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Nutritional requirements are typically estimated based on feeding trials with animals or birds offered several amounts of the critical nutrient(s). A nutrient response function is then fitted to data from the feeding trials. Modern computer techniques allow for a variety of functional forms to be used as nutrient response functions. However, the performance of these models is almost undistinguishable from a purely statistical perspective. This paper approaches the issue of determining nutrient requirements from an economic prospective. Crude protein amounts that would maximize profits were calculated for combinations of corn, soybean meal, and live broilers prices using several nutrient response models fitted to technical data from a trial with several balanced CP amounts fed to broiler chickens. Under certain combinations of input prices, differences between the models were between 1.5 and 3.0% CP. No model consistently predicted the greatest or least CP amounts or net profits, emphasizing that the (tangential) slopes of the models change at different rates over the range of nutrient (CP) amounts studied. Models providing adequate statistical fits to research data do not necessarily provide functions that are clearly most appropriate for maximizing producer profits. [ABSTRACT FROM AUTHOR]

Methionine is the first-limiting amino acid in corn and soybean meal-based poultry diets. Therefore, its supplementation level is of primary economic importance to poultry production. The responses to the methionine sources DL-methionine (DLM) and methionine-hydroxy analog-free acid (HMTBA) have been compared using various methodologies. The so-called common plateau nonlinear model has been used to estimate relative bioavailabilities of the sources. This model has a coefficient that is used as a single value to compare the relative bioavailabilities of the sources for independent technical parameters like gain and feed efficiency. This model was used previously in a meta-analysis of published experiments, and 79 and 81% relative biological efficiencies of HMTBA were found for DLM for ADG and feed utilization efficiency, respectively. Because different sources would have different optimal feeding levels to maximize profits, we demonstrate the challenge of calculating a single optimal level for the different methionine sources. Further, we apply an economic analysis to results of the previous meta-analysis to demonstrate that the relative values of HMTBA and DLM for BW and ADG are between 81 and 86%, depending on the value of a broiler and the costs of feed and DLM. [ABSTRACT FROM AUTHOR]

1. Research papers use a variety of methods for evaluating experiments designed to determine nutritional requirements of poultry. Growth trials result in a set of ordered pairs of data. Often, point-by-point comparisons are made between treatments using analysis of variance. This approach ignores that response variables (body weight, feed efficiency, bone ash, etc.) are continuous rather than discrete. Point-by-point analyses harvest much less than the total amount of information from the data. Regression models are more effective at gleaning information from data, but the concept of “requirements” is poorly defined by many regression models. 2. Response data from a study of the lysine requirements of young broilers was used to compare methods of determining requirements. In this study, multiple range tests were compared with quadratic polynomials (QP), broken line models with linear (BLL) or quadratic (BLQ) ascending portions, the saturation kinetics model (SK) a logistic model (LM) and a compartmental (CM) model. 3. The sum of total residuals squared was used to compare the models. The SK and LM were the best fit models, followed by the CM, BLL, BLQ, and QP models. A plot of the residuals versus nutrient intake showed clearly that the BLQ and SK models fitted the data best in the important region where the ascending portion meets the plateau. 4. The BLQ model clearly defines the technical concept of nutritional requirements as typically defined by nutritionists. However, the SK, LM and CM models better depict the relationship typically defined by economists as the “law of diminishing marginal productivity”. The SK model was used to demonstrate how the law of diminishing marginal productivity can be applied to poultry nutrition, and how the “most economical feeding level” may replace the concept of “requirements”. [ABSTRACT FROM AUTHOR]

A variety of models have been proposed to fit nutritional input-output response data. The models are typically nonlinear; therefore, fitting the models usually requires sophisticated statistical software and training to use it. An alternative tool for fitting nutritional response models was developed by using widely available and easier-to-use Microsoft Excel software. The tool, implemented as an Excel workbook (NRM.xls), allows simultaneous fitting and side-by-side comparisons of several popular models. This study compared the results produced by the tool we developed and PROC NLIN of SAS. The models compared were the broken line (ascending linear and quadratic segments), saturation kinetics, 4-parameter logistics, sigmoidal, and exponential models. The NRM.xls workbook provided results nearly identical to those of PROC NUN. Furthermore, the workbook successfully fit several models that failed to converge in PROC NUN. Two data sets were used as examples to compare fits by the different models. The results suggest that no particular nonlinear model is necessarily best for all nutritional response data. [ABSTRACT FROM AUTHOR]

An experiment was conducted to quantify the growth response of broiler chicks to cumulative dietary lysine and CP intakes. From d 7 to 17, chicks were fed one combination of dietary lysine and CP (17, 20, 23, arid 26% CP and 3.5, 4.0, 4.5, and 5.0 g lysine per 100 g of CP) in a diet containing 3,200 kcal/kg ME. There were significant linear and quadratic effects of dietary CP intake and quadratic effects of dietary lysine intake on body weight gain (BWG), confirming that a diminishing response (marginal BWG decreased as intake of dietary lysine increased) existed (R² = 0.92 and 0.95, respectively). A significant interaction between dietary CP and lysine for BWG complicates economic modeling because responses must be considered together. A quadratic growth response equation describing BWG as a function of dietary lysine and CP intake was used to develop and demonstrate a quadratic programming model. In general, increasing the price of soybean meal (SBM) decreased the dietary CP concentrations that gave maximum BWG and the concentration of dietary lysine decreased proportionally. In SBM-based diets, the concentration of dietary lysine that maximized BWG was less than or equal to the concentration reached by the proportions of corn and SBM needed to meet dietary CP constraints. Savings from using maximum-profit vs. least-cost formulation models could approach $637,000 per year for a single model poultry complex under some economic situations for the starter diet alone. [ABSTRACT FROM AUTHOR]

The use of non-linear regression models in the analysis of biological data has led to advances in poultry nutrition. Spline or broken-line nonlinear regression models are commonly used to estimate nutritional requirements. One particular application of broken-line models is estimating the maximum safe level (MSL) of feed ingredients beyond which the ingredients become toxic, resulting in reduced performance. The objectives of this study were to evaluate the effectiveness of broken-line models (broken-line linear or BLL; and broken-line quadratic or BLQ) in estimating the MSL; to identify the most efficient design of feeding trials by finding the optimal number of ingredient levels and replications; and to re-estimate the MSL of various test ingredients reported in the nutrition literature for comparison purposes. The Maximum Ingredient level OptimizationWorkbook (MIOW) was developed to simulate a series of experiments and estimate the MSL and the corresponding descriptive statistics (SD, SE, CI, and R2). The results showed that the broken-line models provided good estimates of the MSL (small SE and high R2) with the BLL model producing higher MSL values as compared to the BLQ model. Increasing the number of experimental replications or ingredient levels (independently of each other) reduced the SE of the MSL with diminishing returns. The SE of the MSL was reduced with increasing the size (total pens) of the simulated experiments by increasing either the number of replications or levels or both. The evaluation of MSLs reported in the existing literature revealed that the multiple range procedure used to determine the MSL in several reports can both overestimate and underestimate the MSL compared to the results obtained by the broken-line models. The results suggest that the broken-line linear models can be used in lieu of the multiple range test to estimate the MSL of feed ingredients along with the corresponding descriptive statistics, such as the SE of the MSL. [ABSTRACT FROM AUTHOR]