Higher input prices can increase economic incentives for precision agriculture. The study evaluated fertilizer application rates using four scenarios on a farm with nine years of GPS yield data. Scenario 1 used the farmer's normal practices. Scenario 2 used 2.5 acre grid soil sampling. Scenario 3 used management zones based on soil type. Scenario 4 used zones based on GPS crop removal. Scenarios 2-4 all reduced fertilizer use and increased net returns, with savings of $36-88 per acre compared to normal practices. Precision agriculture was shown to be economically beneficial.

1. HIGHER INPUT PRICES RESULT IN GREATER ECONOMIC INCENTIVES FOR PRECISON AGRICULTURE. F. John Barker III, Extension Educator, OSU Extension – Knox County, Mt. Vernon OH 43050 EMPOWERMENT THROUGH EDUCATION OSU Extension embraces human diversity and is committed to ensuring that all educational programs conducted by Ohio State University Extension are available to clientele on a nondiscriminatory basis without regard to race, color, age, sex, gender identity or expression, disability, religion, sexual orientation, national origin, or veteran status. Methods Nine years of accurate and calibrated yield data was available for a local field utilizing a GPS based yield monitor. This field was in a strict corn-soybean rotation. Fertilizer recommendations were developed utilizing the four following scenarios. Scenario 1: Fertilizer recommendations were made according to the farmers’ normal production practices. Variable rate technology was not utilized in this scenario. All applications were made through the planter. Farmers often question the economic value GPS-based technology. Does precision agriculture pay? In most precision agriculture circles, this is the most often asked question, and at times a most difficult question to answer. Today’s technology allows farmers to vary the application rates of crop inputs throughout a field. GIS software allows field specific data to be analyzed and incorporated into the decision making process. Theoretically, combining field based data with the ability to vary input usage at specific locations within a field should increase input efficiency. Increased efficiency should improve profit margin and result in the adoption of more environmentally sound practices. The objective of this study was to evaluate phosphorus and potassium fertilizer application rates utilizing four different fertility scenarios on a Central Ohio farm with nine years of GPS based yield data. These scenarios were; 1) The farmers normal production practices, 2) Soil testing and fertilizer recommendations based upon 2.5 acre grid samples, 3) Soil testing and fertilizer recommendations based upon management zones developed by soil type and 4) Fertilizer recommendations based upon management zones developed by GPS based crop removal. Does precision agriculture pay? The results of this analysis show economic advantages for each GPS based scenario. When compared to the farmers’ normal production plans, the grid sampling scenario resulted in savings of $36.36 per acre. The soil type management zones and the crop removal management zones resulted in savings of $84.91 and $88.04 respectively. Abstract Objective The objective of this study was to evaluate fertilizer use and application rates utilizing four different fertility recommendation scenarios. Only phosphorus and potassium applications were analyzed in this study. Economic implications will also be analyzed . Results Table 1 contains the fertilizer use data from this analysis. Fertilizer recommendations were made for each of the four scenarios using the Tri-State Fertilizer Recommendations as a guide (OSU Extension Bulletin E-2567). Overall fertilizer use was the highest using the farmers’ normal production practices (scenario 1). Utilizing grid soil sampling and variable rate applications (scenario 2) fertilizer use was reduced by 3,420 pounds. Soil sampling using management zones based upon soil type and utilizing variable rate fertilizer applications (scenario 3) reduced overall fertilizer use by more than 3.5 tons. Scenario 4 which utilized G.I.S. software to divide the field into management zones based upon crop removal and utilizing variable rate fertilizer applications produced the most efficient fertilizer use. This scenario, which is based on the actual field production, shows phosphorus recommendations were reduced by almost 1.5 tons and the potash recommendations were cut in half. Economic Implications Table 2: Economic Results Table 1: Fertilizer Comparison The economic implications of this study are displayed in Table 2. Fertilizer prices of $650/ton for Potash and $850/ton for D.A.P. were used for this analysis. Soil testing charges and variable rate fertilizer application charges were included where appropriate. Scenario 4, fertilizer recommendations based upon crop removal produced the greatest savings. This scenario which had the lowest fertilizer use and no soil testing charges resulted in a savings of $88.04 per acre when compared to the farmers normal production plans. Soil sampling by soil type (scenario 3) and 2.5 acre grid sampling (scenario 2) resulted in savings of $84.91 per acre and $36.36 per acre respectively, when compared to the normal production practices for this farm. But does it pay? In this analysis Yes! Each scenario involving variable rate fertilizer applications resulted in lower fertilizer use and a greater net return. With today’s soaring fertilizer prices, savings of $36 to more than $88 per acre can have a significant impact on most Central Ohio farms. Figure 2: Harvest Dreams. Scenario 2 : The field was divided into 2.5 acre grids. Soil samples were pulled and sent to a lab for analysis. The fertilizer application data was developed for this field utilizing a variable rate technology based upon the results from the soil test data. Scenario 3 : The field was divided into management zones based upon soil type. Soil samples were then pulled from each soil type. Each sample size was approximately 2.5 acres or less. The fertilizer application data was developed for this field utilizing variable rate technology based upon the results from the soil test data. Scenario 4: GIS software was used to divide the field into management zones. These zones were based upon actual, historic crop removal data from this field. Fertilizer recommendations were based upon the actual crop removal in each of these management zones. Fertilizer applications were made utilizing variable rate technology (Fig. 1.). Figure 1: Management Zones based on Crop Removal. $88.04 $84.91 $36.36 $0.00 Saving vs. Normal Plan ($/A) $134.81 $137.94 $186.49 $222.85 Total Cost ($/A) $6.00 $6.00 $6.00 $0.00 Variable Rate Fert. Application $128.81 $131.94 $180.49 $222.85 Fertilizer Cost + Soil Test ($/A) 0.00 $0.70 $0.70 $0.00 Soil Test Cost($/A/Year) $128.81 $131.24 $179.79 $222.85 Total Fertilizer Cost ($/A) $55.00 $49.50 $79.75 $110.00 K Cost ($/A) $73.81 $81.74 $100.04 $112.85 P Cost ($/A) 9,945 10,080 13,905 17,325 Total Fertilizer Use (Lbs./Field) 100 90 145 200 K Recommendation (LBS. K 2 O/A) 121 134 164 185 P Recommendation (LBS. P 2 O 5 /A) Crop Removal Soil Type 2.5 Acre Grid Normal (-4500) (-4950) (-2475) -- K Difference (LBS. K 2 O /Field) 4500 4050 6525 9000 K Recommendation (LBS. K 2 O /Field) (-2880) (-2295) (-945) -- P Difference (LBS. P 2 O 5 /Field) 5445 6030 7380 8325 P Recommendation (LBS. P 2 O 5 /Field) Crop Removal Soil Type 2.5 A Grids Normal