Bioresource and Agricultural Engineering Commons^™

Development Of A Machine Learning System For Irrigation Decision Support With Disparate Data Streams, Eric Wilkening

Department of Biological Systems Engineering: Dissertations, Theses, and Student Research

In recent years, advancements in irrigation technologies have led to increased efficiency in irrigation applications, encompassing the adoption of practices that utilize data-driven irrigation scheduling and leveraging variable rate irrigation (VRI). These technological improvements have the potential to reduce water withdrawals and diversions from both groundwater and surface water sources. However, it is vital to recognize that improved application efficiency does not necessarily equate to increased water availability for future or downstream use. This is particularly crucial in the context of consumptive water use, which refers to water consumed and not returned to the local or sub-regional watershed, representing a …

Representativeness Evaluation Of Delta-Flux Eddy Covariance Towers For Assessing Greenhouse Gas Emissions From Rice Fields In The Mid-South Region, Katherine Skiles

Biological and Agricultural Engineering Undergraduate Honors Theses

Rice grown in 5 states across the Mid-South (AR, LA, MS, TX, and MO) account for nearly 80% of all domestic U.S. rice production. Methane emissions produced during rice farming and the large seasonal water demand to maintain flooded fields have created a need for alternative irrigation research that can reduce methane emissions and conserve water. Structures called eddy covariance towers (ECTs) can observe methane and other flux responses to changing irrigation styles, and their data is shared across flux tower networks such as Delta-Flux in the Mid-South. The Delta-Flux network is relatively new, and its data-sharing capacity is not …

Aicropcam: Deploying Classification, Segmentation, Detection, And Counting Deep-Learning Models For Crop Monitoring On The Edge, Nipuna Chamara, Geng (Frank) Bai, Yufeng Ge

Biological Systems Engineering: Papers and Publications

Precision Agriculture (PA) promises to meet the future demands for food, feed, fiber, and fuel while keeping their production sustainable and environmentally friendly. PA relies heavily on sensing technologies to inform site-specific decision supports for planting, irrigation, fertilization, spraying, and harvesting. Traditional point-based sensors enjoy small data sizes but are limited in their capacity to measure plant and canopy parameters. On the other hand, imaging sensors can be powerful in measuring a wide range of these parameters, especially when coupled with Artificial Intelligence. The challenge, however, is the lack of computing, electric power, and connectivity infrastructure in agricultural fields, preventing …

Optimal And Robust Control Problems Of Microalgae Cultivation, Mariana Rodriguez-Jara, Luis A. Ricardez-Sandoval, Carlos E. Ramirez-Castelan, Hector Puebla

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Modeling Overdraft-Driven Nitrate Transport In Shallow Wells For Mitigation And Scenario Planning, Jonathan Cronk

Department of Biological Systems Engineering: Dissertations, Theses, and Student Research

In Nebraska, average nitrate concentrations in groundwater have doubled since 1974, making water quality management more important than ever. As droughts, heat waves, and floods become more common climate events, understanding their impacts will be necessary to make informed management decisions. Emerging literature describes that drought correlates to an increase in the concentration of nitrate-N at domestic and irrigation wells, however the relative contributions of the mechanisms thought to be responsible is currently unknown.

This research assessed the impact of recharge and pumping rate changes as two mechanisms affecting nitrate-N concentration during drought, assessed the relationship between well depth and …

Hydrothermal Carbonization Of Biomass Wastes: Sustainability And Geochemistry, Michael A. Kruge, Teresa A. Centeno, Alvaro Amado-Fierro, José Manuel González-Lafuente, Ruben Forjan-Castro, José Luis Gallego

Department of Earth and Environmental Studies Faculty Scholarship and Creative Works

Introduction. To reduce the stream of solid waste going to landfills, innovative means for beneficial use are essential. The diversity and volume of organic wastes pose singular problems and opportunities for recovery and circularity. Common processes for organics include conversion to biofuels and carbonization to biochar, typically done by torrefaction (dry pyrolysis). Research on biochar explores its potential as pollutant adsorbent, agricultural or polluted soil amendment, biofuel (directly or as feedstock), and for carbon sequestration (Ighalo et al., 2022; Cavali et al., 2023). Recently, other processes at lower temperatures such as hydrothermal carbonization (HTC) offer new possibilities (Seshadri et al., …

Modeling The Moisture Content And Drying Rate Of Zucchini (Cucurbita Pepo L.) In A Solar Hybrid Dryer Using Ann And Anfis Methods, Halil Nusret Bulus, Aytac Moralar, Soner Celen

The Philippine Agricultural Scientist

Estimating product drying kinetics is critical to obtain the best drying process without compromising product quality and necessitates the development of numerical drying models. This research aims to compare the prediction models developed using artificial neural network (ANN) and adaptive network-based fuzzy inference system (ANFIS), two popular machine learning approaches in the recent years. Zucchini slices were chosen as samples and dried in a solar-assisted microwave belt dryer at 0.245 m/min belt speed and microwave powers of 0.7, 1, and 1.4 kW. On the data set obtained by computing the moisture content and drying rate values, prediction models were developed …

Plant Height Estimation Using Rtk-Gnss Enabled Unmanned Aerial Vehicle (Uav) Photogrammetry, Pascal Izere

Department of Biological Systems Engineering: Dissertations, Theses, and Student Research

Using Unmanned Aerial Vehicle (UAV) based remote sensing technology to provide high-throughput plant phenotypic traits has shown a great potential of eliminating manual measurements. For example, the use of UAV imaging to estimate plant height is of great interest to plant breeders and agronomists. Height is linked to a plant’s physical growth, light competition, health, biomass, and yield; thus, its accurate estimation is crucial in breeding. Conventionally, accurate height estimation by UAV platforms relies heavily on the use of ground control points (GCPs) for geometric calibration due to the relatively low positioning accuracy of regular differential global navigation satellite system …

Influence Of Ultrasound Machine Settings On Quantitative Measures Derived From Spatial Frequency Analysis Of Muscle Tissue, Scott K. Crawford, Stephanie A. Kliethermes, Bryan C. Heiderscheit, Greg Bashford

Biological Systems Engineering: Papers and Publications

Background Ultrasound is a powerful tool for diagnostic purposes and provides insight into both normal and pathologic tissue structure. Spatial frequency analysis (SFA) methods characterize musculoskeletal tissue organization from ultrasound images. Both sonographers in clinical imaging and researchers may alter a minimized range of ultrasound settings to optimize image quality, and it is important to know how these small adjustments of these settings affect SFA parameters. The purpose of this study was to investigate the effects of making small adjustments in a typical default ultrasound machine setting on extracted spatial frequency parameters (peak spatial frequency radius (PSFR), Mmax, Mmax%, and …

Non-Destructive Evaluation Of White Striping And Microbial Spoilage Of Broiler Breast Meat Using Structured-Illumination Reflectance Imaging, Ebenezer O. Olaniyi

Theses and Dissertations

Manual inspection is a prevailing practice for quality assessment of poultry meat, but it is labor-intensive, tedious, and subjective. This thesis aims to assess the efficacy of an emerging structured illumination reflectance imaging (SIRI) technique with machine learning approaches for assessing WS and microbial spoilage in broiler breast meat. Broiler breast meat samples were imaged by an in house-assembled SIRI platform under sinusoidal illumination. In first experiment, handcrafted texture features were extracted from direct component (DC, corresponding to conventional uniform illumination) and amplitude component (AC, unique to the use of sinusoidal illumination) images retrieved from raw SIRI pattern images build …

Characterizing Feedlot Feed Using Depth Cameras And Imaging Technology, Jean Niwenshuti

Department of Biological Systems Engineering: Dissertations, Theses, and Student Research

Imaging technology is a growing field that provides solutions in many areas from manufacturing to agriculture. Through previous research, imaging technologies have been studied in livestock farming to monitor the animal’s health and welfare in the production process. However, the feedlot industry is still behind in validating the feasibility to use some of these technologies nor to adopt such technologies to address challenges the industry is facing, such as lack of skilled labor.This work proposes using novel imaging methods to identify feed types and estimate the amount of feed remaining in a typical Midwestern feedlot feed bunk. These methods have …

Development Of Mass Transfer Coefficient Correlations Between Carbon Dioxide And Oxygen For Air-Lift Devices, John Walker

All Theses

An experimental method for measurement and determination of carbon dioxide volumetric mass transfer coefficients (k_La) in high pH water was developed. The goal of this research was to develop a relationship between CO₂ and O₂ volumetric mass transfer coefficients for accurate k_La values in order to meet the needs of carbon capture systems and other industries. Results included dissolved oxygen (DO) and total inorganic carbon (TIC) k_La comparisons, as well as polarographic DO (mg/L) and galvanic DO (mV) k_La correlation. CO₂ k_La estimation based on O_{2 …}

Examining The Relationship Between Lignocellulosic Biomass Structural Constituents And Its Flow Behavior, Ekramul Haque Ehite

Doctoral Dissertations

Lignocellulosic biomass material sourced from plants and herbaceous sources is a promising substrate of inexpensive, abundant, and potentially carbon-neutral energy. One of the leading limitations of using lignocellulosic biomass as a feedstock for bioenergy products is the flow issues encountered during biomass conveyance in biorefineries. In the biorefining process, the biomass feedstock undergoes flow through a variety of conveyance systems. The inherent variability of the feedstock materials, as evidenced by their complex microstructural composition and non-uniform morphology, coupled with the varying flow conditions in the conveyance systems, gives rise to flow issues such as bridging, ratholing, and clogging. These issues …

Understanding Lignin’S Fast Pyrolysis Through Examination Of The Thermolysis Mechanisms Of Model Oligomers, Ross Wesley Houston

Doctoral Dissertations

The lignocellulosic biorefinery is a visionary concept that endeavors to provide an alternative to fossil-based refineries by producing biobased fungible fuels and specialty chemicals almost exclusively derived currently from petroleum refineries. This vision of the lignocellulosic biorefinery can only be realized if all fractions of lignocellulosic biomass are efficiently deconstructed and valorized to generate a diverse portfolio of products to sustain it against market vicissitudes. Of the three main structural constituents of lignocellulosic biomass (i.e., cellulose, hemicellulose, and lignin), lignin is underutilized despite being the most abundant renewable source of aromatic platform chemicals, representing a growing 250 billion dollar market. …

Assessment Of Integrated Nutrient Management Practices On Soil Health And Nitrogen Efficiency In Cropping Systems, María José Oviedo Ventura

Department of Biological Systems Engineering: Dissertations, Theses, and Student Research

Groundwater quality in Nebraska is threatened by non-point source contributions of nitrate-nitrogen, primarily by agricultural systems. Intensive crop and livestock production that neglects the value of manure in crop fertility plans can contribute to soil degradation and natural resource impairment. The purpose of this study is to evaluate opportunities to improve agricultural nutrient management throughout Nebraska by quantifying opportunities for manure distribution, evaluating soil health implications of organic and inorganic soil amendments, and assessing nutrient management practices focused on reducing nitrate leaching in agricultural soils.

This study described in Chapter 2 provides a spatial illustration of nitrogen and phosphorus balances …

Non-Energy Circular Economy Potential Of Rice Husks: A Techno-Eco-Environmental Assessment, Winfred Oppong Yeboah

Graduate Theses and Dissertations

The non-energy circular bioeconomy potential of rice husks was examined via sustainability assessments, namely life cycle assessment (LCA), life cycle impact cost assessment (LCICA), and techno-economic assessment (TEA). The study was conducted with three objectives. The first objective was to review previous studies on the non-energy utilization potential of rice husks by the method of meta-analysis. This review followed a systematic approach where research papers were collected following a defined set of criteria. The study revealed 16 key utilization pathways, all of which showed promising results. However, a comprehensive sustainability assessment was lacking in all of the pathways. The second …

Prairie Protector: Student Development Of Systems Thinking Habits In The Context Of Agroecosystems, Erin Ingram, Jennifer Keshwani

Biological Systems Engineering: Papers and Publications

Introduction: The Great Plains ecosystem offers an opportunity for young people to gain knowledge about intricate systems through practical learning. The spread of woody plants into grasslands, known as the “Green Glacier,” poses a risk to biodiversity and animal production. Although effective management strategies exist, some land managers are reluctant to use them. It is critical to cultivate a scientifically literate population that can think systematically and make informed decisions based on STEM principles to address such complex agroecosystem problems.

Methods: In this study, semi-structured focus group discussions with high school students were analyzed to determine whether Prairie …

Challenges And Solution For Identification Of Plant Disease Using Machine Learning & Iot, Suprava Ranjan Ranjan Laha Mr., Sonali Samal, Debasish Swapnesh Kumar Nayak, Saumendra Pattnaik, Binod Kumar Pattanayak Prof. (Dr.)

International Journal of Computer and Communication Technology

Internet of Thing (IoT) is a groundbreaking technology that has been introduced in the field of agriculture to improve the quality and quantity of food production. As agriculture plays a vital role in feeding most of the world's population, the increasing demand for food has led to a rise in food grain production. The identification of plant diseases is a critical task for farmers and agronomists as it enables them to take proactive measures to prevent the spread of diseases, protect crops, and maximize yields. Traditional methods of plant disease detection involve visual inspections by experts, which can be time-consuming …

Assessing The Impact Of Spatial Resolution Of Uas-Based Remote Sensing And Spectral Resolution Of Proximal Sensing On Crop Nitrogen Retrieval Accuracy, Kianoosh Hassani, Hamed Gholizadeh, Saleh Taghvaeian, Victoria Natalie, Jonathan Carpenter, Jamey Jacob

Biological Systems Engineering: Papers and Publications

Foliar nitrogen (N) plays a central role in photosynthetic machinery of plants, regulating their growth rates. However, field-based methods for monitoring plant N concentration are costly and limited in their ability to cover large spatial extents. In this study, we had two objectives: (1) assess the capability of unoccupied aerial system (UAS) and non-imaging spectroscopic data in estimating sorghum and corn N concentration and (2) determine the impact of spatial and spectral resolution of reflectance data on estimating sorghum and corn N concentration. We used a UAS and an ASD spectroradiometer to collect canopy- and leaf-level spectral data from sorghum …

Exploring The Determinants Of Organic Matter Bioavailability Through Substrate-Explicit Thermodynamic Modeling, Firnaaz Ahamed, Yaqi You, Amy Burgin, James C. Stegen, Timothy D. Scheibe, Hyun-Seob Song

Biological Systems Engineering: Papers and Publications

Microbial decomposition of organic matter (OM) in river corridors is a major driver of nutrient and energy cycles in natural ecosystems. Recent advances in omics technologies enabled high-throughput generation of molecular data that could be used to inform biogeochemical models. With ultrahigh-resolution OM data becoming more readily available, in particular, the substrate-explicit thermodynamic modeling (SXTM) has emerged as a promising approach due to its ability to predict OM degradation and respiration rates from chemical formulae of compounds. This model implicitly assumes that all detected organic compounds are bioavailable, and that aerobic respiration is driven solely by thermodynamics. Despite promising demonstrations …