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Evaluating Commercial Precision Agriculture Software
                                                         To Automate On-Farm Research
       Shannon,          D.K.1,          Carpenter,              B.D.2,        Ellis,      C.E.3,        Harper,           J.R.4,   Hoorman,            R.G.5,          Lorenz,           T.E.6,       Rapp,          W.F.7,         Schmitz,        E.G.8

                            1.   Natural Resource Engineering Specialist, University of Missouri Extension, Columbia, MO, 65203               5. Agronomy Specialist, University of Missouri Extension, Montgomery City, MO, 63361
                                      2. Agriculture Business Specialist, University of Missouri Extension, Sedalia, MO, 65301                       7. Livestock Specialist, University of Missouri Extension, Fayette, MO, 65248

                                  3. Natural Resource Engineering Specialist, University of Missouri Extension, Troy, MO, 63379             6. Horticulture/Agronomy Specialist, University of Missouri Extension, Boonville, MO, 65233

                                           4. Agronomy Specialist, University of Missouri Extension, Versailles, MO, 65084                           8. Livestock Specialist, University of Missouri Extension, Warsaw, MO, 65355



                                                                                                                              Abstract
As complicated as precision agriculture is, it offers producers the best opportunity to increase profitability while protecting the environment. The ability to conduct on-farm research is a tool which provides an
opportunity for one to succeed in the adoption of precision agriculture technologies. On-farm research is certainly no replacement for the small plot, university trials, but on-farm research can complement small plot
research and validate small plot research in a large field environment. Precision agriculture tools, such as a yield monitor, can be utilized for conducting field-scale research and spatially documenting yield differences
across fields or treatments. One aspect of on-farm research not as easy to implement is the design and development of field-scale research plots through software automation. The focus of this study is to evaluate
two commercial precision agriculture software packages for the purpose of automating the process of designing strip or block on-farm research trials. Part of the study also evaluated the process on analyzing yield
monitor data from three example on-farm research trials. It was concluded commercial precision agriculture software can automate the process of conducting on-farm research by extending the functionality of current
software capabilities. Future products of this study will be a guide and online course on the design and analysis of on-farm research trials utilizing commercial precision agriculture software..

                                                  Background                                                                                                                Example of Implementation
The ability to conduct on-farm research is a tool which provides an opportunity for one to succeed in the                            The following is an example of an on-farm research study evaluating variable rate phosphorous and
adoption of precision agriculture technologies and allows producers to make better management                                        potassium fertility recommendation strategies. The fields selected for this study were grid soil sampled
decisions. One aspect of on-farm research not as easy to implement is the design and development of                                  utilizing a one acre grid. Four different fertility recommendation maps were created utilizing Ag Leader
field-scale research plots through software automation. In the past one tool available for implementing                              SMSTM Advanced software as treatments for the study (Figure 1). Each treatment was overlaid on 80’ x
on-farm research was Enhanced Farm Research Analyst (EFRA) (Rund, 2000). EFRA extended the                                           300’ plots and replicated 12 times in each field (Figure 2). Plots were embedded in a variable rate
capabilities of ESRI ArcView GIS to accommodate tasks needed for in field scale experimentation                                      application map and applied with standard variable rate fertilizer application equipment. Plots were
through a variety of tools. EFRA simplified many of the tasks involved in setting up on-farm research                                harvested with a yield mapping equipped combine. Yield data was processed utilizing Ag Leader SMSTM
plots using a GIS. EFRA also made possible tools for analyzing yield monitor data at the research plot                               Advanced software to analyze treatment differences. In obtaining treatment differences, 15’ analysis
scale. With the evolution of ESRI ArcView GIS and the Windows operating system, EFRA has nearly                                      buffers were applied to each plot allowing the selection of yield data points only within the plot boundary
reached its usefulness leading to the need for this study.                                                                           (Figure 3). It was found by using the 15’ buffers 7 of the replications from each field could not be
                                                                                                                                     included in the data analysis due to few yield data points within the plot boundary. Table 1 shows the
                                                                                                                                     summary of yield results for one field in the study.
                                            Project Objectives
                                                                                                                                                                             Rep 1         Rep 2          Rep 3          Rep 4            Rep 5   Treatment
Evaluate two commercial precision agriculture software packages for the purpose of automating on-farm                                                                                                                                               Mean
research processes using the following criteria:                                                                                              Treatment                               ---- bu/acre ----
  • The ability to create experimental plots either strips or blocks. In the area of plot design, specific                                    No Fertilizer            163.4    172.3       155.2       188.2                             146.2     164.8
    items evaluated were the effectiveness in the creation of physical plot dimensions and assignment of                                      Whole Field              149.2    150.7       142.6       190.8                             148.9     156.1
    treatments and blocks for replication.
                                                                                                                                              Current                  150.8    180.2       153.0       182.3                             151.3     163.0
  • How yield monitor data can be processed to obtain individual plot yield means for the purpose of
                                                                                                                                              Recommendations
    statistical analysis. This part of the software evaluation included the ability to create plot buffers for
                                                                                                                                              Proposed                 156.4    171.7       153.5       194.8                             165.4     169.1
    accurately selecting yield data points only contained within a plot boundary. These buffers also
    eliminate any confounding of data due to treatment affect.                                                                                Recommendations
                                                                                                                                              Block Mean               154.9    170.4       150.6       189.2                             152.8     163.1
                                                                                                                                                            No significant treatment differences (P=0.05)                                           LSD
                                        Materials and Methods                                                                                                                                                                                        9.9

The two software packages chosen to be evaluated for this project were Ag Leader SMSTM Advanced and                                                                             Table 1. Yield Results for Example Field
Farm WorksTM Mapping and Surface. It should be noted at this point in time only Ag Leader SMSTM
Advanced software has been evaluated. The software chosen were selected using the following criteria:                                There were no significant yield differences between treatments at the 5% probability level. In this field,
ability to process soil sample data, develop fertility recommendation maps, create soil sampling grids, and                          the phosphorus recommendation was 36 lbs/acre less and the potassium recommendation was 56
process yield monitor data. The software’s ability to create soil sampling grids was utilized for the design                         lbs/acre less.
of plots as either strips or blocks.

                                                                                                                                                                         Conclusions and Future Work
                                                                                                                                     It was concluded commercial precision agriculture software can assist in automating the process of
                                                                                                                                     conducting on-farm research. This will allow producers to further utilize precision agriculture
                                                                                                                                     technologies for improving management decisions. During the next year, Farm WorksTM Mapping and
                                                                                                                                     Surface software will be evaluated. Future products of this study will be a guide and online course on
                                                                                                                                     the design and analysis of on-farm research trials utilizing commercial precision agriculture software.

                                                                                                                                                                                                References
                                                                                                                                     Rund, Q. 2000. Enhanced Farm Research Analyst: Tools for On-Farm Crop Production Research. In Proceedings, 20th    Annual   ESRI
                                                                                                                                           International User Conference. ESRI, San Diego, CA.

                                                                                                                                     SMSTM Advanced. 2012. Ag Leader Technology - SMS Advanced Software – Version 12.00. Ames, IA.:. Ag Leader Technology.

   Figure 1. Phosphorus Proposed                Figure 2. Plot Layout Map            Figure 3. Analysis Buffer Overlaid              Farm WorksTM Mapping and Surface. 2012. Farm WorksTM Mapping and Surface – Version 2012.03.0517. Hamilton, IN. Farm Works
    Fertility Recommendation Map                                                               on a Yield Map                             Information Management - A Division of Trimble.

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Shannon prec ag software nacaa poster

  • 1. Evaluating Commercial Precision Agriculture Software To Automate On-Farm Research Shannon, D.K.1, Carpenter, B.D.2, Ellis, C.E.3, Harper, J.R.4, Hoorman, R.G.5, Lorenz, T.E.6, Rapp, W.F.7, Schmitz, E.G.8 1. Natural Resource Engineering Specialist, University of Missouri Extension, Columbia, MO, 65203 5. Agronomy Specialist, University of Missouri Extension, Montgomery City, MO, 63361 2. Agriculture Business Specialist, University of Missouri Extension, Sedalia, MO, 65301 7. Livestock Specialist, University of Missouri Extension, Fayette, MO, 65248 3. Natural Resource Engineering Specialist, University of Missouri Extension, Troy, MO, 63379 6. Horticulture/Agronomy Specialist, University of Missouri Extension, Boonville, MO, 65233 4. Agronomy Specialist, University of Missouri Extension, Versailles, MO, 65084 8. Livestock Specialist, University of Missouri Extension, Warsaw, MO, 65355 Abstract As complicated as precision agriculture is, it offers producers the best opportunity to increase profitability while protecting the environment. The ability to conduct on-farm research is a tool which provides an opportunity for one to succeed in the adoption of precision agriculture technologies. On-farm research is certainly no replacement for the small plot, university trials, but on-farm research can complement small plot research and validate small plot research in a large field environment. Precision agriculture tools, such as a yield monitor, can be utilized for conducting field-scale research and spatially documenting yield differences across fields or treatments. One aspect of on-farm research not as easy to implement is the design and development of field-scale research plots through software automation. The focus of this study is to evaluate two commercial precision agriculture software packages for the purpose of automating the process of designing strip or block on-farm research trials. Part of the study also evaluated the process on analyzing yield monitor data from three example on-farm research trials. It was concluded commercial precision agriculture software can automate the process of conducting on-farm research by extending the functionality of current software capabilities. Future products of this study will be a guide and online course on the design and analysis of on-farm research trials utilizing commercial precision agriculture software.. Background Example of Implementation The ability to conduct on-farm research is a tool which provides an opportunity for one to succeed in the The following is an example of an on-farm research study evaluating variable rate phosphorous and adoption of precision agriculture technologies and allows producers to make better management potassium fertility recommendation strategies. The fields selected for this study were grid soil sampled decisions. One aspect of on-farm research not as easy to implement is the design and development of utilizing a one acre grid. Four different fertility recommendation maps were created utilizing Ag Leader field-scale research plots through software automation. In the past one tool available for implementing SMSTM Advanced software as treatments for the study (Figure 1). Each treatment was overlaid on 80’ x on-farm research was Enhanced Farm Research Analyst (EFRA) (Rund, 2000). EFRA extended the 300’ plots and replicated 12 times in each field (Figure 2). Plots were embedded in a variable rate capabilities of ESRI ArcView GIS to accommodate tasks needed for in field scale experimentation application map and applied with standard variable rate fertilizer application equipment. Plots were through a variety of tools. EFRA simplified many of the tasks involved in setting up on-farm research harvested with a yield mapping equipped combine. Yield data was processed utilizing Ag Leader SMSTM plots using a GIS. EFRA also made possible tools for analyzing yield monitor data at the research plot Advanced software to analyze treatment differences. In obtaining treatment differences, 15’ analysis scale. With the evolution of ESRI ArcView GIS and the Windows operating system, EFRA has nearly buffers were applied to each plot allowing the selection of yield data points only within the plot boundary reached its usefulness leading to the need for this study. (Figure 3). It was found by using the 15’ buffers 7 of the replications from each field could not be included in the data analysis due to few yield data points within the plot boundary. Table 1 shows the summary of yield results for one field in the study. Project Objectives Rep 1 Rep 2 Rep 3 Rep 4 Rep 5 Treatment Evaluate two commercial precision agriculture software packages for the purpose of automating on-farm Mean research processes using the following criteria: Treatment ---- bu/acre ---- • The ability to create experimental plots either strips or blocks. In the area of plot design, specific No Fertilizer 163.4 172.3 155.2 188.2 146.2 164.8 items evaluated were the effectiveness in the creation of physical plot dimensions and assignment of Whole Field 149.2 150.7 142.6 190.8 148.9 156.1 treatments and blocks for replication. Current 150.8 180.2 153.0 182.3 151.3 163.0 • How yield monitor data can be processed to obtain individual plot yield means for the purpose of Recommendations statistical analysis. This part of the software evaluation included the ability to create plot buffers for Proposed 156.4 171.7 153.5 194.8 165.4 169.1 accurately selecting yield data points only contained within a plot boundary. These buffers also eliminate any confounding of data due to treatment affect. Recommendations Block Mean 154.9 170.4 150.6 189.2 152.8 163.1 No significant treatment differences (P=0.05) LSD Materials and Methods 9.9 The two software packages chosen to be evaluated for this project were Ag Leader SMSTM Advanced and Table 1. Yield Results for Example Field Farm WorksTM Mapping and Surface. It should be noted at this point in time only Ag Leader SMSTM Advanced software has been evaluated. The software chosen were selected using the following criteria: There were no significant yield differences between treatments at the 5% probability level. In this field, ability to process soil sample data, develop fertility recommendation maps, create soil sampling grids, and the phosphorus recommendation was 36 lbs/acre less and the potassium recommendation was 56 process yield monitor data. The software’s ability to create soil sampling grids was utilized for the design lbs/acre less. of plots as either strips or blocks. Conclusions and Future Work It was concluded commercial precision agriculture software can assist in automating the process of conducting on-farm research. This will allow producers to further utilize precision agriculture technologies for improving management decisions. During the next year, Farm WorksTM Mapping and Surface software will be evaluated. Future products of this study will be a guide and online course on the design and analysis of on-farm research trials utilizing commercial precision agriculture software. References Rund, Q. 2000. Enhanced Farm Research Analyst: Tools for On-Farm Crop Production Research. In Proceedings, 20th Annual ESRI International User Conference. ESRI, San Diego, CA. SMSTM Advanced. 2012. Ag Leader Technology - SMS Advanced Software – Version 12.00. Ames, IA.:. Ag Leader Technology. Figure 1. Phosphorus Proposed Figure 2. Plot Layout Map Figure 3. Analysis Buffer Overlaid Farm WorksTM Mapping and Surface. 2012. Farm WorksTM Mapping and Surface – Version 2012.03.0517. Hamilton, IN. Farm Works Fertility Recommendation Map on a Yield Map Information Management - A Division of Trimble.