the fields with high variability. Farmers often have a broad idea of variability across the field based on characteristics like soil series, slope, soil depth and yield variability shown by yield monitors. Planned sampling needs to be guided by such prior experience.

The land mix on the field impacts the economic outcome of VRT. The method developed here helps find the minimum spatial variability needed on fields with two or more land types so the farmer can at least offset the custom charges with VRT adoption. The method is flexible and incorporates changing input and product prices as well as custom charges.

VRT holds environmental promise. However, a farmer's motive to adopt the technology is purely economic. As such, efforts are needed to make the technology attractive to farmer. Where the technology proves beneficial for the environment, government can subsidize custom charges to promote VRT adoption. Restricting input use could also promote technology adoption without much adverse effect on income and production. Farmers need to be more informed in formulating weather expectations under precision farming; the adverse effects on their economic interests due to wrong expectations can be more severe with VRT than with URT.

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