bluuebunny/crossref_metadata_2025_split huggingface dataset:
35 Warm-season perennial grass management in tropical and subtropical regions
Authors: Vendramini Joao 
Published: December 2019

Abstract
Warm-season perennial grass, also called C4, are the predominant forages for ruminant production in tropical and subtropical regions. In general, C4 grasses have greater herbage production in warm-climate regions due to a more efficient carbon fixation pathway than cool-season forages (C3) and anatomical characteristics results in C4 plants with less concentration of CP and soluble carbohydrates, and greater concentrations of cell wall components such as cellulose and hemicelluloses than C3 grasses. Several factors may contribute to the differences in nutritive value in C4 grasses, including species, cultivars within species, maturity, fertilization, and conservation practices. Routine forage testing programs only using NDF and ADF may often provide unacceptable values of DM intake and digestible DM for C4 grasses. Forage quality is a function of nutritive value and intake; however, it is challenging to estimate intake on grazing animals and DM intake is not well correlated to NDF concentration in C4 grasses. The vertical heterogeneity in sward canopy composition and the amount and accessibility of leaf are major canopy characteristics associated with intake. Green herbage mass or green leaf proportion in grazed horizon usually shows positive relationship with bite weight and intake is a function of bite weight and bite rate. Leaf density, plant-part composition and nutritive value of the upper canopy are also important to explain the variations in intake. Besides the plant-intrinsic characteristics, animal genetics and environmental factors may affect intake as well. Grazing is the most used method of C4 grasses utilization in tropical and sub-tropical regions; however, a small proportion of the forage produced is conserved as hay or silage. Greater forage production during the growing season may coincide with greater rainfall and inadequate climactic conditions for harvesting and baling forage in tropical and subtropical regions.
207 Structural conformation among spatially distributed West African dwarf goats as measures of adaptation to different environments
Authors: Jesuyon Oluwatosin M , Olawumi Simeon O 
Published: December 2019

Abstract
Goat production and breeding in West Africa is largely under traditional rearing system with little or no efforts geared towards improving their productivity. To understand underlining body conformation among spatially distributed West African dwarf (WAD) goats, a survey was conducted between May 2015 and June 2017 in two states of Nigeria. Data were recorded on two hundred and twenty-seven freely-scavenging West African dwarf goats, on Body weight (BWT), Heart girth (HGH), Diagonal trunk length (DTL), Height at the withers (HWT), Height at the rump (HRP), Body Breadth Index (BBI), Body Depth Index (BDI), Body length Index (BLI), Trunk length index (TLI), Weight-Height Index (WHI), Overbuilding Index (OBI) and Withers-Girth Index (WGI). These were subjected to randomized complete block design, GLM, multiple linear regression analysis procedures by Statistical Analytical Systems. Significant values (P &lt; 0.05) were obtained between locations for BWT, DTL, TLI, OBI, BLI and WHI, between sexes for all traits and on the interaction of LOC by SEX for DTL, TLI, OBI, BDI, BBI, WGI and BLI. Bucks differ on trunk and girth between states. Body conformation for does and bucks – girth-breadth-depth and trunk-weight-height also differ greatly respectively. Results were significant for studying environmental adaptation and selection for development of meat type animals based on structural conformation.
211 Changes in genetic parameters of fitness and growth traits under genomic selection in pigs
Authors: Hidalgo Jorge , Tsuruta Shogo , Lourenco Daniela , Huang Yijian , Gray Kent , Misztal Ignacy 
Published: December 2019

Abstract
Genomic selection increases intensity of selection and decreases generation interval. However, intensive selection reduces genetic variation and can strengthen undesirable genetic correlations. The purpose of this study was to investigate changes in genetic parameters of litter size (LS), number born alive (NBA), number born dead (NBD) and average daily gain (ADG) and weight at off-test (WT) in pigs over time. The data set contained 20,086 (LS), 21,230 (NBA), 21,230 (NBD), 144,717 (ADG) and 144,718 (WT) phenotypic records. Pedigree file included 369,776 animals born between 2001 and 2018, of which 39,038 were genotyped. Two trait models were evaluated (LS-ADG, LS-WT, NBA-ADG, NBA-WT, NBD-ADG and NBD-WT) using 3-year sliding subsets starting from 2010. Variance components and genetic parameters were estimated using GIBBS2F90 program. Computations were performed with (BLUP) or without (ssGBLUP) genotypes. For BLUP (ssGBLUP), the changes in heritability from 2010–2012 to 2015–2018 were 0.08 to 0.09 (0.08 to 0.06) for LS, 0.33 to 0.24 (0.37 to 0.16) for ADG, 0.11 to 0.07 (0.10 to 0.07) for NBD, and 0.32 to 0.24 (0.38 to 0.17) for WT. Differences were also observed for genetic correlations as they were -0.23 to -0.73 (-0.31 to -0.58) for LS-ADG, -0.24 to -0.74 (-0.31 to -0.50) for LS-WT, -0.33 to -0.65 (-0.41 to -0.53) for NBA-ADG, -0.35 to -0.66 (-0.42 to -0.45) for NBA-WT, 0.12 to 0.04 (0.12 to 0.16) for NBD-ADG, and 0.11 to 0.05 (0.11 to 0.22) for NBD-WT. Genomic selection in pigs reduced heritabilities and emphasized the antagonistic relationship that are under strong selection. Heritabilities estimated from ssGBLUP declined more than those by BLUP while changes in the genetic correlations were smaller and more gradual by ssGBLUP. Differences between ssGBLUP and BLUP could be caused by genomic pre-selection unaccounted for by BLUP.
218 Quantifying resilience in growing pigs under a heavy disease challenge using daily individual feed intake records
Authors: Putz Austin M , Harding John , Dyck Micheal , Canada PigGen , Fortin Frederic , Plastow Graham , Dekkers Jack C 
Published: December 2019

Abstract
Resilience is defined as the ability to maintain productivity through any number of stressors such as disease or heat stress. A total of 2273 animals, in groups of ~60–75 piglets, were sent through a natural disease challenge barn every three weeks that consisted of three phases: i) a healthy quarantine nursery to collect immune parameters, ii) a challenge nursery, and iii) a challenged finishing unit which was attached to the challenge nursery. Individual feed intake (FI) was collected in the finishing unit with IVOG® feeders and aggregated into daily totals. Three resilience phenotypes were extracted from the individual trends in feed intake over time, including the root mean square error (RMSE), the quantile regression (QR), and run of depression (ROD) phenotypes. The RMSE phenotype was calculated by fitting a simple linear regression of FI on age within animal and taking the square root of the average squared residual from the model. To calculate the QR phenotype, a 5% quantile regression was fitted across all daily feed intake records to set a lower bound for off-feed days. The QR phenotype was quantified as the proportion of days within animal that fell below the overall quantile regression line. The ROD phenotype was calculated by fitting a within animal linear regression line, flagging extended consecutive stretches of days below that regression line (i.e. a ROD), and calculating the percentage of days that fall within a ROD for each animal. Heritability estimates for the FI resilience phenotypes ranged from 0.10±0.04 to 0.17±0.04. Genetic correlations of the FI resilience phenotypes with mortality and treatment rate ranged from 0.66±20 to 0.94±0.20. This research demonstrates that resilience phenotypes can effectively quantify resilience and can add value to a breeding program to improve resilience to many stressors. Funded by Genome Canada, Genome Alberta, and PigGen Canada.
332 Indirect predictions based on SNP effects from GBLUP with increasing number of genotyped animals
Authors: Garcia Andre , Masuda Yutaka , Miller Stephen P , Misztal Ignacy , Lourenco Daniela 
Published: December 2019

Abstract
With the increasing number of genotyped animals, the algorithm for proven and young (APY) can be used to compute the inverse of the genomic relationship matrix (G-1apy) in genomic BLUP (GBLUP) and single-step GBLUP (ssGBLUP). This algorithm also allows the use of all genotyped animals to calculate SNP effects from genomic EBV (GEBV), which can then be used to obtain indirect predictions (IP) for interim evaluations, or as genomic prediction for animals not included in official evaluations. The objective of the study was to evaluate the quality of IP from GBLUP with increasing number of genotyped animals. Birth weight, weaning weight and post-wearing gain phenotypes and genotypes were provided by the American Angus Association. Phenotypes and genotypes were divided in 3 scenarios based on birth year: genotyped animals born up to 2013 (114,937), 2014 (183,847) and 2015 (280,506). A 3-trait model was fit and GBLUP with APY was used to calculate GEBV and SNP effects. To calculate G-1apy, 19,021 core animals were randomly sampled from animals born up to 2013. Core animals remained the same, whereas the number of non-core animals increased as more genotyped animals were added. Additional analyses had updated core animals for each scenario. SNP effects were also calculated based on G-1apy and G-1 only for core animals (G-1core). IP were computed for all animals in each scenario by multiplying the centered genotypes by the SNP effects. To access the quality of IP, correlation between IP and GEBV was calculated. The Correlations were greater than 0.99 for all traits in all scenarios. Despite the increase of non-core animals in APY, GEBV were successfully retrieved from SNP effects using IP. When SNP effects were calculated based on G-1core, updating the core animals as the number of genotyped animals increase seems to be the best choice.
330 A hybrid model for genomic selection using prioritized SNPs based on FST scores in the presence of non-genotyped animals
Authors: Toghiani Sajjad , Chang Ling-Yun , Hay El H , Roberts Andrew J , Aggrey Samuel E , Rekaya Romdhane 
Published: December 2019

Abstract
The dramatic advancement in genotyping technology has greatly reduced the complexity and cost of genotyping. The continuous increase in the density of marker panels is resulting in little to no improvement in the accuracy of genomic selection. Direct inversion of the genomic relationship matrix is infeasible for some livestock populations due to the excessive computational cost. In addition, most animals in genetic evaluation programs are non-genotyped. Including these animals in a genomic evaluation requires the imputation of the missing genotypes when using regression methods. To overcome these challenges, a hybrid approach is proposed. This approach fits a subset of SNP markers selected based on FST scores and a classical polygenic effect. The method was first tested using only genotyped animals and then extended to accommodate non-genotyped animals. The proposed approach was evaluated using simulated data for a trait with heritability of 0.1 and 0.4 and weaning weight in a crossbred beef cattle population. When all animals were genotyped, the hybrid approach using only 2.5% of prioritized SNPs exceeded the prediction accuracies of BayesB, BayesC, and GBLUP by more than 7%. When non-genotyped animals were incorporated, the proposed approach significantly outperformed ss-GBLUP method in terms of prediction accuracy under both simulated heritability scenarios. Although the results seem to depend on the genetic complexity of the trait, the proposed approach resulted in higher prediction accuracies than current methods. Furthermore, its computational costs in terms of CPU time and peak memory are substantially lower than the current methods.
329 Mendelian sampling, QTL similarity, and accuracy of genomic selection
Authors: Ling Ashley , Aggrey Samuel E , Rekaya Romdhane 
Published: December 2019

Abstract
Superiority of genomic selection (GS) is argued to be due to better modeling of the Mendelian sampling (MS) and tracking of QTL similarities between individuals. It is not clear that a better genome-wide modeling of MS contributes to the increased accuracy. In fact, it might be that modeling of MS outside areas of the genome under selection pressure is detrimental to the accuracy of GS. If true, this hypothesis will provide a better framework to understand the complex relationships between MS, QTL similarity and accuracy. Increases in marker density and the need for marker prioritization makes this hypothesis even more practically important. Answering this question could have a significant impact on accuracy and the computational costs of GS implementation. A 30-chromosome genome with 50K SNPs was simulated. 200 QTL were simulated on two chromosomes for a trait with heritability of 0.4. Genomic relationships were calculated based on all 50K SNPs (G30), 3,333 SNPs on the two chromosomes carrying QTL (G2), and 46,667 SNPs on chromosomes without QTL (G28). Table 1 shows accuracies after 3 and 10 generations of (G)EBV-based selection (M1) and random selection (M2). BLUP accuracies are consistently higher (11.5 to 43.8%) than G28, showing that expected relationships better model QTL similarities than a dense panel of markers that lie outside QTL regions. Inclusion of markers that lie outside QTL regions with markers inside QTL regions reduces accuracies, as shown by the inferior (20.2 to 22.8%) performance of G30 compared to G2. Coefficients of variation were higher for low than high additive relationships suggesting that errors made in estimating QTL similarities for lowly related animals may have the most detrimental impact. Furthermore, while G28 markers capture more variation than pedigree, the superiority of BLUP indicates that variation captured by G28 is not consistent with true variation in QTL inheritance.
50 Genomic selection in the dairy industry: excitement, challenges, and future directions
Authors: Lawlor Tom 
Published: December 2019

Abstract
Dairy cattle, and Holsteins in particular, were the first major agricultural industry to fully embrace genomic selection (GS). Few of us had predicted that, by May 2019, the number of genotyped animals would exceed 3 million. Farmers are changing the frequency of individual alleles and making use of genomic information to select better bulls; identify elite embryo donors; determine if a cow should be bred with conventional, sexed or beef semen; become an embryo recipient or be culled. Our industry has traditionally been an open system, where top genetics are sourced from the general population and phenotypes are provided on a voluntary basis. Contractual agreements have allowed this system to continue and have been extended to access of data, differential pricing, international collaboration and more. Phenotypes no longer come from well designed, highly organized progeny testing programs but rather from paid contributors who provide data that are quality certified and representative of the population. Over time, we’ve improved our genome map, SNP chips, reference populations, statistical models, computing ability, data pipeline, and most importantly our knowledge of genetics. Combining different types of data from multiple sources continues to be a challenge. Interdisciplinary approach and collaboration with other scientists are now the norm. GS has caused a paradigm shift within the dairy industry. But, after 10 years, we are in a better position to more quickly integrate new scientific knowledge. Making our industry and the production of dairy products more efficient and sustainable.
239 Stray and abandoned dog overpopulation management- Israel’s unique system
Authors: Morgan Liat , Yakobson Boris , Raz Tal 
Published: December 2019

Abstract
Dog overpopulation is a major problem worldwide, which impacts animal welfare and health, as well as public health. In Israel, a unique governmental database is managed in order to enforce mandatory dog registration and rabies yearly vaccination policy. In addition, since 2012, a unique online searchable database has been gathering most homeless pets offered for adoption from non-profit organizations and municipal shelters (http://Yad4.co.il). Our objectives were (1) to investigate the registered dog population in Israel and to assess its association to the abandoned dog population; and (2) to reveal the risk factors for a dog to be adopted or to stay at the shelter. Data analyses included 758,288 registered dogs and 22,545 adoptable dogs. Analyses revealed that only 214,101 out of the 343,872 dogs that are registered as “active” are known to have owners. Approximately 40,000 dogs “disappear” from the database every year, which means that some of them may be abandoned. Multi-Variate Linear regression strengthened it by revealing that the number of abandoned dogs increased by the numbers of active registered dogs and dogs which had “disappeared” from the database in the previous year (P &lt; 0.05). Among the registered dogs, 8% were younger than one year, but only 1.7% of the abandoned dogs were that young. Among these dogs, the risk factors to stay at the shelter were when the dogs were described as: “mix-breed”, “male”, “suitable for senior” or “for athletes” (P &lt; 0.05). In conclusion, a governmental national database is an important dog population management tool, with the potential to predict the number of abandoned dogs. Since most abandoned dogs are older than one year, promoting responsible ownership would be vital. Moreover, a national online database, such as Yad4 website, may successfully improve dog adoption rate, while dogs’ description online significantly impacts the adoption chances.
80 Effects of macronutrient composition of milk replacer on body composition and intestinal development in neonatal dairy calves
Authors: Welboren Anna C , Hatew Bayissa , Leal Leonel , Martin-Tereso Javier , Steele Michael A 
Published: December 2019

Abstract
Most milk replacers (MR) contain a higher lactose:fat ratio compared to whole milk, potentially affecting nutrient absorption and use by the calf. This study evaluated how body composition and intestinal development were affected when lactose was replaced with fat in MR. Thirty-four calves (43.3 ± 0.8 kg) were blocked (BW and dam parity), and randomly assigned to a high-lactose (43.8% lactose and 17.1% crude fat) or high-fat (37.9% lactose and 23.4% crude fat) MR. Calves were fed pooled colostrum within 2 h (18% of metabolic body weight (MBW)) and 12 h (9 %MBW) postnatal, followed by MR feeding (18 %MBW) twice daily. Calves were weighed pre-prandially at birth and on d 7. Calves were euthanized on d 7 to sample intestinal tissue and analyze body composition using dual-energy x-ray absorptiometry. Samples of intestinal segments were processed to evaluate histomorphology using bright-field microscopy. Data were analyzed using PROC MIXED in SAS software. Total gain (3.90 vs. 2.29 ± 0.38 kg, P = 0.01) and gain:ME intake (44.64 vs. 28.61 ± 4.32 kg, P = 0.02) were greater for high-fat compared to high-lactose calves, whereas body composition was unaffected (P = 0.13). Proportionally, the large intestine was 0.11 ± 0.02 %BW heavier (P = 0.03) in high-fat calves compared to high-lactose calves, while their small intestine tended to be 0.16 ± 0.06 %BW heavier (P = 0.09). Small and large intestine length did not differ (P = 0.96). High-fat calves had wider villi (125.41 vs. 96.58 µm, P = 0.05) in the jejunum but shorter villi (414.17 vs. 470.96 µm, P = 0.02) in the ileum compared to high-lactose calves. Macronutrient composition affected intestinal histomorphology and improved efficiency of ME use for BW gain. Understanding how fat (including its source) influences nutrient efficiency in dairy calves may improve nutritional strategies on farm.
74 Effects of particle size and levels of inclusion of selected engineered biocarbon on methane emission and rumen fermentation of barley-silage based diet in batch culture
Authors: Tamayao Paul , McAllister Tim A , Ominski Kim , Ribeiro Gabriel , Okine Erasmus , McGeough Emma 
Published: December 2019

Abstract
This in vitro study assessed the effects of three pine-based engineered biocarbons (CP002, CP016, CP023) that differed in particle size (&lt; 0.5, 0.5–2.0, &lt; 2.0 mm) at two inclusion levels (0.25 mg/ml and 0.5 mg/ml) on total gas and CH4 production as well as rumen fermentation parameters when added to a barley silage-based total mixed ration diet. Biocarbon products differed in bulk density, surface area, pore volume, and pH but had similar chemical compositions. The control consisted of the barley-silage diet only. In each jar, 0.5g DM of the total mixed ration was supplemented with the above biocarbon treatments. These jars were incubated for 48 hr at 39 °C. Gas samples were collected at 3, 6, 9, 12, 24, 36 and 48 hr. Data were analysed by using PROC MIXED in SAS in a randomized complete block design with treatment, rate, and particle size as fixed effects and run and replicate as random effects. Methane production was not affected by treatment (P = 0.37), inclusion rate (P = 0.57) or particle size (P = 0.39). Gas production linearly increased (P &lt; 0.01) with biocarbon. Digested DM was not affected (P = 0.23) by biocarbon addition. Additionally, treatment, rate and particle size had no effect (P &gt; 0.05) on pH, VFA and ammonia N concentrations. In conclusion, the amount of biocarbon differing particle sizes at different rates did not affect CH4 emissions but did increase gas production.
76 Does supplemental protein and rumen-protected methionine improve performance and digestibility during late-gestation in beef cows?
Authors: Collins Madeline M , Lievre Michaela K S , Lawson Kaitlyn V J , Mandell Ira B , Shoveller Anna-Kate , Wood Katie M 
Published: December 2019

Abstract
Methionine (MET) is likely the first limiting amino acid in low-protein forages fed to beef cattle during late-gestation. Therefore, the objective of this study was to determine if supplemental protein and rumen-protected MET improve cow performance and apparent tract digestibility (TTD) during late-gestation. This study used 147 late-gestation Angus crossbred cows and heifers in a 3x2 factorial arrangement for dietary treatments. The cattle were randomly assigned to one of six diets formulated to 90, 100 or 110% of metabolizable protein (MP) requirements (NRC, 2016), with (without) 9 g/d of rumen-protected MET (MetaSmart, Adisseo Inc.). These diets were fed for approximately 8 wks before calving. All data was analyzed as a randomized block design using SAS 9.4 PROC GLIMMIX procedure. Cows fed at 90% MP requirements lost body weight (BW), while cows fed at 100% and 110% MP requirements maintained and (or) gained BW over the trial (P = 0.02). Similarly, cows fed at 90% MP requirements lost more pregnancy corrected BW than cows fed at 100% and 110% MP requirements (P = 0.01). However, supplemental MET did not affect body weight gains (P &gt; 0.07). Cows and heifers fed at 90% MP requirements had reduced TTD for crude protein compared to cattle fed to 110% MP requirements (P &lt; 0.001), MET supplementation did not impact TTD (P &gt; 0.20). Additionally, cattle fed at 90% MP requirements had increased serum cholesterol and reduced urea concentrations compared to cows fed to 100% and 110% MP requirements (P &lt; 0.0001). MET supplementation increased serum concentrations for glucose, isoleucine, leucine, lysine, serine, threonine and valine (P &lt; 0.02). Calf birth weights were not significantly impacted by dietary treatment (P &gt; 0.31). Feeding cows above their MP requirements may improve late-gestation performance and CP digestibility. Supplemental MET may increase amino acid utilization but did not improve beef cow performance or digestibility parameters measured in late-gestation.