Combining on-farm and climate data for risk management of nitrogen decisions

Abstract

Historical climate data are underutilized in agricultural decision making. We illustrate how long-term climate data and observations from farmers’ fields can be combined to quantify risks from seasonal weather and climate variability for nitrogen fertilizer management for corn (Zea mays L.). We developed a probability model for estimating the risk of deficient corn nitrogen status using within-field late-season plant measurements, field information about previous crop, nitrogen rate, form and application timing in combination with rainfall data. Using three grower risk attitudes (risk-tolerant, risk-neutral, risk-averse) we demonstrate the use of deficient corn nitrogen status probability values for making decisions about nitrogen logistics prior to and within the growing seasons and multi-year investments in more efficient and less risky fertilizer management practices. We find these probabilities could enable growers to explore alternative management scenarios (rates, timing and fertilizer forms) for in-season nitrogen management for each risk attitudes. We conclude that annual surveys of corn nitrogen status across Iowa should be useful not only for field-level logistic decisions but also new in-season weather-based plant status monitoring strategies and tools for evaluating business risk from past weather trends or anticipated changes in weather. While developed for the Midwest United States, the use of annual surveys and on-farm data to translate historical climate data can be implemented in any growing region.

Keywords

• Agriculture risk management
• Rainfall trend
• Seasonal agriculture management