Profitability Maps as an Input for Site‐Specific Management Decision Making

For over a decade, farmers have been collecting site‐specific yield data. Many have formed doubts about this investment because of their inability to directly apply this information as feedback for improving management. The objective of this case‐study analysis was to investigate how site‐specific decisions can be improved by transforming a long‐term multiple‐crop yield‐map dataset into profit maps that contain economic thresholds representing profitability zones. Ten years (1993–2002) of cleaned yield map data 4, 5, and 1 yr for corn ( Zea mays L.), soybean [ Glycine max (L.) Merr., and grain sorghum ( Sorghum bicolor L.), respectively] were collected for a 35.6‐ha claypan‐soil field in Missouri. Actual input costs and crop prices, published custom rates for field operations, and region‐specific land rental prices were used to transform yield maps into profitability maps by year, by crop, and overall for 10 yr. Profit maps revealed large field areas where net profit was negative, largely due to negative profit from corn production on areas where topsoil was eroded. The areal extent and degree to which other unique field features affected profitability, such as a tree line and a drainage way, are discussed. This analysis demonstrates how changing yield into profitability metrics can help a producer consider and then decide on different management options. We explore how assessment and exploratory analysis with profitability mapping supports multiple aspects of the decision process, including identification, development , and selection . The decision process discussed supports a producer's need to manage fields with incomplete information and where satisficing rather than optimizing behavior often occurs. This analysis demonstrated how profit mapping can be of value for a producer and provides impetus for the precision agriculture community to consider profit mapping protocols and standards.