Bioresource and Agricultural Engineering Commons^™

Machine Learning-Based Disease Classification In Tomato (Solanum Lycopersicum) Plants = Klasifikasi Penyakit Berbasis Pembelajaran Mesin Pada Tanaman Tomat (Solanum Lycopersicum), Md Towfiqur Rahman, Sudipto Dhar Dipto, Israt Jahan June, Abdul Momin, Muhammad Rashed Al Mamun

Department of Agricultural and Biological Systems Engineering: Faculty Publications

English abstract

In Bangladesh, tomato cultivation faces significant challenges due to its susceptibility to various microorganisms, parasites, and bacterial infections. Typically, the early symptoms of these diseases first appear in roots and leaves, complicating timely detection. This study addresses the challenge of timely and accurate detection of diseases in tomato plants, crucial for effective plant protection management. Conventional manual inspection methods are time-consuming and subjective, resulting in delays in implementing necessary protection measures. Therefore, an image processing technique and machine learning algorithms were used for rapid and robust detection of diseases in tomato plant leaves, aiming to streamline the detection …

A Validation Of Wepp Water Quality Routines In Uniform And Nonuniform Agricultural Hillslopes, Ryan P. Mcgehee, Dennis C. Flanagan, Bernard A. Engel, John E. Gilley

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Nutrients in agricultural runoff may cause offsite environmental impacts. The objective of this investigation was to examine nutrient transport by overland sheet flow on sites containing swine slurry. Data examined in this study was collected during field rainfall simulation tests conducted on cropland sites in southeast Nebraska, USA. Inflow was added to the top of experimental plots in four successive increments to simulate runoff rates occurring at greater downslope distances. Runoff rates on the experimental sites ranged from 2.3 to 21.2 L min 1 and maximum equivalent downslope distances varied from 5 to 108 m. Phosphorus (P) and nitrogen (N) …

Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia

Journal of Nonprofit Innovation

Urban farming can enhance the lives of communities and help reduce food scarcity. This paper presents a conceptual prototype of an efficient urban farming community that can be scaled for a single apartment building or an entire community across all global geoeconomics regions, including densely populated cities and rural, developing towns and communities. When deployed in coordination with smart crop choices, local farm support, and efficient transportation then the result isn’t just sustainability, but also increasing fresh produce accessibility, optimizing nutritional value, eliminating the use of ‘forever chemicals’, reducing transportation costs, and fostering global environmental benefits.

Imagine Doris, who is …

Red Cabbage Juice-Mediated Gut Microbiota Modulation Improves Intestinal Epithelial Homeostasis And Ameliorates Colitis, Emily Jean Wilson, Nagabhishek Sirpu Natesh, Parsa Ghadermazi, Ramesh Pothuraju, Dipakkumar R. Prajapati, Sanjit Pandey, Jussuf T. Kaifi, John R. Dodam, Jeffrey Bryan, Christian L. Lorson, Aude A. Watrelot, Jason M. Foster, Thomas J. Mansell, Siu Hung Joshua Chan, Surinder K. Batra, Jeyamkondan Subbiah, Satyanarayana Rachagani

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Gut microbiota plays a crucial role in inflammatory bowel diseases (IBD) and can potentially prevent IBD through microbial-derived metabolites, making it a promising therapeutic avenue. Recent evidence suggests that despite an unclear underlying mechanism, red cabbage juice (RCJ) alleviates Dextran Sodium Sulfate (DSS)-induced colitis in mice. Thus, the study aims to unravel the molecular mechanism by which RCJ modulates the gut microbiota to alleviate DSS-induced colitis in mice. Using C57BL/6J mice, we evaluated RCJ’s protective role in DSS-induced colitis through two cycles of 3% DSS. Mice were daily gavaged with PBS or RCJ until the endpoint, and gut microbiota composition …

Determining The Presence And Size Of Shoulder Lesions In Sows Using Computer Vision, Shubham Bery, Tami M. Brown-Bandl, Bradley T. Jones, Gary A. Rohrer, Sudhendu Raj Sharma

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Shoulder sores predominantly arise in breeding sows and often result in untimely culling. Reported prevalence rates vary significantly, spanning between 5% and 50% depending upon the type of crate flooring inside a farm, the animal’s body condition, or an existing injury that causes lameness. These lesions represent not only a welfare concern but also have an economic impact due to the labor needed for treatment and medication. The objective of this study was to evaluate the use of computer vision techniques in detecting and determining the size of shoulder lesions. A Microsoft Kinect V2 camera captured the top-down depth and …

Deep Learning Models To Predict Finishing Pig Weight Using Point Clouds, Shiva Paudel, Rafael Vieira De Sousa, Sudhendu Raj Sharma, Tami M. Brown-Bandl

Department of Agricultural and Biological Systems Engineering: Faculty Publications

The selection of animals to be marketed is largely completed by their visual assessment, solely relying on the skill level of the animal caretaker. Real-time monitoring of the weight of farm animals would provide important information for not only marketing, but also for the assessment of health and well-being issues. The objective of this study was to develop and evaluate a method based on 3D Convolutional Neural Network to predict weight from point clouds. Intel Real Sense D435 stereo depth camera placed at 2.7 m height was used to capture the 3D videos of a single finishing pig freely walking …

Deep Learning Models To Predict Finishing Pig Weight Using Point Clouds, Shiva Paudel, Rafael Vieira De Sousa, Sudhendu Raj Sharma, Tami M. Brown-Bandl

Department of Agricultural and Biological Systems Engineering: Faculty Publications

The selection of animals to be marketed is largely completed by their visual assessment, solely relying on the skill level of the animal caretaker. Real-time monitoring of the weight of farm animals would provide important information for not only marketing, but also for the assessment of health and well-being issues. The objective of this study was to develop and evaluate a method based on 3D Convolutional Neural Network to predict weight from point clouds. Intel Real Sense D435 stereo depth camera placed at 2.7 m height was used to capture the 3D videos of a single finishing pig freely walking …

Impact Of Irrigation On Vulnerability Of Winter Wheat Under Extreme Climate Change Scenario: A Case Study Of North China Plain, Yulian Gao, Lin Wang, Yaojie Yue

Department of Agricultural and Biological Systems Engineering: Faculty Publications

An inadequate understanding of the impacts of adaptation countermeasures tends to exaggerate the adverse e􀀀ects of climate change on agricultural systems. Motivated by proposing reasonable climate change adaptation countermeasures, the present study applied the EPIC model to quantify the impacts of climate change and irrigation changes with future socioeconomic development on agricultural production. Winter wheat yield losses using dynamic irrigation parameters in the North China Plain (NCP) from 2010 to 2099 under a scenario coupling climate change and future socioeconomic development (RCP8.5-SSP3), and those under an extreme climate change scenario (RCP8.5), were simulated. Results show that EPIC model demonstrates superior …

Study Of Surface And Groundwater Quality And Quantity At Watershed Scale In Mississippi, Dipesh Nepal

Theses and Dissertations

Hydrology and water quality are affected by land use and climate changes. Mississippi’s diverse agro–ecosystem comprises of a range of land use land cover (LULC) including agriculture, forest, wetlands, urban, and grasslands. The objectives of this study were to investigate the impacts of various factors such as Best Management Practices (BMPs), wetlands, LULC, and climate changes on water quality and quantity. The hydrologic and water quality responses to dynamic LULC input in Soil and Water Assessment Tool (SWAT) were evaluated. Results showed that agricultural and forest expansion were major drivers of hydrologic and water quality changes in Big Sunflower River …

Systematic Comparison Of Nonviral Gene Delivery Strategies For Efficient Co-Expression Of Two Transgenes In Human Mesenchymal Stem Cells, Tyler Kozisek, Luke Samuelson, Andrew Hamann, Angela K. Pannier

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Background Human mesenchymal stem cells (hMSCs) are being researched for cell-based therapies due to a host of unique properties, however, genetic modification of hMSCs, accomplished through nonviral gene delivery, could greatly advance their therapeutic potential. Furthermore, expression of multiple transgenes in hMSCs could greatly advance their clinical significance for treatment of multifaceted diseases, as individual transgenes could be expressed that target separate pathogenic drivers of complex diseases. Expressing multiple transgenes can be accomplished by delivering multiple DNA vectors encoding for each transgene, or by delivering a single poly-cistronic vector that encodes for each transgene and accomplishes expression through either use …

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

Department of Agricultural and Biological Systems Engineering: Faculty 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 …

Determining The Presence And Size Of Shoulder Lesions In Sows Using Computer Vision, Shubham Bery, Tami M. Brown-Brandl, Bradley T. Jones, Gary A. Rohrer, Sudhendu Raj Sharma

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Shoulder sores predominantly arise in breeding sows and often result in untimely culling. Reported prevalence rates vary significantly, spanning between 5% and 50% depending upon the type of crate flooring inside a farm, the animal’s body condition, or an existing injury that causes lameness. These lesions represent not only a welfare concern but also have an economic impact due to the labor needed for treatment and medication. The objective of this study was to evaluate the use of computer vision techniques in detecting and determining the size of shoulder lesions. A Microsoft Kinect V2 camera captured the top-down depth and …

A Text Analytics Model For Agricultural Knowledge Discovery And Sustainable Food Production: A Case Study From Oklahoma Panhandle, Ali Bagheri, Saleh Taghvaeian, Dursun Delen

Department of Agricultural and Biological Systems Engineering: Faculty Publications

With recent increases in the use of social media in agricultural communities, many farmers are showing more and more interest in participating in social media and sharing different aspects of their profession with peers and policymakers. However, researchers have not explored this valuable data source well enough to help improve agribusiness decision-making. This study aims to investigate the potential capability and richness of social media for agricultural knowledge discovery, which can help monitor, detect, and predict critical agricultural events and activities and develop more sustainable food production and agricultural economy. This research utilizes text-mining tools and techniques to collect, process, …

Statistical And Machine Learning Approaches To Describe Factors Affecting Preweaning Mortality Of Piglets, Md Towfiqur Rahman, Tami M. Brown-Brandl, Gary A. Rohrer, Sudhendu R. Sharma, Vamsi Manthena, Yeyin Shi

Department of Agricultural and Biological Systems Engineering: Faculty Publications

High preweaning mortality (PWM) rates for piglets are a significant concern for the worldwide pork industries, causing economic loss and well-being issues. This study focused on identifying the factors affecting PWM, overlays, and predicting PWM using historical production data with statistical and machine learning models. Data were collected from 1,982 litters from the United States Meat Animal Research Center, Nebraska, over the years 2016 to 2021. Sows were housed in a farrowing building with three rooms, each with 20 farrowing crates, and taken care of by well-trained animal caretakers. A generalized linear model was used to analyze the various sow, …

Statistical And Machine Learning Approaches To Describe Factors Affecting Preweaning Mortality Of Piglets, Md Towfiqur Rahman, Tami M. Brown-Bandl, Gary A. Rohrer, Sudhendu R. Sharma, Vamsi Manthena, Yeyin Shi

Department of Agricultural and Biological Systems Engineering: Faculty Publications

High preweaning mortality (PWM) rates for piglets are a significant concern for the worldwide pork industries, causing economic loss and well-being issues. This study focused on identifying the factors affecting PWM, overlays, and predicting PWM using historical production data with statistical and machine learning models. Data were collected from 1,982 litters from the U.S. Meat Animal Research Center, Nebraska, over the years 2016 to 2021. Sows were housed in a farrowing building with three rooms, each with 20 farrowing crates, and taken care of by well-trained animal caretakers. A generalized linear model was used to analyze the various sow, litter, …

Statistical And Machine Learning Approaches To Describe Factors Affecting Preweaning Mortality Of Piglets, Md Towfiqur Rahman, Tami M. Brown-Bandl, Gary A. Rohrer, Sudhendu R. Sharma, Vamsi Manthena, Yeyin Shi

Department of Agricultural and Biological Systems Engineering: Faculty Publications

High preweaning mortality (PWM) rates for piglets are a significant concern for the worldwide pork industries, causing economic loss and well-being issues. This study focused on identifying the factors affecting PWM, overlays, and predicting PWM using historical production data with statistical and machine learning models. Data were collected from 1,982 litters from the U.S. Meat Animal Research Center, Nebraska, over the years 2016 to 2021. Sows were housed in a farrowing building with three rooms, each with 20 farrowing crates, and taken care of by well-trained animal caretakers. A generalized linear model was used to analyze the various sow, litter, …

Upscaling Wetland Methane Emissions From The Fluxnet-Ch4 Eddy Covariance Network (Upch4 V1.0): Model Development, Network Assessment, And Budget Comparison, Gavin Mcnicol, Etienne Fluet-Chouinard, Zutao Ouyang, Sara Knox, Zhen Zhang, Tuula Aalto, Sheel Bansal, Kuang Yu Chang, Min Chen, Kyle Delwiche, Sarah Feron, Mathias Goeckede, Jinxun Liu, Avni Malhotra, Joe R. Melton, William Riley, Rodrigo Vargas, Kunxiaojia Yuan, Qing Ying, Qing Zhu, Pavel Alekseychik, Mika Aurela, David Billesbach, David I. Campbell, Jiquan Chen, Housen Chu, Ankur R. Desai, Eugenie Euskirchen, Jordan Goodrich, Timothy Griffis, Manuel Helbig, Takashi Hirano, Hiroki Iwata, Gerald Jurasinski, John King, Franziska Koebsch, Randall Kolka, Ken Krauss, Annalea Lohila, Ivan Mammarella

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Wetlands are responsible for 20%–31% of global methane (CH4) emissions and account for a large source of uncertainty in the global CH4 budget. Data-driven upscaling of CH4 fluxes from eddy covariance measurements can provide new and independent bottom-up estimates of wetland CH4 emissions. Here, we develop a six-predictor random forest upscaling model (UpCH4), trained on 119 site-years of eddy covariance CH4 flux data from 43 freshwater wetland sites in the FLUXNET-CH4 Community Product. Network patterns in site-level annual means and mean seasonal cycles of CH4 fluxes were reproduced accurately in tundra, boreal, and temperate regions (Nash-Sutcliffe Efficiency ∼0.52–0.63 and 0.53). …

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., …

Resilin Distribution And Abundance In Apis Mellifera Across Biological Age Classes And Castes, Audrey Anderson, Noah Keime, Chandler Fong, Andrew Kraemer, Carol Fassbinder-Orth

Department of Agricultural and Biological Systems Engineering: Faculty Publications

The presence of resilin, an elastomeric protein, in insect vein joints provides the flexible, passive deformations that are crucial to flapping flight. This study investigated the resilin gene expression and autofluorescence dynamics among Apis mellifera (honey bee) worker age classes and drone honey bees. Resilin gene expression was determined via ddPCR on whole honey bees and resilin autofluorescence was measured in the 1m-cu, 2m-cu, Cu-V, and Cu2-V joints on the forewing and the Cu-V joint of the hindwing. Resilin gene expression varied significantly with age, with resilin activity being highest in the pupae. Autofluorescence of the 1m-cu and the Cu-V …

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

Department of Agricultural and Biological Systems Engineering: Faculty 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 …

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

Department of Agricultural and Biological Systems Engineering: Faculty 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 …

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

Department of Agricultural and Biological Systems Engineering: Faculty 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

Department of Agricultural and Biological Systems Engineering: Faculty 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 …

Aeroponic System Optimization For Butterhead Lettuce Growth And Future Sustainability Using Flow Blurring Atomization, Taylor J. Johnson

Doctoral Dissertations and Master's Theses

The global population has grown by 6 billion people over the last century and is trending toward 9.7 billion people by the year 2050. Agriculture accounts for 70% of global fresh water usage. Technology must be developed to accommodate the increase of food production demanded by the growing global population and the subsequent increase in water usage. Aeroponic technology is a water-efficient vertical farming technology that can reduce water usage by 90% by suspending plant roots in air within a controlled chamber and supplying atomized droplets of a water-nutrient solution directly to the roots.

This study simultaneously tests six droplet …

Maize Nitrogen Uptake, Grain Nitrogen Concentration And Root-Zone Residual Nitrate Nitrogen Response Under Center Pivot, Subsurface Drip And Surface (Furrow) Irrigation, Suat Irmak, Ali T. Mohammed, Matthew Drudik

Department of Agricultural and Biological Systems Engineering: Faculty Publications

While the impact(s) of irrigation and nitrogen (N) levels on crop yields have been investigated separately, research lacks about how different irrigation methods coupled with different N application timing strategies under full and limited irrigation levels effect yield, soil nitrate nitrogen (NO₃-N) residual and stover N uptake. Knowledge of these dynamics can help to establish effective water and N management guidelines for the same crop under different irrigation methods and irrigation levels. This research investigated maize (Zea mays L.) residual soil NO₃-N concentration and stover and grain N uptake response to water under different irrigation …

Engineering A Multicompartment In Vitro Model For Dorsal Root Ganglia Phenotypic Assessment, Sydney M. Caparaso, Adan Redwine, Rebecca A. Wachs

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Despite the significant global prevalence of chronic pain, current methods to identify pain therapeutics often fail translation to the clinic. Phenotypic screening platforms rely on modeling and assessing key pathologies relevant to chronic pain, improving predictive capability. Patients with chronic pain often present with sensitization of primary sensory neurons (that extend from dorsal root ganglia [DRG]). During neuronal sensitization, painful nociceptors display lowered stimulation thresholds. To model neuronal excitability, it is necessary to maintain three key anatomical features of DRGs to have a physiologically relevant platform: (1) isolation between DRG cell bodies and neurons, (2) 3D platform to preserve cell–cell …

Post-Processed Data And Graphical Tools For A Conus-Wide Eddy Flux Evapotranspiration Dataset, J. M. Volk, J. L. Huntington, F. Melton, B. Minor, T. Wang, S. Anapalli, R. G. Anderson, S. Evett, A. French, R. Jasoni, N. Bambach, W. P. Kustas, J. Alfieri, J. Prueger, L. Hipps, L. Mckee, S. J. Castro, M. M. Alsina, A. J. Mcelrone, M. Reba, B. Runkle, M. Saber, C. Sanchez, E. Tajfar, R. Allen, M. Anderson

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Large sample datasets of in situ evapotranspiration (ET) measurements with well documented data provenance and quality assurance are critical for water management and many fields of earth science research. We present a post-processed ET oriented dataset at daily and monthly timesteps, from 161 stations, including 148 eddy covariance flux towers, that were chosen based on their data quality from nearly 350 stations across the contiguous United States. In addition to ET, the data includes energy and heat fluxes, meteorological measurements, and reference ET downloaded from grid- MET for each flux station. Data processing techniques were conducted in a reproducible manner …

Soybean Crop Coefficients Under Different Seeding Rates And Full And Limited Irrigation And Rainfed Management, Suat Irmak, Rupinder Sandhu

Department of Agricultural and Biological Systems Engineering: Faculty Publications

The effects of soybean seeding rates on evapotranspiration (ET_c) and grassand alfalfa-reference crop coefficients (K_co and K_cr) were investigated under five seeding rates (185,250, 247,000, 308,750, 370,500 and 432,250 seeds ha^-1) (62, 82, 103, 124 and 144% of the recommended seeding rate of 300,000 seeds ha^-1 in the experimental region) and different irrigation strategies (i.e. full irrigation treatment [FIT], limited irrigation of 75% FIT and 50% FIT and rainfed treatment). K_co and K_cr values were developed for each soybean growth stage. The seasonal ET_c ranged from 460 mm for …

Streambank Erosion Phenomena And Understanding: Current Research And Future Directions, Celso Castro-Bolinaga, Aaron R. Mittelstet, Kyle Mankin

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Streams are in dynamic equilibrium with their environments, and as that environment is altered by human development and changing climate, streambank erosion is a common, but little understood, result. This article highlights the contributions of the special collection “Streambank Erosion, Sediment Dynamics, and Restoration (SER),” which assembled six studies that represent key advances in streambank erosion research, highlight current research in the field, and identify directions for future research. The studies in this special collection were grouped into three central themes: (1) streambank erosion monitoring, (2) streambank erodibility characterization, and (3) streambank erosion loading. In this article, key findings within …

Toward Automated Irrigation Management With Integrated Crop Water Stress Index And Spatial Soil Water Balance, Sandeep Bhatti, Derek M. Heeren, Susan A. O’Shaughnessy, Christopher M. U. Neale, Jacob Larue, Steve Melvin, Eric Wilkening, Geng Bai

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Decision support systems intended for precision irrigation aim at reducing irrigation applications while optimizing crop yield to achieve maximum crop water productivity (CWP). These systems incorporate on-site sensor data, remote sensing inputs, and advanced algorithms with spatial and temporal characteristics to compute precise crop water needs. The availability of variable rate irrigation (VRI) systems enables irrigation applications at a sub-field scale. The combination of an appropriate VRI system along with a precise decision support system would be ideal for improved CWP. The objective of this study was to compare and evaluate two decision support systems in terms of seasonal applied …