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Annual Report of Progress
to the
MISSISSIPPI SOYBEAN PROMOTION BOARD
for 1997


Project Title: Advanced information Systems for Improved Soybean Production
Project Leader: Michael S. Cox, Department of Plant and Soil Science
Other Participants: M. Alan Blaine, Department of Plant and Soil Science, MCES
David R. Shaw, Department of Plant and Soil Science, MAFES
James Thomas, Department of Agricultural and Biological Engineering, MCES
David Laughlin, Department of Agricultural Economics, MAFES

Objectives and Significant Accomplishments

A three-year study into the benefits of precision agriculture to soybean production was proposed. The objectives of this research were two-fold. The first objective is to use a Global Positioning System (GPS) and a Geographical Information System (GIS) to gather, store, and manipulate site-specific, within-field management information (yield, fertility, physical characteristics, weed populations, etc.). The second objective is to analyze and use this information to develop and make site-specific managemen t recommendations and measure their effect on yield.

In the fall of 1996 and spring of 1997 (the soil sampling season for the first year of this study), three producer fields were identified to participate in this study. These fields were chosen based on the accessibility of yield-monitor-equipped combines, management system, soil variability, and the willingness of the producer to cooperate in the study. The fields are located near Leland, Shaw, and Hernando, Mississippi. Management systems include two irrigated sites and one dryland site. Each field was divided into 2.5 acre cells. Geo referenced soil subsamples were collected from a 10 meter radius around the centerpoint of each cell. Subsamples were combined to represent one sample for each cell. Soils were analyzed for P, K, Ca, Mg, S, Zn, pH, percent organic matter (%OM), and cation exchange capacity (CEC). Soybeans were grown during the 1997 growing season. In the fall of 1997, the soybeans were harvested using the yield-monitor equipped combines. The yield and fertility data have been entered in a GIS. The data is currently being analyzed to determine if fertility had an effect on yield. Attempts to determine weed populations on these three fields were also made. However, the producers had excellent weed control thus weed populations were not consi dered to be limiting yield. After the Fall 1997 harvest the soils were resampled from the same points in the field. Nutrient analysis is currently underway. Samples from these points were also taken to analyze for selected physical properties (hydraulic c onductivity, bulk density, moisture content at field capacity, etc).

During the proposal review process in 1997, we were asked to combine the above study with one proposed by D. Laughlin. This second study was conducted at the Black Belt Branch Experiment Station, Brooksville, MS. Prior to planting soybean, a 15 ha field w as intensively soil sampled on a 0.4 ha grid. Soil samples were analyzed for pH, % OM, CEC, Ca, K, Mg, Na, and P. Variable rate technology for fertilizer application was not available, therefore recommendations from the participating soil scientist along with the Mississippi State Soil Testing Laboratory were followed. Conventional tillage and planting practices were used to facilitate emergence of the crop in late May - early June. Using the same point locations six weeks after planting, natural weed pop ulations within a 1-m2 area were counted. Pitted morningglory (Jpomoea lacunosa L.) exhibited patchy distribution throughout the field and therefore was used in this study. Results of weed population analysis with MSU-HERB indicated the presence of pitt ed morningglory, if present in a 1-m2 sample, was above the economic threshold level. The binary response variable and the soil nutrient data were analyzed using stepwise logistic regression analysis to construct a prediction model for pitted morningglory based on soil properties.

Within a predicted probability range of 0.30 to 0.46, the logistic regression model correctly predicted pitted morningglory presence or absence at 76% of the sampled field locations. Under a given set of soil pH, K, and Na parameters, and within a predict ed probability range of 0.30 to 0.46, this model will correctly predict pitted morningglory presence at least 84% of the time and correctly predict its absence at least 65% of the time.

After the 1997 growing season, an attempt was made to harvest the soybean with a yield monitored combine. However, technical problems with the yield monitor were encountered thus, yield amounts for this field are questionable. Current plans are to continue this study.

Equipment expenditures included: one computer and associated peripherals and one DGPS receiver. Both of these purchases were made by D. Laughlin. No other equipment purchases were made.

Publications

None.
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Soybeans in Mississippi
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