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[null,"NUTRITIONAL"]
[null,null,"RESPONSE",null,null,null,null,null,null,"Verson 1.0"]
[null,null,null,"DETERMINATION"]
[null,null,null,null,"OPTIMIZATION"]
[]
[null,"A workbook to determine the best arrangement of levels and replicates "]
[null,null,"for estimating nutritional requirements"]
[]
[]
[null,"Dmitry Vedenov",null,null,"Department of Agricultural Economics",null,null,null,null,null,null,null,null,"vedenov@tamu.edu"]
[null,null,null,null,"Texas A&M University"]
[null,null,null,null,"College Station, TX 77843"]
[]
[null,"Gene Pesti",null,null,"Department of Poultry Science",null,null,null,null,null,null,null,null,"gpesti@uga.edu"]
[null,null,null,null,"The University of Georgia"]
[null,null,null,null,"Athens, Georgia 30602"]

{"sheet":"Information","index":1,"n_rows":68,"n_cols":2,"rows_kept":68,"cut":false,"hidden":false,"merged":[]}
[]
["OBJECTIVE:","NuRDO simulates a series of experiments and calculates the nutritional ruquirement by two spline functions, a second order polynomial and a sigmoidal model."]
[]
[null,"The broken line linear model depicts a linear response to increasing levels of the limiting nutrient, then a plateau with a slope of zero."]
[]
[null,"The broken line quadratic model depicts a non-linear diminishing returns response to increasing levels of the limiting nutrient, then a plateau with a slope of zero."]
[]
[null,"Experimental \"results\" from different combinations of nutrient levels and replicates per level can be calculated."]
[]
[null,"The combination of levels & reps with the smallest standard error of the requirement should be the most efficient design for determining requirements"]
[]
[]
["BACKGROUND:","It is widely held that enzyme catylized reactions follow Michales-Menten kenetics."]
[]
[null,"Some enzyme catalyzed reaction should be limiting performance whenever a nutrient is at a limiting concentration in the diet."]
[]
[null,"Mercer, Morgan and Flodin (1975) examined a series of nutritional responses and showed how they could all be fitted very well using what they called the \"Saturation Kinetics\" response model."]
[]
[null,"The SK model is a super set of the Mechalis-Menton model of enzyme kinetics."]
[]
[null,"Nutritionists may believe that the true response to increasing levels of nutrients in a diet result in a non-linear response."]
[]
[null,"But in searching for a requirement, they most often use one-way ANOVA and a multiple range test to determine requirements."]
[]
[null,"Spline models with an ascending line and plateau can be used to estimate a requirement with confidence limits."]
[]
[null,"The SK model only approaches a maximum.  Requirements are sometimes taken as the nutrient intake as some arbitrary fraction of the maximal response."]
[]
[null,"Sometimes quadratic polynomials are fitted to nutritional data and the nutrient level at the maximum response is taken to represent the requirement."]
[]
[null,"With NuRDO researchers can simulate what they think is the real shape of the response curve."]
[]
[null,"They can run up to 1000 simulated experiments to see the combination of levels and replications that minimize the standard error of the requierments"]
[null," using broken-line models. "]
[]
[]
[null,"Bibliography "]
[]
[null,"Almquist, H. J. 1953. Interpretation of amino acid requirement data according to the law of diminishing returns. Arch. Biochem.Biophys. 44:245–247."]
[null,"Baker DH. 1987.Problems and pitfalls in animal experiments designed to establish dietary requirements for essential nutrient. J Nutr,; 116:2339-2349."]
[null,"Dourmad JY, Étienne M, Valancogne A, Dubois S, van Milgen J, Noblet J. InraPorc. 2008. A model and decision support tool for the nutrition of sows. Anim Feed Sci Tech.; 143:372–386."]
[null,"Duncan, D.B. 1955. Multiple range and multiple F tests. Biometrics, 11: 1–42. "]
[null,"Fisher, C., T. R. Morris, and R. C. Jennings. 1973. A model for the description and prediction of the response of laying hens to amino acid intake. Br. Poult. Sci. 14:469–484."]
[null,"Guevara VR. 2004. Use of nonlinear programming to optimize performance response to energy density in broiler feed formulation. Poultry Science. 83:147-151."]
[null,"Hassanien MH, Hussein LA, Robinson EN, Mercer LP. 2003. Human iodine requirements determined by the saturation kinetics model. J Nutr Biochem.; 14: 280–287."]
[null,"Hernandez-Llamas A. Conventional and alternative dose–response models to estimate nutrient requirements of aquaculture species. Aquacult. 2009; 292: 207–213."]
[null,"Khalaji S, Naderi AH, Mousavi SN, Zaghari M, Malakzadegan A. 2014. Determination of phosphorus requirement for post molted laying hens using nonlinear and multivariate nonlinear mixed effects models. J Poult Sci. 51: 22-28."]
[null,"Lamberson WR, Firman. 2002 JD.. A comparison of quadratic versus segmented regression procedures for estimating nutrient requirements. Poult Sci.; 81: 481-484."]
[null,"Mercer, L. P. 1982. The quantitative nutrient-response relationship. J. Nutr. 112:560–566."]
[null,"Mercer, L. P. 1992. The determination of nutritional requirements: Mathematical modeling of nutrient-response curves. J. Nutr.122:706–708."]
[null,"Mercer, L. P., N. W. Flodin, and P. H. Morgan. 1978. New methods for comparing the biological efficiency of alternative nutrient sources. J. Nutr. 108:1244–1249."]
[null,"Microsoft Corporation. One Microsoft way Redmond WA 98052"]
[null,"Morgan, P. H., L. P. Mercer, and N. W. Flodin. 1975. General model for nutritional responses in higher animals. Proc. Natl. Acad. Sci. USA 72:4327–4331."]
[null,"Pesti GM, Vedenov D, Cason JA, Billard L. 2009. A comparison of methods to estimate nutritional requirements from experimental data. Br Poult Sci.; 50:16-32."]
[null,"Pesti GM, Vedenov D. 2011. An economic comparison of several models fitted to nutritional response data. J Anim Sci. 89: 3344-3349."]
[null,"Robbins KR, Norton HW, Baker DH. Estimation of nutrient requirements from growth data. J Nutr. 1979; 109: 1710-1714."]
[null,"Robbins KR, Norton HW, Baker DH. Estimation of nutrient requirements from growth data. 1979. J Nutr. 109: 1710-1714."]
[null,"Robbins KR, Saxton AM, Southern LL. 2006 Estimation of nutrient requirements using broken-line regression analysis. J Anim Sci.; 84 suppl: E155-65."]
[null,"Scheffe, H. 1953. A method for judging all contrasts in the analysis of variance. Biometrika, 40: 87–104."]
[null,"Shearer KD. 2000. Experimental design, statistical analysis and modelling of dietary nutrient requirement studies for fish: a critical review. Aquacult Nutr. 6: 91–102."]
[null,"Simongiovanni A, Corrent E, Floc’h NL, van Milgen J. 2012. Estimation of the tryptophan requirement in piglets by meta-analysis. Anim.; 6: 594-602."]
[null,"Sterling KG, Vedenov DV, Pesti GM, Bakalli RI. 2005. Economically optimal dietary crude protein and lysine levels for starting broiler chicks. Poult Sci.; 84: 29-36."]
[null,"Strathe AB, Lemme A, Htoo JK, Kebreab E. 2011. Estimating digestible methionine requirements for laying hens using multivariate nonlinear mixed effect models. Poult Sci. 90: 1496-1507."]
[null,"van der Voet H, de Boer WJ, Souverein OW, Doets EL, van't Veer P. A 2014 Statistical method to base nutrient recommendations on meta-analysis of intake and health-related status biomarkers. PLoS ONE. 9: e93171."]
[null,"Vedenov D, Pesti GM. 2008.A comparison of methods of fitting several models to nutritional response data. J Anim Sci.; 6: 500-507."]
[null,"Vedenov D, Pesti GM. 2010.An economic analysis of a methionine source comparison response model. Poult Sci. 89:2514-2520."]
[null,"Waldroup PW, Oviedo-Rondon EO. 2002Models to estimate amino acid requirements for broiler chickens: a review. Int J Poult Sci. 1: 106-113"]
[null,"Whittemore CT. 1980. The use of a computer model in determining the nutrient requirement of pigs. Proc Nutr Soc.; 39: 205-211."]

{"sheet":"Instructions","index":2,"n_rows":13,"n_cols":1,"rows_kept":13,"cut":false,"hidden":false,"merged":[]}
["Do not move cells!"]
["1. Make changes in cells with yellow text and red backgrounds only"]
["2. On the \"Levels & Reps\" tab: "]
["          2a. Press the \"Create Grid\" button on the \"Levels & Reps\" tab "]
["          2b. If you want to adjust levels, edit directly in corresponding cells"]
["3. On the \"Simulations\" tab: "]
["          3a.  Select the baseline model which will be used to generate random data"]
["          3b.  Enter \"true\" coefficients of the baseline mode"]
["4. Provide guesses for coefficients for all remaining models (this is necessary to ensure convergence of Solver Routine)"]
["5. Select simulation parameters (number of \"experiments\" and coefficient of variation for random draws)"]
["6.. Press \"Run Simulations\""]
[]
["Note: If you end up with poor estimates for a particular model, try to provide more accurate initial guesses for the coefficients"]

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[]
[]
[null,"1. Experiment Design",null,null,null,null,null,null,null,null,"Experimental Grid"]
[]
[null,"Number of Levels (>1, < 25)",4]
[null,"Number of Reps (max = 20)",4]
[]
[null,"Minimum Nutrient Level",0.8]
[null,"Maximum Nutrient Level",1.8]
[null,null,null,null,null,"Levels"]
[null,null,null,null,null,1,2,3,4]
[null,null,null,"Replicates",1,0.8,1.1333333333333333,1.4666666666666668,1.8]
[null,null,null,null,2,0.8,1.1333333333333333,1.4666666666666668,1.8]
[null,null,null,null,3,0.8,1.1333333333333333,1.4666666666666668,1.8]
[null,null,null,null,4,0.8,1.1333333333333333,1.4666666666666668,1.8]

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[]
[]
[null,null,"1. Choose One Model to Simulate Experiments From",null,null,null,null,null,null,null,"3. Choose Simulation Parameters"]
[]
[null,null,"Model","True Parameters of the Response Function",null,null,null,null,null,null,"Selected (\"True\") Model",null,null,null,"BL"]
[null,null,null,"Max","Rate Constant","Requirement",null,null,null,null,"Number of Experiments (Max = 1000)",null,null,null,20]
[null,null,null,4.3600000000000003,-5.57,1.06,null,null,null,null,"Coefficient of variation (%)",null,null,null,0.08]
[null,null,null,"Max","Rate Constant","Requirement"]
[null,null,null,4.4783999999999997,-5.5972,1.3051999999999999]
[null,null,null,"Const","Linear","Quadratic"]
[null,null,null,-5.0503,14.5969,-5.5896999999999997]
[null,null,null,"Max","Rate Constant","Intercept","Kinetic Order"]
[null,null,null,17837.4902,380.33460000000002,-43.035600000000002,8.6400000000000005E-2]
[]
[]
[]
[null,null,"2. Select up to Four Model to Fit to Simulated Experiments"]
[]
[null,null,"Model","Initial Guesses for the Parameters of Fitted Functions"]
[null,null,null,"Max","Rate Constant","Requirement"]
[null,null,null,4.3600000000000003,-5.57,1.06]
[null,null,null,"Max","Rate Constant","Requirement"]
[null,null,null,4.3600000000000003,-5.6,1.06]
[null,null,null,"Const","Linear","Quadratic"]
[null,null,null,-5.05,14.6,-5.59]
[null,null,null,"Max","Rate Constant","Intercept","Kinetic Order"]
[null,null,null,17837.5,380.3,-43,0.08]
[]
[]
[]
[]
[null,null,"4. Results"]
[]
[null,null,"Experiment #","Model Fits"]
[null,null,null,"Broken Line Model",null,null,null,null,null,"Broken Line Quadratic Model",null,null,null,null,null,"Quadratic (2nd Order Polynomial)",null,null,null,null,null,"Saturation Kinetics"]
[null,null,null,"Max/Min","Rate Constant","Requirement","R-Squared","SE of Requirement",null,"Max/Min","Rate Constant","Requirement","R-Squared","SE of Requirement",null,"Const","Linear","Square","Requirement (Calculated)","R-Squared",null,"Max/Min","Rate Constant","Intercept","Kinetic Order","R-Squared"]
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