Abstract  The corn dry-grind process is the most widely used method in the U.S. for generating fuel ethanol by fermentation of grain. Increasing demand for domestically produced fuel and changes in the regulations on fuel oxygenates have led to increased production of ethanol mainly by the dry-grind process. Fuel ethanol plants are being commissioned and constructed at an unprecedented rate based on this demand, though a need for a more efficient and cost-effective plant still exists. A process and cost model for a conventional corn dry-grind processing facility producing 119 million kg/year (40 million gal/year) of ethanol was developed as a research tool for use in evaluating new processing technologies and products from starch-based commodities. The models were developed using SuperPro Designer(trademark) software and they handle the composition of raw materials and products, sizing of unit operations, utility consumptions, estimation of capital and operating costs, and the revenues from products and coproducts. The model is based on data gathered from ethanol producers, technology suppliers, equipment manufacturers, and engineers working in the industry. Intended applications of this model include: evaluating existing and new grain conversion technologies, determining the impact of alternate feedstocks, and sensitivity analysis of key economic factors. In one sensitivity analysis, the cost of producing ethanol increased from US$ 0.235 l-1 to US$ 0.365 l-1 (US$ 0.89 gal-1 to US$ 1.38 gal-1) as the price of corn increased from US$ 0.071 kg-1 to US$ 0.125 kg-1 (US$ 1.80 bu-1 to US$ 3.20 bu-1). Another example gave a reduction from 151 to 140 million l/year as the amount of starch in the feed was lowered from 59.5% to 55% (w/w). This model is available on request from the authors for non-commercial research and educational uses to show the impact on ethanol production costs of changes in the process and coproducts of the ethanol from starch process.

Abstract  Seeds for the historic drought of 2012 were sown during the back-to-back La Niña episodes of 2010–11 and 2011–12. La Niña, a name given to anomalous cooling of the equatorial waters of the central and eastern Pacific Ocean, often correlates with drought development and expansion across the southern United States. Indeed, drought began to develop across the southern tier of the U.S. during the winter of 2010–11, and quickly intensified during the 2011 growing season. Effects of the 2011 drought were particularly severe in the south-central U.S.

Abstract  Soybean [Glycine max (L.) Merr.] seed costs have more than tripled, so high seeding rates are expensive insurance against poor emergence associated with planting conditions or pest damage to established plant stands. Drilled soybeans (0.19 m spacing) were evaluated in New York (NY) in 2006 and 2007 at three seeding (358,000; 469,000; and 580,000 seeds ha−1) and four thinning rates (0, 10, 25, and 50% at the sixth node stage) to determine if yields can be maintained at lower seeding rates. Soybean plants responded linearly to seeding rates with 20% more grams of biomass, 0.9 more side branches, 21% more pods, and 21% more seeds plant−1 at 358,000 seeds ha−1 vs. the recommended 469,000 seeds ha−1 (21.1 g, 1.4 side branches, 30.6 pods, and 70.1 seeds plant−1), resulting in similar biomass accumulation (∼555 g m−2) during seed development (∼R5 stage), pod density (817 vs. 805 m−2), and seed density (1883 vs. 1816 m−2, respectively). Seeds pod−1 (∼2.30) and seed mass (∼170 mg) did not vary and all seeding rates yielded similarly (∼3.1 Mg ha−1). Thinning rates resulted in linear reductions in biomass accumulation and pod density with no effect on seeds pod−1 or seed mass. Thinning reduced yields linearly (3.3 Mg ha−1 for no-thinning and 2.8 Mg ha−1 for 50% thinning). Seeding by thinning rate interactions were not observed so plant density reductions after stand establishment posed no greater risk at lower seeding rates. Growers who drill soybeans in the northeastern United States should consider lower seeding rates.

Abstract  This report provides a snapshot of the bioenergy industry status at the end of 2017. The report compliments other annual market reports from the Department of Energy's (DOE's) Office of Energy Efficiency and Renewable Energy (EERE) offices and is supported by DOE's Bioenergy Technologies Office (BETO). The 2017 Bioenergy Industry Status Report focuses on past year data covering multiple dimensions of the bioenergy industry and does not attempt to make future market projections. The report provides a balanced and unbiased assessment of the industry and associated markets. It is openly available to the public and is intended to compliment International Energy Agency and industry reports with a focus on DOE stakeholder needs.

Abstract  Nitrogen is an important agricultural input that is critical for crop production. However, the introduction of large amounts of nitrogen into the environment has a number of undesirable impacts on water, terrestrial, and atmospheric resources. This report explores the use of nitrogen in U.S. agriculture and assesses changes in nutrient management by farmers that may improve nitrogen use efficiency. It also reviews a number of policy approaches for improving nitrogen management and identifies issues affecting their potential performance. Findings reveal that about two-thirds of U.S. cropland is not meeting three criteria for good nitrogen management related to the rate, timing, and method of application. Several policy approaches, including financial incentives, nitrogen management as a condition of farm program eligibility, and regulation, could induce farmers to improve their nitrogen management and reduce nitrogen losses to the environment.

Abstract  In 2018, U.S. farmers planted over 90 percent of corn and cotton acres with genetically engineered (GE) seeds. These GE seeds can be herbicide tolerant (HT), insect resistant (Bt), or both (stacked). Adoption rates vary by trait, crop, and region. In particular, the percentage of acreage planted with seeds that were “stacked” with both HT and Bt traits has greatly increased since 2000.

Abstract  Farmers use a suite of management practices to optimize corn (Zea mays L.) grain yield, including planting at appropriate times for their location. Research on planting dates across the years has tended to use categorical analysis and determination of recommendations by identifying a particular calendar date as optimum and setting yield decline relative to that. This approach was suitable given the experimental designs and number of sites available for analyses. An 18 site-year Iowa dataset, however, that was constructed with planting dates on a sliding scale allowed regression analysis to be used instead of categorical analysis. This approach resulted in the construction of planting-date recommendations as a window of time. Three distinct site-groupings resulted for Iowa, which is different than previous statewide research: north-central (NC) and northeast (NE); northwest (NW) and central (C); and southwest (SW) and southeast (SE). Two planting windows were developed for each site-group based on the maximum yield on the response curve and a subtraction of 2 or 5% relative yield to develop yield windows of 98–100% or 95–100%, respectively. The response curves for each site-grouping identify locations that exhibit a stronger grain-yield response to planting date, especially in the northern and southern locations. The NC–NE grouping had the earliest 98–100% planting window (12–30 April) whereas the NW–C grouping (15 April–9 May) and SW–SE grouping (17 April–8 May) were later.

Abstract  At maturity a black closing layer develops in the placental region of corn (Zea mays L.). The suitability of this black layer as an indicator of physiological maturity was studied in four hybrids of a range in maturity. As viewed by the naked eye the layer developed in 3 days or less, and its appearance coincided with the achievement of maximum kernel dry weight. An examination of a wide range of genotypes indicated that the black-layer formation is a common feature of commercial hybrids at maturity. An investigation of incompletely developed florets on partially barren ears or in the tip region of normal ears revealed black-layer formation in those showing limited endosperm development. No black-layer development was seen in nonfertilized or parthenocarpic florets. The cause and mechanisms of black-layer formation are unknown. However, it is speculated that such development is related to assimilate movement into the developing floret.

Abstract  Reducing tillage and increasing soil cover (through crop rotations and cover crops) can enhance soil health. To gauge the intensity of tillage over time, this report estimates the number of years no-till or strip-till are used over a 4-year period. Conservation tillage was used on 70 percent of soybean (2012), 65 percent of corn (2016), and 67 percent of wheat (2017) acres. Errata: On October 12, 2018, the report Tillage Intensity and Conservation Cropping in the United States was reposted to correct for coding errors that resulted in the miscalculation of some estimates for conservation cropping, cover crops, and other practices that affect crop residue. Specifically, Figure 3, Figure 4, Table 1a, and Table 1b have been replaced. Conforming changes have been made in the text on pages 6, 9, 10, 11, 12, and 18. The largest changes are an increase in cover crop acreage for corn (2016) and cotton (2015) and an increase in conservation cropping for wheat (2017). Acreages for tillage types in Tables 1a and 1b are lower because observations with less than 4 years of crop and tillage data were inadvertently included (but have now been excluded). All changes are restricted to figures, tables, and text that rely on ARMS cropping and tillage history data.

Abstract  The mature corn-to-ethanol industry has many similarities to the emerging lignocellulose-to-ethanol industry. It is certainly possible that some of the early practitioners of this new technology will be the current corn ethanol producers. In order to begin to explore synergies between the two industries, a joint project between two agencies responsible for aiding these technologies in the Federal government was established. This joint project of the USDA-ARS and DOE/NREL looked at the two processes on a similar process design and engineering basis, and will eventually explore ways to combine them. This report describes the comparison of the processes, each producing 25 million annual gallons of fuel ethanol. This paper attempts to compare the two processes as mature technologies, which requires assuming that the technology improvements needed to make the lignocellulosic process commercializable are achieved, and enough plants have been built to make the design well-understood. Ass umptions about yield and design improvements possible from continued research were made for the emerging lignocellulose process. In order to compare the lignocellulose-to-ethanol process costs with the commercial corn-to-ethanol costs, it was assumed that the lignocellulose plant was an Nth generation plant, built after the industry had been sufficiently established to eliminate first-of-a-kind costs.

Abstract  This work presents a detailed analysis of the production design and economics of the cellulosic isobutanol conversion processes and compares cellulosic isobutanol with cellulosic ethanol and n-butanol in the areas of fuel properties and engine compatibility, fermentation technology, product purification process design and energy consumption, overall process economics, and life cycle assessment. Techno-economic analysis is used to understand the current stage of isobutanol process development and the impact of key parameters on the overall process economics in a consistent way (i.e. using the same financial assumptions, plant scale, and cost basis). The calculated minimum isobutanol selling price is $3.62/gasoline gallon equivalent ($/GGE) – similar to $3.66/GGE from the n-butanol process and higher than $3.26/GGE from the cellulosic ethanol conversion process. At the conversion stage, the n-butanol process emits the most direct CO2, at 26.42 kg CO2/GGE. Isobutanol and ethanol plants have relatively similar CO2 emissions, at 21.91 kg CO2/GGE and 21.01 kg CO2/GGE, respectively. The consumptive water use of the biorefineries increases in the following order: ethanol (8.19 gal/GGE) < isobutanol (8.98 gal/GGE) < n-butanol (10.84 gal/GGE). Field-to-wheel life cycle greenhouse gas (GHG) emissions for the ethanol and n-butanol conversion processes are similar at 4.3 and 4.5 kg CO2-eq/GGE, respectively. The life cycle GHG emissions result for the isobutanol conversion process is 5.0 kg CO2-eq/GGE, approximately 17% higher than that of ethanol. The life cycle fossil fuel consumption is 39 MJ/GGE for n-butanol, 43 MJ/GGE for ethanol and 51 MJ/GGE for isobutanol. The energy return on investment for each biofuel is also determined and compared: isobutanol (2.2:1) < ethanol (2.7:1) < n-butanol (2.8:1).