Intensive tillage requires high energy input and may be detrimental to the environment. There is a need to develop decision support tools to assist farmers in determining optimum tillage intensity for high yields. Previous studies developed quantitative indices that related tilth conditions to yield. The indices, however, proved to be inadequate and sometimes inconsistent. Thus, a three-part research project was carried out from 1998 to 2000 to quantify seedbed condition following tillage and to explain subsequent variation in corn (Zea mays L.) yield. Conventional and spatial statistics were used to study the effects of bulk density, penetration resistance and soil moisture content on and biomass at the V2 growth stage (the corn growth stage when the collar of the second leaf has fully developed), and grain yield. A soil condition index was developed and it combined soil physical properties into a single value that was related to yield using regression methods. The soil condition index gave promising results for prediction of early season plant biomass, but was not helpful in predicting grain yield. Confounding of weather conditions made it difficult to determine the true functional relationship between soil tilth and crop yield. Yield and soil map overlays revealed spatial patterns that would have otherwise been aggregated if only conventional statistical methods were used. With careful experimental design, the impact of weather and other sources of experimental error in tillage trials could be minimized. The research project provided a framework for future experiments focused on quantifying soil tilth.