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This article explores the impact of ectoparasitic mites on cage-free egg production in the United States and strategies for managing these mites. The transition to cage-free housing has resulted in an increase in mite infestations, which negatively affect the health, behavior, and productivity of hens. The article discusses the genetic variability for mite resistance and the potential use of genomic selection to improve mite resistance in poultry populations. It also provides information on the biology of the northern fowl mite and poultry red mite, as well as various management strategies, including the use of pesticides and biosecurity measures. The authors stress the importance of monitoring and managing mite infestations in egg production and call for further research to develop effective and sustainable strategies for improving hen welfare. They suggest that genomic selection could be a promising approach for breeding mite-resistant poultry strains. [Extracted from the article]

The article presents the discussion on historical and current potential of using insects as an alternative protein source in animal feeds, driven by declining fishmeal availability and environmental concerns. Topics include the evolution of insect use in feed, the impact of overfishing on fishmeal supply; and the sustainability benefits of insect farming for reducing environmental impact and utilizing organic waste.

The first record of captive-bred red foxes (Vulpes vulpes) dates to 1896 when a breeding enterprise emerged in the provinces of Atlantic Canada. Because its domestication happened during recent history, the red fox offers a unique opportunity to examine the genetic diversity of an emerging domesticated species in the context of documented historical and economic influences. In particular, the historical record suggests that North American and Eurasian farm-bred populations likely experienced different demographic trajectories. Here, we focus on the likely impacts of founder effects and genetic drift given historical trends in fox farming on North American and Eurasian farms. A total of 15 mitochondrial haplotypes were identified in 369 foxes from 10 farm populations that we genotyped (n  = 161) or that were previously published. All haplotypes are endemic to North America. Although most haplotypes were consistent with eastern Canadian ancestry, a small number of foxes carried haplotypes typically found in Alaska and other regions of western North America. The presence of these haplotypes supports historical reports of wild foxes outside of Atlantic Canada being introduced into the breeding stock. These putative Alaskan and Western haplotypes were more frequently identified in Eurasian farms compared to North American farms, consistent with historical documentation suggesting that Eurasian economic and breeding practices were likely to maintain low-frequency haplotypes more effectively than in North America. Contextualizing inter- vs. intra-farm genetic diversity alongside the historical record is critical to understanding the origins of this emerging domesticate and the relationships between wild and farm-bred fox populations. [ABSTRACT FROM AUTHOR]

Hanwoo is one of the indigenous cattle breeds in South Korea, and genetic evaluation at the national level is conducted using custom Illumina SNP arrays. Accurate gender assignment is essential in genetic evaluation and breeding programs for livestock species. In this study, we described a method for using custom single nucleotide polymorphism (SNP) array data to predict gender of Hanwoo cattle using logistic regression model. We analyzed a set of 958 SNPs, with 947 located on the X chromosome and 11 on the Y chromosome, focusing on heterozygosity rates from the X chromosome and missing rates from Y chromosome SNPs. Using a training dataset comprising 5,000 bulls and 2,005 cows with accurately recorded genders, we built a prediction model. Subsequently, we evaluated the performance of the model on test datasets consisting of 6,657 bulls, 27 steers, and 8,418 cows. The concordance between predicted gender and recorded gender were 99.98%, 100.00% and 99.98% for bulls, steers, and cows, respectively. This result showed better accuracy of gender prediction compared with the GENOMESTUDIO tool that uses only the heterozygosity rate of SNPs in X chromosome in the case of restricted number of SNPs in sex chromosomes. Overall, our findings could be used as an effective method for more precise genetic evaluation by correcting potential gender errors in Hanwoo cattle breeding programs. [ABSTRACT FROM AUTHOR]

Selection for milk production later in lactation (changing the shape of the lactation curve) also may provide an opportunity to increase milk production during a time in an animal's life when energy allocation is possible. Keywords: Genetic Selection; Estimated Breeding Value; Milk Composition EN Genetic Selection Estimated Breeding Value Milk Composition 55 63 9 06/20/23 20230601 NES 230601 Implications Genetic selection to increase milk yield has been very successful. Milk production of domesticated dairy cows can reach 30-50 L per day or 6,000 to 12,000 Lover a lactation compared to 8-10 L per day and <1,000 L over lactation in feral cows ([85]). Milk production in cows follow a dynamic curve starting with an initial rapid increase in milk yield in early lactation (approx. 0-45 days-in-milk, [DIM]), followed by a peak (approx. 46-55 DIM), and then a slow decline in milk yield during late lactation (approx. 56-340 DIM) ([76]). Flow of data between different components of a national milk recording system, including DNA and test-day milk samples collected on farms, milk composition information produced by milk testing laboratories, standardized records computed by dairy records processing centers, and breeding values calculated by the genetic evaluation center. [Extracted from the article]

She is currently conducting an online ethnography with cage-free egg consumers in China, which would shed light on both their perspectives and behaviours of purchasing and consuming cage-free eggs. In the chapter devoted to chickens, recommended housing systems included indoor coops/cages with perches, sheltered coops with outdoor access, or bramble cages complete with nests provided in the walls ([12]). Caged-laying hens or cage-free eggs: a qualitative study on Chinese egg producers' views on animal welfare and adopting cage-free systems. Lever China also examined 873 packaged egg products sold in 10 major supermarkets in four first-tier cities in China and found that more than 17% of these products claimed to be produced in cage-free conditions (using descriptors such as "free-range" [ ], "cage-free" [ ], "organic"[ ], or images of cage-free environments). [Extracted from the article]

Lameness is a persistent animal health con- cern in the meat goat industry. A survey was developed to describe lameness in commercial meat goat herds in the southeastern US. The survey included 35 multiple- choice questions about general herd attributes, various management practices, and specific herd lameness characteristics. A photo guide of goat hoof lesions was included in the survey package. The survey was sent by postal mail to 629 farms in Tennessee and bordering states with 183 completed surveys returned. The ma- jority of herds managed Kiko (32%), Boer (22%), and Myotonic (19%) goat breeds. Reasons for raising goats included seed stock or breeding stock (78.1%), com- mercial, market, or slaughter purposes (62.3%), hobby, pets, or show (48.6%), and for brush, vegetation, or weed control (25.7%). Most respondents (90.7%) ac- quired goats from breeder farms, whereas only 2.7% of respondents purchased goats from sale barns. Most respondents quarantine new animals before adding them to the herd (78.1%), while 19.7% did not quar- antine new animals and 1.1% were unfamiliar with the practice. The average monthly lameness rate was esti- mated to be at 6% with seasonal occurrences identified by respondents as 6% in the fall, 31.4% in the winter, 25.1% in the spring, and 50.5% in the summer. Some respondents indicated no seasonal variation (24.0%) or did not know (3.3%) if seasonal variation existed. Primary causes of lameness identified by respondents were overgrown hooves (50%), foot scald (19%), and foot rot (14%). Other lesions were identified at less than 8%. Sources of lameness treatment information for re- spondents were other producers (34.9%), veterinarians (30.6%), books (22.4%), online chat groups (19.1%), magazines (8.7%), and the extension service (8.2%). When lame goats were identified, more respondents (56.8%) did not isolate lame goats than those that prac- ticed lame goat isolation (24.0%). Most respondents indicated that they treated lame goats (76.5%), a few did not treat lame goats (4.9%), and notable proportion (19.6%) did not respond to the question. Management approaches to treating lameness identified most frequently by respondents included hoof trimming (85%), topical hoof applications (40%), injectable antibiotics (32%), and footbaths (17%); 4% of respondents noted other methods. As a form of general hoof care management, most producers conducted hoof trimmings two or three times a year (51.9%), compared with trimming hooves once a year (9.8%), monthly (14.2%), or only trim hooves when goats became lame (6.6%). As a culling criterion, 29.5% responded lameness was a cull factor, 45.4% indicated it was not a cull factor, and 25.1% of respondents either did not know or did not response. Survey results showed that lameness is an issue in meat goat herds of the southeastern U.S. and a diversity of management approaches are used by producers to address the concern. [ABSTRACT FROM AUTHOR]

Implementing breeding strategies for a more sustainable food system is one of the most pressing topics for livestock industries. Although different species face different challenges, large-scale research projects can pave the way for future opportunities in these key sectors. Herein, we present two examples (dairy and poultry) of how research projects can result in meaningful changes to commercial breeding programs. The first example is an international large-scale dairy project, which will deliver a roadmap for greenhouse gas (GHG) management using genomics and nutrition. The project aims to facilitate a 55% reduction in GHG emissions from Canadian dairy at an estimated value of $338M CAD. This systems-level approach will leverage resources developed through previous and current large-scale projects to produce accurate multi-level emission estimates and identify opportunities to mitigate enteric GHG emissions. The results of this project will provide accurate, reliable, and robust data for industry stakeholders, national policy, and GHG inventories. The second example is a research collaboration with a commercial turkey breeding company that will enable breeding strategies for long-term and sustainable genetic improvement in health traits. This project aims to reduce preslaughter mortality by 5% and condemnations due to myopathies and health issues. This reduction alone is expected to result in 7.5M kg more turkey meat at a value of $19.8M CAD. Furthermore, there is also an expected reduction of 2.3M kg of CO2 equivalent per year for each 1% livability improvement due to production efficiencies and reduced inputs wasted for more sustainable and ethical meat production. Overall, ongoing and future research initiatives will continue to deliver solutions for key Canadian livestock sectors to improve animal health and welfare as well as efficiency and sustainability. The strides made in these ongoing collaborative projects are imperative for enhancing the sustainability of animal agriculture to feed the growing population. [ABSTRACT FROM AUTHOR]

Quantum computing (QC) is not a futuristic notion in agriculture, though its full potential has yet to be realized. QC is an emerging field at the intersection of physics and computer science that holds immense potential to revolutionize various sectors, including agriculture production and artificial intelligence (AI) modeling. While QC is still in the early stages of development and practical applications within agriculture are not yet widespread, researchers are actively exploring its potential benefits in various agricultural domains, including crop optimization, livestock breeding, and environmental monitoring. QC harnesses the principles of quantum mechanics to perform computations using quantum bits or qubits, which can exist in multiple states simultaneously. Unlike classical computers, which rely on binary bits representing 0 or 1, quantum computers exploit phenomena such as superposition and entanglement to process information in parallel, potentially offering exponential speedup for certain types of problems. In agriculture production, particularly in animal science, QC offers promising avenues for optimizing processes and enhancing productivity. Quantum algorithms can analyze vast amounts of genomic data to improve breeding programs, leading to the development of more resilient and productive livestock breeds. Furthermore, QC can facilitate precision farming techniques by modeling complex environmental factors and animal behavior to optimize feeding strategies, disease management, and overall farm management practices. Moreover, QC can significantly benefit AI modeling by accelerating computations and enabling more efficient training of AI models. Quantum algorithms can enhance the performance of AI algorithms in various tasks, including pattern recognition, natural language processing, and predictive analytics. By leveraging quantum-enhanced optimization algorithms, AI models can achieve better convergence and accuracy, leading to more effective decision-making and problem-solving capabilities. While hybrid intelligent models also represent a novel frontier in agriculture, QC has the potential to expedite the merging of mechanistic and AI modeling paradigms, facilitating a more holistic understanding of complex systems in agriculture and beyond. By integrating mechanistic models, which describe the underlying physical processes, with AI models, which learn patterns from data, quantum computing can enable comprehensive simulations and predictions of agricultural systems. This fusion of modeling paradigms can lead to more accurate and robust predictions of crop yields, livestock performance, and environmental impacts, facilitating informed decision-making for farmers and policymakers. The application of QC in agriculture, however, requires interdisciplinary collaborations between physicists, computer scientists, agronomists/animal scientists, and AI researchers. These collaborations can drive the development of quantum algorithms tailored to agricultural applications, the integration of quantum-enhanced AI techniques into existing modeling frameworks, and the deployment of QC resources in real-world agricultural systems. Ultimately, harnessing the power of QC holds the potential to revolutionize agriculture production practices, including regenerative agriculture, and advance AI modeling capabilities, paving the way for a more sustainable and efficient agricultural industry [ABSTRACT FROM AUTHOR]

Rabbits are one of the most popular livestock breeds raised for their meat, fur, and companionship. Rabbit meat is fast gaining prominence as a healthier meat compared with beef, mutton, pork and chevon, which are mostly consumed in Nigeria. This study investigated breed differences in mortality, survival rates and post-weaning growth rate of rabbits reared under inimical environmental conditions. The animals were fed commercially compounded feed with 18% crude protein and 2300Kcal metabolizable energy with intermittent feeding of Panicum sp and Tridax sp. The study area, located at latitude 6.5867° N and longitude 3.9700° E, had an average daily temperature of 35°C and relative humidity of 64%, which negatively impacted the adaptation, survival rates and growth performance of the rabbits. A total of 48 weaner rabbits 8 wk of age, comprising 12 each (9 does and 3 bucks) of Checkered, Chestnut, Dutch and Hyla breeds were reared for 10 wk post-weaning. Mortality was recorded across the breeds and the body weights (BW) of the rabbits were also recorded on a weekly basis for the entire 10-wk period. The study evaluated survival rates across breeds and sex and BW gain. Statistical analyses were conducted using the Minitab software for Chi Squared test of independence for counts and descriptive statistics and general linear model analysis of variance for bodyweight gain. The statistical model describing the analysis was Yijk = µ + αi + (α:β) ij + eijk where αi is the i th fixed effect of breed and βj is the jth fixed effect of sex. The model accounted for 67.03% variation in total weight gain. Further mean separation was done using the Tukey’s multiple comparison procedure. Mortality rates across breeds on the average was 56.25%, with Checkered, Chestnut, Dutch and Hyla respectively recording 66.67%, 41.67%, 50.00% and 66.67% mortality, respectively. Mortality rate across sexes was 63.89% for does and 33.33% for bucks; however, mortality rates were independent (P > 0.05) of both breed and sex with a Chi-Squared value of 2.285 and 3.41, respectively, despite the numerical differences in mortality rates across breeds and sexes. Average total BW gain during the study period across the breeds and within breeds is as presented in Table 1. The nesting of sex within breed revealed that the only significant (P > 0.05) difference was noticed between the Hyla buck and Chestnut doe, while other means were not statistically different (P > 0.05). The Chestnut breed with the least BW gain adapted well in the environment with greatest survival rate, while the Hyla breed had the greatest BW gain and least survival rate throughout the study. This study indicated a negative relationship between survival rates and BW gain, that lighter breeds of rabbit tend to have greater survival rates than the heavier breeds. [ABSTRACT FROM AUTHOR]

The article discusses the wildlife-livestock interface and its implications for biodiversity conservation. It highlights the increasing interactions between wildlife and livestock due to changes in farming practices, human demography, and land use. The article presents different perspectives on the positive and negative impacts of this coexistence and proposes interventions such as zoning and land use planning, diversifying community livelihoods, and implementing biosafety measures. It also explores the bidirectional relationships between livestock production and biodiversity preservation, emphasizing the importance of integrating both concepts. The article concludes by emphasizing the need for cooperation among stakeholders and multidisciplinary approaches to manage the wildlife-livestock interface effectively. [Extracted from the article]

Escalating impacts of climate change present a credible threat to livestock-based food production. Increasing environmental challenges directly affect animal fitness, production performance, and reproductive efficiency with accumulative morbidities and mortality. Albeit extant livestock breeds are adapted to different climate extremes, the steep trajectory of decline in genetic diversity poses a serious threat to the sustenance of livestock farming. After pluripotent stem cells (PSCs) were derived for mice more than 30 years ago, scientists were quick to recognize PSCs as an approach to accelerate livestock biotechnology and assisted reproduction. We posited that core PSC characteristics such as indefinite self-renewal make them ideal for setting up an inexhaustible diploid livestock genetic resource bank. Nevertheless, it has been difficult to derive and sustain naïve PSCs from ruminants. Even reports of generating induced-PSCs (iPSCs) via reprogramming somatic cells that circumvents the embryo and factors such as sex, age or reproductive status, has been crippled with reproducibility issues precluding any livestock applications. In recent systematic studies, we documented two roadblocks: First, that signaling pathways necessary to sustain self-renewal of PSCs from cattle remained unknown. Second, bovine somatic cells have a stable epigenome that is resistant to complete reprogramming to pluripotency. Through systems biology examination of signal homeostasis in the bovine blastocyst inner cell mass (ICM), we uncovered that transforming growth factor (TGF) ß effects are actively perturbed in the bovine ICM. This led to the discovery that inhibition of downstream ALK 4/5/7 together with GSK3ß and MEK1/2 signaling, supported robust in vitro self-renewal of naïve bovine iPSCs. Simultaneously, we uncovered that epigenetic regulation by the SV40 large T antigen together with the reprogramming genes (OCT4, SOX2, KLF4 and MYC) could result in not only complete reprogramming, but also cells that are set to a stable ground state of pluripotency akin to totipotent stem cells (TPSCs) seen in 16-cell-stage bovine embryos. Cloning performed using the induced TPSCs (iTPSCs) showed significantly greater efficiency of blastocyst formation. Surprisingly, applying identical methods to murine somatic cells also resulted in iTPSCs that can contribute to placenta formation in vivo indicating that the mechanistic basis for sustaining the ground state of developmental plasticity was conserved across species. These findings have now defined a high-fidelity platform for achieving iPSC-based biotechnologies (gene editing and cloning) and for exploring different ruminant livestock applications that have not been previously practicable. Of central importance, these findings also open a path to establishing a live regenerative repository of inexhaustible diploid livestock that can secure the evolving genetic needs for sustaining animal production into the future. Permanent assets of genetic diversity preserved as iTPSCs would ensure rapid resilience in production, health and fertility through propagating heterosis and enabling genetic fixes for regional climate-resilient livestock phenotypes that better tolerate environmental extremes. [ABSTRACT FROM AUTHOR]

Captive breeding and reintroduction programs have been established for several threatened amphibian species globally, but with varied success. This reflects our relatively poor understanding of the hormonal control of amphibian reproduction and the stimuli required to initiate and complete reproductive events. While the amphibian hypothalamo–pituitary–gonadal (HPG) axis shares fundamental similarities with both teleosts and tetrapods, there are more species differences than previously assumed. As a result, many amphibian captive breeding programs fail to reliably initiate breeding behaviour, achieve high rates of fertilization or generate large numbers of healthy, genetically diverse offspring. Reproductive technologies have the potential to overcome these challenges but should be used in concert with traditional methods that manipulate environmental conditions (including temperature, nutrition and social environment). Species-dependent methods for handling, restraint and hormone administration (including route and frequency) are discussed to ensure optimal welfare of captive breeding stock. We summarize advances in hormone therapies and discuss two case studies that illustrate some of the challenges and successes with amphibian reproductive technologies: the mountain yellow-legged frog (Rana muscosa ; USA) and the northern corroboree frog (Pseudophryne pengilleyi ; Australia). Further research is required to develop hormone therapies for a greater number of species to boost global conservation efforts. [ABSTRACT FROM AUTHOR]

Optimizing beef production system efficiency requires an understanding of genetic potential suitable for a given production environment. Therefore, the objective of this retrospective analysis was to determine the influence of cow body weight (BW) adjusted to a common body condition score (BCS) of 5 at weaning-influenced cow-calf performance and postweaning steer and heifer progeny performance. Data were collected at the Gudmundsen Sandhills Laboratory, Whitman, NE, on crossbred, mature cows (n = 1,607) from 2005 to 2017. Cow BCS at calving, prebreeding, and weaning were positively associated (P < 0.01) with greater cow BW. Increasing cow BW was positively associated (P < 0.01) with the percentage of cows that conceived during a 45-d breeding season. For every additional 100-kg increase in cow BW, calf BW increased (P < 0.01) at birth by 2.70 kg and adjusted 205-d weaning BW by 14.76 kg. Calf preweaning average daily gain (ADG) increased (P < 0.01) 0.06 kg/d for every additional 100-kg increase in cow BW. Heifer progeny BW increased (P < 0.01) postweaning with every additional 100-kg increase in dam BW. Dam BW did not influence (P ≥ 0.11) heifer puberty status prior to breeding, overall pregnancy rates, or the percentage of heifers calving in the first 21 d of the calving season. Steer initial feedlot BW increased by 7.20 kg, reimplant BW increased by 10.47 kg, and final BW increased by 10.29 kg (P ≤ 0.01) for every additional 100-kg increase in dam BW. However, steer feedlot ADG was not influenced (P > 0.67) by dam BW. Hot carcass weights of steers were increased (P = 0.01) by 6.48 kg with every additional 100-kg increase in cow BW. In a hypothetical model using the regression coefficients from this study, regardless of pricing method, cow-calf producers maximize the highest amount of profit by selecting smaller cows. Overall, larger-sized cows within this herd and production system of the current study had increased reproductive performance and offspring BW; however, total production output and economic returns would be potentially greater when utilizing smaller-sized cows. [ABSTRACT FROM AUTHOR]

The article discusses livestock breeding in the United States during the early twentieth century, focusing particularly on aspects of eugenics and government policy towards certain animals between 1919 and 1933. The U.S. Department of Agriculture (USDA) and Cooperative Extension Service (CES) defined scrubs as bulls of mixed or unknown breeding capable of passing along undesirable traits if bred, thus leading to many of them being killed after mock trials to prevent their breeding and passing along their traits to their progeny. It argues such programs followed popularly held notions of eugenics and race of the period.

The aim of this study was to investigate whether HtrA is responsible for differences in adherence and invasion of Campylobacter jejuni towards human and chicken cell lines. Gentamicin protection assays were performed with either human Caco‐2 or chicken 2G4 cells using C. jejuni strain NCTC11168 to compare the adhesion and invasion rates towards these two cell types. The results revealed significant differences in the adhesion and invasion rates between the human and avian cells. Deletion of the Campylobacter htrA gene, coding for the dual function of serine protease and chaperonin with a role in pathogenesis, led to a reduction of the rates in both cell lines. Using a single‐amino acid substitution mutant (ΔhtrA/htrAS197A) that lacked protease activity, but retained chaperonin activity, we show that the first is involved in the invasion of human Caco‐2 and chicken 2G4 cells, whereas the latter mutant invaded at lower levels. Adherence towards the chicken cells is higher than towards Caco‐2 cells and this is also dependent on HtrA. Together, these data suggest that the proteolytic activity of HtrA is involved in the difference in host response of C. jejuni towards human and chicken‐derived cells. Significance and Impact of the Study: Campylobacter jejuni is the main cause for bacterial foodborne enterocolitis worldwide. While colonization of the human intestine can lead to severe problems, avian hosts – as the major source of infection – remain unaffected by the bacteria. We showed that the bacterial serine protease and chaperonin HtrA are involved in adhesion and invasion in both species and not responsible for the discrepancy of virulence between the different hosts. In future, HtrA might act as a target for inhibitors to avoid or eradicate colonization in chickens as a less problematic alternative to antibiotics in commercial livestock breeding. [ABSTRACT FROM AUTHOR]

An incident of sudden deaths in the breeding stock was reported from a farrow‐to‐finish commercial pig farm in Greece. The 8·4% of sows during lactation and gestation period presented anorexia, fever, haematuria, return‐to‐oestrus and sudden deaths (mortality rate: 2·3%). Blood and urine samples were collected from four diseased sows. Furthermore, swabs from urine bladders were collected from two dead sows and four culled sows at the slaughterhouse. Blood testing demonstrated mild leucocytosis and absence of azotaemia. Urinalysis revealed haematuria, proteinuria, bilirubinuria and active urine sediment with bacilli, epithelial cells and leucocytes, crystals and granular casts. Histopathological evaluation of the bladder demonstrated chronic active polypoid cystitis. The bacterial culture revealed the presence of Serratia liquefaciens. The antibiotic susceptibility testing showed high resistance to the most common antibiotics, with the highest sensitivity of the isolate towards quinolones. After the administration of a single dose of 7·5 mg kg−1 body weight enrofloxacin intramuscularly, the mortality rate decreased to less than 0·5% along with a remarkable reduction in the severity of clinical signs. Based on our findings, S. liquefaciens induced severe clinical signs and deaths in sows, mainly due to urinary infection. Inadequate water sanitation might have been responsible for increased exposure to S. liquefaciens. Significance and Impact of the Study: In this study, the isolation of Serratia liquefaciens from the urinary tract of pigs associated with clinical signs and increased mortality was described for the first time. Serratia liquefaciens is an important cause of hospital‐acquired human infections. The isolate in this study was resistant to the most common antibiotics. Therefore, the use of quinolones which are drugs of last resort for treatment of infections was the only therapeutic option. The presence of the resistant bacterium in the urinary tract raises concerns for its zoonotic potential. [ABSTRACT FROM AUTHOR]

Genetic evaluation programs can provide valuable selection tools for sheep breeders. However, industry acceptance and utilization of these tools is still limited. The objective here was to evaluate the performance and value of rams enrolled in the National Sheep Improvement Program (NSIP) compared with those not enrolled during a ram test program. Rams (Katahdin = 16, Texel = 3) were delivered to the Southwest Virginia Agricultural Research and Extension Center Ram Test on May 31. Rams were dewormed and rested for two weeks. On June 21, rams were given Haemonchus contortus L3 larvae adjusted for body weight (average = 5000 L3). FAMACHA scores and fecal egg counts (FEC) were monitored every two weeks until August 30. Rams were dewormed based on FAMACHA = 3. The top 50% of rams, excluding any dewormed rams, based on the sale index [Sale Index = 0.50*(0.33*average daily gain ratio + 0.67*weight per day of age ratio) + 0.50*logFEC ratio] were sold at auction as breeding stock. Rams were classified as NSIP if enrolled. Statistical analyses were performed using SAS (SAS Institute, Cary, NC). Of the19 rams on test, 52% were NSIP. Thirteen rams required deworming during the test (38% of these were NSIP rams). Average sale index of NSIP rams tended to be greater than that of non-NSIP rams (101.4 vs. 98.3, P = 0.06). Of rams with sale index = 100 (top 50%), a greater percentage of these rams were NSIP vs. non-NSIP (61% vs. 39%, respectively; P < 0.05). When NSIP status was evaluated for the top 20% of rams (sale index =07), a greater percentage of these rams were also NSIP vs. non-NSIP (78% vs. 22%, respectively; P < 0.01). Rams (n = 57) were sold on September 23 with an average sale price of $1,482. Rams enrolled in NSIP commanded greater prices than those not enrolled ($1,659 vs. $1,222, P < 0.05). When sale price was regressed on sale index for NSIP and non-NSIP rams, R2 for NSIP rams was 0.19 compared with the R2 for non-NSIP rams of 0.76. Given the weaker relationship between price and sale index for NSIP rams, estimated breeding values (EBVs) were evaluated. NSIP rams with EBVs reported for post-weaning weight, post-weaning FEC, and Maternal Hair Index sold for greater prices than those rams missing one or all of these EBVs ($1,837 vs. $971, respectively; P < 0.05). In summary, NSIP rams had greater performance (as indicated by sale index) and value compared with non-NSIP rams. For rams enrolled in NSIP, sale index was a poor predictor of value indicating buyers may be considering other factors besides sale index, such as EBVs, when purchasing NSIP rams. [ABSTRACT FROM AUTHOR]

The usefulness of genomic prediction in crop and livestock breeding programs has prompted efforts to develop new and improved genomic prediction algorithms, such as artificial neural networks and gradient tree boosting. However, the performance of these algorithms has not been compared in a systematic manner using a wide range of datasets and models. Using data of 18 traits across six plant species with different marker densities and training population sizes, we compared the performance of six linear and six non-linear algorithms. First, we found that hyperparameter selection was necessary for all non-linear algorithms and that feature selection prior to model training was critical for artificial neural networks when the markers greatly outnumbered the number of training lines. Across all species and trait combinations, no one algorithm performed best, however predictions based on a combination of results from multiple algorithms (i.e., ensemble predictions) performed consistently well. While linear and non-linear algorithms performed best for a similar number of traits, the performance of non-linear algorithms vary more between traits. Although artificial neural networks did not perform best for any trait, we identified strategies (i.e., feature selection, seeded starting weights) that boosted their performance to near the level of other algorithms. Our results highlight the importance of algorithm selection for the prediction of trait values. [ABSTRACT FROM AUTHOR]

While the environmental impacts of livestock production, such as greenhouse gas emissions and water usage, have been studied for a variety of US livestock production systems, the environmental impact of US sheep production is still unknown. A cradle-to-farm gate life cycle assessment (LCA) was conducted according to international standards (ISO 14040/44), analyzing the impacts of CS representing five different meat sheep production systems in California, and focusing on carbon footprint (carbon dioxide equivalents, CO2e) and irrigated water usage (metric ton, MT). This study is the first to look specifically at the carbon footprint of the California sheep industry and consider both wool and meat production across the diverse sheep production systems within California. This study also explicitly examined the carbon footprint of hair sheep as compared with wooled sheep production. Data were derived from producer interviews and literature values, and California-specific emission factors were used wherever possible. Flock outputs studied included market lamb meat, breeding stock, 2-d-old lambs, cull adult meat, and wool. Four different methane prediction models were examined, including the current IPCC tier 1 and 2 equations, and an additional sensitivity analysis was conducted to examine the effect of a fixed vs. flexible coefficient of gain (k g) in mature ewes on carbon footprint per ewe. Mass, economic, and protein mass allocation were used to examine the impact of allocation method on carbon footprint and water usage, while sensitivity analyses were used to examine the impact of ewe replacement rate (% of ewe flock per year) and lamb crop (lambs born per ewe bred) on carbon footprint per kilogram market lamb. The carbon footprint of market lamb production ranged from 13.9 to 30.6 kg CO2e/kg market lamb production on a mass basis, 10.4 to 18.1 kg CO2e/kg market lamb on an economic basis, and 6.6 to 10.1 kg CO2e/kg market lamb on a protein mass basis. Enteric methane (CH4) production was the largest single source of emissions for all CS, averaging 72% of total emissions. Emissions from feed production averaged 22% in total, primarily from manure emissions credited to feed. Whole-ranch water usage ranged from 2.1 to 44.8 MT/kg market lamb, almost entirely from feed production. Overall results were in agreement with those from meat-focused sheep systems in the United Kingdom as well as beef raised under similar conditions in California. [ABSTRACT FROM AUTHOR]

Until now, the development of precision livestock farming has been largely based on data acquisition automation. The future challenge is to develop interpretative tools to capitalize on highthroughput raw data and to generate benchmarks for phenotypic traits. We developed a dynamic model of female BW that converts BW time series into a vector of biologically meaningful parameters. The model is based on a first submodel that split a female's weight into elementary mass changes related to biological functions: growth (G component), reserves balance (R component), uterine load (U component), and maternal investment (M component). These elementary weight components are linked to the second submodel, which represents the litter developmental stages (oocyte, fetus, neonate, and juvenile) that drive elementary components of dam weight over each reproductive cycle. The so-called GRUM model is based on ordinary differential equations and laws of mass action. Input data are BW measures, age, and litter weight at birth for each parturition. Outputs of the fitting procedure are a vector of parameters related to each GRUM component and indexed by reproductive cycle. We illustrated the potential application of the model with a case study including growth and successive lactations (n = 202) from 45 dairy goats from the Alpine (n = 27) and Saanen (n = 18) breeds. The fitting procedure converged for all individuals, including goats that went through extended lactations. We analyzed the fitted parameters to quantify breed and parity effects over 4 reproductive cycles. We found significant differences between breeds regarding gestation components (fetal growth and reserves balance). We also found significant differences among reproductive cycles for reserves balance. Although these findings are based on a small sample, they illustrate how use the model can be to adapt herd management and implement grouping strategies to account for individual variability. [ABSTRACT FROM AUTHOR]

Combining purebreed and crossbreed information is beneficial for genetic evaluation of some livestock species. Genetic evaluations can use relationships based on genomic information, relying on allele frequencies that are breed specific. Singlestep genomic BLUP (ssGBLUP) does not account for different allele frequencies, which could limit the genetic gain in crossbreed evaluations. In this study, we tested the performance of different breed-specific genomic relationship matrices (GB) in ssGBLUP for crossbreed evaluations; we also tested the importance of genotyping crossbred animals. Genotypes were available for purebreeds (AA and BB) and crossbreeds (F1) in simulated and real pig populations. The number of genotyped animals was, on average, 4,315 for the simulated population and 15,798 for the real population. Cross-validation was performed on 1,200 and 3,117 F1 animals in the simulated and real populations, respectively. Simulated scenarios were under no artificial selection, mass selection, or BLUP selection. Two genomic relationship matrices were constructed based on breed-specific allele frequencies: 1) GB1, a genomic relationship matrix centered by breed-specific allele frequencies, and 2) GB2, a genomic relationship matrix centered and scaled by breed-specific allele frequencies. All G (the across-breed genomic relationship matrix), GB1, and GB2 were also tuned to account for selective genotyping. Using breed-specific allele frequencies reduced the number of negative relationships between 2 purebreeds, pulling the average closer to 0, as in the pedigree-based relationship matrix. For simulated populations that included mass selection, genomic EBV (GEBV) in F1, when using GB1 and GB2, were, on average, 10% more accurate than G; however, after tuning to account for selective genotyping, G provided the same accuracy as for breed-specific genomic relationship matrices. For the real population, accuracies for litter size in F1 were 0.62 for G, GB1, and GB2, and tuning had no impact on accuracy, except for GB2, which was 1 percentage point less accurate. Accuracy of GEBV for number of stillborns in F1 was 0.5 for all tested genomic relationship matrices with no changes after tuning. We observed that genotyping F1 increased accuracies of GEBV for the same animals by up to 39% compared with having genotypes for only AA and BB. In crossbreed evaluations, accounting for breed-specific allele frequencies promoted changes in G that were not influential enough to improve accuracy of GEBV. Therefore, the best performance of ssGBLUP for crossbreed evaluations requires genotypes for pure- and crossbreeds and no breed-specific adjustments in the realized relationship matrix. [ABSTRACT FROM AUTHOR]

In the last couple of years, the interest in possible applications of epigenetics aiming to improve livestock production and welfare has grown. In due course, the livestock industry will have the increased ability to tailor the animal's epigenome to produce phenotypes that are more desirable, while increasing animal welfare and resiliency. Altered DNA methylation was shown to impact livestock phenotypes including egg-laying, fiber growth, heat stress, mastitis, meat and milk production. [Extracted from the article]

Understanding the underlying effects of ongoing selection is of interest to livestock breeding programs. Commercial livestock genotyping has generated datasets well-suited to explore how strong artificial selection has impacted the genome over very short time periods. We have developed a method for mapping ongoing polygenic selection in populations with temporally stratified genomic data called Generation Proxy Selection Mapping (GPSM). GPSM utilizes a genome-wide linear mixed model to identify allelic associations with an animal's generation number or some proxy (i.e., birth date). We applied GPSM to two large contemporary beef cattle datasets from Red Angus (n = 46,454) and Simmental (n = 90,580) breeds, with 11,759,568 high-quality imputed variants per animal. This analysis identified 294 distinct loci actively under selection. Due to the high power of these datasets, we found that GPSM could detect very small and recent(< 10 years) allele frequency changes consistent with polygenic selection. These analyses identified variants within genomic regions associated with known breed characteristics, like fertility and maternal ability in Red Angus and carcass merit and coat color in Simmental. Over 60% of GPSM loci resided in or near (< 50kb) annotated genes. We leveraged the resolution of our imputed sequence variants to overlay known epigenetic marks and possibly functional regions. 36% of GPSM loci overlapped these putatively functional regions genomic intervals. In addition to GPSM, we used two other more traditional selective sweep methods, the number of segregating loci (nSL) and Raised Accuracy in Sweep Detecting (RAiSD), to detect selection in this data. We observed minimal overlap (< 10% of loci) between traditional selective sweep mapping and GPSM. This suggests that selection mapping with GPSM can complement traditional sweep mapping methods when temporal genomic data exists. In addition to better understanding the biological processes and features that underlie artificial selection, GPSM signatures might serve as important genomic annotations. [ABSTRACT FROM AUTHOR]

The genetic selection is a form of optimization. Traits in explicit or implicit selection index are improved, while other traits change according to genetic correlations among the traits. After long selection, usually production traits improve while fitness traits deteriorate. At the gene level, it seems that genes associated with positive effects on major traits tend to fixation, and remaining genes with large effect exhibit pleiotropy. While selection for fitness traits is moderately successful because of small heritability, constantly improving management counterbalances the deterioration of fitness traits. Treating the selection as an optimization raises a question about selection limits, particular with feed conversion. Latest experiences suggest that eventually strong selection for residual feed intake reduces fertility and increases late mortality. The environment changes, with climate change having a profound effect. The industry faces a choice of either breeding for new conditions or devising new managemental modifications. The choice depends on species as the environment can be more easily improved for animals in confinement or raised in intensive conditions (pigs, broilers, dairy cattle), but less for animals on pasture (beef cattle and sheep). The choice depends on financials and speed. An interesting example of such a trade-off is in dairy industry approach to mitigate heat stress, which results in plummeting fertility, decreased milk yield, and premature culling leading to insufficient replacements. To counter these challenges, a methodology for genetic evaluation for heat tolerance was developed and applied to US national data for Holsteins. Instead of genetics, the industry implemented managemental modifications: improved cooling devices, timed AI increased fertility, and the use of sexed semen. In pigs and chicken, that the response to stress is less in nucleus and stronger in commercial environment, and selection for commercial performance is paramount. In summary, mitigations of stress involve a combination of genetic and environmental factors. [ABSTRACT FROM AUTHOR]

Animal breeders have exploited many technological advances for increasing genetic gain in economically and functionally important traits. The implementation of such technologies in routine breeding programs has permitted genetic gains in traditional milk, meat and egg production traits as well as, more recently, in low-heritability traits like health, fertility, and even behavior. As global demand for animal products increases, animal breeders must ensure the technologies, methods and strategies employed are sustainable, to consider the many emerging technologies that are currently being investigated in various fields, and to ensure a social license to continue producing animal products. Here we discuss the societal, ethical, environmental, and economical aspects of sustainability in the context of livestock breeding. We review a number of technologies that have helped shape livestock breeding programs in the past and present, along with those potentially forthcoming. These tools have materialized in the areas of reproduction, genotyping and sequencing, genetic modification, epigenetics, and other areas of "omics" technologies. Although many of these technologies bring encouraging opportunities for genetic improvement of livestock populations, their applications and benefits need to be weighed with their impacts on sustainability. [ABSTRACT FROM AUTHOR]

Whole genome prediction (WGP) based on high density SNP marker panels is known to improve the accuracy of breeding value (BV) prediction in livestock. However, these accuracies can be compromised when genotype by environment interaction (G×E) exists but is not accounted for. Reaction norm (RN) and random regression (RR) models have proven to be useful in accounting for G×E in pre-WGP evaluations by modeling BV as linear or higher order functions of environmental or temporal covariates. We extend these RR/RN models based on several alternative specifications for SNP-specific intercepts and linear slopes on environmental covariates. One specification is based on bivariate normality (BVN) of SNP-specific intercepts and slopes, whereas 2 others, IW-BayesA and based on inverted Wishart (IW) extensions IW-BayesB, are, respectively, bivariate Student t extensions of currently popular models without (BayesA) or with (BayesB) variable selection. We highlight alternative specifications based on the square root free Cholesky decomposition (CD) of SNP-specific variance-covariance (VCV) matrices in an attempt to better differentially model environmentally sensitive from environmentally robust QTL. Two CD specifications were considered with (CD-BayesB) or without (CD-BayesA) any variable selection on intercept and slope effects. We compared each of the 5 models based on an RN simulation study. Six scenarios were considered based on differences in overall genetic correlations between SNP-specific intercept and slope effects as well as on heritabilities and numbers of environmentally robust versus sensitive QTL. In most scenarios, IW-BayesA had the greatest accuracy, whereas CD-BayesB exhibited the greatest accuracy in low complexity architectures (i.e., low number of QTL). In an RR application of a Duroc × Pietrain resource population at Michigan State University, 5,271 SNP markers and 928 F2 animals with known pedigree were analyzed for backfat thickness at wk 10, 13, 16, 19, and 22. SNP-based RR methods had a 2.5% greater (P < 0.0001) cross-validation accuracy for predicting phenotypes than the SNP-based conventional BayesA/ BayesB and/or pedigree based RR BLUP; however, none of the proposed RR models had performances that were different from each other. [ABSTRACT FROM AUTHOR]

The article discusses the Breeding and Genetics symposium titled "Resilience of Livestock to Changing Environments" held at Salt Lake City, Utah on July 19–24, 2016. It mentions focus of the symposium to provide a comprehensive overview of current knowledge about the effects of hot environments on livestock species. It also presents the views of speaker R. J. Spelman on introgression of genes conveying resistance to heat stress into cattle populations.

Although animal breeding was practiced long before the science of genetics and the relevant disciplines of population and quantitative genetics were known, breeding programs have mainly relied on simply selecting and mating the best individuals on their own or relatives' performance. This is based on sound quantitative genetic principles, developed and expounded by Lush, who attributed much of his understanding to Wright, and formalized in Fisher's infinitesimal model. Analysis at the level of individual loci and gene frequency distributions has had relatively little impact. Now with access to genomic data, a revolution in which molecular information is being used to enhance response with "genomic selection" is occurring. The predictions of breeding value still utilize multiple loci throughout the genome and, indeed, are largely compatible with additive and specifically infinitesimal model assumptions. I discuss some of the history and genetic issues as applied to the science of livestock improvement, which has had and continues to have major spin-offs into ideas and applications in other areas. [ABSTRACT FROM AUTHOR]

Sire selection can have long-term impacts on flock performance. The objective here was to evaluate the effect of performance-tested and/or NSIP rams on progeny performance and value in a ram test program. Rams (Katahdin = 104, Dorper = 7, Texel = 3, Cheviot = 3) were delivered to the Southwest Virginia Agricultural Research and Extension Center (SWAREC) Ram Test on June 1. Ram pedigrees were obtained from consignors and rams were classified based on whether their sires were tested in a previous SWAREC Ram Test (TESTED), enrolled in the National Sheep Improvement Program (NSIP), or neither TESTED nor NSIP (NEITHER). Some sires (16%) were previously tested and enrolled in NSIP. Rams were dewormed and rested for two weeks. On June 22, rams were given Haemonchus contortus larvae adjusted for body weight (average = 5000 L3). FAMACHA scores and fecal egg counts (FEC) were monitored every two weeks until August 31. Rams were dewormed based on FAMACHA ≥ 3. Select rams were sold at auction as breeding stock. Statistical analysis were performed using SAS (SAS Institute, Cary, NC). Rams requiring deworming had greater FAMACHA scores and FEC at all time points (P < 0.05), despite not requiring treatment until August 17 (5%) and August 31 (12%). In total, 17% of rams were dewormed. Of the dewormed rams, a smaller portion of rams sired by TESTED rams (10%) and NSIP rams (15%) required treatment compared to rams sired by NEITHER rams (85%; P < 0.05). Rams sired by TESTED and NSIP rams had a higher average value than those sired by NEITHER rams ($2070 and $1838, respectively, vs. $1078; P < 0.05). Selection of sires that are TESTED and/or NSIP resulted in progeny that had a lesser chance of requiring treatment and sold for greater value. [ABSTRACT FROM AUTHOR]

Three workshops were held to increase producer awareness of new production practices and opportunities for sheep production. These events were coordinated by Amazing Grazing with the assistance of county livestock agents. All workshops included classroom and breakout sessions featuring hands-on activities. In September 2016, the first sheep-focused workshop was held at the E. Carroll Joyner Beef Education Unit in Raleigh. Topics included opportunities for sheep production, ram selection, marketing, using temporary electric fence, grazing management to improve soil health, grazing sheep in solar farms and health management. The 2017 event was held in May at the Western NC Regional Livestock Center near Canton. Producers learned about opportunities for sheep production, improved grazing management, sheep marketing and fencing options. The Piedmont Research Station near Salisbury served as the location for the 2018 workshop. The agenda featured hoof health management and pre-breeding nutrition management, improving forage systems, breeding stock selection, pasture improvement cost-share programs and hoof trimming. Total registration was 132 with 83 evaluations completed. Participants were 60% male and 40% female with 57% being over age 50. Total pasture hectares grazed by participants was 886 with 97 ha as hay. Livestock inventories totaled 2,183 sheep, 733 goats, 720 beef cattle and 99 horses. A few participants had no livestock but were gathering information for future ventures. Post-workshop evaluation indicated 100% of attendees increased understanding of each major agenda topic. On a scale of 1 to 4 (1 = not satisfied to 4 = very satisfied), participants indicated they were very satisfied with the instructors' knowledge (3.80±0.45), workshop environment/format (3.68±0.58), and overall quality (3.78±0.44). Ninety-seven percent of the attendees indicated that this workshop met their expectations, and one hundred percent would recommend it to others. Producer responses indicate a growing interest in sheep/goat production and a need for practical education programs. [ABSTRACT FROM AUTHOR]

Tall fescue possesses heat, drought, and pest resistance conferred to the plant by its mutualistic relationship with the ergot alkaloid producing fungal endophyte, Neotyphodium coenophialum. The objec-tive of this study was to evaluate the impact of ergot alkaloid consumption on growth, scrotal circumference (SC), and semen quality. The SC measurement and percentage of motile and normal sperm were used to determine if a bull passed the breeding soundness exam (BSE) requirements. Bulls (n = 14) between 13 and 16 mo of age exhibiting >32 cm SC and having passed a BSE were assigned to 1 of 2 dietary treatments account-ing for BCS and BW. Bulls were fed the treatment diet containing toxic tall fescue seed (E+; 0.8 μg of ergo-valine and ergovalanine/g DM) or the control diet con-taining endophyte-free nontoxic tall fescue seed (E-) for 126 d. Blood samples were collected and BSE and BCS accessed at the start of the test (d 0) and every 21 d to the end of test (d 126). Weights were obtained on d 0 and d 126. Semm prolactin (PRL) concentrations were affected by treatment x day interactions (P = 0.04) veri-fying the effectiveness of the E+ diet. Bulls consuming the E+ diet exhibited declining PRL concentrations from 250 ± 52.1 ng/mL on d 0 to 30.6 ± 46.9 ng/mL by d 126 whereas bulls receiving the E- ration maintained serum PRL concentrations greater than or equal to 226.7 ± 50.4 ng/mL across the 126-d study. Body condition score (P = 0.4) and BW (P = 0.4) were not different between treatments. No difference due to treatment was observed for the percentage of bulls passing a standard BSE exam (P = 0.6) and no treatment effect was observed for any semen characteristic measured by computer-assisted semen analysis (CASA; P > 0.2). The SC was nega-tively affected by treatment x day interaction (P = 0.04) with E- bulls exhibiting a larger SC at d 126 compared with E+ bulls of 36.7 ± 0.8 versus 34.3 ± 0.8 cm, respec-tively. Within treatment, E+ bulls exhibited a decrease in SC (P = 0.0001) with ad 0 SC of 37.3 ± 0.8 cm and dropping to 34.3 ± 0.8 by d 126. Theoretically, reduced SC would negatively impact semen quality, but this was not observed. However, CASA and BSE evaluation data are consistent with recent reports indicating that bulls grazing E+ tall fescue exhibited only subtle, if any, dif-ferences on semen characteristics. [ABSTRACT FROM AUTHOR]

Two models can be used for studying binary results of AT. The additive threshold model proposes an underlying variable as summing the environmental and genetic effects from the 2 individuals involved in the mating, and the product threshold model assumes that the conditional probability of AT success is the product of the probabilities of success of 2 unobserved binary phenotypes (one is the male fertility; the other is the female fertility). The purpose of this paper is to compare the predictive ability of the product and the additive threshold models for studying AT results and to compare results obtained with the 2 models in 3 different species: cattle, sheep, and rabbits. Results showed that the predictive ability of the product model is similar to the additive model in sheep and rabbits but worst in cattle (percentage Sf wrong prediction = 42, 27, and 35% in the additive model; 43, 28, and 47% in the product model in sheep, rabbits, and cattle, respectively). Even when the 2 models have similar performance, they differed in their EBV (for instance, Pearson correlation between EBV predicted with the 2 models = 0.46 in sheep for male fertility). The product model can determine which sex is responsible for an AT failure. In sheep, the female was the responsible in 94% of the cases and male in 2% of them; in rabbits, the female was the responsible in 54% of the cases and the male in 39% of them. Different estimates of probabilities for male and female fertility success obtained with the product model in the 3 species suggest that male and female fertilities behave differently depending on the species and the uniqueness of the data sets. Although product model seems to provide additional information in the fertility process, further research is needed to understand the worst performance of the product model in cattle. [ABSTRACT FROM AUTHOR]

A total of 84 sows (PIC Line 1050) were blocked according to day of farrowing and parity and allotted in a 2 × 2 factorial arrangement of treatments with lactation feed intake (ad libitum vs. restricted) and creep feeding (no vs. yes) as factors. Sows fed for ad libiturn intake (ad libitum-fed) were allowed free access to a common lactation diet (3,503 kcal of ME/kg, 0.97% standardized ileal digestible Lys), and sows with restricted intake (restricted-fed) were fed 25% less than ad libitum-fed sows. A creep diet (3,495 ME/kg, 1.56% standardized ileal digestible Lys) with 1.0% chromic oxide was offered to creep-fed pigs from d 3 to 21. Fecal samples from creep-fed pigs were taken with sterile swabs on d 7, 14, and 21, and color was assessed to categorize pigs as eaters or non-eaters. There were no interactions (P > 0.15) between lactation feed intake and creep feeding. Ad libitum-fed sows had greater (P < 0.01) total feed intake and ADFI (99.4, 4.9 kg) than restricted-fed sows (67.9, 3.6 kg). Ad libitum-fed sows had reduced BW loss (-15 vs. -24 kg; P < 0.01), improved total (46.7 vs. 43.0 kg; P < 0.04) and daily (2.56 vs. 2.36 kg; P < 0.04) BW gains of litters, and increased (90 vs. 71%; P < 0.03) percentage of sows returning to estrus by d 14 compared with restricted-fed sows. Creep feeding for 18 d did not affect (P > 0.34) sow BW and backfat loss but increased days to estrus (5.4 vs. 4.9 d; P < 0.03). Creep feeding had no (P> 0.16) effect on preweaning growth performance. Postweaning performance of creep-fed and non-creep-fed pigs was similar (P > 0.86). When individual pigs were categorized on the basis of creep feed consumption category, eaters had greater (P < 0.05) ADG (393, 376, and 378 g) and total BW gains (11.0, 10.5, and 10.6 kg) than non-eaters or non-creep-fed pigs. In conclusion, creep feeding for 18 d did not affect preweaning and lactating sow performance. Low feed intake during lactation negatively affected sow and litter performance. Creating more creep-feed eaters during the lactation period may benefit postweaning performance. Therefore, dietary and nondietary factors that can enhance the proportion of eaters in litters should be investigated. [ABSTRACT FROM AUTHOR]

The genomics revolution has spurred the undertaking of HapMap studies of numerous species, allowing for population genomics to increase the understanding of how selection has created genetic differences between subspecies populations. The objectives of this study were to (1) develop an approach to detect signatures of selection in subsets of phenotypically similar breeds of livestock by comparing single nucleotide polymorphism (SNP) diversity between the subset and a larger population, (2) verify this method in breeds selected for simply inherited traits, and (3) apply this method to the dairy breeds in the International Bovine HapMap (IBHM) study. The data consisted of genotypes for 32,689 SNPs of 497 animals from 19 breeds. For a given subset of breeds, the test statistic was the parametric composite log likelihood (CLL) of the differences in allelic frequencies between the subset and the IBHM for a sliding window of SNPs. The null distribution was obtained by calculating CLL for 50,000 random subsets (per chromosome) of individuals. The validity of this approach was confirmed by obtaining extremely large CLLs at the sites of causative variation for polled (BTA1) and black-coat-color (BTA18) phenotypes. Across the 30 bovine chromosomes, 699 putative selection signatures were detected. The largest CLL was on BTA6 and corresponded to KIT, which is responsible for the piebald phenotype present in four of the five dairy breeds. Potassium channel-related genes were at the site of the largest CLL on three chromosomes (BTA14, -16, and -25) whereas integrins (BTA18 and -19) and serine/arginine rich splicing factors (BTA20 and -23) each had the largest CLL on two chromosomes. On the basis of the results of this study, the application of population genomics to farm animals seems quite promising. Comparisons between breed groups have the potential to identify genomic regions influencing complex traits with no need for complex equipment and the collection of extensive phenotypic records and can contribute to the identification of candidate genes and to the understanding of the biological mechanisms controlling complex traits. [ABSTRACT FROM AUTHOR]

Demographic history, current status, and efficiency of the mating strategy were analyzed using the pedigree of Pannon White (PW) rabbits born between 1992 and 2007. Potential accumulation of detrimental effects and loss of genetic diversity were also considered. Calculations and estimates were done most often for ral)bits born in 2007, whereas other reference populations (REFPOPXXXX) were specified explicitly. The pedigree contained 4,749 individuals and 580 founders, and its completeness was 82.1% up to 10 and 94.5% up to 5 generations, respectively. Generation intervals through different pathways averaged 1.2 yr. When adjusted to the pedigree completeness, the amount of inbreeding (Fi) of rabbits was comparable (5.54%) with that of other livestock populations, whereas the 10 (30) founders contributing the most to inbreeding explained a large part of the population inbreeding [i.e., 42.24% (73.18%)]. The ancestral inbreeding coefficient of REFPOP2004 (10.67%) was one-half that of REFPOP2007 (20.66%), showing its strong dependence on pedigree length. Family variance, inbreeding, and realized effective population size were 84.18 (REFPOP2006; this variable could not be calculated for the last year examined), 37.19, and 91.08, respectively. The effective numbers of ancestors, founders, and founder genomes were 48, 26, and 7.33, respectively. Although the circular mating scheme applied was generally effective, the large accumulated reduction in genetic variability indicates the need to revise and improve the current breeding strategy. [ABSTRACT FROM AUTHOR]

Little is known about mutational variability in livestock, among which only a few mutations with relatively large effects have been reported. In this manuscript, mutational variability was analyzed in 1,765 litter size records from 404 Ripollesa ewes to characterize the magnitude of this genetic source of variation and check the suitability of including mutational effects in genetic evaluations of this breed. Threshold animal models accounting for additive genetic mutations were preferred to models without mutational contributions, with an average difference in the deviance information criterion of more than 5 units. Moreover, the statistical relevance of the additive genetic mutation term was checked through a Bayes factor approach, which showed that the models with mutational variability were 8.5 to 22.7 times more probable than the others. The mutational heritability (percentage of the phenotypic variance accounted for by mutational variance) was 0.6 or 0.9%, depending on whether genetic dominance effects were accounted for by the analytical model. The inclusion of mutational effects in the genetic model for evaluating litter size in Ripollesa ewes called for some minor modifications in the genetic merit order of the individuals evaluated, which suggested that the continuous uploading of new additive mutations could be taken into account to optimize the selection scheme. This study is the first attempt to estimate mutational variances in a livestock species and thereby contribute to better characterization of the genetic background of productive traits of interest. [ABSTRACT FROM AUTHOR]

National beef cattle genetic evaluation programs have evolved in the United States over the last 35 yr to create important tools that are part of sustainable breeding programs. The history of national beef cattle genetic evaluation programs has lessons to offer the next generation of researchers as new approaches in molecular genetics and decision support are developed. Through a series of complex and intricate pressures from technology and organizational challenges, national cattle evaluation programs continue to grow in importance and impact. Development of enabling technologies and the interface of the disciplines of computer science, numerical methods, statistics, and quantitative genetics have created an example of how academics, government, and industry can work together to create more effective solutions to technical problems. The advent of mixed model procedures was complemented by a series of breakthrough discoveries that made what was previously considered intractable a reality. The creation of modern genetic evaluation procedures has followed a path characterized by a steady and constant approach to identification and solution for each technical problem encountered. At its core, the driving force for the evolution has been the need to constantly improve the accuracy of the predictions of genetic merit for breeding stock, especially young animals. Sensible approaches, such as the principle of economically relevant traits, were developed that created the rules to be followed as the programs grew. However, the current systems are far from complete or perfect. Modern genetic evaluation programs have a long way to go, and a great deal of improvement in the accuracy of prediction is still possible. But the greatest challenge remains: the need to understand that genetic predictions are only parameters for decision support procedures and not an end in themselves. [ABSTRACT FROM AUTHOR]

Sow longevity influences farm economy and can be considered an important indicator of animal welfare. Body features such as leg conformation can play a key role in sow longevity, although little is known about its effect on culling decisions. Within this context, longevity data from 587 Duroc, 239 Landrace, and 217 Large White sows were analyzed with special emphasis on the effect of leg conformation. Sow longevity was analyzed twice for each breed, testing the effect of a subjective overall score for leg conformation, or the presence or absence of 6 specific leg conformation defects. Each preliminary model also included a teat conformation score with 3 levels, farm or origin, backfat thickness at 6 mo of age, and 2 continuous sources of variation, namely the age at the first farrowing and the number of piglets born alive at each farrowing. Overall leg conformation score influenced (P < 0.01) sow longevity in Duroc, Landrace, and Large White sows, with a greater hazard ratio (HR) for poorly conformed sows (1.56, 2.16, and 1.79, respectively) than for well-conformed sows (0.32, 0.66, and 0.68, respectively). Abnormal hoof growth reduced survivability in Duroc (HR = 2.78; P < 0.001) and Landrace sows (HR = 1.88; P < 0.01); the presence of splayed feet (P < 0.05) or bumps and injuries (P < 0.00 1) increased the risk of culling in Duroc sows (HR = 2.08 and 3.57, respectively), whereas the incidence of straight pastern increased the HR in Large White sows (HR = 2.49; P < 0.01). In all 3 breeds, longevity decreased for plantigrade sows, with a greater HR in Duroc (HR = 3.38; P < 0.00 1) than in Landrace (HR = 1.53; P < 0.10) and Large White sows (HR = 1.73; P < 0.05). Teat conformation did not influence sow longevity (P > 0.10). Estimates of heritability for longevity in Duroc sows ranged from 0.05 to 0.07 depending on the algorithm applied. Leg conforma- tion had a substantial effect on sow longevity, where an accurate removal of poorly leg-conformed candidate gilts before first mating could improve sow survival and reduce culling costs. These moderate estimates of heritability indicated that survivability of Duroc sows could be genetically improved by direct selection for leg conformation. [ABSTRACT FROM AUTHOR]

Dietary trace mineral sources and levels were fed to developing gilts to evaluate their performance responses during the growth phase, but treatments were continued into the reproductive phase in which subsequent reproductive responses were evaluated. In Exp. 1, three groups of guts (n = 216) were used in a 2 x 2 factorial in a randomized complete block design (6 replicates) with treatment diets initially fed at 30 kg of BW. The first factor was trace mineral source (organic or inorganic), whereas the second factor evaluated dietary levels. The NRC requirement was the first level evaluated, whereas the second level was formulated to average industry standards (IND). Organic trace minerals were mineral proteinates, whereas the inorganic minerals were provided in salt form. The results of Exp. 1 indicated that trace mineral source or level did not affect gilt growth or feed performance responses to 110 kg of BW. Experiment 2 continued with the same females but was a 2 x 3 factorial in a split-plot design using 3 groups of females over a 6-parity period and had a total of 375 farrowings. Factors in Exp. 2 were the same as in Exp. 1, except that 2 additional pens of gilts during their development had been fed the IND level trace mineral levels of both trace mineral sources. At breeding, the gilts from these 2 additional pens were continued on the same trace mineral source and level but fed greater dietary Ca and P levels (IND + Ca:P). Litters were standardized by 3 d postpartum within each farrowing. Sows fed organic trace minerals farrowed more (P < 0.05) total (12.2 vs. 11.3) and live pigs (11.3 vs. 10.6) compared with sows fed inorganic trace minerals. Sows fed the IND + Ca:P level tended to have fewer (P < 0.10) total pigs born for both trace mineral sources. Litter birth weights were heavier (P <0.05) when sows were fed organic trace minerals, but individual piglet weights were similar. Nursing pig ADG tended to be greater (P < 0.10) when sows were fed organic trace minerals. Other sow reproductive traits (BW, feed intake, and rebreeding interval) were not affected by trace mineral source or level. Daily mineral intake increased by parity but declined when trace mineral intakes were expressed on an amount per kilogram of BW and declined during later lactations. These results suggest that feeding sows organic trace minerals may improve sow reproductive performance, but there were minimal effects on other reproductive measurements. [ABSTRACT FROM AUTHOR]

Second-parity sows (n = 7) were fed diets containing organic or inorganic trace minerals, and their progeny (n = 68) were used to determine the Fe status of pigs at birth and nursing and postweaning phases. The experiment comprised 2 parts, in which the first experiment was a 2 × 2 factorial arrangement. Sow trace mineral (organic vs. inorganic) was the first factor evaluated, and the injection of Fe (0 or 200 mg) to neonatal pigs within litter was the second factor. In Exp. 2, half the pigs in each litter from each neonatal Fe injection group were injected with Fe (0 vs. 200 mg) at weaning as an added factor in a 2 × 2 × 2 factorial arrangement in a split-split-plot design. Weanling pigs were fed diets fortified with 90 mg/kg of Fe (sulfate), but the analyzed indigenous and fortified Fe content was 170 mg/kg. Pigs in both experiments were bled at periodic intervals to determine hemoglobin (Hb) concentration, percentage of hematocrit (Hct), and ceruloplasmin oxidase activity. Neonates and d-2 pigs from sows fed organic trace minerals had lower (P < 0.05) Hb concentrations compared with sows fed inorganic trace minerals, but they had similar percentages of Hct values. Blood Hb seemed to remain lower throughout the nursing period when sows were fed organic vs. inorganic Fe. Pigs without Fe injection had decreased ADG (P < 0.05) from 0 to 7 and 7 to 17 d than pigs injected with Fe. Although Hb values increased when neonatal pigs received Fe injection, they were somewhat lower when sows were fed the organic Fe. Ceruloplasmin oxidase activity was low at birth, increased to weaning in each treatment group, and was greater in pigs without Fe injection at d 13 (P < 0.05) and those from sows fed organic minerals at d 17 (P< 0.01). In Exp. 2, when the Fe-fortified diet was fed, BW and ADG responses were both greater (P < 0.01) to 28 d postweaning when neonates had received Fe injections. Neonates not injected with Fe at birth but injected at weaning had greater ADG, Hb, and Hct values, whereas pigs injected with Fe did not respond to Fe injection at weaning, which resulted in interactions (P < 0.05) in those criteria at most measurement periods. The results indicated a reduced Fe bioavailability when sows were fed the organic Fe source, but this may also have been due to the greater Fe need, lowered Fe status, or both, of the sow because of the greater number of pigs farrowed and heavier litter weights at parturition and weaning. The results also indicated that Fe injections at birth may be critical to achieving maximum pig growth response to weaning. There was no apparent advantage to injecting Fe at weaning when neonatal pigs received Fe injections. [ABSTRACT FROM AUTHOR]

Two experiments were conducted to compare the ileal digestibility of AA in distillers dried grains with solubles (DDGS) sourced from different regions (IL, MN, KY), to compare AA digestibility in DDGS and in distillers dried grains (DDG) and to compare AA digestibility in DDGS from ethanol production (DDGSethanol) and DDGS from beverage production (DDGSbeverage). In Exp. 1, five samples of DDGSethanol were sourced from Minnesota (MN1, MN2), Illinois (ILl, 1L2), and from Kentucky (KY). In Exp. 2, six samples of DDGSethanol, 1 sample of DDG, and 1 sample of DDGSbeverage were used to compare values for apparent ileal digestibility and standardized ileal digestibility (SID) of AA between DDGSethanol and DDGSbeverage and between DDG and DDGSethanol. Results of Exp. 1 showed that the SID of Lys in DDGS from MN2 (72.8%) was greater (P < 0.01) than in DDGS from MN1 (66.8%), ILl (66.8%), and KY (65.8%) but not different from 1L2 (70.1%). Except for Leu and Glu, no differences in SID for any of the other AA were observed among the 5 sources of DDGS. In Exp. 2, the SID for Lys in DDGSbeverage was greater (P < 0.01) than in DDGSethanol (69.3 vs. 64.8%), but for CP and all other AA except His, no differences between the 2 types of DDGS were observed. The SID for most AA in DDG were greater (P < 0.05) than in DDGSethanol, which suggests that the AA in the solubles that are added to DDGS may be less digestible than the AA in DDG. In conclusion, results of these experiments confirm that the digestibility of Lys is more variable among sources of DDGS than the digestibility of other AA. However, the SID of AA among DDGS sources within a region can vary as much as among DDGS sources from different regions, and AA in DDGSbeverage may be as digestible as AA in DDGSethanol. The digestibility of AA in DDG is greater than in DDGS, which indicates that AA in the solubles have a lower digestibility than AA in DDG. [ABSTRACT FROM AUTHOR]

Selection was used to create select and control lines within 4 purebred and 3 composite cattle populations. Both lines were selected for similar direct yearling weight and maternal weaning weight EBV. Select lines were selected for lower 2-yr-old heifer calving difficulty score EBV and control lines were selected for average birth weight EBV. Select (n = 6,926) and control (n = 2,043) line calves were born from 1993 through 1999 and selection began with the 1992 mating. High replacement rates resulted in 2,188 births to select line and 598 births to control line heifers. Data used to calculate EBV came from these populations and from 15 yr of data preceding the experiment. Calving difficulty was scored from 1 (no assistance) to 7 (cesarean). Calving difficulty scores from all twins, malpresentations, and cows 3 yr old and older were eliminated. Except for the first year, when a single-trait BLUP was used, a multiple-trait BLUP was used to calculate direct and maternal EBV for calving difficulty score, birth weight, and weaning weight, and direct EBV for postweaning gain. Sires (n = 498) were selected from those born in both the preceding populations and the select and control lines. In purebred populations, some industry sires (n = 88) were introduced based on their EPD. Tests of mean select and control line EBV differences of calves born in the final 2 yr were based on population variation. Select line direct EBV were 1.06 lower for heifer calving difficulty score (P < 0.001) and 3.5 kg lower (P <0.001) for birth weight than controls. Average differences for other EBV were small and not significant. Yearling weight EBV was intentionally increased in both select and control lines of purebred populations. Angus, Hereford, Charolais, and Gelbvieh yearling weight EBV in control lines increased by 32.4, 27.2, 21.0, and 10.5 kg, respectively, from 1991 and 1992 to 1998 and 1999 compared with an average increase of 2.7 kg in composite populations. Birth weight direct EBV in purebred control lines increased by approximately 8% of yearling weight EBV increases. Selection based on a multiple-trait BLUP was able to create lines differing in calving difficulty score and birth weight EBV, but not in weaning weight and postweaning gain EBV. Differences between lines should be useful for evaluating BLUP and other traits and for identifying potential limitations of genetically decreasing calving difficulty score and birth weight. [ABSTRACT FROM AUTHOR]

Two experiments evaluated prebreeding target BW or progestin exposure for heifers developed lighter than traditional recommendations. Experiment 1 evaluated the effects of the system on heifer performance through subsequent calving and rebreeding over 3 yr. Heifers (229 kg) were assigned randomly to be developed to 55% of mature BW (299 kg) before a 45-d breeding season (intensive, TNT; n = 119) or 50% of mature BW (272 kg) before a 60-d breeding season (relaxed, RLX; n = 142). Prebreeding and pregnancy diagnosis BW were greater (P ≤ 0.006) for INT than RLX heifers. Overall pregnancy rate did not differ (88.4%; P = 0.51), but RLX heifers had later calving dates (7 d; P < 0.001) and lighter calf weaning weights (194 ± 4 vs. 199 ± 4 kg; P < 0.07) compared with INT heifers. Calf birth weight, calving difficulty, second-calf conception rates, and 2-yr-old retention rate did not differ (P> 0.15) between systems. Cost per pregnant 2- yr-old cow was less for the RLX than the INT heifer development system. Of heifers that failed to become pregnant, a greater proportion (P = 0.07) of heifers in the RLX than in the INT system were prepubertal when the breeding season began. Therefore, a second 2-yr experiment evaluated melengestrol acetate (MGA, 0.5 mg/d) as a means of hastening puberty in heifers developed to 50% of mature BW. Heifers were assigned randomly to the control (n = 103) or MGA (n = 81) treatment for 14 d and were placed with bulls 13 d later for 45 d. Prebreeding and pregnancy diagnosis BW were similar (280 and 380 kg, respectively; P> 0.10) for heifers in the control and MGA treatments. The proportion of heifers pubertal before breeding (74%), pregnancy rate (90%), calving date, calf weaning weight, and second breeding season pregnancy rate (92%) were similar (P > 0.10) between treatments. Developing heifers to 50 or 55% of mature BW resulted in similar overall pregnancy rates, and supplementing the diets of heifers developed to 50% of mature BW with MGA before breeding did not improve reproductive performance. [ABSTRACT FROM AUTHOR]

The article presents abstracts of topics related to livestock breeding and genetics which include genetic variations in chicken aggressive behavior: the role of serotonergic system, non-major histocompatibility complex effects on the outcome of Rous sarcoma virus in Arkansas Progressor and Regressor chicken lines and association between SNPs and mortality in commercial broilers: a machine learning approach.