A Dynamic Tool to Describe Lamb Growth and Its Use as a Decision Support System

• Published in: Animals (Basel) Vol. 14; no. 15; p. 2246
• Main Authors: Amaral, Rafael Marzall, Rodrigues, Marcelo Teixeira, Schultz, Erica Beatriz, Reis, Cristiano Eduardo Rodrigues
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 02-08-2024
• Subjects: Animal behavior; Animals; Body fat; Cattle; Datasets; Decision-making; Diet; Energy; energy efficiency; Environmental impact; Feedback; feedlot; Feeds; Growth; growth curve; Livestock; Management decisions; Metabolism; Metabolites; Nutrients; Nutrition; Ordinary differential equations; performance simulation; Physiological aspects; Proteins; Requirements; Simulation; Simulation methods; Software; system dynamics; feedlot; growth curve; system dynamics; performance simulation; energy efficiency
• ISSN: 2076-2615; 2076-2615
• DOI: 10.3390/ani14152246

A dynamic model has been developed to simulate aspects of feedlot lamb growth and body composition, including energy and protein requirements, growth rate, composition of gain, and body mass. Model inputs include initial body mass (kg), standard final mass (kg), age (days), and dietary energy concentration (Mcal·kg
). The model was assessed as a decision support tool using a dataset of 564 individual measures of final body mass and diet energy. The simulations provide graphical and numerical descriptions of nutrient requirements, composition of gain, and estimates of animal performance over time. The model is accurate and precise, with a root mean squared error of 7.79% of the observed final body mass and a coefficient of determination of 0.89 when simulating the same variable. The model can be used as a reliable decision support tool to estimate final body mass and the days on feed required to reach a certain final mass with precision and accuracy. Moreover, the dynamic model can also serve as a learning tool to illustrate practical principles of animal nutrition, nutrient requirement relationships, and body composition changes. This model holds the potential to enhance livestock management practices and assist producers in making informed decisions about feedlot lamb production.