Accurate flow measurement is required to effectively manage water resources. California Senate Bill X7-7 (SB X7-7), legislates this need by requiring agricultural water providers serving areas greater than 25,000 acres to develop an Agricultural Water Management Plan (AWMP) and adopt pricing based at least partly on volumetric water deliveries (DWR, 2009). This study focused on two of the most common flow measurement/flow control devices used in California open channel water conveyance systems: the circular meter gate and the rectangular meter gate. Testing was conducted on three Armco-type (round gates over round discharge pipe) gates measuring 12”, 18”, and 24” and two rectangular gates (rectangular gates over round discharge pipe) measuring 18” and 24”. The three round gates used in the study were the Model 101C produced and provided by Fresno Valve and Castings Incorporated. The two rectangular meter gates were manufactured by Mechanical Associates located in Visalia, California and provided by the San Luis Canal Company located in Dos Palos, California. Testing was conducted in an outdoor laboratory setting at the Irrigation Training and Research Center’s (ITRC) Water Resources Facility at the California Polytechnic State University in San Luis Obispo, California under a variety of flow conditions as experienced in the field in order to: 1) evaluate the effectiveness of these gates as flow measurement devices and determine whether they meet the volumetric accuracy requirements outlined in SB X7-7, 2) develop standards for installation and use that improve flow measurement accuracy, 3) configure more accurate gate rating tables based on updated coefficient of discharge values, and 4) determine if additional gate rating tables are needed for “high” supply channel velocities. The meter gate was set perpendicular to the supply channel. Baseline data was first collected through testing with low supply channel water velocities. Additional testing was then conducted with high supply channel water velocities to analyze the effect on the coefficient of discharge. Based on previous studies it was hypothesized that as the Froude number (FR#) in the supply channel increased (water approach velocity increased), the coefficient of discharge would decrease as a result of an increase in energy needed for the perpendicular velocity transition. Data evaluation, however, indicated no statistically significant effect of water approach velocity on the coefficient of discharge for the 12”, 18” and 24” circular gates or the 18” and 24” rectangular gates at an α-level = 0.01. When operating the gates under recommended conditions relative flow uncertainty was within +/- 5%. This meets the accuracy requirements set by SB X7-7 for turnout flow measurement devices. Based on the results of this study, Cd values do not need to be adjusted for Froude numbers up to 0.35 for any of the studied gates. It should be noted, however, that while most meter gates used will be in conditions where supply channel Froude numbers do not exceed 0.35, further research is needed to study potential effects from Froude numbers exceeding the range found in this study.

Plastic contamination in cotton is a problem in cotton industry and researchers have worked on this problem with different approaches. This thesis documents the design of mechanical and electronic real-time systems for detecting and removing plastic contaminants. The mechanical system was designed to expose plastic embedded inside the seed cotton to the sensor and to separate plastic contaminated cotton from the process stream. The detection system consisted of an embedded computer interfaced with a USB camera and Neural Network (NN) software running in it. Two NN models were tested, a transfer learning model and a built-from-scratch original model. The original NN model had better performance and accuracy than the transfer learning model. An accuracy 95% was achieved for classifying images containing plastic or not containing plastic with an original model. The plastic removal rate of the overall machine was 68%.

Cotton is harvested with large and heavy machines that are very efficient but have some disadvantages. They can harvest the crop only once at the end of the growing season. Since cotton bolls do not mature uniformly, the early opened bolls expose their fiber to weather for extended periods, reducing lint quality. In addition, the machines can also compact the soil, reducing water and fertilizer usage efficiencies and crop yields in the following years. Robotic cotton harvesting offers a promising solution to these issues. Smaller robotic harvesters could go to the field multiple times during the season to pick cotton bolls as soon as they open. Such harvesters could be lightweight, minimizing the risk of soil compaction. This dissertation research includes designing an end-effector for robotic cotton harvesting, designing a robotic platform and integrating the custom-designed end-effector, and developing multiple manipulation control algorithms. The robotic platform has a 3-DOF (degrees of freedom) manipulator and a ZED 2i stereo camera. The robot was tested under lab and field conditions to evaluate its performance in object detection, localization, and picking. The tests proved that manipulating the arm while picking a boll increased the picking ratio – the weight of the picked seed cotton over the whole weight of the seed cotton that the robot attempted to pick – by up to 23%. However, it increased the cycle time. Therefore, the control algorithm was improved to a closed-loop system to touch just the unpicked areas of a boll. The best control algorithm, i.e., I-FMW (improved-feedback-based manipulation while picking), could achieve a 72.0% picking ratio with a cycle time of 8.8 s during lab tests. The field tests were conducted to find the contribution of three main systems (detection, localization, and picking) to the losses. The tests showed that detection, localization, and picking subsystems could achieve performance of 78.1%, 70.0%, and 83.1% respectively. Therefore, detection and localization systems must be improved. Utilizing better sensors, modifying detection and localization algorithms, adding the boll orientation information, and controlling illumination conditions as much as possible would improve the picking performance and make the robot a step closer to a commercial product.

The organism Clostridium thermocellum grows on cellulosic substrates and produces ethanol, acetate, lactate, formic acid, and CO2. The organic acids produced alter the growth environment in which the bacteria grows and ultimately inhibit bacterial growth. One method which has been used successfully to maintain the system at acceptable growth conditions is to intermittently flush out the spent media and metabolic products and replace with new fermentation media. Our goal was to design and build an automated system that will automatically flush the spent media from the growing culture and resupply new media without manual intervention. An automated control system was designed and built to control growth parameters. Heated water was pumped through the jacket of each culture vessel and used to regulate the reactor temperature. Sensors for pH and temperature were connected to a central data acquisition system and NI LabVIEW software was used to control each of the components through the signals provided by the data acquisition system. Peristaltic and vacuum pumps were used to supply growth media and acquire reproducible samples for HPLC analysis with limited contamination. In a series of trials, targeted temperature and moisture conditions were achieved and new media was passed through each reactor using a time trigger. More product was produced in manual and automatically flushed cultures than in batch.

A new continuous one-dimensional sedimentation model incorporating a new continuous flocculation model that considers aggregation and fragmentation processes was derived and tested. Additionally, a new procedure to model sediment particle size distribution (PSD) was derived. Basic to this development were three different parametric models: Jaky, Fredlund and the Gamma probability distribution (GPD) were chosen to fit three different glass micro-spheres PSDs having average particle sizes of 7, 25 and 35 microns. The GPD provided the best fit with the least parameters. The bimodal GPD was used to fit ten sediment samples with excellent results (< 5% average error). A continuous flocculation model was derived using the method of moments for solving the continuous Smoluchowski coagulation equation with fragmentation. The initial sediment PSD was modeled using a bimodal GPD. This new flocculation model resulted in a new general moments’ equation that considers aggregation and fragmentation processes, which is represented by a system of ordinary differential equations. The model was calibrated using a genetic algorithm with initial and flocculated PSDs of four sediment samples and four anionic polyacrylamides flocculants. The results show excellent correlation between predicted and observed values (R2 > 0.9878). A new continuous one-dimensional sedimentation model that resulted in a scalar hyperbolic conservation law was derived from the well-known Kynch kinematic sedimentation model. The model was calibrated using column tests results with glass micro-spheres particles. Two different glass microspheres particle size distributions (PSDs) were used with average diameters of 7 and 37 microns. Excellent values of coefficient of determination (R2 > 0.89, except for one test replicate) were obtained for both the small and large glass micro-spheres PSDs. These results suggest that the proposed sedimentation model can be expanded to model the sedimentation process inside a sediment pond.

Development of biomass feedstocks with desirable traits for cost-effective conversion is one of the main focus areas in biofuels research. As suggested by techno-economic analyses, the success of a lignocellulose-based biorefinery largely relies on the utilization of lignin to generate value-added products, i.e. fuels and chemicals. The fate of lignin and its structural/compositional changes during pretreatment have received increasing attention; however, the effect of genetic modification on the fractionation, depolymerization and catalytic upgrading of lignin from genetically engineered plants is not well understood. This study aims to fractionate and characterize the lignin streams from a wild-type and two genetically engineered switchgrass (Panicum virgatum) species (low lignin content with high S/G ratio and high lignin content) using three different pretreatment methods, i.e. dilute sulfuric acid, ammonia hydroxide, and aqueous ionic liquid (cholinium lysinate). The structural and compositional features and impact of lignin modification on lignin-carbohydrate complex characteristics and the deconstruction of cell-wall compounds were investigated. Moreover, a potential way to upgrade low molecular weight lignin to lipids by Rhodococcus opacus was evaluated. Results from this study provide a better understanding of how lignin engineering of switchgrass influences lignin fractionation and upgrading during conversion processes based on different pretreatment technologies.

Precision agriculture requires detailed and timely information about field condition. In less than the short flight time a UAV (Unmanned Aerial Vehicle) can provide, an entire field can be scanned at the highest allowed altitude. The resulting NDVI (Normalized Difference Vegetation Index) imagery can then be used to classify each point in the field using a FIS (Fuzzy Inference System). This identifies areas that are expected to be similar, but only closer inspection can quantify and diagnose crop properties. In the remaining flight time, the goal is to scout a set of representative points maximizing the quality of actionable information about the field condition. This quality is defined by two new metrics: the average sampling probability (ASP) and the total scouting luminance (TSL). In simulations, the scouting flight plan created using a GA (Genetic Algorithm) significantly outperformed plans created by grid sampling or human experts, obtaining over 99% ASP while improving TSL by an average of 285%.

Agricultural runoff is one of largest contributors of phosphorus (P), nitrogen (N), and sediment affecting freshwater systems in watersheds across the Northeastern U.S., including the Lake Champlain Basin in Vermont. Agricultural cropping systems, such as corn silage and haylands, used for dairy feed production have been shown to impact watershed hydrology and water quality. Agricultural best management practices (BMPs) have the potential to decrease runoff volumes and flow rates and the associated export of nutrients and sediment from agricultural fields. Many states in the Northeastern U.S., including Vermont, are beginning to require farmers to implement water quality BMPs and further improve risk evaluation of export of P in runoff using evolving P site assessment tools, such as the Phosphorus Index (P-Index). Quantifying the effects of BMPs on hydrologic and nutrient exports from fields is critical for informing site assessment tools that aid in the development of nutrient management plans and to help design agroecosystems that do not degrade water quality. However, there is a lack of data on the effects of BMPs on edge-of-field hydrologic and nutrient fluxes, especially in cold-climate regions with snow-melt induced runoff events. This thesis consists of four chapters, Chapter 1 is a comprehensive literature review on agricultural hydrology and water quality, BMP effectiveness, and P site assessment tools. Chapters 2 and 3 address research objectives related to the evaluation of BMP and P site assessment tool effectiveness. Chapter 4 is a summary of the conclusions drawn from the work done in Chapters 2 and 3, and suggestions for future work. Chapter 2 evaluates the effects of soil aeration prior to manure application on edge-of-field hydrology, water quality, and P fluxes in haylands with clay soils during both precipitation and snow-melt induced runoff events. Edge-of-field water quality monitoring techniques and passive-capillary lysimeter systems were used to continuously measure the losses of surface runoff, subsurface leachate, and the associated export of nutrients (total phosphorus, total dissolved phosphorus, total nitrogen, and total dissolved nitrogen) and total suspended solids resulting from runoff events year-round from 2012 to 2018. Annual P fluxes in the form of vegetative uptake and removal, manure additions, and soil test P were also recorded. Results from this study indicated that soil aeration had the potential to reduce nutrient and sediment exports from haylands with poorly-drained, high runoff producing soils in the Northeastern U.S. where winter freeze-thaw conditions exist. However, potential increases in surface and subsurface hydrologic flows can accompany these reductions; these implications should be considered before implementation. Chapter 3 identifies potential P-Index improvements through the representation of topographic controls on phosphorus (P) transport by comparing results from the Vermont P-Index (VT P-Index) and a more complex process-based model, TopoSWAT, across topographic regions in a small agricultural watershed (360 ha) in the Lake Champlain Basin. Scenarios of varying P management strategies were modeled for corn silage production fields with poorly-drained soils and rolling topography. Modeled outputs of P risk assessments and edge-of-field dissolved and particulate P losses were compared. Results from this study suggest that the VT P-Index could improve its ability to support farm nutrient management planning and other P-based management decisions by incorporating topographic controls of runoff production into its estimation of P transport.

The use of velocity traverses to measure in-situ air flow rate of ventilation fans can be subject to significant errors. The Fan Assessment Numeration System (FANS) was developed by the USD-ARS Southern Poultry Research Laboratory and refined at the University of Kentucky to measure air flow of fans in-situ. The procedures for using the FANS unit to test fans in-situ are not completely standardized. This study evaluated the effect of operating fan positions relative to the FANS unit for ten 1.22 m diameter fans in two types of poultry barns, with fans placed immediately next to each other and 1.6 m apart. Fans were tested with the FANS unit placed near both the intake and discharge sides of the tested fans. Data were analyzed as two Generalized Randomized Complete Block designs (GRCB), with a 2 (FANS inside or outside) x 6 (operating fan combinations) factorial arrangement of treatments. Results showed significant differences as much as 12.6 ± 4.4% between air flow values obtained under conditions of different operating fan combinations. Placing the FANS unit outside provided valid fan test results. A standardized procedure for using the FANS unit to test fans in-situ was elaborated and presented in this work.

Clostridium thermocellum is a thermophilic anaerobe that is capable of producing ethanol directly from lignocellulosic compounds, however this organism suffers from low ethanol tolerance and low ethanol yields. In vivo mathematical modeling studies based on steady state traditional metabolic flux analysis, metabolic control analysis, transient and steady states’ flux spectrum analysis (FSA) were conducted on C. thermocellum’s central metabolism. The models were developed in Matrix Laboratory software ( MATLAB® (The Language of Technical Computing), R2008b, Version 7.7.0.471)) based on known stoichiometry from C. thermocellum pathway and known physical constraints. Growth on cellobiose from Metabolic flux analysis (MFA) and Metabolic control analysis (MCA) of wild type (WT) and ethanol adapted (EA) cells showed that, at lower than optimum exogenous ethanol levels, ethanol to acetate (E/A) ratios increased by approximately 29% in WT cells and 7% in EA cells. Sensitivity analyses of the MFA and MCA models indicated that the effects of variability in experimental data on model predictions were minimal (within ±5% differences in predictions if the experimental data varied up to ±20%). Steady state FSA model predictions showed that, an optimum hydrogen flux of ~5mM/hr in the presence of pressure equal to or above 7MPa inhibits ferrodoxin hydrogenase which causes NAD re-oxidation in the system to increase ethanol yields to about 3.5 mol ethanol/mol cellobiose.