Klein E. Ileleji

Life Cycle Assessment of Potential Biojet Fuel Production in the United States

The objective of this paper is to reveal to what degree biobased jet fuels (biojet) can reduce greenhouse gas (GHG) emissions from the U.S. aviation sector. A model of the supply and demand chain of biojet involving farmers, biorefineries, airlines, and policymakers is developed by considering factors that drive the decisions of actors (i.e., decision-makers and stakeholders) in the life cycle stages. Two kinds of feedstock are considered: oil-producing feedstock (i.e., camelina and algae) and lignocellulosic biomass (i.e., corn stover, switchgrass, and short rotation woody crops). By factoring in farmer/feedstock producer and biorefinery profitability requirements and risk attitudes, land availability and suitability, as well as a time delay and technological learning factor, a more realistic estimate of the level of biojet supply and emissions reduction can be developed under different oil price assumptions. Factors that drive biojet GHG emissions and unit production costs from each feedstock are identified and quantified. Overall, this study finds that at likely adoption rates biojet alone would not be sufficient to achieve the aviation emissions reduction target. In 2050, under high oil price scenario assumption, GHG emissions can be reduced to a level ranging from 55 to 92%, with a median value of 74%, compared to the 2005 baseline level.

The effect of process variables during drying on the physical and chemical characteristics of corn dried distillers grains with solubles (DDGS) - Plant scale experiments

Corn dried distillers grains with solubles (DDGS) are highly valued as an animal feed for its nutrient content. The amount of wet distillers grains (WDG) and condensed distillers solubles (CDS) blended together during drying affects nutritive value and physical characteristics of DDGS. Effect of changing the ratio of WDG and CDS, and recycled DDGS during drying on particle size, particle size distribution, particle and bulk densities, color, chemical composition, and amino acid content was studied. Moisture content and particle size of DDGS decreased with decreasing amount of CDS added. About 80% of the particles were within a narrow size range (<1500 microm). Bulk density and tapped density of samples produced with different CDS content ranged from 420.5 to 458.1 and 498.8 to 544.3 kg/m(3), respectively. True density decreased with reduction in CDS added. As the CDS content reduced, DDGS became lighter in color. Insoluble fiber contents (protein and insoluble fiber) and amino acids increased while fat, total soluble sugars and glycerol decreased as the CDS content added to WDG reduced. The correlation coefficient of individual chemical components with CDS was above 0.90. Results from this study will be helpful in predicting the physical and nutritive property changes due to variable ratios of blending CDS to WDG during the drying process.

Comparison of two diet types in the determination of metabolizable energy content of corn distillers dried grains with solubles for broiler chickens by the regression method

The objective of this study was to compare 2 diet types, practical and semi-purified, in the determination of ME and ME(n) contents of corn distillers dried grains with solubles (CDDGS) for broiler chickens by the regression method. Two hundred eighty-eight 14-d-old Ross 308 broiler chickens were assigned to 6 diets consisting of 2 factors in a 2 x 3 factorial arrangement: diet type (practical corn-soybean meal or semi-purified nitrogen-free diet) and CDDGS (0, 300, or 600 g/kg). The birds were fed for 7 d, and there were 6 birds per cage and 8 replicate cages per diet in a randomized complete block design. The CDDGS sample used in the present experiment contained (by analysis) 895 g/kg of DM, 4.811 kcal/g of gross energy, 265.7 g/ kg of CP, 107.6 g/kg of crude fat, 61.3 g/kg of crude fiber, and 41.8 g/kg of ash. There was the expected interaction (P < 0.001) between diet type and CDDGS level in nitrogen retention response of the birds with a decrease as CDDGS level in the practical diet increased but an increase in the semi-purified diet. There were interactions (P < 0.001) between diet type and CD-DGS level in energy retention response, ME, and ME(n). Energy retention linearly decreased (P < 0.0001) from 78.6 to 58.6% as CDDGS increased from 0 to 600 g/kg in the practical diets, whereas the decrease was from 86.8 to 75.4% in the semi-purified diet. The ME and ME(n) (kcal/g) contents of the diets linearly decreased (P < 0.0001) from 3.615 and 3.414 to 2.753 and 2.642, respectively, as CDDGS increased from 0 to 600 g/kg in the practical diets. Corresponding linear decrease (P < 0.0001) values for semi-purified diets were 3.210 and 3.227 to 2.732 and 2.697, respectively. Regression of CDDGS-associated ME intake in kilocalories against grams of CDDGS intake generated the following equations for practical and semi-purified diets respectively: Y = 2.904X + 52, r(2) = 0.987 and Y = 3.013X + 67, r(2) = 0.983. The regression equations for CDDGS-associated ME(n) intake in kilocalories against grams of CD-DGS intake were Y = 2.787X + 46, r(2) = 0.989 and Y = 2.963X + 66, r(2) = 0.983 for practical and semi-purified diets, respectively. Comparison using ANOVA procedures indicated the slope for semi-purified diet type was greater (P < 0.05) than that for the practical diet type. These data indicate that the respective ME and ME(n) values (kcal/g) of the CDDGS sample evaluated were 3.013 and 2.963 when semi-purified nitrogen-free diet was used as the basal diet; and 2.904 and 2.787 when practical corn-soybean meal diet was used as the basal diet. These differences imply that broiler chicken nutritionists should exercise due caution regarding the source of data for ME values of CDDGS when formulating diets containing CDDGS.

Detection of a Developing Hot Spot in Stored Corn with a CO2 Sensor

The primary objective of this study was to determine the effectiveness of detecting a hot spot primarily due to spoilage of high moisture corn in a stored grain bulk with a CO2 sensor installed in the headspace of the bin compared to detecting with temperature cables. Three experimental trials were conducted in a 12.5-t pilot-scale bin from September 2001 to March 2002. A hot spot in the grain bulk was initiated by dripping a controlled amount of water into a confined grain mass held in five layers of cylindrical mesh trays within the grain bulk. Temperature sensors in the core of the hot spot formation monitored its progress and confirmed biological activity, which paralleled the increasing CO2 concentration recorded by the CO2 sensor in the headspace of the bin. CO2 concentrations in the bin headspace rose from the initial base level of 500 to 1500 ppm for Trial 1, 1700 ppm for Trial 2, and 2300 ppm for Trial 3 and were recorded after 400, 600, and 1800 h, respectively. There was a strong positive linear correlation between the rise in headspace CO2 concentration and the parallel rise in temperature recorded by sensors in the core of the hot spot during all three trials. Field tests of spoilage detection with a CO2 sensor conducted in 33,000- to 51,000-t grain piles and a 12,500-t cylindrical steel tank with stored corn indicated that a CO2 sensor was effective in detecting the occurrence of spoilage in the stored grain and detected spoilage earlier than temperature cables. Spoilage detection was effective either by measuring CO2 concentration of the air stream from a negative draft aeration duct with a handheld CO2 sensor, or by installing a wall-mounted CO2 sensor in the tank headspace. Our results show that temperature cables alone might not be a reliable indicator of stored grain conditions and CO2 sensors could be used as an additional complimentary tool for stored grain management.

Application of elastic net and infrared spectroscopy in the discrimination between defective and non-defective roasted coffees.

The quality of the coffee beverage is negatively affected by the presence of defective coffee beans and its evaluation still relies on highly subjective sensory panels. To tackle the problem of subjectivity, sophisticated analytical techniques have been developed and have been shown capable of discriminating defective from non-defective coffees after roasting. However, these techniques are not adequate for routine analysis, for they are laborious (sample preparation) and time consuming, and reliable, simpler and faster techniques need to be developed for such purpose. Thus, it was the aim of this study to evaluate the performance of infrared spectroscopic methods, namely FTIR and NIR, for the discrimination of roasted defective and non-defective coffees, employing a novel statistical approach. The classification models based on Elastic Net exhibited high percentage of correct classification, and the discriminant infrared spectra variables extracted provided a good interpretation of the models. The discrimination of defective and non-defective beans was associated with main chemical descriptors of coffee, such as carbohydrates, proteins/amino acids, lipids, caffeine and chlorogenic acids.

Particle heterogeneity of corn distillers dried grains with solubles (DDGS).

In this study the physical, morphological and chemical characteristics of distillers dried grains with solubles (DDGS) produced by mixing three levels of condensed distillers soluble (CDS) (0%, 3.69% and 7.39% volumetric basis, v.b.) with wet distillers grains and drying were characterized. Decreasing the CDS level from 7.39% to 0% v.b. resulted in a reduction of 13.9% in geometric mean particle size and 8.8% in bulk density while the compressibility of the material increased by 3%. As the CDS level increased, pore volume, particle porosity and effective bulk porosity decreased. Crude fat, crude protein, crude fiber and ash content showed distinct patterns for all three samples studied and suggest that US sieve no. 16 (1190 μm) may be an inflection point for the chemical characteristics of DDGS granules within a bulk. The observed heterogeneity could cause sampling errors and particle segregation, and as a consequence nutrient and bulk density variability.

Fourier transform infrared spectroscopy and near infrared spectroscopy for the quantification of defects in roasted coffees.

The coffee strip-picking harvesting method, preferred in Brazil, results in high percentages of immature and overripe beans, as the fruits in a single tree branch do not reach ripeness at the same time. This practice, together with inappropriate processing and storage conditions, contribute to the production of high amounts of defective coffee beans in Brazil, which upon roasting will impart negative sensory aspects to the beverage. Therefore, the development of analytical methodologies that will enable the discrimination and quantification of defective and non-defective coffees after roasting is rather desirable. Given that infrared spectroscopy has been successfully applied to coffee analysis, the objective of this work was to evaluate and to compare the performances of Fourier transform infrared (FTIR) and near infrared (NIR) spectroscopies for the quantification of defective beans in roasted coffees. Defective and non-defective Arabica coffee beans were manually selected, roasted, ground and sieved. Mixtures of defective and non-defective roasted and ground coffees were produced and analyzed, with % defects ranging from 0% to 30%. FTIR and NIR spectra were recorded, respectively, within a range of 3100-800 cm(-1) and 1200-2400 nm and submitted to mathematical processing. Quantitative models were developed by partial least squares regression (PLSR). Excellent predictive results were obtained indicating that defective coffees could be satisfactorily quantified. The correlation coefficients and the root mean squared errors of validation for the FTIR and NIR models developed to quantify the amount of defective roasted coffees mixed with non-defective ones were, respectively, as high as 0.891 and as low as 0.032, and as high as 0.953 and as low as 0.026. A comparison between the two techniques indicated that NIR provided more robust models.

Basics of Energy Production through Anaerobic Digestion of Livestock Manure

Abstract This chapter gives an overview of the Anaerobic Digestion Process using livestock manure. The benefits of anaerobic digestion and what makes an operation appropriate for anaerobic digestion are described.

How Fuel Ethanol Is Made from Corn

Abstract In this chapter, fuel ethanol, yeasts role in ethanol production, corn as ethanol feedstock, industrial ethanol production including wet milling, and dry-grind ethanol processing steps (milling, liquefaction, saccharification, fermentation, distillation and recovery) are described along with the energy use in ethanol production.

Evaluation of Measurement Procedures Used to Determine the Bulk Density of Distillers Dried Grains with Solubles (DDGS)

The production of corn-based ethanol in the U.S. has been dramatically increasing in recent years, and consequently so has the quantity of co-products, especially distillers dried grains with solubles (DDGS), generated from this industrial sector. DDGS is sold as a commodity for animal feed, and like corn, its bulk physical and chemical properties are quality attributes that can be used in trading by merchandisers. Consistency in product quality has been a cause for concern in the industry, and the lack of standard methods for physical and chemical property determination potentially confounds the issue, especially when results of attributes measured by different methods have not been evaluated for method parity. Toward that end, this research examined the sources of DDGS bulk density variability using samples from six commercial ethanol plants (three from Indiana, and three from South Dakota) and conducted in two different laboratories. Variations due to sample handling, container filling method, filling height, and container size were also examined. It was ascertained that DDGS source accounted for most of the bulk density variability observed. It was also determined that filling height and measuring container size resulted in significant differences in the resulting bulk density values.