The northern plains states of Montana, Minnesota, and North Dakota have historically based fertilization on the use of composite soil samples, which results in one soil teart number to represent a field. Recent methods, including grian protein mapping in Montana, topography and remote imagery in North Dakota, and renote imagery in Minnesota have revealed patterns within fields of nutrient availability, particularly nitrogen, suggesting new ways to increase the efficiency of nutrient application. Furthermore, these methods appear to have the potential to decrease adverse environmental effects and reduce costs of implementing precision farming. By reducing costs and maintaining high levels of spatial nutrient information compared to dense grid sampling, growers of lower value commodities and higher value crops may benefit from adoption of precision nutrient management compared to a grid sampled system. Due to fragmentation of research between states and lack of funding for precision farming research, there has been little comparision of nutrient zone methods within the region. The objectives of this project are to evaluate methods of zone sampling; to determine ways of combining information from different zone sampling methods; to automate, through algorithms, the nutrient zone boundary determination process. Nitrogen management zones will be determined using topography, remote imaging, protein analysis, electrical conductivity, yield and Order 1 soil series. Fertilization of nutrient zones will be compared to uniform fertilization based on composite soil tests to determine economic impact of zone methods. The economics and environmental consequences of different zone methods with respect to nitrogen fertilization will be compared.

View the CRIS report for the project.