title: Methods for simulating nutritional requirement and response studies with all organisms to increase research efficiency.
abstract: Nutritional requirements and responses of all organisms are estimated using various models representing the response to different dietary levels of the nutrient in question. To help nutritionists design experiments for estimating responses and requirements, we developed a simulation workbook using Microsoft Excel. The objective of the present study was to demonstrate the influence of different numbers of nutrient levels, ranges of nutrient levels and replications per nutrient level on the estimates of requirements based on common nutritional response models. The user provides estimates of the shape of the response curve, requirements and other parameters and observation to observation variation. The Excel workbook then produces 1-1000 randomly simulated responses based on the given response curve and estimates the standard errors of the requirement (and other parameters) from different models as an indication of the expected power of the experiment. Interpretations are based on the assumption that the smaller the standard error of the requirement, the more powerful the experiment. The user can see the potential effects of using one or more subjects, different nutrient levels, etc., on the expected outcome of future experiments. From a theoretical perspective, each organism should have some enzyme-catalysed reaction whose rate is limited by the availability of some limiting nutrient. The response to the limiting nutrient should therefore be similar to enzyme kinetics. In conclusion, the workbook eliminates some of the guesswork involved in designing experiments and determining the minimum number of subjects needed to achieve desired outcomes.
authors.affiliation: 1Department of Agricultural Economics,Texas A&M University,College Station,TX 77843,USA.
authors.forename: Dmitry
authors.initials: D
authors.lastname: Vedenov
authors.affiliation: 2Department of Poultry Science,The University of Georgia,Athens,GA 30602,USA.
authors.forename: Rashed A
authors.initials: RA
authors.lastname: Alhotan
authors.affiliation: 2Department of Poultry Science,The University of Georgia,Athens,GA 30602,USA.
authors.forename: Runlian
authors.initials: R
authors.lastname: Wang
authors.affiliation: 2Department of Poultry Science,The University of Georgia,Athens,GA 30602,USA.
authors.forename: Gene M
authors.initials: GM
authors.lastname: Pesti
mesh_terms: D000818:Animals; D004032:Diet; D004798:Enzymes; D005260:Female; D006801:Humans; D007700:Kinetics; D008297:Male; D008954:Models, Biological; D009751:Nutritional Requirements / Q000502:physiology*; D012107:Research Design
chemical_list: D004798:Enzymes
keywords:  BLL broken-line spline model with linear ascending segment or broken-line linear model;  BLQ broken-line spline model with quadratic ascending segment or broken-line quadratic model;  NuRDO.xls Nutritional Response Determination Optimization workbook;  QP;  RC rate constant;  SK saturation kinetics model;  quadratic regression; Excel; Models; Nutritional requirements; Simulation