Integrating Data from Various Field Experiments: The Case of Corn in Texas

Procedures to integrate field experimental data from diverse experiments into a comprehensive production function are needed. Such functions would more effectively use available information and result in better systems recommendations for producers. A proposed procedure was used to estimate a corn (Zea mays L.) production function incorporating four management inputs; hybrid maturity, applied N, planting density, and planting date. Estimated production function relationships were used to identify production and profit‐maximizing levels of the variable inputs. The returns above variable costs (RAVC) surface in four dimensions (N, population, planting date, and net returns) was very flat within the relevant range of inputs. A flat RAVC surface indicates that differing input levels will give approximately the same RAVC. Such a flat surface helps explain why differing input levels are observed across “successful” farmers within a given region. The results also suggested a strong relationship between input levels and the variance of corn yield. Knowledge of such relationships is essential when making recommendations to farmers on how to manage risk.