2014 Forecasted Corn Yields Based on Aug. 1 Hybrid-Maize Model Simulations

2014 Forecasted Corn Yields Based on Aug. 1 Hybrid-Maize Model Simulations

Locations of Hybrid Maize Model Models
Figure 1. Hybrid-Maize Model locations.

Interpreting Yield Forecasts

When the range of possible (i.e., simulated) end-of-season yield potential for the current year is compared to the long-term average yield potential (Long-term Yp, third column from left in Table 2 and Table 3), it is possible to estimate the likelihood for below- (75%), average (median, 50%), or above-average (25%) yields.

Comparing estimated 2014 median Yp versus the long-term Yp gives the yield difference from the mean. Minus ("-") and plus ("+") signs next to the median Yp forecast (third column from right) indicate that median Yp is forecasted to be well below (i.e., <-10%) the long-term Yp (minus sign) or well above (>10%) the long-term Yp (plus sign). At a given site, the 75% scenario is most likely if weather conditions are harsher than normal (for example, hot and dry weather or early killing frost) from Aug 1 until crop maturity, whereas the 25% scenario could occur if weather is more favorable (cool, adequate rainfall, no late-season frost) than is typical for this period. Therefore, for a given location, there is a 50% probability that end-of-season yield potential will fall between the 75% and 25% scenarios.

Another way to interpret these odds is to note that end-of-season yield is likely to be above-average when the 75% scenario is higher than the long-term Yp. In contrast, below-average end-of-season yield is likely when the 25% yield scenario is lower than the long-term Yp. As the season progresses, the range of yield outcomes will shrink as the estimated yield levels for the 75% and 25% scenarios converge toward the median value. The change in median Yp since the July 20 forecast helps illustrate how weather has affected Yp during the last two weeks (first column from right).

So, how reliable are Hybrid-Maize forecasts? In well-managed, timely planted fields with good crop establishment that have not been damaged by hail, flooding, diseases, weeds, and insect pests, past experience indicates that estimates of yield potential using Hybrid-Maize are robust. In fields with poor establishment, high disease or pest pressure, or those affected by hail or flooding or replanted late due to devastating storm damage (as is the case in many fields in south-central and eastern Nebraska this year), we expect Hybrid-Maize yield forecasts to be considerably higher than actual yields. Likewise, the model will tend to overestimate yields in crops that suffered large kernel abortion due to severe heat and water stress during pollination.

Aug. 7, 2014

Corn pollination has finished throughout much of Nebraska and grain filling has already started or is about to start. The past two weeks have alternated between below- and above-average temperatures with scattered rainfall across the state. Questions are being asked about how these weather conditions have changed the 2014 end-of-season yield predictions performed on July 20 using the Hybrid-Maize model.

To evaluate, in "real-time" fashion, the impact of current weather on corn yield potential, and its spatial variability across the Corn Belt, simulations of 2014 end-of-season corn yield potential were performed on Aug 1 for 25 locations (Figure 1). Details about Hybrid-Maize and the underpinning methodology to forecast end-of-season yields can be found in the July 25 CropWatch article. The Hybrid-Maize model simulates daily corn growth and development and final grain yield under irrigated and dryland conditions. The model estimates "yield potential," which is the yield obtained when the crop is not limited by nutrient supply, diseases, insect pressure, or weed competition — conditions that represent an "optimal management" scenario. It also assumes a uniform plant stand at the specified plant population, and no problems from flooding or hail. Because weather and management factors are "location-specific," Hybrid-Maize simulations are based on actual weather data and typical management practices at the location being simulated as provided by extension educators in each state (See contributors and site information, Table 1).

Irrigated and dryland yield forecasts as of Aug. 1 are shown in Table 2 (western Corn Belt) and Table 3 (central and eastern Corn Belt). For irrigated corn there has been little change (≤6%) in yield potential forecasts since July 20. Median irrigated yield forecast is within ±10% of long-term average in Nebraska and Kansas, except for two locations in Kansas where the forecast median irrigated yield potential is 12% to 16% higher than the long-term median. The probability of above-average irrigated yields is high in Kansas and at two sites in Nebraska (Clay Center and Mead). Similar to irrigated corn, there has been little change in dryland yield forecasts, except for a 12% increase at Mead, a 17% decrease at Clay Center, and a 9% decrease at Manhattan, KS (decreases at the two previous sites is due to lack of rainfall), and a 12% decrease at Arlington, WI (due to increasing probability of early killing frost during grain filling). Nevertheless, at all dryland sites but one, median dryland yield forecast is near (35% of the sites) or above the long-term average (60% of the sites), with a high probability of above-average yield in 70% of the dryland sites.

Conclusions

Dryland and irrigated yield forecasts at 25 locations across the Corn Belt have changed little since July 20 except at a few locations in Nebraska, Kansas, and Wisconsin. Median dryland and irrigated yields are near or above average at all sites but one, with a high probability of above-average irrigated yields at some locations in Kansas and Nebraska and above-average dryland yields at most sites across the Corn Belt. However, if rainfall stops and temperatures rise throughout August, we would expect both dryland and irrigated yield forecasts to decrease. We will follow up with further forecasts in mid-August and early- and mid-September.

Patricio Grassini, UNL Assistant Professor of Agronomy and Horticulture, Extension Cropping System Specialist and Robert B. Daugherty Water for Food Institute Fellow
Haishun Yang, UNL Associate Professor of Agronomy and Horticulture and Robert B. Daugherty Water for Food Institute Fellow
Roger Elmore, UNL Professor of Agronomy and Horticulture, Extension Cropping System Specialist and Robert B. Daugherty Water for Food Institute Fellow
Ken Cassman, UNL Professor of Agronomy and Horticulture and Robert B. Daugherty Water for Food Institute Fellow
Jenny Rees, UNL Extension Educator
Charles Shapiro, UNL Extension Soils Specialist  and Professor of Agronomy and Horticulture
Keith Glewen, UNL Extension Educator
Greg Kruger, UNL Assistant Professor of Agronomy and Horticulture and UNL Extension Cropping System Specialist
Mark Licht, Extension Cropping System Agronomist, Iowa State University
Ignacio Ciampitti, Crop Production and Cropping System Specialist and Assistant Professor of Agronomy, Kansas State University
Peter Thomison, Extension Specialist and Professor, Ohio State University
Joe Lauer, Professor, University of Wisconsin-Madison