Civil and Environmental Engineering Commons^™

Identification Of Compounds That Cause Axonal Dieback Without Cytotoxicity In Dorsal Root Ganglia Explants And Intervertebral Disc Cells With Potential To Treat Pain Via Denervation, Fei San Lee, Uyen N. Nguyen, Eliza J. Munns, Rebecca A. Wachs

Department of Biological Systems Engineering: Papers and Publications

Low back pain, knee osteoarthritis, and cancer patients suffer from chronic pain. Aberrant nerve growth into intervertebral disc, knee, and tumors, are common pathologies that lead to these chronic pain conditions. Axonal dieback induced by capsaicin (Caps) denervation has been FDA-approved to treat painful neuropathies and knee osteoarthritis but with shortterm efficacy and discomfort. Herein, we propose to evaluate pyridoxine (Pyr), vincristine sulfate (Vcr) and ionomycin (Imy) as axonal dieback compounds for denervation with potential to alleviate pain. Previous literature suggests Pyr, Vcr, and Imy can cause undesired axonal degeneration, but no previous work has evaluated axonal dieback and cytotoxicity …

Kinetics-Based Inference Of Environment-Dependent Microbial Interactions And Their Dynamic Variation, Hyun-Seob Song, Na-Rae Lee, Aimee K. Kessell, Hugh C. Mccullough, Seo-Young Park, Kang Zhou, Dong-Yup Lee

Department of Biological Systems Engineering: Papers and Publications

Microbial communities in nature are dynamically evolving as member species change their interactions subject to environmental variations. Accounting for such context-dependent dynamic variations in interspecies interactions is critical for predictive ecological modeling. In the absence of generalizable theoretical foundations, we lack a fundamental understanding of how microbial interactions are driven by environmental factors, significantly limiting our capability to predict and engineer community dynamics and function. To address this issue, we propose a novel theoretical framework that allows us to represent interspecies interactions as an explicit function of environmental variables (such as substrate concentrations) by combining growth kinetics and a generalized …

Image Filtering To Improve Maize Tassel Detection Accuracy Using Machine Learning Algorithms, Eric Rodene, Gayara Demini Fernando, Ved Piyush, Yufeng Ge, James C. Schnable, Souparno Ghosh, Jinliang Yang

Department of Biological Systems Engineering: Papers and Publications

Unmanned aerial vehicle (UAV)-based imagery has become widely used to collect timeseries agronomic data, which are then incorporated into plant breeding programs to enhance crop improvements. To make efficient analysis possible, in this study, by leveraging an aerial photography dataset for a field trial of 233 different inbred lines from the maize diversity panel, we developed machine learning methods for obtaining automated tassel counts at the plot level. We employed both an object-based counting-by-detection (CBD) approach and a density-based counting-by-regression (CBR) approach. Using an image segmentation method that removes most of the pixels not associated with the plant tassels, the …

Composting Reduces The Risks Of Resistome In Beef Cattle Manure At The Transcriptional Level, Yuepeng Sun, Zachery R. Staley, Bryan Woodbury, Jean-Jack Riethoven, Xu Li

Department of Biological Systems Engineering: Papers and Publications

Transcriptomic evidence is needed to determine whether composting is more effective than conventional stockpiling in mitigating the risk of resistome in livestock manure. The objective of this study is to compare composting and stockpiling for their effectiveness in reducing the risk of antibiotic resistance in beef cattle manure. Samples collected from the center and the surface of full-size manure stockpiling and composting piles were subject to metagenomic and metatranscriptomic analyses. While the distinctions in resistome between stockpiled and composted manure were not evident at the DNA level, the advantages of composting over stockpiling were evident at the transcriptomic level in …

Enhancing Estimation Of Cover Crop Biomass Using Field-Based High-Throughput Phenotyping And Machine Learning Models, Geng Bai, Katja Koehler-Cole, David Scoby, Vesh R. Thapa, Andrea D. Basche, Yufeng Ge

Department of Biological Systems Engineering: Papers and Publications

Incorporating cover crops into cropping systems offers numerous potential benefits, including the reduction of soil erosion, suppression of weeds, decreased nitrogen requirements for subsequent crops, and increased carbon sequestration. The aboveground biomass (AGB) of cover crops strongly influences their performance in delivering these benefits. Despite the significance of AGB, a comprehensive field-based high-throughput phenotyping study to quantify AGB of multiple cover crops in the U.S. Midwest has not been found. This study presents a two-year field experiment carried out in Eastern Nebraska, USA, to estimate AGB of five different cover crop species [canola (Brassica napus L.), rye (Secale …

Stage And Discharge Prediction From Documentary Time-Lapse Imagery, Kenneth W. Chapman, Troy E. Gilmore, Mehrube Mehrubeoglu, Christian D. Chapman, Aaron R. Mittelstet, John E. Stranzl Jr.

Department of Biological Systems Engineering: Papers and Publications

Imagery from fixed, ground-based cameras is rich in qualitative and quantitative information that can improve stream discharge monitoring. For instance, time-lapse imagery may be valuable for filling data gaps when sensors fail and/or during lapses in funding for monitoring programs. In this study, we used a large image archive (> 40,000 images from 2012 to 2019) from a fixed, ground-based camera that is part of a documentary watershed imaging project (https://plattebasintimelapse.com/). Scalar image features were extracted from daylight images taken at one-hour intervals. The image features were fused with United States Geological Survey stage and discharge data as …

Life Cycle Greenhouse Gas Emissions In Maize No-Till Agroecosystems In Southern Brazil Based On A Long-Term Experiment, Guilherme Rosa Da Silva, Adam J. Liska, Cimelio Bayer

Department of Biological Systems Engineering: Papers and Publications

Brazilian agriculture is constantly questioned concerning its environmental impacts, particularly greenhouse gas (GHG) emissions. This research study used data from a 34-year field experiment to estimate the life cycle GHG emissions intensity of maize production for grain in farming systems under no-tillage (NT) and conventional tillage (CT) combined with Gramineae (oat) and legume (vetch) cover crops in southern Brazil. We applied the Feedstock Carbon Intensity Calculator for modeling the “field-to-farm gate” emissions with measured annual soil N₂O and CH₄ emissions data. For net CO₂ emissions, increases in soil organic C (SOC) were applied as a proxy, …

Student Use Of Anchors And Metacognitive Strategies In Reflection, Anu Singh, Heidi A. Diefes-Dux

Department of Biological Systems Engineering: Papers and Publications

Context: Self-regulation, a skillset involving taking charge of one’s own learning processes, is crucial for workplace success. Learners develop self-regulation skills through reflection where they recognize weaknesses and strengths by employing metacognitive strategies: planning, monitoring, and evaluating. Use of anchors assists learners’ engagement in reflection. Purpose or Goal: The purpose of this work was to gain insight into students’ use of anchors when reflecting on their learning. The two research questions: (1) To what extent do students link their self-evaluation and learning objective (LO) self-ratings to their reflections? and (2) What dimensions and level of metacognitive strategies do students use …

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 Biological Systems Engineering: Papers and 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 Biological Systems Engineering: Papers and 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 Biological Systems Engineering: Papers and 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 Biological Systems Engineering: Papers and 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 …

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 Biological Systems Engineering: Papers and 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 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 …

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 Biological Systems Engineering: Papers and 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 Biological Systems Engineering: Papers and 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 Biological Systems Engineering: Papers and 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 Biological Systems Engineering: Papers and 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). …

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 Biological Systems Engineering: Papers and 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 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 …

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

Department of 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 …

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 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

Department of 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 …

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 Biological Systems Engineering: Papers and 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 Biological Systems Engineering: Papers and 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 Biological Systems Engineering: Papers and 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 Biological Systems Engineering: Papers and 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 Biological Systems Engineering: Papers and 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 Biological Systems Engineering: Papers and 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 …

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 Biological Systems Engineering: Papers and 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 …