ABEN Masters Theses

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Rapid Evaluation of Canola Lines for Cold Soak Filterability in Biodiesel
(North Dakota State University, 2010) Lin, Hongjian, M.S.
Worldwide concerns about fossil fuel depletion and energy security have recently triggered a research interest in biodiesel, which is renewable, biodegradable, and has several other advantages as an alternative to petro diesel. However, biodiesel may cause engine problems, especially fuel filter plugging, associated with its use in cold weather conditions. Trace contaminants such as glycerin, saturated monoglycerides (SMG), and soap compromise cold weather performance of biodiesel. A cold soak filtration test was recently included in the U.S. specifications for biodiesel (ASTM D 6751-09) to evaluate biodiesel cold weather performance. Canola seed has good potential to be a locally important biodiesel feedstock because of its high yield (1500 to 2200 kg/ha) and oil content (40 to 50%, Brassica napus L.), as well as a suitable fatty acid profile for good cold weather performance. For a plant breeding program evaluating canola biodiesel quality traits, rapid preparation of biodiesel samples and assessment of its quality is important. In this work, an in situ alkaline transesterification method was adopted for preparing canola biodiesel. It was found that the biodiesel yield via this method was improved by reducing seed moisture from 6.7% to 0% after oven-drying. The resulting biodiesel had qualities comparable to or better than biodiesel prepared through the conventional alkaline transesterification. Only a limited amount of seed from new canola lines is typically available in a plant breeding program; obtaining the required volume of biodiesel for evaluating cold soak filterability (300 mL) is not possible. In order to rapidly screen canola breeding lines for B 100 quality, cold soak filterability must be assessed with reduced volumes of biodiesel. Therefore, this study evaluated the impact of SMG, glycerin, and soap on cold soak filterability. Biodiesel filtration time rapidly increased to unacceptable levels and became much less reproducible when the SMG concentration was raised above 0.28%. A regression model was generated to predict the filterability of biodiesel against the concentrations of trace contaminants. A downscaled model of the filtration test with a reduced volume of biodiesel sample (25 mL) was also tested and calibrated. The in situ transesterification method saved 30% operator time compared with the conventional method. By combining the downscaled cold soak filtration test, the goal of analyzing 40 biodiesel samples/wk was achieved.
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.
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.
Using UAS Imagery and Computer Vision to Support Site-Specific Weed Control in Corn
(North Dakota State University, 2022) Sapkota, Ranjan
Currently, a blanket application of herbicides across the field without considering the spatial distribution of weeds is the most used method to control weeds in corn. Unmanned aerial systems (UASs) can provide high spatial resolution imagery, which can be used to map weeds across a field with a high spatial and temporal resolution during early growing season to support site-specific weed control (SSWC). The proposed approach assumes that plants growing outside the corn rows are weeds that need to be controlled. For that, we are proposing the use of “Pixel Intensity Projection” (PIP) algorithm for the detection of corn rows on UAS imagery. After being identified, corn rows were then removed from the imagery and the remaining vegetation fraction was assumed to be weeds. A weed prescription map based on the remaining vegetation fraction was created and implemented through a commercial sprayer field weed control.
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.
Using Prescription Maps for In Field Evaluation of Parameters Affecting Spraying Accuracy of a Self-Propelled Sprayer
(North Dakota State University, 2021) Mayer, John Christopher
Advanced sprayer control systems aim to improve accuracy and reduce waste in spray application. The objective of this study was to determine an optimum prescription map cell size/resolution that is compatible with current technology. A prescription map with several cell sizes was created and tested in field conditions to evaluate the effect different cell size parameters have on spray accuracy. The outcomes show that the dependent variable cell width had the greatest effect on application accuracy (p-values < 0.05), followed by cell length, and that an optimum cell width of 1.5 m [4.92 ft], a length of 3.05 m [10 ft], and application speed of 10.3 km h-1 [6.4 mph] is recommended. To further refine this analysis, the testing should be expanded with the inclusion of a variety of manufacturers and equipment and a test prescription map with a truly randomized cell distribution to better reflect actual field conditions.
Using UAS Images to Remotely Estimate Soil Moisture Content in the Red River Valley
(North Dakota State University, 2021) Mack, Talon Clancy
Accurate measurements of soil moisture in a timely manner are necessary in making critical management decisions, but it is often very difficult to obtain. Even though soil moisture can be measured on the ground using various methods, or estimated via satellite imagery, soil moisture conditions at a field scale can be more beneficial. Since Unmanned Aircraft System (UAS) technology has become an effective tool in many different ways for producers and researchers, the spatial and temporal gaps between the ground and the satellite approaches can be fulfilled with the use of UAS. In this study, multi-spectral images were collected over an agricultural field in the Red River Valley from an UAS platform. Using this data, the soil moisture content was calculated, and a soil moisture map was developed. The remotely sensed soil moisture was then compared to the in-situ field moisture measurements to gage the soil moisture mapping accuracy.
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.
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.
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.
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.
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.
Palmer Amaranth (Amaranthus palmeri S. Watson) Identification Using Hyperspectral Imaging Technology
(North Dakota State University, 2020) Barros da Costa, Cristiano Manuel
Palmer amaranth is a troublesome weed in modern day agriculture. Timely identification, along with adoption of site-specific weed management practices, will enable farmers to reduce Palmer amaranth control costs and improve efficacy. The feasibility of collecting hyperspectral imagery to identify Palmer amaranth and soybean was evaluated in the greenhouse and field. Hyperspectral images were collected across 224 spectral bands onPalmer amaranth and soybean twice weekly from the one to three-leaf growth stage in three different runs (28 replications per run) temporally separated in a greenhouse. Partial least squares-discriminant analysis and soft independent modelling of class analogy models were developed to identify Palmer amaranth and soybean plants and had cumulative variations of 60% and 85%, and predictive abilities of 60% and 82%, respectively. This study concluded that hyperspectral imaging could be a potential tool to decipher Palmer amaranth from soybean plants.
Process Benefits of Using Biomass Pellets in a Biorefinery
(North Dakota State University, 2019) Pandey, Ramsharan
Pelleted biomass can help simplify biomass supply systems and reduce downstream processing costs that are vital for the development of commercial biorefineries. This study is based on comparison of process benefits and economic factors of using loose and pelleted biomass over a range of low to high pretreatment severity and hydrolysis enzyme loadings. Use of pelleted biomass provides flexibility either to reduce pretreatment severity, enzyme loadings, hydrolysis time, or combinations of these. Either enzyme loadings can be reduced by 80% or hydrolysis times reduced by 58% with the use of pelleted biomass. A comparative techno-economic analysis using each form of biomass reveals that using pelleted biomass is economically beneficial. The minimum ethanol selling price for loose biomass was found to be $4.41/gal ethanol and $3.83/gal ethanol for pelleted biomass. The economic study suggests that optimizing conversion processes could lower the final ethanol costs even further.
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.
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.
Reference Evapotranspiration and Actual Evapotranspiration Measurements in Southeastern North Dakota
(North Dakota State University, 2011) Rijal, Ishara
Subsurface drainage (SSD) has been used to remove excess water from fields in the United States upper Midwest for more than a century, but only since the last decade in the Red River Basin of the North in North Dakota (ND). The water leaving from a SSD system can affect both the quality and quantity of water that flows to a surface water system. Therefore, determination of the water balance components is the first step to study the impact of SSD on water quantity, while evapotranspiration (ET), one of the most important components in the water balance, needs to be accurately measured for SSD field. A field experiment was conducted to study the water balance in SSD and undrained (having no artificial drainage system) fields in southeast ND. The field had three different water management systems: 22 ha undrained (UD), 11 ha subsurface drained, and the remaining 11 ha subsurface drained and subsurface irrigated. The ET rates were measured directly using an eddy covariance (EC) system for the SSD and UD fields. The changes in water table were monitored in 8 wells installed in both fields. Rainfall, SSD drainage volume, and soil moisture at six different depths at two locations were measured in both fields. The measurements were conducted in the growing seasons of 2009 and 2010. The ET rates were calculated for two different field crops: Com (Zea Mays) in 2009 and soybean (Glycine Max) in 2010. Crop coefficient (Kc) value was also developed using the ET measured by the EC system and the reference ET (ETref) estimated using the American Society of Civil Engineers Environmental and Water Resources Institute (ASCE-EWRI, alfalfa) method. The ETref was also estimated using the ASCE-EWRI grass and the Jensen Haise (JH) methods. The results indicated that the water table in the SSD field was lower during spring and fall than that in the UD field. The shallow water table and high soil moisture content in the spring and fall have resulted in higher ET rates in the UD field. In the summer, SSD field has favorable soil moisture at the root zone depth; the ET in the SSD field was 30% and 13% higher than that in UD field in summer 2009 and 2010, respectively. For the entire growing season, the ET in the SSD field was 15% higher compared to UD field and the difference was minimal in 2010. Though there were differences in the ET values, they were not statistically different. However, difference in magnitude of ET during summer 2009 yielded a statistical difference. During the peak growing season in July and August, the Kc values were greater in the SSD field due to healthy crops.
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.
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.
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.

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