Can Yield Maps Predict Future Yields?

To maximize field productivity and profitability, growers are increasingly using site-specific management rather than whole field management practices. Our objective is to describe spatial and temporal yield variability to predict grain yield of specific land cells (parcels of land). The goal is to determine if yield maps allow accurate delineation of management zones for prescription applications.

Grain yield data for twenty-six years of continuous corn (CC), continuous soybean (SS), and corn-soybean rotations (CS) in no-tillage (NT) and conventional tillage (CT) systems were used in the analysis.

Spatial variability is the variation of land cells within a field for a given year (i.e. yield map) and in this example averaged + 12 bu/A (+5 to +24 bu/A). Temporal variability is the variability of a land cell over time and in this example averaged + 42 bu/A (+40 to +43 bu/A).

Within corn systems, spatial variability was +11 to +15 bu/A and temporal variability was +42 to +44 bu/A. Within soybean systems, spatial variability was +4 to +5 bu/A, while temporal variability was +9 to +13 bu/A.

Each land cell was ranked within its rotation x tillage combination; therefore, to incorporate the CS rotation effect, two years are required for one cycle. Our analysis found that land cells are significantly different for grain yield and could be ranked within a tillage x rotation treatment. CC-NT required 2 years (one cycle) before a significant yield difference was first found between land cells, while corn in CS-NT required 20 years (10 cycles). High- and low-yielding land cells were not consistently identified until 16-20 years (8-10 cycles) had passed, with the exception of CC-CT which only required 4 years (2 cycles).

For specific land cells, high corn yield did not always predict high soybean yield and vice-versa. For example, land cell 102 was the lowest yielding cell for corn, while yielding statistically the same as the highest land cell for soybean.

In this uniform field, consistent land cell grain yield patterns were observed for tillage x rotation treatments. These patterns did not consistently predict grain yield between corn and soybean. Since spatial variation is lower than temporal variation, prescription predictions remain challenging.

For a complete report including tables click here.

Pricing Corn Silage

Pricing corn silage is a difficult decision because it often comes at a time when emotions between sellers and buyers are high. The seller has the opportunity to sell a corn field for either silage or grain and incorporate the fertilizer value of the stover back into the field. The buyer has the opportunity to buy a corn field for silage or buy grain from the market and purchase low quality straw (wheat or corn stover aftermath) to formulate rations.

Arriving at a fair price and being able to take into account the markets (grain, straw, milk and silage), fertilizer, harvesting and quality costs is a difficult decision. Somewhere in the middle of the seller and buyer perspectives negotiations should be able to arrive at a fair price. The Sterry et al. spreadsheet (see http://corn.agronomy.wisc.edu/Season/DSS.aspx) accounts for both the seller and buyer perspectives to arrive at a fair price for corn silage. This article performs a sensitivity analysis of this spreadsheet.

The assumptions and initial values typical for the market conditions heading into the 2013 harvest are shown on page 2 of the original article (click here). To produce the sensitivity analysis in Table 1, one input value at a time was changed on the spreadsheet for grain price, milk price, grain yield, starch content, straw price and NDFD. This can lead to somewhat ambiguous conclusions. For example, often the seller receives a lower price than what the buyer must pay for grain, however, in this example the seller and buyer grain prices are held the same. Also, when one quality measure moves in a certain direction (i.e. starch content) other measures (i.e. grain yield or NDFD) are affected as well. In 2013 many corn fields were late late-planted and affected by drought which affects yield, starch content and NDFD.

Table 1. Sensitivity analysis of seller and buyer perspectives using the Sterry et al. spreadsheet for calculating the value of standing corn silage ($/T) with quality adjustments.

Grain prices between $4 and $7 per bushel affect corn silage price from $28 to $51 per Ton wet. Milk price affects the buyer decision much more than the seller. Low grain yields reduce the price of standing corn silage as does lower starch content. Straw price does not affect the seller perspective, but does affect the buyer perspective of a standing corn silage field because he has the option to buy wheat straw. NDFD had little effect on corn silage price in this spreadsheet.

Users of this spreadsheet need to input their own data for the values used in the calculations.