bluuebunny/crossref_metadata_2025_split huggingface dataset:
187 Protocols, standard operating procedures, and employee training to improve milk safety and quality
Authors: Chahine Mireille , Rovai Maristela 
Published: November 2020

Abstract
Dairy farm employees play a key role in ensuring the highest quality milk being delivered to manufacturers. Major concerns associated with milk quality on dairies include the number of clinical mastitis cases, elevated somatic cell counts, elevated bacteria count, and presence of residues in raw milk. All these factors are impacted by the knowledge, skills, and performance of dairy employees working in the milking parlor and other areas of the operation. Exemplary performance on dairies is driven by effective training, motivation, and communication between various team members. Standard operating procedures (SOPs) provide a basis for training employees, improving consistency between and within shifts, and conducting performance evaluations with valuable feedback. SOPs also have the potential to improve milk quality, herd performance, and herd health. SOPs should be specific to the dairy operation and developed with detailed instructions on completing a task. These procedures need to be written in the employees’ native language in addition to English and should be easy to read and understand. The font used should be large and when appropriate, photos should be used to explain or highlight step by step procedures. Once developed, SOPs need to be evaluated at least once a year and revised as needed. Regular trainings are also important for prevention of procedural drifts. Hybrid learning models combining classroom/online and hands-on activities should be considered and implemented. This approach ensures that dairy employees are engaged and appropriately trained, independent of their literacy and reading proficiency. Dairies should also strive to provide a positive, safe, and comfortable work environment for their employees. A positive environment can lead to improvements in employee morale, performance, and retention. Finally, it is important to establish clear and firm expectations on producing the highest quality of milk while providing specific, timely, and constructive feedback.
17 Challenges and implications of feeding diets with excess concentrations of leucine to growing-finishing pigs
Authors: Tokach Mike D , Cemin Henrique S , Kerkaert Hayden R , Woodworth Jason C , Dritz Steve S , DeRouchey Joel M , Goodband Robert D 
Published: November 2020

Abstract
Excess dietary leucine stimulates the key enzymes involved in branched-chain catabolism causing breakdown of all branched-chain amino acids, including isoleucine and valine. Branched-chain amino acids share a common brain transporter with other large neutral amino acids (LNAA). Excess levels of one of the LNAA increases brain uptake of that amino acid and decreases the uptake of the other LNAA, including tryptophan. Thus, excess leucine can impact the requirements for many amino acids. From a practical basis, this effect was first demonstrated with diets containing blood meal, but was thought to be of limited concern unless high blood meal diets were fed. Use of corn dried distillers grains with solubles (DDGS) or high protein DDGS in corn-based diets results in diets containing excess leucine. These high leucine levels are of limited concern if adequate levels of other branched-chain amino acids and LNAA are fed, which is often the case if the diet consists largely of intact protein sources. Feed grade amino acids, such as L-lysine, L-threonine, L-tryptophan, DL-methionine, L-valine, and L-isoleucine have been widely adopted as a means to lower nitrogen excretion and diet cost. Including these amino acids in diets containing corn products reduces dietary leucine; but the resulting diets are formulated near the requirement for the first 6 limiting amino acids, including valine, isoleucine, and tryptophan, while still being high in leucine. The excess leucine increases the requirements for valine, isoleucine, and possibly other LNAA, such as tryptophan and possibly others. The exact relationship between these amino acids and how to handle them in practical diet formulation is still being elucidated; however, recent meta-analysis and experimental data confirm the importance of these ratios and provide useful direction for future research.
112 Young Scholar Presentation: Protein and Amino Acid Nutrition in Fresh Cows
Authors: Tebbe Alex , Weiss Bill 
Published: November 2020

Abstract
During the 4 weeks after parturition, postpartum dairy cows (i.e., fresh cows) have the highest risk of disease and metabolic disorders. This is largely because nutrient requirements for lactation outweigh the cow’s metabolizable intake. As a result, cows enter negative nutrient balances and mobilize endogenous protein and energy stores to meet demands. Although negative energy balance, in terms of mass, is more negative than protein balances over this time frame, intake of metabolize protein (MP) and its amino acid (AA) profile may influence the performance and health of fresh cows more than increasing energy intake. Better performance from greater MP and AA supplies may also carry over and enhance milk production further into lactation. In our recent experiment, increasing MP supplies to fresh cows by feeding a greater rumen undegradable protein concentration (RUP; 7 vs 10% of DM) also increased milk and milk component yields. However, when the AA profile of the supplemental RUP was optimized to mimic the AA profile of casein, the greater yields were sustained much further into lactation. This may be because fresh cows fed the “casein like AA profile” had improved health and less body protein catabolism than cows fed a similar MP concentration. However, production responses with a greater MP intake depended on what the RUP replaced in the diet and on parity. When replacing forage fiber with RUP instead of nonforage fiber, multiparous cows had a reduction in milk and milk fat yields whereas primiparous cows performed similarly regardless of what type fiber was replaced. This suggested reducing forage fiber in a high MP diet will not increase overall MP intake, and multiparous cows may require more forage fiber during the fresh period than primiparous cows. Overall, MP intake and the AA supply is important for the health and production of fresh cows.
193 Equine teaching programs – where do they fit?
Authors: Anderson Kathy 
Published: November 2020

Abstract
Equine teaching programs in Animal Science Departments throughout the Midwest region land grant institutions have greatly expanded over the past 20 years. However, private schools with equine programs focused on large equitation programs have shown a reduction in recent years. Most indicated cost and reduced student numbers as factors to the decline. In evaluation of 12 land-grant institutions in the Midwest Animal Science region, 100% offer one or more equine Animal Science courses with a range of 1 to 16 different equine focused courses. Nearly all schools offer a combination of lecture and “hands-on” courses. Lecture courses focused on management, nutrition, evaluation, etc. were offed at all 12 institutions with most offering between 2 to 4 equine lecture type courses. Enrollments in these courses range between 10 – 50 students or more. However, highly popular hands on courses covering training, equitation, and handling have lower enrollment limits (10-15), lab fees, and schools offer between one to 6 different courses. Makeup of students enrolling in all courses is highly diverse from students with extensive prior horse skills and experience, to those with minimal experience. Furthermore, all of the institutions evaluated used the equine courses within their Animal Science major and three offered an Equine Option within Animal Science. However, this may be reflective of the structure of each Animal Science Department. Equine courses tend to be highly popular and attract students from various majors across intuitions. Offering courses to serve and attract this diverse student population is a challenge to departments, especially with the increased cost of maintaining herds for highly popular hands on courses. However, departments must strive to find a balance between lecture/distance and hands-on courses to provide students the educational experience exposing them to the equine industry and future careers.
99 Breed authentication of five lines comparing Structure, Admixture, and an allele frequency method
Authors: Putz Austin M , Charagu Patrick , Huisman Abe 
Published: November 2020

Abstract
Two commonly used population structure software packages are freely available for breed authentication, Structure and Admixture. Structure uses a Bayesian approach to model population structure, while Admixture uses a frequentist approach. More recently, an allele frequency method has been updated to use quadratic programming to constrain the multiple linear regression coefficients of the regression of genotype count (divided by two) on the matrix of allele frequencies for each known breed or line. This constraint forced coefficients to sum to one and be greater than or equal to 0 and less than or equal to 1. The goal of this research was to compare and contrast these three methods to determine the breed/line authenticity for each of the five genetic lines. These five lines included Large White, Landrace, a lean Duroc, a meat quality Duroc, and a Pietrain line. Only animals with a 50K SNP panel were used in this analysis. Analyses were run five times for Structure and Admixture to check repeatability. The allele frequency method did not need to be repeated because it remains the same as long as the reference allele frequency matrix stays constant. For Structure, results of breed composition were inconsistent across replicates. Structure separated at least one of the maternal lines in three out of the five replicates with only 500 animals and kept the Duroc lines together as one population. Only 500 animals could be utilized in each run of Structure due to computational restraints. Admixture was very consistent across runs for each animal, but also failed to separate the two Duroc lines, instead splitting one of the two maternal lines. Finally, the allele frequency method split all five lines correctly and was 100% reproducible as long as the reference allele frequency matrix stays the same across runs.
98 Using differential evolution to improve predictive accuracy of deep learning models applied to pig production data
Authors: Han Junjie , Gondro Cedric , Steibel Juan 
Published: November 2020

Abstract
Deep learning (DL) is being used for prediction in precision livestock farming and in genomic prediction. However, optimizing hyperparameters in DL models is critical for their predictive performance. Grid search is the traditional approach to select hyperparameters in DL, but it requires exhaustive search over the parameter space. We propose hyperparameter selection using differential evolution (DE), which is a heuristic algorithm that does not require exhaustive search. The goal of this study was to design and apply DE to optimize hyperparameters of DL models for genomic prediction and image analysis in pig production systems. One dataset consisted of 910 pigs genotyped with 28,916 SNP markers to predict their post-mortem meat pH. Another dataset consisted of 1,334 images of pigs eating inside a single-spaced feeder classified as: “single pig” or “multiple pigs.” The accuracy of genomic prediction was defined as the correlation between the predicted pH and the observed pH. The image classification prediction accuracy was the proportion of correctly classified images. For genomic prediction, a multilayer perceptron (MLP) was optimized. For image classification, MLP and convolutional neural networks (CNN) were optimized. For genomic prediction, the initial hyperparameter set resulted in an accuracy of 0.032 and for image classification, the initial accuracy was between 0.72 and 0.76. After optimization using DE, the genomic prediction accuracy was 0.3688 compared to 0.334 using GBLUP. The top selected models included one layer, 60 neurons, sigmoid activation and L2 penalty = 0.3. The accuracy of image classification after optimization was between 0.89 and 0.92. Selected models included three layers, adamax optimizer and relu or elu activation for the MLP, and one layer, 64 filters and 5×5 filter size for the CNN. DE can adapt the hyperparameter selection to each problem, dataset and model, and it significantly increased prediction accuracy with minimal user input.
92 Phenotypic and genomic relationships between vulva score and reproductive performance in first-parity sows
Authors: Corredor Flor-Anita , Sanglard Letícia P , Ross Jason W , Keating Aileen F , Serão Nick 
Published: November 2020

Abstract
Reproductive efficiency is critical to maximizing productivity in the swine industry. A recent study indicated that vulva score (VSC) assessed prior to puberty may be predictive of reproductive performance in sows, in which gilts with greater VSC had greater reproductive performance. The objective of this study was to validate the effect of VSC on reproductive performance, to estimate genetic parameters, and to perform genomic analysis of VSC. A total of 5494 phenotypes and 1326 genotypes (~50K SNPs) from two farms were available for this study. Measurements included VSC assessed using a three-point scale: small (VSC-S), medium (VSC-M), and large (VSC-L), at 15 and 14 weeks of age, for Farm 1 and 2, respectively, and subsequent first parity performance. Genetic parameters were estimated using single-step GBLUP. Genome-wide association study (GWAS) was performed for VSC using BayesB (p=0.999). For Farm1, VSC-L was associated with a greater (P-value=0.04) farrow rate (0.68±0.03) than VSC-S (0.53±0.07). For Farm2, VSC-L was associated with greater (P-value=0.04) number of piglets born alive (NBA; 11.4±0.17) and less mummified fetuses (P-value=0.03; 0.09±0.01) than VSC-S (10.9±0.14; 0.14±0.01). Heritability estimates of VSC were 0.35±0.06 for Farm1 and 0.34±0.05 for Farm2. Moderate genetic correlations between VSC with reproductive traits were found for total number born (0.61±0.21) and NBA (0.62±0.19). The GWAS identified multiple genomic regions associated with VSC. Of these, a QTL located on chromosome 1 at 85Mb accounted for &gt;3% of the genetic variance. This region harbors ADAM21, a gene that has been associated with early embryonic development in pigs. These results validated the use of VSC for prediction of first-parity performance, identified genomic regions controlling VSC, and indicate that selection for increased VSC is possible and could improve reproductive efficiency in swine. We are grateful to Fast Genetics for providing the data and the Iowa Pork Industry Center for financial support.
93 Genomic basis of antibody response to porcine reproductive and respiratory syndrome virus vaccination
Authors: Sanglard Letícia P , Fernando Rohan L , Gray Kent , Linhares Daniel C L , Dekkers Jack , Niederwerder Megan C , Serão Nick 
Published: November 2020

Abstract
Antibody (Ab) response to natural infection with porcine reproductive and respiratory syndrome (PRRS) virus has been shown to be highly heritable (~0.40), to be genetically correlated with farrowing performance in PRRSV-infected sows, be controlled by two major QTL on chromosome 7, among others, and have moderate genomic prediction accuracy. However, waiting for PRRS outbreaks to occur to collect data limits the use of Ab response to select for increased PRRS resilience. Thus, we investigated the genomic basis of Ab response to PRRS vaccination with a modified live PRRSV vaccine as a strategy to generate data for this purpose. Nine hundred and six commercial F1 replacement gilts (189±16 days old) were vaccinated with a commercial PRRS modified live virus vaccine. Blood samples were collected 52 days after vaccination to measure Ab response, as sample-to-positive (S/P) ratio using a commercial ELISA, and for SNP genotyping (~50K). BayesC0 was used to estimate heritability for S/P ratio using in a model with contemporary group (CG) as fixed effect and SNP effects as random. Genome-wide association study and genomic prediction for S/P ratio were performed with BayesB (Pi=0.99). For genomic prediction, a three-fold cross-validation was used, in which each CG (n=3) was used as validation dataset. Accuracy of genomic prediction was defined as the correlation between genomic estimated breeding values and phenotypes adjusted for estimates of fixed effects, weighed by the number of individuals in the validation dataset. Heritability of S/P was moderate (0.35±0.04). A QTL was identified on chromosome 7 (25 Mb) explaining ~28% of the genetic variance. Accuracy of genomic prediction was fairly high (0.60±0.15). This is the first study describing the genomic basis of Ab response to PRRS vaccination with modified-live virus vaccine. Additional work is needed to evaluate the genetic correlation of Ab response to vaccination with resilience traits in pigs.
97 An insight into the piglet’s microbial colonization evolution: From birth towards weaning
Authors: García Mireia Saladrigas , Durán Mario , Coma Jaume , Pérez José Francisco , Martín-Orúe Susana María 
Published: November 2020

Abstract
The aim of the present study was to explore the evolution of piglet gut microbiota from birth to weaning. Moreover, it was hypothesized that different farm environments could condition this process. Two farms, distinct in their use of antibiotics, and 10 litters per farm were selected. A total of 100 fecal samples were obtained from the same pig of each litter on d2, d7, d14 and d21 of lactation and d14 after weaning. The DNA was extracted by using the PSP® Spin Stool DNA Kit and sequencing of the 16S rRNA gene (V3-V4 region) performed by Illumina MiSeq Platform. Bioinformatics and biostatistical analysis were performed with QIIME and the open-source software R v3.5.3. (phyloseq package). Alpha diversity was strongly affected by age (P&lt; 0.001), with an increasing richness of species through time. Beta diversity decreased after weaning (P&lt; 0.001), suggesting a convergent evolution among individuals. Regarding the structure of the microbiota, a clear clustering of the samples according to age was observed (P&lt; 0.001). A progressive decrease was observed as the piglets aged for Clostridiaceae, Enterobacteriaceae, Fusobacteriaceae, Pasteurellaceae and Streptococcaceae (P&lt; 0.001). In contrast, Lachnospiraceae (P=0.003), Lactobacillaceae (P=0.003) and Veillonellaceae (P=0.025) increased along the d7–d14 period, but decreased afterwards. Campylobacteraceae, Erysipelotrichaceae, Ruminococcaceae (P&lt; 0.001) and Prevotellaceae (P=0.005) gradually increased with age reflecting the change from a milk-oriented microbiome towards a butyrate-producing one. Regarding the impact of the farm, differences in species richness were found and also a distinct microbial structure (ANOSIM: P=0.025) associated to changes in some particular taxonomic groups. In conclusion, during the transition from birth to weaning, the pig microbiota showed a relevant succession of microbial groups towards a more stable ecosystem better adapted to the dry feed. In this relevant early-age process differences between farms seems to have a limited impact.
51 Intranasal oxytocin improves plasma non-esterified fatty acids but not distance walked or cortisol concentrations at weaning
Authors: Nickles Kirsten , Relling Alejandro E , Parker Anthony J 
Published: November 2020

Abstract
Beef calves express behaviors such as walking and vocalizing to a greater extend during weaning. These behaviors increase production costs due to compromised calf growth, health, and welfare. Oxytocin treatment reduces anxious behaviors and attenuates the HPA axis, thus the objective of this experiment was to evaluate the effects of oxytocin on calf growth, cortisol, and distance walked at weaning. A total of 20 Angus x Simmental heifer calves were randomly allotted to each treatment group (n = 10), intranasal oxytocin or saline (OXT, CON). All calves were administered the respective intranasal treatment at weaning (day 0), and then placed in the same pasture. Calves were weighed and blood sampled on days 0, 1, 7, and 14. Blood samples were used to quantify non-esterified fatty acids (NEFA), β-hydroxybutyrate, and cortisol. Each heifer was fitted with a global positioning system collar that recorded calf location every 10 seconds for 16 h on days 0, 7, and 14. To further evaluate calf behavior, observations were made on days 0, 7, and 14 using instantaneous scan sampling from 0730 to 0830, 1200 to 1300, and 1700 to 1800 h. Data were analyzed using a completely randomized design with repeated measures model (SAS 9.4). Providing calves with intranasal oxytocin on the day of weaning did not have an effect on the distance walked, observed behavior, body weight, β-hydroxybutyrate, or cortisol concentrations, however, there was a day effect (P &lt; 0.05) for these variables. Intranasal oxytocin treatment did affect NEFA concentrations, as calves in the CON group had greater NEFA concentrations on day 1 compared with calves in the OXT group (P &lt; 0.05). These data imply that intranasal oxytocin could have the capacity to decrease mobilization of NEFA, but this change was not enough to affect body weight 14 days after weaning.
49 Solar radiation as a predictor variable for dry matter intake in beef steers
Authors: Yusuf Mustapha , Swanson Kendall C , Hulsman Hanna Lauren L , Degges Ronald , Bauer Marc L 
Published: November 2020

Abstract
The objective of this experiment was to examine the relationship between ambient temperature and solar radiation with dry matter intake (DMI) in beef steers. Daily intake data from 790 beef steers collected from years 2011 to 2017 using an Insentec feeding system were used for this experiment. Data were condensed from daily data into weekly averages (n = 14250 steer-weeks). The variables considered for this experiment include DMI (2.50 to 23.60 kg/d), body weights (197.3 to 796.1 kg), energy density of diets (NEm; 0.7930 to 2.970 Mcal/kg), ambient temperature (-23.72 to 26.40 °C), two week lag of temperature, monthly lag of temperature, solar radiation (30.81 to 297.12 W/m2), two week lag of solar radiation and monthly lag of solar radiation. Residuals of DMI generated after fitting week of year as a fixed effect were used in scatter plots with explanatory variables to identify if non-linear relationships existed. Body weight and energy density were observed to have both linear and quadratic relationships, while the relationship for average temperature and solar radiation vs. DMI were observed to be linear. The MIXED procedure of SAS was used to assess the fit and regression parameters of explanatory variables as fixed covariates. Repeated measures were handled using the REPEATED statement and within-individual relationship were accounted for by autoregressive 1 covariance structure. Absolute average temperature (P = 0.0024) and monthly lag of average solar radiation (P = 0.0014) are the best predictor variables for ambient temperature and solar radiation based on p-values. An interaction (P &lt; 0.001) between average temperature and monthly lag of solar radiation was also observed. The coefficient of determination (R2) for our model was 0.23. This study indicates that monthly lag of solar radiation interacts with ambient temperature in affecting DMI by beef steers and improves DMI prediction equations.