Corn Yield Forecast: The fundamentals
Creating a corn yield forecast is a process of understanding what drives corn yield forecasts, finding the necessary data to create a relevant statistical model, and then using machine learning techniques to find the relationship between the important factors of crop growth.
CropProphet is a corn, soybean, and winter wheat forecasting system that uses weather data to predict yield in bushels per acre and total crop production. While this discussion focuses on creating a corn yield forecast, the method is the same for the other crops as well.
The trading and grains markets focus on yields because, as discussed below, it is fundamentally impacted by the growing season weather. Crop production, which can be calculated as a yield * the number of planted acres, varies year-to-year based weather. The market perceptions of total corn production can impact market prices such as the July corn futures price. Trading opportunities are created because CropProphet is more accurate the market perceptions.
Crop production can also change based on the planting decisions of producers. Crop yields are, therefore, a relatively easy metric to follow and is an easy proxy for crop production. The market perceptions of the likely annual crop supply are a primary factor causing corn and soybean futures prices to change.
Corn Yield Forecast: The Model
- Technology Trend +
- Weather +
- The error that remains after creating the model.
Where is corn grown?
To be able to model yields, it is important to have corn yield data. Corn yield data is provided by the USDA NASS. The final national yield estimates for each growing season is reported by the USDA in January of the next year. For example, the 2019 US national corn yield estimate was released in January of 2020. This data is what is used to model corn yields.
The regions of the United States that grow corn are shown below. The regions with darker green shading depict counties that grow more corn relative to its contribution to national production. This predominantly corn area is called the “Corn Belt.”
For application to corn yield forecasting, the technology trend is created by all factors that cause the average yield per harvested acre for corn the United States is larger than the year before. This includes all of the seed, fertilizer, machinery, management technology that has been developed to improve yields.
The collective result is the technology trend, which is the upward sloping yield in the graphic below. The technology trend, which increases the average yield each year, helps to create the baseline corn yield potential to start forecasting each year.
Corn Yield Forecast: Weather
It’s possible to remove the technology tend from the history of corn yield data. Doing so removes the impact of the technology trend. The information that remains, based on the model stated above, is the impact of weather conditions on corn yields.
The technology trend estimation for this blog post is measured as the simple linear trend of corn data above over time. For implementation in CropProphet, however, we use a much more sophisticated method to estimate the technology trend.
Using techniques of Big Data analytics and machine learning, it’s possible to include the impact of weather on the forecasted end of season yields. The process used for CropProphet seeks to find the optimal relationship between weather and corn in regions smaller than states.
The national yield forecast is then created by production weighting the smaller regions yield forecasts. CropProphet uses weather data sets developed from 3rd party sources of weather information. The weather data is used to model the USDA end-of-season reported corn, soybean, and winter wheat yields.
Corn Yield Forecast: Example from 2012
Many people remember the summer of 2012, which was an extremely warm and dry year across much of the central United States. 2012 creates an excellent test case for to evaluate the performance of a yield forecasting model. Watch the animation below to see how the 2012 season evolved.
Impact of Weather Forecast Models
But it’s difficult to know the impact that any single weather forecast may have on a crop during the growing season. To address this problem, CropProphet also converts the weather forecast information into an analysis of the impact on the crop yield forecast. This provides an advantage of being ahead of the market expectations of crop production and therefore in the corn or soybean futures market.
An example of an ECMWF weather forecast model is provided below.
The resulting product is a sophisticated corn yield forecast model that can be used to gain an advantage in corn futures and soybean futures market trading.
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