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The lack of real-life experiences, such as handling livestock at a production facility (e.g., ranch), exists for a variety of reasons such as availability, liability, time, and cost, amongst others. As more students enter undergraduate animal science programs without prior exposure to animal handling, the necessity for more hands-on, real-life experiences has increased dramatically. Complementary, educational simulation games (edugames) might provide means to overcome the lack of "hands-on" experiential learning by providing similar interactions in a virtual context. The primary goal of this study was to document the design and construction phase of a virtual cattle-handling simulation (CowSim) edugame, and to analyse preliminary survey data. An association exists between students' notion of cattle being mishandled (or not) depending on students' previous opportunity to work with animals (X[superscript 2]P value = 0.0017). Furthermore, students with previous experience handling cattle did not feel more prepared to handle cattle after playing CowSim, but students with previous experience handling cattle indicated they learned more about cattle handling after playing CowSim. After playing the CowSim game, students were, in general, optimistic about their playing experience. They perceived the CowSim game was realistic enough to increase their preparedness towards handling cattle. Our findings suggested there is heightened interest was for the use of an edugame to help visualize difficult concepts. Virtual learning tools such as the CowSim edugame are essential for advancing animal science education through the integration of virtual technology. However, improvements are warranted in the CowSim to capture more realistic scenarios given the complexity of the simulation game.

Simple Summary: In this study, we wanted to find the best way to predict the overall chemical composition of Boer × Saanen male kids by evaluating different parts of their bodies. We conducted two experiments where goats were fed different intake levels and slaughtered at various weights. We used various body parts such as the neck, ribs, leg, shoulder, loin, hide, head + feet, and organs to see which ones best estimate the whole body composition regarding nutrients such as fat, protein, and minerals. We found that the neck, loin, and 9–11th ribs could precisely predict the body composition. However, using the loin or 9–11th ribs to do this can lower the price one can obtain from selling the meat because they are valuable parts of the carcass. Our study suggests that the neck can be used as effectively as the 9–11th ribs to estimate the chemical body composition. This finding is useful for farmers, nutritionists, and meat processors as it helps them choose a cost-effective method for evaluating body composition without sacrificing valuable parts of the goat carcass. Two experiments were conducted to determine which part of the empty body of Boer × Saanen intact male kids can be used to predict the chemical composition of the whole body. In the first experiment, kids were fed ad libitum and slaughtered at 5, 10, and 15 kg body weight (BW). Eighteen animals were group-fed at three intake levels (ad libitum or restricted to 30% and 60% of the ad libitum level). When the ad libitum animal in the group reached 15 kg BW, all animals in the group were slaughtered. In the second experiment, kids were fed ad libitum and slaughtered at 15, 20, and 25 kg BW. Twenty-one animals were group-fed at three intake levels and slaughtered when the ad libitum animal within the group reached 25 kg BW. Analyzed body parts included head + feet, hide, organs, neck, shoulder, ribs, loin, leg, 9–11th ribs, and half carcass. Principal component and cluster analyses showed that the neck, 9–11th ribs, and loin had the highest frequency of grouping with the empty body. These body parts were used to develop prediction models for estimating body composition. The neck, loin, and 9–11th ribs accurately and precisely predicted the dry matter, ash, fat, protein, and energy body composition of goats, with most models also incorporating BW as a predictor variable. The equations showed root mean squared error (RMSE) lower than 13.5% and a concordance correlation coefficient (CCC) greater than 0.84. Fat and protein concentrations in the loin and neck were also reliable predictors of empty body energy composition (RMSE = 2.9% of mean and concordance correlation coefficient = 0.93). Removing the loin and 9–11th ribs could reduce the carcass retail price. Using the neck to estimate body composition in growing Boer × Saanen goats provides a valuable alternative for nutrition studies, given its low commercial value. [ABSTRACT FROM AUTHOR]

We used systems thinking (ST) to identify the critical components of beef cattle production through the lens of ecosystem services (ES), offering a holistic approach to address its adverse externalities. We identified eight critical feedback loops in beef production systems: (i) grazing and soil health, (ii) manure management and soil fertility, (iii) feed efficiency and meat production, (iv) water use and soil moisture, (v) cultural services and community engagement, (vi) energy use, (vii) carbon sequestration and climate regulation, and (viii) environmental impact. Our analysis reveals how these interconnected loops influence each other, demonstrating the complex nature of beef production systems. The dynamic hypothesis identified through the loops indicated that improved grazing and manure management practices enhance soil health, leading to better vegetation growth and cattle nutrition, which, in turn, have a positive impact on economic returns to producers and society, all of which encourage the continuation of interlinked beef and ecosystem stewardship practices. The management of beef production ES using ST might help cattle systems across the globe to contribute to 9 of the 17 different United Nations' Sustainable Development Goals, including the "zero hunger" and "climate action" goals. We discussed the evaluation framework for agrifood systems developed by the economics of ecosystems and biodiversity to illustrate how ST in beef cattle systems could be harnessed to simultaneously achieve the intended environmental, economic, social, and health impacts of beef cattle systems. Our analysis of the literature for modeling and empirical case studies indicates that ST can reveal hidden feedback loops and interactions overlooked by traditional practices, leading to more sustainable beef cattle production outcomes. ST offers a robust framework for enhancing ES in beef cattle production by recognizing the interconnectedness of ecological and agricultural systems, enabling policymakers and managers to develop more effective and sustainable strategies that ensure the long-term health and resilience of humans and ES. [ABSTRACT FROM AUTHOR]

Simple Summary: Accurate and precise predictions of microbial crude protein (MCP) synthesis are crucial to predicting the supply of metabolizable protein in cattle. Inaccurate estimates of MCP can lead to over- or underfeeding of protein in beef cattle diets, which can have important animal performance and economic consequences. Extant MCP prediction equations are generally based on the intake of energy (e.g., total digestible nutrients (TDN) or digestible energy) and protein. We developed new equations based on the intake of organic matter, which yielded similar fit statistics to the extant equations for observed vs. predicted values, but the precision of all MCP predictions was less than desired, with errors averaging more than 28% of the observed mean. A simple approach of calculating MCP as 10% of the TDN intake was as effective as more complex equations. To move forward and improve the accuracy and precision of MCP prediction equations, research is needed to develop consistent and more precise techniques to measure MCP synthesis in cattle that will yield reliable estimates across a wide range of diets and production situations. Meta-omics tools might be a useful component of these new methods, but additional research is needed. Predictions of microbial crude protein (MCP) synthesis for beef cattle generally rely on empirical regression equations, with intakes of energy and protein as key variables. Using a database from published literature, we developed new equations based on the intake of organic matter (OM) and intakes or concentrations of crude protein (CP) and neutral detergent fiber (NDF). We compared these new equations to several extant equations based on intakes of total digestible nutrients (TDN) and CP. Regression fit statistics were evaluated using both resampling and sampling from a simulated multivariate normal population. Newly developed equations yielded similar fit statistics to extant equations, but the root mean square error of prediction averaged 155 g (28.7% of the mean MCP of 540.7 g/d) across all equations, indicating considerable variation in predictions. A simple approach of calculating MCP as 10% of the TDN intake yielded MCP estimates and fit statistics that were similar to more complicated equations. Adding a classification code to account for unique dietary characteristics did not have significant effects. Because MCP synthesis is measured indirectly, most often using surgically altered animals, literature estimates are relatively few and highly variable. A random sample of individual studies from our literature database indicated a standard deviation for MCP synthesis that averaged 19.1% of the observed mean, likely contributing to imprecision in the MCP predictions. Research to develop additional MCP estimates across various diets and production situations is needed, with a focus on developing consistent and reliable methodologies for MCP measurements. The use of new meta-omics tools might improve the accuracy and precision of MCP predictions, but further research will be needed to assess the utility of such tools. [ABSTRACT FROM AUTHOR]

This review delves into the intricate realm of ruminal microbes, shedding light on their complexity beyond previously recognized dimensions. Existing publications have probed the essential facets of these microorganisms on a finer scale than previously acknowledged. Mathematical models have emerged to simulate the behavior of approximately 200 distinct bacterial species, 25 genera of ciliate protozoa, and five genera of anaerobic fungi, constituting about 10% of the total viable bacteria in the rumen. However, the expansive diversity and density of rumen microbes challenge the complete characterization of species or genera in relation to substrates or end products. Consequently, continuous revision and re-engineering of mathematical models become imperative. In the context of ruminants, prevalent models often categorize bacteria into fiber-fermenting and nonfiber-fermenting groups. An additional subgroup featuring hyper-ammoniaproducing bacteria has been proposed, but its explicit integration into nutrition models remains unexplored. Furthermore, incorporating a more mechanistic evaluation of protozoa and fungal growth may be warranted to improve nutrition models. The time horizon and intervals at which models are constructed present another critical consideration, with feed efficiency variations among ruminants believed to be closely tied to differences in the ruminal microbiota. Addressing immediate concerns, this review underscores the need for a comprehensive exploration of factors influencing microbial growth in the rumen. Several indices have been suggested and adopted to predict microbial efficiencies, but they may provide simplification for practical application. Thus, a mechanistic approach should be considered to remove dependencies between estimates and improve predictive accuracy and precision. While artificial intelligence holds promise in elucidating gaps within empirical and mechanistic models, the generation of accurate, vetted datasets is paramount. Furthermore, this review posits that factors such as recycled nitrogen, endotoxins, and microbial population dynamics (i.e., cross-feeding and competition) may be limiting our understanding of microbial growth, suggesting the necessity of modeling these intricacies concurrently to achieve a more nuanced comprehension. This multifaceted approach aims to propel the understanding of ruminal microbial dynamics into new frontiers, paving the way for more informed and effective modeling in the future. [ABSTRACT FROM AUTHOR]

Considering the growing accessibility of dried distillers grains with solubles (DDGS) in Brazil, coupled with the limited research examining its integration into conventional confinement diets in the southeast region, comprising ingredients such as flint corn, citrus pulp, and whole cottonseed, there is a clear imperative for conducting studies to deter- mine optimal inclusion levels of this product in such diets. The objective of the study was to compare the performance (experiment 1) and metabolism (experiment 2) of Nellore bulls finished with diets containing 0, 10, 20, 30, or 40% DDGS (% DM) in total replacement of whole cottonseed and partial replacement of ground flint corn and citrus pulp. In experiment 1, Nellore bulls [n = 368; body weight (BW) = 420 ± 30 kg] were used, allocated in 60 experimental pens for 125 d (n = 12 pens per treatment), evaluating variables such as dry matter intake, average daily gain (ADG), feed efficiency, observed net energy (NE) for maintenance and gain, and carcass characteristics. In experiment 2, rumen-cannulated Nellore bulls (n = 30; BW = 503 ± 46) were kept in individual pens for 21 d (n = 6 animals per treatment), evaluating ruminal parameters (proportion of short-chain fatty acids, ammonia concentration, ruminal pH) and apparent digestibility of nutrients in the total tract. The experimental design adopted was randomized blocks, and the data were analyzed using R v. 4.3.1 (R Core Team, 2023). Linear increases were observed in carcass adjusted final BW (P = 0.013), carcass adjusted ADG (P = 0.024), carcass adjusted feed efficiency (P = 0.0003), hot carcass weight (P = 0.0004), and dressing percentage (P < 0.0001) with the incremental inclusion of DDGS in the diets (Table 1). For every 10-percentage unit inclusion in these type of diets, hot carcass weight is increased by 2.56 kg. Additionally, the inclusion of DDGS resulted in linear increases in observed NE for maintenance (P = 0.001) and NE for gain (P = 0.001), calculated according to Zinn and Shen (1998). Digestibility out- comes, determined through the difference of nutrients present in the consumed diet and in the feces, exhibited linearly decreasing effects with the escalating inclusion of DDGS for dry matter (P = 0.004), organic matter (P = 0.004), neutral detergent fiber (P = 0.01), acid detergent fiber (P = 0.04), and total digestible nutrients (P = 0.004). We also observed linear increases for isobutyrate (P = 0.004) and isovalerate (P = 0.002) as the DDGS level in the diet increased. The 40% DDGS diet exhibited 0.6 mmol/100 mol and 0.7 mmol/100 mol more of isobutyrate and isovalerate, respectively, compared with the 0% DDGS diet. In summary, a high inclusion of DDGS emerges as a viable alternative in the nutrition of Bos indicus cattle fed diets containing ground flint corn and citrus pulp, manifesting significant improvements in performance and carcass quality. [ABSTRACT FROM AUTHOR]

The inclusion of the coproduct dry distil- lers grains plus soluble (DDGS) in the diet of finishing cattle can lead to changes in the nutritional profile of the diets, causing an increase in protein content and a reduction in starch. It is necessary to understand how changes in rumen substrates affect rumen metabolic activity, acids, and enteric methane (CH4) production. Five treatments were used, considering levels of DDGS inclusion in the dry matter (DM) of 1) 0 g/kg of DDGS, 2) 150 g/kg of DDGS, 3) 300 g/kg of DDGS, 4) 450 g/kg DDGS, or 5) 600 g/kg DDGS in finishing diets. The metabolism experiment was conducted with rumen-cannulated Nellore bulls (n = 20) with initial body weight (BW) of 401.8 ± 27.0 kg. The production of short-chain fatty acids (SCFA) and CH4 were determined using the ex-situ ruminal fermentation technique. Rumen content was manually collected from 0, 4, 8 and 12 h post-feeding. The liquid and solid fractions of rumen content were used in four 50 mL penicillin-type flasks per animal. Of the four flasks prepared, two are called “blank” and inactivated in boiling water to stop fermentation, and the other two (microrumen) are incubated in a thermostatic bath, simulating the conditions existing in the rumen of animals (presence of microorganisms, anaerobes, temperature of 39ºC, natural animal saliva, physiological pH) for 30 min. After 30 min, incubated flasks were also inactivated in boiling water to stop fermentation. Subsequently, measurements of the final products of rumen fermentation (SCFA and CH4) were carried out in each bottle. Total rumen emptying was performed to determine the rumen pool of DM. The data will be analyzed in the SAS software, the mean of the treatments will be compared using test of mean and orthogonal contrasts. The declared significance is P ≤ 0.05. The inclusion or levels of DDGS did not affect CH4 production of gּ·kg DM-1ּ·d-1ּ and gּ·kg DM-1ּ d-1ּ (P > 0.05). There was an effect of the treatments on the production of propionate (gּ·kg DM-1ּ d-1ּ; P = 0.0448), with a decreasing linear effect (P = 0.0087) with the increase in the inclusion of DDGS in diet (0; 150; 300; 450; 600 g/kg of DDGS; means 137.20; 160.32; 117.60; 87.09; 91.52 gּ·kg DM-1ּ d-1ּ propionate, respectively). There was no effect of DDGS levels on the production of Acetate, Butyrate, or total SCFAs (gּ·kg DM-1ּ d-1ּ). In summary, DDGS inclusion affects rumen metabolic activity, decreasing propionate production, but does not affect the production of other SCFAs nor CH4 production. [ABSTRACT FROM AUTHOR]

has been studied as a soil amendment for the storage of stable carbon in the soil, contributing to carbon capture and mitigation of greenhouse gas emissions. There may be potential for biochar use as a feed additive to reduce enteric methane (CH4 ) emissions from growing beef cattle, but it may be dependent on several factors, including biomass source, production methodology, biochar particle size, and several others. Thus, our objective was to determine the effects of 3 different biochars and their level of inclusion on in vitro gas production dynamics of bermudagrass (Cynodon dactylon) hay. Biochars included yellow pine wood (W, Waste to Energy Inc., Slocomb, AL), yellow pine wood modified with calcium hydroxide (CW), and dairy cattle manure (M, Ecochar, Heehugowaard, Netherlands). Air-dried bermudagrass hay with or without biochars was incubated for 48 h with fresh rumen inoculum collected from 4 ruminally cannulated steers. Biochars were investigated at 3 inclusion levels (IL; IL.5 = 0.5%, IL1 = 1.0%, and IL2 = 2.0% of DM). Four incubations were performed. Incubations were performed in an unbalanced, incomplete randomized block design as inclusion levels differed among incubations, with IL.5 only included in the first two incubations (Group1) and IL2 only included in the last two incubations (Group2), but IL1 was included in all four incubations, and it was used to scale the IL.5 and IL2 variables linearly. Enumeration of CH4 production was performed for all samples. Statistical analyses were performed using PROC GLIMMIX of SAS version 9.4 (SAS Institute Inc., Cary, NC). Data were evaluated by group, with biochar, IL, and biochar × IL included in the model, and incubation included as a random variable. There were no effects of biochar, IL, or biochar × IL for either group on any of the fermentation dynamics (P ≥ 0.05), including total gas production, fractional rate of gas production, and lag time before initiation of gas production, for either the exponential or log 2-pool functions. Additionally, there were no differences in grams of CH4 production (P ≥ 0.12) for either group. To compare biochars at all IL, relative CH4 production was explored after adjusting values for IL1 and IL2 in the last two incubations based on the difference in CH4 produced at IL1 in the first two incubations. In terms of relative CH4 production, the M biochar produced approximately 16 and 28% less CH4 than W and CW, respectively, at IL1. Our results indicate that M biochar may allow for reduced CH4 production from beef cattle, but several factors, including biomass source, production methodology, and particle size, should be considered to understand the differences better. Ultimately, further research is warranted to evaluate biochar in greater depth as a feed additive for growing beef cattle. [ABSTRACT FROM AUTHOR]

Integrating tannin extracts (TE) into the diet of growing and finishing beef cattle has shown promise in optimizing protein utilization while potentially mitigating methane emissions. Despite these potential benefits, there is a notable gap in a comprehensive analysis of the influence of TE on growth rate. This study addressed this gap by collecting data on the supplementation of a blend of condensed (from Schinopsis spp.) and hydrolyzable (from Castanea spp.) tannins, which has about 70% total tannins, and its impact on critical metrics, such as average daily gain (ADG, kg/d), dry matter intake (DMI, kg/d), and feed efficiency ratio (FER, g/kg). Our objective was to conduct meta-regression analyses to understand better the nuanced effects of condensed tannin supplementation on the overall performance of beef cattle during the critical stages of growth and finishing. The dataset was constructed by collecting published studies that reported in vivo experimental data on growing and finishing beef cattle supplemented with different levels of TE. It contained 132 observations from 35 publications. The meta-analysis was conducted by linear regression with a mixed-effects model fitted by the restricted maximum likelihood method using the nlme package of R software (ver. 4.3.1). Studies were assumed as random variables, and their interaction with the intercept and slope were included in the regression. The number of animals per treatment was used as a study-specific weight. Studies accounted for 32%, 35%, or 27% of the total variance when regressing ADG, DMI, or FER, respectively, on TE (% DM). After adjusting for random effects, the ADG increased (P < 0.001) with increasing levels of dietary TE (P < 0.001): 1.344 (± 0.0071) + 0.240 (±0.0298) × TE (n = 99, r2 = 0.40). It was observed that as the dietary TE level increased, its impact on the ADG tended to decrease from 0.33 kg d-1 % TE-1 when fed up to 0.5% TE to 0.24 kg d-1 % TE-1 when fed up to 1.5% TE, suggesting a possible nonlinear relationship between these two variables. Similarly, DMI decreased slightly (P < 0.001) at 0.61 kg/d/% TE, but with a lower precision (n = 115, r² = 0.14). Consequently, FER increased (P < 0.001) at 17 kg d-1 % TE-1 (n = 93, r² = 0.34). Initial findings suggest that incorporating TE into the diet of growing and finishing cattle, up to a concentration of 0.5% DM, positively influences the growth rate and enhances FER while minimally affecting DMI. Subsequent research endeavors should delve into a more intricate examination of optimal TE inclusion levels and explore additional performance indicators for a comprehensive understanding of its impact. [ABSTRACT FROM AUTHOR]

Understanding beef cattle enteric emissions on extensive western U.S. rangeland systems is critical for implementing sustainable grazing practices that reduce greenhouse gas (GHG) emissions. These practices must also improve livestock and plant productivity and climate resiliency while maintaining or reducing production costs. However, enteric emissions of grazing cattle under different stocking rates and grazing management strategies are largely unknown for western U.S. rangelands. Thus, our objective was to evaluate the differences in enteric emissions of stocker steers grazing native rangeland. Yearling Angus steers (n = 127) were stratified by initial body weight (BW) to six groups, then randomly assigned to one of six pastures grazed from June to September 2023 at the South Dakota State University Cottonwood Field Station (Cottonwood, SD) as part of a long-term stocking rate trial (80+ yr). Each pasture was equipped with a GreenFeed (C-Lock Inc, Rapid City, SD) pasture system to measure individual animal CH4 and CO2 emissions for continuous grazing (CG) and rotational grazing (RG) strategies in three stocking rates (Light, Moderate, and Heavy, 0.32, 0.40, and 0.72 animal unit months, respectively) in a 2 x 3 factorial design. Differences in enteric emissions among stocking rate and grazing strategy were analyzed using a linear mixed effects model in R, using the lme4 package, with animal as a random effect, and a post-hoc contrast among treatments was assessed using the lsmeans package. Steer initial and final BW were similar (P > 0.05) among treatments. For CH4 emissions, there was a significant interaction between stocking rate and grazing strategy (P < 0.05). Specifically, CH4 emissions for moderate-RG (195 ± 4.3 g/d) were less than those from heavy-CG (221 ± 4.5 g/d) and light-RG (221 ± 4.7 g/d) over the study period (P < 0.05). For CO2 emissions, light-CG steers respired greater CO2 emissions (6892 ± 101 g/d) than heavy-RG (6398 ± 107 g/d; P < 0.05). All other treatment lsmeans were similar (P > 0.05) and intermediate to these treatment effects. The assessment of GHG emission values for cattle grazing native rangeland is essential for informing climate mitigation strategies, improving animal efficiency, and understanding changes in GHG emissions over production phases and across animal classes. [ABSTRACT FROM AUTHOR]