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PRODUCTION PAPER

Analysis of Seedbeds and Maturity Groups for Dryland Soybean on Clayey Soil

^a Dep. of Agric. Econ. and Agribusiness, 220 Agric. Building, Univ. of Arkansas, Fayetteville, AR 72701
^b Dep. of Crop, Soil, and Environ. Sci., Univ. of Arkansas, Northeast Res. and Ext. Cent., P.O. Box 48, Keiser, AR 72351
^c Dep. of Crop, Soil, and Environ. Sci., 276 Altheimer Drive, Univ. of Arkansas, Fayetteville, AR 72701
^d Dep. of Agric. Econ., 403 Agric. Eng. Building, no. 2, Univ. of Kentucky, Lexington, KY 40546-0276

* Corresponding author (mpopp{at}comp.uark.edu)

Received for publication May 8, 2000. Soybean [Glycine max (L.) Merr.] production systems on clayey soils are difficult to manage. With improvements in no-till planting equipment and herbicide technologies in the early 1990s, no-till production has become a viable alternative to the traditional tilled seedbed. Therefore, the relative economic performance of tilled and no-till seedbeds with respect to profitability, sensitivity to input price changes, and risk is assessed for maturity group (MG) IV, V, and VI soybean. Field experiments using split plots (main plots were MG and subplots were seedbeds) and a randomized complete block design with four replications were conducted from 1992 to 1994 at Rohwer, AR and from 1990 to 1997 at Keiser, AR on Sharkey and Sharkey silty clay, respectively. The importance of weather conditions is highlighted in the varied seedbed preparation effect on grain yields, with no clear advantage to either method. On average, yields were higher for MG IV at Rohwer and MG VI at Keiser. The breakeven price and yield analysis suggested that MG selection had a larger economic impact than seedbed preparation, regardless of location. This analysis also showed the extent of production cost differences and associated risk of loss by location. Risk analysis revealed that optimal production strategies changed when input costs were added to yield information and further confirmed that MG selection affects profitability more than seedbed preparation. Production practices that better exploit the yield potential of various MG cultivars (as related to weather conditions) therefore deserve further research attention.

Abbreviations: CDFs, cumulative distribution functions • FSD, first-degree stochastic dominance • GSD, generalized stochastic dominance • MG, maturity group • MSBG, Mississippi State Budget Generator • NEREC, Northeast Research and Extension Center • NRAT, net returns above total specified cost • RACs, risk aversion coefficients • SSD, second-degree stochastic dominance