ABEN Masters Theses

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Anaerobic Co-digestion of Dairy Manure with Canola Meal
(North Dakota State University, 2011) Atandi, Eric Michieka
There has been an increase of confined animal feeding operations (CAFOs) generating large amounts of manure. When this manure is not handled properly, it generates greenhouse gases (GHGs), odors and water pollution. Anaerobic digestion (AD) is touted as an acceptable approach to address manure management and associated environmental problems. Biogas production from manure alone is limited by low volumes of biogas yield, thus it has a poor economic reputation. Co-digestion of dairy manure with other agricultural wastes has emerged as a promising strategy to enhance the economic viability of AD. Among the agricultural wastes, canola meal (a by-product from extraction of oil from canola seed) was considered as a potential candidate for co-digestion with dairy manure. The purpose of this research was to investigate the suitability and appropriate ratios of canola meal for anaerobic co-digestion with dairy manure. In this study, various proportions of canola meal: dairy manure (100:0, 10:90, 40:60, 20:80, 0:100) by volume-basis were co-digested in 0.5 L batch bioreactors at a temperature of 35±1 °c for 25 d. Two types of canola meal were used in the study; high oil content (HOC) and low oil content (LOC) canola meal with oil contents of 8.0% and 2.5%, respectively. For HOC, the total solids (TS) were high organic loading (HOL, 7.5±2% TS) and low organic loading (LOL, 4.5±2% TS). LOC trials were done at HOL only. In addition, the pretreatment of the canola meal with caustic solution and digestion at high temperature (60±2°C) were evaluated. Results from this study indicated that at HOL, canola meal is not a viable candidate for anaerobic co-digestion with manure as it lowers biogas production. Manure only digestion performed better than bioreactors augmented with canola meal. The specific methane yield was 352 L/kg VS for manure only and 84 L/kg VS for LOC canola meal only digestion. Nonetheless, at LOL, both 10% and 20% HOC canola meal resulted in increased specific methane of 535 L/kg VS and 445 L/kg VS, respectively. This is 78% and 48% higher than 300 L/kg VS obtained in manure only digestion. Hence, canola meal is beneficial in dairy manure co-digestion at LOL. At all organic loading levels, canola meal alone digestion had the lowest cumulative biogas production (0.9 L per 0.35 L bioreactor) and specific methane yield (83 L/kg VS). For HOL, the cumulative biogas yield and specific methane yield decreased as the canola meal ratio increased, while at LOL, the decrease was only noted for bioreactors with 40% canola meal. This is suspected to be caused by elevated levels of total volatile fatty acids (VF As) of more than 4000 mg/L. Two factors are suspected to impact the accumulation of VF As: the ratio of canola-to-manure in the bioreactor and the organic loading or oil content in the canola meal. In future it will be necessary to look into ways of overcoming the inhibition caused by elevated VF As.
Application of SWAT for Impact Analysis of Subsurface Drainage on Streamflows in a Snow Dominated Watershed
(North Dakota State University, 2011) Rahman, Mohammed Mizanur
The wet weather pattern since the early 1990's has created two problems for the people living in the Red River Valley (RRV): (1) wet field conditions for farmers and (2) more frequent major spring floods in the Red River system. Farmers in the region are increasingly adopting subsurface drainage practice to remove excess water from their fields to mitigate the first problem. However, it is not clear whether subsurface drainage will deteriorate or mitigate the spring flood situation, the second problem. The Soil and Water Assessment Tool (SWAT) model was applied to evaluate the impacts of tile drainage on the Red River's streamflows. The model was calibrated and validated against monthly streamflows at the watershed scale and against daily tile flows at the field scale. The locations and areas of the existing and potential tile drained (PTD) areas were identified using a GIS based decision tree classification method. The existing and maximum PTD areas were found to be about 0.75 and 17.40% of the basin area, respectively. At the field scale, the range of Nash-Sutcliffe efficiency (NSE) for model calibration and validation was 0.34-0.63. At the watershed scale, the model showed satisfactory performance in simulating monthly streamflows with NSE ranging from 0.69 to 0.99, except that the model under-predicted the highest spring flood peak flows in three years. The results of modeling a 100% tiled experimental field showed that about 30-40% of water yield was produced as tile flow. Surface runoff and soil water content decreased about 34% and 19%, respectively, due to tile drainage. However, the impact of subsurface drainage on evapotranspiration (ET) and water yield was mixed. ET slightly decreased in a wet year and slightly increased in a dry year, while the pattern for water yield was opposite to that of ET. The watershed-scaled modeling results showed that a tiling rate of 0.75-5.70% would not have significant effects on the monthly average streamflows in the Red River at Fargo. For the 17.40% tiling rate, the streamflow in the Red River at Fargo might increase up to 1% in April and about 2% in Fall (September to November), while decreasing up to 5% in the remaining months. This SWAT modeling study helped to better understand the impact of subsurface drainage on the water balance and streamflows in the Red River of the North basin. The findings will also help watershed managers in making decisions for the purpose of managing agricultural drainage development in the RRV and other snow dominated watersheds around the world.
Bioavailability and Biodegradability of Dissolved Organic Nitrogen Originated From Municipal and Animal Wastewater
(North Dakota State University, 2015) Sun, Jingyi
Due to the increased concern on dissolved organic nitrogen (DON) in surface waters, it is necessary to understand the biodegradability and bioavailability of DON in point and non-point sources. In this study, algae and bacteria were applied under lab condition to undestand the impact of DON to water environment. Biodegradable DON (BDON) was determined using bacteria while bioavailable DON (ABDON) was determined using green algae Selenastrum capricornutum, Chlamydomonas reinhardtii, and Chlorella vulgaris and/or mixed culture bacteria in municipal and animal wastewaters. In both wastewater sources, ABDON efficiencies (%) for all three algae were not significantly different indicating that Chlamydomonas reinhardtii and Chlorella vulgaris can be used as a test species for nitrogen determination similar to Selenastrum capricornutum. Results showed that, the ranges of BDON and ABDON in municipal wastewaters were 50-60% and 30-77%, respectively, while the ranges of BDON and ABDON in animal wastewaters were 48-54% and 40-81%, respectively.
Characterization of Biochar from Different Feedstocks under Low and High Temperature and Their Effects on Greenhouse Gas Emission and Ammonia Volatilazation from Soil Incubation
(North Dakota State University, 2020) Rahman, Syed MD Wahidur
Biochar is a potential soil amendment that likely to reduce GHG emissions from land application to soil, but their properties depend on biomass types and pyrolysis temperature. In this study, biochars were produced from different biomasses (wet distiller grains (WDG), dry distiller grains (DDG), and corn stover (CS)) at two temperatures (low & high). Biochars were analyzed for pH, electrical conductivity, proximate and ultimate analysis, elemental analysis, and morphological structure. Also, biochar's efficacy on GHGs and ammonia (NH3) emission were measured from soil and manure incubated at 25℃ for 76 days. DDG and CS derived biochar properties outperformed other biochars. Manure treated with high-temperature DDG biochar emitted the lowest amount of N2O (0.09 mg N2O-N kg−1), and CH4 (0.04 mg CH4-C kg−1). Biochar application also reduced CO2 emission from 11 to 59%, but resulted in higher cumulative NH3 volatilization. Overall, biochars reduced GHG emissions when applied with N treatments.
Combined Effect of Densification and Pretreatment on Cellulosic Ethanol Production
(North Dakota State University, 2012) Rijal, Binod
Biomass densification enhances material stability, improves flowability, and decreases both handling and transportation costs. The effect of densification, before or after pretreatment, was tested to determine the effect on cellulosic ethanol processing. Pelleting increased glucose yields of non-pretreated materials by 210% and pelleting followed by acidic and alkaline pretreatments had significant positive impacts on hydrolysis rates or yields. The increase in sugar yields was attributed predominantly to grinding of biomass within the pellet mill. The effects of low pressure densification following AFEX pretreatment were tested under several enzyme loadings both with and without prolonged storage. Densification had no adverse effects on ethanol yields from switchgrass or corn stover; however, prairie cordgrass yields were reduced by 16%. High enzyme loading (15 FPU/g-glucan) produced 15-20% higher ethanol yields than low enzyme loading (5 FPU/g-glucan). Biomass storage by 6-months did not have any negative effects on ethanol yields of AFEX-treated and densified biomass.
Developing a New Powered Seed Delivery System with Constant Seed Release Speed Using Two Confronting Belts
(North Dakota State University, 2018) Ahmadi, Mojtaba
Seed delivery devices are aimed to carry seeds down to open furrow that might affect uniformity of plant stand and spacing. The objective of this study was to develop and evaluate a new seed delivery system utilizing a two-belt mechanism configuration for sunflower (Helianthus annuus). A prototype were fabricated and tested with MeterMax® Ultra Test Stand in order to evaluate the new seed delivery system. The outcomes show that dependent variables like seed population, singulation, skips, and multiples rates were not affected by planting speed levels (Pvalues > 0.05), while planting speed had a negative effect on seed spacing consistency (P-values < 0.05). In addition, due to facing broken seeds during test process, multiples rate were between 8.0 to 9.5% and consequently affected other variables as well. To improve this mechanism and avoid the systematic error that caused by broken seeds, this system should be redesigned in a single-belt form.
Effect of Water Table Level on Soybean Water Use, Growth and Yield Parameters
(North Dakota State University, 2018) Fidantemiz, Yavuz F.
Responses of soybean (Glycine max) water uptake and crop growth to four constant water table depths (30, 50, 70, and 90 cm) were studied under a controlled environment using lysimeters. Additionally, control lysimeters with irrigation and no water table were used for comparison. A randomized complete block design (RCBD) was used with six replications in each treatment. The results indicated that the water table depths of 30, 50, 70 and 90 cm contributed to 77, 71, 65 and 62% of soybean water use, respectively. Thus, the water use efficiency, total grain yield (g lysimeter-1) per unit water use (mm) was 0.008, 0.022, 0.018, 0.025, and 0.031 for irrigation, 30, 50, 70, and 90 cm water table depth treatments, respectively. Soybean was found to be tolerant to shallow groundwater conditions, and root mass distribution in the soil profile was significantly influenced by the presence of shallow water table depths.
Efficacy and Recovery of Cellulases Immobilized on Polymer Brushes Grafted on Silica Nanoparticles
(North Dakota State University, 2014) Samaratunga, Ashani Rangana
Cellulosic biofuels can be more economical if cellulases are recovered and reused. Cellulase and β-glucosidase were immobilized on poly(acrylic acid) brush particles. Impact of brush enzyme density on efficacy and recovery was tested. Use of free enzymes led to higher sugar concentrations than the attached for both the enzymes. Increasing cellulase density on the brushes did not impact efficacy. Higher proportions of cellobiose in hydrolyzates suggest differential attachment or efficacy of attached enzymes. Higher β-glucosidase density on brushes led to increased glucose concentrations. Density on brushes did not impact β-glucosidase recovery and [approximately] 66% was recovered. Effect of pH and temperature on hydrolysis rates and enzyme recovery was modeled. Free β-glucosidase was more stable with temperature than attached. Optimal pH for attached cellulase and β-glucosidase was 4.98 and 4.39, respectively. Recovery of β-glucosidase decreased with increasing pH and was not impacted by temperature.
Evaluating Standard Wet Chemistry Techniques and NIR Spectroscopic Models for Determining Composition and Potential Ethanol Yields of Multi-Species Herbaceous Bioenergy Crops
(North Dakota State University, 2011) Monona, Ewumbua Menyoli
Herbaceous perennials represent a considerable portion of potential biomass feedstocks available for the growing bioenergy industry. Their chemical composition and biomass yields, which are important in determining ethanol potential on an area and mass basis, vary with plant variety and type, environment, and management practices. Therefore, a study was conducted to assess the variability of lignin and carbohydrate content, biomass yields, and theoretical ethanol yields on an area basis among different herbaceous perennial species combinations grown in Minot (2008) and Williston (2008, 2009, and 2010), North Dakota (ND). After wet chemistry compositional analysis was done, the carbohydrate contents were used to determine theoretical ethanol potential on a mass basis. Using the dry-matter yield, the theoretical ethanol yield on an area basis was also calculated for these biomass species. Total carbohydrate content for the biomass samples in Williston and Minot varied from 45 to 61% dry basis. Analysis of Variance (ANOVA) at a= 0.05 showed that carbohydrate content varied between years and environments. Also an interaction plot shows that no biomass species had consistently higher or lower carbohydrate content in the different environments. Switchgrass (Panicum vigatum L.) grown as single species or together with other perennial grasses had higher dry-matter yield and theoretical ethanol yield potential in Williston irrigated plots while mixtures containing intermediate or tall wheatgrass species (Thinopyrum spp.) produced better yields in Minot non-irrigated plots. Variability in theoretical ethanol yield on a mass basis (3.7% coefficient of variation (CV) in Williston and 9.7% CV in Minot) was much less than the variability in dry-matter yields (27.5% CV in Williston and 14.8% CV Minot). Therefore, biomass production is much more important than composition in choosing species to grow for ethanol production. Recently, many studies have focused on developing faster methods to determine biomass composition using near infrared (NIR) spectroscopy. Other NIR models have been developed on single biomass feedstocks but a broad-based model for mixed herbaceous perennials is yet to be developed. Therefore, NIR calibration models for lignin, glucan, and xylan were developed with 65 mixed herbaceous perennial species using a DA 7200 NIR spectrometer (950 - 1,650 nm) and GRAMS statistical software. The models for lignin and xylan had R(2) values of 0.844 and 0.872, respectively, upon validation and are classified as good for quality assurance purposes while glucan model had an R(2) of 0.81 which is considered sufficient for screening. The R(2) and the root mean square error of prediction (RMSEP) results showed that it is possible to develop calibration models to predict chemical composition for mixed perennial biomass when compared with results for models developed for single feedstock by Wolfrum and Sluiter (2009) and Liu et al. (2010). Studying the variability in predicting constituents using NIR spectroscopy over time (hours and days), it was observed that the average CV was between 1.4 to 1.6%. The average CV due to repacking (presentation) alone was 1.3%. The CVs for NIR predictions ranged between 1.4 to 5.7% while for wet chemistry ranged between 3.8 to 13.5%; hence, NIR predictions were more precise than wet chemistry analysis.
Evaluation of Storage Techniques to Preserve Fermentable Sugars from Sugar Beets for Ethanol Production
(North Dakota State University, 2012) Vargas-Ramirez, Juan Manuel
New sugar beet varieties may qualify as an advanced biofuel feedstock in the U.S., but new alternatives to conventional pile storage are necessary to preserve fermentable sugars and allow yearlong beet ethanol production. Fermentable sugar preservation was assessed in sugar beets stored under aerobic and anaerobic atmospheres and in raw thick juice stored at acidic (2≤ pH≤ 5) and alkaline (8≤ pH≤11) conditions. Aerobic storage of sugar beets at 4°C for 14 wk resulted in higher fermentable sugar retention (99± 4%) than at 25°C or anaerobic storage at 4° C and 25° C. Raw thick juice retained ≥ 99% of fermentable sugars at pH 3.5 and 9.5 and refractometric dissolved solids content of 64.5° Bx. The changes in fermentable sugars in raw thick juice stored for 24 wk at acidic and alkaline pH were modeled by response surface methodology. Although raw thick juice was stored successfully at acidic and alkaline pH, conditions for high-efficiency fermentation must be developed.
Extracting Carotenoids from Corn Industry Coproducts
(North Dakota State University, 2016) Cobb, Bonnie Finn
Two experiments were completed to develop methods for extracting xanthophylls from corn industry co-products, post fermentation (PF) corn oil and corn gluten meal (CGM). A solid phase extraction (SPE) method was used to fractionate a xanthophyll-rich portion of PF corn oil by varying conditioning and eluting solvents used with a diol SPE column. Conditioning with dichloromethane yielded highest xanthophyll fractionation, 86.5%. The elution solvent selected did not impact fractionation based on a two-way ANOVA. Supercritical fluid extraction of xanthohpylls from CGM was modeled using a Box-Behnken design, varying temperature, pressure, and co-solvent ratio. The optimum conditions were determined to be 40 °C, 6820 psi, and 15% co-solvent, which would extract 85.4 µg lutein/g CGM, 2.6 times more lutein than an ethanol and chloroform: dichloromethane solvent extraction. Co-solvent was the most influential extraction parameter and increasing it further could yield higher xanthophyll recovery. With further studies, this work has industrial potential.
A Field Study on LiDAR Sensor for Unmanned Ground Vehicle Navigation Application in Precision Agriculture
(North Dakota State University, 2022) Pederson, Breeya
LiDAR sensor’s mapping and detection abilities make these sensors an important tool for research on navigation and object detection for robots and vehicles. This study used a ground robot and LiDAR sensor to collect navigational data sets from North Dakota State University Research Extension Center agricultural test plots in Carrington, ND. Three different height and angle combinations were used to study the factors that could potentially affect object detection. Three trials were run for each sensor placement and recorded the distance the laser pulse traveled and the intensity of the laser. The analysis results showed that the data did not have a normal distribution. However, statistical analysis showed a relationship between the return intensity of the laser pulse from the sensor and the distance the object was from the sensor. Thus, this study showed that LiDAR sensors could be a navigation tool for UGV applications in precision agriculture.
Implementing High-Throughput Phenotyping at the NDSU Dry Bean (Phaseolus vulgaris l.) Breeding Program Using Unmanned Aerial Systems
(North Dakota State University, 2021) Gris, Diego Jose
Plant breeding has led to considerable yield gains to several crops. However, it alone might not be able to keep up with the growing demand for food. In this study, data extracted from UAS-collected RGB and multispectral images were assessed on their ability to estimate four agronomic traits in three market classes of dry beans in a breeding program. The results showed that (i) seed yield, 100-seed weight, stem diameter and days to flowering can be estimated within the same market class with variable accuracy; (ii) aggregating data from several flights yielded better results than using a single flight; (iii) canopy cover was better than NDVI to estimate all agronomic traits; (iv) UAS-based HTP is more efficient than manual phenotyping for fields with more than 300 plots; (v) models fitted to one market class were able to estimate agronomic traits in other market classes with similar data distribution.
Incorporation of Subsurface Drainage and Subirrigation Into the Checkbook Method
(North Dakota State University, 2016) Kolars, Kelsey Aaron
The highly variable climate of the Red River Valley of the North brings both flood and drought conditions, leading to an interest in subsurface water management systems (WMS). These subsurface WMS can drain excess water from the soil profile through subsurface drainage (SSD), manage water tables through controlled drainage (CD), and add additional water through subirrigation (SI). The subsurface WMS used in this study included a 21 ha CD, 17 ha CD + SI, and 16 ha undrained (control) field over a clay loam and silty clay loam soil planted with corn (2013) and soybean (2014). Both SSD and contributions from a shallow WT, through upward flux (UF), were incorporated into the Checkbook method for Irrigation Scheduling. Over the 2013 and 2014 growing seasons, daily soil moisture deficit (SMD), estimated through the modified Checkbook method (SMDSSD,UF) produced similar, if not more accurate, estimations of daily SMD.
Increased Oil Recovery from Distillers Dried Grains with Solubles and Whole Stillage
(North Dakota State University, 2020) Huda, Md. Sanaul
Finding a viable method to recover oil from the corn ethanol industry's co-products has considerable economic prospects for ethanol bio-refineries. This study examined the effects of enzymes and ethanol on oil recovery from dried distillers' grains with solubles (DDGS) and oil distribution in the whole stillage (WS). Protease and cellulase enzymes were tested either individually or in combination with the heavier fractions of DDGS and resulted in 18-20% more oil than the original DDGS. More than 90% of the oil was recovered from the heavier fraction of DDGS using ethanol at 30ºC with 30% solid loadings. Ethanol addition also improved oil partition in WS's liquid fraction by 17–20%. Overall, enzymes and ethanol treatments showed a positive effect on oil recovery from DDGS and WS. Ethanol bio-refineries may use these findings to recover oil as no significant changes are required in the ethanol plant's design.
Infield Biomass Bales Aggregation Logistics and Equipment Track Impacted Area Evaluation
(North Dakota State University, 2017) Navaneetha Srinivasagan, Subhashree
Efficient bale stack location, infield bale logistics, and equipment track impacted area were conducted in three different studies using simulation in R. Even though the geometric median produced the best logistics, among the five mathematical grouping methods, the field middle was recommended as it was comparable and easily accessible in the field. Curvilinear method developed (8-259 ha), incorporating equipment turning (tractor: 1 and 2 bales/trip, automatic bale picker (ABP): 8-23 bales/trip, harvester, and baler), evaluated the aggregation distance, impacted area, and operation time. The harvester generated the most, followed by the baler, and the ABP the least impacted area and operation time. The ABP was considered as the most effective bale aggregation equipment compared to the tractor. Simple specific and generalized prediction models, developed for aggregation logistics, impacted area, and operation time, have performed well (0.88≤R2≤0.99). An ABP of 8 bales capacity, also capable of 11 bales/trip, was recommended.
Machine Vision Methods for Evaluating Plant Stand Count and Weed Classification Using Open-Source Platforms
(North Dakota State University, 2021) Pathak, Harsh
Evaluating plant stand count or classifying weeds by manual scouting is time-consuming, laborious, and subject to human errors. Proximal remote sensed imagery used in conjunction with machine vision algorithms can be used for these purposes. Despite its great potential, the rate of using these technologies is still slow due to their subscription cost and data privacy issues. Therefore, in this research, open-source image processing software, ImageJ and Python that support in-house processing, was used to develop algorithms to evaluate stand count, develop spatial distribution maps, and classify the four common weeds of North Dakota. A novel sliding and shifting region of interest method was developed for plant stand count. Handcrafted simple image processing and machine learning approaches with shape features were successfully employed for weed species classification. Such tools and methodologies using open-source platforms can be extended to other scenarios and are expected to be impactful and helpful to stakeholders.
Manufacturing Low-Density Particleboards from Wheat Straw and Distiller's Dried Grains with Solubles
(North Dakota State University, 2021) Regmi, Sagar
Agricultural byproducts like wheat straw and distillers dried grains with solubles (DDGS) have not found a good market in the wood composite industry. Utilizing DDGS for particleboard in addition to using it as feed will add economic value. This study investigated the potential of using DDGS and wheat straw at different proportions in low-density particleboard with phenol-formaldehyde binder. The effect of alkaline pretreatment of DDGS and wheat straw on the properties of board was also studied. Particleboards were tested for physical and mechanical properties, including density, water absorption, thickness swelling, flexural, internal bond, screw withdrawal, and hardness properties. Particleboards with 25% DDGS loading and 75% wheat straw met most of the mechanical properties requirement for low-density particleboards. Alkaline pretreatment did not improve the properties of manufactured particleboards. This study suggests that a higher fiber fraction DDGS and wheat straw can be used in low-density particleboards with reduced synthetic resins.
Methods for Ethanol Production from the Enzymatic Hydrolysis and Fermentation of Sugar Beet Pulp
(North Dakota State University, 2010) Rorick, Rachel Elizabeth
Sugar beet pulp (SBP), the residue remaining after sucrose extraction, is currently sold as an animal feed. Humans cannot digest the cellulose in the pulp unlike ruminant animals. The pulp is primarily comprised of cellulose, hemicellulose, and pectin which can be hydrolyzed with commercial enzymes into fermentable sugars such as, glucose, arabinose, galacturonic acid, xylose, and galactose. These sugars can be fermented to produce ethanol. This research tested the variation of several enzymes, enzyme loading rates, solids loading rates, and fermenting organisms to increase ethanol yields from sugar beet pulp. Several commercial enzymes (cellulases, hemicellulases, pectinases, and proteases) were tested to determine impact on SBP hydrolysis. Two commercial enzyme preparations (Viscozyme and Pectinex) were compared. Viscozyme produced the highest sugar yields because of increased cellulose hydrolysis, while Pectinex showed less cellulase activity. All enzyme treatments resulted in similar hemicellulose and pectin hydrolysis. Pretreatment with proteases reduced sugar yields from hydrolysis by 10-30% compared to hydrolysis without pretreatment. Escherichia coli K011, a genetically modified organism (GMO), and Saccharomyces cerevisiae were used to ferment SBP hydrolyzate to increase ethanol yields (g EtOH/g SBP) and concentrations (g/L). In the "Parallel" fermentation, pectinase was used to solubilize pectin and hemicellulose. After separation, the liquid stream was fermented with E. coli K011 and the high-cellulose solid fraction was fermented using S. cerevisiae and additional cellulase enzymes (Celluclast and Novozyme 188). The "Parallel" method initially produced under 0.15 g EtOH/g SBP but was improved with pH regulation to yield 0.23 g EtOH/g SBP. The separation method limited ethanol production. The ethanol yields from three additional fermentation methods ("E. coli K011 Only", "Serial", and "Reverse Serial") were compared. The "E. coli K011 Only" method was the baseline fermentation for comparison of the remaining three fermentation methods. SBP was hydrolyzed with pectinase, cellulase, and cellobiase before fermentation with E. coli K011 to yield 0.192 g ethanol/ g SBP. The total hydrolysis of the SBP limited ethanol production. The "Serial" fermentation began by solubilizing pectin and hemicellulose with pectinases. All of the flask contents were fermented with E. coli K011. The remaining cellulose-rich SBP was then hydrolyzed with cellulases and fermented by S. cerevisiae. Initial ethanol yields were under 0.15 g EtOH/g SBP but improved to 0.238 g EtOH/g SBP. Acetic acid concentrations limited ethanol production by S. cerevisiae. The "Reverse Serial" simultaneous saccharification and fermentation (SSF) started with pectinases, cellulases, cellobiases, and S. cerevisiae. Remaining arabinose and galacturonic acid were fermented with E. coli K011 to produce a peak ethanol yield of 0.299 g EtOH/g SBP. The methods approached and exceeded published results (0.277 g EtOH/g SBP) (Doran and Foster, 2000) to successfully increase ethanol yields. Ethanol concentrations were limited by high SBP moisture content and low solids loading rates.
Non-Destructive Analysis of Single Plant Canola (Brassica Napus) Seed Using Near Infrared Spectroscopy
(North Dakota State University, 2013) Sidhu, Harjot
Near Infrared Spectroscopy (NIRS) is widely used for quantitative analysis of oilseeds in a non-destructive manner. Canola (Brassica napus) is a popular oilseed crop that is used for food and biofuel markets. Due to limited seed availability in plant breeding programs, single plant analysis is often preferred. An NIRS commercial calibration model was evaluated to predict single plant canola seed, but the results showed the need for new NIRS calibration models to predict moisture content, oil content, and fatty acid content for single plant canola seed (3 g) with minimal sample preparation. A separate NIRS calibration model was developed for glucosinolates content utilizing 20 g seed. The resulting NIRS calibration models for moisture and oil content were acceptable. However, suitable NIRS calibration models were not obtained for fatty acids and glucosinolates content due to limited constituent variability and the narrow wavelength range used to collect spectra.

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Browsing ABEN Masters Theses by browse.metadata.program "Agricultural and Biosystems Engineering"