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Rumen microorganisms are responsible for providing the major part of the energy requirements of the host animal by transforming dietary carbohydrates to acetate, propionate and butyrate. In order to do this and to exploit the energy potential of the food fully, they must grow and multiply and this involves large-scale synthesis of microbial protein. The nitrogen for this is obtained, in the form of amino acids, peptides and ammonia, by breakdown of the nitrogen fraction of the food. Bacteria acting on the structural carbohydrate SC fraction of the diet use only ammonia, whereas those acting on the non-structural fraction NSC derive about 65 per cent of their nitrogen from amino acids and peptides, and the remainder from ammonia.

The magnitude of this contribution depends upon the speed and extent of microbial breakdown of the dietary nitrogen fraction, upon the efficiency of the transformation of the degraded material into microbial protein nitrogenous compounds , the digestibility of the microbial protein and the biological value of the latter. The routine measure of the contribution of fermentation products to metabolisable energy individual foods has not been a feasible proposition and assumed values are commonly used.

Sophisticated models attempt to relate microbial yield to the rate carbohydrate fermentation and rate of passage, theoretical growth the energy cost of bacterial maintenance and the form of nitrogen available to the rumen microorganisms. Many of the relationships involved such calculations are based on laboratory characterisation of the food, and the value of the model will depend on the validity of the relationships between the laboratory determinations and the values used in models.

Here it is broken down to amino acids, which are then absorbed into the body. However, protozoal protein constitutes some 5 to 15 per cent only of the total microbial protein flow from the rumen and its influence on the overall digestibility of microbial protein will be small. The composition of bacteria is variable but that shown in Table About 15 per cent of the total nitrogen is in the form of nucleic acids, about 25 per cent is cell wall protein and the remainder is true protein.

Available evidence indicates that the digestibility of nucleic acid nitrogen is of the order of 0. Most estimates of the true digestibility of microbial protein are of the order of 0. Although nucleic acids are highly digestible their nitrogen is of no use to the animal, as after absorption they are totally excreted in the urine. The digestibility of the undegraded dietary protein is a characteristic of the protein mix in the food and may vary considerably from diet to diet. Digestibility has been shown to be inversely related to the content of acid detergent insoluble nitrogen ADIN , which reflects that part of the food nitrogen which is closely bound to insoluble fibre.

The digestible undegradable protein content DUP of a food is calculated thus:. This equation is based on the assumptions that ADIN is indigestible and that the digestible fraction has a true digestibility of 0. In the case of foods such as maize gluten and some distillery and brewery by-products, which have been heat treated under moist conditions, Maillard-type reactions may occur, resulting in an increase the concentration of nitrogenous compounds insoluble in acid-detergent.

Such 'acquired ADIN' does have a finite though low digestibility and the above equation is unreliable when used for such foods. The mixture of amino acids of dietary origin absorbed from the small tine i.

This will in turn depend upon the biological values of the digested undegraded dietary protein and digested microbial protein, and upon the relative proportions of each contributing to the mix. In addition, it will vary with the primary function which it is required. Microbial protein is thought to have a relative constant biological value of about 0. Prediction of such dietary values is extremely difficult, since the biological values of the individual proteins are no guide to their value in combinations. An alternative approach is to estimate the supply of essential amino acids made available to the tissues i.

Intestinal CHO B1 digestibility depends on type of grain, degree and type of processing, and level of intake above maintenance Knowlton et al. Guidelines for intestinal digestion of the CHO B1 for growing beef steers and lactating dairy cows consuming feed at two to three times maintenance level of intake are: Guidelines for intestinal digestion of the CHO B1 fraction for high producing dairy cows above 45 kg milk are: The equations used to compute NE derived from feeds are empirical, but the validations indicate they have represented the complexity of energy and protein metabolism reasonably well in predicting animal responses in combination with the rumen model described above.

Apparent TDN is the sum of total tract digestible nutrients. Because Kp increases as the intake increases, apparent TDN is adjusted for level of intake. Variations in ME are in part due to variations in ruminal methane production. The NE l values are based on the respiration chamber data of Moe The interactions of DMI, digestion and passage have several implications: The CNCPS has several outputs that can be used to assess whether protein or energy is the first limiting nutrient for milk production or growth. Two of the N outputs rumen N balance and peptide balance show the N status of the ruminal bacteria, but the peptide balance is not a requirement per se.

The peptide balance is the amount of peptides needed to maximize protein production from NFC bacteria. A negative peptide balance indicates that the yield of microbial protein from NFC bacteria could be increased by adding ruminally degraded true protein to the diet. If the total flow of microbial protein or escape protein exceeds the protein needs of the animal, production will not increase. The remaining two N outputs MP balance and AA allowable milk or gain reflect the needs and supply of protein and essential amino acids to the animal. Scrutiny of all four N balances is essential in diet evaluation.

Energy and nutrient requirements - Energy available for productive functions depends on the proportion of energy consumed that must be used for meeting maintenance NE m requirements, and therefore it is considered first in evaluating a diet and animal performance. Maintenance requirements in the CNCPS are determined by accounting for breed, physiological state, activity, urea excretion, heat or cold stress and environmental acclimatization effects Fox et al. In a recent evaluation of three comparative slaughter experiments with Nellore cattle fed high forage diets, Tedeschi et al.

As in the AFRC, the NE m requirement is adjusted for activity and energy needed to maintain a normal body temperature for all classes of cattle. The current effective temperature index CETI uses current temperature and relative humidity to adjust predicted intake for temperature effects. Growth requirements are based on empty body tissue composition of the gain expected, based on expected mature size for breeding herd replacements or expected weight at a particular final composition, considering body size, effect of dietary ingredients, and anabolic implants Fox et al.

Shrunk body weight SBW is adjusted to a weight equivalent to that of a standard reference animal at the same stage of growth. In beef or dairy cows, mature weight is defined as the weight at which additional added body mass does not contain additional net protein gain, a condition assumed to occur by 4 years of age and at a BCS of 5 on a 1 to 9 scale for beef cows or at BCS 3 on a 1 to 5 scale for dairy cows.

For growing cattle to be harvested for beef, mature weight is the expected weight at the target body composition. Recent research indicates that the growth rate for dairy herd replacement heifers affects first lactation milk production Fox et al. The amino acid requirements for maintenance depend on the prediction of sloughed protein and net tissue turnover losses, as predicted from metabolic fecal nitrogen, urinary nitrogen loss, and scurf protein. The pregnancy requirements and weight gain from growth of the gravid uterus based on expected calf birth weight and day of gestation Bell et al.

Energy and protein required for lactation are calculated from actual milk production and components. Metabolizable energy required for lactation is computed from milk energy with an efficiency of Since actual milk production of beef cows usually is not measured, their lactation requirements are estimated from age of cow, time of lactation peak, expected peak milk yield based on breed and calf weaning weights, day of lactation, duration of lactation, milk fat content, milk solids not fat, and protein as described by NRC Body reserves are used to meet requirements when nutrient intake is inadequate.

Further, since there are significant exchanges in body water and fat throughout lactation Andrew et al. After reaching maturity, body weight changes reflect use or deposition of energy reserves Fox et al. Weight gain and loss after maturity has nearly the same composition as weight gain during growth Fox et al. The cycle of reserve depletion and replenishment during lactation and the dry period is reflected by predicted condition score change.

Modifications and evaluations for dynamic application of the CNCPS model concepts for lactating dual-purpose cows Reynoso-Campos et al. There are several models that employ dynamic modeling at the metabolism level, such as enzyme-substrate relationships, to ultimately predict animal responses and performance to different substrates. Generally, these models have been developed in support of research rather than for application. As research tools, mechanistic, dynamic and deterministic models enable scientists to integrate existing information, identify research needs and evaluate alternative hypotheses.

Nonetheless, these models aggregate the basic scientific knowledge that is necessary to increase our ability to understand certain biological mechanisms and identify priorities for fundamental and applied research. As an example of the differences in philosophy and approaches between research and application modeling, the models of Baldwin et al.

Michaelis-Menten , so that the overall system is more stable than if linear mass-action equations were used,. Since the main objective was to evaluate available data and concepts for adequacy, feed descriptions input data are limited to those characteristics that can be measured in the laboratory. For example, detailed chemical and physical properties of the feeds are required inputs, but not digestion and passage rate constants because these are considered to be animal-dependent. This constraint limits the applicability of the models for practical use, but enables researchers to focus on the identification of research priorities.

Future developments in the modeling field must accompany improved understating of the underlying biology. In fact, modeling and research must go hand in hand. This fact, long understood by physical scientists, is only now being realized by biologists: Comparison of mathematical models for adequacy and appropriateness is not an easy task since models require different set of inputs and sometimes a common input has a different connotation among models. As expected, predicted intake was the most influential measurement upon the relative differences in simulating growth and composition among the models; that's why actual intake is necessary to ascertain good accuracy and evaluation of models.

The definition of mature weight was different among models and higher prediction performance was obtained when the mature weight of the simulated animal was relatively adjusted to the specific definition of each model. The authors concluded each model would perform differently upon the same production scenario regardless of the similarity of inputs used. The authors concluded that more detailed and complex mechanistic models are needed to account for more of the variation. The authors found large differences in the microbial functions of substrate fermentation, substrate incorporation, and microbial synthesis among these models.

They also differ in extramicrobial ruminal functions, and microbial mechanisms had important consequences for simulated nutrient outputs from the rumen. Milk production requirements were similar among all systems. The energy and protein requirements for pregnancy were very different among systems, both in the approach used and in the predicted requirements. Areas with great differences surfaced in the assessment of requirements for growth of heifers and for body reserves. The approaches used in the partitioning of nutrients between growth and reserves for heifers and the prediction of the energy, fat and protein content of reserves differed between systems.

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For a model to be useful on-farm, however the combination of model equations must accurately predict animal responses. In recent years, mineral requirements have received a great deal of consideration because accurate prediction of mineral requirements may minimize mineral excretion and environmental pollution. It was concluded the net requirements for growth estimated by Lana et al. We conclude the lack of information for endogenous losses and absorption coefficients for major minerals in tropical conditions requires the use of values from experiments conducted in different conditions from those found in the tropics.

Studies with pen-fed growing cattle consuming high-forage diets indicated that the NRC tabular system had an overprediction bias because intake effects were not considered and the carbohydrate and protein fractions were not adequately described Tedeschi, , Ch. Although it uses similar carbohydrate and protein fractions as CNCPS level 1, the CNCPS level 2 accounted for more of the variation in animal performance because variables such as digestion rates, effects of level of intake, microbial growth on cell wall and noncell wall carbohydrate fractions, rate of passage, rumen pH, and ruminal nitrogen deficiency, on feed ME and MP values were considered.

Unfortunately, the models did not accurately predict fiber digestion in the rumen or volatile fatty acids concentrations. The authors recommended that future improvements in rumen modeling could be considered by pooling the advantages of each model. Priorities for research and routine feed analysis procedures that need to be implemented depend on the ratio of cost to benefit and the procedures available to measure sensitive variables. There is little value in developing more complex models for amino acid balancing until the first limiting factors can be accurately predicted.

This was demonstrated when measured duodenal flows from 80 diets were not predicted as accurately with the dynamic, low level aggregation rumen model of Baldwin et al. The sensitivity analysis of Fox et al.

Similarly, due to the lack of better description of feed samples, laboratorial methods that accurately and precisely predict the nutritive value of feeds used in ruminant diets are needed. Nonetheless, the prediction of digestibility of the latter one has proven to be troublesome. The authors concluded that there are differences among the six predictive approaches in the number of laboratorial assays, and their costs, as well as that the NRC approach three empirical equations that require categorical description of feeds; therefore, inappropriate for mixed feeds. No procedure was able to consistently discriminate the ME values of individual feeds within feedstuffs determined in vivo among these approaches.

Preliminary sensitivity analysis based on Monte Carlo simulations have indicated that the current fractionation scheme of protein does not increase the variability in the RUP or MCP measurements, but has an impact on which inputs become more critical Cristina Lanzas , personal communication. The following concerns have been raised regarding the current feed protein fractionation structure in the CNCPS.

The assigned digestion rates for protein B fractions are based on the number of pools and rates identified by curve-peeling technique of data based on protein in vitro degradation when incubated with protease from Streptomyces griseus. The low rates for the B3 protein fraction 0. If the B3 diges tion rate was assigned wrongly to the B3 pool as the result of this approach, then one should be concerned about the assigned B2 rates;.

This implies that it may be released from the fiber matrix at a degradation rate similar to the avail able NDF. The ADIN measure may not represent a totally unavail able pool. Lucas' tests regression of digestible pro tein on protein content have shown that for some feeds, ADIN does not behave as a completely indigest ible entity slope different than unity. The high levels of ADIN from distiller's grains have been associated with heat damage during processing Van Soest, ; however, it may be pos- sible that prolamin proteins such as zein may be re- covered in the ADIN fraction; and.

The lack of a reliable and feasible laboratory assay to estimate NPN in the soluble protein may affect the cal culation of MCP.

Animal nutrition

It is known that the protein A frac tion is rapidly converted into ammonia and that pep tides from this protein fraction do not contribute to theruminal peptides pool, which is derived from the degraded protein. We have shown via simulation mod eling that a failure in accounting for these solubilized peptides is one of the major factors that contributes to the under prediction of MP allowable milk low MCP prediction indiets based on high quality alfalfa silage, which affects NFC microbial protein production Aquino et al.

The ability to describe metabolic transactions, and their resultant affects on nutrient requirements, is critical to raise food-producing animals in efficient ways around the world. Complex models, ever grounded in validated research data, will continue to be enhanced. The only way to eventually define the true complexity of the organisms that we are dealing with is to have an ordered model approach which, in a planned iterative fashion, asks complex questions and increases our knowledge with the clear answers we receive McNamara, There are several limitations in modeling the dynamics of metabolism as discussed by McNamara The main one is the lack of detailed and accurate data.

Similarly, the rapid dynamic changes in metabolic flux during lactation, especially in late pregnancy and early lactation pose another major limitation. It is likely that these limitations arise from the experimental focus and design.

A diet supplement for captive wild ruminants.

Another major restriction is the complexity of the system itself: The development and deployment of sustainable agriculture concepts require an insightful knowledge of the dynamics of agricultural systems at both the farm and regional levels. The efficient use of nutrients in agriculture to improve profitability while protecting water and air quality relies on our ability to understand and manage the complex interactions and impacts of decisions made in developing animal-soil-crop-environmental system ASCES on farms. Concerns about N and P concentrations underscore the necessity of simulating nutrient flows and their environmental impacts Berntsen et al.

Nonetheless, few simulation models Kebreab et al. A principal limitation of these models is they focus only on a specific subsystem crop, water, and soil, respectively and their lack of feedback relationships, that is, the manner in which the integrated system developed affects future outcomes. Therefore, the development of a model to predict nutrient flows and fate on livestock farms, using systems dynamics modeling is necessary to understand the impact of the intrinsic nonlinear behavior of different subsystems on environment pollution as depicted in Figure 1.

This type of model can be used to predict how alternative farm-level nutrient management strategies will influence N and P utilization and losses as well as farm financial performance over time. The great concern in NH 3 air emission is mainly caused by the uncertainty in the NH 3 emission fractions from animal manure and the major concern in N 2 O emission is due to the uncertainty in the fractions relating total nitrification and denitrification to NO 2 emissions de Vries et al.

Therefore, a dynamic model that simulates the flow and behavior of N compounds can assist in detecting the effects, extent, and prevention of N pollution into the environment. Mathematical models integrate our scientific knowledge of feeds and feeding, intake, and digestion and passage rates upon feed energy values, escape of dietary protein, and microbial growth efficiency to estimate energy and nutrient supply and requirements and feed utilization in each unique farm production scenario.

Therefore, they have an important role in assisting the improvement of feeding systems. These models can be used to further improve cattle and sheep production systems by accounting for more of the variation in predicting requirements and supply of nutrients while minimizing the environmental impacts through reduced nutrient excretion in an economically feasible fashion.

For the coming decades, producing meat and milk from cattle will become more efficient in the use of nutrients by using mathematical models to accurately predict requirements and feed utilization in each unique production setting. These mathematical models must allow inputs from each situation to be adjusted in a logical way until the cattle and feeds are accurately described. Then, when predicted and observed performance match, improved feeding programs can be developed for that unique situation where nutritional safety excess supply factors and nutrient excretion are minimized.

The challenge will be to develop systems that are aggregated at a level that can reflect our understanding of the underlying biology; yet, be usable on farm considering information available, ability to monitor and quantify key input variables and animal responses, and knowledge and time available of the consultant using the models. The CNCPS is a mechanistic, deterministic, and static mathematical model that was developed and continues to be improved from basic biological principles to assist producers, consultants, and researchers in evalu ating diets and animal performance.

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Models such as the CNCPS enable nutritionists to identify sources of variation and can be used to formulate more economical and environmentally friendly rations. By more accurately formulating diets in each unique production situation, the need for expensive, and often environmentally detrimental, nutritional safety factors can be minimized.

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