Predicting Microbial Protein Synthesis in Cattle: Evaluation of Extant Equations and Steps Needed to Improve Accuracy and Precision of Future Equations.

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.

Using sentinel-2 satellite images and machine learning algorithms to predict tropical pasture forage mass, crude protein, and fiber content.

Grasslands cover approximately 24% of the Earth's surface and are the main feed source for cattle and other ruminants. Sustainable and efficient grazing systems require regular monitoring of the quantity and nutritive value of pastures. This study demonstrates the potential of estimating pasture leaf forage mass (FM), crude protein (CP) and fiber content of tropical pastures using Sentinel-2 satellite images and machine learning algorithms.

The influence of virginiamycin on digestion and ruminal parameters under feedlot conditions.

This experiment aimed to assess the impact of virginiamycin on in vitro gas production dynamics, rumen kinetics, and nutrient digestibility in beef steers fed a grain-based diet. Nine ruminally cannulated British-crossbred steers (596 ± 49 kg) were assigned to this experiment. Animals were housed in three pens ( = 3/pen) equipped with a Calan gate feed system and water troughs.

ASAS-NANP symposium: Mathematical Modeling in Animal Nutrition: The power of identifiability analysis for dynamic modeling in animal science:a practitioner approach.

Constructing dynamic mathematical models of biological systems requires estimating unknown parameters from available experimental data, usually using a statistical fitting procedure. This procedure is usually called parameter identification, parameter estimation, model fitting, or model calibration. In animal science, parameter identification is often performed without analytic considerations on the possibility of determining unique values of the model parameters.

ASAS-NANP symposium: mathematical modeling in animal nutrition-Making sense of big data and machine learning: how open-source code can advance training of animal scientists.

Advancements in precision livestock technology have resulted in an unprecedented amount of data being collected on individual animals. Throughout the data analysis chain, many bottlenecks occur, including processing raw sensor data, integrating multiple streams of information, incorporating data into animal growth and nutrition models, developing decision support tools for producers, and training animal science students as data scientists. To realize the promise of precision livestock management technologies, open-source tools and tutorials must be developed to reduce these bottlenecks, which are a direct result of the tremendous time and effort required to create data pipelines from scratch.

ASAS-NANP symposium: mathematical modeling in animal nutrition: agent-based modeling for livestock systems: the mechanics of development and application.

Over the last three decades, agent-based modeling/model (ABM) has been one of the most powerful and valuable simulation-based decision modeling techniques used to study the complex dynamic interactions between animals and their environment. ABM is a relatively new modeling technique in the animal research arena, with immense potential for routine decision-making in livestock systems. We describe ABM's fundamental characteristics for developing intelligent modeling systems, exemplify its use for livestock production, and describe commonly used software for designing and developing ABM.

Forages and pastures symposium: an update on in vitro and in situ experimental techniques for approximation of ruminal fiber degradation.

Static quantification measures of chemical components are commonly used to make certain assumptions about forage or feed nutritive value and quality. In order for modern nutrient requirement models to estimate intake and digestibility more accurately, kinetic measures of ruminal fiber degradation are necessary. Compared to in vivo experiments, in vitro (IV) and in situ (IS) experimental techniques are relatively simple and inexpensive methods to determine the extent and rate of ruminal fiber degradation.

Galyean appreciation club review: a holistic perspective of the societal relevance of beef production and its impacts on climate change.

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.

Forages and Pastures Symposium: revisiting mechanisms, methods, and models for altering forage cell wall utilization for ruminants.

Several ruminant animals rely almost exclusively on the complex polysaccharide matrix from the plant cell wall (CW) as their primary energy source via volatile fatty acids produced through ruminal and some hindgut fermentation processes. The CW contains different types and proportions of polysaccharides, proteins, phenolic compounds, and minerals in their macromolecular structure that influence the rate and extent of fiber digestion and selective retention of particulate matter due to its physical characteristics (buoyancy and comminuting) in the reticulorumen. The biosynthetic formation of the CW dictates possible manipulation mechanisms (targeted plant and microbes selection) and processing methods (physical, chemical, microbial, and enzymatic treatments and the use of genetically engineered bacteria) to increase its digestibility, leading to better utilization of the CW by the ruminant animal and hopefully lower the contribution of ruminants' greenhouse gas emissions.

Combined use of monensin and virginiamycin to improve rumen and liver health and performance of feedlot-finished steers.

Monensin and virginiamycin are included in beef cattle finishing diets as prophylaxis to minimize the incidence of ruminal acidosis and liver abscesses. Due to different and probably complementary modes of action, this study aimed to determine the effects of a combination of monensin and virginiamycin, both included in the diet at recommended doses, on ruminal health, the occurrence of liver abscesses, and growth performance of feedlot-finished cattle. One hundred and forty-four steers (6 animals/pen) were fed 1 of 3 corn-based finishing diets containing 30 mg of monensin (), 25 mg of virginiamycin (), or 30 and 25 mg of monensin and virginiamycin (), respectively, per kilogram of dry matter.

Effect of live yeast supplementation on energy partitioning and ruminal fermentation characteristics of steers fed a grower-type diet in heat-stress conditions.

The objective of this trial was to determine the influence of live yeast supplementation (LY), environmental condition (ENV), and their interaction (TRT) on energy partitioning, nitrogen metabolism, and ruminal fermentation dynamics of steers receiving a grower-type diet. The effects of LY and ENV were investigated using a 2 × 2 crossover design that spanned five periods. Eight Angus-crossbred steers were randomly split into pairs and housed in four outdoor pens outfitted with an individualized feeding system.

Technical note: Evaluation of sampling methods for methane concentration from in vitro fermentation.

The objectives of this multipart study were 1) to assess the efficacy of sampling methods of methane concentration ([CH4]) of headspace gas produced during in vitro gas production (IVGP) fermentation, 2) to verify whether headspace [CH4] sampled from an exetainer has the same [CH4] as the headspace of IVGP bottles, 3) to measure relative humidity (RH) within an IVGP bottle, and 4) to compare [CH4] on a dry-gas (DG) basis when accounting for water vapor pressure (Pw). The original IVGP protocol recommends placing bottles on ice (0 °C) for 30 min to stop fermentation (ICE). A laboratory protocol recommends placing the bottles in the refrigerator (4 to 6 °C) to slow fermentation for 48 h and subsequently allowing the bottles to return to ambient temperature before sampling (FRIDGE).

The Impact of Fetal Programming in Ewe Nutrition with Chromium Propionate or Calcium Salts of Palm Oil on the Meat Quality and Bone of the Progeny.

This study aimed to evaluate the inclusion of chromium propionate or calcium salts of palm oil in ewes' diet during the final third of gestation and lactation on progeny performance, carcass characteristics, non-carcass components, and bone density. Forty-three ewe, Santa Inês and Dorper breed, three ± one-year-old, and body weight 57 ± 10 kg were used. The experimental design was in casual blocks in three treatments, CTL treatment (n = 15) with starch from corn; CR (n = 15) diet CTL plus chromium propionate; PF (n = 13) diet CTL plus calcium salts of palm oil.

Quantification of methane emitted by ruminants: a review of methods.

The contribution of greenhouse gas (GHG) emissions from ruminant production systems varies between countries and between regions within individual countries. The appropriate quantification of GHG emissions, specifically methane (CH4), has raised questions about the correct reporting of GHG inventories and, perhaps more importantly, how best to mitigate CH4 emissions. This review documents existing methods and methodologies to measure and estimate CH4 emissions from ruminant animals and the manure produced therein over various scales and conditions.

Nutrient content and degradation study of some unconventional feed resources of Bangladesh.

This study aimed to evaluate six unconventional feed resources of Bangladesh, including water hyacinth (), banana leaves (), roadside grass (), bamboo leaves ( Scrad), Seaweed ( sp.) and sugarcane bagasse (). Evaluations were based on dry matter (DM), crude protein (CP), crude fiber (CF), neutral detergent fiber (NDF), acid detergent fiber (ADF), ether extract (EE), ash content, DM and OM digestibilities and fractional rate of degradation.

ASAS-NANP Symposium: Mathematical Modeling in Animal Nutrition: Opportunities and challenges of confined and extensive precision livestock production.

Modern animal scientists, industry, and managers have never faced a more complex world. Precision livestock technologies have altered management in confined operations to meet production, environmental, and consumer goals. Applications of precision technologies have been limited in extensive systems such as rangelands due to lack of infrastructure, electrical power, communication, and durability.

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

The field of animal science, and especially animal nutrition, relies heavily on modeling to accomplish its day-to-day objectives. New data streams ("big data") and the exponential increase in computing power have allowed the appearance of "new" modeling methodologies, under the umbrella of artificial intelligence (AI). However, many of these modeling methodologies have been around for decades.

The energy requirement for maintenance of Nellore crossbreds in tropical conditions during the finishing period.

This study determined the energy requirement for maintenance of purebred Nellore cattle and its crossbreds using data from a comparative slaughter trial in which animals were raised under the same plane of nutrition from birth through slaughter and born from a single commercial Nellore cowherd. A total of 79 castrated steers (361 ± 54 kg initial body weight [BW]) were used in a completely randomized design by age (22 mo ± 23 d of age) with four genetic groups (GG): Nellore (NL), ½ Angus × ½ Nellore (AN), ½ Canchim × ½ Nellore (CN), and ½ Simmental × ½ Nellore (SN). The experimental design provided ranges in metabolizable energy (ME) intake (MEI), BW, and average daily gain needed to develop regression equations to predict net energy for maintenance (NEm) requirements.

ASAS-NANP symposium: mathematical modeling in animal nutrition: the progression of data analytics and artificial intelligence in support of sustainable development in animal science.

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.

Effects of supplementation rate of an extruded dried distillers' grains cube fed to growing heifers on voluntary intake and digestibility of bermudagrass hay.

Our objectives were to 1) investigate the difference in chemical composition and disappearance kinetics between loose dried distillers' grains (DDG) and extruded DDG cubes and 2) evaluate the effects of supplementation rate of extruded DDG cubes on voluntary dry matter intake (DMI), rate and extent of digestibility, and blood parameters of growing beef heifers offered ad libitum bermudagrass (Cynodon dactylon) hay. To characterize the changes in chemical composition during the extrusion process, loose and extruded DDG were evaluated via near-infrared reflectance spectroscopy, and dry matter (DM) disappearance kinetics were evaluated via time point in situ incubations. Extruded DDG cubes had greater (P ≤ 0.

A mathematical nutrition model adequately predicts beef and dairy cow intake and biological efficiency.

The beef cow-calf sector accounts for 70% of feed consumed and greenhouse gases emitted for the beef industry, but there is no straightforward method to measure biological efficiency in grazing conditions. The objective of this study was to evaluate a mathematical nutrition model to estimate the feed intake and biological efficiency of mature beef cows. Data from dams ( = 160) and their second and third progeny (312 pairs) were collected from 1953 through 1980.

Predicting metabolizable energy from digestible energy for growing and finishing beef cattle and relationships to the prediction of methane.

Reliable predictions of metabolizable energy (ME) from digestible energy (DE) are necessary to prescribe nutrient requirements of beef cattle accurately. A previously developed database that included 87 treatment means from 23 respiration calorimetry studies has been updated to evaluate the efficiency of converting DE to ME by adding 47 treatment means from 11 additional studies. Diets were fed to growing-finishing cattle under individual feeding conditions.

Effect of inclusion levels of low-fat dried distillers grains in finishing diets on protein and energy intake and retention and estimation of protein and energy requirements of young Nellore bulls fed with high concentrate diets.

The objective was to evaluate the effect of including low-fat dried distillers grains (DDG) in finishing diets on protein and energy intake and retention and to estimate the protein and energy requirement of young Nellore bulls. Thirty-five animals were used: baseline (n = 4), maintenance (n = 4), and ad libitum intake (n = 27). Ad libitum animals were divided into four groups: diets with the inclusion of DDG at the levels of 0, 150, 300, and 450 g/kg (dry matter basis).

Modifying the National Research Council weight gain model to estimate daily gain for stockers grazing bermudagrass in the southern United States.

The energy requirements, feed intake, and performance of grazing animals vary daily due to changes in weather conditions, forage nutritive values, and plant and animal maturity throughout the grazing season. Hence, realistic simulations of daily animal performance can be made only by the models that can address these changes. Given the dearth of simple, user-friendly models of this kind, especially for pastures, we developed a daily gain model for large-frame stockers grazing bermudagrass sCynodon dactylon (L.