The primary objective of this work is to identify the optimal bioethanol production plant capacity and configuration based on currently available technology for all the processing sections involved. To effect this study, a systematic method is utilized which involves the development of a superstructure for the overall technology selection, process simulation and model regression of each processing step as well as equipment costing and overall economic evaluation. The developed optimization model is also designed to incorporate various biomass feedstocks as well as realistic maximum equipment sizing thereby ensuring pragmatism of the work. For this study, the criterion for optimization is minimum ethanol price. The secondary and more interesting aim of this work was to develop a systematic method for evaluating the economics of biomass storage due to seasonal availabilities. In essence, a mathematical model was developed to link seasonal availabilities with plant capacity with subsequent integration into the original model developed. Similarly, the criterion for optimization is minimum ethanol price. The results of this work reveal that the optimal bioethanol production plant capacity is ~2800 MT biomass/day utilizing Ammonia Fiber Explosion pretreatment technology and corn stover as the preferred biomass feedstock. This configuration provides a minimum ethanol price of $1.96/gal. Results also show that this optimal pretreatment choice has a relatively high sensitivity to chemical cost thereby increasing the risk of implementation. Secondary to this optimal selection was lime pretreatment using switchgrass which showed a fairly stable sensitivity to market chemical cost. For the storage economics evaluation, results indicated that biomass storage is not economical beyond a plant capacity of ~98 MMgal/yr with an average biomass shortage period of 3 months. The study also showed that for storage to be economical at all plant capacities, the storage scheme employed should be general open air land use with a corresponding biomass loss rate as defined in the study of 0.5 percent per month.

Rice produces a lot of biomass which is an important trait in increasing grain yield and it is a potential feedstock for bioenergy production. High biomass rice is important to meet the growing demands of grains and biomass for food, fodder and bio-fuel industries. Limited studies have been conducted to determine its response to unfavorable conditions. The main objectives of this study were to determine the response of selected high biomass rice to drought, rainfed and flooded conditions and identify best genotypes that can be grown in unfavorable areas. Two experiments were conducted in summer 2009 to evaluate biomass yield and agronomic traits of selected high biomass genotypes. A greenhouse study had genotypes grown under drought condition - different field capacity (FC) i.e. 100 percent, 75 percent and 50 percent FC, while the field study had rainfed and flooded environments. Most of the genotypes performed well under fully saturated soil conditions but some were less affected by drought. Limited water delayed first tiller emergence and reduced tiller count, rate of tiller production, plant height, rate of increase in height, shoot and root weight, root:shoot (R:S) ratio, percent dry matter (percent DM) and total biomass. The plant height, tiller plant-1, and total biomass at maturity were lower under rainfed conditions and their flowering was delayed compared to flooded conditions. Majority of these traits were correlated with high biomass yield. Genotype 11 which is tall and late maturing produced the highest number of tillers plant-1 and tillers/ 750 cm2 and had the highest biomass yield under both rainfed and flooded conditions. It performed equally well under drought conditions particularly in root and R:S ratio, but genotype 12 was the best in most parameters measured in the greenhouse. Although it was the shortest genotype, it was highest in biomass yield, earliest to tiller, had the highest shoot weight and tiller count, and had the fastest tiller production. The high biomass genotypes like conventional rice were affected by drought and performed better under flooded conditions. However, these two genotypes can produce optimum results under limited availability of water and hence be used for biomass production under stressed environments.

Sorghum (Sorghum bicolor) has the potential to be used as a cellulosic feedstock for ethanol production due to its diversity and wide adaptation to many different climates. With a wide range of diversity, this crop could be tailored specifically for use as a feedstock for ethanol production. Other factors such as water use efficiency, drought tolerance, yield potential, composition, and established production systems also make sorghum a logical choice as a feedstock for bioenergy production. The objectives of this study were to better understand the biomass potential of different types of sorghum that may be used for energy production, and determine the composition of these sorghums over the season to better understand biomass yield and composition over time. Six commercial sorghum cultivars or hybrids that represent sorghum types from grain to energy were evaluated near College Station, Texas during the 2008 and 2009 cropping years. An optimal harvest window (defined by maximum yield) was established for all genotypes, and significant variation was seen among the genotypes for fresh and dry biomass production. The later maturity genotypes, including the photo-period sensitive and modified photo-period sensitive type sorghums, produced the highest yields (up to 24 dry Mg/ha). Compositional analysis using near infrared reflectance spectroscopy (NIR) for lignin, hemicellulose, and cellulose was performed on a dry matter basis for the optimal harvest window for each genotype. Significant differences were seen in 2009 between the genotypes for lignin, hemicellulose, cellulose, ash and protein; with the earlier genotypes having higher percentage of lignin, and the later genotypes having lower percentages of lignin. Genotype x Environment interactions were also seen, and show the significance that rainfall can have. Based on this research, grain sorghum could be harvested first, followed by photo-period insensitive forage varieties, then moderately photo-period sensitive forage varieties followed by dedicated bioenergy sorghums (that are full photo-period sensitive), allowing for a more constant supply of feedstock to processing plants. Sweet sorghums would also allow the end user to obtain biomass when needed, however these types of sorghum may be much better suited to a different end application (i.e. crushing the stalks to obtain the juice).

The majority of biofuels are produced from corn and grain. The drawback to these sources of biofuels is the vast amount of cultivated land needed to produce substantial amounts of biofuel, potentially increasing the price of food and livestock products. Mesquite trees, a type of woody plant, are a proven source of bioenergy feedstock found on semi-arid lands. The overall objectives of this study were to develop algorithms for determining woody plant biomass on rangelands in Texas at plot-level using terrestrial lidar and at the local scale by integrating reference biomass and multispectral imagery. Terrestrial lidar offers a more efficient method for estimating biomass than traditional field measurements. Variables from the terrestrial lidar point cloud were compared to ground measurements of biomass to find a best fitting regression model. Two processing methods were investigated for analyzing the lidar point cloud data, namely: 1) percentile height statistics and 2) a height bin approach. Regression models were developed for variables obtained through each processing technique for estimating woody plant, above-ground biomass. Regression models were able to explain 81 percent and 77 percent of the variance associated with the aboveground biomass using percentile height statistics and height bins, respectively. The aboveground biomass map was generated by using the cokriging interpolation method with NDVI and ground biomass data. According to cross-validation, ordinary cokriging estimated biomass accurately (R^2 = 0.99). The results of this study revealed that terrestrial lidar can be used to accurately and efficiently estimate the aboveground biomass of mesquite trees in a semi-arid environment at plot level. Moreover, spatial interpolation techniques proved useful in scaling up biomass estimates to local scale.

Several species of fishes have been used for cage culture in Taiwan, including cobia, brown croaker, red drum, grouper, red seabream, emperor and snapper. Roughly speaking, the main factors determining the choice of the target species are mainly the selling price deleting the production cost. Different species have different biological characteristics that affect the economical performance. Included were specific growth rates, death or survival within cultural period, and efficiency in food conversion, etc.. By employing and modified the so-called Biomass model used in fishery biology (Kings, 1995), this research integrates the above factors into one single spreadsheet for each individual species, allowing for systematic observation of the continuous change in level of production (in terms of biomass). Through the culturing period, degrade in number was gradually offset by the gain in averaged body weights until a maximum value is reached before going downhill. This gives rise to the optimal solution of yield with the respective culturing period thus required. The results for different species were further compared in terms of expected investment and return by the end of the production. Results from this study showed that cobia has more advantage (in terms of biomass, biovalue and return on investment) than others as the prior choice under the current situation. Basic information for this study included the value of natural mortality, length-and-weigh relationship and the growth equation of the target species. The system was programmed under the EXCEL-Spreadsheet system of the Microsoft Inc. In the future other species of fishes may also be tested as possible candidates for cage culture. The program could also expected to serve as an auxiliary tool in education and fishery extension services.

Global energy demands combined with environmental restrictions are fueling a move to alternative energy sources. Biofuels are formed from biomass; the MixAlco process is one such method. In this work, food scraps are explored as a potential feedstock to the MixAlco process. Batch fermentation with various temperatures, buffers, and pH control methods elucidated the behavior of food scraps during fermentation. The pH and reactor configuration were limiting factors when maximizing production. A fermentor was developed and tested with constant pH control. This resulted in elevated concentration (100 g/L) and selectivity (82%) of desired products. The fermentation resulted in elevated concentrations, but low conversion of solids. The undigested material may serve as a nutrient source for fermenting lignocellulosic feedstocks. Combining various nutrient sources with lignocellulose, such as bagasse, resulted in additional production and further conversion. Multiple nutrient sources were tested resulting in total acid concentration ranging from 20.2 to 34.5 g/L.

Thesis (Ph. D.)--Oregon State University, 2003. / Typescript (photocopy). Includes bibliographical references (leaves 133-142). Also available on the World Wide Web.

Thesis (Ph. D.)--University of Texas at Austin, 2001. / Vita. Includes bibliographical references (leaves 212-220). Available also in a digital version from Dissertation Abstracts.

Thesis (Ph. D.)--University of Missouri-Columbia, 2002. / Typescript. Vita. Includes bibliographical references (leaves 240-244). Also available on the Internet.

Thesis (Ph. D.)--University of Missouri-Columbia, 2002. / Typescript. Vita. Includes bibliographical references (leaves 240-244). Also available on the Internet.