Forecasted corn yield potential and attainable yields for 2015

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At this point in the season, a large proportion of Kansas corn is at flowering stage. The most recent USDA Kansas Agricultural Statistics Service crop progress report (July 12, 2015) projected 47% of Kansas’ corn crop is at the silking stage, less than the percentage from last year at this time but still near the average. Overall, more than 50% of the corn crop in Kansas was classified by Kansas Agricultural Statistics as good or better. Pollination conditions around the state are generally acceptable, but high temperatures can represent a challenge in early-pollinated corn, and could potentially affect final effective grain number per ear. From now until harvest, weather will be one of the primary components driving changes and affecting corn yield potential.

Potential corn yield estimation

Estimating potential corn yields can help us understand the maximum yield attainable if management is optimal and in absence of unmanageable adversities, such as hail or flooding. A research team based at the University of Nebraska is currently leading a project for forecasting corn yield using historical and current weather and management information in collaboration with faculty and extension educators from 10 universities across the U.S. Corn Belt (

The corn simulation model -- Hybrid-Maize Model ( -- was developed by researchers in the Agronomy and Horticulture Department at UNL and takes into consideration several factors such as weather, plant population, hybrid relative maturity, planting date, and soil type, among other factors. The model assumes optimal management, with no limitation imposed by nutrients or biotic factors (weeds, insect pests, pathogens) and no adversities such as flooding, hail or abiotic factors (heat, drought). Thus, the model provides maximum yield is conditions are optimal. A yield gap, difference between final attainable yield and maximum yield predicted, will increase if management was sub-optimal or there were other adverse factors not accounted by the model that may reduce corn yield. Simulations can be performed to forecast current-season corn yields. Factors such as site-specific weather conditions from planting until the simulation date and historical weather information to simulate the rest of the 2015 growing season are used for the simulation. Myriad yield scenarios could be produced depending on the growing conditions from the simulation date until harvesting time, but forecasts are more accurate and reliable as the simulation time approaches corn maturity.

Simulation results for Kansas

A total of 45 sites were simulated for corn yields across the U.S. Corn Belt, including 5 sites for Kansas – rainfed, irrigated, or both water scenarios, and 1 site in Missouri (Fig. 1) that is relevant for the northeast Kansas area. Sites include Garden City, Hutchinson, Silver Lake, Manhattan, Scandia, and St. Joseph, Mo. A separate yield forecast was performed for irrigated and dryland corn for Scandia and Silver Lake, while only irrigated corn was simulated at Garden City. The dryland scenarios for corn yield forecast were Manhattan, Hutchinson, and St. Joseph, Mo.

Daily weather data used for simulating these locations were retrieved from the High Plains Regional Climate Center (HPRCC For Kansas, local agronomists provided information about soil properties and crop management (hybrid maturity, plant populations, and historical and 2015 planting dates) required for the simulations (Table 1). The following agronomists should be properly acknowledged for investing their time and providing their expertise: Eric Adee, Agronomist-in charge, Kansas River Valley Experimental Research Field, Topeka; Gary Cramer, Agronomist-in charge, South Central Kansas Experimental Field, Hutchinson; and John Holman, Southwest Research-Extension Center Cropping Systems Agronomist, Garden City.

The current locations represent just a sample of the corn area in the state. More sites could be added in the coming years to increase the site-specificity of the corn yield forecast analysis.

Figure 1. Locations utilized for simulation purposes for Kansas.




Table 1. Management and soil data used for forecasts in Kansas and St. Joseph, Mo.


Forecasted corn yield potential (“Yp” in Table 2) was calculated first as long-term yield potential, based on 25+ years of weather data. The model then calculated 2015-forecasted yield potential, utilizing current-season weather (link to weather conditions across 10 states: summary). The 2015 in-season yield potential forecasts for Kansas is presented in Table 2.

At almost all sites simulated in Kansas, there is close to 50% probability of achieving near average yields for the current season as relative to the long-term yield potential (Yp).

Under irrigated conditions (Scandia, Silver Lake, and Garden City), there is a greater probability of having above-average yields compared to the long-term yield potential for Scandia (34%) than for Garden City (21%) or Silver Lake (10%). Under rainfed conditions, there is a higher probability of having above-average corn yields in 2015 in the northeast corner of Kansas if planted before first week of May (Table 1). There is a fair probability (>=30%) of having above-average yields for the rest of the dryland sites as well (except for Silver Lake; 24% - Table 2). It should be emphasized that forecasted yield for corn regardless of the weather scenario looking promising overall for this growing season.

Table 2. 2015 In-season Yield Potential Forecasts for Kansas and St. Joseph, Mo. (July 15).



Stress conditions impacting corn in the coming weeks would likely reduce yields through an impact on grain number (grain abortion). As clarified in the UNL article (see link below), these predictions do not assume any current or past production problems (e.g. saturated soils, replanting, hail/flooding, nitrate leaching and nutrient deficiencies) nor any influence of biotic (e.g. disease, insects) or abiotic (e.g. heat, drought) stress factors.

You can read the full paper related to forecasted yields in 45 locations around the Corn Belt at:


Ignacio Ciampitti, Cropping Systems and Crop Production Specialist