Economic and Stochastic Efficiency Comparison of Experimental Tillage Systems in Corn and Soybean Under Risk

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Fathelrahman, Eihab
Ascough, James
Hoag, Dana
Malone, Robert
Heilman, Philip
Wiles, Lori
Kanwar, Ramesh
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Kanwar, Rameshwar
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Agricultural and Biosystems Engineering

Since 1905, the Department of Agricultural Engineering, now the Department of Agricultural and Biosystems Engineering (ABE), has been a leader in providing engineering solutions to agricultural problems in the United States and the world. The department’s original mission was to mechanize agriculture. That mission has evolved to encompass a global view of the entire food production system–the wise management of natural resources in the production, processing, storage, handling, and use of food fiber and other biological products.

In 1905 Agricultural Engineering was recognized as a subdivision of the Department of Agronomy, and in 1907 it was recognized as a unique department. It was renamed the Department of Agricultural and Biosystems Engineering in 1990. The department merged with the Department of Industrial Education and Technology in 2004.

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  • Department of Agricultural Engineering (1907–1990)

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There are many reasons why agricultural researchers carefully evaluate approaches to experimental data analysis. Agricultural experiments are typically highly complex, with many types of variables often collected at a wide range of temporal and spatial scales. Furthermore, research in the developing world is often conducted on-farm where simple and conventional experimental designs are often unsuitable. Recently, a variant of stochastic dominance called stochastic efficiency with respect to a function (SERF) has been developed and used to analyse long-term experimental data. Unlike traditional stochastic dominance approaches, SERF uses the concept of certainty equivalents (CEs) to rank a set of risk-efficient alternatives instead of finding a subset of dominated alternatives. This study evaluates the efficacy of the SERF methodology for analysing conventional and conservation tillage systems using 14 years (1990–2003) of economic budget data collected from 36 experimental plots at the Iowa State University Northeast Research Station near Nashua, IA, USA. Specifically, the SERF approach is used to examine which of two different tillage systems (chisel plough and no-till) on continuous corn (Zea mays) and corn/soyabean (Glycine max) rotation cropping systems are the most risk-efficient in terms of maximizing economic profitability (gross margin and net return) by crop across a range of risk aversion preferences. In addition to the SERF analysis, we also conduct an economic analysis of the tillage system alternatives using mean-standard deviation and coefficient of variation for ranking purposes. Decision criteria analysis of the economic measures alone provided somewhat contradictive and non-conclusive rankings, e.g. examination of the decision criteria results for gross margin and net return showed that different tillage system alternatives were the highest ranked depending on the criterion and the cropping system (e.g. individual or rotation). SERF analysis results for the tillage systems were also dependent on the cropping system (individual, rotation or whole-farm combined) and economic outcome of interest (gross margin or net return) but only marginally on the level of risk aversion. For the individual cropping systems (continuous corn, rotation corn and rotation soyabean), the no-till tillage and rotation soyabean system was the most preferred and the chisel plough tillage and continuous corn system the least preferred across the entire range of risk aversion for both gross margin and net return. The no-till tillage system was preferred to the chisel plough tillage system when ranking within the continuous corn and the corn-soyabean rotation cropping systems for both gross margin and net return. Finally, when analysing the tillage system alternatives on a whole-farm basis (i.e. combined continuous corn and corn-soybean rotation), the no-till tillage system was clearly preferred to the chisel plough tillage system for both gross margin and net return. This study indicates that the SERF method appears to be a useful and easily understood tool to assist farm managers, experimental researchers and, potentially, policy makers and advisers on problems involving agricultural risk.


This article is from Experimental Agriculture 47 (2011): 111–136, doi:10.1017/S0014479710000979.