Iowa Research Articles

Early- and in-season crop type mapping without current-year ground truth: Generating labels from historical information via a topology-based approach

Land cover classification in remote sensing is often faced with the challenge of limited ground truth labels. Incorporating historical ground information has the potential to significantly lower the expensive cost associated with collecting ground truth and, more importantly, enable early- and in-season mapping that is helpful to many pre-harvest decisions. In this study, we propose a new approach that can effectively transfer knowledge about the topology (i.e. relative position) of different crop types in the spectral feature space (e.g. the histogram of SWIR1 vs RDEG1 bands) to generate labels, thereby supporting crop classification in a different year. Importantly, our approach does not attempt to transfer classification decision boundaries that are susceptible to inter-annual variations of weather and management, but relies on the more robust and shift-invariant topology information. We tested this approach for mapping corn/soybeans in the US Midwest, paddy rice/corn/soybeans in Northeast China and multiple crops in Northern France using Landsat-8 and Sentinel-2 data. Results show that our approach automatically generates high-quality labels for crops in the target year immediately after each image becomes available. Based on these generated labels from our approach, the subsequent crop type mapping using a random forest classifier can reach the F1 score as high as 0.887 for corn as early as the silking stage and 0.851 for soybean as early as the flowering stage and the overall accuracy of 0.873 in the test state of Iowa. In Northeast China, F1 scores of paddy rice, corn and soybeans and the overall accuracy can exceed 0.85 two and half months ahead of harvest. In the Hauts-de-France region, the OA of multiple crop mapping could reach 0.837 based on labels generated from our approach. Overall, these results highlight the unique advantages of our approach in transferring historical knowledge and maximizing the timeliness of crop maps. Our approach supports a general paradigm shift towards learning transferrable and generalizable knowledge to facilitate land cover classification.

Severe mandibular osteomyelitis and exfoliation of a mandibular canine tooth in a Vietnamese potbellied pig

A 10-year-old male castrated Vietnamese potbellied pig presented for evaluation of a dermal mass present on the left cervico-mandibular region. The patient had a mass removed 6 years earlier from the same region, which was diagnosed as squamous cell carcinoma on histopathology. On physical examination, all vital parameters, including heart rate, respiratory rate and temperature, were within normal reference ranges, and the owner reported a normal appetite with no recent history of weight loss. Upon intubation for the dermal mass removal, a large heterogeneous mass of material was observed in the rostral aspect of the left mandible (Figure 1). Once removed, the mass appeared to be grossly composed of foodstuffs, hair, and a firm, mineralized segment of unknown material (Figure 2a). Within the contents of this debris, the left mandibular canine tooth (304) or tusk was identified. For the size of the mass of material, there was minimal inflammation associated with the gingiva and the mucosa (Figure 2b). There did not appear to be any evidence of displacement of the remaining teeth in the area. The periodontal attachment appeared to be normal in the remaining teeth. Computed tomography (CT) of the head was performed with the patient anaesthetized as previously described1 and positioned in sternal recumbency. Findings included severe, multifocal, chronic periodontal disease. The left mandibular canine tooth (304) or tusk was absent, and there was a large bony defect associated with the left mandibular body along the alveolar margin. The bony defect continued to affect the buccal aspect of the mandibular body (Figure 3). There was also extensive periapical lysis and evidence of external tooth resorption of the right mandibular canine tooth (404). The radiographic dental abnormalities were consistent with severe diffuse mandibular osteomyelitis characterized by multifocal moth-eaten bone lysis and irregular periosteal new bone formation, and multiple draining tracts from the right ventral mandible. Additional radiographic findings included absence of all premolar and molar teeth except the right first maxillary premolar (105), multifocal periapical lysis of the remaining teeth, bilateral medial retropharyngeal lymphadenopathy, and evidence of bilateral otitis externa and right otitis media. Miniature companion pigs (MCPs) are increasing in popularity as companion animal pets in North America.2 While data for exact numbers are limited, MCPs first appeared in the United States in the 1980s, with a dramatic increase in popularity over the past 17 years.3 With the increase in numbers, preventive care strategies are essential to improve animal health and welfare. Commonly reported dental pathologies in MCPs include missing teeth (most commonly the first mandibular premolar), periodontal disease, and tooth resorption.4 Early diagnosis of dental disease and mandibular osteomyelitis is important for companion animal pigs, considering their potentially long life span. Extraction of an infected tusk can be quite challenging. In cases of severe infection and disease, the integrity of the mandible can be affected to the point where it can be unstable after the extraction.5 Osteomyelitis can be managed with long-term antimicrobial therapy, including oral, injectable, and regional infusion of antibiotic-impregnated compounds, depending on lesion location.6 Removal of the infected nidus, in many cases the tooth, is critical for a positive long-term outcome. A complete oral assessment with inclusion of dental radiographs in MCPs should be considered for proper preventative dental care.4 As evidenced by our case, CT is also beneficial for a thorough oral evaluation and dental assessment. The authors declare no conflict of interest. This case represents a retrospective clinical case report and not a prospective study that requires institutional approval. The authors received no specific funding for this work. Open access funding provided by the Iowa State University Library.

Improving Subject Headings for Iowa Indigenous Peoples

By authorizing outdated terms for North American Indigenous peoples, the Library of Congress Subject Headings (LCSH) vocabulary deprioritizes or ignores the preferred names of the peoples being described. As a result, cataloging and metadata professionals constrained by LCSH often must apply names imposed during colonization. For example, in many library catalogs, works about people of the Meskwaki Nation in Iowa are labeled with “Fox Indians--Iowa” and “Sauk Indians--Iowa,” and Ioway peoples are described as “Iowa Indians.” As part of a diversity, equity, and inclusion (DEI) initiative at Iowa State University Library, a working group in the Metadata Services department undertook a project to build, publish, and use a controlled vocabulary of preferred terms for Indigenous communities with ties to land that is now part of the state of Iowa. This paper describes the working group’s research, outreach efforts, published vocabulary, and process for adding the preferred subject headings to library metadata.

Updating a Commitment to Openness

In 2021, the Iowa State University Library passed a new Open Access Commitment, replacing an outdated document with one that better supports the diverse range of work done by the library staff at Iowa State University.

Public School District Characteristics and the Formation of Longitudinal Interdistrict Collaboration Networks

Purpose: School leaders rely on a number of collaborative policy tools to address fiscal and governance issues. While prior research has examined the dynamics and implications of research-practice and public-private partnerships, this study addresses a third form of collaboration: interdistrict cooperative agreements. Method: We develop a unique data set to study the formation of interdistrict agreements formed among 333 public school districts in the state of Iowa from 2008 through 2017. Aimed at reducing costs and improving student outcomes, these agreements collectively reflect an intergovernmental network that develops through predominantly bilateral agreements. We examine the factors and mechanisms that can facilitate and hinder interdistrict collaboration through a stochastic actor-oriented model for analyzing panels of network observations. Findings: We find both transitivity and popularity to be positively associated with the inclination to form cooperative relationships. Further, school districts are more likely to collaborate with districts that have a: (1) greater number of enrolled students; (2) smaller percentage of students that receive free or reduced-price lunch; (3) higher student-to-teacher ratio; and (4) lower average teacher salary. Propinquity and homophily effects are present as well: between any two given school districts, the likelihood of collaboration improves as geographical distance and the absolute difference in district-level measures decreases. Implications: Understanding the antecedents of education network formation enables examinations of how network characteristics can reduce the cost of providing education or improve student outcomes.

Until Justice Be Done: America's First Civil Rights Movement, from the Revolution to Reconstruction

Until Justice Be Done: America's First Civil Rights Movement, from the Revolution to Reconstruction

Echoes, and: Mist

Echoes, and: Mist Romeo Oriogun (bio) Echoes In Boston, I walked the night.From blackness I beheld the salvationof dreams. I have moved. In rural Oregon, the plants spoke.Red Alders, White Oaks stood still,two geldings ran aroundin a small enclosure. Tiny creatures ran underneathmy foot as I walked the wooden bridgethat separated small pondfrom paths leading to a farmhouse. So much hope ran through this familiarspace. Across the bridge, in the small pond,I saw the algae of my childhood. I trembled,I fell to the ground, it was August. I heard the earthworms saying,we are of this world,this world is ours only,our great bounty, in it you live. In all your yearning for home,you can only tread this pondfrom here to there, the beginningof a narrowing path. [End Page 44] Mist I entered a train stationand the air trembled, swallows searchedfor rooms in the brief wonder of flight. The graffiti on the pillars spoke of nothing.The day ran into the nightlike a child who having been harmedby a stranger must seek refugein the darkness of a closed room. I wanted the world to be still, the cloudsshaped like bicycles to stop moving.I wanted the girl, whose black clothes spokeof mourning, to look at me. The world has happened, I had left home,and from afar I could imagine the houseson the hill of my birth, the houses leaninginto each other like old souls fallinginto the slow embrace of pity. The doors to my country have been closedto me, the canvas of my mind torn into shreds.What home I knew is now the abode of hawks,and the falconer whose falcon escapedinto the wild must begin to think about freedom. In every mirror, I said to myself, I did not dietoday; the world kept moving. At my departure I said goodbye, I said welcome,I said nothing, and the city turned its back at me, [End Page 45] becoming a stranger I will walk past someday,in a country beyond rivers, then turnto wonder, where have I seen this face, this kingdom,where was my life taken from me? [End Page 46] Romeo Oriogun Romeo Oriogun is the author of Sacrament of Bodies, a finalist for the Lambda Award for Gay Poetry. He has received fellowships and support from Ebedi International Writers Residency, Harvard University, Hutchins Center for African and African American Research, Oregon Institute for Creative Research, and the IIE Artist Protection Fund. Winner of the 2017 Brunel International African Poetry Prize and an alumnus of the Iowa Writers' Workshop, he currently lives in Ames where he is a Postdoctoral Research Associate at Iowa State University. Copyright © 2022 University of Nebraska Press

Agricultural flood vulnerability assessment and risk quantification in Iowa

Agricultural lands are often impacted by flooding, which results in economic losses and causes food insecurity across the world. Due to the world's growing population, land-use alteration is frequently practiced meeting global demand. However, land-use changes combined with climate change have resulted in extreme hydrological changes (i.e., flooding and drought) in many areas. The state of Iowa has experienced several flooding events over the last couple of decades (e.g., 1993, 2008, 2014, 2016, 2019). Also, agribusiness is conducted across 85% of the state. In this research, we present a comprehensive assessment for agricultural flood risk in the state of Iowa utilizing most up-to-date flood inundation maps and crop layer raster datasets. The study analyzes the seasonal variation of the statewide agricultural flood risk by focusing on corn, soybean, and alfalfa crops. The results show that over $230 million average annualized losses estimated at statewide considering studied crop types. The crop frequency layers and corn suitability rating datasets are investigated to reveal regions with lower or higher productivity ratings. The study founds nearly half a million acres of cropland is under 2-year return period flood zone. Additionally, a data-driven flood model, Height Above the Nearest Drainage (HAND), is used to analyze performance against the FEMA maps. We found that the HAND flood maps performed with the correlation of 0.93 and 0.94 for 100-year and 500-year flood events regarding to the FEMA maps.

A global seamless 1 km resolution daily land surface temperature dataset (2003–2020)

Abstract. Land surface temperature (LST) is one of the most important and widely used parameters for studying land surface processes. Moderate Resolution Imaging Spectroradiometer (MODIS) LST products (e.g., MOD11A1 and MYD11A1) can provide this information with moderate spatiotemporal resolution with global coverage. However, the applications of these data are hampered because of missing values caused by factors such as cloud contamination, indicating the necessity to produce a seamless global MODIS-like LST dataset, which is still not available. In this study, we used a spatiotemporal gap-filling framework to generate a seamless global 1 km daily (mid-daytime and mid-nighttime) MODIS-like LST dataset from 2003 to 2020 based on standard MODIS LST products. The method includes two steps: (1) data pre-processing and (2) spatiotemporal fitting. In the data pre-processing, we filtered pixels with low data quality and filled gaps using the observed LST at another three time points of the same day. In the spatiotemporal fitting, first we fitted the temporal trend (overall mean) of observations based on the day of year (independent variable) in each pixel using the smoothing spline function. Then we spatiotemporally interpolated residuals between observations and overall mean values for each day. Finally, we estimated missing values of LST by adding the overall mean and interpolated residuals. The results show that the missing values in the original MODIS LST were effectively and efficiently filled with reduced computational cost, and there is no obvious block effect caused by large areas of missing values, especially near the boundary of tiles, which might exist in other seamless LST datasets. The cross-validation with different missing rates at the global scale indicates that the gap-filled LST data have high accuracies with the average root mean squared error (RMSE) of 1.88 and 1.33∘, respectively, for mid-daytime (13:30) and mid-nighttime (01:30). The seamless global daily (mid-daytime and mid-nighttime) LST dataset at a 1 km spatial resolution is of great use in global studies of urban systems, climate research and modeling, and terrestrial ecosystem studies. The data are available at Iowa State University's DataShare at https://doi.org/10.25380/iastate.c.5078492 (T. Zhang et al., 2021).

Beneficial Arthropods of the Corn Belt and Great Plains

This article is the first in a three‐part series on beneficial arthropods. It will highlight some beneficial insects that kill crop pests and are largely unnoticed in the Corn Belt and Great Plains. The focus will be on two groups of insects that survive by eating insect pests of crops: predators and parasitoids. Information for this article comes from the University of Illinois, Iowa State University, Kansas State University, Michigan State University, University of Minnesota, Texas A&M University, and Utah State University. Earn 1 CEU in Integrated Pest Management by reading the article and taking the quiz at https://bit.ly/3InrtoP. View all CEUs online at https://web.sciencesocieties.org/Learning‐Center/Courses.

Exploring global online course participants’ interactions: Value of high-level engagement

AbstractParticipation in online courses has become essential for training language professionals in under-resourced contexts with skills in computer-assisted language learning (CALL) (Godwin-Jones, 2014). Most online CALL courses use asynchronous computer-mediated communication (ACMC) to facilitate meaningful learning for participants. Although participants’ sustained engagement with ACMC is the target, global realities of participants interfere with their participation levels. This article investigates participants’ engagement profiles in asynchronous online discussions in an 8-week CALL-based global online course developed and implemented by a team at Iowa State University. Using a case study approach, nine focal participants’ engagement profiles have been analyzed in terms of identifying patterns of engagement in the discussion posts and their relation to the types of discussion prompts. Then, social network analysis (SNA) and thematic analysis were employed to investigate patterns of interaction among the participants in the replies. The results indicated that engagement patterns observed in discussion posts overall aligned with the primary goals of prompt types. SNA further identified two participants as social mediators to connect participants with each other. These findings are significant in that they suggest the effectiveness of using ACMC to promote co-construction of knowledge for a global audience. This article also provides implications regarding the design of discussion prompts to help maximize participant engagement with course content.

Iowa State Tops 2021 National Crops Contests

CSA NewsVolume 67, Issue 3 p. 48-49 STUDENTS Iowa State Tops 2021 National Crops Contests First published: 14 February 2022 https://doi.org/10.1002/csan.20691Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume67, Issue3March 2022Pages 48-49 RelatedInformation

Effects of late gestation nutrient restriction on cow body weight, body condition score, colostrum quality, future reproduction and subsequent calf performance

The objective of this study was to evaluate the effects of metabolizable protein and energy restriction during late gestation on the body condition score, bodyweight, and colostrum quality of fall calving cows, as well as their subsequent calf performance. For this study, 48 multiparous Angus cows were used from the Iowa State University-McNay Research and Demonstration Farm fall herd. 

Iowa State University Beef Teaching Herd Feed efficiency selection – year 1

Over the past 15 years there have been a number of research and extension efforts directed towards the improvement of feed efficiency in beef cattle. This effort had always involved herds other than the actual university’s herd, but now the university’s teaching herd has been enrolled and the developments will be made available as time moves on for the public to follow.

Subfield maize yield prediction improves when in-season crop water deficit is included in remote sensing imagery-based models

In-season prediction of crop yield is a topic of research studied by several scientists using different methods. Seasonal forecasts provide critical insights to different stakeholders who use the information for strategic and tactical decisions. In this study, we propose a novel scalable method to forecast in season subfield crop yield through a machine learning model based on remotely sensed imagery and data from a process-based crop model on a cumulative crop drought index (CDI) designed to capture the impact of in-season crop water deficit on crops. To evaluate the performance of our proposed model, we used 352 growers' fields of different sizes across the states of Michigan, Indiana, Iowa, and Illinois, with 2520 respective yield maps generated by combine harvesters equipped with precise high-resolution yield monitor sensor, over multiple years (from 2006 up to 2019). We obtained high resolution digital elevation model, climate, and soil data to execute the SALUS model, a process-based crop model, to calculate the CDI for each field used in the study. We used Landsat Analysis Ready Dataset (ARD) products generated by USGS as image source to calculate the green chlorophyll vegetation index (GCVI). We found that the inclusion of the CDI in remote sensing-based random forest models substantially improved in-season subfield corn yield prediction. The addition of the CDI in the yield prediction model showed that the greatest improvements in predictions were observed in the driest year (2012) in our case study. The proposed approach also showed that the subfield spatial variations of corn yield are better captured with the inclusion of CDI for most fields. The earliest prediction in the growing season with GCVI and CDI together outperformed the latest prediction with GCVI alone, highlighting the potential of CDI for predicting spatial variability of maize yield around grain filling period, which is on average close to two months before typical crop harvest in the US Midwest.

Instrument flying infrequency and weather decision-making for general aviation pilots -implications for flight safety in degraded visibility

IntroductionInstrument-rated private pilots (PPL-IFRs) are trained to fly in degraded visibility (where visual references are lost) and, towards maintaining proficiency, required to complete 6 instrument approaches in as many months. Nevertheless, operations in such weather carry an elevated risk of a fatal accident. Two hypotheses were advanced: (i) the majority of PPL-IFRs complete fewer than 6 instrument approaches/6 months and (ii) that a subset of such aviators still depart into such weather. Methods: Instrument approaches for a group of light aircraft in single PPL-IFR ownership (aircraft/owners) in the state with the largest count of single piston engine aircraft (Texas) was determined using Automatic Dependent Surveillance-Broadcast (ADS-B) data. Departure aerodrome weather flight category was per the Iowa State University database. IMC accidents were identified from the National Transportation Safety Board database and rates determined using GA fleet time. Statistical testing used Poisson Distribution, Chi-Square and Mann-Whitney U tests. Results: Over the Aug 2020-Mar 2021 period, 1,684 flights involving 106 aircraft/owners were ADS-B-tracked. Of these aircraft/owners, 81.2% completed < six approaches (median = 1.5). Importantly, for aircraft/owners completing < six approaches in the preceding 6 months, 24% departed into obscuration. Conclusions: This study demonstrates that, for the state most populous for reciprocating engine aircraft, the majority of aircraft in single PPL-IFR ownership fail to complete 6 in-flight instrument approaches/6 months. Nevertheless, some of these aircraft/owners elect to undertake flights in degraded visibility. From a practical perspective, PPL-IFRs unable to maintain instrument currency should be cautioned on the risks of operating in degraded visibility.

Comparison of microbial communities in replicated woodchip bioreactors.

Denitrification in woodchip bioreactors is a microbial process, but the effects of variations in bioreactors operation on microbial community structure are not well understood. Here, our goals were to understand hydraulic retention time (HRT) as a factor that influences woodchip bioreactor microbial community variation and structure in replicated field bioreactors and to evaluate relationships between microbial community membership and marker genes for denitrification. We used a combination of quantitative polymerase chain reaction of nirS, nirK, nosZI, and nosZII and 16S rRNA amplicon sequencing to characterize the microbial communities of nine pilot-scale woodchip bioreactors located at Iowa State University. Our results showed dynamic microbial communities but with persistent taxa between two sampling years and three HRTs. Similarities between functional gene copy numbers across sampling year and HRT indicate that the potential for denitrification is conserved despite differences in the microbial communities. These results are evidence that there are specific and persistent taxa within replicated bioreactors. Woodchip bioreactor microbial community membership is recommended to be the focus of future studies to better understand the relationship between microbial community functions and bioreactor management.

Classifying behavior from short-interval biologging data: An example with GPS tracking of birds.

Recent advances in digital data collection have spurred accumulation of immense quantities of data that have potential to lead to remarkable ecological insight, but that also present analytic challenges. In the case of biologging data from birds, common analytical approaches to classifying movement behaviors are largely inappropriate for these massive data sets.We apply a framework for using K‐means clustering to classify bird behavior using points from short time interval GPS tracks. K‐means clustering is a well‐known and computationally efficient statistical tool that has been used in animal movement studies primarily for clustering segments of consecutive points. To illustrate the utility of our approach, we apply K‐means clustering to six focal variables derived from GPS data collected at 1–11 s intervals from free‐flying bald eagles (Haliaeetus leucocephalus) throughout the state of Iowa, USA. We illustrate how these data can be used to identify behaviors and life‐stage‐ and age‐related variation in behavior.After filtering for data quality, the K‐means algorithm identified four clusters in >2 million GPS telemetry data points. These four clusters corresponded to three movement states: ascending, flapping, and gliding flight; and one non‐moving state: perching. Mapping these states illustrated how they corresponded tightly to expectations derived from natural history observations; for example, long periods of ascending flight were often followed by long gliding descents, birds alternated between flapping and gliding flight.The K‐means clustering approach we applied is both an efficient and effective mechanism to classify and interpret short‐interval biologging data to understand movement behaviors. Furthermore, because it can apply to an abundance of very short, irregular, and high‐dimensional movement data, it provides insight into small‐scale variation in behavior that would not be possible with many other analytical approaches.

Hydrologic investigations of radar-rainfall error propagation to rainfall-runoff model hydrographs

Rainfall is arguably the most important yet most variable input for rainfall-runoff hydrologic models. In this study, the authors search for the characteristics of radar-rainfall estimates that are most important for skillful streamflow predictions. They perform comprehensive hydrologic investigations of radar-rainfall characteristics, including spatiotemporal resolution, radar range visibility, statistical characterization of rainfall variability, all vis-a-vis basin characteristics such as size and river network topology. Since the true rainfall fields are unknown, the authors exploit a paradigm of using two independently constructed radar-rainfall products i.e., Multi-Radar Multi-Sensor and IFC-ZR used operationally by the Iowa Flood Center (IFC). Using the distributed hydrologic model called the Hillslope-Link Model for the domain of the state of Iowa, they evaluate streamflow prediction at 140 USGS gauge stations that monitor rivers in Iowa. Through spatial and temporal rainfall aggregation experiments, the authors show that the impact of spatial and temporal resolution of rainfall is significant typically for smaller basins while starts reducing significantly for basins larger than 1,000 km2. Other rainfall characteristics they explored do not reveal a strong signature in the relationship of rainfall differences between the two products and hydrograph errors. However, exploring the product similarities rather than differences reveals that the basin-wide rainfall volume has the most significant effect on streamflow prediction. The results from this study are generalizable for all rainfall observing systems.

Mitochondrial and Glycolytic Capacity of Peripheral Blood Mononuclear Cells Isolated From Diverse Poultry Genetic Lines: Optimization and Assessment.

Cellular metabolic preference is a culmination of environment, nutrition, genetics, and individual variation in poultry. The Seahorse XFe24 analyzer was used to generate foundational immune cellular metabolic data in layer, broiler, and legacy genetic strains using fresh chicken peripheral blood mononuclear cells (PBMCs). Baseline mitochondrial respiration [oxygen consumption rate (OCR)] and glycolytic activity [extracellular acidification rate (ECAR)] were determined in modern commercial laying hen (Bovans White) and broiler (Ross 308) lines, as well as the highly inbred lines of Iowa State University (L8, Fayoumi M-15.2, Spanish, Ghs-6), partially inbred broiler line, and advanced intercrosses of broiler by Fayoumi M-15.2 and broiler by Leghorn lines. Commercial broiler vs. Bovans layer and unvaccinated vs. vaccinated Bovans layer immune cell metabolic potential were compared following an in-assay pathway inhibitor challenge. Titrations consistently showed that optimal PBMC density in laying hens and broilers was 3 million cells per well monolayer. Assay media substrate titrations identified 25 mM glucose, 1 mM glutamine, and 1 mM sodium pyruvate as the optimal concentration for layer PBMCs. Pathway inhibitor injection titrations in Bovans layers and broilers showed that 0.5 μM carbonyl cyanide-4 phenylhydrazone (FCCP) and 1 μM oligomycin were optimal. Baseline OCR and ECAR were significantly affected by genetic line of bird (p < 0.05), with the dual-purpose, L8 inbred line showing the highest OCR (mean 680 pmol/min) and the partially inbred broiler line showing the greatest ECAR (mean 74 mpH/min). ECAR metabolic potential tended to be greater in modern layers than broilers (p < 0.10), indicating increased ability to utilize the glycolytic pathway to produce energy. OCR was significantly higher in vaccinated than unvaccinated hens (p < 0.05), while baseline ECAR values were significantly lower in vaccinated Bovans laying hens, showing increased oxidative capacity in activated immune cells. These baseline data indicate that different genetic strains of birds utilized the mitochondrial respiration pathway differently and that modern commercial lines may have reduced immune cell metabolic capacity compared with legacy lines due to intense selection for production traits. Furthermore, the Seahorse assay demonstrated the ability to detect differences in cellular metabolism between genetic lines and immune status of chickens.