No abstract

-Protein supply and requirements by ruminants have been studied for more than a century. These studies led to the accumulation of lots of scientific information about digestion and metabolism of protein by ruminants as well as the characterization of the dietary protein in order to maximize animal performance. During the 1980s and 1990s, when computers became more accessible and powerful, scientists began to conceptualize and develop mathematical nutrition models, and to program them into computers to assist with ration balancing and formulation for domesticated ruminants, specifically dairy and beef cattle. The most commonly known nutrition models developed during this period were the National Research Council (NRC) in the United States, Agricultural Research Council (ARC) in the United Kingdom, Institut National de la Recherche Agronomique (INRA) in France, and the Commonwealth Scientific and Industrial Research Organization (CSIRO) in Australia. Others were derivative works from these models with different degrees of modifications in the supply or requirement calculations, and the modeling nature (e.g., static or dynamic, mechanistic, or deterministic). Circa 1990s, most models adopted the metabolizable protein (MP) system over the crude protein (CP) and digestible CP systems to estimate supply of MP and the factorial system to calculate MP required by the animal. The MP system included two portions of protein (i.e., the rumen-undegraded dietary CP -RUP -and the contributions of microbial CP -MCP) as the main sources of MP for the animal. Some models would explicitly account for the impact of dry matter intake (DMI) on the MP required for maintenance (MPm; e.g., Cornell Net Carbohydrate and Protein System -CNCPS, the Dutch system -DVE/OEB), while others would simply account for scurf, urinary, metabolic fecal, and endogenous contributions independently of DMI. All models included milk yield and its components in estimating MP required for lactation (MPl) and calf birth weight and some form of an empirical, exponential equation to compute MP for pregnancy (MPp). The MP required for growth (MPg) varied tremendously among the original models and their derivative works mainly due to the differences in computing growth pattern and the composition of the gain. The calculation of MCP differs among models; some rely on the total digestible nutrient (TDN; e.g., NRC, CNCPS level 1) intake to estimate MCP, while others use fermentable organic matter (FOM; e.g., INRA, DVE/OEB), fermentable carbohydrate (e.g., CNCPS level 2, NorFor), or metabolizable energy (ME; e.g., ARC, CSIRO, Rostock). Most models acknowledged the importance of ruminal recycled N, but not all accounted for it. Our Monte Carlo simulation indicated the prediction of most models for required MPl overlapped, confirming uniformity among models when predicting requirements for lactating animals, but a large variation in required MPg for growing animals exists.

The contemporary concern about anthropogenic release of greenhouse gas (GHG) into the environment and the contribution of livestock to this phenomenon have sparked animal scientists’ interest in predicting methane (CH4) emissions by ruminants. We contend that improving the adequacy of mathematical nutrition model estimates of production of meat and milk is a sine qua non condition to reliably determine ruminants’ worldwide contribution to GHG. Focusing on milk production, we address six basic nutrition models or feeding standards (mostly empirical systems) and five complex nutrition models (mostly mechanistic systems), describe their key characteristics, and highlight their similarities and differences. We also present derivative systems. We compiled a database of milk production information from 37 published studies from six regions of the world, totalling 173 data points: 19 for Africa, 45 for Asia, 16 for Europe, 12 for Latin America, 44 for North America and 37 for Oceania. Four models were used to predict milk production in lactating dairy cows, and the adequacy of their predictions was measured against the observed milk production from our database. Even though these mathematical nutrition models shared similar assumptions and calculations, they have different conceptual and structural foundations inherent to their intended purposes. A direct comparison among these models was further complicated by the different models requiring unique inputs that are very often not available, and the low reliability of the inputs prevents an unbiased assessment of the model predictions. Very few studies have collected the necessary information to run more mechanistic systems, and users have to rely on standard information to populate many model inputs. Study effect was a critical source of variation that limited our ability to conclusively evaluate the models’ applicability under different scenarios of production around the world. Only after study variation was removed from the database did the adequacy of the model predictions of milk production improved, but deficiencies still existed. On the basis of these analyses, we conclude that not all models were suitable for predicting milk production and that simpler systems might be more resilient to variations in studies and production conditions around the world. Improving the predictability of milk production by mathematical nutrition models is a prerequisite to further development of systems that can effectively and correctly estimate the contribution of ruminants to GHG emissions and their true share of the global warming event.

The objective of this study was to evaluate residual feed intake (RFI), residual intake and body weight gain (RIG) and their relationship with other traits of efficiency, performance, and economic analysis of sheep. Lambs (n = 102) were evaluated during 56 days and a herd consisting of 500 ewes was simulated with the mean of dry matter intake (DMI) and final body weight of the lambs, the same as that of the experimental lambs. The lambs were fed hay-based diet of Tifton 85 (Cynodon spp.), corn, and soybean in the voluminous:concentrate ratio of 35:65. Residual feed intake and RIG were correlated with DMI, feed conversion ratio, and feed efficiency. Residual intake and body weight gain were positively correlated with average daily gain, relative growth rate, and Kleiber's rate. The most efficient production systems (lower RFI and higher RIG) had lower costs and higher profit margins. The net present value (NPV) and internal rate of return (IRR) were higher in systems with more efficient lambs. In systems with less efficient lambs, NPV and IRR were negative and lower, respectively. Efficient animals for RFI and RIG showed satisfactory performance and better economic results.

A respiration system consisting of 4 climate-controlled chambers and 1 set of flowmeters and analyzers was constructed and validated. Each chamber had volume of 21.10m(3) (3.68×2.56×2.24m) and was made from steel with double-glazed windows on either side enabling visual contact between animals. The chambers are independently climate-controlled and can maintain temperature and relative humidity in a range from 5 to 45°C and 30 to 80%, respectively. A flow generator and mass flowmeter continuously pull air from each chamber and a slight negative pressure inside the chamber is ensured. Air from all chambers and ambient air share a common gas analysis and data acquisition system for monitoring O2, CO2, and CH4 concentrations over the measurement period, with the cycle time set to 20min. Analyzers are regularly calibrated and the chambers have mean recoveries of 99.0 and 98.0% for CO2 and CH4, respectively. The chambers are equipped with infrared cameras and electronic feed and water bins for intake measurements, as well as sensors for monitoring animal position and heart rate. Data acquisition and analysis software is used to calculate the rate of consumption of O2 and production of CO2 and CH4. The dynamic respiration measurements are integrated with feed intake data and other sensors. The daily gas exchanges are estimated by integration to determine methane emission and heat production. We conducted a trial with 12 lactating 3/4 Holstein × 1/4 Gyr crossbred dairy cows (6 multiparous and 6 primiparous) under 2 feeding regimens (ad libitum or restricted) to validate the system. Two 22-h respiration measurements were obtained from each cow. Restricted-fed cows showed lower values for milk yield, methane emission, and heat production compared with ad libitum-fed animals. We found no difference between groups for CH4 produced per kilogram of dry matter intake. Repeatability for CH4 emission and heat production was high (0.97 and 0.92, respectively). The respiration system described herein is a useful tool for measuring the dynamic and accumulated data of heat production, methane emission, and feed intake.