Estimating forage availability is important in optimizing livestock stocking rates. The rising plate meter was developed to estimate forage availability. It needs a calibration equation to convert its measurement to a prediction of forage mass, and predictions can vary across crops, seasons, and locations. Our research objective was to derive new calibration equations for wheat (Triticum aestivum L.) and rye (Secale cereale L.). Most past literature used a linear model, but recent literature has suggested that using a quadratic model without an intercept could improve predictions. A non-nested test was used to test among these two non-nested models for wheat and rye calibration equations. The results favored the more encompassing model of a quadratic with an intercept; however, with wheat the quadratic with no intercept was not rejected. A pooling test indicated different equations were needed for species, seasonality (winter and non-winter), and tillage type (tilled or no-till).

The linear response with plateau (LRP) is widely used in agronomic and agricultural economic studies of crop yield response. This empirical example uses data from an under-replicated experiment to compare maize (Zea maize L.) yield response to nitrogen under different plant and corridor row spacing. Not all replications received a 0-nitrogen rate, making estimation of the LRP difficult because data for the intercept terms is absent. We leverage information from other treatments using Bayesian methods to estimate the yield response of each treatment using a LRP function, given limited replication and absence of check plots for some treatments. We use a linearized LRP, which bypasses using the “min” operator typically required to estimate LRP functions. Economically optimal nitrogen rates were determined and net returns from treatments compared from the perspective of risk-averse producers. The wide plant/narrow row treatment was most profitable when the decision rule was to apply nitrogen. The statistical procedure used here may be useful for exploratory analyses of pilot agronomic trials that may include unbalanced and under-replicated treatments.

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