Biomedical subjects

N R St-Pierre

Publications and source records attributed to N R St-Pierre.

23 records · Page 2Linked to original sources

PubMed2000

Estimating unit costs of nutrients from market prices of feedstuffs.

The determinations of nutrient costs and breakeven prices of feedstuffs are important activities in the field of nutritional economics. Current methods are either extensions of the Petersen method, which dates back to 1932, or mathematical programming methods generally set as linear programming problems. Both sets of methods have severe limitations that make them unsuitable or biased for deriving unit costs of nutrients and aggregate breakeven costs of feedstuffs in a given market. We propose a least-squares method that, under verifiable conditions, yields maximum likelihood estimates of unit costs of nutrients and breakeven prices of feedstuffs. Assumptions to the maximum likelihood estimates are verified with studentized residuals, leverage values, and variance inflation factors. The method has been programmed into a Windows application and can be used by those with little formal training in statistics.

Animal Feed↗

PubMed1999

Interpretation and design of nonregulatory on-farm feeding trials.

Nonregulatory feeding trials are used to determine the frequency and magnitude of response to a nutritional treatment, the odds of success, and factors that influence the odds and to provide an estimate of potential economic impact. These types of trials are not appropriate for elucidating mechanisms or modes of action. Correct experimental design is critical. Important factors that impact the validity of these trials are animal randomization, potential confounding with time, identification of the proper experimental unit, and adequate replication. Animals should be assigned to treatment without a systematic influence of environmental or physiological factors. The experimental design must account for and remove these influences. The experimental unit is the smallest entity to which the treatment can be applied randomly. In commercial settings, this is often a pen of animals. In a pen feeding situation, the experimental unit is the pen, although measurements may be taken on an individual animal basis. Frequency of data collection generally does not influence the treatment effect; however, it does influence the variance associated with the observations and the power to detect differences in treatments. Statistical methods that account for repeated observations over time are required when analyzing data with multiple observations on the same animal. Improper accounting for environmental changes over time is the most common error. Other errors include improper assignment of animals to treatment, failure to replicate the treatment across multiple experimental units, lack of on-farm oversight, and poor calibration of test equipment.

Animal Feed↗

PubMed1999

Animal grouping strategies, sources of variation, and economic factors affecting nutrient balance on dairy farms.

Increasing environmental concerns are forcing animal industries to reevaluate current feeding practices and their relationships to nutrient excretion. Previous modeling efforts have used simple budgets of nutrient flows through animals, assuming a constant productivity level. This assumption is not valid if animals are not in a steady state. A response model of dairy cow production to levels of net energy for lactation (NEL) and crude protein (CP) was derived from an abrupt threshold and plateau model of individuals. Monte Carlo techniques were used to simulate populations of cows fed diets of various NEL and CP concentrations, to derive the optimum allocation of NEL and CP, and to estimate how the optimum is affected by herd production potential, prices of inputs, and uncertainty of parameters. The simulation showed that a 25% increase in milk production reduced N excretion per kilogram of milk produced by 8%. Improved knowledge of the biology involved and feed composition can reduce N excretion by an additional 8%. Grouping strategies and number of groups used affect optimum allocation of nutrients. An optimum of six milking groups per production unit was derived from the simulation and would reduce N excretion by 8% compared to herds fed in one group.

Agriculture↗

PubMed1999

Estimation of microbial nitrogen flow to the duodenum of cattle based on dry matter intake and diet composition.

The objectives of this study were: 1) to evaluate the National Research Council equation used to predict microbial N flow to the duodenum in lactating cows, and 2) to determine whether improved equations could be developed by using dietary parameters used in the field. Treatment means from 55 trials with lactating and nonlactating cattle with duodenal cannulas were subjected to the backward elimination procedure of multiple regression. Variation within and among trials was accounted for by weighting the observations and including trial effects in all models. The equations to predict microbial N flow based on net energy for lactation (NEL) intake were different from the equation based on NEL intake used by the dairy National Research Council. Dry matter intake (DMI) estimated microbial N flow as well as did NEL intake, indicating that DMI drives predictions based on NEL intake. When multiple dietary factors [i.e., DMI; dietary percentages of crude protein, forage, and neutral detergent fiber; and all two-way interactions] were included, the resulting equation [microbial N (grams per day) = 16.1 + 22.9 x DMI (kilograms per day) - 0.365 x DMI2 - 1.74 x dietary neutral detergent fiber (percentage of dry matter)] tended to fit the data better than the equations based on NEL intake but not better than the equation based on DMI alone. The multiple-factor equation appeared to be the best overall equation for prediction; in contrast to the equation based on DMI, this equation is sensitive to diet composition. An asymptotic multiple-factor equation was developed, which may be more appropriate when extrapolating beyond the data range.

Animal Feed↗

PubMed1998

Modeling ruminal digestibility of carbohydrates and microbial protein flow to the duodenum.

Carbohydrates are the major source of energy for dairy cows and for microbial protein synthesis in the rumen. The prediction of ruminal carbohydrate digestibility and of the flow of microbial protein to the small intestine is difficult because of the variability among various feeds in the kinetics of digestion and passage of neutral detergent fiber and starch. Disappearance of fiber and starch in vitro or in situ and gas production in vitro have been extensively evaluated, improved, and reviewed. Similarly, markers and models to measure ruminal passage rate have been extensively researched and improved. Sources of variation and decreased accuracy for these techniques are discussed. Variation and potential errors also remain for the prediction of microbial protein flow to the duodenum using in vivo procedures. However, when in vivo results were accumulated into a database, microbial N flow to the duodenum over a wide range of conditions could be predicted accurately by intake of net energy for lactation or by dry matter intake and percentage of neutral detergent fiber in the diet. Although evaluation of feeding interactions and specific dietary limitations for microbial protein production in the rumen are possible with some models but not with this regression approach, mechanistic models need further validation and more accurate rate constants for improved accuracy over a wide range of conditions.

Animals↗