Growing Industry-University Partnerships: Virtual Workshop On Industry Sponsored Research,
2024
University of Nebraska-Lincoln
Growing Industry-University Partnerships: Virtual Workshop On Industry Sponsored Research, Mark Stone, Santosh K. Pitla
Department of Agricultural and Biological Systems Engineering: Presentations and White Papers
The Department of Biological Systems Engineering (BSE) at the University of Nebraska-Lincoln (UNL) hosted a virtual workshop on developing capacity for industry-sponsored research (ISR). This dynamic event brought together faculty, researchers, industry leaders, and students to explore innovative strategies for advancing ISR.
The workshop addressed four key themes: (1) fostering sustainable industry-academic partnerships; (2) tackling intellectual property (IP) challenges; (3) building institutional and individual capacity for ISR, and (4) empowering students as critical contributors to industry research. Through expert-led presentations, an engaging panel discussion, and interactive brainstorming sessions, participants identified actionable steps and articulated a vision for the future of …
Neural Network Architecture Search Enabled Wide-Deep Learning (Nas-Wd) Integrated Hyperspectral Imaging Understanding For Woody Breast In Poultry Processing,
2024
University of Arkansas, Fayetteville
Neural Network Architecture Search Enabled Wide-Deep Learning (Nas-Wd) Integrated Hyperspectral Imaging Understanding For Woody Breast In Poultry Processing, Chaitanya Kumar Reddy Pallerla
Graduate Theses and Dissertations
The development and implementation of a Wide & Deep (WD) learning model tailored for classification and regression tasks utilizing spectral data provides a robust solution to evaluate woody breast (WB) conditions in poultry fillets. This process begins with thorough data preprocessing, which includes loading spectral and classification datasets, imputing missing values with medians, and splitting the data into training and testing sets to ensure rigorous model evaluation. The WD model architecture integrates wide linear models and deep neural networks to harness the strengths of both approaches. The wide component excels at memorizing sparse feature interactions, while the deep component captures …
Isolation And Upgrading Of Lignin From Agricultural Sources Using Phase Equilibria,
2024
Clemson University
Isolation And Upgrading Of Lignin From Agricultural Sources Using Phase Equilibria, Bronson Lynn
All Dissertations
In the emerging bioeconomy, agricultural residues from our nationwide crop harvests are positioned to be a cornerstone of renewable and sustainable fuels, chemicals, and materials. However, to be economically viable, the basic constituents of this plant matter must be separated and funneled to the appropriate application to maximize value and overall usability.
This work focuses on the component that has, to this point, been largely left behind: lignin. Although it is the most abundant aromatic biopolymer on the planet, making up 15-40% of grasses, hardwoods, and softwoods, the processing involved to isolate usable lignins is too complex and expensive to …
Compact Solar-Powered Plasma Water Generator: Enhanced Germination Of Aged Seed With The Corona Dielectric Barrier Discharger,
2024
University of Arkansas, Fayetteville
Compact Solar-Powered Plasma Water Generator: Enhanced Germination Of Aged Seed With The Corona Dielectric Barrier Discharger, Yiting Xiao, Yang Tian, Haizheng Xiong, Ainong Shi, Jun Zhu
Biological and Agricultural Engineering Faculty Publications and Presentations
Seed aging adversely affects agricultural productivity by reducing germination rates and seedling vigor, leading to significant costs for seed banks and companies due to the need for frequent seed renewals. This study demonstrated the use of plasma-activated water (PAW), generated by a solar-powered corona dielectric barrier discharger, to enhance germination rates of spinach seeds that had been stored at 4 °C for 23 years. Treating seeds with PAW at 17 kV for 15 min improved germination (by 135%) and seedling growth compared to untreated seeds. Through detailed analysis, beneficial PAW properties for seed development were identified, and a molecular mechanism …
Effective Nutrient Management Of Surface Waters In The United States Requires Expanded Water Quality Monitoring In Agriculturally Intensive Areas,
2024
North Carolina State University
Effective Nutrient Management Of Surface Waters In The United States Requires Expanded Water Quality Monitoring In Agriculturally Intensive Areas, Christopher Oates, Hactor Fajardo, Khara Grieger, Daniel Obenaur, Rebecca Muenich, Natalie G. Nelson
Biological and Agricultural Engineering Faculty Publications and Presentations
The U.S. Clean Water Act is believed to have driven widespread decreases in pollutants from point sources and developed areas, but has not substantially affected nutrient pollution from agriculture. Today, the highest nutrient concentrations in surface waters are often associated with agricultural production. In this Perspective, we explore whether challenges stemming from the Clean Water Act’s inability to mitigate agricultural nutrient pollution are also exacerbated by coarse nutrient monitoring. We evaluate the current state of nutrient monitoring in surface waters of the contiguous U.S. relative to agricultural nutrient inputs to assess how monitoring effort varies across agriculturally intensive areas. The …
Identifying Hidden Factors Influencing Soil Olsen-P In An Alkaline Calcareous Soil Using Machine Learning And Geostatistical Techniques,
2024
Mohammed VI Polytechnic University (UM6P), Ben Guerir, Morocco
Identifying Hidden Factors Influencing Soil Olsen-P In An Alkaline Calcareous Soil Using Machine Learning And Geostatistical Techniques, Moussa Bouray, Mohammed Bayad, Adnane Beniaich, Ahmed G. El-Naggar, Rebecca Muenich, Kahlil El Mejahed, Abdallah Oukarroum, Mohamed El Gharous
Biological and Agricultural Engineering Faculty Publications and Presentations
Phosphorus (P) deficiency is one of the major constraints for sustainable crop production in calcareous soils. This study aimed to elucidate the key soil characteristics modulating the variability of soil Olsen P in these typical soils. A comprehensive soil sampling initiative (1.5 samples per hectare) was conducted on a 100-ha farm, considering 31 attributes that included soil physical and chemical properties, and geographic attributes. Three machine learning algorithms—partial least squares regression (PLSR), random forest (RF), and cubist regression (CR)—were employed to understand key variables controlling soil Olsen P. Furthermore, the same data set was used to spatially map the …
Harvesting Modulation In Three Species Food Chains Using A Robust Control Approach,
2024
Universidad Autonoma Metropolitana - Azcapotzalco
Harvesting Modulation In Three Species Food Chains Using A Robust Control Approach, Hector Puebla, Mariana Rodriguez-Jara, Priti Kumar Roy
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Internet Of Things-Based Automated Solutions Utilizing
Machine Learning For Smart And Real-Time Irrigation
Management: A Review,
2024
University of Nebraska-Lincoln
Internet Of Things-Based Automated Solutions Utilizing Machine Learning For Smart And Real-Time Irrigation Management: A Review, Bryan Nsoh, Abia Katimbo, Hongzhi Guo, Derek M. Heeren, Hope Njuki Nakabuye, Xin Qiao, Yufeng Ge, Daran R. Rudnick, Joshua Wanyama, Erion Bwambale, Shafik Kiraga
Department of Agricultural and Biological Systems Engineering: Faculty Publications
This systematic review critically evaluates the current state and future potential of real-time, end-to-end smart, and automated irrigation management systems, focusing on integrating the Internet of Things (IoTs) and machine learning technologies for enhanced agricultural water use efficiency and crop productivity. In this review, the automation of each component is examined in the irrigation management pipeline from data collection to application while analyzing its effectiveness, efficiency, and integration with various precision agriculture technologies. It also investigates the role of the interoperability, standardization, and cybersecurity of IoT-based automated solutions for irrigation applications. Furthermore, in this review, the existing gaps are identified …
Excavated Tanks (Farm Dams),
2024
Department of Primary Industries and Regional Development, Western Australia
Excavated Tanks (Farm Dams), Department Of Primary Industries And Regional Development, Western Australia
Natural resources factsheets
Guidelines and information for planning, legal requirements, design, construction and management of excavated tanks for water storage on farm.
Excavated tanks (farm dams) provide effective water storage wherever surface water run-off can be harvested for livestock, crop spraying, irrigation and domestic use on rural properties.
Excavated tanks for rainfall storage are common in the southern agricultural areas of WA.
Well-designed and constructed dams are farm assets, safe and require little maintenance.
Poor design and construction can lead to poor water harvesting and storage, excessive costs, downstream erosion and risks to property and people.
DPIRD recommends that excavated tanks should be …
Development Of Crop2cloud: An Iot-Integrated Platform For Automated Irrigation Scheduling Using Multi-Source Stress Indices,
2024
University of Nebraska-Lincoln
Development Of Crop2cloud: An Iot-Integrated Platform For Automated Irrigation Scheduling Using Multi-Source Stress Indices, Bryan Nsoh
Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research
Efficient water management in agriculture is critical, as irrigation accounts for 70% of global freshwater withdrawals. While precision agriculture technologies offer potential solutions, integrating diverse data streams for real-time irrigation scheduling remains challenging, particularly in combining plant and soil-based stress indicators. This research addresses these challenges through three interconnected studies.
A systematic review first examined the current state and future potential of IoT-based automated irrigation management systems, analyzing how these technologies can enhance agricultural water use efficiency and crop productivity. The review identified critical gaps in data integration and real-time processing while highlighting opportunities for combining multiple stress indices for …
Blackberry Growth Monitoring And Feature Quantification With Unmanned Aerial Vehicle (Uav) Remote Sensing,
2024
University of Arkansas, Fayetteville
Blackberry Growth Monitoring And Feature Quantification With Unmanned Aerial Vehicle (Uav) Remote Sensing, Akwasi Tagoe, Alexander Silva, Cengiz Koparan, Aurelie Poncet, Dongyi Wang, Donald Johnson, Margaret Worthington
Biological and Agricultural Engineering Faculty Publications and Presentations
Efficiently managing agricultural systems necessitates accurate data collection from crops to examine phenotypic characteristics and improve productivity. Traditional data collection processes for specialty horticultural crops are often subjective, labor-intensive, and may not provide accurate information for precise management decisions in phenotypic studies and crop production. Reliable and standardized techniques to record and evaluate crop features using agricultural technology are essential for improving agricultural systems. The objective of the research was to develop a methodology for accurate measurement of blackberry flowers and vegetation coverage using UAV remote sensing and image analysis. The UAV captured 20,812 images in the visible spectrum, and …
Efficient Real-Time Droplet Tracking In Crop-Spraying Systems,
2024
Florida Institute of Technology
Efficient Real-Time Droplet Tracking In Crop-Spraying Systems, Troung Nhut Huynh, Travis Burgers, Kim-Doang Nguyen
Mechanical Engineering Faculty Publications
Spray systems in agriculture serve essential roles in the precision application of pesticides, fertilizers, and water, contributing to effective pest control, nutrient management, and irrigation. These systems enhance efficiency, reduce labor, and promote environmentally friendly practices by minimizing chemical waste and runoff. The efficacy of a spray is largely determined by the characteristics of its droplets, including their size and velocity. These parameters are not only pivotal in assessing spray retention, i.e., how much of the spray adheres to crops versus becoming environmental runoff, but also in understanding spray drift dynamics. This study introduces a real-time deep learning-based approach for …
Targeted Weed Management Of
Palmer Amaranth Using Robotics
And Deep Learning (Yolov7),
2024
University of Nebraska-Lincoln
Targeted Weed Management Of Palmer Amaranth Using Robotics And Deep Learning (Yolov7), Amlan Balabantaray, Shaswati Behera, Cheetown Liew, Nipuna Chamara, Mandeep Singh, Amit J. Jhala, Santosh Pitla
Department of Agricultural and Biological Systems Engineering: Faculty Publications
Effective weed management is a significant challenge in agronomic crops which necessitates innovative solutions to reduce negative environmental impacts and minimize crop damage. Traditional methods often rely on indiscriminate herbicide application, which lacks precision and sustainability. To address this critical need, this study demonstrated an AI-enabled robotic system, Weeding robot, designed for targeted weed management. Palmer amaranth (Amaranthus palmeri S. Watson) was selected as it is the most troublesome weed in Nebraska. We developed the full stack (vision, hardware, software, robotic platform, and AI model) for precision spraying using YOLOv7, a state-of-the-art object detection deep learning technique. The …
Irrigation Pumping Plants: Energy Consumption And Pumping Plant Performance [Class Handout],
2024
University of Nebraska-Lincoln
Irrigation Pumping Plants: Energy Consumption And Pumping Plant Performance [Class Handout], Derek M. Heeren, Saleh Taghvaeian, Abia Katimbo, Xin Qiao
Department of Agricultural and Biological Systems Engineering: Faculty Publications
Irrigation can be a large contributor to energy consumption on an irrigated farm. It is important to understand factors that impact irrigation energy use and to identify opportunities to reduce energy consumption. This class handout introduces a set of equations for calculating energy consumption for an irrigation pumping plant based on flow conditions and pump efficiency. It also presents typical values for motor performance (including both electric motors and internal combustion engines) in both SI and USCS units. Finally, the handout introduces the concept of a field evaluation of an irrigation pumping plant along with the Nebraska Pumping Plant Performance …
A Step By Step Shoreline Attribute Analysis For Selected Waterbodies In The Gulf Of Mexico To Promote The Use Of Living Shorelines,
2024
Troy University
A Step By Step Shoreline Attribute Analysis For Selected Waterbodies In The Gulf Of Mexico To Promote The Use Of Living Shorelines, Christoper Boyd, Xutong Niu, Taylor R. Horn
Journal of Extension
Living Shorelines are being promoted by coastal extension professionals as a more resilient nature-based solution to control shoreline erosion. The Virginia Institute of Marine Sciences Living Shorelines Suitability Model was run in selected waterbodies within the Gulf of Mexico.
The locations of the selected water bodies, coastal data sets used, and shoreline protection recommendations generated by the Model are presented. A step-by-step statistical analysis conducted through ArcGIS Pro from these selected coastal shorelines will illustrate how extension professionals with novice GIS experience can use the model output to promote living shorelines to coastal property owners, city managers, and developers.
Gsp-Ai: An Ai-Powered Platform For
Identifying Key Growth Stages And The
Vegetative-To-Reproductive Transition In
Wheat Using Trilateral Drone Imagery And
Meteorological Data,
2024
Nanjing Agricultural University
Gsp-Ai: An Ai-Powered Platform For Identifying Key Growth Stages And The Vegetative-To-Reproductive Transition In Wheat Using Trilateral Drone Imagery And Meteorological Data, Liyan Shen, Guohui Ding, Robert Jackson, Mujahid Ali, Shuchen Liu, Arthur Mitchell, Yeyin Shi, Xuqi Lu, Jie Dai, Greg Deakin, Katherine Anna Frels, Haiyan Cen, Yufeng Ge, Ji Zhou
Department of Agricultural and Biological Systems Engineering: Faculty Publications
Wheat (Triticum aestivum) is one of the most important staple crops worldwide. To ensure its global supply, the timing and duration of its growth cycle needs to be closely monitored in the field so that necessary crop management activities can be arranged in a timely manner. Also, breeders and plant researchers need to evaluate growth stages (GSs) for tens of thousands of genotypes at the plot level, at different sites and across multiple seasons. These indicate the importance of providing a reliable and scalable toolkit to address the challenge so that the plot-level assessment of GS can be …
Assessing Soil Properties & Suitability For Optimized Irrigation Development In Sudan, Northern Africa,
2024
University of Nebraska-Lincoln
Assessing Soil Properties & Suitability For Optimized Irrigation Development In Sudan, Northern Africa, Suhib O. Hamid
Department of Agricultural and Biological Systems Engineering: Masters Project Reports
In Chapter 1, soil properties essential for efficient irrigation are thoroughly assessed. Factors such as soil texture, infiltration rates, and nutrient content are analyzed to provide insights into the selection of modern irrigation systems. Utilizing data collected from 3,192 locations through GPS and laboratory analyses, alongside sophisticated ranking systems, the research determines the most suitable irrigation methods for specific soil series. Findings highlight the remarkable efficiency of drip irrigation across various soil types, contrasting with the consistently lower performance of surface irrigation. The chapter emphasizes the significance of considering soil variability, evapotranspiration, and investment factors in selecting irrigation methods for …
Assessing Even Flat-Fan Nozzles For Spot Spray Herbicide Applications,
2024
University of Nebraska-Lincoln
Assessing Even Flat-Fan Nozzles For Spot Spray Herbicide Applications, Thiago H. Vitti
Department of Agronomy and Horticulture: Dissertations, Theses, and Student Research
Herbicide efficiency in row-crop agriculture can be improved using precision technologies for controlling weeds and minimize agronomic, economic, and environmental impacts. Site-specific weed management technologies, such as spot-sprayers, allow herbicides to be sprayed only where weeds are present in the field. Understanding application parameters and their influence on weed control for site-specific spot-spray applications is essential. This research involved laboratory and greenhouse studies to investigate the coverage and coefficient of variation (CV) of even flat-fan spray nozzles under different spot-spray application scenarios, as well as the effect of weed size and application method on the control of various weed species …
Development Of An Egg-Specific Mass Spectrometry Targeted Method For Processed Food Matrices,
2024
University of Nebraska-Lincoln
Development Of An Egg-Specific Mass Spectrometry Targeted Method For Processed Food Matrices, Liyun Zhang
Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–
Egg is a major food allergen in the United States, causing symptoms from mild reactions to severe anaphylaxis. An egg-free diet remains the only management approach for egg allergy. Therefore, individuals and families living with egg allergies rely heavily on allergen statements on packaged food products for informed food choices. Currently, no labeling regulations exist for unintentionally introduced allergens, posing risks to consumers with egg allergies. Therefore, it is critical to have an accurate and reliable detection method in allergen control and management to determine the concentration of total protein from allergenic food sources. Traditional enzyme-linked immunosorbent assays are routinely …
Integration Of Matlab And Machine Learning To Accelerate Evaluation Of Biological Activity In Agricultural Soils And Promote Soil Health Improvement Goals,
2024
University of Nebraska-Lincoln
Integration Of Matlab And Machine Learning To Accelerate Evaluation Of Biological Activity In Agricultural Soils And Promote Soil Health Improvement Goals, Andrew Stiven Ortiz Balsero
Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research
Traditionally, assessments of soil biological activity have been confined to laboratory settings, creating a disconnect with practical in-field methods. To bridge this gap, cotton fabric degradation has been used to illustrate soil microbial activity under different management practices. While effective, these demonstrations are subjective and labor-intensive.
Researchers have explored using image processing software like ImageJ and Adobe Photoshop to streamline this process. Although these tools accurately quantified fabric degradation under varying soil conditions, the methods remained labor-intensive and complex. Consequently, these methods were still not ideal for on-farm use by agricultural practitioners.
To further address labor and complexity limitations, the …
