Other Civil and Environmental Engineering Commons^™

Introduction To Special Issue Of Irrigation Science: Improving Irrigation Management Across The Ogallala Aquifer, Usa, Allan A. Andales, Daran Rudnick, José L. Chávez

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Groundwater stored in aquifers is a major source of irrigation water for many agricultural regions that receive insufficient precipitation for crop production. In the U.S.A., the High Plains aquifer (HPA) that underlies parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming supplies irrigation water for agricultural production. The HPA underlies around 450,658 km² (174,000 mi²) of which the Ogallala aquifer is the principal geologic formation underlying 347,059 km² (134,000 mi²) (Gutentag et al. 1984). The Ogallala aquifer is primarily a water table (unconfined) aquifer with saturated thickness ranging from 0 …

Climate Change And Market-Based Insurance Feedbacks, Eric R. Holley, Adam Liska, Cory Walters, Geoffrey C. Friesen, Michael Hayes, Max J. Rudolph, Donald A. Wilhite

Adam Liska Papers

Climatic events have accounted for 91% of $1.05 trillion in insured costs for global catastrophic events from 1980 to 2016. Costs are driven by socio-economic development and increased frequency and severity of climatic disasters driven by climate change. Government policies to reduce systemic risk (e.g., cap-and-trade, carbon tax) have been a predominant approach for mitigation and adaptation. Alternatively, market-based incentives for climate change adaptation and mitigation already operate via the insurance industry to lessen impacts on society. Insurance feedbacks include changes in 1) premiums and insurance policies, 2) non-coverage, and 3) policy making and litigation. Alongside government policies, insurance feedbacks …

Comparison Of Object Detection And Patch-Based Classification Deep Learning Models On Mid- To Late-Seasonweed Detection In Uav Imagery, Arun Narenthiran Veeranampalayam Sivakumar, Jiating Li, Stephen Scott, Eric T. Psota, Amit J. Jhala, Joe D. Luck, Jiating Li

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Mid- to late-season weeds that escape from the routine early-season weed management threaten agricultural production by creating a large number of seeds for several future growing seasons. Rapid and accurate detection of weed patches in field is the first step of site-specific weed management. In this study, object detection-based convolutional neural network models were trained and evaluated over low-altitude unmanned aerial vehicle (UAV) imagery for mid- to late-season weed detection in soybean fields. The performance of two object detection models, Faster RCNN and the Single Shot Detector (SSD), were evaluated and compared in terms of weed detection performance using mean …

Past, Present And Future Of Irrigation On The U.S. Great Plains, Steve R. Evett, Paul D. Colaizzi, Freddie R. Lamm, Susan A. O'Shaughnessy, Derek M. Heeren, Thomas J. Trout, William L. Kranz, Xiaomao Lin

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Motivated by the need for sustainable water management and technology for next-generation crop production, the future of irrigation on the U.S. Great Plains was examined through the lenses of past changes in water supply, historical changes in irrigated area, and innovations in irrigation technology, management, and agronomy. We analyzed the history of irrigated agriculture through the 1900s to the present day. We focused particularly on the efficiency and water productivity of irrigation systems (application efficiency, crop water productivity, and irrigation water use productivity) as a connection between water resource management and agricultural production. Technology innovations have greatly increased the efficiency …

Retention Of Swine Slurry Constituents In Soil And Crop Residue As Affected By Setback Distance, John E. Gilley, Shannon L. Bartelt-Hunt, Kent M. Eskridge, Xu Li, Amy M. Schmidt, Daniel D. Snow

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Setbacks are prescribed distances from surface waters within which manure application is not allowed. Little information is available concerning the retention of swine slurry constituents in soil and crop residue materials within setback areas. This study was conducted to measure the retention of selected constituents within a setback area following the upslope application of swine slurry and the introduction of simulated rainfall. The no-till cropland site had a slope gradient of 4.9% and a mean winter wheat residue cover of 7.73 Mg ha−1 . Soil and vegetative samples were collected on 3.7 m wide by 23.2 m long plots with …

Economic Comparisons Of Variable Rate Irrigation And Fertigation With Fixed (Uniform) Rate Irrigation And Fertigation And Pre-Plant Fertilizer Management For Maize In Three Soils, Vasudha Sharma, Suat Irmak

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Extensive field research for data collection to conduct economic comparisons of variable rate irrigation (VRI) with fixed (uniform) rate irrigation (FRI) and no irrigation (NI) in combination with three nitrogen application strategies of fixed (uniform) rate fertigation (FRF), variable rate fertigation (VRF) and pre-plant nitrogen (PP) management for maize (Zea mays L.) were conducted. Research was conducted in three soil types [(i) Crete silt loam (S1); (ii) Hastings silty clay loam (S2); and (iii) Hastings silt loam (S3)] for three growing seasons (2015, 2016 and 2017) in Nebraska, USA. For the economic analyses, the average initial investment of the …

Extracellular Matrix Disparities In An Nkx2-5 Mutant Mouse Model Of Congenital Heart Disease, Deanna Bousalis, Christopher S. Lacko, Nora Hlavac, Fariz Alkassis, Rebecca A. Wachs, Sahba Mobini, Christine E. Schmidt, Hideko Kasahara

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Congenital heart disease (CHD) affects almost one percent of all live births. Despite diagnostic and surgical reparative advances, the causes and mechanisms of CHD are still primarily unknown. The extracellular matrix plays a large role in cell communication, function, and differentiation, and therefore likely plays a role in disease development and pathophysiology. Cell adhesion and gap junction proteins, such as integrins and connexins, are also essential to cellular communication and behavior, and could interact directly (integrins) or indirectly (connexins) with the extracellular matrix. In this work, we explore disparities in the expression and spatial patterning of extracellular matrix, adhesion, and …

Development Of An In Vitro Intervertebral Disc Innervation Model To Screen Neuroinhibitory Biomaterials, Sarah M. Romereim, Caleb A. Johnston, Adan L. Redwine,, Rebecca A. Wachs

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Pain originating from an intervertebral disc (discogenic pain) is a major source of chronic low back pain. Pathological innervation of the disc by pain‐sensing nerve fibers is thought to be a key component of discogenic pain, so treatment with biomaterials that have the ability to inhibit neurite growth will greatly benefit novel disc therapeutics. Currently, disc therapeutic biomaterials are rarely screened for their ability to modulate nerve growth, mainly due to a lack of models to screen neuromodulation. To address this deficit, our lab has engineered a three dimensional in vitro disc innervation model that mimics the interface between primary …

Evaluation Of Low-Cost Depth Cameras For Agricultural Applications, Isabella C.F.S. Condotta, Tami M. Brown-Bandl, Santosh Pitla, John P. Stinn, Késia O. Silva-Miranda

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Low-cost depth-cameras have been used in many agricultural applications with reported advantages of low cost, reliability and speed of measurement. However, some problems were also reported and seem to be technology related, so understanding the limitations of each type of depth camera technology could provide a basis for technology selection and the development of research involving its use. The cameras use one or a combination of two of the three available technologies: structured light, time-of-flight (ToF), and stereoscopy. The objectives were to evaluate these different technologies for depth sensing, including measuring accuracy and repeatability of distance data and measurements at …

Biological Systems Engineering, Asmaa Abdella, Fernando Segato, Mark R. Wilkins

Department of Agricultural and Biological Systems Engineering: Faculty Publications

The present work studied the optimization of aeration rate, agitation rate and oxygen transfer and the use of various batch fermentation strategies for xylanase production from a recombinant Aspergillus nidulans strain in a 3 L stirred tank reactor. Maximum xylanase production of 1250 U/mL with productivity of 313 U/mL/day was obtained under an aeration rate of 2 vvm and an agitation rate of 400 rpm using batch fermentation. The optimum volumetric oxygen transfer coefficient (kLa) for efficient xylanase production was found to be 38.6 h1. Fed batch mode and repeated batch fermentation was also performed with kLa was 38.6 h1. …

Capturing Spatial Variability In Maize And Soybean Using Stationary Sensor Nodes, Jasreman Singh, Derek M. Heeren, Yufeng Ge, Geng Bai

Department of Agricultural and Biological Systems Engineering: Faculty Publications

• Irrigation in agriculture maximizes crop yield and improves food security globally • Irrigation scheduling is strongly based on the ability to accurately estimate the appropriate amount and timing of water application • The timing of the irrigation can best be informed through the crop canopy stress, and the amount of irrigation is informed through soil moisture depletion

• Developing upper (non-water stressed) and lower (non-transpiring) baselines for irrigated and non-irrigated maize and soybean • Investigating the relationship between the canopy stress and the soil moisture stress

The canopy temperature stress and soil moisture depletion had stronger correlation for non-irrigated …

Evidence Of Arithmetical Uncertainty In Estimation Of Light And Water Use Efficiency, Meetpal S. Kukal, Suat Irmak Dr.

Department of Agricultural and Biological Systems Engineering: Faculty Publications

It was demonstrated that conventional resource use efficiency (RUE) estimation methodology is largely subject to arithmetic weakness. Extensive field research data on aboveground biomass (AGB), absorbed photosynthetically active radiation (APAR), and crop evapotranspiration (ETc) in maize, soybean, sorghum, and winter wheat confirmed this methodological bias for light use efficiency (LUE) and water use efficiency (WUE) estimation. LUE and WUE were derived using cumulated (data aggregates across samplings) and independent (data increments across samplings) approaches. Use of cumulated data yielded strong-but-false correlation between AGB and APAR or Etc, being a statistical artefact. RUE values from an independent (data increments across samplings) …

Predicting Escherichia Coli Loads In Cascading Dams With Machine Learning: An Integration Of Hydrometeorology, Animal Density And Grazing Pattern, Olufemi P. Abimbola, Aaron R. Mittelstet, Tiffany Messer, Elaine D. Berry, Shannon L. Bartelt-Hunt, Samuel Hansen

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Accurate prediction of Escherichia coli contamination in surface waters is challenging due to considerable uncertainty in the physical, chemical and biological variables that control E. coli occurrence and sources in surface waters. This study proposes a novel approach by integrating hydro-climatic variables as well as animal density and grazing pattern in the feature selection modeling phase to increase E. coli prediction accuracy for two cascading dams at the USMeat Animal Research Center (USMARC), Nebraska. Predictive models were developed using regression techniques and an artificial neural network (ANN). Two adaptive neuro-fuzzy inference system (ANFIS) structures including subtractive clustering and fuzzy c-means …

Banning Carbon Nanotubes Would Be Scientifically Unjustified And Damaging To Innovation, Daniel A. Heller, Prakrit V. Jena, Matteo Pasquali, Kostas Kostarelos, Lucia G. Delogu, Rachel E. Meidl, Slava V. Rotkin, David A. Scheinberg, Robert E. Schwartz, Mauricio Terrones, Yu Huang Wang, Alberto Bianco, Ardemis A. Boghossian, Sofie Cambré, Laurent Cognet, Simon R. Corrie, Philip Demokritou, Silvia Giordani, Tobias Hertel, Tetyana Ignatova, Mohammad F. Islam, Nicole M. Iverson, Anand Jagota, Dawid Janas, Junichiro Kono, Sebastian Kruss, Markita P. Landry, Yan Li, Richard Martel, Shigeo Maruyama, Anton V. Naumov, Maurizio Prato, Susan J. Quinn, Daniel Roxbury, Michael S. Strano, James M. Tour, R. Bruce Weisman, Wim Wenseleers, Masako Yudasaka

Department of Agricultural and Biological Systems Engineering: Faculty Publications

In a recent correspondence, the Swedish non-profit organization ChemSec announced the addition of carbon nanotubes to the SIN (‘Substitute It Now’) list1. Carbon nanotubes were added as an entire material class that “should be restricted or banned in the EU.” We believe that this recommendation confuses researchers and the public as it is based on evidence from a very narrow subset of data. Such a designation will likely hinder innovations that could lead to safe and effective applications of carbon nanotubes. Furthermore, this line of reasoning could damage other fields of science and technology, if applied similarly. We have worked …

Field Assessment Of Interreplicate Variability From Eight Electromagnetic Soil Moisture Sensors, Tsz Him Lo, Daran Rudnick, Jasreman Singh, Hope Njuki Nakabuye, Abia Katimbo, Derek M. Heeren, Yufeng Ge

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Interreplicate variability—the spread in output values among units of the same sensor subjected to essentially the same condition—can be a major source of uncertainty in sensor data. To investigate the interreplicate variability among eight electromagnetic soil moisture sensors through a field study, eight units of TDR315, CS616, CS655, HydraProbe2, EC5, 5TE, and Teros12 were installed at a depth of 0.30 m within 3 m of each other, whereas three units of AquaSpy Vector Probe were installed within 3 m of each other. The magnitude of interreplicate variability in volumetric water content (θ_v) was generally similar between a static …

Development And Application Of A Performance And Operational Feasibility Guide To Facilitate Adoption Of Soil Moisture Sensors, Meetpal S. Kukal, Suat Irmak, Kiran Sharma

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Soil moisture sensors can be effective and promising decision-making tools for diverse applications and audiences, including agricultural managers, irrigation practitioners, and researchers. Nevertheless, there exists immense adoption potential in the United States, with only 1.2 in 10 farms nationally using soil moisture sensors to decide when to irrigate. This number is much lower in the global scale. Increased adoption is likely hindered by lack of scientific support in need assessment, selection, suitability and use of these sensors. Here, through extensive field research, we address the operational feasibility of soil moisture sensors, an aspect which has been overlooked in the past, …

Prediction Of Neighbor-Dependent Microbial Interactions From Limited Population Data, Joon-Yong Lee, Shin Haruta, Souichiro Kato, Hans C. Bernstein, Stephen R. Lindemann, Dong-Yup Lee, Jim K. Fredrickson, Hyun-Seob Song

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Modulation of interspecies interactions by the presence of neighbor species is a key ecological factor that governs dynamics and function of microbial communities, yet the development of theoretical frameworks explicit for understanding context-dependent interactions are still nascent. In a recent study, we proposed a novel rule-based inference method termed the Minimal Interspecies Interaction Adjustment (MIIA) that predicts the reorganization of interaction networks in response to the addition of new species such that the modulation in interaction coefficients caused by additional members is minimal. While the theoretical basis of MIIA was established through the previous work by assuming the full availability …

Effects Of Farrowing Stall Layout And Number Of Heat Lamps On Sow And Piglet Production Performance, Suzanne M. Leonard, Hongwei Xin, Tami M. Brown-Bandl, Brett C. Ramirez, Somak Dutta, Gary A. Rohrer

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Most farrowing facilities in the United States use stalls and heat lamps to improve sow and piglet productivity. This study investigated these factors by comparing production outcomes for three different farrowing stall layouts (traditional, expanded creep area, expanded sow area) and use of one or two heat lamps. Data were collected on 427 sows and their litters over one year. Results showed no statistical differences due to experimental treatment for any of the production metrics recorded, excluding percent stillborn. Parity one sows had fewer piglets born alive (p < 0.001), lower percent mortality (p = 0.001) and over-lay (p = 0.003), and a …

Influence Of Watershed Characteristics On Streambed Hydraulic Conductivity Across Multiple Stream Orders, Olufemi P. Abimbola, Aaron R. Mittelstet, Troy E. Gilmore, Jesse T. Korus

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Streambeds are critical hydrological interfaces: their physical properties regulate the rate, timing, and location of fluxes between aquifers and streams. Streambed vertical hydraulic conductivity (K_v) is a key parameter in watershed models, so understanding its spatial variability and uncertainty is essential to accurately predicting how stresses and environmental signals propagate through the hydrologic system. Most distributed modeling studies use generalized K_v estimates from column experiments or grain-size distribution, but K_v may include a wide range of orders of magnitude for a given particle size group. Thus, precisely predicting K_v spatially has remained conceptual, experimental, …

Calibration Of A Common Shortwave Multispectral Camera System For Quantitative Agricultural Applications, J. Burdette Barker, Wayne Woldt, Brian Wardlow, Christopher Michael Usher Neale, Mitchell S. Maguire, Bryan Leavitt, Derek M. Heeren

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Unmanned aerial systems (UAS) for collecting multispectral imagery of agricultural fields are becoming more affordable and accessible. However, there is need to validate calibration of sensors on these systems when using them for quantitative analyses such as evapotranspiration, and other modeling for agricultural applications. The results of laboratory testing of a MicaSense (Seattle, WA, USA) RedEdge™ 3 multispectral camera and MicaSense Downwelling Light Sensor (irradiance sensor) system using a calibrated integrating sphere were presented. Responses of the camera and irradiance sensor were linear over many light levels and became non-linear at light levels below expected real-world, field conditions. Simple linear …

High-Throughput Screening Of Clinically Approved Drugs That Prime Nonviral Gene Delivery To Human Mesenchymal Stem Cells, Tyler Kozisek, Andrew Hamann, Albert Nguyen, Michael Miller, Sarah Plautz, Angela K. Pannier

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Background: Human mesenchymal stem cells (hMSCs) are intensely researched for applications in cell therapeutics due to their unique properties, however, intrinsic therapeutic properties of hMSCs could be enhanced by genetic modification. Viral transduction is efficient, but suffers from safety issues. Conversely, nonviral gene delivery, while safer compared to viral, suffers from inefficiency and cytotoxicity, especially in hMSCs. To address the shortcomings of nonviral gene delivery to hMSCs, our lab has previously demonstrated that pharmacological ‘priming’ of hMSCs with the glucocorticoid dexamethasone can significantly increase transfection in hMSCs by modulating transfection-induced cytotoxicity. This work seeks to establish a library of transfection …

An Automated Seepage Meter For Streams And Lakes, D. Kip Solomon, Eric Humphrey, Troy E. Gilmore, David P. Genereux, Vitaly Zlotnik

Department of Agricultural and Biological Systems Engineering: Faculty Publications

We describe a new automatic seepage meter for use in soft bottom streams and lakes. The meter utilizes a thin‐walled tube that is inserted into the streambed or lakebed. A hole in the side of the tube is fitted with an electric valve. Prior to the test, the valve is open and the water level inside the tube is the same as the water level outside the tube. The test starts with closure of the valve, and the water level inside the tube changes as it moves toward the equilibrium hydraulic head that exists at the bottom of the tube. …

Deep Learning Predicts Microbial Interactions From Self-Organized Spatiotemporal Patterns, Joon-Yong Lee, Natalie C. Sadler, Robert G. Egbert, Christopher R. Anderton, Kirsten S. Hofmockel, Janet K. Jansson, Hyun-Seob Song

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Microbial communities organize into spatial patterns that are largely governed by interspecies interactions. This phenomenon is an important metric for understanding community functional dynamics, yet the use of spatial patterns for predicting microbial interactions is currently lacking. Here we propose supervised deep learning as a new tool for network inference. An agent-based model was used to simulate the spatiotemporal evolution of two interacting organisms under diverse growth and interaction scenarios, the data of which was subsequently used to train deep neural networks. For small-size domains (100 mm x 100 mm) over which interaction coefficients are assumed to be invariant, we …

Swine Slurry Characteristics As Affected By Selected Additives And Disinfectants, Jon Duerschner, Shannon L. Bartelt-Hunt, Kent Eskridge, John E. Gilley, Xu Li, Amy M. Schmidt, Daniel D. Snow

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Current swine industry practice is to house animals in confinement facilities which capture and store feces and urine as slurry in pits below the production area. Additives and disinfectants may be introduced into the manure pits. This study was conducted to measure the effects of additives and disinfectants on temporal changes in swine slurry characteristics. Slurry from a commercial swine production facility in southeast Nebraska, USA was collected and transferred to 57 L reactors located within a greenhouse. Selected additives and disinfectants were added to the reactors and physical properties, chemical characteristics, and antibiotic concentrations were monitored for 40 days. …

Evaluation Of Low-Cost Depth Cameras For Agricultural Applications, Isabella C.F.S. Condotta, T. M. Brown-Brandl, Santosh Pitla, John P. Stinn, Késia O. Silva-Miranda

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Low-cost depth-cameras have been used in many agricultural applications with reported advantages of low cost, reliability and speed of measurement. However, some problems were also reported and seem to be technology- related, so understanding the limitations of each type of depth camera technology could provide a basis for technology selection and the development of research involving its use. The cameras use one or a combination of two of the three available technologies: structured light, time-of-flight (ToF), and stereoscopy. The objectives were to evaluate these different technologies for depth sensing, including measuring accuracy and repeatability of distance data and measurements at …

Ultrasmall Mixed Eu−Gd Oxide Nanoparticles For Multimodal Fluorescence And Magnetic Resonance Imaging Of Passive Accumulation And Retention In Tbi, Badrul Alam Bony, Hunter A. Miller, Aria W. Tarudji, Connor C. Gee, Anandakumar Sarella, Michael G. Nichols, Forrest Kievit

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Traumatic brain injury (TBI) is a leading cause of death and disability worldwide. TBI can have a long-term impact on the quality of life for survivors of all ages. However, there remains no approved treatment that improves outcomes following TBI, which is partially due to poor delivery of therapies into the brain. Therefore, there is a significant unmet need to develop more effective delivery strategies that increase the accumulation and retention of potentially efficacious treatments in the injured brain. Recent work has revealed that nanoparticles (NPs) may offer a promising approach for site-specific delivery; however, a detailed understanding of the …

Optimal Depth Jump Height Quantified As Percentage Of Athlete Stature, Curtis L. Tomasevicz, Ryan Hasenkamp, Jack W. Ransone, David Jones

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Purpose: An individual’s optimal depth jump platform height provides a resistive force which allows an athlete to rebound with substantial velocity resulting in maximum power exertion. The objective of this investigation was to show that the optimal platform height in a depth jump can be quantified as a percentage of individual body stature which can serve as measurable quantified value. Although athlete height is not highly correlated to power ability nor does a universal height exist, this value can provide a basis for a rehabilitation or strength and conditioning program. The desired intensity of a program can be prescribed as …

Comparison Of Object Detection And Patch-Based Classification Deep Learning Models On Mid- To Late-Season Weed Detection In Uav Imagery, Arun Narenthiran Veeranampalayam Sivakumar, Jiating Li, Stephen Scott, Eric T. Psota, Amit J. Jhala, Joe D. Luck, Yeyin Shi

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Mid- to late-season weeds that escape from the routine early-season weed management threaten agricultural production by creating a large number of seeds for several future growing seasons. Rapid and accurate detection of weed patches in field is the first step of site-specific weed management. In this study, object detection-based convolutional neural network models were trained and evaluated over low-altitude unmanned aerial vehicle (UAV) imagery for mid- to late-season weed detection in soybean fields. The performance of two object detection models, Faster RCNN and the Single Shot Detector (SSD), were evaluated and compared in terms of weed detection performance using mean …

Representing Organic Matter Thermodynamics In Biogeochemical Reations Via Substrate-Explicit Modeling, Hyun-Seob Song, James C. Stegen, Emily B. Graham, Joon-Yong Lee, Vanessa A. Garayburu-Caruso, William C. Nelson, Xingyuan Chen, J. David Moulton, Timothy D. Scheibe

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Predictive biogeochemical modeling requires data-model integration that enables explicit representation of the sophisticated roles of microbial processes that transform substrates. Data from high-resolution organic matter (OM) characterization are increasingly available and can serve as a critical resource for this purpose, but their incorporation into biogeochemical models is often prohibited due to an over-simplified description of reaction networks. To fill this gap, we proposed a new concept of biogeochemical modeling—termed substrate-explicit modeling—that enables parameterizing OM-specific oxidative degradation pathways and reaction rates based on the thermodynamic properties of OM pools. Based on previous developments in the literature, we characterized the resulting kinetic …

Automatic Wheat Lodging Detection And Mapping In Aerial Imagery To Support High-Throughput Phenotyping And In-Season Crop Management, Biquan Zhao, Jiating Li, P. Stephen Baenziger, Vikas Belamkar, Yufeng Ge, Jian Zhang, Yeyin Shi

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Latest advances in unmanned aerial vehicle (UAV) technology and convolutional neural networks (CNNs) allow us to detect crop lodging in a more precise and accurate way. However, the performance and generalization of a model capable of detecting lodging when the plants may show different spectral and morphological signatures have not been investigated much. This study investigated and compared the performance of models trained using aerial imagery collected at two growth stages of winter wheat with different canopy phenotypes. Specifically, three CNN-based models were trained with aerial imagery collected at early grain filling stage only, at physiological maturity only, and at …