Bioresource and Agricultural Engineering Commons^™

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

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Precision Agriculture (PA) promises to meet the future demands for food, feed, fiber, and fuel while keeping their production sustainable and environmentally friendly. PA relies heavily on sensing technologies to inform site-specific decision supports for planting, irrigation, fertilization, spraying, and harvesting. Traditional point-based sensors enjoy small data sizes but are limited in their capacity to measure plant and canopy parameters. On the other hand, imaging sensors can be powerful in measuring a wide range of these parameters, especially when coupled with Artificial Intelligence. The challenge, however, is the lack of computing, electric power, and connectivity infrastructure in agricultural fields, preventing …

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

Department of Agricultural and Biological Systems Engineering: Faculty Publications

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

Modeling Overdraft-Driven Nitrate Transport In Shallow Wells For Mitigation And Scenario Planning, Jonathan Cronk

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

In Nebraska, average nitrate concentrations in groundwater have doubled since 1974, making water quality management more important than ever. As droughts, heat waves, and floods become more common climate events, understanding their impacts will be necessary to make informed management decisions. Emerging literature describes that drought correlates to an increase in the concentration of nitrate-N at domestic and irrigation wells, however the relative contributions of the mechanisms thought to be responsible is currently unknown.

This research assessed the impact of recharge and pumping rate changes as two mechanisms affecting nitrate-N concentration during drought, assessed the relationship between well depth and …

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

Department of Agricultural and Biological Systems Engineering: Faculty Publications

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

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

Department of Agricultural and Biological Systems Engineering: Faculty Publications

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

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

Department of Agricultural and Biological Systems Engineering: Faculty Publications

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

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

Department of Agricultural and Biological Systems Engineering: Faculty Publications

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

Creating An Automatic Lowering Function For Quarter-Scale Tractor Pulling Sled, Sam Wilkins

Honors Program: Senior Projects (Public)

As the agricultural industry works to continuously integrate innovative technology and improve production efficiency, improved on-board data acquisition and transmission will be necessary for all agricultural machines. To make this a reality, the utilization of controller area network (CAN) technology will be crucial. Therefore, it is important for all agricultural engineers to have foundational knowledge of CAN bus systems and the standards that govern their use in industry. The UNL quarter-scale tractor team regularly utilizes CAN buses on their tractors and testing equipment. One such testing machine is the team’s pulling sled, which uses CAN messages to transport important information …

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

Department of Agricultural and Biological Systems Engineering: Faculty Publications

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

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

Department of Agricultural and Biological Systems Engineering: Faculty Publications

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

Plant Height Estimation Using Rtk-Gnss Enabled Unmanned Aerial Vehicle (Uav) Photogrammetry, Pascal Izere

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

Using Unmanned Aerial Vehicle (UAV) based remote sensing technology to provide high-throughput plant phenotypic traits has shown a great potential of eliminating manual measurements. For example, the use of UAV imaging to estimate plant height is of great interest to plant breeders and agronomists. Height is linked to a plant’s physical growth, light competition, health, biomass, and yield; thus, its accurate estimation is crucial in breeding. Conventionally, accurate height estimation by UAV platforms relies heavily on the use of ground control points (GCPs) for geometric calibration due to the relatively low positioning accuracy of regular differential global navigation satellite system …

Influence Of Ultrasound Machine Settings On Quantitative Measures Derived From Spatial Frequency Analysis Of Muscle Tissue, Scott K. Crawford, Stephanie A. Kliethermes, Bryan C. Heiderscheit, Greg Bashford

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Background Ultrasound is a powerful tool for diagnostic purposes and provides insight into both normal and pathologic tissue structure. Spatial frequency analysis (SFA) methods characterize musculoskeletal tissue organization from ultrasound images. Both sonographers in clinical imaging and researchers may alter a minimized range of ultrasound settings to optimize image quality, and it is important to know how these small adjustments of these settings affect SFA parameters. The purpose of this study was to investigate the effects of making small adjustments in a typical default ultrasound machine setting on extracted spatial frequency parameters (peak spatial frequency radius (PSFR), Mmax, Mmax%, and …

Characterizing Feedlot Feed Using Depth Cameras And Imaging Technology, Jean Niwenshuti

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

Imaging technology is a growing field that provides solutions in many areas from manufacturing to agriculture. Through previous research, imaging technologies have been studied in livestock farming to monitor the animal’s health and welfare in the production process. However, the feedlot industry is still behind in validating the feasibility to use some of these technologies nor to adopt such technologies to address challenges the industry is facing, such as lack of skilled labor.This work proposes using novel imaging methods to identify feed types and estimate the amount of feed remaining in a typical Midwestern feedlot feed bunk. These methods have …

Flex-Ro: Development And Testing Of A Semi-Autonomous Robotic Planter, Ian Tempelmeyer

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

The need for more crop production with minimal negative environmental impact is a continuing pursuit around the world. As the population continues to increase at an exponential rate, the demand for food, fiber, fuel, and energy also increases. Robotics and automation are seen as one of the useful technology tools to increase field productivity. This work specifically focuses on addressing labor challenges for one of the most important field operations, planting. A robotic planter unit was designed as part of this work that mounted on unmanned ground vehicle (UGV) to perform autonomous planting operation in a 1 ha (2.5 acre) …

Assessment Of Integrated Nutrient Management Practices On Soil Health And Nitrogen Efficiency In Cropping Systems, María José Oviedo Ventura

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

Groundwater quality in Nebraska is threatened by non-point source contributions of nitrate-nitrogen, primarily by agricultural systems. Intensive crop and livestock production that neglects the value of manure in crop fertility plans can contribute to soil degradation and natural resource impairment. The purpose of this study is to evaluate opportunities to improve agricultural nutrient management throughout Nebraska by quantifying opportunities for manure distribution, evaluating soil health implications of organic and inorganic soil amendments, and assessing nutrient management practices focused on reducing nitrate leaching in agricultural soils.

This study described in Chapter 2 provides a spatial illustration of nitrogen and phosphorus balances …

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

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Introduction: The Great Plains ecosystem offers an opportunity for young people to gain knowledge about intricate systems through practical learning. The spread of woody plants into grasslands, known as the “Green Glacier,” poses a risk to biodiversity and animal production. Although effective management strategies exist, some land managers are reluctant to use them. It is critical to cultivate a scientifically literate population that can think systematically and make informed decisions based on STEM principles to address such complex agroecosystem problems.

Methods: In this study, semi-structured focus group discussions with high school students were analyzed to determine whether Prairie …

Assessing The Impact Of Spatial Resolution Of Uas-Based Remote Sensing And Spectral Resolution Of Proximal Sensing On Crop Nitrogen Retrieval Accuracy, Kianoosh Hassani, Hamed Gholizadeh, Saleh Taghvaeian, Victoria Natalie, Jonathan Carpenter, Jamey Jacob

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Foliar nitrogen (N) plays a central role in photosynthetic machinery of plants, regulating their growth rates. However, field-based methods for monitoring plant N concentration are costly and limited in their ability to cover large spatial extents. In this study, we had two objectives: (1) assess the capability of unoccupied aerial system (UAS) and non-imaging spectroscopic data in estimating sorghum and corn N concentration and (2) determine the impact of spatial and spectral resolution of reflectance data on estimating sorghum and corn N concentration. We used a UAS and an ASD spectroradiometer to collect canopy- and leaf-level spectral data from sorghum …

Exploring The Determinants Of Organic Matter Bioavailability Through Substrate-Explicit Thermodynamic Modeling, Firnaaz Ahamed, Yaqi You, Amy Burgin, James C. Stegen, Timothy D. Scheibe, Hyun-Seob Song

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Microbial decomposition of organic matter (OM) in river corridors is a major driver of nutrient and energy cycles in natural ecosystems. Recent advances in omics technologies enabled high-throughput generation of molecular data that could be used to inform biogeochemical models. With ultrahigh-resolution OM data becoming more readily available, in particular, the substrate-explicit thermodynamic modeling (SXTM) has emerged as a promising approach due to its ability to predict OM degradation and respiration rates from chemical formulae of compounds. This model implicitly assumes that all detected organic compounds are bioavailable, and that aerobic respiration is driven solely by thermodynamics. Despite promising demonstrations …

A Robotic System For In-Situ Measurement Of Soil Total Carbon And Nitrogen, Husein Harun

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

Surges in the cost of fertilizer in recent times coupled with the environmental effects of their over-application have driven the need for farmers to optimize the amount of fertilizer they apply on the farm. One of the key steps in determining the right amount of fertilizer to apply in a given field is measuring the amount of nutrients present in the soil. To ascertain nutrient deficiencies, most farmers perform wet chemistry analysis of soil samples which requires a lot of time and is expensive. In this research project, a robotic system was designed and developed that could autonomously move to …

Development Of A Scalable Edge-Cloud Computing Based Variable Rate Irrigation Scheduling Framework, Eric J. Wilkening, Derek M. Heeren, Yeyin Shi, Abia Katimbo, Precious N. Amori, Guillermo R. Balboa, Laila A. Puntel, Kuan Zhang, Daran R. Rudnick

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

Currently, variable-rate precision irrigation (VRI) scheduling methods require large amounts of data and processing time to accurately determine crop water demands and spatially process those demands into an irrigation prescription. Unfortunately, irrigated crops continue to develop additional water stress when the previously collected data is being processed. Machine learning is a helpful tool, but handling and transmitting large datasets can be problematic; more rural areas may not have access to necessary wireless data transmission infrastructure to support cloud interaction. The introduction of “edge-cloud” processing to agricultural applications has shown to be effective at increasing data processing speed and reducing the …

Peer Review Of Teaching: Et Theory, Deficit Irrigation And Consumptive Use, Derek M. Heeren, Saleh Taghvaeian

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

A BSE Peer Review of Teaching was carried out for a graduate level course on Advanced Irrigation Management. This course has been offered for several years; each time improvements are made, but there is always a need for additional improvement. In particular, ET theory, deficit irrigation, and consumptive use are topics that the students struggle to grasp. These topics involve a relatively high level of math for an MS-level (800-level) Agricultural Systems Technology course, and the available materials on these topics either were not well developed or were not a good fit for this class. The primary objective was to …

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

Department of Agricultural and Biological Systems Engineering: Faculty Publications

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

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

Department of Agricultural and Biological Systems Engineering: Faculty Publications

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

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

Department of Agricultural and Biological Systems Engineering: Faculty Publications

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

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

Department of Agricultural and Biological Systems Engineering: Faculty Publications

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

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

Department of Agricultural and Biological Systems Engineering: Faculty Publications

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

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

Department of Agricultural and Biological Systems Engineering: Faculty Publications

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

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

Department of Agricultural and Biological Systems Engineering: Faculty Publications

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

High-Throughput Phenotyping Of Plant Leaf Morphological, Physiological, And Biochemical Traits On Multiple Scales Using Optical Sensing, Huichun Zhang, Lu Wang, Xiuliang Jin, Liming Bian, Yufeng Ge

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Acquisition of plant phenotypic information facilitates plant breeding, sheds light on gene action, and can be applied to optimize the quality of agricultural and forestry products. Because leaves often show the fastest responses to external environmental stimuli, leaf phenotypic traits are indicators of plant growth, health, and stress levels. Combination of new imaging sensors, image processing, and data analytics permits measurement over the full life span of plants at high temporal resolution and at several organizational levels from organs to individual plants to field populations of plants. We review the optical sensors and associated data analytics used for measuring morphological, …

Design Of University Small-Scale Dairy Processing Facility, Philip J. Hildebrand, Joshua Arejola, Alicia Andersen, Terry Howell Jr, Tami M. Brown-Brandl

Department of Agricultural and Biological Systems Engineering: Faculty Publications

This project was assigned to research the feasibility and value of implementing a dairy processing facility on the campus of the University of Nebraska-Lincoln. The facility would process milk produced from cows under the same roof and will serve as an educational experience for Nebraska dairy farmers, UNL students, and K-12 students in the Lincoln-Lancaster County area. If the project is successful and replicated across the state, this facility could have a significant impact on the reduction of milk transportation costs in the Nebraska dairy industry.

The project began with researching milk processing methods and steps from production to consumption. …