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Measurement of nutrient digestibility is a key pillar in estimating the value of feeds for livestock. Conditions are not always amendable to estimating feed digestibility through total collection methods, and as a result digestibility markers are frequently employed. The first “Digestibility markers” were reported in the early 1900s where colored glass beads were used to estimate the flow of digesta through the digestive tract. Subsequently, a myriad of digestibility markers has been assessed with the internal markers; acid insoluble ash, acid detergent lignin, indigestible neutral detergent fiber and n-alkanes and the external markers titanium dioxide and chromic oxide being the most common. Chromic oxide (Cr2 O3) was first proposed as a digestibility maker in 1918 and continues to be widely used in modern day metabolism, confined performance and grazing livestock experiments. It was the demand to use chromic acid as a digestibility marker that led Terry and Mira Fenton to publish the article “An improved procedure for the determination of chromic oxide in feed and feces” in the Canadian Journal of Animal Science in 1979. This became the most cited article in the history of the journal with over 800 citations. The procedure eliminated the use of nitric acid in a pre-digestion step and ashing reduced the organic matter content, making it less likely that perchloric acid would be converted to anhydrous perchloric acid which poses an explosive hazard. The procedure continues to be widely used to measure Cr2 O3 as a digestibility marker and has made a significant contribution to our assessment of the value of a wide range of feeds for Canadian livestock. [ABSTRACT FROM AUTHOR]

Graduate education is an important aspect of the life of most academic scientists and a serious responsibility because it comes with the obligation to help students achieve their career and life goals. It can also be very fulfilling for the graduate mentor in terms of personal satisfaction and advancement of the research program. Learning to be a good major professor is an active process that depends on developing a formal framework of education and modifying that framework for each student based on past experiences and experimentation, advice from colleagues, and the individual personality of the student. Perhaps most important is for the graduate mentor to buy into the success and well-being of the student. Among the characteristics that a major professor could seek to instill in his or her students are critical and independent thinking, self-confidence, a thick skin, teamwork, laboratory skills and understanding, and the ability for hard work. Work to make science joyful by celebrating accomplishments, creating a fun environment in the lab, and stressing the societal value of science as compared to personal rewards or ambition. [ABSTRACT FROM AUTHOR]

A renewed interest in data analytics and decision support systems in developing automated computer systems is facilitating the emergence of hybrid intelligent systems by combining artificial intelligence (AI) algorithms with classical modeling paradigms such as mechanistic modeling (HIMM) and agent-based models (iABM). Data analytics have evolved remarkably, and the scientific community may not yet fully grasp the power and limitations of some tools. Existing statistical assumptions might need to be re-assessed to provide a more thorough competitive advantage in animal production systems towards sustainability. This paper discussed the evolution of data analytics from a competitive advantage perspective within academia and illustrated the combination of different advanced technological systems in developing HIMM. The progress of analytical tools was divided into three stages: collect and respond, predict and prescribe, and smart learning and policy making, depending on the level of their sophistication (simple to complicated analysis). The collect and respond stage is responsible for ensuring the data is correct and free of influential data points, and it represents the data and information phases for which data are cataloged and organized. The predict and prescribe stage results in gained knowledge from the data and comprises most predictive modeling paradigms, and optimization and risk assessment tools are used to prescribe future decision-making opportunities. The third stage aims to apply the information obtained in the previous stages to foment knowledge and use it for rational decisions. This stage represents the pinnacle of acquired knowledge that leads to wisdom, and AI technology is intrinsic. Although still incipient, HIMM and iABM form the forthcoming stage of competitive advantage. HIMM may not increase our ability to understand the underlying mechanisms controlling the outcomes of a system, but it may increase the predictive ability of existing models by helping the analyst explain more of the data variation. The scientific community still has some issues to be resolved, including the lack of transparency and reporting of AI that might limit code reproducibility. It might be prudent for the scientific community to avoid the shiny object syndrome (i.e. AI) and look beyond the current knowledge to understand the mechanisms that might improve productivity and efficiency to lead agriculture towards sustainable and responsible achievements. [ABSTRACT FROM AUTHOR]

The objective of this paper is to report observations from a 10-week summer training program on Data Management in Animal and Plant Sciences. A total of six undergraduate students from three universities in the Texas A&M University System [Texas A&M University (TAMU)-College Station, TAMUKingsville, and TAMU-Corpus Christi] representing disciplines of Animal Science, Plant Science, and Computer Science learned handling and interpretation of sensor-based data derived from both animal sensors and UAV images of plant fields. Students attended weekly training sessions on data collection, management, processing, and visualization software including ArcGIS, MySQL and power BI. In addition, students also worked as a team and developed a database project and gave an oral presentation on their team project. On the pretraining survey, two students indicated that they had a background in animal science, two students indicated a background in plant science, one student in computer science, and one student with experience in spatial data. To begin with, the students had a mean score of 4.3 (range 0-8; on a scale of 0-10) for knowledge of data management in agriculture. One third of the students indicated that they did not have data handling experience, and one half of the students had some data analysis experience whereas one student indicated partial experience of working with data. In general, students indicated that they were very satisfied with the internship experience. On a scale of 0-10, the mean satisfaction score was 8.75 (range 7.5-10). Students indicated that they were more confident to work with and talk about data from animal systems (mean 8.5; range 7-10) and plant systems (mean = 8.4; range = 7-10). All students agreed that they learned at least one new concept related to animal and plant data ecosystems. Students indicated that the program was a good start for understanding the overall data architecture, indicated progress on data handling and thought helpful to understand opportunities in agriculture. All students agreed that their understanding of data management in agriculture changed significantly because of the course. Consequently, four students indicated that they were interested in career opportunities related to data in agriculture whereas two students indicated their interest in application of the developed tools for the on-farm use. When evaluating effect of the cross disciplinary training, students agreed that the training was helpful in learning concepts outside of their own discipline with the mean score 9.4(range 8-10) on a scale of 0-10. All students indicated that they learned team management skills and skills working with people that are different from their own. Students suggested improvement on the communications, prerecorded videos, in-person meetings, weekly reporting reviews in the future iterations for students to benefit more from the program. [ABSTRACT FROM AUTHOR]

The scientific publication system should evolve into practices that enhance free dissemination and full access to research findings. At the same time, it should ensure reproducibility and transparency and safeguard scientific integrity from the detrimental effects of the current "publish or perish" culture. The objective of this contribution is to introduce the Peer Community In (PCI) Animal Science initiative (https://animsci.peercommunityin.org/), which represents an alternative to the current publication system under the umbrella of the "Peer Community In" project (https://peercommunityin.org/). PCI Animal Science is an international community of researchers working in animal science and related areas and it promotes open science and research transparency. Although PCI Animal Science is not a scientific journal, it operates similarly with editors (here: recommenders) and reviewers. Currently, the PCI Animal Science community has 64 recommenders from 20 countries. PCI Animal Science is a non-profit initiative, run and managed by researchers. The PCI Animal Science community performs, at no cost, rigorous open reviews of preprints that have been deposited on repositories such as bioRxiv and Zenodo from a wide range of research areas related to animal science. Based on independent reviews, a recommender decides whether a paper is recommended or not. Recommended preprints are peer-reviewed and citable stand-alone articles of high scientific value that do not need publication in traditional journals. However, if the authors wish, they can also publish their recommended preprint in the Diamond Open Access Peer Community Journal (https://peercommunityjournal.org/section/animsci/) at no cost. Authors can also submit their recommended manuscript to PCI-friendly journals (i.e., journals that consider the PCI evaluation in their own review processes) or to other journals. This contribution shows the workflow of the evaluation of manuscripts by PCI Animal Science and the advantages of adopting this new publishing model. [ABSTRACT FROM AUTHOR]

Some popular press articles and social media discussions continue to cite the erroneous data presented in the "Livestock's Long Shadow" publication (FAO, 2006). While this data has subsequently been shown to be incorrect (Pitesky et al, 2009), on-going discussions about the high level of impact of livestock on global GHG emissions continue to be shared as fact nearly 15 years later. There is inherent complexity in studying the biology of livestock for meat and milk production. Efforts to make this complexity more understandable can lead to incorrect assumptions and create an unfavorable and incorrect view of dairy and livestock production for the general public. An unfavorable image of animal production creates added challenge for dairy and livestock producers. If the general public is to believe information about the environmental impact of livestock production, it is critical that that information is both accurate and easily understood. The following paper that highlights sustainable animal science and practices by Capper and Cady (2020) provides a review using modeling techniques for more recent updates (2007–2017), GHG emissions and overall impact of dairy production on environmental sustainability. Additionally, the contribution of ruminants to overall GHG emissions has also been more recently been summarized by Mitloehner (2018.) [ABSTRACT FROM AUTHOR]

This article provides a science-based, data-driven perspective on the relevance of the beef herd in the U.S. to our society and greenhouse gas (GHG) contribution to climate change. Cattle operations are subject to criticism for their environmental burden, often based on incomplete information disseminated about their social, economic, nutritional, and ecological benefits and detriments. The 2019 data published by the U.S. Environmental Protection Agency reported that U.S. beef cattle emitted 22.6% of the total agricultural emissions, representing about 2.2% of the total anthropogenic emissions of CO2 equivalent (CO2e). Simulations from a computer model developed to address global energy and climate challenges, set to use extreme improvements in livestock and crop production systems, indicated a potential reduction in global CO2e emissions of 4.6% but without significant enhancement in the temperature change by 2030. There are many natural and anthropogenic sources of CH4 emissions. Contrary to the increased contribution of peatlands and water reservoirs to atmospheric CO2e, the steady decrease in the U.S. cattle population is estimated to have reduced its methane (CH4) emissions by about 30% from 1975 to 2021. This CH4 emission deacceleration of 2.46 Mt CO2 e/yr2 might be even more significant than reported. Many opportunities exist to mitigate CH4 emissions of beef production, leading to a realistic prospect of a 5% to 15% reduction in the short term after considering the overlapping impacts of combined strategies. Reduction strategies include feeding synthetic chemicals that inactivate the methyl-coenzyme M reductase (the enzyme that catalyzes the last step of methanogenesis in the rumen), red seaweed or algae extracts, ionophore antibiotics, phytochemicals (e.g., condensed tannins and essential oils), and other nutritional manipulations. The proposed net-zero concept might not solve the global warming problem because it will only balance future anthropogenic GHG emissions with anthropogenic removals, leaving global warming on a standby state. Recommendations for consuming red meat products should consider human nutrition, health, and disease and remain independent of controversial evidence of causational relationships with perceived negative environmental impacts of beef production that are not based on scientific data. [ABSTRACT FROM AUTHOR]

With most of the student attrition occurring early in undergraduate educational programs (Braunstein et al. 1997) it is necessary to interest and motivate students early on. The demographics of animal science students have shifted to students with minimal background in food producing animals. This presents a unique challenge as the current student population represents a diverse array of backgrounds and prior experiences. As a result, students enroll in undergraduate animal science programs with various expectations for their undergraduate degree and a focus primarily on careers in veterinary medicine. To engage all students, interest and motivation need to be generated. This review will use motivational frameworks as outlined by the self-determination theory, expectancy value theory, and interest, to explain the impact of the proposed solutions. Active learning classroom strategies are linked to increased knowledge compared with traditional, passive classrooms (Wells et al. 2019). Active learning shifts from a traditional teaching model to a student-centered model, which transitions instructors to facilitators of learning. This review summarizes current proposed pedagogies that have been researched in animal science classrooms such as experiential learning, flipped classrooms, hands-on animal experience, undergraduate research experiences, mentorship opportunities, capstone experiences, service-learning experiences, team-based learning, and cooperative learning. The limitations of these proposed pedagogies and the future research needed are also discussed. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Microbiome studies in animal science using 16S rRNA gene sequencing have become increasingly common in recent years as sequencing costs continue to fall and bioinformatic tools become more powerful and user-friendly. The combination of molecular biology, microbiology, microbial ecology, computer science, and bioinformatics—in addition to the traditional considerations when conducting an animal science study—makes microbiome studies sometimes intimidating due to the intersection of different fields. The objective of this review is to serve as a jumping-off point for those animal scientists less familiar with 16S rRNA gene sequencing and analyses and to bring up common issues and concerns that arise when planning an animal microbiome study from design through analysis. This review includes an overview of 16S rRNA gene sequencing, its advantages, and its limitations; experimental design considerations such as study design, sample size, sample pooling, and sample locations; wet lab considerations such as field handing, microbial cell lysis, low biomass samples, library preparation, and sequencing controls; and computational considerations such as identification of contamination, accounting for uneven sequencing depth, constructing diversity metrics, assigning taxonomy, differential abundance testing, and, finally, data availability. In addition to general considerations, we highlight some special considerations by species and sample type. [ABSTRACT FROM AUTHOR]

In this paper, we present a case study of using an online collaborative tool - Padlet® (www.padlet.com) in two sessions of a course on Animal Rights and Welfare. The animal rights and animal welfare course is divided in two sections: section A (n = 40 students) and section B (n = 42 students). Padlets act as a giant online post-it board allowing participants to post text, audio, image, GIF, video, or URL. Padlet® was used during one class in the semester in which students in both sections were asked to brainstorm on the question "What factor(s) would you consider to be able to use animals for entertainment?" with the learning objective of identifying if students recognized and were able to discuss the use of animals for entertainment. Students had five minutes to post their response to the question. Section A was in a general university classroom and students were not required to write their names on their padlet post. Section B was in a technology enabled active learning classroom and students were asked to write their names on their post. The padlets were analyzed using social-cognitive theory, with an emphasis on content and multimedia use. Observations were recorded in field notes, and student feedback and their perception of social community was collected through surveys. Additionally, the instructor's reflection was recorded on the experience of using Padlet in class. In section A, 6 of a total of 53 posts, and in section B, 17 of a total of 51 posts had multimedia such as image, video, or web URL. Further, all multimedia posts in section B were relevant to the discussion while only half the multimedia posts in section A contributed to the discussion. The use of this free media technology (Padlet®) allowed students to prime their responses simultaneously and thus encouraged discussion with more participants, some of whom do not usually respond in class. Lastly, while no statistical difference was found in student perceptions of social community (Section A = 107.88 ± 18.57, Section B = 109.91 ± 17.81; maximum 133), student feedback provides insight into differences in the overall success of the activity based on the nature of students' engagement in regular discussion, comfort with using technology in class, and availability of convenient device. [ABSTRACT FROM AUTHOR]

Beef cows using next generation sequencing and demonstrated Cytology on reproductive performance in post-partum beef cows Microbiome in beef cows associated with causal factors such. [Extracted from the article]

Graduate education in animal science prepares students to enhance the understanding of biology and to utilize this knowledge to increase animal productivity. The mentor is instrumental in the development of scientists and must be dedicated to success of students. The approach used to guide an inquisitive student into a productive researcher and educator is formulated from the experiences of the mentor. The training program that the mentor was exposed to, as well as experiences to identify activities that are successful, can result in a unique program to nurture and stimulate students. A dedication to a productive research program is essential for mentoring. Participation in research early in a graduate program is important and it helps students realize that their research can be innovative and exciting. Frequent meetings between students and mentors are essential and participation in data collection and analyses by the student and mentor are great teaching events. Students must have knowledge of the basic sciences and the discipline as well as their focused research area. A demanding and comprehensive graduate education is essential to expand the scientific development of the future generation of researchers and educators. [ABSTRACT FROM AUTHOR]

Undergraduate research involves experiential learning methods that helps animal science students gain critical thinking skills. There is high demand for these opportunities. For example, 77.9% of incoming freshmen in the Department of Animal Sciences & Industry at Kansas State University in Fall 2017 and Fall 2018 planned to conduct research sometime during their undergraduate career (422 of 542 students). Conventional, one-on-one mentoring methods in the department were only serving 1.7% of the undergraduate population (21 of 1,212 students). This creates a unique challenge of increasing the number of undergraduate research opportunities, while maintaining the impact of individualized experiential learning. One method to address this challenge is the incorporation of a course-based research program. In this model, research projects are conducted during a conventional semester during scheduled classroom hours, with project components divided into 3 sections: (1) research preparation, including compliance requirements, hypothesis testing, experimental design, and protocol development; (2) data collection; and (3) data interpretation and dissemination. Students collect data as a team, but individually develop their own research abstract and poster to maintain a high level of experiential learning. By teaching multiple sections of this course per semester and incorporating the concepts into existing laboratories, 13.5% of students in the department completed undergraduate research in the 2018–2019 academic year (162 of 1,197 students). To monitor the quality of these experiences, student critical thinking ability was assessed using the online Critical Thinking Basic Concepts & Understanding Test (Foundation for Critical Thinking, Tomales, CA). Undergraduate research experiences increased (P = 0.028) the growth in student critical thinking score, but the type of research experience did not influence assessed skills (P > 0.281). Thus, course-based undergraduate research experiences may be an option for growing the quantity and quality of undergraduate research experience in animal science. [ABSTRACT FROM AUTHOR]

A majority of animal science undergraduates have limited livestock handling experience when they come to college. To address this issue, a course based on livestock handling, safety, and welfare was implemented in the Department of Animal Science at Iowa State University. This study aimed to (i) determine whether the course was effective at improving the comfort level of a student while handling livestock and (ii) identify demographic factors that contributed to student performance in the course. The course was delivered as an 8-wk, lecture-laboratory format. Each semester, a precourse survey and precourse exam were administered during the first class period (N = 87). The survey collected self-reported demographic information, prior livestock handling experience, and comfort level by specie. The exam tested the prior knowledge of each student. At the semester conclusion, a postcourse survey and postcourse exam were given to determine whether the course was effective at improving comfort and knowledge levels of each student, respectively (N = 75). Students from farm backgrounds outscored urban students by 5.56 ± 2.96% on the precourse exam (P = 0.06). Cumulative grade point average at the time of the course (GPA) had a role in the preexam score (P = 0.003) while gender, semester, involvement in 4H (cooperative extension program) or Future Farmers of America (FFA), and high school or collegiate judging were not factors in the preexam score (P > 0.10). Background and student rank did not have an effect on the postcourse exam score (P = 0.96 and P = 0.58, respectively). As expected, GPA was significant when fit as a covariate (P < 0.001) in the postcourse exam model. Upon course completion, students reported that their comfort level while handling livestock had increased for all livestock species. The largest increases were observed with poultry (37.8% to 66.9%) and dairy (49.3% to 84.3%). Of the 75 students polled, 96% felt that the hands-on approach was beneficial at reinforcing lecture material, and 100% reported that they were more likely to voluntarily interact with livestock inside or outside of the classroom setting after course completion. In conclusion, some demographic attributes play a role in student performance at the beginning of the course, but these factors are no longer significant after completion of the course. In addition, the level of comfort with and knowledge of livestock handling, safety, and welfare all improved, which shows that the course was successful at achieving the intended learning outcomes. [ABSTRACT FROM AUTHOR]

A biography of professor Dr. (doctor) Cornelis Franciscus Maria de Lange is presented. He was born on on April 19, 1961 in De Weere, the Netherlands. It informs on education in animal science, and animal nutrition. He was married to Deirdre “Dede" Conway with four children. It also reports on Lange being as a highly prolific scientist, his manuscripts and research accomplishments.

A calendar of events for the American Society of Animal Science (ASAS) sectional and national meetings to be held in the U.S. from February to July 2017 is presented.

The American beef bulls have been neglected in terms of animal science research. Metabolomics is a respected for of science that will aid in developing hypothesis for future research in beef bulls. The objective of this study was to identify metabolites within a 65-day breeding season that were affect by breeding season duration and workload. Over a two-year period, 8 purebred Angus bulls owned and housed by the Cal Poly beef unit were surveyed using serum (collected via the coccygeal vein) and seminal fluid (collected via electroejaculation) at the beginning and end of a 65-day post-AI breeding season. Samples underwent HPLC-MS to observe metabolites within the fluids. Data were stratified for sample day and workload and compared using t-test for day and ANOVA for workload. Within serum, 8 metabolites of interest were observed. Effects included differences between workload groups in the abundance of guanosine (P = 0.01) a metabolite associated with purine metabolism. Within seminal fluid, 13 metabolites of interest were observed including Inosine, a metabolite also involved in purine metabolism and fluctuating based on workload (P = 0.05). Purine metabolism will be of interest to future research of beef bulls. [ABSTRACT FROM AUTHOR]

Over time and with enough semesters and students, student course evaluations can provide valuable information about instructor effectiveness and course organization. However, student evaluations are anonymous, and responses often lack accountability and constructive comments for improvement. The student point of view, while important, may lack perspective that faculty assessment is able to provide. Additionally, as promotion documents increasingly require more documentation of teaching effectiveness, a consistent, fair, summative peer evaluation of teaching can add breadth and depth to the assessment while strengthening the departmental curriculum. Therefore, a protocol was developed to provide guidance and continuity in the peer evaluation of teaching process. Peer evaluation of teaching includes all materials and assessments from the course as well as classroom presentation and delivery. The undergraduate teaching coordinator accepts requests from faculty who wish to have their course reviewed at the beginning of each semester and then assigns two peer reviewers. The three faculty then meet to discuss course objectives and learning outcomes. The instructor also shares their teaching philosophy for the course, and the syllabus, handouts, assignments, quizzes and exams. Some instructors also choose to add the reviewers to the learning management platform for the class. The reviewers plan to attend the class (and/or laboratory) at least two different times (not necessarily together) throughout the semester and record their observations. If at all possible, it is advised that the instructor and reviewer meet immediately after class to discuss initial thoughts, reactions and questions. Both evaluators then meet together with the instructor to visit about their evaluation and then draft a letter with their assessment. The peer evaluation document is then shared with the instructor. Informal feedback from instructors includes the fact that many faculty enjoy talking about teaching, but that these conversations are preempted by daily activities and duties unless given a specific reason. The evaluation process gives a platform to visit about pedagogy, course content and teaching techniques. Outcomes and impacts of implementation of this protocol have not only yielded improvement of classroom teaching practices (via student course evaluation improvement) and exchange of ideas, but also increased faculty relationships and collaboration. Additionally, anecdotal improvement of overall course content, especially amongst related courses or courses within a series or sequence was mentioned. A coordinated, transparent protocol that assesses not only classroom performance but course content can be an effective tool for both class delivery and instruction as well as curricular improvements. [ABSTRACT FROM AUTHOR]

It is well established that the demographics of undergraduate students entering Animal Science programs across the country are ever changing. What used to be considered a major for "farm kids" has seen a large influx of students from non-traditional, non-agricultural backgrounds. With the high demand for graduates in most areas of agriculture, this is exciting, but not without challenges. The 2105 incoming freshmen class at Iowa State University (ISU), 42% of 315 responded identified "Rural/Farm" as their background, 32% answered "Small Town/City (under 100,000 population)", and 26% indicated "Urban/City". Even "farm kids" typically have either only 4-H/FFA (showring) experience with livestock, or if they have commercial industry experience, it is usually with a single species. Therefore, it is more important than ever to include the science and husbandry associated with Animal Science throughout the curriculum and not make any assumptions on previous knowledge. Courses such as "Practicum in Safe Equine Handling and Welfare" and "Livestock Handling, Safety and Welfare" have been introduced as electives into the Iowa State University Animal Science curriculum, with a Lab Animal Science course to be started in the fall of 2016. Other courses, especially at the introductory and 200-level, have also incorporated more basic information that was previously thought to be understood prior. There are advantages to this: 1) previous assumptions of understanding may have overestimated students' background knowledge; and 2) all students receive the same, correct and updated information on topics; and 3) exposure to all species and disciplines may spark new areas of interests for all students, regardless of previous animal experience. Many animal science students (62% of 315 ISU Animal Science freshmen in 2015) have an interest in vet school. This percentage is much higher than the current demand by the veterinary industry. Therefore, exposing all Animal Science students to the wide array of career opportunities associated with the various scientific disciplines may lead to rewarding careers in fields that were previously never considered. The primary interest of the 2015 ISU Animal Science freshmen was companion animals (34%), followed by equine (19%), beef (16%), exotics (12%), swine (8%), dairy (6%), sheep (2%), goats (2%) and finally poultry (1%) at the beginning of their first semester. Anecdotal evidence and job placement would suggest that these interests change by the end of a student's college career. Exposure to new species may encourage students to explore careers in areas beyond their initial primary interest. [ABSTRACT FROM AUTHOR]

The article offers information on the two upcoming sectional meetings of the American Society of Animal Science in 2018, including the Southern Section Meeting to be held in Texas during February 3 to 6, 2018 and Midwestern Section Meeting to be held in Nebraska during March 12 to 14, 2018.