Bioresource and Agricultural Engineering Commons^™

Nebraska And The Midwest Agtech Ecosystem: Benchmarking Innovation Investment And Translation Gaps, Ankit Chandra, Ishani Lal, Brennan Costello

Department of Agricultural and Biological Systems Engineering: Presentations and White Papers

Agricultural innovation is central to the sustainable transformation of food systems, yet the capital that finances it is unevenly distributed relative to where food is produced. This paper develops a diagnostic framework for measuring this mismatch and applies it across the U.S. Midwest from 2021 to 2025, with particular emphasis on Nebraska's structural position within this landscape. Drawing on venture capital deal-flow data, 17 stakeholder interviews, and a novel strength-weakness-opportunity-gap (SWOG) ecosystem mapping methodology, we document $736 million in tracked Midwest AgTech funding across eight states (Nebraska, Iowa, Missouri, Illinois, Indiana, Kansas, North Dakota, and South Dakota). We introduce three …

Evaluation Of A Vortex Flow Device On A Center Pivot Irrigation System, Ankit Chandra, Derek M. Heeren, Tyler Smith

Department of Agricultural and Biological Systems Engineering: Presentations and White Papers

This study presents the first independent field evaluation of a passive vortex flow device designed to reduce hydraulic friction in pressurized irrigation systems. Experiments were conducted on a full-scale, groundwater-fed center pivot irrigation system at the Eastern Nebraska Research, Extension, and Education Center (ENREEC). A paired comparison approach was used to quantify differences in flow rate, energy consumption, and pressure distribution along the pivot lateral under baseline (no device) and treatment (device installed) conditions. Results showed negligible change in system flow rate (621 vs. 618 gpm) and energy consumption (~1.2% difference), consistent with expectations for pressure-regulated irrigation systems. However, the …

Can Generative Ai Make Farming Decisions? Current Status And Future Pathways: A Case Study In Row Crop Production With Chatgpt, Nipuna Chamara, Yufeng Ge, Joe Luck, Yu Pan, Saleh Taghvaeian, Cory Walters, Christopher Proctor, Daran Rudnick, Daren Redfearn

Department of Agricultural and Biological Systems Engineering: Faculty Publications

The agricultural decision-making process is experience-based, knowledge-dependent, time-sensitive, complex, and driven by historical data. Planting, fertilization, irrigation, and chemigation are key categories in farm decision-making, and currently there is no one-shot decision-support tool that covers all these activities. Generative Artificial Intelligence (AI) models are more advanced than traditional machine learning and deep learning models. These models have been trained on vast amounts of data from the internet, allowing them to accept unstructured data in various forms and generate human-like text, solutions to problems, and scenario predictions. Given this capability, we became interested in exploring the potential of generative AI in …

Thermodynamic Modeling Of Ph Impacts On Subsurface Microbial Consortia, Jackfin K C

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

Underground hydrogen storage is affected by microbial consumption, and the different minerals present in the subsurface. However, most studies consider either biotic or abiotic factors in isolation and hence, the conditions that drive a self-sustaining storage remain poorly understood. This thesis uses a genome-informed thermodynamic model developed by Kharel et al. (2026) in which pH is the central variable coupling hydrogenotrophic microbial metabolism, inter-species competition, and carbonate mineral buffering. The model includes four hydrogen-consuming species: methanogen (Methanobacterium), acetogen (Acetoanaerobium), aerobic acetate oxidizer (Pseudomonas stutzeri), and sulfate reducer (Nitratidesulfovibrio) by conditioning each organism's …

Undergraduate Design Spine For Biological Systems Engineering And Agricultural Engineering, David Mabie, Derek M. Heeren, Deepak R. Keshwani, Heidi A. Diefes-Dux, Nicole M. Iverson, Rachel Padrnos, Greg Bashford, Taryn King, Jenna Hefley, Curtis L. Tomasevicz

Department of Agricultural and Biological Systems Engineering: Presentations and White Papers

Engineering education is undergoing a shift toward preparing graduates with demonstrated capabilities that integrate technical knowledge, durable skills, and the ability to adapt in a rapidly evolving professional landscape. This paper describes a comprehensive redesign of the undergraduate curriculum in Biological Systems Engineering (BSEN) and Agricultural Engineering (AGEN) at the University of Nebraska–Lincoln. The redesign is grounded in a “Design Spine” framework, which distributes and scaffolds design experiences across all four years of the program to support progressive development of problem solving, systems thinking, communication, and professional skills. The curriculum is organized around clearly defined capabilities and threads that connect …

Assessment Of Super Absorbent Polymer In Soybean Cultivation Under Variable Irrigation Conditions In Nebraska, Ankit Chandra, Abia Katimbo, Ronaldo Marchezan, Martha Nabaggala

Department of Agricultural and Biological Systems Engineering: Presentations and White Papers

Water limitation is a primary constraint to soybean productivity in both irrigated and rainfed systems. Soil-applied superabsorbent polymers (SAPs) have been proposed as a strategy to buffer crops against episodic drought stress; however, their physiological and agronomic performance under varying irrigation regimes remains insufficiently quantified. Here, we evaluate three biodegradable polymer formulations: broader granules (BB), original granules (OG), and powder (PWR) applied at low (17.7 lb/ac) and high (120 lb/ac) rates under full (100% ET), reduced (50% ET), and no irrigation conditions in western Nebraska. Polymer application had negligible effects under full irrigation, with yields comparable to untreated controls. Under …

A New Electroencephalography Electrode Design For Curly And Kinky Hair Types, Elena Butler

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

Medical discrimination and implicit bias are present in both societal systems and into the design and validation of medical devices. Traditional electroencephalography (EEG) systems often fail to provide reliable physiological recordings on curly and kinky hair types (3B–4C), associated typically with Black American and others of African descent. EEG on these hair types often results in high electrode-scalp impedance, poor signal quality, and participant discomfort. Consequently, such technical biases contribute to the underrepresentation of these populations in neuroscience research and clinical diagnostics, while simultaneously limiting equitable access to EEG-based medical care.

To address this gap, a novel conductive electrode attachment …

Beyond Local Pathology: Exploring The Role Of Gut Microbiota In Chronic Low Back Pain Using An Integrated Behavioral And Microbiological Approach, Adan L. Redwine

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

Chronic low back pain (LBP) affects millions worldwide, often originating from intervertebral disc (IVD) degeneration. While the gut microbiome modulates musculoskeletal pain, prior studies of the gut-disc axis have focused entirely on structural changes. This leaves a critical gap: does the microbiome influence the experience of discogenic pain? To answer this, an integrated approach using longitudinal gut microbiome profiling, machine learning-based behavioral phenotyping, and structural disc assessments in a rat model of discogenic LBP was utilized.

Female Sprague Dawley rats underwent one of four conditions: sham surgery, IVD injury, antibiotic-mediated microbiome depletion + IVD injury, or IVD injury + treatment …

Understanding Agtech Adoption: Evidence From The Farm Tech Adoption Challenge 2025, Ankit Chandra, Mark Stone

Department of Agricultural and Biological Systems Engineering: Presentations and White Papers

The Farm Tech Adoption Challenge (FTAC) examined how farmers evaluate emerging agricultural technologies through structured interactions with startups. Farmers assessed solutions based on their on-farm challenges and indicated adoption decisions. Results showed that adoption was driven by how well technologies addressed economic pressure, risk reduction, and operational simplicity. Startups aligned with these priorities were more likely to gain traction, with five out of nine receiving farmer commitments for adoption. However, adoption also depended on clear economic value, field validation, and system integration. Overall, the findings suggest that the primary bottleneck in agtech is not the lack of relevant technologies, but …

Why Agtech Startups Fail? Evidence From Global Shutdown Patterns In 2025 And The Cost-Adoption Mismatch Effect, Ankit Chandra, Ishani Lal

Department of Agricultural and Biological Systems Engineering: Presentations and White Papers

Agricultural technologies are widely seen as a driver for sustainability, resilience, and food-system transformation. Yet in 2025, agtech startup across North America, Europe, Asia, and Africa experienced multiple shutdowns. Although each company closed for its own reasons, the failures highlight consistent underlying patterns. We analyze 18 publicly reported shutdowns across controlled-environment agriculture (CEA), robotics, insect protein, digital platforms, sensors, and ag-biotechnology. We find that most ventures struggled not with scientific feasibility but with economic and adoption dynamics at the farm level. We identify a Cost-Adoption Mismatch Effect, in which the capital and operational burden of a technology exceeds farmers’ capacity …

Ammonia Synthesis By Nanosecond Pulsed Atmospheric Pressure Plasma Jets Impinging On Water, Zach Caudell, Lynnet Rich, Olga Pakhomova, Chunqi Jiang

Bioelectrics Publications

Developing energy-efficient technologies for carbon-neutral ammonia (NH₃) synthesis is critical for decentralized fertilizer production and global decarbonization. This study investigates generating NH₃ from water using a nanosecond pulsed atmospheric pressure plasma jet (ns‑APPJ) operating in either N₂ or dry air. The plasma jet reactor employed approximately 250 ns, up-to-22 kV pulses at 500 Hz to sustain a nonequilibrium discharge impinging directly on static liquid water. The kinetics, energy efficiency, and product selectivity of NH3 formation were quantified as functions of the pulse voltage, repetition frequency (PRF), and gas flow rate. NH₃ production increased linearly with treatment time and scaled strongly …

Design And Fabrication Of A Scaled Automated Dairy Farm Model: A Report, Md Towfiqur Rahman

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Summary

This study investigates how ventilation systems work in dairy barns and builds a scaled model to support education and research. The project is designed to help students from the University of Nebraska–Lincoln (UNL), K-12 learners, and researchers in animal science, veterinary medicine, and engineering gain visual experience with dairy facility components and processes. Different ventilation methods were studied, leading to the design of a 1/64-scale tunnel-ventilated dairy barn meant for 60 Holstein Friesian cows. Barn dimensions were set based on real Holstein cow measurements to ensure proper cow comfort, while airflow requirements were calculated and scaled down. Miniature fans …

The Transport Of New Make Spirits Through American White Oak, Taylor E. Scott, Jarrad Gollihue, Michael P. Sama, Michael Shaffer, Brad J. Berron

Biosystems and Agricultural Engineering Faculty Publications

Why was the work done: The reduction of maturation loss is a significant opportunity for increased revenue in aged spirits and varies through several factors. This work aims to better understand maturation loss by isolating and measuring spirit flow through wood.

How was the work done: Bourbon stave disks were fabricated by computer numeric control milling and loaded into a sealed module consisting of flanges holding the stave disk over a liquid filled pipe. The modules were filled with new make spirit at 50, 62.5 or 70% ABV, with either liquid or vapour contact with the stave disk. Further, the …

Co-Encapsulation Of Microalgae Haematococcus Pluvialis And Lactic Acid Bacteria Lacticaseibacillus Casei Via Filamentous Fungi Scaffolds Improved Probiotic Viability In Simulated Gastro-Intestinal Conditions, Suvro Talukdar, Tyler J. Barzee

Biosystems and Agricultural Engineering Faculty Publications

Fungal-assisted cell immobilization has emerged as a promising approach for food, energy and environmental applications, utilizing the hyphal network of filamentous fungi to encapsulate microorganisms. Co-encapsulation of multiple microorganisms within fungal pellets enables the development of food delivery systems that combine complementary functional and nutritional properties, including enhanced probiotic protection and delivery of bioactive compounds. This study used edible filamentous fungus Aspergillus awamori to encapsulate Haematococcus pluvialis microalgae and Lacticaseibacillus casei lactic acid bacteria (LAB) for probiotic delivery. Both active and heat-deactivated pellets successfully co-encapsulated microalgae and LAB, although low shear conditions were required for inactive fungal states. Under in-vitro …

Exploring Relational Farming Futures For Responsible Innovation In Precision Agriculture Through Q-Method And Speculative Design, Bhavna Joshi, Maaz Gardezi, Edward Prutzer, Awais Hameed Khan, Asim Zia, Benjamin E. K. Ryan, Ali Dadkhah, Donna M. Rizzo, John T. Mcmaine, David Clay

Biosystems and Agricultural Engineering Faculty Publications

This article draws on concepts of speculative design and responsible innovation to examine the possible impacts of data-driven precision agriculture on farmers and farm work. We use an innovative mixed-method approach to research design. Using artistic depiction of futures of precision agriculture in design workshop and in-depth semistructured interviews conducted with the farmers in Vermont and South Dakota, we explain how farmers perceive different futures of precision agriculture. Specifically, in our design workshop, we combined visual arts and social science methods, namely Q-method, to explore existing and new relationships between humans, technologies, and environment in the design, deployment, and use …

Deep Learning Framework For Sow Posture Classification From Depth Images: Comparison With Data Transformation Techniques, Models, And Cross-Validation, Md Towfiqur Rahman, Tami M. Brown-Brandl, Gary A. Rohrer, Sudhendu R. Sharma, Suzanne M. Leonard, Yeyin Shi

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Piglet preweaning mortality (PWM) in the United States averages ≈14–15%, with sow overlaying causing about one third proportion of these losses. This research aimed to develop and evaluate deep learning models to classify six sow postures using depth images to monitor behaviors linked to overlaying risk. Top-down depth images were captured with Kinect V2^® cameras at 10 frames min^-1 for five consecutive days (2 days before to 2 days after farrowing), yielding 26,506 training images from 18 sows, 17,901 testing images from 12 sows, and 4,697 additional images from three sows in diagonal stalls for external validation. Three …

Assessment Of Soybean Response To Irrigation Variability In Eastern Nebraska Using The Aquacrop Model, Anmol Singh, Saleh Taghvaeian, Yufeng Ge, Derek M. Heeren, Frank Bai

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Soybean [Glycine max (L.) Merr.] is a major irrigated crop in eastern Nebraska, where recent expansions in irrigated agriculture and projected trends in irrigation demand necessitate thorough investigations of approaches that can optimize its irrigation management. In this study, the AquaCrop model was calibrated and validated using 19 variable irrigation treatments from a five-year field experiment. The model accurately simulated canopy cover, soil water content, and grain yield, with validation normalized root mean square error (nRMSE) of 12%, 7%, and 7%, respectively. The model was subsequently applied to estimate soybean yield and water requirement during a 15-year period (2010–2024) …

Mechanical Quality Of Hemp Fiber As Influenced By Tillage, Cover Crop, And Nitrogen Management In Regenerative Organic Systems, Parinaz Heydar, Alyssa Pierce, Gabriella Fioravanti, Ronald Kander

School of Design and Engineering Papers

Industrial hemp (Cannabis sativa L.) is an emerging crop for renewable fiber materials. For farmers, finding a balance between agronomic performance and economic return is crucial, especially when targeting specific markets like the textile industry, which values not just fiber quantity, but overall quality. This field study, conducted at the Rodale Institute in Kutztown, Pennsylvania, assessed the effects of tillage (till vs. no till), cover crop (with cover vs. no cover), and nitrogen (N) rate (0, 50, 100, 150 kg ha⁻¹) on hemp fiber yield, N concentrations in leaf and stalk, and mechanical performance under regenerative organic conditions. Fiber mechanical …

Deep-Learning-Enhanced Automated Coherent-Light Diffraction System For High-Speed, Highly Accurate Strain-Specific Foodborne Bacterial Recognition, Yang Tian, Ziyu Liu, Yinuo Huang, Ramesh Bahadur Bist, Yiting Xiao, Samantha Marrianne Howe, Tsung Cheng Tsai, Terry Howell, Jeyam Subbiah, Michael L. Looper, Dongyi Wang

Biological and Agricultural Engineering Faculty Publications and Presentations

Rapid, accurate differentiation of bacterial pathogens at both species and strain levels is critical for clinical diagnostics, food safety, and epidemiological surveillance. We report a fully automated laser-diffraction platform that achieves rapid, label-free identification of bacterial pathogens at both species and strain levels. The system integrates dual cameras, an automated X-Y stage, and deep-learning classifiers to deliver sub-second, nondestructive diagnostics without reagents or culture. Using diffraction patterns from eight strains, including Escherichia coli O157:H7, K12, ATCC 25922, F18, Salmonella enterica, Listeria monocytogenes, Listeria innocua, and Staphylococcus aureus, a custom YOLO11x model attained 100 % Top-1 accuracy under five-fold stratified cross-validation …

In-Field Tractor Operational Load Profile Generation In Support Of Advanced Tractor Testing In Mixedmode Power, Andrew Donesky

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This dissertation addresses the need to better characterize real-world tractor power requirements across drawbar, power take-off (PTO), and hydraulic modes to support more representative tractor testing. Conventional testing protocols, such as OECD Code 2, emphasize steady-state performance under controlled high-load conditions, which do not reflect the mixed and dynamic demands of modern field operations. To address this gap, a Tractor Instrumentation System (TIS) was developed, validated, and deployed to collect high-resolution, mixed-mode power data during planting, anhydrous ammonia application, and grain cart operations. The TIS integrates physical sensors, including custom load pins, hydraulic pressure/flow sensors, and a redesigned PTO torque …

An Integrated Modeling Framework To Evaluate Circularity Of The Corn–Water–Ethanol–Beef Nexus, Heydi Han

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This dissertation examines the transition from conventional linear agricultural and food bioenergy systems toward more circular, resilient, and resource-efficient configurations. Prior research indicates that spatial and temporal variability in soil, weather, animal biological responses, and management decisions strongly influences productivity, nutrient-use efficiency, and profitability. Studies have also shown that a diversified circular system can buffer these sources of variability, improving stability and adaptive capacity. Building on these insights, the central focus of this work is to develop an integrated modeling framework to evaluate circularity within the Corn-Water-Ethanol-Beef (CWEB) nexus and explore how climate variability and management choices shape system-wide performance. …

Locations Of Outfalls In The Indian River Lagoon And Lake Worth Lagoon, Florida, Kelly M. Kibler, Melinda J. Donnelly, Vincent Encomio, Madison Giuntoli, Manisha Thenuwara, Brice Bennett, Laura Andrade Barron, Mariam Sonbol, Wynter Raine Seppala, Namritha Ramakrishnan, Jennifer Jordan Báez, Beth Orlando, Irene Arpayoglou, Melissa Meisenburg

Indian River Lagoon Shorelines

The spatial dataset: UCF_Outfalls_IRL_LWL.shp was created under grants from the Indian River Lagoon National Estuaries Program and Florida Sea Grant. These projects cumulatively led to creation of a living shoreline restoration prioritization model and hydrodynamic habitat suitability models for 1,550 km (963 miles) of estuarine shorelines in Indian River Lagoon (IRL) and Lake Worth Lagoon (LWL).

The dataset presented here includes the location of outfalls identified throughout the study region and general characteristics of the shoreline where they were identified.

Seagrass Persistence In The Indian River Lagoon And Lake Worth Lagoon, Florida, Kelly Kibler, Melinda Donnelly, Vincent Encomio, Madison Giuntoli, Manisha Thenuwara, Brice Bennett, Laura Andrade Barron, Mariam Sonbol, Wynter Raine Seppala, Namritha Ramakrishnan, Jennifer Jordan Báez, Beth Orlando, Irene Arpayoglou, Melissa Meisenburg

Indian River Lagoon Shorelines

The spatial dataset: UCF_seagrasspersistence_IRL_LWL.shp was created with support from the Indian River Lagoon National Estuaries Program and Florida Sea Grant. These projects cumulatively led to creation of a living shoreline restoration prioritization model and hydrodynamic habitat suitability models for 1,550 km (963 miles) of estuarine shorelines in Indian River Lagoon (IRL) and Lake Worth Lagoon (LWL). The dataset presented herein represents persistence of seagrass throughout waters of the IRL and LWL.

Living Shoreline Prioritization And Hydrodynamic Habitat Suitability Models For Restoration In The Indian River Lagoon And Lake Worth Lagoon, Florida, Kelly M. Kibler, Melinda J. Donnelly, Vincent Encomio, Madison Giuntoli, Manisha Thenuwara, Brice Bennett, Laura Andrade Barron, Mariam Sonbol, Wynter Raine Seppala, Namritha Ramakrishnan, Jennifer Jordan Báez, Beth Orlando, Irene Arpayoglou, Melissa Meisenburg

Indian River Lagoon Shorelines

The spatial dataset: UCF_shorelinemodel_IRL_LWL.shp, was created with support from the Indian River Lagoon National Estuaries Program and Florida Sea Grant. These projects cumulatively led to creation of a living shoreline restoration prioritization model and hydrodynamic habitat suitability models for 1,550 km (963 miles) of estuarine shorelines in Indian River Lagoon and Lake Worth Lagoon.

The dataset presented herein includes:

1. shoreline data from >15,000 transects collected in the field,
2. shoreline wave climate data created through hydrodynamic modeling and frequency analysis of historic data,
3. categorization of potential risk for shoreline boat wake impact,
4. persistence of seagrass within 210 m of the shoreline, …

Reengineering Resilience: Bio-Resilience Bonds For Financing Microbial Infrastructure And Climate Equity, Reece Buckley

COP30

This policy proposal introduces Bio-Resilience Bonds (BRBs), a performance-based financial instrument designed to monetise microbial ecosystem services as measurable climate infrastructure. Microbial ecosystems are crucial for climate resilience, yet they are often overlooked in mainstream adaptation f inance frameworks. Their ability to regulate carbon and nitrogen cycles, reduce methane emissions and enhance soil and water stability (Delgado-Baquerizo et al., 2016) makes them essential assets for climate mitigation and adaptation. With global adaptation needs exceeding £2.7 trillion (UNEP, 2024), this oversight indicates a systemic failure to recognise biology as a form of infrastructure. BRBs transform microbial outputs into localised key performance …

Using Drone And Ai To Map Leaf Water Potential And Stem Water Potential For Water Stress Management In Commercial Vineyards, Alfonso F. Torres-Rua

Funded Research Records

No abstract provided.

Evaluation Of Robotic Swabbing And Fluorescent Sensing To Monitor The Hygiene Of Food Contact Surfaces, Siavash Mahmoudi, Clark Griscom, Pouya Sohrabipour, Yang Tian, Chaitanya Palleria, Philip G. Crandall, Dongyi Wang

Biological and Agricultural Engineering Faculty Publications and Presentations

Effective environmental monitoring is critical for preventing microbial and allergenic cross-contamination. However, manual swabbing methods, commonly used to verify hygienic conditions, are prone to inconsistent results because of variability in pressure, coverage, and techniques. Two novel solutions will be explored to address these challenges: a robotic swabbing system with tactile sensing control, and a fluorescence/absorbance spectrometer for non-contact, protein-based residue detection. The robotic system was evaluated against trained and untrained humans, measuring water pickup, surface coverage, and pressure consistency. Concurrently, the fluorescence system analyzed model poultry protein soil to correlate spectral patterns with contamination levels. The robotic system demonstrated statistically …

Irrigation Scheduling Methods: Checkbook Vs Fao-56, Adarsha Neupane, Vidya Samadi

Forestry and Natural Resources

Irrigation scheduling addresses two critical questions: when to irrigate and how much water to apply. Providing the optimal amount of water at the right time enhances water use efficiency, leading to improved crop production, while minimizing water losses and ensuring sustainable water management. This article compares two widely used soil water balance-based irrigation scheduling methods—Checkbook and FAO-56—by evaluating their principles, advantages, and limitations, with a focus on how each method tracks and manages soil moisture. To illustrate their differences, we present example calculations demonstrating how each method estimates irrigation timing and amount. The Checkbook method, widely adopted for its simplicity, …

Evaluation Of Performance Characteristics And Groundwater Contamination Risks Associated With On-Farm Swine Carcass Disposal Via Composting And Shallow Burial With Carbon, Gustavo Castro Garcia

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This dissertation evaluates the performance of three on-farm swine carcass disposal methods: whole carcass composting (WCC), ground carcass composting (GCC), and shallow burial with carbon (SBC), focusing on biosecurity factors and groundwater contamination risks. Foreign animal diseases (FADs), such as African swine fever and classical swine fever, pose severe economic and animal well-being risks if introduced to the United States. With confirmation of an FAD, swine movement will be halted, creating an urgent need for practical, biosecure, and environmentally responsible on-farm disposal strategies for swine carcasses. Nebraska, as a leading swine-producing state, exemplifies the vulnerability of high-density livestock regions to …

Development Of A Machine Learning Framework For An Irrigation Decision Support System, Eric Wilkening, Derek M. Heeren, Yeyin Shi, Laila A. Puntel, Guillermo R. Balboa, Abia Katimbo, Kuan Zhang, Precious Nneka Amori, Bruno Lena

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Currently used irrigation scheduling techniques often require significant human intervention and are time consuming, particularly for variable rate irrigation. This research aimed to develop a conceptual framework that incorporates disparate data sources leveraging both mechanistic and machine learning (ML) approaches. The overarching objective is to utilize the growing availability of data and technology to manage irrigation more precisely, which will minimize negative impacts of irrigation on our water resources. An initial irrigation machine learning model was proposed and tested in this study as a key component of an edge-cloud computing and federated learning decision-making framework. The specific objectives were (1) …