A system dynamics approach to model heat stress accumulation in dairy cows during a heatwave event.

Climate change is expected to increase the number of heat wave events, leading to prolonged exposures to severe heat stress (HS) and the corresponding adverse effects on dairy cattle productivity. Modelling dairy cattle productivity under HS conditions is complicated because it requires comprehending the complexity, non-linearity, dynamicity, and delays in animal response. In this paper, we applied the System Dynamics methodology to understand the dynamics of animal response and system delays of observed milk yield (MY) in dairy cows under HS. Data on MY and temperature-humidity index were collected from a dairy cattle farm. Model development involved: (i) articulation of the problem, identification of the feedback mechanisms, and development of the dynamic hypothesis through a causal loop diagram; (ii) formulation of the quantitative model through a stock-and-flow structure; (iii) calibration of the model parameters; and (iv) analysis of results for individual cows. The model was successively evaluated with 20 cows in the case study farm, and the relevant parameters of their HS response were quantified with calibration. According to the evaluation of the results, the proposed model structure was able to capture the effect of HS for 11 cows with high accuracy with mean absolute percent error <5%, concordance correlation coefficient >0.6, and R2 > 0.6, except for two cows (ID #13 and #20) with R2 less than 0.6, implying that the rest of the nine animals do not exhibit heat-sensitive behaviour for the defined parameter space. The presented HS model considered non-linear feedback mechanisms as an attempt to help farmers and decision makers quantify the animal response to HS, predict MY under HS conditions, and distinguish the heat-sensitive cows from heat-tolerant cows at the farm level.

Predicting microbial crude protein synthesis in cattle from intakes of dietary energy and crude protein.

Accurate predictions of microbial crude protein (MCP) synthesis are needed to predict metabolizable protein supply in ruminants. Since 1996, the National Academies of Sciences, Engineering, and Medicine series on beef cattle nutrient requirements has used the intake of total digestible nutrients (TDN) to predict ruminal MCP synthesis. Because various tabular energy values for feeds are highly correlated, our objective was to determine whether intakes of digestible energy (DE), metabolizable energy (ME), and net energy for maintenance (NEm) could be used as predictors of MCP synthesis in beef cattle. A published database of 285 treatment means from experiments that evaluated MCP synthesis was updated with 50 additional treatment mean observations. When intakes of TDN, fat-free TDN, DE, ME, NEm, dry matter, organic matter, crude protein (CP), ether extract, neutral detergent fiber, and starch were used in a stepwise regression analysis to predict MCP, only intakes of DE and CP met the P < 0.10 criterion for entry into the model. Mixed-model regression analyses were used to adjust for random intercept and slope effects of citations to evaluate intake of DE alone or in combination with CP intake as predictors of MCP synthesis, and the intakes of TDN, ME, and NEm as alternatives to DE intake. Similar precisions in predicting MCP synthesis were obtained with all measures of energy intake (CV = root mean square error [RMSE] as a percentage of the overall mean MCP varied from 9% to 9.67%), and adding CP intake to statistical models increased precision (CV ranged from 8.43% to 9.39%). Resampling analyses were used to evaluate observed vs. predicted values for the various energy intake models with or without CP intake, as well as the TDN-based equation used in the current beef cattle nutrient requirements calculations. The coefficient of determination, concordance correlation coefficient, and RMSE of prediction as a percentage of the mean averaged 0.595%, 0.730%, and 28.6% for the four measures of energy intake, with average values of 0.630%, 0.757%, and 27.4%, respectively, for equations that included CP intake. The TDN equation adopted by the 2016 beef cattle nutrient requirements system yielded similar results to newly developed equations but had a slightly greater mean bias. We concluded that any of the measures of energy intake we evaluated can be used to predict MCP synthesis by beef cattle and that adding CP intake improves model precision.

The ability to accurately and precisely predict microbial protein synthesis is crucial in predicting the supply of metabolizable protein in beef cattle. We updated a database previously used to predict microbial crude protein (CP) supply in beef cattle. Then we evaluated the utility of using total digestible nutrients (TDN) and different measures of energy intake to predict ruminal microbial protein synthesis. Using regression analyses, we found that intakes of digestible and metabolizable energy and intake of net energy for maintenance were as effective as the intake of TDN as independent variables to predict microbial protein synthesis. Adding the intake of CP to the models improved the precision of predictions, and all models performed as well or better than the regression model adopted by the 2016 nutrient requirement system for beef cattle.

Using dynamic modelling to enhance the assessment of the beef water footprint.

Current water footprint assessment methods make a meaningful assessment of livestock water consumption difficult as they are mainly static, thus poorly adaptable to understanding future water consumption and requirements. They lack the integration of fundamental ruminant nutrition and growth equations within a dynamic context that accounts for short- and long-term behaviour and time delays associated with economically significant beef-producing areas. The current study utilised the System Dynamics methodology to conceptualise a water footprint for beef cattle within a dynamic and mechanistic modelling framework. The problem of assessing the water footprint of beef cattle was articulated, and a dynamic hypothesis was formed to represent the Texas livestock water use system as the initial step in developing the Dynamic Beef Water Footprint model (DWFB). The dynamic hypothesis development resulted in three causal loop diagrams (CLD): cattle population, growth and nutrition, and the livestock water footprint, that captured the daily water footprint of beef (WFB). Simulations and sensitivity analysis from the hypothesised CLD structures indicated that the framework was able to capture the dynamic behaviour of the WFB system. These behaviours included key reinforcing and balancing feedback processes that drive the WFB. It is extremely difficult to identify policy interventions (i.e., management strategies) for complex systems, like the U.S. beef cattle system, because there are many actors (i.e., cow-calf, stocker, feedlot) and interrelated variables that have delayed effects within and across the supply chain. Identification and understanding of feedback processes driving water use over time will help to overcome policy resistance for more sustainable beef production. Thus, the causal loops identified in the current study provide a system-level insight for the drivers of the WFB within and across each major segment of the beef supply chain to address freshwater concerns more adequately. Further, the nutrient scenarios and sensitivity analysis revealed that the high versus low nutrient composition of pasture, hay, and concentrates resulted in a significant difference in the WFB (2 669 L/kg boneless beef, P < 0.05). The WFB was sensitive to changes in nutrient composition and specific water demand (m3/t) for each production phase, not only phases with high levels of concentrate feed use. As models evolve, there is potential for the DWFB to integrate precision livestock data, further improving quantification of the WFB, precision water-efficient strategies, and selection of water-efficient livestock.

Review: The prevailing mathematical modeling classifications and paradigms to support the advancement of sustainable animal production.

Mathematical modeling is typically framed as the art of reductionism of scientific knowledge into an arithmetical layout. However, most untrained people get the art of modeling wrong and end up neglecting it because modeling is not simply about writing equations and generating numbers through simulations. Models tell not only about a story; they are spoken to by the circumstances under which they are envisioned. They guide apprentice and experienced modelers to build better models by preventing known pitfalls and invalid assumptions in the virtual world and, most importantly, learn from them through simulation and identify gaps in pushing scientific knowledge further. The power of the human mind is well-documented for idealizing concepts and creating virtual reality models, and as our hypotheses grow more complicated and more complex data become available, modeling earns more noticeable footing in biological sciences. The fundamental modeling paradigms include discrete-events, dynamic systems, agent-based (AB), and system dynamics (SD). The source of knowledge is the most critical step in the model-building process regardless of the paradigm, and the necessary expertise includes (a) clear and concise mental concepts acquired through different ways that provide the fundamental structure and expected behaviors of the model and (b) numerical data necessary for statistical analysis, not for building the model. The unreasonable effectiveness of models to grow scientific learning and knowledge in sciences arise because different researchers would model the same problem differently, given their knowledge and experiential background, leading to choosing different variables and model structures. Secondly, different researchers might use different paradigms and even unalike mathematics to resolve the same problem; thus, model needs are intrinsic to their perceived assumptions and structures. Thirdly, models evolve as the scientific community knowledge accumulates and matures over time, hopefully resulting in improved modeling efforts; thus, the perfect model is fictional. Some paradigms are most appropriate for macro, high abstraction with less detailed-oriented scenarios, while others are most suitable for micro, low abstraction with higher detailed-oriented strategies. Modern hybridization aggregating artificial intelligence (AI) to mathematical models can become the next technological wave in modeling. AI can be an integral part of the SD/AB models and, before long, write the model code by itself. Success and failures in model building are more related to the ability of the researcher to interpret the data and understand the underlying principles and mechanisms to formulate the correct relationship among variables rather than profound mathematical knowledge.

Forages and pastures symposium: forage biodegradation: advances in ruminal microbial ecology.

The rumen microbial ecosystem provides ruminants a selective advantage, the ability to utilize forages, allowing them to flourish worldwide in various environments. For many years, our understanding of the ruminal microbial ecosystem was limited to understanding the microbes (usually only laboratory-amenable bacteria) grown in pure culture, meaning that much of our understanding of ruminal function remained a "black box." However, the ruminal degradation of plant cell walls is performed by a consortium of bacteria, archaea, protozoa, and fungi that produces a wide variety of carbohydrate-active enzymes (CAZymes) that are responsible for the catabolism of cellulose, hemicellulose, and pectin. The past 15 years have seen the development and implementation of numerous next-generation sequencing (NGS) approaches (e.g., pyrosequencing, Illumina, and shotgun sequencing), which have contributed significantly to a greater level of insight regarding the microbial ecology of ruminants fed a variety of forages. There has also been an increase in the utilization of liquid chromatography and mass spectrometry that revolutionized transcriptomic approaches, and further improvements in the measurement of fermentation intermediates and end products have advanced with metabolomics. These advanced NGS techniques along with other analytic approaches, such as metaproteomics, have been utilized to elucidate the specific role of microbial CAZymes in forage degradation. Other methods have provided new insights into dynamic changes in the ruminal microbial population fed different diets and how these changes impact the assortment of products presented to the host animal. As more omics-based data has accumulated on forage-fed ruminants, the sequence of events that occur during fiber colonization by the microbial consortium has become more apparent, with fungal populations and fibrolytic bacterial populations working in conjunction, as well as expanding understanding of the individual microbial contributions to degradation of plant cell walls and polysaccharide components. In the future, the ability to predict microbial population and enzymatic activity and end products will be able to support the development of dynamic predictive models of rumen forage degradation and fermentation. Consequently, it is imperative to understand the rumen's microbial population better to improve fiber degradation in ruminants and, thus, stimulate more sustainable production systems.

Forage degradation in the rumen is critical to producing ruminant animals. For many years, scientists were limited to biochemical techniques to understand how ruminal microbes degraded forage, impairing our understanding of which microbes were involved with degrading which forage components. However, we have understood that as the ruminant opened up plant cells to microbial activity, a succession of microbes was involved in colonizing and breaking fiber into increasingly smaller pieces. The recent development of sequencing techniques has allowed a more detailed understanding of changes in the microbial population of the rumen during forage degradation and the types of degradative enzymes produced by this complex microbial ecosystem. We described the enzymes involved in the degradation of specific forage components, how their end products impact the microbial population through cross-feeding interactions, and how fermentation products can impact food animal production.

Review: Harnessing extant energy and protein requirement modeling for sustainable beef production.

Numerous mathematical nutrition models have been developed in the last sixty years to predict the dietary supply and requirement of farm animals' energy and protein. Although these models, usually developed by different groups, share similar concepts and data, their calculation routines (i.e., submodels) have rarely been combined into generalized models. This lack of mixing submodels is partly because different models have different attributes, including paradigms, structural decisions, inputs/outputs, and parameterization processes that could render them incompatible for merging. Another reason is that predictability might increase due to offsetting errors that cannot be thoroughly studied. Alternatively, combining concepts might be more accessible and safer than combining models' calculation routines because concepts can be incorporated into existing models without changing the modeling structure and calculation logic, though additional inputs might be needed. Instead of developing new models, improving the merging of extant models' concepts might curtail the time and effort needed to develop models capable of evaluating aspects of sustainability. Two areas of beef production research that are needed to ensure adequate diet formulation include accurate energy requirements of grazing animals (decrease methane emissions) and efficiency of energy use (reduce carcass waste and resource use) by growing cattle. A revised model for energy expenditure of grazing animals was proposed to incorporate the energy needed for physical activity, as the British feeding system recommended, and eating and rumination (HjEer) into the total energy requirement. Unfortunately, the proposed equation can only be solved iteratively through optimization because HjEer requires metabolizable energy (ME) intake. The other revised model expanded an existing model to estimate the partial efficiency of using ME for growth (kg) from protein proportion in the retained energy by including an animal degree of maturity and average daily gain (ADG) as used in the Australian feeding system. The revised kg model uses carcass composition, and it is less dependent on dietary ME content, but still requires an accurate assessment of the degree of maturity and ADG, which in turn depends on the kg. Therefore, it needs to be solved iteratively or using one-step delayed continuous calculation (i.e., use the previous day's ADG to compute the current day's kg). We believe that generalized models developed by merging different models' concepts might improve our understanding of the relationships of existing variables that were known for their importance but not included in extant models because of the lack of proper information or confidence at that time.

Astronomical tuning of the Aptian stage and its implications for age recalibrations and paleoclimatic events.

The Aptian was characterized by dramatic tectonic, oceanographic, climatic and biotic changes and its record is punctuated by Oceanic Anoxic Events (OAEs). The timing and duration of these events are still contentious, particularly the age of the Barremian-Aptian boundary. This study presents a cyclostratigraphic evaluation of a high-resolution multiproxy dataset (δ13C, δ18O, MS and ARM) from the Poggio le Guaine core. The identification of Milankovitch-band imprints allowed us to construct a 405-kyr astronomically-tuned age model that provides new constraints for the Aptian climato-chronostratigraphic framework. Based on the astronomical tuning, we propose: (i) a timespan of ~7.2 Myr for the Aptian; (ii) a timespan of ~420 kyr for the magnetic polarity Chron M0r and an age of ~120.2 Ma for the Barremian-Aptian boundary; and (iii) new age constraints on the onset and duration of Aptian OAEs and the 'cold snap'. The new framework significantly impacts the Early Cretaceous geological timescale.

Ruminal pH and its relationship with dry matter intake, growth rate, and feed conversion ratio in commercial Australian feedlot cattle fed for 148 days.

OBJECTIVES: Measurement of ruminal pH throughout a 148-day feeding period in cattle fed commercial diets and to relate this to feed intake, growth rate and feed conversion ratio. Factors contributing to variation in rumen pH, including meal frequency, duration and weight, and, total daily intake, were also evaluated. METHODS: Forty-eight cattle were randomly allocated to two pens and 12 randomly selected from each pen had rumen pH monitoring boli inserted. Ruminal pH was measured every 10 min and feed intake was measured continually. The cattle were fed a commercial feedlot diet for 148 days and weighed into and out of the feedlot to measure growth rate and to calculate feed conversion ratio. Cattle from both pens were registered to collect individual feed intake data using the GrowSafe® feed management system. RESULTS: Mean ruminal pH decreased with days on feed. Mean daily dry matter intake was the major contributor to greater average daily gain and lower ruminal pH. Lower mean ruminal pH was associated with greater average daily gain and lower feed conversion ratio, where it remained above the threshold of 5.6. There was no association between ruminal pH and average daily gain or feed conversion ratio for mean ruminal pH below 5.6. CONCLUSIONS: Ruminal acidosis can occur at any time during the feeding period, and the risk could be greater as days on feed increase. Feedlot production outcomes are not improved by ruminal pH depression below the threshold of 5.6.

Effect of quebracho condensed tannin extract on fecal gas flux in steers.

Naturally occurring gaseous by-products of ruminant production-carbon dioxide (CO2 ), methane (CH4 ), and nitrous oxide (N2 O)-can negatively affect the environment. Along with enteric fermentation, manure on pasture is among the most significant contributors to non-CO2 emissions. Condensed tannins, a group of naturally occurring phenolic compounds, can alter the route of nutrient excretion and interact with microbes, suggesting they are a plausible feed additive for reducing excreta gas emissions. We evaluated how quebracho (Schinopsis balansae) tannin extract fed at 0, 15, 30, and 45 g kg-1 of dry matter (DM) within a roughage-based diet affected fecal gas emissions at multiple locations (College Station and Stephenville, TX) during two periods corresponding to winter and spring. During both periods, CO2 , CH4 , and N2 O fluxes were determined using the vented-static chamber methodology over 39 d, and cumulative emissions were calculated. A random coefficients model with animal nested within dietary treatment and period as the random factor was analyzed by location due to the presence of collinearity with soil parameters within periods. Daily CO2 flux was influenced by soil moisture and temperature (r = .34; P < .01), whereas CH4 and N2 O were associated with soil moisture. Cumulative gas production confirmed a dietary effect for CO2 and gross CO2 equivalent at the College Station site (P ≤ .001), demonstrating a linear reduction as quebracho inclusion increased. Variance partitioning indicated that dietary treatment and seasonal period likely influenced animal digestive and metabolic parameters. Within specific environments, quebracho supplementation may assist in reducing fecal gas emissions.

An improved algorithm for solving profit-maximizing cattle diet problems.

Feeding cattle with on-pasture supplementation or feedlot diets can increase animal efficiency and system profitability while minimizing environmental impacts. However, cattle system profit margins are relatively small and nutrient supply accounts for most of the costs. This paper introduces a nonlinear profit-maximizing diet formulation problem for beef cattle based on well-established predictive equations. Nonlinearity in predictive equations for nutrient requirements poses methodological challenges in the application of optimization techniques. In contrast to other widely used diet formulation methods, we develop a mathematical model that guarantees an exact solution for maximum profit diet formulations. Our method can efficiently solve an often-impractical nonlinear problem by solving a finite number of linear problems, that is, linear time complexity is achieved through parametric linear programming. Results show the impacts of choosing different objective functions (minimizing cost, maximizing profit and maximizing profit per daily weight gain) and how this may lead to different optimal solutions. In targeting improved ration formulation on feedlot systems, this paper demonstrates how profitability and nutritional constraints can be met as an important part of a sustainable intensification production strategy.

A multi-inverse approach for a holistic understanding of applied animal science systems.

Technological and mathematical advances have provided opportunities to investigate new approaches for the holistic quantification of complex biological systems. One objective of these approaches, including the multi-inverse deterministic approach proposed in this paper, is to deepen the understanding of biological systems through the structural development of a useful, best-fitted inverse mechanistic model. The objective of the present work was to evaluate the capacity of a deterministic approach, that is, the multi-inverse approach (MIA), to yield meaningful quantitative nutritional information. To this end, a case study addressing the effect of diet composition on sheep weight was performed using data from a previous experiment on saccharina (a sugarcane byproduct), and an inverse deterministic model (named Paracoa) was developed. The MIA successfully revealed an increase in the final weight of sheep with an increase in the percentage of corn in the diet. Although the soluble fraction also increased with increasing corn percentage, the effective nonsoluble degradation increased fourfold, indicating that the increased weight gain resulted from the nonsoluble substrate. A profile likelihood analysis showed that the potential best-fitted model had identifiable parameters, and that the parameter relationships were affected by the type of data, number of parameters and model structure. It is necessary to apply the MIA to larger and/or more complex datasets to obtain a clearer understanding of its potential.

Development of equations, based on milk intake, to predict starter feed intake of preweaned dairy calves.

There is a lack of studies that provide models or equations capable of predicting starter feed intake (SFI) for milk-fed dairy calves. Therefore, a multi-study analysis was conducted to identify variables that influence SFI, and to develop equations to predict SFI in milk-fed dairy calves up to 64 days of age. The database was composed of individual data of 176 calves from eight experiments, totaling 6426 daily observations of intake. The information collected from the studies were: birth BW (kg), SFI (kg/day), fluid milk or milk replacer intake (MI; l/day), sex (male or female), breed (Holstein or Holstein×Gyr crossbred) and age (days). Correlations between SFI and the quantitative variables MI, birth BW, metabolic birth BW, fat intake, CP intake, metabolizable energy intake, and age were calculated. Subsequently, data were graphed, and based on a visual appraisal of the pattern of the data, an exponential function was chosen. Data were evaluated using a meta-analysis approach to estimate fixed and random effects of the experiments using nonlinear mixed coefficient statistical models. A negative correlation between SFI and MI was observed (r=-0.39), but age was positively correlated with SFI (r=0.66). No effect of liquid feed source (milk or milk replacer) was observed in developing the equation. Two equations, significantly different for all parameters, were fit to predict SFI for calves that consume less than 5 (SFI5) l/day of milk or milk replacer: ${\rm SFI}_{{\,\lt\,5}} {\equals}0.1839_{{\,\pm\,0.0581}} {\times}{\rm MI}{\times}{\rm exp}^{{\left( {\left( {0.0333_{{\,\pm\,0.0021 }} {\minus}0.0040_{{\,\pm\,0.0011}} {\times}{\rm MI}} \right){\times}\left( {{\rm A}{\minus}{\rm }\left( {0.8302_{{\,\pm\,0.5092}} {\plus}6.0332_{{\,\pm\,0.3583}} {\times}{\rm MI}} \right)} \right)} \right)}} {\minus}\left( {0.12{\times}{\rm MI}} \right)$ ; ${\rm SFI}_{{\,\gt\,5}} {\equals}0.1225_{{\,\pm\,0.0005 }} {\times}{\rm MI}{\times}{\rm exp}^{{\left( {\left( {0.0217_{{\,\pm\,0.0006 }} {\minus}0.0015_{{\,\pm\,0.0001}} {\times}{\rm MI}} \right){\times}\left( {{\rm A}{\minus}\left( {3.5382_{{\,\pm\,1.3140 }} {\plus}1.9508_{{\,\pm\,0.1710}} {\times}{\rm MI}} \right)} \right)} \right)}} {\minus}\left( {0.12{\times}{\rm MI}} \right)$ where MI is the milk or milk replacer intake (l/day) and A the age (days). Cross-validation and bootstrap analyses demonstrated that these equations had high accuracy and moderate precision. In conclusion, the use of milk or milk replacer as liquid feed did not affect SFI, or development of SFI over time, which increased exponentially with calf age. Because SFI of calves receiving more than 5 l/day of milk/milk replacer had a different pattern over time than those receiving <5 l/day, separate prediction equations are recommended.

Review: Precision nutrition of ruminants: approaches, challenges and potential gains.

A plethora of sensors and information technologies with applications to the precision nutrition of herbivores have been developed and continue to be developed. The nutritional processes start outside of the animal body with the available feed (quantity and quality) and continue inside it once the feed is consumed, degraded in the gastrointestinal tract and metabolised by organs and tissues. Finally, some nutrients are wasted via urination, defecation and gaseous emissions through breathing and belching whereas remaining nutrients ensure maintenance and production. Nowadays, several processes can be monitored in real-time using new technologies, but although these provide valuable data 'as is', further gains could be obtained using this information as inputs to nutrition simulation models to predict unmeasurable variables in real-time and to forecast outcomes of interest. Data provided by sensors can create synergies with simulation models and this approach has the potential to expand current applications. In addition, data provided by sensors could be used with advanced analytical techniques such as data fusion, optimisation techniques and machine learning to improve their value for applications in precision animal nutrition. The present paper reviews technologies that can monitor different nutritional processes relevant to animal production, profitability, environmental management and welfare. We discussed the model-data fusion approach in which data provided by sensor technologies can be used as input of nutrition simulation models in near-real time to produce more accurate, certain and timely predictions. We also discuss some examples that have taken this model-data fusion approach to complement the capabilities of both models and sensor data, and provided examples such as predicting feed intake and methane emissions. Challenges with automatising the nutritional management of individual animals include monitoring and predicting of the flow of nutrients including nutrient intake, quantity and composition of body growth and milk production, gestation, maintenance and physical activities at the individual animal level. We concluded that the livestock industries are already seeing benefits from the development of sensor and information technologies, and this benefit is expected to grow exponentially soon with the integration of nutrition simulation models and techniques for big data analysis. However, this approach may need re-evaluating or performing new empirical research in both fields of animal nutrition and simulation modelling to accommodate a new type of data provided by the sensor technologies.

Consistency of feed efficiency ranking and mechanisms associated with inter-animal variation among growing calves.

This study investigated the possible mechanisms for explaining interanimal variation in efficiency of feed utilization in intact male Holstein calves. Additionally, we examined whether the feed efficiency (FE) ranking of calves (n = 26) changed due to age and/or diet quality. Calves were evaluated during three periods (P1, P2, and P3) while fed a high-quality diet (calculated mobilizable energy [ME] of 11.8 MJ/kg DM) during P1 and P3, and a low-quality diet (calculated ME of 7.7 MJ/kg DM) during P2. The study periods were 84, 119, and 127 d, respectively. Initial ages of the calves in P1, P2, and P3 were 7, 11, and 15 mo, respectively, and initial body weight (BW) were 245, 367, and 458 kg, respectively. Individual dry matter intake (DMI), average daily gain (ADG), diet digestibility, and heat production (HP) were measured in all periods. The measured FE indexes were: residual feed intake (RFI), the gain-to-feed ratio (G:F), residual gain (RG), residual gain and intake (RIG), the ratio of HP-to-ME intake (HP/MEI), and residual heat production (RHP). For statistical analysis, animals' performance data in each period, were ranked by RFI, and categorized into high-, medium-, and low-RFI groups (H-RFI, M-RFI, and L-RFI). RFI was not correlated with in vivo digestibility, age, BW, BCS, or ADG in all three periods. The L-RFI group had lowest DMI, MEI, HP, retained energy (RE), and RE/ADG. Chemical analysis of the longissimus dorsi muscle shows that the L-RFI group had a higher percentage of protein and a lower percentage of fat compared to the H-RFI group. We suggested that the main mechanism separating L- from H-RFI calves is the protein-to-fat ratio in the deposited tissues. When efficiency was related to kg/day (DMI and ADG) and not to daily retained energy, the selected efficient L-RFI calves deposited more protein and less fat per daily gain than less efficient H-RFI calves. However, when the significant greater heat increment and maintenance energy requirement of protein compared to fat deposition in tissue were considered, we could not exclude the hypothesis that variation in efficiency is partly explained by efficient energy utilization. The ranking classification of calves to groups according to their RFI efficiency was independent of diet quality and age.

Effects of rotating antibiotic and ionophore feed additives on volatile fatty acid production, potential for methane production, and microbial populations of steers consuming a moderate-forage diet.

Ionophores and antibiotics have been shown to decrease ruminal methanogenesis both in vitro and in vivo but have shown little evidence toward a sustainable means of mitigation. Feed additive rotation was proposed and investigated for methane, VFA, and microbial population response. In the present study, cannulated steers ( = 12) were fed a moderate-forage basal diet in a Calan gate facility for 13 wk. In addition to the basal diet, steers were randomly assigned to 1 of 6 treatments: 1) control, no additive; 2) bambermycin, 20 mg bambermycin/d; 3) monensin, 200 mg monensin/d; 4) the basal diet + weekly rotation of bambermycin and monensin treatments (B7M); 5) the basal diet + rotation of bambermycin and monensin treatments every 14 d (B14M); and 6) the basal diet + rotation of bambermycin and monensin treatments every 21 d (B21M). Steers were blocked by weight in a randomized complete block design where the week was the repeated measure. Rumen fluid was collected weekly for analysis ( = 13), and results were normalized according to individual OM intake (OMI; kg/d). Potential activity of methane production was not significantly different among treatments ( > 0.05). However, treatment tended to affect the CH-to-propionate ratio ( = 0.0565), which was highest in the control and lowest in the monensin, B21M, and B14M treatments (0.42 vs. 0.36, 0.36, and 0.33, respectively). The CH:propionate ratio was lowest in wk 2 and 3 ( < 0.05) but the ratio in wk 4 to 12 was not different from the ratio in wk 0. Week also affected total VFA, with total VFA peaking at wk 3 and plummeting at wk 4 (4.02 vs. 2.86 m/kg OMI; < 0.05). A significant treatment × week interaction was observed for the acetate-to-propionate (A:P) ratio, where bambermycin- and rotationally fed steers did not have a reduced A:P ratio compared with monensin-fed steers throughout the feeding period ( < 0.0001). Microbial analysis revealed significant shifts, but several predominant classes showed adaptation between 4 and 6 wk after additive initiation. There was no significant evidence to suggest that rotations of monensin and bambermycin provided additional benefits to steers consuming a moderate-forage diet at the microbial/animal and environmental level versus those continuously fed.

Interaction of dietary energy source and body weight gain during the juvenile period on metabolic endocrine status and age at puberty in beef heifers.

Using a previously established model for nutritional acceleration of puberty, beef heifers ( = 48; 1/2 Angus × 1/4 Hereford × 1/4 Brahman) were used in a replicated 2 × 2 factorial design to examine the effects of diet type (high forage [HF] vs. high concentrate [HC]) and rate of BW gain (low gain [LG], 0.45 kg/d, vs. high gain [HG], 0.91 kg/d) on key metabolic hormones and age at puberty. After weaning at 14 ± 1 wk of age, heifers were assigned randomly to be fed HC-HG, HC-LG, HF-HG, or HF-LG ( = 12/group) beginning at 4 mo of age for 14 wk. Heifers were then switched to a common growth diet until puberty. Average daily gain was greater ( < 0.04) during the dietary treatment phase in HG heifers (0.81 ± 0.06 kg/d) than in LG heifers (0.43 ± 0.06 kg/d), and there was no diet type × rate of gain interaction. Puberty was achieved at a younger age (54.5 ± 1.8 wk) in both HG groups than in LG groups (60.2 ± 1.9 wk; < 0.04), but dietary energy source (HC vs. HF) did not influence this variable. Moreover, mean BW at puberty did not differ by diet type or rate of gain during the dietary treatment phase. Nonetheless, heifers fed HC-HG exhibited a striking increase ( < 0.0001) in serum leptin beginning at 26 ± 1 wk of age and remained elevated ( < 0.01) throughout the remainder of the experimental feeding phase compared to all other treatments. However, serum leptin in HC-HG dropped precipitously when heifers were switched to the common growth diet and did not differ from that of other groups thereafter. Overall mean concentrations of serum glucose were greater ( < 0.006) in HG heifers than in LG during the dietary treatment phase, with serum insulin also greater ( < 0.04) in HG than in LG only during weeks 20, 22, and 30. Mean serum IGF-1 was not affected by dietary type or rate of BW gain. We speculate that failure of the marked increase in serum leptin observed in HC-HG heifers during the dietary treatment phase to further accelerate puberty compared to HF-HG occurred because of its abrupt decline at the onset of the common growth phase, thus attenuating the temporal cue for activation of the reproductive neuroendocrine system.

Effects of roughage inclusion and particle size on digestion and ruminal fermentation characteristics of beef steers.

Roughage is fed in finishing diets to promote ruminal health and decrease digestive upset, but the inclusion rate is limited because of the cost per unit of energy and feed management issues. Rumination behavior of cattle may be a means to standardize roughage in beef cattle finishing diets, and increasing the particle size of roughage could modulate the ruminal environment and aid in maintaining ruminal pH. Therefore, this experiment was conducted to determine the effects of corn stalk (CS) inclusion rate and particle size in finishing diets on digestibility, rumination, and ruminal fermentation characteristics of beef steers. Four ruminally cannulated steers were used in a 4 × 4 Latin square experiment. Treatments were arranged as a 2 × 2 factorial with treatments consisting of 5% inclusion of a short-grind roughage (5SG), 10% inclusion of a short-grind roughage (10SG), 5% inclusion of a long-grind roughage (5LG), and 10% inclusion of a long-grind roughage (10LG). Differences in particle size were obtained by grinding corn stalks once (LG) or twice (SG) using a commercial tub grinder equipped with a 7.6-cm screen and quantified using the Penn State Particle Separator (PSPS) to estimate physically effective NDF (peNDF). Each period included 14 d for adaptation and 4 d for diet, fecal, and ruminal fluid collections. Animals were outfitted with rumination monitoring collars to continuously measure rumination activity. The 10LG treatment had a greater ( < 0.01) percentage of large particles (retained on the top 3 sieves of the PSPS) compared to the other treatments. This resulted in a greater ( < 0.01) percentage of estimated peNDF for the 10LG diet compared to the others. Feeding diets containing 5% roughage tended to increase ( ≤ 0.09) DM, NDF, and starch total tract digestibility compared to diets containing 10% roughage. Cattle consuming LG treatments had greater ( < 0.01) rumination time and greater ( < 0.01) ruminal pH than cattle consuming diets containing SG roughage. Cattle receiving the 5% inclusion rate of roughage tended to have greater ( = 0.09) time (h/d) under a ruminal pH of 5.6 and a larger ( = 0.03) area under the threshold compared to cattle receiving the 10% roughage treatments. Overall, feeding a lower inclusion of roughage with a larger particle size may stimulate rumination and aid in ruminal buffering similar to that of a higher inclusion of roughage with a smaller particle size, without negatively impacting digestibility and fermentation.

Residual feed intake, carcass traits and meat quality in Nellore cattle.

A total of 127 Nellore bulls classified as low and high residual feed intake (RFI), from three selection lines, were evaluated in five experiments aiming to identify associations between RFI, carcass, and meat quality traits. Feedlot performance, carcass traits, and meat quality of Longissimus muscle were evaluated. A mixed model including the fixed effects of RFI class, selection line, interaction between RFI class and selection line, and age at slaughter as a covariate, and the random effects of diet within experiment and experiment was used, with means compared by the t-test. Feed intake average difference was 0.962kg/day; low RFI animals consumed 0.479kg/day less feed and high RFI animals consumed 0.483kg/day more feed than expected. No differences between RFI classes were detected for most of studied variables, demonstrating the absence of unfavorable associations between RFI and carcass and meat quality traits. Low RFI Nellore animals use feed efficiently and produce good quality carcasses and meat.

Investigation of the effect of pegbovigrastim on some periparturient immune disorders and performance in Mexican dairy herds.

This study analyzed the efficacy of pegbovigrastim (Imrestor, Elanco Animal Health, Greenfield, IN) on some health and production parameters in lactating dairy cows. Primiparous and multiparous Holsteins from 17 Mexican dairy herds (n = 10,238) were included in this study, which was conducted in 2015. Treated cows (n = 5,025) received Imrestor approximately 7 d before expected calving and again within 24 h after calving; control cows (n = 5,213) did not receive a placebo. Clinical mastitis (MAS; 0 to 30 DIM), retained placenta (RP), and clinical metritis (MET; 0 to 21 DIM) occurrences were recorded, as well as the number of medication days, medical treatments needed, and the number of days that milk was discarded due to medication administered for disease. Milk yield was measured from calving until 120 d in milk. Imrestor reduced the incidence of MAS by 25%, and the odds ratio of having mastitis in the first 30 d in milk was 35% greater for control cows than for Imrestor cows. Imrestor treatment reduced the number of medical treatments required for MAS by 6%, and less milk was discarded due to medication for MAS as a result of the Imrestor treatment. The incidence of RP was reduced by 4.15% with Imrestor and the odds of cows having RP were 4.6% greater for control than Imrestor treatments, but they did not differ. The MET incidence was increased by 17.1% with Imrestor. The use of Imrestor around parturition increased by 5.8% the odds of inseminating cows during the first 100 d after calving. Imrestor-treated multiparous cows with MAS produced 2.1 kg/d more milk than control cows with MAS during the first 30 d of their lactation. Imrestor-treated multiparous cows with MET produced 2.3 kg/d more milk than MET control cows during the first 120 d of their lactation. We conclude that Imrestor can help the dairy cow cope with immune periparturient disorders and can increase the milk yield of dairy cows due to a healthier transition, despite a reported increase in the incidence of MET.

Development of highly digestible animal feed from lignocellulosic biomass Part 1: Oxidative lime pretreatment (OLP) and ball milling of forage sorghum.

To feed a growing population, alternative sources of animal feed (e.g., lignocellulose) are needed to replace grains (e.g., corn). Oxidative lime pretreatment (OLP) increases lignocellulose digestibility by removing lignin and hemicellulose acetyl content. Adding a mechanical pretreatment (e.g., ball milling) further improves digestibility. This study determines the effectiveness of OLP and ball milling to enhance the ruminant digestibility of lignocellulose. For forage sorghum, the 48-h in vitro TDN were 40, 64, and 84 g nutrients digested/100 g organic matter (OM) for raw, short-term OLP, and short-term OLP + ball milling, respectively. In terms of compositional changes, OLP increases NDF and decreases non-fiber carbohydrate (NFC) and crude protein (CP), all of which would normally be associated with a decrease in digestibility. However, because OLP and ball milling beneficially change composition (lignin removal) and structural features (reduced crystallinity), digestibility actually increases. Although ball milling increases digestibility according to standard laboratory assays, it reduces particle size possibly allowing fine particles to escape from the rumen before they are digested, thus limiting its practical application. Nonetheless, this study indicates that mechanical pretreatment greatly increases digestibility, and therefore it is desirable to identify an effective mechanical treatment that retains fiber integrity.