Field Of Animal Science Research Articles

The role of an equine nutritionist in equine health, performance and wellbeing: Ideas stemming from an equine science society symposium workshop

In the United States, there is little clarity on the qualifications and availability of equine nutritionists. Currently, no regulatory body exists for formal credentialing outside of veterinary medicine. Most equine nutritionists are not veterinarians but do have advanced scientific degrees (Master of Science and/or Doctor of Philosophy) in the field of Animal Science. However, not all reporting to be equine nutritionists have formal education in the field of equine nutrition. To discuss this, a workshop was held at the 2023 Equine Science Society (ESS) meeting. The purpose of this discussion was to share ideas among equine nutrition professionals about how best to provide support for the inclusion of the specialty as part of a horse's health team, alongside the veterinarian, farrier and other equine health specialists. In human, small animal and livestock practices, the importance of nutrition as part of an overall health, production (livestock) and well-being plan has been documented. However, surveys of veterinarians, the top source of information for horse owners, reveal a lack of confidence in the area of nutrition after graduating from veterinary school and a lack of available continuing education opportunities to learn more. Further, it appears that many horse owners may unknowingly be obtaining nutrition information from unverified sources (such as the internet). The discussion included formal and informal education of equine nutritionists, as well as avenues to open lines of communication with the veterinary community to provide nutrition resources for horse owners, managers and veterinarians.

Prediction of Body Weight by Using PCA-Supported Gradient Boosting and Random Forest Algorithms in Water Buffaloes (Bubalus bubalis) Reared in South-Eastern Mexico.

This study aims to use advanced machine learning techniques supported by Principal Component Analysis (PCA) to estimate body weight (BW) in buffalos raised in southeastern Mexico and compare their performance. The first stage of the current study consists of body measurements and the process of determining the most informative variables using PCA, a dimension reduction method. This process reduces the data size by eliminating the complex structure of the model and provides a faster and more effective learning process. As a second stage, two separate prediction models were developed with Gradient Boosting and Random Forest algorithms, using the principal components obtained from the data set reduced by PCA. The performances of both models were compared using R2, RMSE and MAE metrics, and showed that the Gradient Boosting model achieved a better prediction performance with a higher R2 value and lower error rates than the Random Forest model. In conclusion, PCA-supported modeling applications can provide more reliable results, and the Gradient Boosting algorithm is superior to Random Forest in this context. The current study demonstrates the potential use of machine learning approaches in estimating body weight in water buffalos, and will support sustainable animal husbandry by contributing to decision making processes in the field of animal science.

Bibliometric Analysis for Use of Time Series in Animal Science

In this study, bibliometric analysis was applied to time series, which has been widely used in animal science studies in recent years. In the method part of the study, a bibliometric analysis was carried out for time series commonly used in animal science studies. In the study is to determine the trends in recent years in the field of animal science, by examining 3895 studies with the term "time series" in the title of the article published within the scope of SCI-Expanded between 1980 and 2023, within the scope of bibliometric analysis. Statistical evaluations were calculated using the R software belonging to the "bibliometrix" package. All data were generated bibliographically from the WoS system in plain text format. Time series has been one of the most popular research areas due to its application in many different fields such as cell biology, plant sciences, zoology, animal science, etc. There are many authors' works in the field of time series. According to the analysis, a total of 3202 studies, such as articles, journals, books, etc. by 14154 authors, were published on time series in animal science. As a result of the analysis, in the 14154 authors, only 247 studies has been single authored documents of afromentioned topic. Time series in animal science examined within the scope of author’s collaboration that there were 0.275 authors per document. This study aims to conduct bibliometric analysis to determine the importance of time series in the field of agriculture, the number of publications by year, annual publication increase, and distribution by country and number of articles by keywords. The analysis results will be an important contribution to both readers and researchers.

Bibliometric Analysis for Genome-Wide Association Studies in Animal Science

The main idea of the study is to determine the trends in recent years in the field of animal science, by examining 379 studies with the term "genome-wide association studies" in the title of the article published within the scope of SCI-Expanded between 2007 and 2021, within the scope of bibliometric analysis. In this context, the term of “Genome-Wide Association Studies” was searched in the Web of Science database in the study titles and the bibliometric data of the studies were accessed in plaintext format. The bibliometric results show that GWAS within animal science is developing steadily as a field of scientific research and is currently a highly topical issue. GWAS has been one of the most popular research areas due to its application in many different fields such as cell biology, plant sciences, zoology, animal science, etc. In the light of this information, it can be listed as an important contribution that GWAS studies with bibliometric analysis are still up-to-date and that the studies to be done will increase their contribution to animal science.

ASAS-NANP symposium: mathematical modeling in animal nutrition: limitations and potential next steps for modeling and modelers in the animal sciences.

The field of animal science, and especially animal nutrition, relies heavily on modeling to accomplish its day-to-day objectives. New data streams ("big data") and the exponential increase in computing power have allowed the appearance of "new" modeling methodologies, under the umbrella of artificial intelligence (AI). However, many of these modeling methodologies have been around for decades. According to Gartner, technological innovation follows five distinct phases: technology trigger, peak of inflated expectations, trough of disillusionment, slope of enlightenment, and plateau of productivity. The appearance of AI certainly elicited much hype within agriculture leading to overpromised plug-and-play solutions in a field heavily dependent on custom solutions. The threat of failure can become real when advertising a disruptive innovation as sustainable. This does not mean that we need to abandon AI models. What is most necessary is to demystify the field and place a lesser emphasis on the technology and more on business application. As AI becomes increasingly more powerful and applications start to diverge, new research fields are introduced, and opportunities arise to combine "old" and "new" modeling technologies into hybrids. However, sustainable application is still many years away, and companies and universities alike do well to remain at the forefront. This requires investment in hardware, software, and analytical talent. It also requires a strong connection to the outside world to test, that which does, and does not work in practice and a close view of when the field of agriculture is ready to take its next big steps. Other research fields, such as engineering and automotive, have shown that the application power of AI can be far reaching but only if a realistic view of models as whole is maintained. In this review, we share our view on the current and future limitations of modeling and potential next steps for modelers in the animal sciences. First, we discuss the inherent dependencies and limitations of modeling as a human process. Then, we highlight how models, fueled by AI, can play an enhanced sustainable role in the animal sciences ecosystem. Lastly, we provide recommendations for future animal scientists on how to support themselves, the farmers, and their field, considering the opportunities and challenges the technological innovation brings.

Assessing Intestinal Health. In Vitro and Ex vivo Gut Barrier Models of Farm Animals: Benefits and Limitations.

Animal performance is determined by the functionality and health of the gastrointestinal tract (GIT). Complex mechanisms and interactions are involved in the regulation of GIT functionality and health. The understanding of these relationships could be crucial for developing strategies to improve animal production yields. The concept of “gut health" is not well defined, but this concept has begun to play a very important role in the field of animal science. However, a clear definition of GIT health and the means by which to measure it are lacking. In vitro and ex vivo models can facilitate these studies, creating well-controlled and repeatable conditions to understand how to improve animal gut health. Over the years, several models have been developed and used to study the beneficial or pathogenic relationships between the GIT and the external environment. This review aims to describe the most commonly used animals' in vitro or ex vivo models and techniques that are useful for better understanding the intestinal health of production animals, elucidating their benefits and limitations.

Effect of De-noising by Wavelet Filtering and Data Augmentation by Borderline SMOTE on the Classification of Imbalanced Datasets of Pig Behavior

Classification of imbalanced datasets of animal behavior has been one of the top challenges in the field of animal science. An imbalanced dataset will lead many classification algorithms to being less effective and result in a higher misclassification rate for the minority classes. The aim of this study was to assess a method for addressing the problem of imbalanced datasets of pigs' behavior by using an over-sampling method, namely Borderline-SMOTE. The pigs' activity was measured using a triaxial accelerometer, which was mounted on the back of the pigs. Wavelet filtering and Borderline-SMOTE were both applied as methods to pre-process the dataset. A multilayer feed-forward neural network was trained and validated with 21 input features to classify four pig activities: lying, standing, walking, and exploring. The results showed that wavelet filtering and Borderline-SMOTE both lead to improved performance. Furthermore, Borderline-SMOTE yielded greater improvements in classification performance than an alternative method for balancing the training data, namely random under-sampling, which is commonly used in animal science research. However, the overall performance was not adequate to satisfy the research needs in this field and to address the common but urgent problem of imbalanced behavior dataset.

252 Better Preparing Animal Science Students for Education Associated Careers

Abstract An Animal Science degree prepares students for a broad range of career opportunities yet the two most discussed in the literature and assumed by society are in animal science industry or veterinary medicine. However, studies indicate that -60% of our students enter into education as a career path, yet animal science departments typically do not emphasize educational careers or provide opportunities for students to develop skills in methods relevant for animal science related teaching. To combat this lack of representation for educational career opportunities, our research university’s animal science department has acted in two ways:-Developed a laboratory teaching methods course that allows undergraduate students to serve as teaching assistants for an animal handling lab with support and supervision from the course and graduate student lab instructors-Performed a content analysis to identify the type, frequency, and way educational career paths are discussed and/or assessed in introductory animal science courses. These are the first steps in ensuring that students are as prepared for pursuit of a possible educational career at a level equal to that for industry or veterinary careers. Sustainability of animal science includes retaining students in educational careers and actively improving our educational practices within the discipline. These changes better prepare our undergraduate students to have more realistic job expectations and competence in teaching when they pursue graduate school or animal science related educational career options. The university animal science program also benefits, as the undergraduate teaching assistants improve the instructor-to-student ratio thus positively impacting safety and logistics of hands-on large animal labs while increasing one-on-one instruction time with students. These practices increase student engagement and learning. Additionally, the field of animal science will prosper from increased competence in pedagogical techniques providing a richer, more complete educational experience for our students both in and out of university settings.

Preface

On behalf of the committee, I would like to welcome the conference participants. The 2nd ICAST 2019 International Conference is a forum for bringing together leading experts to discuss various issues in the field of animal science and the environment. Various research topics and latest discoveries will be discussed in this forum. The main topics discussed are related to problems in the world of animal science and the environment such as: physiology and reproduction of livestock, nutrition and feed technology, waste management, environment and by-products of livestock, breeding, animal welfare, poultry production, socio-economics and agriculture extension.At this international conference, approximately 200 papers will be presented orally and posters (including papers from keynote speakers). The paper came from several universities and research institutions within the scope of ASEAN countries and outside ASEAN. The 2nd ICAST 2019 International Conference raised the theme “Sustainable Animal Production and Walfare in The Tropical Environment”. I would like to thank the keynote speakers and participants who have contributed their thoughts in advancing the world of animal science and the environment.In particular, I would like to thank the Government of South Sulawesi Province, the Rector of Hasanuddin University, Dean of Animal Science Faculty, Hasanuddin University, the sponsors of the activities, the committee of The 2nd ICAST 2019 and all those who have supported this conference. Without your participation, this conference will not be as successful as it is today.

Policy driven changes in animal research practices: mapping researchers\u2019 attitudes towards animal-free innovations using the Netherlands as an example

BackgroundReducing the number of animals used in experiments has become a priority for the governments of many countries. For these reductions to occur, animal-free alternatives must be made more available and, crucially, must be embraced by researchers.MethodsWe conducted an international online survey for academics in the field of animal science (N = 367) to explore researchers’ attitudes towards the implementation of animal-free innovations. Through this survey, we address three key questions. The first question is whether scientists who use animals in their research consider governmental goals for animal-free innovations achievable and whether they would support such goals. Secondly, responders were asked to rank the importance of ten roadblocks that could hamper the implementation of animal-free innovations. Finally, responders were asked whether they would migrate (either themselves or their research) if increased animal research regulations in their country of residence restricted their research.ResultsWhile nearly half (40%) of the responders support governmental goals, the majority (71%) of researchers did not consider such goals achievable in their field within the near future. In terms of roadblocks for implementation of animal-free methods, ~ 80% of the responders considered ‘reliability’ as important, making it the most highly ranked roadblock. However, all other roadblocks were reported by most responders as somewhat important, suggesting that they must also be considered when addressing animal-free innovations. Importantly, a majority reported that they would consider migration to another country in response to a restrictive animal research policy. Thus, governments must consider the risk of researchers migrating to other institutes, states or countries, leading to a ‘brain-drain’ if policies are too strict or suitable animal-free alternatives are not available.ConclusionOur findings suggest that development and implementation of animal-free innovations are hampered by multiple factors. We outline three pillars concerning education, governmental influence and data sharing, the implementation of which may help to overcome these roadblocks to animal-free innovations.

A1 and A2 Bovine Milk, the Risk of Beta-casomorphin-7 and Its Possible Effects on Human Health:(I) A1 and A2 Milk and the Risk of Beta-casomorphin-7

Milk proteins are generally composed of proteins such as casein, lactalbumin, lactoglobulin, blood serum albumin, and immunoglobulin. One of them, casein from milk proteins consists of fractions such as alpha, beta, kappa and gamma. Beta casein gene in cattle consists of 209 amino acids and contains proline amino acid (CCT) at position 67 of the amino acid sequence. The milk obtained from animals with this genotype is defined as the original A2 milk. Proline/Histidine amino acid substitution (C/A) at position 67 of the amino acid sequence results in the beta-casomorphine-7 (BCM-7) which is a naturally occurring opioid peptide from cow’s milk. By this substitution (CAT), the milk obtained from animals with genotypes (A1A1 or A1A2) is defined as the A1 milk. BCM-7 is a polypeptide consisting of seven amino acids and is produced from A1 milk during digestion of beta-casein protein. As a result, BCM-7 has harmful effects on human health. The aim of this study is to raise awareness in the field of animal science as well as to contribute to the taking of professional measures by using the literature on A1 / A2 milk and beta-casomorphine-7.

Social defeat models in animal science: What we have learned from rodent models.

Studies on stress and its impacts on animals are very important in many fields of science, including animal science, because various stresses influence animal production and animal welfare. In particular, the social stresses within animal groups have profound impact on animals, with the potential to induce abnormal behaviors and health problems. In humans, social stress induces several health problems, including psychiatric disorders. In animal stress models, social defeat models are well characterized and used in various research fields, particularly in studies concerning mental disorders. Recently, we have focused on behavior, nutrition and metabolism in rodent models of social defeat to elucidate how social stresses affect animals. In this review, recent significant progress in studies related to animal social defeat models are described. In the field of animal science, these stress models may contribute to advances in the development of functional foods and in the management of animal welfare.

William N. Garrett (1926–2016): A brief biography

The field of animal science has lost a great mentor, colleague, and inspired thinker. William N. Garrett, professor emeritus of the Department of Animal Science at the University of California, Davis, passed away at the age of 90 on September 18, 2016, surrounded by his family. Garrett was a renowned ruminant nutritionist who, along with Glen Lofgreen, developed a system based on validated energy utilization of cattle, which ultimately impacted animal feed evaluation and ration formulation worldwide. He served on the faculty at UC Davis for 32 yr during which he received many accolades for his research in nutrition and influenced the careers of many students. Garrett was a kind, modest, generous mentor with keen wit and intellect. Garrett was born June 8, 1926, in Munster, PA, and graduated from Cresson High School. Immediately after high school in June 1944, he enlisted in the US Navy. After initial training, Garrett...

The Regulation of Lipolysis in Adipose Tissue

Knowledge regarding lipid catabolism has been of great interest in the field of animal sciences. In the livestock industry, excess fat accretion in meat is costly to the producer and undesirable to the consumer. However, intramuscular fat (marbling) is desirable to enhance carcass and product quality. The manipulation of lipid content to meet the goals of animal production requires an understanding of the detailed mechanisms of lipid catabolism to help meticulously design nutritional, pharmacological, and physiological approaches to regulate fat accretion. The concept of a basic system of lipases and their co-regulators has been identified. The major lipases cleave triacylglycerol (TAG) stored in lipid droplets in a sequential manner. In adipose tissue, adipose triglyceride lipase (ATGL) performs the first and rate-limiting step of TAG breakdown through hydrolysis at the sn-1 position of TAG to release a non-esterified fatty acid (NEFA) and diacylglycerol (DAG). Subsequently, cleavage of DAG occurs via the rate-limiting enzyme hormone-sensitive lipase (HSL) for DAG catabolism, which is followed by monoglyceride lipase (MGL) for monoacylglycerol (MAG) hydrolysis. Recent identification of the co-activator (Comparative Gene Identification-58) and inhibitor [G(0)/G(1) Switch Gene 2] of ATGL have helped elucidate this important initial step of TAG breakdown, while also generating more questions. Additionally, the roles of these lipolysis-related enzymes in muscle, liver and skin tissue have also been found to be of great importance for the investigation of systemic lipolytic regulation.

Cutting-edge topics in research on animal sciences

The editors and publishers are pleased to announce the first edition of the Journal of Experimental and Applied Animal Sciences (JEAAS). We hope that our new journal will help advance the exciting field of animal sciences. The journal is particularly keen to provide a broad view of the field of animal sciences. Therefore, interdisciplinar manuscripts, which may not suit the narrow specialties of other journals, are highly welcome. The editors acknowledge that a precise definition of “animal sciences” is challenging. Here, we suggest three categories of animal sciences, with the awareness that categorization may be difficult: 1) traditional and applied animal sciences; 2) animal models and basic research; and 3) complementary in vivo research to in vitro systems. We hope that JEAAS will play a constructive role in this exciting field of research.

Mass spectrometry and animal science: Protein identification strategies and particularities of farm animal species

Proteomic approaches are gaining increasing importance in the context of all fields of animal and veterinary sciences, including physiology, productive characterization, and disease/parasite tolerance, among others. Proteomic studies mainly aim the proteome characterization of a certain organ, tissue, cell type or organism, either in a specific condition or comparing protein differential expression within two or more selected situations. Due to the high complexity of samples, usually total protein extracts, proteomics relies heavily on separation procedures, being 2D-electrophoresis and HPLC the most common, as well as on protein identification using mass spectrometry (MS) based methodologies. Despite the increasing importance of MS in the context of animal and veterinary science studies, the usefulness of such tools is still poorly perceived by the animal science community. This is primarily due to the limited knowledge on mass spectrometry by animal scientists. Additionally, confidence and success in protein identification is hindered by the lack of information in public databases for most of farm animal species and their pathogens, with the exception of cattle (Bos taurus), pig (Sus scrofa) and chicken (Gallus gallus). In this article, we will briefly summarize the main methodologies available for protein identification using mass spectrometry providing a case study of specific applications in the field of animal science. We will also address the difficulties inherent to protein identification using MS, with particular reference to experiments using animal species poorly described in public databases. Additionally, we will suggest strategies to increase the rate of successful identifications when working with farm animal species.

A new start: Journal of Animal Science and Biotechnology re-launches with BioMed Central.

A new start: Journal of Animal Science and Biotechnology re-launches with BioMed Central.

Bayesian analysis of autoregressive panel data model: application in genetic evaluation of beef cattle

The animal breeding values forecasting at futures times is a relevant technological innovation in the field of Animal Science, since its enables a previous indication of animals that will be either kept by the producer for breeding purposes or discarded. This study discusses an MCMC Bayesian methodology applied to panel data in a time series context. We consider Bayesian analysis of an autoregressive, AR(p), panel data model of order p, using an exact likelihood function, comparative analysis of prior distributions and predictive distributions of future observations. The methodology was tested by a simulation study using three priors: hierarchical Multivariate Normal-Inverse Gamma (model 1), independent Multivariate Student's t Inverse Gamma (model 2) and Jeffrey's (model 3). Comparisons by Pseudo-Bayes Factor favored model 2. The proposed methodology was applied to longitudinal data relative to Expected Progeny Difference (EPD) of beef cattle sires. The forecast efficiency was around 80%. Regarding the mean width of the EPD interval estimation (95%) in a future time, a great advantage was observed for the proposed Bayesian methodology over usual asymptotic frequentist method.

Application of Recent DNA/RNA-based Techniques in Rumen Ecology

Conventional culture-based methods of enumerating rumen microorganisms (bacteria, archaea, protozoa, and fungi) are being rapidly replaced by nucleic acid-based techniques which can be used to characterise complex microbial communities without incubation. The foundation of these techniques is 16S/18S rDNA sequence analysis which has provided a phylogenetically based classification scheme for enumeration and identification of microbial community members. While these analyses are very informative for determining the composition of the microbial community and monitoring changes in population size, they can only infer function based on these observations. The next step in functional analysis of the ecosystem is to measure how specific and, or, predominant members of the ecosystem are operating and interacting with other groups. It is also apparent that techniques which optimise the analysis of complex microbial communities rather than the detection of single organisms will need to address the issues of high throughput analysis using many primers/probes in a single sample. Nearly all the molecular ecological techniques are dependant upon the efficient extraction of high quality DNA/RNA representing the diversity of ruminal microbial communities. Recent reviews and technical manuals written on the subject of molecular microbial ecology of animals provide a broad perspective of the variety of techniques available and their potential application in the field of animal science which is beyond the scope of this treatise. This paper will focus on nucleic acid based molecular methods which have recently been developed for studying major functional groups (cellulolytic bacteria, protozoa, fungi and methanogens) of microorganisms that are important in nutritional studies, as well as, novel methods for studying microbial diversity and function from a genomics perspective.

Neural networks for animal science applications: Two case studies

Artificial neural networks have shown to be a powerful tool for system modelling in a wide range of applications. In this paper, we focus on neural network applications to intelligent data analysis in the field of animal science. Two classical applications of neural networks are proposed: time series prediction and clustering. The first task is related to the prediction of weekly milk production in goat flocks, which includes a knowledge discovery stage in order to analyse the relative relevance of the different variables. The second task is the clustering of goat flocks; it is used to analyse different livestock surveys by using self-organizing maps and the adaptive resonance theory, thus obtaining a qualitative knowledge from these surveys. Achieved results show the usefulness of neural networks in two animal science applications.