Abstract

A technology that can measure wheat grain protein concentration and then segregate grain based on measurements during harvesting is on the horizon. This new technology provides wheat growers with opportunities to segregate grain that can be directed to premium markets. In this article, we identify an individual grower's optimal segregation and blending strategies under non‐uniformly curved price schedules. When price schedules are three‐step shaped, we show that the optimal segregation and blending strategies can be obtained by solving a specified non‐linear programming problem. Based on cash price and protein distribution data for wheat in the U.S. Pacific Northwest region over 1991–2011, an application of our theoretical model shows that on average a Hard Red Winter (respectively, Hard Red Spring) wheat grower should be willing to pay about 17.7 (respectively, 30.8) cents for segregating one bushel of wheat. We also study how growers’ net returns would be affected were the technology to be adopted.

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