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The National Science Foundation's Louis Stokes Alliances for Minority Participation (LSAMP), and HBCU Undergraduate Program (HBCU-UP) have paved the way for undergraduate research involvement in Science, Technology, Engineering, and Mathematics (STEM) disciplines at University of Maryland Eastern Shore(UMES) among the underrepresented minority students. Ongoing multidisciplinary experiential learning and research efforts titled (i) AIRSPACES : Aerial Imaging and Remote Sensing for Precision Agriculture and Environmental Stewardship funded by the Maryland Space Grant Consortium and (ii) Environmentally Conscious Precision Agriculture (ECPA) : A Platform for Active Learning and Community Engagement funded by the United States Department of Agriculture provide synergistic platforms for undergraduate involvement that promotes both the LSAMP and HBCU-UP objectives, while enhancing the proposed outcomes for the AIRSPACES and ECPA projects. The principal author who serves as the principal investigator for the AIRSPACES and ECPA projects at UMES mentored one of the undergraduate students in the LSAMP program in the spring and summer of 2008. The student was partially supported by the HBCU-UP program. The undergraduate student who is also the co-author of this paper got an opportunity to work with the NASA and the USDA collaborators, UMES farm personnel, graduate students, and a team of interdisciplinary UMES faculty collaborators, while performing analyses of geo-referenced harvest data collected over one of the UMES agricultural fields since the inception of the project in 2004. At early stages of the ECPA project, the UMES combine was retrofitted with a yield monitor and GPS unit, and spatial distribution of harvest data have been recorded for the field for all subsequent harvests. The student got an opportunity to learn spatial mapping software such as “ARCGIS” and “SMS Advanced”, while getting exposed to various aspects of the growing field of “precision agriculture”. Based on the analyses of several years of yield data, a simplified “management zone” framework for the field has been obtained. This framework will be refined and utilized for “variable rate seeding” effort in the future for improving the profitability of the field. 1.0 Introduction The benefits of implementing undergraduate research for faculty, students, institution, and the nation as a whole particularly in the STEM disciplines are well documented [1] . The involvement in experiential learning and research by students not only improves content knowledge, and P ge 14059.2 motivation to pursue graduate studies, but also promotes creativity, critical thinking, and selfassurance. The faculty mentor benefits through improved teaching skills and by broadening opportunities for securing funding. The primary author serves as principal investigator for two synergistic projects titled “AIRSPACES: Aerial Imaging and Remote Sensing for Precision Agriculture and Environmental Stewardship”, and “Environmentally Conscious Precision Agriculture : A Platform for Active Learning and Community Engagement” that promotes involvement of undergraduate students from all the STEM disciplines. The former is supported by NASA and the Maryland Space Grant Consortium, while the latter is supported by the United States Department of Agriculture. Involving underrepresented minority undergraduate students in these projects is facilitated through the National Science Foundation’s HBCU-UP and LSAMP programs. These efforts are strongly aligned to both the UMES’ land-grant (UMES is an 1890 Land Grant Institution) mission and the historic mission to serve the underrepresented minority populations. In the summer of 2004, the UMES combine was retrofitted with a yield monitor and a GPS unit as the first step towards engaging in a comprehensive “Precision Agriculture” program [2] . Subsequently, significant progress has been made in enhancing aerial imaging and remote sensing efforts, improving geospatial information technology facilities, development of variable rate application capability, and acquisition of field sensors and data collection tools to support precision agriculture at UMES [3-5] . Significant effort related to the precision agriculture project at UMES has utilized Bozman, a 50 acre production field as the primary test facility. Since the initiation of the project, yield data have been archived for Bozman and other production fields at UMES for further analyses at a later date. This paper reports a study that was performed by an undergraduate engineering student who worked as part of the precision agriculture team to develop simplified “Management Zones” based on multiple years of harvest data of the Bozman field. Appropriate delineation of “management zones” within a production field allows the farmer to manage seeding rate and other nutrients through variable rate application methods with improved efficacy and profitability. Researchers and practitioners have explored several approaches for identifying appropriate “management zones” that utilize soil fertility information, electrical conductivity data, remote imagery of the fields, and yield data [6-8] . Sophisticated computational techniques and statistical analyses have also been utilized to delineate management zones [9, 10] . The approach described in this paper utilizes multiple years of spatially distributed harvest data obtained from the yield monitor, and incorporates simple analyses techniques using software tools such as EXCEL, ARCGIS, and SMS Advanced that may be readily available and used by farmers. 2.0 Site Location, Software Tools, and Data Analysis UMES is an 1890 land grant institution. Figure 1 shows the agricultural fields within the UMES campus. The work described in this paper involves analyses of multiple years of harvest data acquired using combine mounted yield monitor on the Bozman field (shown in light green in Figure 1). The yield monitor system retrofitted on UMES New Holland combine has been acquired from Agleader Technologies [11] . PF-Advantage yield monitor records location information using a GPS against a variety of harvest related data from agricultural fields as shown in the Table 1. The information is recorded in a data card and can be read into a digital P ge 14059.3 computer with PCMCIA slot. In this project, only the data for the “dry yield volume” that appear on the 16 th column in Table 1, are utilized along with GPS information. SMS Advanced, a software tool that has also been acquired from Agleader is used for initial data processing efforts. Spatial distribution maps of yield volume data can be easily developed using SMS Advanced. Figure 2 shows map of grain harvest data of portion of the Bozman field developed using SMS Advanced. Figure 1: UMES Agricultural Fields Figure 2: Yield Map on SMS Advanced TABLE 1: Yield Monitor Data Fields Field Dataset Product Obj__Id Track_degSwth_Wdth_Distance_f Duration_h Elevation_ Area_Count Diff_Statu Time Crop_Flow_ Moisture__ Yld_Mass_D Yld_Vol_Dr Yld_Mass_W Yld_Vol_WePass_Num Speed_mph_ Prod_ac_hr BOZ4 L1: (2004180264) WHEAT 1.0000 333.8458 19.3333 3.4500 0.0006 17.7165 On Yes 6/26/2008 4.8143 17.0000 6068.8314 101.1472 6288.1867 104.8031 1.0000 1.1761 2.7562 BOZ4 L1: (2004180264) WHEAT 2.0000 329.4900 19.3333 4.4500 0.0006 17.7165 On Yes 6/26/2008 3.6762 17.0000 3592.8263 59.8804 3722.6875 62.0448 1.0000 1.5170 3.5551 BOZ4 L1: (2004180264) WHEAT 3.0000 321.8430 19.3333 4.4500 0.0006 18.0446 On Yes 6/26/2008 2.7451 17.000

Simplified Management Zones From Analyses And Mapping Of Multiple Years Of Spatially Distributed Harvest Data