2016 FACTS Crop Year in Review

November 16, 2016
ICM News

The 2016 crop year is in the books. While there were a couple of periods where it looked like the weather was going to have significant impact, it turns out only to be short lived. State average yields are projected to be a record for both corn (199 bushels per acre) and soybean (59 bushels per acre).

With record breaking, bin-busting corn and soybean production this year, it would be easy to think there is not a need to look back on the growing season. That couldn’t be further from the truth. We should look back on the growing season to evaluate what went right. To look back at the 2016 growing season we are going to use FACTS (Forecast and Assessment of Cropping sysTemS) to understand how this complex interaction between crops, soil, weather, and management influenced grain yields. More information is available on the FACTS website regarding all aspects of the project.

2016 weather implications

The weather in 2016 could be split into two periods: warm and dry weather conditions during late May and June followed by cool and wet weather in July and August (Table 1). June resulted in 2.4 to 3.9 inches less rainfall than normal, except in northeast Iowa where they received 5 inches more rainfall than normal. On average, our locations had 8.6 more heat stress days and 110 accumulated growing degree days than normal for June. Rainfall in July and August was 0 to 3 inches per month greater than normal, whereas heat stress days were 0 to 4 days less than normal.

Table 1: Actual cumulative monthly differences between 2016 and long-term (1980-2016) weather variables across six locations in Iowa. A negative value means that 2016 was below climatology and vice versa. Central-A is Ames and Central-K is Kelly.

Precipitation from November 2015 to April of 2016 provided a full to nearly full soil moisture profile going into planting. This available soil moisture kept both the corn and soybean crop from experiencing moisture stress because root growth was able to follow the soil moisture depletion zone during the dry June conditions. Most Iowa soils are deep and can hold approximately 10 inches of available water, providing substantial buffering capacity. Not surprising, warm temperatures and less precipitation  led to more solar radiation and growing degree day accumulation. At the time, this was a concern because corn leaf development was occurring faster than normal while corn growth, or vegetative biomass accumulation, was less than normal. This resulted in pollination occurring about seven days earlier with less vegetative biomass than in 2015.

During July and August, temperatures subsided and rainfall was received during pollination and grain filling. This provided non-limiting soil moisture and minimized crop stress during pollination. Cooler temperatures helped extend the grain filling period, allowing kernel size and weight to achieve full potential. In the end, the shortened vegetative period was compensated for by a lengthened reproductive period. This is evident with a corn harvest index in 2016 (0.57) reflecting more grain production with less vegetative biomass.

In contrast to corn, our 2016 soybean crop biomass measurements were somewhat higher than 2015. The soybean crop benefited more than corn from the higher radiation in June (15% higher than normal) and this resulted in more vegetative biomass. Also, soybean has higher thermal requirement than corn. This higher thermal requirement means that the higher temperatures in June promoted faster canopy closure and thus more light interception occurred. The near optimum soil moisture conditions during grain fill helped soybeans achieve high yields. We did not observed any major pod loss over time in 2016.

FACTS prediction compared to actual in-field harvest

Our FACTS corn yields ranged from 200 to 240 bushels per acre and our soybean yields ranged from 55 to 75 bushels per acre. On average across 10 corn systems and 10 soybean systems, FACTS predictions were 2.3% lower than actual corn yields and 3.1% greater than actual soybean yields. In most cases, the prediction error was ± 5-10%. The reasons for under-prediction and over-prediction were primarily due to uncertainties of the initial soil moisture profile at planting, cultivar characteristics, and biotic factors. For example, in central and southeast Iowa corn yield was under-predicted because of underestimating the influence of the groundwater table and soil moisture. In northeast Iowa, corn yield over-prediction was due to excessive rain near maturity causing an environment conducive for in-field ear drop and yield loss.

We found yield predictions at the time of planting are a good proxy for final, actual yield by using accurate field management, 35-year historical weather conditions, and accounting for soil moisture and nitrate at planting. The prediction error is still within ± 5-10% with a few exceptions. This may be hard to believe but is supported by our FACTS results in both 2015 and 2016. In summary, the key point for reaching record corn yield and production levels can be attributed to a full soil moisture profile at planting, more solar radiation and higher temperatures in June, and a cooler wetter grain filling period.

Figure 1. Actual FACTS corn and soybean yields at 6 locations for 10 corn systems and 10 soybean systems. The red triangle represents the FACTS predictions at the last forecast of September 12, 2016. The asterisk represents sites with tile drainage.


Figure 2.  Validation of the FACTS yield forecast as percent error for the prediction at crop planting.



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Mark Licht Associate Professor

Dr. Mark Licht is an associate professor and extension cropping systems specialist with Iowa State University Extension and Outreach. His extension, research and teaching program is focused on how to holistically manage Iowa cropping systems to achieve productivity, profitability and en...

Sotirios Archontoulis Professor of Integrated Cropping Systems

Dr. Sotirios Archontoulis is an assistant professor of integrated cropping systems at the Department of Agronomy. His main research interests involve understanding complex Genotype by Management by Environment interactions and modeling various components of the soil-plant-atmosphere continuum. Dr...