Calculating trendline yields can be a useful tool for budgeting or developing a crop marketing plan. Using trendline yield estimates at the start of the production year can assist in determining potential profitability, at current market prices, and determine if additional sales or price risk management is warranted.

Projected yields should be periodically revisited during the production year to make adjustments to management practices and marketing strategies to improve the likelihood of positive financial outcomes. This article examines differences in linear trendline yields for corn across Southern States.   

Yield variability

There is tremendous variability in average USDA NASS corn yields across the Southern States (Figure 1).  Over the past five years (2019-2023), Arkansas had the highest average corn yield at 179.8 bushels per acre followed by Kentucky (177.6 bushels per acre) and Mississippi (176.2 bushels per acre).

The lowest five-year average yields occurred in Texas (121.2 bushels per acre), North Carolina (129.2 bushels per acre), and South Carolina (129.8 bushels per acre). 

Projected linear trendline yields in 2024 for corn, using USDA NASS data from 1980-2023, vary tremendously (Table 1). The slope coefficient, in Table 1, provides the annual average increase in yield for each state from 1980 to 2023.

The constant in Table 1 is the initial yield at the start of the linear trend line. For example, on average from 1980-2023, corn yields in Mississippi increased 3.33 bushels per acre per year from a starting trendline yield of 43.57 bushels per acre. An easier way to think about this is that over a ten-year period, average yield in the state of Mississippi increased by 33.3 bushels per acre.

Increases can be a result of production practices (such as irrigation) or technology (genetic improvements).

Slowed yield improvement

In the past ten years (2014-2023), the increase in annual yield improvement for most Southern states has slowed.  R2 is a measure of the proportion of variation in the dependent variable (yield) that can be explained by the independent variable (time).

Across the Southern U.S., we see tremendous variation in the R2 for linear trendline yields, ranging from a high of 0.926 for Mississippi to a low of 0.285 for Texas. Low R2 values indicate that the independent variable (in this case time) does not explain the variation in yield, thus other variables need to be considered when projecting yield.  

Ideally, projecting annual yield should be conducted at the farm or field level using producer data. Crop insurance records or yield monitor data can allow producers to analyze, and project, yield and production to guide management and marketing decisions.

Source: Southern Ag Today, a collaboration of economists from 13 Southern universities.