ABEN Doctoral Work

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Advanced Evapotranspiration Measurement for Crop Water Management in the Red River Valley
(North Dakota State University, 2019) Niaghi, Ali Rashid
As the main component of terrestrial energy and water balance, evapotranspiration (ET) moves a large amount of water and energy in the form of latent heat flux from bare soil and vegetated surfaces into the atmosphere. Despite the development of many methods and equations through past decades, accurate ET estimation is still a challenging task, especially for the Red River Valley of the North (RRV) that has limited updated information on ET either for landscape or agricultural water management. The overall objective of first study was to evaluate the ASCE-EWRI reference ET (ETo) method by developing an accurate crop coefficient (Kc) using an eddy covariance (EC) system over an unirrigated turfgrass site. The results showed that with mean ETgrass/ETo ratio as 0.96 for the entire growing seasons of turfgrass, the ASCE-EWRI ETo method is valid for guiding the turfgrass irrigation management in cold climate conditions. In a Controlled drainage with subirrigation (CD+SI) field, an EC system was used to measure and quantify energy flux components along with soil water content (SWC) and water table depth (WTD) measurements during four corn growing. This study showed that the subsurface drainage along with the CD + SI system can be used for optimal water management with an improvement of 26.7% and 6.6% of corn yield during wet and dry year, respectively. For the final task, ET was measured using EC, Bowen ratio system (BREB), and soil water balance (SWB) method during the corn growing season. The comparison of the EC and the BREB system illustrated the advantages of using the residual method to close the energy balance closure of EC. Among the different time approaches for SWB method, ET by the SWB method using the average soil water contents between 24:00 to 2:00 time period showed non-significant differences (alpha = 0.05) compared to the BREB system during the observation periods.
Agricultural Field Applications of Digital Image Processing Using an Open Source ImageJ Platform
(North Dakota State University, 2019) Shajahan, Sunoj
Digital image processing is one of the potential technologies used in precision agriculture to gather information, such as seed emergence, plant health, and phenology from the digital images. Despite its potential, the rate of adoption is slow due to limited accessibility, unsuitability to specific issues, unaffordability, and high technical knowledge requirement from the clientele. Therefore, the development of open source image processing applications that are task-specific, easy-to-use, requiring fewer inputs, and rich with features will be beneficial to the users/farmers for adoption. The Fiji software, an open source free image processing ImageJ platform, was used in this application development study. A collection of four different agricultural field applications were selected to address the existing issues and develop image processing tools by applying novel approaches and simple mathematical principles. First, an automated application, using a digital image and “pixel-march” method, performed multiple radial measurements of sunflower floral components. At least 32 measurements for ray florets and eight for the disc were required statistically for accurate dimensions. Second, the color calibration of digital images addressed the light intensity variations of images using standard calibration chart and derived color calibration matrix from selected color patches. Calibration using just three-color patches: red, green, and blue was sufficient to obtain images of uniform intensity. Third, plant stand count and their spatial distribution from UAS images were determined with an accuracy of ≈96 %, through pixel-profile identification method and plant cluster segmentation. Fourth, the soybean phenological stages from the PhenoCam time-lapse imagery were analyzed and they matched with the manual visual observation. The green leaf index produced the minimum variations from its smoothed curve. The time of image capture and PhenoCam distances had significant effects on the vegetation indices analyzed. A simplified approach using kymograph was developed, which was quick and efficient for phenological observations. Based on the study, these tools can be equally applied to other scenarios, or new user-coded, user-friendly, image processing tools can be developed to address specific requirements. In conclusion, these successful results demonstrated the suitability and possibility of task-specific, open source, digital image processing tools development for agricultural field applications.
Application of Nanoparticles in Livestock Manure for Understanding Hydrogen Sulfide and Greenhouse Gas Reduction Mechanism
(North Dakota State University, 2018) Sarker, Niloy Chandra
The agricultural sector is one of the sources of greenhouse gases (GHGs) emission, especially methane (CH4), and contributing approximately 250 million metric ton carbon dioxide (CO2) equivalent emission per year. Almost 70% of CH4 emission from this sector is enteric fermentation, while 26% is from the livestock manure management. Both rumen and animal manure are the impending sources of carbon (C), sulfur (S), and water (H2O) and microbial populations utilize these constituents to produce GHGs, and hydrogen sulfide (H2S). Nanoparticles (NPs) application in manure is a promising treatment option for mitigating GHG and H2S gases, but limited information is available on how the reduction mechanism occurs. In this study, zinc silica nanogel (ZnSNL), copper silica nanogel (CuSNL), and nano acetyl cysteine (NACL) coated zinc oxide quantum dots (Qdots), zinc oxide (nZnO), and silver (nAg) NPs were tested in manure stored under anaerobic conditions to understand the reduction mechanism of GHG and H2S resulting from NPs application. Additionally, in vitro study with nZnO and two types of feed (alfalfa and corn silage) were conducted to investigate the efficacy of nZnO in mitigating ruminal gas emission. Methane and CO2 concentrations were measured using an SRI-8610 gas chromatograph and H2S was measured using a Jerome 631X meter. Microbial populations were characterized using both plate counts and quantitative real-time polymerase chain reaction (qRT-PCR). Application of NPs reduced gas volumes ranging 16 to 99%, and concentrations reduced by 49 to ~100% for H2S, and 20.24 to ~100% for GHGs. Application of NPs reduced 38.49 to 94.32% aerobic- and 7.43% to 82.04% anaerobic-microbial populations. Furthermore, the qRT-PCR analysis showed that reduction of gases was due to the inhibition of gas specific microbial population. Overall, nZnO based treatments reduced 8.80 to 55.64% methyl coenzyme M reductase (mcrA) gene copies and 0.74 to 25.16% dissimilatory sulfide reductase (DSR). Contrariwise, compared to the control treatment, in vitro study demonstrated 4.89 to 53.65% H2S and GHGs concentration reduction with the applied nZnO inclusion rates. Additionally, alfalfa as feed exhibited 37 to 45% cumulative gas reduction than corn silage but increased GHGs generation 2.17 to 23.17% and ~60% H2S concentration.
Design and Development of an Automatic Steering System for Agricultural Towed Implements
(North Dakota State University, 2022) Delavarpour, Nadia
While an auto steered tractor can improve the overall accuracy and efficiency of an operation, for operations that involve towing an implement, a significant portion of the efficiency reduction comes from uncontrolled motions of the towed implement. Therefore, there is a crucial need to study auto steering system for towed implement as well. In this study different requirements of an auto steering system for a towed implement were developed and studied. In this study the guiding performance of two local positioning sensors (Tactile and Ultrasonic sensors) under similar conditions were studied for reading different trajectories at different traveling speed. Furthermore, a fuzzy logic control algorithm was developed to continually generate correction steering signals and keep the tractor and towed implement within a certain boundary of the reference trajectory. Finally, the designed controller was implemented in a hardware-in-loop (HIL) system to analyze the performance of the controller in real world conditions. The result of this study showed that although the local guidance sensors could locate the tractor or towed implement positions with respect to plant rows accurately, limitations to the performance of sensors were also observed in certain conditions. Sensors were prone to various noises and digital filters were required to apply to collected data. Data analysis showed that at lower speeds (less than 1.79 m/s) the accuracy of sensors was ±2 cm or better. The fuzzy logic controller improved the trajectory tracking accuracy at slow speeds (1-5 m/s) for following non-complex trajectories while no major improvements were achieved for complex trajectories at these speeds. Therefore, the controller had an acceptable accuracy following straight trajectory with negligible deviations at slow speeds. Moreover, experimental results showed that the hydraulic cylinder followed the controller signals with sufficient accuracy. During the experiment the angular displacements remained in the range of ±10˚ and never hit the constraint of maximum achievable angle, which was ±30˚. The satisfactory results showed that the designed automatic steering control system has a good tracking performance with a fast response, thus meeting the navigation control requirement of agricultural equipment to a certain extent.
Effects of Calcium Based Surface Amendments on Hydraulic Conductivity and Selected Physical Properties of Subsurface Drained Sodic Soils
(North Dakota State University, 2016) Wamono, Anthony Walekhwa
Managing excess soil water in agricultural fields in the Northern Great Plains through subsurface drainage increases the risk of sodification in high-risk soils. Leaching sodic soils with low electrical conductivity (EC) water, rainfall, may result in the swelling of soil, dispersion of clay particles and consequently the breakdown of soil structure leading to changes in physical and mechanical properties of soils (e.g., reduced infiltration, hard-setting and reduced trafficability). In this dissertation, the effectiveness of calcium amendments of gypsum and spent lime, a byproduct of the processing sugar beets, with water-management treatments of free drainage (FD) and no drainage (ND) on improving physical properties of the soil were examined. The first objective was to evaluate the effects of drainage and surface treatments on the penetration resistance (PR). The second objective was to use infiltration tests with a mini-disk tension infiltrometer and a Cornell sprinkle infiltrometer to investigate changes in hydraulic properties. Lastly, a drawbar dynamometer was used to measure draft on a chisel plow as it was pulled across the plots by a tractor equipped with an auto-guidance system and instrumentation interfaced with the controller area network of the tractor. The results show that the PR values of plots with gypsum application at high rate of 22.4 Mg ha-1 (GH) were significantly higher than other surface amendments. GH increased the hydraulic conductivity of the soil matrix compared to spent lime application at rate of 22.4 Mg ha-1 (SL); however, the overall flow of water through the soil profile, including the soil matrix and the macropores, was not affected. Both GH and gypsum application at high rate of 11.2 Mg ha-1 (GL) lowered the drawbar power requirements compared to spent lime application. For many farmers, drainage enables early planting and the adding of ameliorants will safeguard against further sodification of their fields.
Evaluation of Different Techniques to Control Hydrogen Sulfide and Greenhouse Gases from Animal Production Systems
(North Dakota State University, 2015) Gautam, Dhan Prasad
The livestock manure management sector is one of the prime sources for the emission of greenhouse gases (GHGs) and other pollutant gases such as ammonia (NH3) and hydrogen sulfide (H2S), which may affect the human health, animal welfare, and the environment. So, worldwide investigations are going on to mitigate these gaseous emissions. The overall objective of this research was to investigate different approaches (dietary manipulation and nanotechnology) for mitigating the gaseous emissions from livestock manure system. A field study was conducted to investigate the effect of different levels of dietary proteins (12 and 16%) and fat levels (3 to 5.5%) fed to beef cattle on gaseous emission (methane-CH4, nitrous oxide-N2O, carbon dioxide-CO2 and hydrogen sulfide-H2S) from the pen surface. To evaluate the effects of different nanoparticles (zinc oxide-nZnO; and zirconium-nZrO2) on these gaseous emissions from livestock manure stored under anaerobic conditions, laboratory studies were conducted with different treatments (control, bare NPs, NPs entrapped alginate beads applying freely and keeping in bags, and used NPs entrapped alginate beads). Field studies showed no significant differences in the GHG and H2S emissions from the manure pen surface. Between nZnO and nZrO2, nZnO outperformed the nZrO2 in terms of gases production and concentration reduction from both swine and dairy liquid manure. Application of nZnO at a rate of 3 g L-1 showed up to 82, 78, 40 and 99% reduction on total gas production, CH4, CO2 and H2S concentrations, respectively. The effectiveness of nZnO entrapped alginate (alginate-nZnO) beads was statistically lower than the bare nZnO, but both of them were very effective in reducing gas production and concentrations. These gaseous reductions were likely due to combination of microbial inhibition of microorganisms and chemical conversion during the treatment, which was confirmed by microbial plate count, SEM-EDS, and XPS analysis. However, further research are needed to understand the reduction mechanism and to transfer the technology in a real life application.
Hull Fiber from DDGS and Corn Grain as Alternative Fillers in Polymer Composites with High Density Polyethylene
(North Dakota State University, 2018) Pandey, Pankaj
The steady increase in corn based ethanol production has resulted in a dramatic rise in the supply of its co-product known as distillers’ dried grain with solubles (DDGS). Currently, the main outlet for DDGS is the animal feed industry, but the presence of fibers makes them indigestible by non-ruminants such as swine and poultry. Separation of fiber from DDGS would increase the nutritional value of DDGS with higher protein and fat contents and reduced fiber content. The fiber from DDGS can be separated through a physical separation process known as elusieve. The DDGS fiber has the potential to be used as a fiber filler in thermoplastic composites. This research project evaluates DDGS fiber as a filler in thermoplastic composites. The fibers from corn hull and DDGS have been used as fillers at 30% and 50% fiber loading in high density polyethylene (HDPE) composites and compared against a standard oak fiber filler composites at a lab scale. DDGS and corn fiber composites showed comparable mechanical properties as the oak wood fiber HDPE composites. Further evaluation was completed on the performance of composite samples at commercial scale with six combinations of oak fiber, corn hull fiber and DDGS fiber with fiber loading maintained at 50%, and then samples were exposed to UV accelerated weathering for 2000 h. The UV weathering decreased the mechanical properties of all the exposed samples compared to the unexposed samples. Also, UV weathering resulted in a severe chain scission of the HDPE polymer, increasing their crystallinity. The performance of mercerized or sodium hydroxide (NaOH) treated DDGS fiber as filler was investigated by characterizing the effects of treated and untreated DDGS fibers on physical, mechanical, and thermal properties of HDPE composites. The NaOH treated DDGS fiber at 25% loading showed consistent improvement in flexural and tensile modulus of elasticities of the composites compared to the neat HDPE.
Identification of Weed Species and Glyphosate-Resistant Weeds Using High Resolution UAS Images
(North Dakota State University, 2018) Shirzadifar, Alimohammad
Adoption of a Site-Specific Weed Management System (SSWMS) can contribute to sustainable agriculture. Weed mapping is a crucial step in SSWMS, leads to saving herbicides and protecting environment by preventing repeated chemical applications. In this study, the feasibility of visible and near infrared spectroscopy to classify three problematic weed species and to identify glyphosate-resistant weeds was evaluated. The canopy temperature was also employed to identify the glyphosate-resistant weeds. Furthermore, the ability of UAS imagery to develop accurate weed map in early growing season was evaluated. A greenhouse experiment was conducted to classify waterhemp (Amaranthus rudis), kochia (Kochia scoparia), and lambsquartes (Chenopodium album) based on spectral signature. The Soft Independent Modeling of Class Analogy (SIMCA) method on NIR (920-2500 nm) and Vis/NIR (400-2500 nm) regions classified three different weed species with accuracy greater than 90 %. The discrimination power of different wavelengths indicated that 640, 676, and 730 nm from red and red-edge region, and 1078, 1435, 1490, and 1615 nm from the NIR region was the best wavelengths for weed species discrimination. While, wave 460, 490, 520 and 670 nm from Vis range, and 760, 790 nm from NIR region were the significant discriminative features for identifying glyphosate-resistant weeds. Random Forest was able to detect glyphosate-resistant weeds based on spectral weed indices with more than 95% accuracy. Analysis of thermal images indicated that the canopy temperature of glyphosate-resistant weeds was less than susceptible ones early after herbicide application. The test set validation results showed the support vector machine method could classify resistant weed species with accuracy greater than 95 %. Based on the stepwise method the best times for discrimination of kochia, and waterhemp resistant were 46 and 95 hours after glyphosate application, respectively. In addition, a field study was proposed on soybean field to identify weed species and glyphosate-resistant weeds using multispectral and thermal imagery. Results revealed that the object-based supervised classification method could classify weed species with greater than 90% accuracy in early growing season. Furthermore, the glyphosate-resistant kochia, waterhemp and ragweed were identified based on canopy temperature with 88%, 93% and 92% accuracy, respectively.
Optimization of Methane Yield in Solid-State Anaerobic Co-Digestion of Dairy Manure and Corn Stover
(North Dakota State University, 2020) Ajayi-banji, Ademola
Sole dependence on fossil fuel and the concomitant environmental concerns could be minimized through the optimization of green energy generation from the growing volume of onfarm organic wastes. In this mesophilic study, green energy, mainly methane, was optimized through the solid-state anerobic co-digestion (SSAD) of two on-farm organic wastes (dairy manure with corn stover). Factors considered to achieve the improved methane yield under a total solids of 16% were particle size of corn stover (0.18 – 0.42 and 0.42 – 0.84 mm), alkaline pretreatment type (thermo-chemical and wet state), alkaline-pretreatment reagent (NaOH, NH4OH, and Ca(OH)2) used for the corn stover, and the magnetite nanoparticles(20, 50, and 75 mg/L) thereafter added to the treatment with highest methane yield. Kinetic models were used to describe some of the high methane yield as well as the environmental impact investigated with life cycle assessment. Results indicated that corn stover with particle size 0.42 - 0.84 mm blended with dairy manure under a C/N of 24 had the highest methane yield (106 L/ kgVS) under 60 days retention time. After pretreatment of the 0.42 - 0.84 mm corn stover with the three different alkaline reagents, methane yield improved under this wet state pretreatment relative to thermochemical. For instance, calcium pretreated corn stover blended with dairy manure (CaW) had the highest methane yield (176 L / kgVS) under a reduced retention time (79 days), overcame potential volatile fatty acids accumulation and digester upset relative to other pretreated treatments. Furthermore, addition of 20 mg of the nanoparticles to the CaW treatment further enhanced methane yield (191 L / kg VS), minimized digester upset, and reduced retention time to 52 days. Suitable process parameters for methanogenic activities were 0.1 - 0.5 for VFA/Ammonia and VFA/Alkalinity ratios. Free ammonia concentration between 258 – 347 mg/L does not affect methanogenic activities. Environmnetal impact aseessment indicated that pretreatment negatively influenced human health factors and eutrophication potentials though reduced ozone depletion, global warming potential, and smog potentials. The solid-state of dairy manure co-digested with corn stover has the potential to improve green energy generation that could complement fossil fuel and address waste management challenges.
Pilot Scale Production, Characterization, and Optimization of Epoxidized Vegetable Oil-Based Resin
(North Dakota State University, 2015) Monono, Ewumbua Menyoli
Novel epoxidized sucrose soyate (ESS) resins perform much better than other vegetable oil-based resins; thus, they are of current interest for commercial scale production and for a wide range of applications in coatings and polymeric materials. However, no work has been published that successfully scaled-up the reaction above a 1 kg batch size. To achieve this goal, canola oil was first epoxidized at a 300 g scale to study the epoxidation rate and thermal profile at different hydrogen peroxide (H2O2) addition rates, bath temperatures, and reaction times. At least 83% conversion of double bonds to oxirane was achieved by 2.5 h, and the reaction temperature was 8-15 oC higher than the water bath temperature within the first 30-40 min of epoxidation. A 38 L stainless steel kettle was modified as a reactor to produce 10 kg of ESS. Twenty 7-10 kg batches of ESS were produced with an overall 87.5% resin yield and > 98% conversion after batch three. The conversion and resin quality were consistent across the batches due to the modifications on the reaction that improved mixing and reaction temperature control within 55-65 oC. The total production time was reduced from 8 to 4 days due to the fabrication of a 40 L separatory funnel for both washing and filtration. A math model was developed to optimize the epoxidation process. This was done by using the Box-Behnken design to model the conversion at various acetic acid, H2O2, and Amberlite ratios and at various reaction temperatures and times. The model had an adjusted R2 of 97.6% and predicted R2 of 96.8%. The model showed that reagent amounts and time can be reduced by 18% without compromising the desired conversion value and quality.
Process Development for Effective, Recoverable and Reusable Magnetic Nanobiocatalysts for Biomass Hydrolysis
(North Dakota State University, 2021) Hammed, Ademola Monsur
Recovery and reuse of enzymes can reduce the high enzyme costs that are challenging for cellulosic biorefineries. Attaching enzymes to magnetic nanoparticles to make magnetic nanobiocatalysts (MNBCs) can facilitate enzyme recovery and reuse. One approach for MNBC synthesis is by attaching enzymes to flexible polymer molecules to form polymer-enzyme conjugates (PECs) which in turn can be attached to superparamagnetic iron-oxide nanoparticles (SPIONs). However, this approach can be complex and unscalable. The research objective is to develop a scalable process to produce effective, recoverable and reusable cellulolytic MNBCs. PECs were produced and tested before incorporation into MNBCs in order to test efficacy and reusability. The effects of different biomass pretreatment methods, temperature, pH and solid loading on PEC efficacy were determined. Hydrolysis conditions affect PEC and free enzyme (FE) efficacy equally suggesting that attachment to the polymer did not interfere with substrate-enzyme interaction. PEC has higher efficacy than FE at higher substrate loading offering potential for processing more substrate per batch. The recovered PECs were effective for subsequent hydrolysis and reduced enzyme requirement to 40% of free enzyme needed in the first stage. A tubular electrochemical system (TES), an electrochemical reactor containing electrolytes flowing through a cathode tube with an inner anode rod, was developed to overcome scalability and sustainability challenges of SPION synthesis. The effects of current density, electrolyte concentration, electrolyte feeding strategy, and flow rate on TES productivity and SPION characteristics were determined. TES productivity and SPION characteristics were both affected by the reaction conditions. Increasing electrolyte flow rate caused a decrease in average SPION size and size-distribution. The flow rate can be used to control SPION size distribution and shape. Gradual addition of more electrolyte resulted in 75% increase in SPION yield. Silica coating of SPIONs improves SPION longevity and adsorption capacity. A single-step process for silica-coated SPION (Si-SPION) synthesis using TES was developed. The coating agent (Na2SiO3) concentration did not affect Si-SPION morphology, but increasing Na2SiO3 concentration reduces SPION productivity. The Si-SPIONs did not dissolve in an acidic environment for 48 h and were suitable support for MNBC synthesis. The MNBCs were recovered and reused four times.
Quality Evaluation of Coated Extra-Large Hulled Sunflower (Helianthus Annuus) Kernels for Precision Planting
(North Dakota State University, 2018) Sidhu, Harjot
Domestic and export demand for extra-large (XL) in-shell confectionary sunflower seeds (Helianthus Annuus) growing; however, a significant proportion of the hybrid seed for planting goes to the snack food market because the extra-large seed is not acceptable to farmers. The extra-large hybrid seed has poor emergence in the field and is not compatible with precision planters. Therefore, the option of coating the hulled sunflower kernels for improved germination and plantability is investigated in this dissertation. Twenty types of kernel coatings have been tested, through collaboration with five seed coating companies and development of our own in-house seed coating capabilities. Coated kernels were tested for germination, seedling vigor, and other indicators of kernel viability. Coated kernels were also tested for plantability using a precision planter test stand. The top-performing coated kernels achieved singulation and post-singulation germination comparable to large planting seed used by farmers. A field trial was conducted in 2017 at Prosper, ND with eight types of coated kernel treatments having zeolite, lime, Polymer A, and Polymer B In-house coating materials each at 30% and 35% build-up levels. Coated kernels produced grain yields up to 55% greater than from XL seeds, and up to 25% greater than large seeds. Live seed emergence of all the coated kernels (93 – 99%) was significantly higher than the XL seeds (88%) and similar or higher than the large seeds (94%). Another small-scale field trial was conducted at Minot, ND, where moisture stressed conditions were observed. Coated kernels showed similar trends to the Prosper location both in terms of live seed emergence and grain yield as compared to XL seeds. Further, an automated image processing method was developed form the RGB images taken with an unmanned aerial vehicle which predicted the emergence counts and a number of multiples in every row of the sunflower field trial at Prosper with R2 of 0.94 and 0.92. Overall, coated kernels showed significant improvements in achieving plant stand uniformity compared to XL seeds.
Rangeland Forage Growth Prediction, Logistics, Energy, and Economics Analysis and Tool Development Using Open-Source Software
(North Dakota State University, 2022) Navaneetha Srinivasagan, Subhashree
Forage availability was crucial for livestock production across the United States. Rangelands occupied vast areas 31 % of land and were the primary source of forage for livestock. However, extreme climatic conditions such as drought affect rangeland forage production and pose a serious threat to the rangeland enterprise. This increases the need to monitor forage in vast rangelands and adapt to other measures such as cultivating or buying forage to balance demand and supply. Despite this need, resources (studies and tools) on rangeland forage monitoring and existing forage production, handling, and economics were scattered and scarce. Therefore, a comprehensive systematic literature review was performed to gather the current understanding of the technology and resources used for monitoring and economics of forage production. Remote sensing technologies were widely used in recent research for their ability to scout vast areas frequently and machine learning (ML) in successfully comprehending complex relationships. Forage production economics was predominantly available for alfalfa forage crop, but other crops and bale collection logistics during production were ignored. Bale collection using conventional tractor carrying 1 and 2 bales/trip (BPT) and automatic bale picker (8-23 BPT) was simulated mathematically and analyzed with open-source R software using realistic equipment turning scenarios. Fuel consumption based on aggregation distance for ABP decreased on average by 72 % and 53 % compared to the tractor with 1 and 2 BPT. A web-based calculator tool was developed using open-source HTML, CSS, and JavaScript software for forage economic analysis including more than 10 varieties of forage crops involving the economics of bale collection (tractor and ABP). Pasture biomass yield prediction was performed with R software using vegetation index (VI) and climate data through ML approaches. Recursive feature selection (RFE) and random forest (RF) model for forage yield emerged as the best methodology based on accuracy. A web-based interactive tool was developed using the Shiny package in R to accommodate “field-specific,” pasture-scale inputs for predicting biomass yield. In conclusion, these successful results demonstrate the possibility of using open-source software for simulating logistics, developing models, and building tools for forage monitoring and analyzing the economics of forage production.
Snowmelt Water Infiltration into Frozen Soil in Red River of the North Basin
(North Dakota State University, 2018) Roy, Debjit
Infiltration into frozen soils is an important process in the hydrological cycle. Though infiltration occurs at the soil surface, it is affected by many factors, e.g. soil water content, temperature, and hydraulic conductivity. Understanding the snowmelt water infiltration processes into frozen soil helps to address issues about runoff generation and spring flooding in seasonally frozen area like Red River of the North basin (RRB). In this study, the methods of soil water release curve (SWRC) development, the effect of soil water content on frozen soil infiltration, and the variation of hydraulic conductivity for different RRB soils in frozen and unfrozen conditions were examined and evaluated. The objectives of this study were: (1) to construct SWRC using combined HYPROP and WP4 method, (2) to evaluate the soil water and temperature effects on the infiltration into frozen soil, and (3) to compare predicted hydraulic conductivity of three frozen soils of RRB with measured values using minidisk infiltrometer. It was found that HYPROP+WP4 combined method produced acceptable SWRC of RRB soils compared to other available traditional methods. However, shrinking and swelling of clay content of the soils might cause difference with in-situ measurement. Infiltration into frozen soil depended on initial soil water contents. The drier the frozen soil, the higher the infiltration rate. Soil water content changed gradually with rising temperature in a dry soil but in a frozen wet soil, it was very rapid due to the phase changing of water. The Horton infiltration model was fitted with measured frozen soil infiltration data with good agreement. Hydraulic conductivity of frozen soils decreased with an increase in soil water contents, but it was also subjected to sand and clay contents of the soil. Simple nonlinear regression model fitted with measured data and resulted reasonable agreement compared to Motivilov model. Freeze-thaw cycles altered the soil pore distribution, decreased the infiltration rate and hydraulic conductivity of frozen soils.
Soybean Leaf Chlorophyll Estimation and Iron Deficiency Field Rating Determination at Plot and Field Scales Through Image Processing and Machine Learning
(North Dakota State University, 2020) Hassanijalilian, Oveis
Iron deficiency chlorosis (IDC) is the most common reason for chlorosis in soybean (Glycine max (L.) Merrill) and causes an average yield loss of 120 million dollars per year across 1.8 million ha in the North Central US alone. As the most effective way to avoid IDC is the use of tolerant cultivars, they are visually rated for IDC by experts; however, this method is subjective and not feasible for a larger scale. An alternate more objective image processing method can be implemented in various platforms and fields. This approach relies on a color vegetation index (CVI) that can quantify chlorophyll, as chlorophyll content is a good IDC indicator. Therefore, this research is aimed at developing image processing methods at leaf, plot, and field scales with machine learning methods for chlorophyll and IDC measurement. This study also reviewed and synthesized the IDC measurement and management methods. Smartphone digital images with machine learning models successfully estimated the chlorophyll content of soybean leaves infield. Dark green color index (DGCI) was the best-correlated CVI with chlorophyll. The pixel count of four different ranges of DGCI (RPC) was used as input features for different models, and the support vector machine produced the highest performance. Handheld camera images of soybean plots extracted DGCI, which mimicked visual rating, and canopy size that were used as inputs to decision-tree based models for IDC classification. The AdaBoost model was the best model in classifying IDC severity. Unmanned aerial vehicle soybean IDC cultivar trial fields images extracted DGCI, canopy size, and their product (CDP) for IDC severity monitoring and yield prediction. The area under the curve (AUC) was employed to aggregate the data into a single value through time, and the correlation between all the features and yield was good. Although CDP at latest growth stage had the highest correlation with yield, AUC of CDP was the most consistent index for soybean yield prediction. This research demonstrated that digital image processing along with the machine learning methods can be successfully applied to the soybean IDC measurement and the various soybean related stakeholders can benefit from this research.
Sugarbeet Model Development for Soil and Water Quality Assessment
(North Dakota State University, 2018) Anar, Mohammad Jahidul
Sugarbeet (Beta vulgaris) is considered as one of the most viable alternatives to corn for biofuel production as it may be qualified as “advanced” biofuel feedstocks under the ‘EISA 2007’. Production of deep rooted sugarbeet may play a significant role in enhancing utilization of deeper layer soil water and nutrients, and thus may significantly affect soil health and water quality through recycling of water and nutrients. A model can be useful in predicting the sugarbeet growth, and its effect on soil and water quality. A sugarbeet model was developed by adopting and modifying the Crop Environment and Resource Synthesis-Beet (CERES-Beet) model. It was linked to the Cropping System Model (CSM) of the Decision Support System for Agrotechnology (DSSAT) and was termed as CSM-CERES-Beet. The CSM-CERES-Beet model was then linked to the plant growth module of the Root Zone Water Quality Model (RZWQM2) to simulate crop growth, soil water and NO3-N transport in crop fields. For both DSSAT and RZWQM2, parameter estimation (PEST) software was used for model calibration, evaluation, predictive uncertainty analysis, sensitivity, and identifiability. The DSSAT model was evaluated with two sets of experimental data collected in two different regions and under different environmental conditions, one in Bucharest, Romania and the other in Carrington, ND, USA, while RZWQM2 was evaluated for only Carrington, ND experimental data. Both DSSAT and RZWQM2 performed well in simulating leaf area index, leaf or top weight, and root weight for the datasets used (d-statistic = 0.783-0.993, rRMSE = 0.006-1.014). RZWQM2 was also used to evaluate soil water and NO3-N contents and did well (d-statistic = 0.709-0.992, rRMSE = 0.066-1.211). The RZWQM2 was applied for simulating the effects of crop rotation and tillage operations on sugarbeet production. Hypothetical crop rotation and tillage operation scenarios identified wheat as the most suitable previous year crop for sugarbeet and moldboard plow as the most suitable tillage operation method. Both DSSAT and RZWQM2 enhanced with CSM-CERES-Beet may be used to simulate sugarbeet production under different management scenarios for different soils and under different climatic conditions in the Red River Valley.
Technical and Economic Assessments of Storage Techniques for Long-term Retention of Industrial-beet Sugar for Non-food Industrial Fermentations
(North Dakota State University, 2015) Vargas-Ramirez, Juan Manuel
Industrial beets may compete against corn grain as an important source of sugars for non-food industrial fermentations. However, dependable and energy-efficient systems for beet sugar storage and processing are necessary to help establish industrial beets as a viable sugar feedstock. Therefore, technical and economic aspects of beet sugar storage and processing were evaluated. First, sugar retention was evaluated in whole beets treated externally with either one of two antimicrobials or a senescence inhibitor and stored for 36 wk at different temperature and atmosphere combinations. Although surface treatment did not improve sugar retention, full retention was enabled by beet dehydration caused by ambient air at 25 °C and with a relative humidity of 37%. This insight led to the evaluation of sugar retention in ground-beet tissue ensiled for 8 wk at different combinations of acidic pH, moisture content (MC), and sugar:solids. Some combinations of pH ≤ 4.0 and MC ≤ 67.5% enabled retentions of at least 90%. Yeast fermentability was also evaluated in non-purified beet juice acidified to enable long-term storage and partially neutralized before fermentation. None of the salts synthesized through juice acidification and partial neutralization inhibited yeast fermentation at the levels evaluated in that work. Conversely, yeast fermentation rates significantly improved in the presence of ammonium salts, which appeared to compensate for nitrogen deficiencies. Capital and operating costs for production and storage of concentrated beet juice for an ethanol plant with a production capacity of 76 × 106 L y-1 were estimated on a dry-sugar basis as U.S. ¢34.0 kg-1 and ¢2.2 kg-1, respectively. Storage and processing techniques evaluated thus far prove that industrial beets are a technically-feasible sugar feedstock for ethanol production.
Treatment of Industrial Wastewater Derived Organic Pollutants Using Electrochemical Methods Through Optimization of Operation Parameters.
(North Dakota State University, 2019) Sharma, Swati
Industrial operations produce a notable amount of wastewaters with high concentration of chemical oxygen demand (COD), mostly consisting of organic carbon compounds. The treatment performance of electrochemical methods for organic removal and the effects of process parameters are the subject of this research. Three research tasks were performed. The first task was the removal of organic pollutants from three different industrial wastewaters using two different electrochemical methods; combined electrocoagulation + electrooxidation (EC+EO) and b) electrochemical peroxidation (ECP). Using only EC process was found to be significantly successful in removing suspended and colloidal pollutants and could remove more than 90% COD and 80% of TOC. The study showed that combined EC+EO process had better removal capability compared to ECP when operated under similar process conditions. The second task was to study the effect of the process parameters; pH, H2O2 dosage, current density, and operation time; and to optimize and estimate the best treatment conditions for the methods using Box-Behnken Design (BBD). For sugar beet wastewater, the results showed that EO could remove 75% of organics at optimum conditions of pH 5.3; current density of 48.5 mA/cm2; and operation time of 393 min. The canola oil refinery wastewater achieved more than 90% pollutant removal when the conditions were optimized at pH 5.8 – 6 with applied current density of 9.2 mA cm-2¬ run for nearly 300 min. The rate of degradation of the wastewater derived organic pollutants followed a first order kinetics for all the wastewaters investigated and the models were validated for goodness of fit with high R2. The final task was to compare treatment efficiency between the electrochemical processes. Based on the energy consumed and the performance efficiency to remove COD, sCOD, TOC and DOC in the three different wastewaters studied, EC+EO process was found suitable for the treatment of canola and sunflower oil wastewater. On the other hand, from the model prediction and the experiments conducted, EO resulted in better removal capability compared to ECP. Also, the consumption of energy by ECP was comparatively higher than EO process while taking longer time of operation for significant removal.
Vegetative Filter Strip: A Best Management Practice (Bmp) for Feedlot Runoff Pollution Control in North Dakota
(North Dakota State University, 2013) Rahman, Md. Atikur
Runoff from animal feeding operations is a major source of water pollution. Vegetative filter strips (VFS) are effective ways to reduce nonpoint source pollution. In this study, vegetative filter strips with different designs and in climatic and management conditions of North Dakota were evaluated. Runoff samples were collected from inflow (before entering VFS) and outflow (after exiting the VFS) locations using automatic samplers. Collected samples were analyzed for solids and nutrients. It was observed that the transport reductions by VFS were ranged from very low to up to 100%. However, soluble nutrients were not as effectively removed as sediment and sediment bound nutrients. Filter with longer length was more effective in reducing transport of sediments and nutrients. Antecedent soil moisture condition had an important effect on VFS performance. An attempt was made by varying the VFS soil pH in a broader range to investigate effect of pH on reducing transport of soluble nutrients from manure borne runoff. Soil was treated with calcium carbonate to adjust pH at different levels. Treated soil was packed into galvanized iron boxes and seeded with grasses to simulate vegetative filter strips. Runoff experiments were conducted with manure solution and inflow, outflow, and leachate samples were collected. Samples were analyzed for sediment and nutrients. It was observed that the soluble nutrients transport was influenced by the pH, and higher ortho-P transport reduction was observed in higher pH. Leaching of NO3-N at higher pH was observed, indicating potential of groundwater pollution from the soil with higher pH. Using calcium carbonate to increase soil pH and thereby reducing transport of soluble nutrient could increase VFS performance. To aid VFS design and evaluation, a model was developed to predict trapping efficiency of sediment, sediment bound P, and dissolved P from VFS. Two procedures were coded into FORTRAN and added into existing VFSMOD model. The model was calibrated and validated using field data. Due to limited data points and difficulties in measuring runoff volume, the model appeared to be under or over predicting. In future, model predictability can be improved by accurately measuring runoff volume and carefully selecting input parameters.

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Browsing ABEN Doctoral Work by browse.metadata.program "Agricultural and Biosystems Engineering"