OLD S1086: Enhancing sustainability of beef cattle production in Southern and Central US through genetic improvement
(Multistate Research Project)
Status: Inactive/Terminating
Date of Annual Report: 08/02/2021
Report Information
Annual Meeting Dates: 05/25/2021
- 05/25/2021
Period the Report Covers: 10/01/2019 - 09/30/2020
Period the Report Covers: 10/01/2019 - 09/30/2020
Participants
Name Institution EmailDavid Riley TAMU david-riley@tamu.edu
Rhonda Vann Mississippi State rcv2@msstate.edu
Bob Godfrey Univ Virgin Islands rgodfre@uvi.edu
Jeremy Powell Univ of Arkansas jerpow@uark.edu
Bryan Kutz Univ of Arkansas bkutz@uark.edu
Megan Rolf Kansas State megrolf@k-state.edu
Brittni Littlejohn Univ of Arkansas bplitt@uark.edu
Ann Straiger Auburn University Eas0115@auburn.edu
Brian Rude Mississippi State Bjr13@ads.msstate.edu
Raluca Mateescu University of Florida raluca@ufl.edu
Andy Herring TAMU Andy.herring@tamu.edu
Mike Looper University of Arkansas looper@uark.edu
Romdhane Rekaya University of Georgia rrekaya@uga.edu
Brief Summary of Minutes
Brief Summary of minutes of annual meeting: Due to the pandemic situation, the meeting was help digitally via zoom. Individual station progress reports were presented and achievements in the different objectives of the project were discussed. Collaboration opportunities including the potential for joint grant applications were explored.
Accomplishments
<p><strong><span style="text-decoration: underline;">Objective 1</span></strong><strong>: Estimate genetic variation associated with animal health and structural soundness using classical animal breeding and genomic techniques to facilitate sustainable beef cattle production systems</strong></p><br /> <ul><br /> <li><strong><em><span style="text-decoration: underline;">Eye pigmentation</span></em></strong></li><br /> </ul><br /> <p><strong> </strong></p><br /> <ul><br /> <li>Digital photographs to determine the proportion of the eyelid pigmentation were collected at multiple locations. Images were collected on Hereford cows (n=435; Texas), Angus-based cows (n=135, Arkansas), purebred Hereford calves (n=??; Mississippi) and Hereford crossbreds (n=??; Mississippi)</li><br /> </ul><br /> <p> </p><br /> <ul><br /> <li>Whole blood samples were collected from the photographed animals and were frozen.</li><br /> </ul><br /> <p> </p><br /> <ul><br /> <li>Additional phenotypes (cow traits related to weaning and calf traits) were collected for potential assessment of their association with eye pigmentation</li><br /> </ul><br /> <p> </p><br /> <ul><br /> <li>Images and whole blood samples collected at Arkansas herd will be transferred to Dr. Riley at TAMU to be added to the eye pigmentation database.</li><br /> </ul><br /> <p> </p><br /> <ul><br /> <li>Around 5,000 animals are already photographed and genotyped</li><br /> </ul><br /> <p> </p><br /> <ul><br /> <li>Images will be used to derive eye pigmentation phenotypes and blood samples will be used for SNP marker genotyping. The resulting data will be used in GWAS analyses</li><br /> </ul><br /> <p> </p><br /> <ul><br /> <li>A grant proposal let by Dr. Hanna (North Dakota University) and the collaboration of the Texas, Mississippi, and Arkansas teams was submitted to USDA-AFRI</li><br /> </ul><br /> <p> </p><br /> <ul><br /> <li><strong><em><span style="text-decoration: underline;">Udder conformation</span></em></strong></li><br /> </ul><br /> <p><strong> </strong></p><br /> <ul><br /> <li>Additional udder conformation data was collected at three Texas locations (McGregor, College Station, Menard). More than 800 cows have been scored</li><br /> </ul><br /> <p> </p><br /> <ul><br /> <li>Udder and teat scores were recorded on around 2xx cows (we need # of cows from Trent) and 9 heifers at Arkansas, Mississippi and Virgin Island stations</li><br /> </ul><br /> <p> </p><br /> <ul><br /> <li>Data is being consolidating for preliminary analyses</li><br /> </ul><br /> <p><strong> </strong></p><br /> <ul><br /> <li><strong><em><span style="text-decoration: underline;">Foot structure</span></em></strong></li><br /> </ul><br /> <p> </p><br /> <ul><br /> <li>An Angus-based fall calving cowherd (n ≈ 135) was observed and hoof scores were recorded at weaning. Cows were evaluated on a scale from 1 to 9 for foot angle and claw set according to the American Angus Association</li><br /> </ul><br /> <p> </p><br /> <ul><br /> <li>Hoof scores and (hoof angle and claw set) were collect on 24 yearling Senepol bulls (n=13) and heifers (n=11)</li><br /> </ul><br /> <p> </p><br /> <ul><br /> <li><strong><em><span style="text-decoration: underline;">Skull conformation</span></em></strong></li><br /> </ul><br /> <p><strong> </strong></p><br /> <ul><br /> <li>Skull conformation images were collected in Bos taurus, Bos indicus, and Bos taurus-Bos indicus crossbred cattle.</li><br /> </ul><br /> <p><strong> </strong></p><br /> <ul><br /> <li>A USDA-AFRI proposal was developed through the collaboration with Dr. Bryan Davis of TAMU College of Veterinary Medicine</li><br /> </ul><br /> <p> </p><br /> <ul><br /> <li>The long-term goal is to identify genomic regions that statistically associate with skull variation.</li><br /> </ul><br /> <p><strong> </strong></p><br /> <p><strong><span style="text-decoration: underline;">Objective 2</span></strong><strong>: Systems approach to analyzing novel ERTs associated with female production including longevity, fertility and meat quality database creation</strong></p><br /> <ul><br /> <li>Fertility data (traits) were collected from fall and spring calving herds (n=??) at the Mississippi station</li><br /> </ul><br /> <p> </p><br /> <ul><br /> <li>A new approach was developed to determine the minimum length of an autozygous track to be declared as a run of homozygosity segment (ROH). The implications of ROH classification on measuring inbreeding depression on growth and fertility traits were assessed using a purebred Hereford cattle population</li><br /> </ul><br /> <p><strong> </strong></p><br /> <ul><br /> <li>The effects on inbreeding on size and reproductive traits across four generations of Nellore-Angus crossbred cattle were assessed using genomic and pedigree information</li><br /> </ul><br /> <p><strong> </strong></p><br /> <ul><br /> <li>A grid search method to classify inbreeding into recent and ancient classes was developed and applied to growth and fertility traits in Herford cattle.</li><br /> </ul><br /> <p><strong><span style="text-decoration: underline;">Objective 3</span></strong><strong>: Documentation of genetic components and development of thermotolerance measurements pertaining to heat tolerance adaptive traits in sustainable beef cattle production systems</strong></p><br /> <p> </p><br /> <ul><br /> <li>Genetic parameters for hair characteristics and core body temperature in a multibreed Brahman-Angus herd were assessed</li><br /> </ul><br /> <p> </p><br /> <ul><br /> <li>Collection of phenotypic data describing thermal tolerance in <em>Bos Indicus</em> influenced populations and characterization of the genetic component underlying these traits.</li><br /> </ul><br /> <p> </p><br /> <ul><br /> <li>Mature cows and replacement heifers (n=135) were evaluated for shedding on a scale from 1 to 5 at the Mississippi station</li><br /> </ul><br /> <p> </p><br /> <p>Collection of coat scores on all herds at Texas station (2 to 4 times per year)</p>Publications
<ol><br /> <li><strong><span style="text-decoration: underline;">Referred articles </span></strong></li><br /> </ol><br /> <p> </p><br /> <p>Delgadillo Liberona*, J.S., J.M. Langdon, A.D. Herring, H.D. Blackburn, S.E. Speidel, S. Sanders, and D.G. Riley. 2020. Random regression of Hereford percentage intramuscular fat on geographical coordinates. J. Anim. Sci. 98:1–10. doi:10.1093/jas/skz359</p><br /> <p>Riley, D.G., C. Mantilla-Rojas, R.K. Miller, K.L. Nicholson, C.A. Gill, A.D. Herring, P.K. Riggs, J.E. Sawyer, J.W. Savell, and J.O. Sanders. 2020. Genome association of carcass and palatability traits from Bos indicus-Bos taurus crossbred steers within electrical stimulation status and correspondence with steer temperament 3. Aroma and flavor attributes of cooked steaks. Livest. Sci. 233:103943. <a href="https://doi.org/10.1016/j.livsci.2019.103943">https://doi.org/10.1016/j.livsci.2019.103943</a></p><br /> <p>Cooke, R.F., R.C. Cardoso, R.L.A. Cerri, G.C. Lamb, K.G. Pohler, D.G. Riley, and J.L.M. Vasconcelos. 2020. Cattle adapted to tropical and subtropical environments: genetic and reproductive considerations. J. Anim. Sci. 98:1–14. <a href="https://doi.org/10.1093/jas/skaa015">https://doi.org/10.1093/jas/skaa015</a></p><br /> <p>Riley, D.G., J.E. Sawyer, and T.M. Craig. 2020. Shedding and characterization of gastrointestinal nematodes of growing beef heifers in Central Texas. Vet. Parasitol.: X 3:100024</p><br /> <p>Rouquette, M. Jr., K.D. Norman, D.G. Riley, and R.D. Randel. 2020. Body condition of F1 (Hereford × or Angus × Brahman) cows at weaning and effects on cow-calf performance and subsequent postpartum performance. Appl. Anim. Sci. 36:890–897</p><br /> <p>Simmons, M.A.*, P.K. Riggs, S. Sanders, A.D. Herring, J.O. Sanders, and D.G. Riley. 2021. Distributional characterizations and testing for differences of relatedness and inbreeding of a subpopulation of American Hereford bulls. Transl. Anim. Sci. 5:1–10. doi: 10.1093/tas/txab008</p><br /> <p>Dikmen S., K.M. Sarlo Davila, E. Rodriguez, T.L. Scheffler, P.A. Oltenacu and R.G. Mateescu. 2020. Comparison of Tympanic and Tail Temperatures in Angus and Brahman Steers. J Anim Sci Res 4(4). dx.doi.org/10.16966/2576-6457.147</p><br /> <p>Leal-Gutiérrez J.D., M.A. Elzo, C. Carr, and R.G. Mateescu. 2020. RNA-seq analysis identifies cytoskeletal structural genes and pathways for meat quality in beef. PLOS One. 15(11): e0240895. doi:10.1371/journal.pone.0240895</p><br /> <p>Leal-Gutiérrez J.D., F.M.Rezende, J.M Reecy, L.M. Krammer, F. Peñagaricano and R.G. Mateescu. 2020. Whole genome sequence data provides novel insights into the genetic architecture of meat quality traits in beef. Frontiers in Genetics. doi: 10.3389/fgene.2020.538640</p><br /> <p>Sarlo Davila K.M., A. Howell, A. Nunez, A. Orelien, V. Roe, E. Rodriguez, S. Dikmen, and R.G. Mateescu. 2020. Genome-wide association study identifies variants associated with hair length in Brangus cattle. Animal Genetics. 51:811-814. doi: 10.1111/age.12970</p><br /> <p>Mateescu R.G., K.M. Sarlo Davila, S. Dikmen, E. Rodriguez, and P.A. Oltenacu. 2020. The effect of Brahman genes on body temperature plasticity of heifers on pasture under heat stress. J. Anim. Sci. 1:98(5):skaa126. DOI: 10.1093/jas/skaa126</p><br /> <p>Leal J.D., M.A. Elzo, and R.G. Mateescu. 2020. Identification of eQTLs and sQTLs associated with meat quality in beef. BMC Genomics. 21:104. doi.org/10.1186/s12864-020-6520-5</p><br /> <p>Sumreddee, P., S. Toghiani, E. H. Hay, A. Roberts, S. E. Aggrey, and R. Rekaya. (2020). Runs of homozygosity and analysis of inbreeding depression. J. Anim. Sci., 98(12), 1-11 <a href="https://doi.org/10.1093/jas/skaa361">https://doi.org/10.1093/jas/skaa361</a></p><br /> <p>Toghiani, S., Hay, E., Fragomeni, B., Rekaya, R., & Roberts, A. J. (2020). Genotype by environment interaction in response to cold stress in a composite beef cattle breed. <em>Animal</em>, 14(8), 1576-1587 doi:<a href="http://doi.org/10.1017/S1751731120000531">10.1017/S1751731120000531</a></p><br /> <p>Toghiani, S., Hay, E. H., Roberts, A., & Rekaya, R. (2020). Impact of cold stress on birth and weaning weight in a composite beef cattle breed. <em>Livestock Science</em>, <em>236</em>, 6 pages. doi:<a href="http://doi.org/10.1016/j.livsci.2020.104053">10.1016/j.livsci.2020.104053</a></p><br /> <p>Sumreddee, P., S. Toghiani, E. H. Hay, A. Roberts, S. E. Aggrey, and R. Rekaya. (2021). Grid search approach to discriminate between old and recent inbreeding using phenotypic, pedigree and genomic information. BMC Genomics DOI: <a href="https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-021-07872-z">10.1186/s12864-021-07872-z</a></p><br /> <p><strong><span style="text-decoration: underline;"> </span></strong></p><br /> <ol start="2"><br /> <li><strong><span style="text-decoration: underline;">Abstracts/Presentations</span></strong></li><br /> </ol><br /> <p><span style="text-decoration: underline;"> </span></p><br /> <p>Burnett, R. H., M. A. Duvic, J. G. Powell, D. Riley, and T. Smith. 2020. Evaluation of hair coat shedding ability as an adaptive trait in Angus cattle in the southern U.S. (Abstr) Southern Section Animal Science meeting, Chattanooga, TN</p><br /> <p> </p><br /> <p>Duvic, M. A., R.H. Burnett, C. Glenn, and T. Smith. 2020. Relationship of winter hair growth and performance in Angus dams. (Abstr) Southern Section Animal Science meeting, Chattanooga, TN</p><br /> <p> </p><br /> <p>deCarvalho Balieiro J. C, J. D. Leal Gutierrez, C. Paschoal V.R., Carr, M.A. Elzo, and R.G. Mateescu. Comparative transcriptomic profile for meat tenderness in a multibreed Brahman-Angus Population. 66th International Congress of Meat Science and Technology. (2020)</p><br /> <p> </p><br /> <p>Sarlo Davila K., Howell A., Nunez A., Orelien A., Roe V. Rodriguez E., Dikmen S. and Mateescu R.G. PRLR and PCCA variants associated with hair length in Brangus heifers. American Association of Animal Science Annual Meeting. Virtual meeting (2020)</p><br /> <p> </p><br /> <p>Mateescu R.G., Leal J.D., M.A. Elzo. Expression QTL mapping for meat quality in beef cattle. American Association of Animal Science Annual Meeting. Virtual meeting (2020)</p><br /> <p> </p><br /> <p>Mateescu R.G., Sarlo Davila K., Dikmen S., Nunez A., Rodriguez E., and Oltenacu P.A. Phenotypic plasticity of heat tolerance in beef cattle. American Association of Animal Science Annual Meeting. Virtual meeting (2020)</p><br /> <p> </p><br /> <p>Mateescu R.G., Leal J.D., M.A. Elzo. Integrated -omics approaches for meat quality improvement. Plant and Animal Genome Meeting, San Diego, CA. (2020)</p><br /> <p> </p><br /> <p>Sarlo Davila K., Howell A., Nunez A., Orelien A., Roe V. Rezende F., Dikmen S. and Mateescu R.G. Genome-wide association study for hair length in Brangus heifers. Plant and Animal Genome Meeting, San Diego, CA. (2020)</p><br /> <p> </p><br /> <p>Dodd, Logan T., David P. Anderson, David G. Riley, Barton Johnson, and Andy D. Herring. 2021. Assessing variability of herd sire economic value for commercial operations. J. Anim. Sci. Suppl. Abstract for ASAS meeting in Louisville.</p><br /> <p> </p><br /> <p>Mickey, Dana M., James O. Sanders, David G. Riley, and Andy D. Herring. 2021. Calf performance and sex ratios in second generation reciprocal Nellore-Angus crosses. J. Anim. Sci. Suppl. Abstract for ASAS meeting in Louisville.</p><br /> <p> </p><br /> <p>Noland, R., W. Shaffer, CM Ahlberg, K. Allwardt, A Broocks, K. Bruno, L. McPhillips, A Taylor, CR Krehbiel, CJ Richards, U DeSilva, DL CanOverbeke, RG Mateescu, LA Kuehn, RL Weaber, JM Bormann, and MM Rolf. 2020. Genome-wide association analysis for respiration rate in beef cattle. ASI Undergraduate Research Forum. Manhattan, KS. December 8.</p><br /> <p> </p><br /> <p><a href="https://uga.elements.symplectic.org/userprofile.html?uid=66015">Sumreddee P</a>, S. Toghiani, E. Hay, S. E. <a href="https://uga.elements.symplectic.org/userprofile.html?uid=2037">Aggrey</a>, and R. <a href="https://uga.elements.symplectic.org/userprofile.html?uid=1839">Rekaya.</a> Partitioning of Inbreeding Depression using Pedigree and Genomic Approaches. Journal of Animal Science 98 (Supplement_4):247-248 30 Nov 2020 </p>Impact Statements
- • Selection tends to reduce or even eliminate deleterious alleles. Therefore, more recent inbreeding is likely to have a greater contribution to inbreeding depression. Distinguishing between new and old inbreeding could provide a better assessment of genome-wide inbreeding and facilitate management of the harmful effects of inbreeding depression largely caused by accumulation of deleterious mutations. A new method to classify
Date of Annual Report: 07/06/2022
Report Information
Annual Meeting Dates: 05/24/2022
- 05/25/2022
Period the Report Covers: 10/01/2021 - 09/30/2022
Period the Report Covers: 10/01/2021 - 09/30/2022
Participants
Brief Summary of Minutes
Accomplishments
<p><strong>Annual Report S-1086</strong></p><br /> <p><strong>Years 2021 – 2022</strong></p><br /> <p> <strong>Project Title: S-1086: Enhancing sustainability of beef cattle production in Southern and Central US through genetic improvement</strong></p><br /> <p> <strong>Agencies and Principal Investigators:</strong></p><br /> <p>University of Arkansas: J. G. Powell, B. R. Kutz, B. P. Littlejohn</p><br /> <p>University of Florida: R. Mateescu</p><br /> <p>University of Georgia: R. Rekaya</p><br /> <p>Kansas State University: M. Rolf</p><br /> <p>Mississippi State University: T. Smith, R. C. Vann, B. Rude</p><br /> <p>Texas A&M University: J. O. Sanders, D. G. Riley, A. D. Herring</p><br /> <p> III. <strong>Objectives</strong>:</p><br /> <p> 1. Estimate genetic variation associated with animal health and structural soundness using classical animal breeding and genomic techniques to facilitate sustainable beef cattle production systems.</p><br /> <p> 2. Systems approach to analyzing novel ERTs associated with female production including longevity, fertility, and meat quality database creation.</p><br /> <p> 3. Documentation of genetic components and development of thermotolerance measurements pertaining to heat tolerance adaptive traits in sustainable beef cattle production systems.</p><br /> <p> <strong>Procedures</strong>:</p><br /> <p> <strong>Objective 1.1 Eye and facial pigmentation</strong></p><br /> <p> We will use photographs and digital quantification software to determine proportion of eyelid with pigmentation. Each animal will have one photo to identify the animal (primarily have used tag or brand), one of full face straight on to clarify markings, one of eye straight across on left side, one of eye aiming up (to characterize the eyelid under the upper eyelashes) on the left side, one of eye straight across on right side, and one of eye aiming up on the right side. Quantifications of pigmentation will be conducted using procedures developed by Davis et al. (2015). Multiple locations will contribute to this objective. Evaluated breed types will include 1) Hereford, 2) Hereford-<em>Bos taurus</em> crosses, and 3) Hereford-<em>Bos indicus</em> crosses (including Braford in this category even though it is recognized as a distinct breed). The target number of animals in each breed type category is 2,000.</p><br /> <p> <strong>Objective 1.2 Udder conformation</strong></p><br /> <p><strong> </strong>Cattle will be evaluated for udder conformation traits and scored according to BIF guidelines (2010) for Udder Suspension and Teat size. Scores for each trait range from 1 to 9 with 9 indicating tight suspension and small teat size and will be evaluated at weaning. In addition, any udder abnormalities such as evidence of mastitis, dead quarters, tumors, injuries or other diseases will be recorded. Cow traits related to weaning performance and calf traits to include birth weight and date, weaning weight and date and post weaning performance will be evaluated.</p><br /> <p> <strong>Objective 1.3 Foot Structure</strong></p><br /> <p><strong> </strong>Cattle will be evaluated for hoof conformation traits and scored according to American Angus Association (2015) for Claw Set and Toe Angle. Scores for each trait range from 1 to 9 with 1 indicating straight pasterns and short toes, and 9 indicating curled toes and crossed claws. Hooves will be evaluated at weaning. Additionally, trim records will be recorded. Cow traits related to reproductive performance and calf traits to include birth weight and date, weaning weight and date and post weaning performance will be evaluated.</p><br /> <p><strong>Objective 3.2 Hair Shedding</strong></p><br /> <p> Documentation of genetic components pertaining to heat tolerance adaptive traits in sustainable beef cattle production systems.Cattle will be evaluated for hair shedding scores from March through July (28 day intervals, 5 scores). Shedding scores will on a 1 through 5 scale: where 1 = slick short summer coat (100% shed); 2 = hair coat is mostly shed (75% shed); 3 = hair coat is halfway shed (50% shed); 4 = hair coat exhibits initial shedding (25% shed); and 5 = full winter coat (0% shed). In addition, cow traits related to reproductive performance, growth performance, and culling will be recorded. Calf traits to be recorded include birth weight and date, weaning weight and date.</p><br /> <p> <strong>Progress of Work:</strong></p><br /> <p> <strong>Objective 1.1</strong></p><br /> <p>Arkansas: An Angus-based fall calving cowherd (n ≈ 167) was observed and photos of eye pigmentation were collected from white-faced cows and calves at weaning in white-faced cows housed at the University of Arkansas beef research unit near Fayetteville.. Whole blood samples were also collected and frozen from calves. Cow traits related to weaning performance and calf traits to include birth weight and date, weaning weight and date were recorded for possible future evaluation. Photos and whole blood will be transferred to Dr. Riley at TAMU in order to collaborate with other locations that are involved with collecting similar data. </p><br /> <p>Mississippi- Photographs of each eye were taken on purebred Hereford and Hereford-cross calves to assess eye pigmentation. Pictures will be sent for quantification and contribution to this objective. Pictures were taken of both eyes for 26 head of purebred Hereford females and 1 Hereford X Angus female. </p><br /> <p>Texas- DNA collected on approximately 200 animals in this year (over 4,000 animals with records and DNA). More photographs (approximately 200 animals) added to the database</p><br /> <p> <strong>Objective 1.2</strong></p><br /> <p> Arkansas: An Angus-based fall calving cowherd (n ≈ 171) was observed and udder scores were recorded at calving in the Fall of 2021 and at weaning in May 2022. Cows were evaluated on a scale from 1 to 9 for udder suspension and teat size according to BIF guidelines. A score of 1 indicated a very pendulous suspension and large, balloon shaped teats and a score of 9 represented a tight suspension and refined teat size. Phenotypic data for cow age, Pre-Breeding BW, Pre-Breeding BCS , BCS of cow at weaning, BW of cow at weaning, AI pregnancy and overall pregnancy, along with calf weaning weight, and adjusted 205-day weaning weight (adjusted for dam age and calf gender) were collected. Means will be generated for suspension and teat scores by dam age. Cows receiving a suspension or teat score of 5-9 or a combination of the two will be considered to have an overall “acceptable” udder. Those that do not will be considered “unacceptable”. Cow performance data will be analyzed using the acceptability parameters described with CORR, GLIMMIX, MIXED, and FREQ procedures of SAS. Significance was declared at <em>P ≤ </em>0.05 and tendencies were observed at 0.05 < <em>P </em>≤ 0.10.</p><br /> <p>Frequency of cows in the acceptable range far outweighed the unacceptable cows at both evaluating periods 133 to 16 at calving and 162 to 4 at weaning. Udder Conformation on weaned calf performance was not significantly different (<em>P</em> > 0.24). Calf weaning weight was not affected by udder conformation (<em>P</em> > 0.46) There did exist a low negative correlation between cow age and conformation at calving and weaning (r= -0.234, -0.151 respectively). Cows with unacceptable udders had higher pre-breeding body weights (<em>P</em> = 0.32) and pre-breeding body condition scores (<em>P</em> = 0.41) compared to cows with acceptable udders. There was no correlation between udder confirmation and pre-breeding body condition scores. Udder confirmation did not affect weaning body weight (<em>P</em> = 0.812), weaning body condition scores (<em>P</em> = 0.588), overall AI conception rates (<em>P </em>= 0.753), or overall pregnancy rates (<em>P</em> = 0.601).<strong> </strong></p><br /> <p>Mississippi- Data were collected on fall calving purebred Angus, Hereford cows and spring calving commercial cows. Udder and teat scores were recorded within 24 hours after calving, during mid-lactation and at weaning. Data will be combined with other stations at the end of the project for analysis. Udder and teat scores were taken on 28 Angus and 27 purebred Hereford cows at birth, mid-lactation, and weaning.</p><br /> <p> </p><br /> <p>Texas- </p><br /> <p>Brahman udder scores mid-lactation</p><br /> <table width="100%"><br /> <tbody><br /> <tr><br /> <td width="28%"><br /> <p><strong>BIF Age</strong></p><br /> </td><br /> <td width="42%"><br /> <p><strong>Udder Suspension</strong></p><br /> </td><br /> <td width="29%"><br /> <p><strong>Teat Size</strong></p><br /> </td><br /> </tr><br /> <tr><br /> <td width="28%"><br /> <p>5 to 9</p><br /> </td><br /> <td width="42%"><br /> <p>3.375</p><br /> </td><br /> <td width="29%"><br /> <p>5.167</p><br /> </td><br /> </tr><br /> <tr><br /> <td width="28%"><br /> <p>10</p><br /> </td><br /> <td width="42%"><br /> <p>2.600</p><br /> </td><br /> <td width="29%"><br /> <p>4.400</p><br /> </td><br /> </tr><br /> <tr><br /> <td width="28%"><br /> <p>11</p><br /> </td><br /> <td width="42%"><br /> <p>3.667</p><br /> </td><br /> <td width="29%"><br /> <p>4.833</p><br /> </td><br /> </tr><br /> <tr><br /> <td width="28%"><br /> <p>12</p><br /> </td><br /> <td width="42%"><br /> <p>2.000</p><br /> </td><br /> <td width="29%"><br /> <p>5.000</p><br /> </td><br /> </tr><br /> <tr><br /> <td width="28%"><br /> <p>13+</p><br /> </td><br /> <td width="42%"><br /> <p>3.444</p><br /> </td><br /> <td width="29%"><br /> <p>5.556</p><br /> </td><br /> </tr><br /> </tbody><br /> </table><br /> <p>Correlations of weaning weight with udder suspension 0.09, and teat size –0.05.</p><br /> <p> </p><br /> <p> Brahman udder scores weaning<strong>ension</strong></p><br /> <table width="100%"><br /> <tbody><br /> <tr><br /> <td width="23%"><br /> <p><strong>BIF Age</strong></p><br /> </td><br /> <td width="50%"><br /> <p><strong>Udder Suspension</strong></p><br /> </td><br /> <td width="26%"><br /> <p><strong>Teat Size</strong></p><br /> </td><br /> </tr><br /> <tr><br /> <td width="23%"><br /> <p>5 to 9</p><br /> </td><br /> <td width="50%"><br /> <p>4.143</p><br /> </td><br /> <td width="26%"><br /> <p>6.429</p><br /> </td><br /> </tr><br /> <tr><br /> <td width="23%"><br /> <p>10</p><br /> </td><br /> <td width="50%"><br /> <p>2.500</p><br /> </td><br /> <td width="26%"><br /> <p>3.500</p><br /> </td><br /> </tr><br /> <tr><br /> <td width="23%"><br /> <p>11</p><br /> </td><br /> <td width="50%"><br /> <p>4.750</p><br /> </td><br /> <td width="26%"><br /> <p>5.250</p><br /> </td><br /> </tr><br /> <tr><br /> <td width="23%"><br /> <p>12</p><br /> </td><br /> <td width="50%"><br /> <p>4.500</p><br /> </td><br /> <td width="26%"><br /> <p>5.500</p><br /> </td><br /> </tr><br /> <tr><br /> <td width="23%"><br /> <p>13+</p><br /> </td><br /> <td width="50%"><br /> <p>4.000</p><br /> </td><br /> <td width="26%"><br /> <p>6.545</p><br /> </td><br /> </tr><br /> </tbody><br /> </table><br /> <p> Correlations of weaning weight with udder suspension –0.246, and teat size 0.269. </p><br /> <p> <strong>Objective 1.3</strong></p><br /> <p>Arkansas: An Angus-based fall calving cowherd (n ≈ 171) was observed and foot scores were recorded at weaning in May 2022. Cows were evaluated on a scale from 1 to 9 for foot angle and claw set according to the American Angus Association with 1 indicating straight pasterns and short toes, and 9 indicating curled toes and crossed claws. Phenotypic data for cow age, Pre-Breeding BW, Pre-Breeding BCS, BCS of cow at weaning, BW of cow at weaning, AI pregnancy and overall pregnancy, along with calf weaning weight, and adjusted 205-day weaning weight (adjusted for dam age and calf gender) were collected. Means will be generated for suspension and teat scores by dam age. We assigned cows with a claw or angle score between 4 and 6 to have an overall “acceptable” foot score. Those that are not “acceptable” will be deemed “unacceptable”. Cow performance data will be analyzed using the acceptability parameters described with CORR, GLIMMIX, MIXED, and FREQ procedures of SAS. Significance was declared at <em>P ≤ </em>0.05 and tendencies were observed at 0.05 < <em>P </em>≤ 0.10.</p><br /> <p> Mean Cow Age of Acceptable foot structure was 6.95 and unacceptable was 5.36. Frequency of Acceptable cows was 43 and unacceptable was 85. Acceptable foot structure had a significant impact on Pre-breeding BW (<em>P</em> < 0.001), Pre-Breeding BCS (<em>P </em>< 0.05), Weaning BW (<em>P </em>< 0.05), Weaning BCS (<em>P</em> < 0.05). Calf weaning weight was not affected by foot structure (<em>P</em> > 0.1). However, acceptable foot structure tended to impact overall AI pregnancy rates (<em>P</em> = 0.074). Positive correlation did exist between foot soundness and cow age (r=0.343), Pre-Breeding BW (r=0.312), Pre-Breeding BCS (r=.184), Weaning BW (r=0.261) and Weaning BCS (r=0.184). Calf weaning weight tended to be significantly correlated with acceptable foot soundness (r=0.158). </p><br /> <p> <strong>Objective 2</strong></p><br /> <p> Mississippi- Cow performance and fertility data were collected on 56 Angus and 28 Hereford purebreds and 87 commercial (Simbrah X Angus, Hereford X Angus) females. </p><br /> <p> Texas- Cow performance and fertility data were collected on approximately 1200 cows, most with some Brahman background. F<sub>2</sub> Nellore-Angus cow fertility did not appear to differ by how the cross was made, i.e., F<sub>1</sub> Nellore-sired bulls bred to F<sub>1</sub> Nellore-sired cows; F<sub>1</sub> Nellore-sired bulls bred to F<sub>1</sub> Angus-sired cows, etc.</p><br /> <p><strong>Objective 3</strong> </p><br /> <p>Arkansas: An Angus-based commercial beef cattle herd (n ≈ 167) was observed in 2021. Once monthly from March until July, at approximately 28-day intervals, mature cows and replacement heifers were evaluated for shedding on a scale from 1 to 5. A score of 5 indicates a full winter coat and a score of 1 represents a slick, short summer coat. Month of first shedding was defined as the month in which a cow received a hair coat score of 3 (approximately 50% shed) or less was reached. Hair coat scores were taken from April through July. Those that had not received a hair coat score of 3 by July were labeled “after”. Phenotypic data for cow age, pregnancy success, pre-breeding cow weight and body condition score, calf birth weight, weaning weight and adjusted weaning weight, and cow weaning weight and body condition score were collected and analyzed using the PROC FREQ and PROC GLIMMIX procedures of SAS. Significance was declared at <em>P ≤ </em>0.05 and tendencies were observed at 0.05 < <em>P </em>≤ 0.10.</p><br /> <p> Frequency of MFS occurred with the following order: June> May>July. Cow age was different (<em>P</em> < 0.01) with MFS group means for May = 5.0, June = 6.1 and July = 5.6 with May having the lowest age and June having the greatest age and July the intermediate age. Artificial and Natural Service breeding success was unaffected by hair coat shedding (<em>P</em> > 0.68). Cow pre-breeding body weight and body weight at weaning was not significantly different (<em>P</em> > 0.19). Calf weaning weight was not significantly different; however, calf birth weight differed (P < 0.01) with mean birth weight averaging 76, 71 and 65 pounds for calves born to cows that shed in May, intermediate for calves born to calves that shed in June, and least for calves weaned to cows that shed in July (<em>P </em>< 0.05). Cow weaning body condition score and prebreeding body condition score differed by MFS (<em>P <</em> 0.05) with cows exhibiting MFS in June showing the highest BCS at prebreeding and weaning with cows exhibiting MFS in May or June showing lower BCS at prebreeding and weaning.</p><br /> <p>Mississippi - Hair shedding scores were collected on 56 Angus and 28 Hereford purebreds and 87 commercial (Simbrah X Angus, Hereford X Angus) females. This year, a metabolism trial will be conducted with bulls from either early or late shedding dams. All bulls will receive the same diet and nutrient digestibility will be determined for each of these two groups. Data will be in next year’s report. The objective of this study was to evaluate winter hair coat shedding ability and its association with uterine artery hemodynamics. Fall calving, artificially inseminated purebred Angus females (n = 29) were observed once monthly by two trained technicians for winter hair coat shedding and given a visual hair shedding score of 1 to 5 with 1 indicating 100% shed, 2 = 75% , 3 = 50% , 4 = 25% , and 5 indicating 0% shedding of winter hair coat. Month of first shedding (MFS) was determined once a female reached an average hair shedding score of ≤ 3.5 from March until July of 2019 and 2020. Uterine artery blood flow (ABF) was determined using color Doppler ultrasonography at d 150, 180, 210, and 240 of gestation. Total uterine artery (summation of ipsilateral and contralateral arteries) and ipsilateral uterine ABF, diameter, resistance and pulsatility index (PI) were analyzed using repeated measures of the MIXED procedure of SAS with significance declared at P ≤ 0.05. Fixed effects included MFS, day, year, and the respected interactions with covariates of dam body weight, ambient temperature and order of cow ultrasonography examination considered as a random effect.</p><br /> <p>Texas- Recorded monthly winter shedding scores on approximately 70 Angus cows. Recorded approximately quarterly coat length scores on approximately 400 <em>Bos indicus</em>-influenced cows.</p><br /> <p><strong>Summary:</strong></p><br /> <p><strong>Objective 1.1</strong> </p><br /> <p> Numbers of images and corresponding DNA samples are reaching appropriate levels for genome-wide association analyses. Some interim work with image management will be required.</p><br /> <p> <strong>Objective 1.2</strong><strong> </strong></p><br /> <p> Locations have accumulated scores across lactations and across years for approximately 300 cows. </p><br /> <p><strong>Objective 1.3</strong><strong> </strong></p><br /> <p>Data was analyzed to determine if cow herd performance is affected by hoof score. Acceptable foot structure had a significant impact on pre-breeding cow BW, pre-Breeding cow BCS, cow BW at weaning, and cow BCS at weaning. Calf weaning weight was not affected by foot structure; however, acceptable foot structure tended to impact overall AI pregnancy rates in these data.</p><br /> <p><strong>Objective 2</strong> </p><br /> <p>Accumulation of records is substantial. Combination for analyses is the next step. </p><br /> <p> <strong>Objective 3</strong> </p><br /> <p>Arkansas: Data was analyzed to determine if cow herd performance is affected by month of first shedding. In these data, MFS score varied by cow age and influenced calf birth weight and cow prebreeding and weaning BCS.</p><br /> <p> Mississippi: No significant MFS by day of gestation interaction (P > 0.32) was observed for total or ipsilateral blood flow (P > 0.23). A MFS by day of gestation (P < 0.04) interaction was observed for both ipsilateral artery diameter and PI, in which females that shed by May had smaller artery diameter (0.74 vs. 0.85 cm) at day 180 of gestation and greater PI (P < 0.02; 1.48 vs. 1.03) at day 150 of gestation compared to June.</p>Publications
Impact Statements
- Impact of Research Objective 1 Udder and teat quality are among the most important functional traits of beef females. Unsound udders and teats are associated with reduced productive life and inferior calf performance, and poor udder and teat conformation is a major reason why cows are culled from the breeding herd. Understanding the implications of theses scores could improve the culling process and improve production efficiency. Udder/teat scores of Brahman cows at weaning appear to be more useful metric as they were more strongly associated with calf weaning weight than those measured mid-lactation (June) in Brahman cows. Sound feet are important components in cattle production systems and can influence nutritional aspects of cattle. Hoof soundness have been reported to have effects on breeding and reproductive success and both body weight and body composition. Implementing these scores can aid in selecting for more sound cows. Objective 3 Hair shedding scores, although subjective, are well within the reach of both commercial and seedstock breeders. By using these scores and understanding their implications in cattle production, producers can utilize them in the match of genetic resource and production resources. This could easily increase current overall production. Hair shedding scores must be considered differently in cattle with more than ¼ Bos indicus, as they do not grow or shed a winter coat the way that Bos taurus cows do. They (some) appear to just get longer or shorter coat, without a pattern of shedding.
Date of Annual Report: 07/06/2022
Report Information
Annual Meeting Dates: 05/23/2023
- 05/25/2023
Period the Report Covers: 10/01/2022 - 10/01/2023
Period the Report Covers: 10/01/2022 - 10/01/2023
Participants
Brief Summary of Minutes
Accomplishments
<p><strong>Objectives</strong>:</p><br /> <p> </p><br /> <ol><br /> <li>Estimate genetic variation associated with animal health and structural soundness using classical animal breeding and genomic techniques to facilitate sustainable beef cattle production systems.</li><br /> </ol><br /> <p> </p><br /> <ol start="2"><br /> <li>Systems approach to analyzing novel ERTs associated with female production including longevity, fertility, and meat quality database creation.</li><br /> </ol><br /> <p> </p><br /> <ol start="3"><br /> <li>Documentation of genetic components and development of thermotolerance measurements pertaining to heat tolerance adaptive traits in sustainable beef cattle production systems.</li><br /> </ol><br /> <p> </p><br /> <ol><br /> <li><strong>Procedures</strong>: </li><br /> </ol><br /> <p><strong>Objective 1.1 Eye and facial pigmentation</strong> </p><br /> <p>We will use photographs and digital quantification software to determine proportion of eyelid with pigmentation. Each animal will have one photo to identify the animal (primarily have used tag or brand), one of full face straight on to clarify markings, one of eye straight across on left side, one of eye aiming up (to characterize the eyelid under the upper eyelashes) on the left side, one of eye straight across on right side, and one of eye aiming up on the right side. Quantifications of pigmentation will be conducted using procedures developed by Davis et al. (2015). Multiple locations will contribute to this objective. Evaluated breed types will include 1) Hereford, 2) Hereford-<em>Bos taurus</em> crosses, and 3) Hereford-<em>Bos indicus</em> crosses (including Braford in this category even though it is recognized as a distinct breed). The target number of animals in each breed type category is 2,000. </p><br /> <p><strong>Objective 1.2 Udder conformation</strong><strong> </strong></p><br /> <p>Cattle will be evaluated for udder conformation traits and scored according to BIF guidelines (2010) for Udder Suspension and Teat size. Scores for each trait range from 1 to 9 with 9 indicating tight suspension and small teat size and will be evaluated at weaning. In addition, any udder abnormalities such as evidence of mastitis, dead quarters, tumors, injuries or other diseases will be recorded. Cow traits related to weaning performance and calf traits to include birth weight and date, weaning weight and date and post weaning performance will be evaluated. </p><br /> <p><strong>Objective 1.3 Foot Structure</strong><strong> </strong></p><br /> <p>Cattle will be evaluated for hoof conformation traits and scored according to American Angus Association (2015) for Claw Set and Toe Angle. Scores for each trait range from 1 to 9 with 1 indicating straight pasterns and short toes, and 9 indicating curled toes and crossed claws. Hooves will be evaluated at weaning. Additionally, trim records will be recorded. Cow traits related to reproductive performance and calf traits to include birth weight and date, weaning weight and date and post weaning performance will be evaluated.<strong> </strong></p><br /> <p><strong>Objective 2 Cow Performance </strong></p><br /> <p>Cow performance and fertility data were collected from fall and spring calving herds and will be combined from each station at the end of the project for analysis.</p><br /> <p><strong>Objective 3.2 Hair Shedding</strong></p><br /> <p> </p><br /> <p>Documentation of genetic components pertaining to heat tolerance adaptive traits in sustainable beef cattle production systems. Cattle will be evaluated for hair shedding scores from March through July (28-day intervals, 5 scores). Shedding scores will on a 1 through 5 scale: where 1 = slick short summer coat (100% shed); 2 = hair coat is mostly shed (75% shed); 3 = hair coat is halfway shed (50% shed); 4 = hair coat exhibits initial shedding (25% shed); and 5 = full winter coat (0% shed). In addition, cow traits related to reproductive performance, growth performance, and culling will be recorded. Calf traits to be recorded include birth weight and date, weaning weight and date. </p><br /> <ol><br /> <li><strong>Progress of Work:</strong></li><br /> </ol><br /> <p> </p><br /> <p><strong>Objective 1.1</strong></p><br /> <p>Arkansas: An Angus-based fall calving cowherd (n ≈ 194) was observed, and photos of eye pigmentation were collected from white-faced cows and calves at weaning in white-faced cows housed at the University of Arkansas beef research unit near Fayetteville. Whole blood samples were also collected and frozen from calves. Cow traits related to weaning performance and calf traits to include birth weight and date, weaning weight and date were recorded for possible future evaluation. Photos and whole blood will be transferred to Dr. Riley at TAMU in order to collaborate with other locations that are involved with collecting similar data. </p><br /> <p>Mississippi- Photographs of each eye were taken on purebred Hereford and Hereford-cross calves to assess eye pigmentation. Pictures will be sent for quantification and contribution to this objective. Pictures were taken of both eyes for 29 head of purebred Hereford females and 1 Hereford X Angus female. </p><br /> <p>Texas- DNA collected on approximately 200 animals in this year (over 4,500 animals with records and DNA). More photographs (approximately 200 animals) were added to the database. A graduate student at North Dakota State University is currently assessing images. Cow herd at the Martin Ranch (Menard, TX) sold because of drought conditions.<strong> </strong></p><br /> <p><strong>Objective 1.2</strong></p><br /> <p>Arkansas: The objective of this study was to determine if any relationships existed between udder conformation and production traits in cows housed at the University of Arkansas beef research unit near Fayetteville. </p><br /> <p>An Angus-based fall calving cowherd (n ≈ 194) was observed, and udder scores were recorded at calving in the Fall of 2022 and at weaning in April 2023. Cows were evaluated on a scale from 1 to 9 for udder suspension and teat size according to BIF guidelines. A score of 1 indicated a very pendulous suspension and large, balloon shaped teats and a score of 9 represented a tight suspension and refined teat size. Phenotypic data for cow age, Pre-Breeding BW, Pre-Breeding BCS, BCS of cow at weaning, BW of cow at weaning, AI pregnancy and overall pregnancy, along with calf weaning weight, and adjusted 205-day weaning weight (adjusted for dam age and calf gender) were collected. Means will be generated for suspension and teat scores by dam age. Cows receiving a suspension or teat score of 1-3 were considered undesirable, scores ranging from 4-6 were ideal and those scores 7-9 will be considered marginal. Cow performance data will be analyzed using the acceptability parameters described with CORR, GLIMMIX, MIXED, and FREQ procedures of SAS. Significance was declared at <em>P ≤ </em>0.05 and tendencies were observed at 0.05 < <em>P </em>≤ 0.10. </p><br /> <p>Very little variation in frequency of cows in the ideal and marginal category but far outnumbered the frequency of cows considered unacceptable. Overall cow frequencies at both calving and weaning for ideal, marginal, and unacceptable for udder suspension were 144, 211 and 13 respectively and teat size frequency were 195, 147 and 4 respectively. Cows that scored the tightest udders and most refine teats were also the youngest in age and those that scored the most pendulous suspension and biggest teats were the oldest cows. Correlation for cow age with suspension at calving was statistically different (r= -0.615, p<.0001). The same was true about cowage with teat size at calving (r= -0.561, p<0.561). At calving, udder suspension and teat size were moderately correlated with cow age (r=-0.394, r=-0.321 respectively). The effect of udder suspension and teat score on weaned calf performance was not significantly different (<em>P</em> > 0.13, 0.79 respectively). Cows with unacceptable suspension and teat size had higher pre-breeding body weights but were not statistically different from ideal and marginal cows. Udder Suspension and Teat size did not affect weaning body weight (<em>P</em> = 0.812), weaning body condition scores (<em>P</em> = 0.588), overall AI conception rates (<em>P </em>= 0.753), or overall pregnancy rates (<em>P</em> = 0.601).<strong> </strong></p><br /> <p>Mississippi- Data were collected on fall calving purebred Angus, Hereford cows and spring calving commercial cows. Udder and teat scores were recorded within 24 hours after calving, during mid-lactation and at weaning. Data will be combined with other stations at the end of the project for analysis. Udder and teat scores were taken on 38 Angus and 18 purebred Hereford cows at birth, mid-lactation, and weaning. </p><br /> <p>Texas- The same cows as resource herds previously described with two scores recorded: teat size scores and udder support scores 1 to 9 per BIF (2010) guidelines at birth when calves are weighed and tagged, mid-lactation 3-4 mo calf age, & one-week post-weaning. Observations at birth will be on different days according to calving. The other observations were conducted as much as possible in a single day, and as much as possible by the same person. Noting abnormalities of the udder may permit us to create analyzable traits. Assignment of accumulated data to graduate students to facilitate additional analyses.<strong> </strong></p><br /> <p><strong>Objective 1.3</strong> </p><br /> <p>Arkansas: The objective of this study was to determine if any relationships existed between foot soundness and production traits in cows housed at the University of Arkansas beef research unit near Fayetteville. An Angus-based fall calving cowherd (n ≈ 194) was observed, and foot scores were recorded at weaning in April 2023. Cows were evaluated on a scale from 1 to 9 for foot angle and claw set according to the American Angus Association with 1 indicating straight pasterns and short toes, and 9 indicating curled toes and crossed claws. Phenotypic data for cow age, Pre-Breeding BW, Pre-Breeding BCS, BCS of cow at weaning, BW of cow at weaning, AI pregnancy and overall pregnancy, along with calf weaning weight, and adjusted 205-day weaning weight (adjusted for dam age and calf gender) were collected. Means will be generated for suspension and teat scores by dam age. We assigned cows with a claw and angle score between 4 and 6 to have an overall “ideal” foot score. Those that scored 3 or 7 were considered “marginal” and any scores outside these were assigned “undesirable”. Cow performance data will be analyzed using the acceptability parameters described with CORR, GLIMMIX, MIXED, and FREQ procedures of SAS. Significance was declared at <em>P ≤ </em>0.05 and tendencies were observed at 0.05 < <em>P </em>≤ 0.10. </p><br /> <p>Mean Cow Age of ideal Claw set was 4.5, 5.6 for marginal, and unacceptable was 6.3. Mean cow age of ideal foot angle was 4.5, 5.4 for marginal, and unacceptable was 7.1 The frequency of ideal, marginal and unacceptable scores for both claw set, and foot angle were 212, 135 and 15 respectively. For claw set and foot angle, statistical differences existed for pre-breeding body weight between ideal and marginal cows (1204,1278, p=0.026, 1200,1269, p=0.021). Pre-Breeding BCS, Weaning BW, Weaning BCS, and calf weaning weight was not affected by claw set or foot angle. </p><br /> <p><strong>Objective 2 </strong></p><br /> <p>Mississippi- Cow performance and fertility data were collected on 47 Angus and 18 Hereford purebreds and 67 commercial (Simbrah X Angus, Hereford X Angus) females. </p><br /> <p>Texas- Cow performance and fertility data were collected on approximately 1200 cows, most with some Brahman background. F<sub>2</sub> Nellore-Angus cow fertility did not appear to differ by how the cross was made, i.e., F<sub>1</sub> Nellore-sired bulls bred to F<sub>1</sub> Nellore-sired cows; F<sub>1</sub> Nellore-sired bulls bred to F<sub>1</sub> Angus-sired cows, etc. </p><br /> <p><strong>Objective 3</strong></p><br /> <p>Arkansas: The objective of this study was to measure variation in hair coat shedding and determine if cowherd production performance traits were affected by timing of winter haircoat shedding in cows housed at the University of Arkansas beef research unit near Fayetteville. An Angus-based commercial beef cattle herd (n ≈ 194) was observed in 2022. Once monthly from March until July, at approximately 28-day intervals, mature cows and replacement heifers were evaluated for shedding on a scale from 1 to 5. A score of 5 indicates a full winter coat and a score of 1 represents a slick, short summer coat. Month of first shedding was defined as the month in which a cow received a hair coat score of 3 (approximately 50% shed) or less was reached. Hair coat scores were taken from April through July. Those that had not received a hair coat score of 3 by July were labeled “no shed”. Phenotypic data for cow age, pregnancy success, pre-breeding cow weight and body condition score, calf birth weight, weaning weight and adjusted weaning weight, and cow weaning weight and body condition score were collected and analyzed using the PROC FREQ and PROC GLIMMIX procedures of SAS. Significance was declared at <em>P ≤ </em>0.05 and tendencies were observed at 0.05 < <em>P </em>≤ 0.10. </p><br /> <p>Frequency of MFS occurred with the following order: June> July>May>No Shed>April. Cow age was different (<em>P</em> < 0.01) with MFS group means for April = 3.7, May = 3.9, June = 5.4, July = 5.1, and No Shed = 2.9. Artificial and Natural Service breeding success was unaffected by hair coat shedding (<em>P</em> > 0.11). Cow pre-breeding body weight and body weight at weaning were both significantly different amongst haircoat shedding groups (<em>P</em> > 0.001) with cows exhibiting MFS in April, May, June and July exhibiting similar body weights at prebreeding and weaning and cows exhibiting MFS as “No Shed” exhibiting lower body weights at prebreeding and weaning. Calf weaning weight and adjusted weaning weight was not significantly different; however, calf birth weight differed (P < 0.01) with mean birth weight averaging 73, 71, 71, 65 and 48 pounds for calves born to cows that shed in April, May, June, July and No Shed. All calf birth weights were similar amongst cows that shed in April, May, June, and July but birth weight was least for calves weaned to cows that were in the No Shed group (<em>P </em>< 0.05). Cow weaning body condition score and prebreeding body condition score did not differ by MFS (<em>P ></em> 0.05). </p><br /> <p>Mississippi- Hair shedding scores were collected on 47 Angus and 18 Hereford purebreds and 67 commercial (Simbrah X Angus, Hereford X Angus) females.<strong> </strong></p><br /> <p><strong>MS Experiment 1. </strong>Evaluation of the relationship between hair coat shedding ability and apparent digestibility in Angus cattle. The objective of this study was to evaluate winter hair coat shedding ability in conjunction with apparent forage digestibility. Data was collected on fall calving purebred Angus females with calves from March until July in 2019 (n=10) and 2020 (n=31). Dams were observed once monthly by two trained technicians for winter hair coat shedding and were given a visual score of 1 to 5. 1 indicated 100% shed, 2 = 75% shed, 3 = 50% shed, 4 = 25% shed, and 5 = 0% shed. Month of first shed (MFS) was determined when a female reached an average hair shedding score of 3.5 for any given month. Fecal samples were collected during the grazing months of March, May, and July and were then analyzed via proximate analysis to calculate apparent digestibility of crude protein (CP), acid detergent fiber (ADF), neutral detergent fiber (NDF), ash, and dry matter percentage (DM) of forage. Data were analyzed using repeated measures of the MIXED procedure of SAS with a significance declared at P 0.05. The model included MFS, month, and MFS by month interaction with year and ambient temperature as a covariate with cow ID nested within MFS Interactions of MFS by month were observed for CP, ADF, NDF, ash, and DM. Females with a MFS in May or June showed decreased CP apparent digestibility during the month of May when compared with cows reaching a MFS in April or July. For DM in July, females with an MFS in June and July were similar but decreased when compared to females with an MFS in April and May. </p><br /> <p><strong>MS Experiment 2. </strong>Evaluation of nutrient digestibility by calves born from early and late shedding Angus dams. Researchers have investigated several factors that could alter fetal growth, including nutrient restriction (Valiente et al., 2021), hair shedding (Gray et al., 2011), and extreme hot and cold temperatures (Davidson et al., 2022). Hot temperatures and increased humidity percentages in the southeast United States caused researchers to investigate the hair coats of Angus cattle in the commercial production setting. An improvement in fiber digestibility and calf birth and weaning weights has been observed in Angus dams that shed 50% of the winter hair coat by May (Gray et al., 2011; Burnett et al., 2021). Our objective of this experiment was to investigate the nutrient digestibility of Angus calves born to cows that on average, shed early compared to calves from cows that later. Newly weaned, purebred Angus bull calves (early; n = 6, late; n = 6) were housed in metabolism crates for 10 d. Prior to the trial, calves had a 14 d adaption period to a 14% CP textured feed (CPC 14% Developer, CPC Commodities, Fountain Run, KY) and offered <em>ad libitum</em> <em>Cynodon dactlyon</em> hay and water. After 3 d crate acclimation period, urine, feces, orts, and hay samples were collected for 7 d. Concentrate was offered at 0.25% of average BW. Approximately 5% samples were taken of feces, and urine samples had 1-1.5% of 25% metaphosphoric acid added to prevent ammonia volatilization, and both collections were composited by animal. Orts were collected at 0600 h daily, dried, and composited by animal. Laboratory analysis included dry matter (DM), organic matter (OM), Ash, neutral detergent fiber (NDF), acid detergent fiber (ADF), Kjeldahl N (CP), and fat. Data were analyzed using the GLM procedure of SAS 9.4 in a completely randomized design with calf as the experimental unit. Significant (<em>P</em> ≤ 0.05) means were separated using Fischer’s protected LSD. The model for intake included average daily DM and OM (kg) and adjusted by body weight (BW%). For digestibility analysis, the model included: DM, OM, ash, NDF, ADF, hemi-cellulose (HC), CP, and fat. The N retention model included: N retained (g/d), N retained/consumed (%), and N retained/DM intake (%). There were no differences between early or late calves for DM intake (5.502 ± 0.2774 kg/d; 2.251 ± 0.1247 %BW), or OM intake (5.199 ± 0.2591 kg/d; 2.128 ± 0.1166 %BW). There were no differences in digestibility for either group for DM, OM, Ash, NDF, ADF, HC, CP, or fat (Table 1.). There were also no differences in N retention in either group of calves (3.686 ± 2.0242 g/d; 4.366 ± 2.3964 %; 0.064 ± 0.0355 %). Replication and further research are needed in this area to adequately understand factors influencing nutrient digestibility in calves born from early and late shedding dams. </p><br /> <p>Texas- Recorded monthly winter shedding scores on approximately 70 Angus cows. Recorded approximately quarterly coat length scores on approximately 400 <em>Bos indicus</em>-influenced cows. </p><br /> <p>Florida- Collection of phenotypic data describing thermal tolerance in <em>Bos Indicus</em> influenced populations and characterization of the genetic component underlying these traits. Vaginal temperature was measured at 5-min intervals for 5 days in 286 cows over two years (2015 and 2017) from the multibreed herd (ranging from 100% Angus to 100% Brahman) of the University of Florida. Ambient environmental conditions were monitored using HOBO data loggers, which continuously record temperature, humidity, solar radiation, black globe temperatures, and wind speed which were used to calculate a temperature humidity index (THI). Skin samples were taken during summer (July 17, 2017 and August 7, 2018) between 0700 and 1100 h. A skin biopsy sample was collected using a 0.6 cm diameter punch biopsy instrument (Biopsy Punch, Miltex Inc., PA) and fixed in 10% formalin for approximately 24 h. Samples were dehydrated in 70% ethanol and infiltrated in liquid paraffin and stored until sectioned and stained at the UF Molecular Pathology Core. Images were obtained with the microscope in 40 X, and analyzed with ImageJ software. Sweat gland area (mm2) and sweat gland depth as the distance from the top of the sweat glands to the skin surface (mm) were determined from a constant 4.6 mm2 cropped image area. A certified technician recorded ultrasound images from yearling calves using an Aloka 500 ultrasound system: yearling ultrasound backfat (UFAT, cm) and yearling ultrasound percent intramuscular fat (UPIMF, %) phenotypes. Average information restricted maximum likelihood (AIREML) variance components, heritabilities, additive genetic correlations, and phenotypic correlations were estimated using single-trait and pairwise two-trait animal linear mixed models. The statistical model for both analyses included the direct additive genetic and residual as random effects, breed group (based on genomic breed composition) and group of data collection as class effect, except for short hair length and skin biopsy records, where group was not significant, and age at measurement as a covariate. The pedigree file consisted of 2,327 individuals, 715 sires and 1,286 dams. All analyses were performed using the airemlf90 package from BLUPF90 software (Misztal et al., 2002). </p><br /> <p>Heritability estimates for skin histology characteristics, hair characteristics, body temperature under high THI conditions, and ultrasound carcass traits are provided in <strong>Table 1</strong>. A high heritability of 0.69 was estimated for the sweat gland area while the sweat gland depth had a low heritability estimate of 0.09. Heritability was estimated to be 0.33 for short hair length (undercoat) and 0.16 for long hair length (top coat). Heritability for coat score has been estimated to be 0.6, (Turner and Schleger, 1960) and McEwan Jenkinson et al. (1975) estimated the heritability of hair follicle measurements to range from 0.15 to 0.76. The heritability for body temperature under high THI conditions was estimated to be 0.13 which is similar the heritability estimated reported for rectal temperature in a Brahman x Angus crossbred population (0.19; Riley et al., 2012) and dairy cattle (0.17; Dikmen at al., 2012). Both studies utilized cattle located in Florida. High heritability estimates were obtained for backfat (0.76) and intramuscular fat (0.37) ultrasound measures. </p><br /> <p>Two-trait AIREML estimates of direct additive genetic and phenotypic correlations between skin histology characteristics, hair characteristics, body temperature under high THI conditions, and ultrasound carcass traits are presented in <strong>Table 2</strong>. Sweat gland area had a negative genetic correlation with sweat gland depth (-0.49), short and long hair length (-0.45 and -0.28, respectively), and body temperature under high THI conditions (-0.65). These negative correlations suggest a similarity in the genetic control underlying these traits which would allow for selection of animals with large sweat glands, short hair (both topcoat and under coat), and able to maintain a lower body temperature under high THI conditions. More importantly, although weak, the genetic correlations between sweat gland area and the two production traits (backfat and intramuscular fat) were favorable (0.22 and 0.20, respectively). Similarly, there was a medium negative genetic correlation between the body temperature under high THI and the two ultrasound carcass traits, suggesting animals able to maintain a lower body temperature would be more productive. </p><br /> <table width="541"><br /> <tbody><br /> <tr><br /> <td colspan="4" width="541"><br /> <p><strong>Table 1.</strong> Additive genetic variance (σ<sup>2</sup><sub>a</sub>), residual variance (σ<sup>2</sup><sub>e</sub>), and heritability (h<sup>2</sup>) estimates for skin histology characteristics (sweat gland area and depth), hair characteristics (short and long hair length), core body temperature under high THI conditions, and ultrasound carcass traits (backfat thickness and intramuscular fat) with approximate sampling errors (in parentheses).</p><br /> </td><br /> </tr><br /> <tr><br /> <td width="181"><br /> <p><strong>Trait</strong><sup>1</sup></p><br /> </td><br /> <td width="120"><br /> <p><strong>σ<sup>2</sup><sub>a</sub></strong></p><br /> </td><br /> <td width="120"><br /> <p><strong>σ<sup>2</sup><sub>e</sub></strong></p><br /> </td><br /> <td width="120"><br /> <p><strong>h<sup>2</sup></strong></p><br /> </td><br /> </tr><br /> <tr><br /> <td width="181"><br /> <p>Sweat gland area (mm<sup>2</sup>)</p><br /> </td><br /> <td width="120"><br /> <p>2.03 (0.62)</p><br /> </td><br /> <td width="120"><br /> <p>0.89 (0.49)</p><br /> </td><br /> <td width="120"><br /> <p>0.69 (0.18)</p><br /> </td><br /> </tr><br /> <tr><br /> <td width="181"><br /> <p>Sweat gland depth (mm)</p><br /> </td><br /> <td width="120"><br /> <p>0.002 (0.004)</p><br /> </td><br /> <td width="120"><br /> <p>0.02 (0.004)</p><br /> </td><br /> <td width="120"><br /> <p>0.09 (0.15)</p><br /> </td><br /> </tr><br /> <tr><br /> <td width="181"><br /> <p>Short hair length (mm)</p><br /> </td><br /> <td width="120"><br /> <p>1.95 (1.07)</p><br /> </td><br /> <td width="120"><br /> <p>3.97 (0.99)</p><br /> </td><br /> <td width="120"><br /> <p>0.33 (0.18)</p><br /> </td><br /> </tr><br /> <tr><br /> <td width="181"><br /> <p>Long hair length (mm)</p><br /> </td><br /> <td width="120"><br /> <p>3.21 (3.39)</p><br /> </td><br /> <td width="120"><br /> <p>16.82 (3.42)</p><br /> </td><br /> <td width="120"><br /> <p>0.16 (0.17)</p><br /> </td><br /> </tr><br /> <tr><br /> <td width="181"><br /> <p>Temperature at high THI (°C) </p><br /> </td><br /> <td width="120"><br /> <p> 0.02 (0.02)</p><br /> </td><br /> <td width="120"><br /> <p>0.10 (0.018)</p><br /> </td><br /> <td width="120"><br /> <p>0.13 (0.15)</p><br /> </td><br /> </tr><br /> <tr><br /> <td width="181"><br /> <p>UFAT (cm)</p><br /> </td><br /> <td width="120"><br /> <p>0.001 (0.0003)</p><br /> </td><br /> <td width="120"><br /> <p>0.0003 (0.0002)</p><br /> </td><br /> <td width="120"><br /> <p>0.76 (0.19)</p><br /> </td><br /> </tr><br /> <tr><br /> <td width="181"><br /> <p>UPIMF (%)</p><br /> </td><br /> <td width="120"><br /> <p>0.22 (0.12)</p><br /> </td><br /> <td width="120"><br /> <p>0.38495 (0.11)</p><br /> </td><br /> <td width="120"><br /> <p>0.37 (0.19)</p><br /> </td><br /> </tr><br /> </tbody><br /> </table><br /> <p><sup>1</sup><em>UFAT, ultrasound backfat (cm); UPIMF, ultrasound intramuscular fat (%).</em></p><br /> <p> </p><br /> <p><strong>Table 2.</strong> Two-trait AIREML estimates of phenotypic and direct additive genetic correlations between skin histology properties, hair characteristics, and carcass traits. </p><br /> <table><br /> <tbody><br /> <tr><br /> <td width="91"><br /> <p><strong>Trait<sup>1</sup></strong></p><br /> </td><br /> <td width="72"><br /> <p><strong>SWGA</strong></p><br /> </td><br /> <td width="66"><br /> <p><strong>SWGD</strong></p><br /> </td><br /> <td width="66"><br /> <p><strong>SHL</strong></p><br /> </td><br /> <td width="60"><br /> <p><strong>LHL</strong></p><br /> </td><br /> <td width="72"><br /> <p><strong>THighTHI</strong></p><br /> </td><br /> <td width="54"><br /> <p><strong>UFAT</strong></p><br /> </td><br /> <td width="55"><br /> <p><strong>UPIMF</strong></p><br /> </td><br /> </tr><br /> <tr><br /> <td width="91"><br /> <p>SWGA</p><br /> </td><br /> <td width="72"><br /> <p>0.69</p><br /> </td><br /> <td width="66"><br /> <p>-0.18</p><br /> </td><br /> <td width="66"><br /> <p>-0.22</p><br /> </td><br /> <td width="60"><br /> <p>0.02</p><br /> </td><br /> <td width="72"><br /> <p>-0.23</p><br /> </td><br /> <td width="54"><br /> <p>-0.05</p><br /> </td><br /> <td width="55"><br /> <p>-0.13</p><br /> </td><br /> </tr><br /> <tr><br /> <td width="91"><br /> <p>SWGD</p><br /> </td><br /> <td width="72"><br /> <p>-0.49</p><br /> </td><br /> <td width="66"><br /> <p>0.10</p><br /> </td><br /> <td width="66"><br /> <p>0.32</p><br /> </td><br /> <td width="60"><br /> <p>0.26</p><br /> </td><br /> <td width="72"><br /> <p>0.12</p><br /> </td><br /> <td width="54"><br /> <p>0.08</p><br /> </td><br /> <td width="55"><br /> <p>0.22</p><br /> </td><br /> </tr><br /> <tr><br /> <td width="91"><br /> <p>SHL</p><br /> </td><br /> <td width="72"><br /> <p>-0.45</p><br /> </td><br /> <td width="66"><br /> <p>0.27</p><br /> </td><br /> <td width="66"><br /> <p>0.33</p><br /> </td><br /> <td width="60"><br /> <p>0.75</p><br /> </td><br /> <td width="72"><br /> <p>0.23</p><br /> </td><br /> <td width="54"><br /> <p>0.07</p><br /> </td><br /> <td width="55"><br /> <p>0.17</p><br /> </td><br /> </tr><br /> <tr><br /> <td width="91"><br /> <p>LHL</p><br /> </td><br /> <td width="72"><br /> <p>-0.28</p><br /> </td><br /> <td width="66"><br /> <p>0.02</p><br /> </td><br /> <td width="66"><br /> <p>1.00</p><br /> </td><br /> <td width="60"><br /> <p>0.16</p><br /> </td><br /> <td width="72"><br /> <p>0.23</p><br /> </td><br /> <td width="54"><br /> <p>0.04</p><br /> </td><br /> <td width="55"><br /> <p>0.11</p><br /> </td><br /> </tr><br /> <tr><br /> <td width="91"><br /> <p>THighTHI </p><br /> </td><br /> <td width="72"><br /> <p>-0.65</p><br /> </td><br /> <td width="66"><br /> <p>-0.61</p><br /> </td><br /> <td width="66"><br /> <p>-0.28</p><br /> </td><br /> <td width="60"><br /> <p>-0.45</p><br /> </td><br /> <td width="72"><br /> <p>0.13</p><br /> </td><br /> <td width="54"><br /> <p>-0.17</p><br /> </td><br /> <td width="55"><br /> <p>0.04</p><br /> </td><br /> </tr><br /> <tr><br /> <td width="91"><br /> <p>UFAT</p><br /> </td><br /> <td width="72"><br /> <p>0.22</p><br /> </td><br /> <td width="66"><br /> <p>-0.57</p><br /> </td><br /> <td width="66"><br /> <p>-0.34</p><br /> </td><br /> <td width="60"><br /> <p>-0.60</p><br /> </td><br /> <td width="72"><br /> <p>-0.38</p><br /> </td><br /> <td width="54"><br /> <p>0.76</p><br /> </td><br /> <td width="55"><br /> <p>0.23</p><br /> </td><br /> </tr><br /> <tr><br /> <td width="91"><br /> <p>UPIMF</p><br /> </td><br /> <td width="72"><br /> <p>0.20</p><br /> </td><br /> <td width="66"><br /> <p>0.49</p><br /> </td><br /> <td width="66"><br /> <p>0.08</p><br /> </td><br /> <td width="60"><br /> <p>0.09</p><br /> </td><br /> <td width="72"><br /> <p>-0.33</p><br /> </td><br /> <td width="54"><br /> <p>0.42</p><br /> </td><br /> <td width="55"><br /> <p>0.37</p><br /> </td><br /> </tr><br /> </tbody><br /> </table><br /> <p><em><sup>1</sup></em><em>SWGA, sweat gland area (mm2); SWGD, sweat gland depth (mm); SHL, short hair length (mm); LHL, long hair length (mm); THighTHI, temperature at high THI (°C); UFAT, ultrasound backfat (cm); UPIMF, ultrasound intramuscular fat (%).</em> </p><br /> <p>South Dakota- Genetic selection tools such as expected progeny differences and DNA testing are widely available in the US beef industry. However, genetic selection tools for economically relevant traits and lowly heritable traits are less widely available and frequently are less accurate. For example, genetic selection tools are not available for water intake in beef cattle. </p><br /> <p>Climate change models predict that water will become scarcer in some geographical regions of the US. Therefore, genetic selection for cattle that require less water may be beneficial to some beef producers. Our overarching hypothesis is that water requirements vary among animals based on their body weight, age, climatic factors, and genetics. Specifically, we aim to (1) correlate water requirements of beef calves and yearlings at different ages, body weights, feed intakes, and climatic factors, and (2) identify genes associated with thirst in beef calves.</p><br /> <p> We expect to estimate updated water requirements in beef calves that can be used by beef producers to predict water needs of their herd. We also expect to determine if genetics affects water intake variation and identify genes important for the thirst response in cattle. Identification of these genes will be an important first step towards understanding genetic variation of water requirements of our beef herd. This project will impact the beef industry by helping producers understand genetic and environmental effects that affect water intake of cattle. </p><br /> <p><strong>SD Experiment 1.</strong> Daily water and feed intake were collected on 27 steers from December 11 until June 8. Data were collected prior to the start of this reporting period but analyzed during the reporting period. Intake data were measured with Insentec feeders and waterers at the SDSU Cow-Calf Education and Research Facility (CCERF). Steers were weighed approximately every 28 days and daily body weights were predicted. Daily body weight was predicted by calculating average daily gain (ADG) between weigh dates and interpolating weight from ADG. Daily weather data were collected from a Mesonet weather station located 2.4 miles from the CCERF. Preliminary analyses show that: 1) liquid water intake increased as body weight and age increased (0.074 kg water intake per 1 kg body weight, P<0.05), and 2) liquid water intake increased as wind chill increased (0.364 kg water intake per 1 kg body weight; P<0.05). The increased fluid water intake with increased body weight was expected from previous reports in the literature, but little to no data has been published describing the relationship between water intake and wind chill values. Beef producers can expect decreased fluid water intake as wind chill decreases. Data on the relationships between water intake, body weight, and age can be used to update predicted water requirements of beef cattle. </p><br /> <p>The efficacy of our winter-spring model of beef calf water intake was compared with previously published water intake models using an independent sample of bull calves raised at the CCERF. The model we developed for this project had the lowest absolute value average residual (3.20) and highest squared correlation (R<sup>2</sup> = 0.81) for liquid water intake, indicating this model explained the largest fraction of water intake variation.</p><br /> <p><strong>SD Experiment 2. </strong>The effects of temperature, humidity, wind speed, and body weight on liquid water and feed intake were monitored in steers (n=25) from August to November. Data were collected prior to the start of this reporting period but analyzed during the reporting period. These steers were housed at the Cow-Calf Education and Research Facility (CCERF) and were weighed every 28 days. Data collected included daily feed and liquid water intake, body weight, and weather (temperature, solar radiation, humidity, and wind speed). Average daily gain and predicted body weight were calculated. A linear mixed effects model with random intercept and slope calculated for each animal was tested to estimate effects of these variables on water intake. Increased total water intake (P < 0.05) was correlated with dry matter intake (1.07 kg water intake/kg DMI), body weight (0.08 kg water intake/kg BW), solar radiation (1.3 kg water intake/W/m<sup>2</sup>), and ambient temperature (0.6 kg water intake/°C). Similar values were estimated for liquid water intake (P < 0.05). Increased liquid water intake was correlated with dry matter intake (0.675 kg water intake/kg DMI), body weight (0.087 kg water intake/kg BW), solar radiation (1.3 kg water intake/W/m<sup>2</sup>), and ambient temperature (0.6 kg water intake/°C).</p><br /> <p><strong> </strong><strong>SD Experiment 3</strong>. Water was withheld from calves (n=3) for 12 h prior to slaughter. After 12 h, calves (n=6; 3 controls) were slaughtered. Insentec water data confirmed that the three control calves consumed water before slaughter. Within 30 minutes of death, the hypothalamus and anterior pituitary gland were removed. The hypothalamus and anterior pituitary tissues were snap frozen in liquid nitrogen. The RNA was isolated from tissue samples, sequencing libraries prepared, and RNA-seq was initiated. Sequencing was completed on hypothalamus tissue for two treatments and two controls and anterior pituitary on one treatment and two controls. Sequencing for the remaining samples is in progress.</p><br /> <p> The sequence traces have been mapped to the bovine genome. Preliminary analysis of data identified 40 transcripts differentially expressed between water restricted and control calves (Adjusted P < 0.05). Of these 40 transcripts, 39 were up-regulated in the water restricted calves, including Arginine Vasopressin. Arginine vasopressin regulates water balance. </p><br /> <ol><br /> <li><strong>Summary:</strong> </li><br /> </ol><br /> <p><strong>Objective 1.1</strong> </p><br /> <p>Numbers of images and corresponding DNA samples are reaching appropriate levels for genome-wide association analyses. Some interim work with image management will be required. </p><br /> <p><strong>Objective 1.2 </strong></p><br /> <p><strong> </strong>Locations have accumulated scores across lactations and across years for approximately 400 cows. </p><br /> <p> <strong>Objective 1.3</strong></p><br /> <p><strong> </strong>Data were analyzed to determine if cow herd performance is affected by hoof score. Acceptable foot structure had a significant impact on pre-breeding cow BW, pre-Breeding cow BCS, cow BW at weaning, and cow BCS at weaning. Calf weaning weight was not affected by foot structure; however, acceptable foot structure tended to impact overall AI pregnancy rates in these data.</p><br /> <p> <strong>Objective 2</strong> </p><br /> <p>The accumulation of records is substantial. Combination for analyses is the next step.</p><br /> <p> <strong>Objective 3</strong> </p><br /> <p>Arkansas: Data were analyzed to determine if cow herd performance is affected by month of first shedding. In these data, MFS score varied by cow age and influenced calf birth weight and cow prebreeding and weaning BCS. </p><br /> <p>Mississippi: There is no clear trend of an association between hair shedding ability and apparent digestibility when measured on cows or their calves. Replication and further research are needed to adequately understand factors influencing nutrient digestibility in calves born from early and late shedding dams.</p><br /> <p><strong>Work plan for next year:</strong> </p><br /> <p> Continue to collect an additional year’s data and begin writing our new project.</p><br /> <p> </p>Publications
<p>Midkiff, K. A., Kegley, E. B., Krumpelman, B., Kutz, B. R., Powell, J. G. 2022. Evaluation of winter hair coat shedding on cow and calf performance in crossbred Angus cattle in Arkansas <em>Journal of Animal Science</em> (Suppl. S3 ed., vol. 100, pp. 208). DOI:10.1093/jas/skac247.378</p><br /> <p> </p><br /> <p>Baker, E.C., A.D. Herring, T.S. Amen, J.E. Sawyer, J.O. Sanders, C.A. Gill, P.K. Riggs, and D.G. Riley. 2022. Evaluation of post-weaning efficiency in Nellore-Angus crossbred steers through model predicted residual consumption. Sust. Agric. Res. 11:46–57.</p><br /> <p> </p><br /> <p>Mickey, D.M., D.G. Riley, J.O. Sanders, and A.D. Herring. 2022. Investigation of reciprocal cross effects in F2 Nellore-Angus calves. Ruminants 2:341–350. doi:10.3390/ruminants2030023</p><br /> <p> </p><br /> <p>Baker, E.C., A.E. San, K.Z. Cilkiz, B.P. Littlejohn, R.C. Cardoso, N. Ghaffari, C.R. Long, P.K. Riggs, R.D. Randel, T.H. Welsh Jr. and D.G. Riley. 2023. Inter-individual variation in DNA methylation patterns across two tissues and leukocytes in mature Brahman cattle. Biology 12, 252. doi:10.3390/biology12020252</p><br /> <p> </p><br /> <p>Ruiz-De-La-Cruz, G., A.M. Sifuentes-Rincón, E. Casas, F.A. Paredes-Sánchez, G.M. Parra-Bracamonte, D.G. Riley, G.A. Perry, T.H. Welsh, Jr., and R.D. Randel. 2023. Genetic variants and their putative effects on microRNA-seed sites: Characterization of the 3′ untranslated region of genes associated with temperament. Genes 14:1004. doi:10.3390/genes14051004</p><br /> <p> </p><br /> <p>Rodriguez E.E, H. Hamblen, S. Flowers, J.D. Leal-Gutiérrez, C. Carr, T. Scheffler, and R.G. Mateescu. 2023. Carcass and Meat quality in Brangus Steers. <em>Translational Animal Science. </em>7, 1-6, doi.org: 10.1093/tas/txad021</p><br /> <p> </p><br /> <p>Martins, T, Rocha, C.C., Driver, J.D., Rae, O., Elzo, M.A., Mateescu, R.G, et al. 2022. What a 31-year multibreed herd taught us about the influence of B. indicus genetics on reproductive performance of cows. <em>J Anim Sci</em>, skac366. doi: 10.1093/jas/skac366.</p><br /> <p> </p><br /> <p>Davidson, B.D., Sarlo Davila, K.M., Mateescu, R.G., Dahl, G.E., and Laporta, J. 2022. Effect of in utero exposure to hyperthermia on postnatal hair length, skin morphology, and thermoregulatory responses. <em>J Dairy Sci </em>105, 8898–8910. doi: 10.3168/jds.2022-22202.</p><br /> <p> </p><br /> <p>Block, J.J., M.J. Webb, K.R. Underwood, M.G. Gonda, A.A. Harty, R.R. Salverson, R.N. Funston, K.C. Olson, and A.D. Blair. 2022. Influence of maternal protein restriction in primiparous beef heifers during mid- and/or late-gestation on progeny feedlot performance and carcass characteristics. Animals. 12(5): 588. doi: 10.3390/ani12050588.</p><br /> <p> </p><br /> <p>Linde, D.A., E. van Marle-Köster, M.M. Scholtz, M.G. Gonda, J.L. Gonzalez-Hernandez, & M.D. MacNeil. 2023. Differential gene expression in the <em>Longissimus dorsi</em> of Nguni and Bonsmara bulls finished on low and high energy diets. South African Journal of Animal Science. 53(1). http://dx.doi.org/10.4314/sajas.v53i1.11</p><br /> <p> </p><br /> <p>Loftin, M. P., R.H. Burnett, B.J. Rude, and T. Smith. 2022. Evaluation of the relationship between hair coat shedding ability and apparent digestibility in Angus cattle. J. Anim. Sci. 100(Suppl. 1):1.</p><br /> <p> </p><br /> <p><span style="text-decoration: underline;">In Press:</span></p><br /> <p>Keele, J.A., M. Masaitis, B. Karisch, T. Smith, and B.J. Rude. 2023. Evaluation of nutrient digestibility by calves born from early and late shedding Angus dams. J. Anim. Sci. (Suppl.).</p>Impact Statements
- A summer-fall (August to November) model of beef calf water intake for calves raised in the Upper Midwest was developed.
Date of Annual Report: 07/18/2024
Report Information
Annual Meeting Dates: 05/22/2024
- 05/23/2024
Period the Report Covers: 10/01/2023 - 09/30/2024
Period the Report Covers: 10/01/2023 - 09/30/2024
Participants
Brief Summary of Minutes
Accomplishments
<p>1. Estimate genetic variation associated with animal health and structural soundness using classical animal breeding and genomic techniques to facilitate sustainable beef cattle production systems.</p><br /> <p> 1.1 Eye and facial pigmentation</p><br /> <p> 1.2 Udder conformation</p><br /> <p> 1.3. Hair Shedding</p><br /> <p>2. Systems approach to analyzing novel ERTs associated with female production including longevity, fertility, and meat quality database creation.</p><br /> <p>3. Documentation of genetic components and development of thermotolerance measurements pertaining to heat tolerance adaptive traits in sustainable beef cattle production systems.</p><br /> <p><strong>Arkansas</strong></p><br /> <p><strong>Procedures:</strong></p><br /> <p><strong>Obj. 1.1</strong></p><br /> <p>We will use photographs and digital quantification software to determine the proportion of eyelid with pigmentation. Each animal will have one photo to identify the animal (primarily have used tag or brand), one of full face straight on to clarify markings, one of eye straight across on left side, one of eye aiming up (to characterize the eyelid under the upper eyelashes) on the left side, one of eye straight across on right side, and one of eye aiming up on the right side. Quantifications of pigmentation will be conducted using procedures developed by Davis et al. (2015). Multiple locations will contribute to this objective. Evaluated breed types will include 1) Hereford, 2) Hereford-<em>Bos taurus</em> crosses, and 3) Hereford-<em>Bos indicus</em> crosses (including Braford in this category even though it is recognized as a distinct breed). The target number of animals in each breed type category is 2,000.</p><br /> <p><strong>Obj. 1.2</strong></p><br /> <p>Cattle will be evaluated for udder conformation traits and scored according to BIF guidelines (2010) for Udder Suspension and Teat size. Scores for each trait range from 1 to 9 with 9 indicating tight suspension and small teat size and will be evaluated at weaning. In addition, any udder abnormalities such as evidence of mastitis, dead quarters, tumors, injuries, or other diseases will be recorded. Cow traits related to weaning performance and calf traits to include birth weight and date, weaning weight and date and post weaning performance will be evaluated.</p><br /> <p><strong>Obj. 1.3</strong></p><br /> <p>Cattle will be evaluated for hoof conformation traits and scored according to American Angus Association (2015) for Claw Set and Toe Angle. Scores for each trait range from 1 to 9 with 1 indicating straight pasterns and short toes, and 9 indicating curled toes and crossed claws. Hooves will be evaluated at weaning. Additionally, trim records will be recorded. Cow traits related to reproductive performance and calf traits to include birth weight and date, weaning weight and date and post weaning performance will be evaluated.</p><br /> <p><strong>Obj. 3.2</strong></p><br /> <p>Documentation of genetic components pertaining to heat tolerance adaptive traits in sustainable beef cattle production systems. Cattle will be evaluated for hair shedding scores from March through July (28 day intervals, 5 scores). Shedding scores will on a 1 through 5 scale: where 1 = slick short summer coat (100% shed); 2 = hair coat is mostly shed (75% shed); 3 = hair coat is halfway shed (50% shed); 4 = hair coat exhibits initial shedding (25% shed); and 5 = full winter coat (0% shed). In addition, cow traits related to reproductive performance, growth performance, and culling will be recorded. Calf traits to be recorded include birth weight and date, weaning weight and date.</p><br /> <p><strong>Progress of Work:</strong></p><br /> <p><strong>Obj. 1.1</strong></p><br /> <p>The objective was to document using digital photographs a determination of proportion of the eyelid pigmentation in white-faced cows housed at the University of Arkansas beef research unit near Fayetteville.</p><br /> <p>An Angus-based fall calving cowherd (n ≈ 167) was observed, and photos of eye pigmentation were collected from white-faced cows and calves at weaning. Whole blood samples were also collected and frozen from calves. Cow traits related to weaning performance and calf traits to include birth weight and date, weaning weight and date were recorded for possible future evaluation. Photos and whole blood will be transferred to Dr. Riley at TAMU to collaborate with other locations that are involved with collecting similar data.</p><br /> <p><strong>Obj. 1.2</strong></p><br /> <p>The objective of this study was to determine if any relationships existed between udder conformation and production traits in cows housed at the University of Arkansas beef research unit near Fayetteville.</p><br /> <p>An Angus-based fall calving cowherd (n ≈ 174) was observed, and udder scores were recorded at calving in the Fall of 2023 and at weaning in May 2024 on cows ranging in age from two to thirteen years grazing endophyte-infected tall fescue. Cows were evaluated on a scale from 1 to 9 for udder suspension and teat size according to BIF guidelines. A score of 1 indicated a very pendulous suspension and large, balloon shaped teats and a score of 9 represented a tight suspension and refined teat size. Phenotypic data for cow age, Pre-Breeding BW, Pre-Breeding BCS, BCS of cow at weaning, BW of cow at weaning, AI pregnancy and overall pregnancy, along with calf weaning weight, and adjusted 205-day weaning weight (adjusted for dam age and calf gender) were collected. Means will be generated for suspension and teat scores by dam age. 4 categories of scores were created to combine categorical scores. Cows receiving a suspension or teat score of 8-9, 6-7, 4-5 and 1-3 were given scores of 1,2,3 and 4 respectively. Cow performance data will be analyzed using the acceptability parameters described with CORR, GLIMMIX, MIXED, and FREQ procedures of SAS. Significance was declared at <em>P ≤ </em>0.05 and tendencies were observed at 0.05 < <em>P </em>≤ 0.10.</p><br /> <p>Frequency of cows in the “2” category far outweighed other categories followed by “3” and then “1”. Udder Suspension at weaning had a significant effect on body weight in that the cows in the “2” category was significantly lower that “1” and “3” (p=0.0001) and those cows in the “3” (5.4) category was significantly higher for BCS than “2” (4.93) (p=0.0009). Weaned calf performance was not significantly different for Udder suspension or teat size (<em>P</em> > 0.24). Calf weaning weight was not affected by udder conformation (<em>P</em> > 0.68, P>0.17 respectively) Udder confirmation did not affect overall AI conception rates or overall pregnancy rates.</p><br /> <p><strong>Obj. 1.3</strong></p><br /> <p>The objective of this study was to determine if any relationships existed between foot soundness and production traits in cows housed at the University of Arkansas beef research unit near Fayetteville.</p><br /> <p>An Angus-based fall calving cowherd (n ≈ 179) was observed, and foot scores were recorded at weaning in May 2022. Cows were evaluated on a scale from 1 to 9 for foot angle and claw set according to the American Angus Association with 1 indicating straight pasterns and short toes, and 9 indicating curled toes and crossed claws. Phenotypic data for cow age, Pre-Breeding BW, Pre-Breeding BCS, BCS of cow at weaning, BW of cow at weaning, AI pregnancy and overall pregnancy, along with calf weaning weight, and adjusted 205-day weaning weight (adjusted for dam age and calf gender) were collected. Means will be generated for suspension and teat scores by dam age. We assigned 4 categories of scores were created to combine categorical scores. Cows receiving a suspension or teat score of 8-9, 6-7, 4-5 and 1-3 were given scores of 1,2,3 and 4 respectively. Cow performance data will be analyzed using the acceptability parameters described with CORR, GLIMMIX, MIXED, and FREQ procedures of SAS. Significance was declared at <em>P ≤ </em>0.05 and tendencies were observed at 0.05 < <em>P </em>≤ 0.10.</p><br /> <p>Mean frequency of Category 2 were substantially higher (148 cows) and cow age of category 3 were younger. There were no significant effects on any performance traits for claw set or foot angle.</p><br /> <p><strong>Obj. 3.2</strong></p><br /> <p>The objective of this study was to measure variation in hair coat shedding and determine if cowherd production performance traits were affected by timing of winter haircoat shedding in cows housed at the University of Arkansas beef research unit near Fayetteville.</p><br /> <p>An Angus-based commercial beef cattle herd (n ≈ 200) was observed in 2023. Once monthly from March until July, at approximately 28-day intervals, mature cows and replacement heifers were evaluated for shedding on a scale from 1 to 5. A score of 5 indicates a full winter coat and a score of 1 represents a slick, short summer coat. Month of first shedding was defined as the month in which a cow received a hair coat score of 3 (approximately 50% shed) or less was reached. Hair coat scores were taken from April through July. Those that had not received a hair coat score of 3 by July were labeled “no shed”. Phenotypic data for cow age, pregnancy success, calf birth weight, weaning weight and adjusted weaning weight, and cow weaning weight and body condition score were collected and analyzed using the PROC FREQ and PROC GLIMMIX procedures of SAS. Significance was declared at <em>P ≤ </em>0.05 and tendencies were observed at 0.05 < <em>P </em>≤ 0.10.</p><br /> <p>Frequency of MFS occurred with the following order: June> July>May>No Shed>April. Cow age tended to be different (<em>P</em> = 0.06) with MFS group means for May = 4, June = 4.8, July = 4, and No Shed = 3. Pregnancy by artificial insemination success was affected by MFS, with dams that shed by May, June, and July having greater AI conception rates than dams that did not shed (≥ 60% vs. 0%; <em>P </em>= 0.0212). Overall pregnancy rates were not affected by shedding scores (<em>P </em>= 0.42). Cow weaning body weight was different among hair shedding groups (<em>P </em>= 0.0071), as cows that shed by May and June had greater body weights than cows that shed in July. Additionally, weaning body condition scores tended to differ (<em>P </em>= 0.0698) with cows shedding by June having a greater body condition than cows shedding by July. Calf weaning weight and adjusted weaning weight was not significantly different; however, calf birth weight differed (<em>P</em> = 0.0102) with mean birth weight averaging 70, 69, 64, and 60 pounds for calves born to cows that shed in May, June, July and No Shed. Calf birth weights were greater for dams that shed by May and June compared to dams that shed by July (<em>P </em>≤ 0.01). Also, cows that shed by May and June tended to have greater calf birth weights compared to No Shed cows (<em>P </em>≤ 0.07). Calving intervals were not different between shedding groups (<em>P </em>= 0.41).</p><br /> <p><strong>Florida</strong></p><br /> <p><strong>Procedures:</strong></p><br /> <p><strong>Obj. 2:</strong></p><br /> <p>Collection of phenotypic data from <em>Bos Indicus</em> influenced populations (growth, ultrasound, carcass, meat palatability, fatty acid composition, mineral composition).</p><br /> <p>A total of 1,066 Brangus steers from the Seminole Tribe of Florida, Inc. born in 2014 and 2015. Cattle were fed at a contract feeder where they were provided a standard feedlot diet consisting of corn, protein, vitamins, and minerals until they reached a subcutaneous fat thickness over the ribeye of approximately 1.27 cm. As cattle achieved appropriate degrees of back fat thickness, they were transported to a commercial packing plant (FPL Food LLC., Augusta, Georgia) where they were harvested in 2016 and 2017 under USDA FSIS inspection. At 48 hours postmortem, carcasses were ribbed between the 12<sup>th</sup> and 13<sup>th</sup> rib, per industry standard and the following carcass measurements were evaluated for each animal according to USDA standards: hot carcass weight (HCW; kg); marbling score; fat over the ribeye (FOE; cm); and ribeye area (REA; cm<sup>2</sup>).</p><br /> <p>Following carcass evaluation, one exposed 2.54 cm thick ribeye steak was removed from the <em>longissimus lumborum</em> of each carcass, posterior to the 12th rib. The steaks were kept on ice and transferred to the University of Florida Meat Processing Center (Gainesville, Florida). Steaks were then trimmed of external fat and connective tissue. A thin shaving across the entire surface of the steak was removed from each sample and frozen at -20 °C for subsequent fatty acid composition, mineral concentration, and DNA extraction.</p><br /> <p><strong><em>Fatty Acid Extraction and Gas Chromatography Analysis</em></strong></p><br /> <p>Fatty acid extraction was performed as described in Flowers et al. (2018). FA extraction and analysis was performed at the W. M. Keck Metabolomics Research Laboratory, Iowa State University (Ames, IA). About 200 mg of finely ground steak sample was dissolved in 1 mL of 2:1 Chloroform-Methanol mixture. The extracted fats were trans-esterified with 25% Sodium Methoxide in methanol. The resulting Fatty Acid Methyl Esters (FAMEs) were extracted into hexane. For detection, 1 µl of sample was injected into Agilent 7890A GC-FID instrument, a Gas Chromatograph equipped with a flame ionization detector for separation and quantification of the FAMEs. The analysis was performed on Agilent CP-Wax 52CB column (15m, 0.32mm, 0.5µm). The oven temperature program was as follows: initial temperature of 100 °C, increased by 2 °C/min to 170 °C, then increased by 0.5 °C/min to 180 °C, finally increased by 1 °C/min to a temperature of 250 °C and held for three minutes. The inlet and detector temperatures were 250 and 220 °C, respectively. Helium was used as the carrier gas and Supelco 37 FAME mix (Catalog # CRM47885 SUPELCO) was used to generate the calibration curve for identification and quantification of FAMEs. Because marbling is a measure of intramuscular fat and because fat content measures are skewed, for analysis, measured FA were expressed as percentages of the total fat and further classified as saturated, monounsaturated, or polyunsaturated.</p><br /> <p><strong><em>Mineral Analysis</em></strong></p><br /> <p>Mineral content was measured using inductive coupled plasma-optical emission spectroscopy (ICP-OES, SPECTRO Analytical Instruments, Mahwah, NJ) as described in Mateescu et al. (2013a and 2013b) and Flowers et al. (2018). Briefly, finely ground steak samples were dried at 105 °C over an 18 hour period according to AOAC official methods 934.01 (Davis and Lin, 2005). Moisture content was calculated, and dried samples were processed using a closed-vessel microwave digestion (CEM, MDS-2000, Matthews, NC) in 5 ml concentrated nitric acid and 2 ml 30% hydrogen peroxide according to AOAC official methods 999.10 (Jorhem et al., 2000). The microwave was programmed as follows: 250 W for 5 min, 630 W for 5 min, and 500 W for 20 min followed by a 15 min resting period. Samples were then diluted in deionized water and concentrations of calcium, copper, iron, magnesium, zinc, potassium, sodium, and phosphorus were measured by ICP-OES.</p><br /> <p><strong>Results</strong></p><br /> <p>Brangus cattle had palmitic acid levels as low as 21%, and stearic acid levels as high as 26%, which is notable since stearic acid is considered to have a neutral or potentially beneficial impact on cholesterol levels, unlike other saturated fats. Additionally, Brangus cattle had oleic acid levels as high as 53%, enhancing the meat's nutritional value, and sensory qualities, thereby aligning with consumer preferences for healthier and tastier beef. The study also showed linoleic acid concentrations as high as 12% in Brangus cattle, an essential omega-6 FA crucial for human health, highlighting the Brangus breed's potential for providing nutritionally enriched beef. Saturated FA showed weak negative correlations (-0.06 to -0.15) with hot carcass weight, marbling, and fat over ribeye, similar to polyunsaturated FA which had moderate negative correlations (-0.19 to -0.37) with these traits. Conversely, monounsaturated FA were positively correlated (0.16 to 0.34) with these traits, suggesting that higher levels of monounsaturated FA, particularly oleic acid, are associated with improved meat quality and consumer-desirable traits such as increased marbling. The study also highlighted a unique relationship in Brangus cattle, where higher marbling is linked with increased monounsaturated FA and decreased saturated FA, differing from other breeds where increased intramuscular fat typically raises FA saturation levels. Overall, the study underscores the intricate relationships between FA composition, mineral content, and meat quality traits, with implications for breeding and nutrition strategies aimed at improving meat quality and healthfulness.</p><br /> <p><strong>Obj. 3:</strong></p><br /> <p>Collection of phenotypic data describing thermal tolerance in <em>Bos Indicus</em> influenced populations and characterization of the genetic component underlying these traits.</p><br /> <p>This study utilized 1,681 two-year old commercial Brangus replacement heifers from the Seminole Tribe of Florida, Inc. in Okeechobee FL, and 720 one-year old commercial Brangus replacement heifers from Williamson Cattle Company in Chiefland, FL. Samples and measurements were collected from groups of 150-200 heifers during the summer. This occurred in the following periods: from July 31st to August 21st in 2017, from July 25th to August 15th in 2018, on July 26th and August 9th in 2021, and on July 27th and August 3rd in 2022. Animals from the Seminole Tribe of Florida, Inc. were measured in eight collection groups during 2017 and 2018, while the Williamson Cattle Company heifers were measured in 4 groups during 2021 and 2022.</p><br /> <p><strong><em>Skin histology preparation</em></strong></p><br /> <p>Skin biopsies were collected from the shoulder, 4 inches down from the spine and halfway along the horizontal axis. The skin was cleaned and disinfected using 70% ethanol and chlorhexidine solution (Clorhexidine 2%; VetOne, Boise, ID), sprayed with 4% Lidocaine Tropical Anesthetic Spray, then punched with a 6-mm biopsy punch (Biopsy Punch, Miltex Inc., PA). Biopsies were placed in 10% formalin and stored at room temperature for 16 – 24 h to allow for fixation. Using a razor blade, biopsies were sliced vertically in half and placed cut side down in 70% ethanol-soaked cassettes. Samples were dehydrated in 70% ethanol, infiltrated in liquid paraffin, and stored until sectioned and stained at the UF Molecular Pathology Core. Sections were cut on a microtome with a thickness of 7μm and four sections from each animal were placed on one slide and stained with Harros-Eosin Hematoxylin. Histology slides were photographed using a Nikon T3000 inverted phase microscope (DMZ1200F with NIS Image Elements software) and phenotypes of interest were measured using computer software, ImageJ [9]. One of the four sections was selected based on clear visualization of phenotypes of interest for further analysis. A total area of 1100 × 1100 pixels was used on each picture.</p><br /> <p><strong><em>Sweat gland phenotypes</em></strong></p><br /> <p>Sweat gland phenotypes included: sweat gland area (mm<sup>2</sup>, Fig. 1) measured as the total area occupied by sweat glands in the 1100 × 1100-pixel image section, sweat gland depth (mm, Fig. 1) as the distance from the top of the sweat glands to the skin surface, and sweat gland length (mm, Fig. 1) as the difference between the bottom of the sweat gland to the skin surface and the top of the sweat gland to the skin surface. Sweat gland depth and length were measured in two different locations on each histology slide and the average of the two measurements was used for statistical analysis. Pixels were converted to millimeters using the following conversion formula: 1,000 pixels = 2.145mm.</p><br /> <p>All animals were genotyped with the Bovine GGP F250K, and BLUPF90 software was used to estimate genetic parameters and for Genome Wide Association Study.</p><br /> <p><strong>Results</strong></p><br /> <p>Sweat gland phenotypes heritability ranged from 0.17 to 0.42 indicating a moderate amount of the phenotypic variation is due to genetics, allowing producers the ability to select for favorable sweat gland properties. A weighted single-step GWAS using sliding 10kb windows identified multiple Quantitative trait loci (QTLs) explaining a significant amount of genetic variation. QTLs located on BTA7 and BTA12 explained over 1.0% of genetic variance and overlap the <em>ADGRV1 </em>and<em> CCDC168</em> genes<em>, </em>respectively. The variants identified in this study are implicated in processes related to immune function and cellular proliferation which could be relevant to heat management. Breed of Origin Alleles (BOA) were predicted using local ancestry in admixed populations (LAMP-LD), allowing for identification of markers’ origin from either Brahman or Angus ancestry. A BOA GWAS was performed to identify regions inherited from particular ancestral breeds that might have a significant impact on sweat gland phenotypes.</p><br /> <p><strong>Mississippi</strong></p><br /> <p><strong>Procedures:</strong></p><br /> <p><strong>Obj. 1.1:</strong></p><br /> <p>Photographs of each eye were taken on purebred Hereford and Hereford-cross calves to assess eye pigmentation. Pictures will be sent for quantification and contribution to this objective.</p><br /> <p><strong>Obj. 1.2:</strong></p><br /> <p>Data were collected on fall calving purebred Angus, Hereford cows and spring calving commercial cows. Udder and teat scores were recorded within 24 hours after calving, during mid-lactation and at weaning. Data will be combined with other stations at the end of the project for analysis.</p><br /> <p><strong>Obj. 2:</strong></p><br /> <p>Cow performance and fertility data were collected from fall and spring calving herds and will be combined with other stations at the end of the project for analysis.</p><br /> <p><strong>Obj. 3:</strong></p><br /> <p>Hair shedding scores and BCS were collected on all spring and fall calving cows.</p><br /> <p><strong>Progress of Work:</strong></p><br /> <p>For objective 1.1 and 1.2 and 3.2, data were collected for pooling with other stations for an overall analysis.</p><br /> <p><strong>Obj. 1.1:</strong></p><br /> <p>Pictures were taken of both eyes for 66 head of purebred Hereford and Hereford Angus cross females</p><br /> <p><strong>Obj. 1.2:</strong></p><br /> <p>Udder and teat scores were taken on 51 Angus and 21 purebred Hereford cows at birth, mid-lactation, and weaning.</p><br /> <p><strong>Obj. 2:</strong></p><br /> <p>Cow performance and fertility data were collected on 51 Angus and 19 Hereford purebreds and 69 commercial (Simbrah X Angus, Hereford X Angus) females.</p><br /> <p><strong>Solubility and degradation of inositol in a rumen environment</strong></p><br /> <p>The accumulation of myo-inositol, a fertility-promoting molecule found in the body, has been shown to enhance breeding performance and pregnancy success in both males and females across several species, including cattle (Martins, et al., 2022). There have also been studies that show positive reproductive effects of oral supplementation in men and women. However, oral supplementation of inositol to ruminant species has not been evaluated. It is unknown if inositol is soluble in the rumen environment, if it is degraded by the microbial populations which exist in this environment, or the timeframe of any potential ruminal degradation of the molecule resulting from oral supplementation. The objectives of this study were to 1) evaluate disappearance (solubility) of different forms of inositol (myo-,and chiro-) and Pyrroloquinoline Quinone (PQQ); and 2) to quantify the in-vitro ruminal degradability of myo-inositol over time. Inositol (0.25g) was placed in Ankom bags and heat sealed. The bags were placed in glass fleakers with an artificial saliva solution and rumen fluid, then incubated at 39 C in a warm shaker bath to simulate ruminal digestion. For the first trial, two bags of myo-inositol, chiro-inositol, and PQQ were removed from incubation at 1, 2, 4, 8, 12, 24, and 48 hr. post initial incubation. These were then evaluated for disappearance of each form of inositol from the Ankom bag and repeated for a total of five replicates. For the second trial, only myo-inositol was evaluated. In addition to bag removal at the same time points, duplicate ruminal fluid samples were collected for myo-inositol concentration determination. This trial had seven replicates. For all forms of inositol 0.00% was removed at 0 hr., and by 1 hr. 99.0 % inositol had disappeared (P > 0.05). There were two exceptions, PQQ-inositol, at 1 hr. was less (P < 0.0001; 96.33 %) and at 4 hr. (98.46 %). For the second trial, myo-inositol disappearance increased (P = 0.0001) from 0.00 % at 1 hr. to 99.53 % at 1 hr. and remained constant (P > 0.05) for subsequent sampling times. Ruminal fluid concentration of myo-inositol increased (P < 0.0001) from 0.197 to 5.39 g/L, and remained constant (P > 0.05) until hour 24 when it had decreased (P < 0.0001) to 2.766 g/L, and decreased (P, 0.0001) further by 48 hours to 0.377 g/L. Ruminal concentration of myo-inositol was not different (P > 0.05) between 0 hr. and 48 hr. This data indicates that inositol is soluble in the rumen environment, though not immediately, with inositol concentrations peaking between 12 and 24 hours and disappearing mostly by hour 48.</p><br /> <p><strong>Obj. 3:</strong></p><br /> <p>Hair shedding scores were collected on 51 Angus and 19 Hereford purebreds and 69 commercial (Simbrah X Angus, Hereford X Angus) females.</p><br /> <p><strong>Texas</strong></p><br /> <p><strong>Procedures:</strong></p><br /> <p><strong>Obj 1.1:</strong></p><br /> <ol><br /> <li>Approximately 150 calves with records</li><br /> <li>Graduate student at North Dakota State University is analyzing data associated with images.</li><br /> <li>Machine learning algorithms are being implemented to quantify eye pigmentation in various eye structures.</li><br /> <li>Over 6,000 animals with images.</li><br /> </ol><br /> <p><strong>Obj. 1.2:</strong></p><br /> <p>Consolidation of data into single spreadsheet for analyses.</p><br /> <p>Brahman and Hereford crossbred cows, two scores collected near parturition, mid-lactation (June) and post weaning.</p><br /> <p><strong>Obj. 2:</strong></p><br /> <p>Data accumulated on approximately 1,000 producing females in 2023-2024.</p><br /> <p><strong>Obj. 3:</strong></p><br /> <p>Consolidation of data into single spreadsheet for analyses.</p>Publications
<p><strong>Arkansas</strong></p><br /> <p>Midkiff, K. A., Kegley, E. B., Krumpelman, B., Kutz, B. R., Powell, J. G. (2022). Evaluation of winter hair coat shedding on cow and calf performance in crossbred Angus cattle in Arkansas <em>Journal of Animal Science</em> (Suppl. S3 ed., vol. 100, pp. 208). DOI:10.1093/jas/skac247.378</p><br /> <p><strong>Florida</strong></p><br /> <p>Hernandez, A.S., Zayas, G.A., Rodriguez, E.E., Sarlo Davila K.M., Rafiq F., Andrade A.N., Titto CG, and <span style="text-decoration: underline;">Mateescu, R. G.</span> Exploring the genetic control of sweat gland characteristics in beef cattle for enhanced heat tolerance. <em>J Animal Sci Biotechnol</em> <strong>15</strong>, 66. <a href="https://doi.org/10.1186/s40104-024-01025-4">https://doi.org/10.1186/s40104-024-01025-4</a></p><br /> <p>Zayas, G. A., Rodriguez, E. E., Hernandez, A. S., Rezende, F. M., and <span style="text-decoration: underline;">Mateescu, R. G.</span> Exploring genomic inbreeding and selection signatures in a commercial Brangus herd through functional annotation<em>. J Appl Genetics.</em> doi: 10.1007/s13353-024-00859-y</p><br /> <p>Pantoja MH, Novais FJ, Mourão GB, Mateescu RG, Poleti MD, Beline M, Monteiro CP, Fukumasu H, and Titto CG. 2024. Exploring candidate genes for heat tolerance in ovine through liver gene expression. <em>HELIYON</em>. doi: <a href="https://doi.org/10.1016/j.heliyon.2024.e25692">https://doi.org/10.1016/j.heliyon.2024.e25692</a></p><br /> <p>Martins T, Rocha CC, Driver J, Rae DO, Elzo MA, Mateescu RG, Santos J and Binelli M. 2024. Intermediate Proportion of B. Indicus Genetics Favors the Productivity of Crossbred Beef Cows Reared in Subtropical Conditions. <a href="http://dx.doi.org/10.2139/ssrn.4671040">http://dx.doi.org/10.2139/ssrn.4671040</a></p><br /> <p>Andrade Pantoja MH, Poleti MD, Novais FJ, Souza Duarte KK, Mateescu RG, Mourão GB, Coutinho LL, Fukumasu H, and Titto CG. 2023. Skin transcriptomic analysis reveals candidate genes and pathways associated with thermotolerance in hair sheep. <em>International Journal of Biometeorology.</em> 68:435–444. doi.org/10.1007/s00484-023-02602-4</p><br /> <p>Hoorn QA, Zayas GA, Rodriguez EE, Jensen LM, Mateescu RG, Hansen PJ. Identification of quantitative trait loci and associated candidate genes for pregnancy success in Angus-Brahman crossbred heifers. 2023. <em>J Anim Sci Biotechnol. </em>4(1):137. doi: 10.1186/s40104-023-00940-2.</p><br /> <p>Mateescu R.G., K.M. Sarlo Davila, A.S. Hernandez, A.N. Andrade, G.A. Zayas, E.E. Rodriguez, S. Dikmen, and P.A. Oltenacu. 2023. Impact of Brahman genetics on skin histology characteristics with implications for heat tolerance in cattle. <em>Frontiers in Genetics.14:1107468</em>. doi: 10.3389/fgene.2023.1107468</p><br /> <p><strong>Texas</strong></p><br /> <p>Young, C.L., D.G. Riley, R.D. Randel, and T.H. Welsh, Jr. 2023. Factors affecting antibody-mediated immune response and cellular-mediated immune response in weaned Brahman calves. Ruminants 3:385–400. https://doi.org/10.3390/ruminants3040032</p><br /> <p>Earnhardt-San, A.L., E.C. Baker, D.G. Riley, N. Ghaffari, C.R. Long, R.C. Cardoso, R.D. Randel, and T.H. Welsh, Jr. 2023. Differential expression of circadian clock genes in the bovine neuroendocrine adrenal system. Genes 14:2082. https://doi.org/10.3390/genes14112082</p><br /> <p>Dodd, L.T., D.P. Anderson, D.G. Riley, and A.D. Herring. 2024. Economic-impact variability among F1 Nellore-Angus herd sires reared together and used in multiple-sire mating groups. Appl. Anim. Sci. 40:69–79. https://doi.org/10.15323/aas.2023.02419</p><br /> <p>Ruiz-De-La-Cruz, G., A.M. Sifuentes-Rincón, F.A. Paredes-Sánchez, G.M. Parra-Bracamonte, E. Casas, D.G. Riley, G.A. Perry, T.H. Welsh, Jr., and R.D. Randel. 2024. Analysis of nonsynonymous SNPs in candidate genes that influence bovine temperament and evaluation of their effect in Brahman cattle. Mol. Biol. Rep. 51:285. https://doi.org/10.1007/s11033-024-09264-4</p><br /> <p>Munguía Vásquez, M.F., C.A. Gill, P.K. Riggs, A.D. Herring, J.O. Sanders, and D.G. Riley. 2024. Genetic evaluation of crossbred Bos indicus cow temperament at parturition. J. Anim. Sci. 102:1–10. https://doi.org/10.1093/jas/skae022</p><br /> <p>Baker*, E.C., II, A.E. Earnhardt, K.Z. Cilkiz*, B.P. Littlejohn, R.C. Cardoso, N. Ghaffari, C.R. Long, P.K. Riggs, T.H. Welsh Jr., and D.G. Riley. 2023. Stress, DNA methylation and their implications in cattle production. Proc. 69th Annual Texas A&M Beef Cattle Short Course. Pages 350 to 355.</p><br /> <p>Riley, D.G., M.F. Munguía Vásquez, A.D. Herring, C.A. Gill, P.K. Riggs, and J.O. Sanders. 2023. Genetics of bovine temperament and cow temperament at parturition. Proc. Northern Beef Res. Update Conf. North Australia Beef Research Council.</p>Impact Statements
- Udder and teat quality are among the most important functional traits of beef females. Unsound udders and teats are associated with reduced productive life and inferior calf performance, and poor udder and teat conformation is a major reason why cows are culled from the breeding herd. Understanding the implications of these scores could improve the culling process and improve production efficiency.
- Sound feet are important components in cattle production systems and can influence nutritional aspects of cattle. Hoof soundness has been reported to have effects on breeding and reproductive success and both body weight and body composition. Implementing these scores can aid in selecting for more sound cows.
- Hair shedding scores, although subjective, are well within the reach of both commercial and seedstock breeders. By using these scores and understanding their implications in cattle production, producers can utilize them in the match of genetic resource and production resources. This could easily increase current overall production.
- Selection for more docile temperament in cows may be offset by decreased performance in critical reproductive traits such as calving or weaning rate and calf survival.
- SNP genotypes in the pseudo-autosomal region of the X chromosome in Bos indicus-Bos taurus crossbred cattle appear to be strongly associated with prenatal growth.
- Custom SNP panels for cow fertility appear to have limited value across breeds and breedtypes of cows.