The Long-Run Impact of Corn-Based Ethanol on the Grain, Oilseed, and Livestock Sectors: A Preliminary Assessment, November 2006

The ongoing growth of corn-based ethanol production raises some fundamental questions about what impact continued growth will have on U.S. and world agriculture. Estimates of the long-run potential for ethanol production can be made by calculating the corn price at which the incentive to expand ethanol production disappears. Under current ethanol tax policy, if the prices of crude oil, natural gas, and distillers grains stay at current levels, then the break-even corn price is $4.05 per bushel. A multi-commodity, multi country system of integrated commodity models is used to estimate the impacts if we ever get to $4.05 corn. At this price, corn-based ethanol production would reach 31.5 billion gallons per year, or about 20% of projected U.S. fuel consumption in 2015. Supporting this level of production would require 95.6 million acres of corn to be planted. Total corn production would be approximately 15.6 billion bushels, compared to 11.0 billion bushels today. Most of the additional corn acres come from reduced soybean acreage. Wheat markets would adjust to fulfill increased demand for feed wheat. Corn exports and production of pork and poultry would all be reduced in response to higher corn prices and increased utilization of corn by ethanol plants. These results should not be viewed as a prediction of what will eventually materialize. Rather, they indicate a logical end point to the current incentives to invest in corn-based ethanol plants.

Iowa Soybean Promotion Board, August 31, 2001 & August 31, 2002

State Agency Audit Report

Iowa Soybean Promotion Board, August 31, 2002 & August 31, 2003

State Agency Audit Report

Iowa Soybean Promotion Board, Independent Auditor's Reports, Financial Statements and Supplemental Information, Schedule of Findings, August 31, 2003 & 2004

State Agency Audit Report

Iowa Soybean Promotion Board, Independent Auditor's Reports, Financial Statements and Supplementary Information, August 31, 2004 & June 30, 2005

State Audit Reports

Emerging Biofuels: Outlook of Effects on U.S. Grain, Oilseed, and Livestock Markets, 2007

Projections of U.S. ethanol production and its impacts on planted acreage, crop prices, livestock production and prices, trade, and retail food costs are presented under the assumption that current tax credits and trade policies are maintained. The projections were made using a multi-product, multi-country deterministic partial equilibrium model. The impacts of higher oil prices, a drought combined with an ethanol mandate, and removal of land from the Conservation Reserve Program (CRP) relative to baseline projections are also presented. The results indicate that expanded U.S. ethanol production will cause long-run crop prices to increase. In response to higher feed costs, livestock farmgate prices will increase enough to cover the feed cost increases. Retail meat, egg, and dairy prices will also increase. If oil prices are permanently $10-per-barrel higher than assumed in the baseline projections, U.S. ethanol will expand significantly. The magnitude of the expansion will depend on the future makeup of the U.S. automobile fleet. If sufficient demand for E-85 from flex-fuel vehicles is available, corn-based ethanol production is projected to increase to over 30 billion gallons per year with the higher oil prices. The direct effect of higher feed costs is that U.S. food prices would increase by a minimum of 1.1% over baseline levels. Results of a model of a 1988-type drought combined with a large mandate for continued ethanol production show sharply higher crop prices, a drop in livestock production, and higher food prices. Corn exports would drop significantly, and feed costs would rise. Wheat feed use would rise sharply. Taking additional land out of the CRP would lower crop prices in the short run. But because long-run corn prices are determined by ethanol prices and not by corn acreage, the long-run impacts on commodity prices and food prices of a smaller CRP are modest. Cellulosic ethanol from switchgrass and biodiesel from soybeans do not become economically viable in the Corn Belt under any of the scenarios. This is so because high energy costs that increase the prices of biodiesel and switchgrass ethanol also increase the price of cornbased ethanol. So long as producers can choose between soybeans for biodiesel, switchgrass for ethanol, and corn for ethanol, they will choose to grow corn. Cellulosic ethanol from corn stover does not enter into any scenario because of the high cost of collecting and transporting corn stover over the large distances required to supply a commercial-sized ethanol facility.

Evaluation of Soybean Varieties Resistant to Soybean Cyst Nematode in Iowa, 2007

Use of resistant soybean varieties is a very effective strategy for managing soybean cyst nematode (SCN), and numerous SCN-resistant soybean varieties are available for Iowa soybean growers. Each year, public and private SCN-resistant soybean varieties are evaluated in SCN-infested fields throughout Iowa by Iowa State University personnel. The research described in this report was performed to assess the agronomic performance of maturity group (MG) I, II, and III SCN-resistant soybean varieties and to determine the effects of the varieties on SCN numbers or population densities.

Managing Soybean Cyst Nematode, 2007

Soybean cyst nematode (SCN) causes the greatest yield loss of any single pathogen of soybean in Iowa. An estimated 50 million bushels were lost in Iowa to SCN in 2004. Damage from SCN is not limited to yield loss from root feeding; SCN also makes other diseases like sudden death syndrome, iron deficiency chlorosis, Pythium, Phytophthora root and stem rot and brown stem rot worse. Once established in a field, SCN cannot be eradicated. However, the use of multiple management tactics can help minimize yield loss.

Managing Soybean for High Yield, 2007

Producers continually strive for high yielding soybeans. The state-wide average yield for Iowa is now more than 50 bu./acre. The “yield plateau” reported by many producers does not exist, and is a perception largely brought on by misuse of an oversimplified management system. High yielding soybeans are achieved through improved and targeted management decisions. Improved agronomic decisions for soybeans are critical since soybean is very sensitive to stresses that influence soybean growth, development and yield.

Soybean Planting Date, 2007

The planting date for soybeans should be based on seedbed conditions and calendar date rather than soil temperature. The optimum time to plant soybeans in Iowa is the last week of April for the southern two thirds of Iowa and the first week of May for the northern one third of Iowa.

Soybean Planting Date, 2007

The planting date for soybeans should be based on seedbed conditions and calendar date rather than soil temperature. The optimum time to plant soybeans in Iowa is the last week of April for the southern two thirds of Iowa and the first week of May for the northern one third of Iowa.

Iowa Grain Facilities Map, July 1, 2009

Iowa Grain Facilities Map

Iowa Grain Facilities Map, July 1, 2010

Iowa Grain Facilities Map

How a soybean plant develops,1982.

This special report from the Iowa State University Cooperative Extension Service, no. 53. is designed to aid those involved in soybean production to more fully understand how the soybean plant develops. The content is both basic and applied. The basic information explains soybean growth and development through one life cycle. Management guides pinpoint practices needed for optimum plant growth and production.

How a soybean plant develops,1985.

This revised special report from the Iowa State University Cooperative Extension Service, no. 53. is designed to aid those involved in soybean production to more fully understand how the soybean plant develops. The content is both basic and applied. The basic information explains soybean growth and development through one life cycle. Management guides pinpoint practices needed for optimum plant growth and production.