The Ruminant Nutrition System (RNS) is a comprehensive nutrition model that integrates cattle, sheep and goats into one platform. The RNS was developed to provide a framework that can be used for incorporating and implementing new scientific knowledge and submodels to more accurately predict nutrient requirements and biological values for ruminants currently used in food production. The RNS has a modern design and interface that uses an integrated object-oriented programming approach to allow for quicker and customized simulations. The RNS structure permits power users to expand their simulation routines through the R script programming.
Click here to go to the RNS web page (not available)
The Large Ruminant Nutrition System (LRNS) is a computer program that estimates beef and dairy cattle requirements and nutrient supply under specific conditions of animal type, environment (climatic factors), management, and physicochemical composition of available feeds, using the computational engine of the Cornell Net Carbohydrate and Protein System (CNCPS) model as published by Fox et al. (2004).
Click here to go to the LRNS web page
The Small Ruminant Nutrition System (SRNS) model is the result of a joint collaboration among Texas A&M University, Cornell University, and Sassari University. The SRNS is a computer model to predict nutrient requirements of sheep and feed biological values on farms based on the structure of the Cornell Net Carbohydrate and Protein System (CNCPS) for Sheep.
Click here to go to the SRNS web page
The Cattle Value Discovery System (CVDS) was developed for use in individual cattle management for growing beef cattle. The CVDS provides (1) prediction of daily gain, incremental cost of gain and days to finish to optimize profits and marketing decisions while marketing within the window of acceptable carcass weights and composition, (2) predictions of carcass composition during growth to avoid discounts for under or over weight carcasses and excess backfat, and (3) allocation of feed fed to pens to individual animals for the purpose of sorting of individuals into pens by days to reach target body composition and maximum individual profitability.
Click here to go to the CVDS web page
The Model Evaluation System (MES) was developed to assist on the adequate evaluation of mathematical models using statistical analysis, including linear regression analysis, mean square error of the prediction, concordance correlation coefficient, distribution analysis, deviation analysis, graphics and histogram, robust statistics, etc.
Click here to go to the MES web page
The Gamma Distribution-like Degradation and Passage Models (GnG1) was developed based on theoretical concepts and probability to generalize the rumen processes of fiber digestion, assuming a gamma distribution. It can be used to interpret fiber degradation and passage profiles. The GnG1 model was evaluated for quality of fit using in vitro fiber degradation profiles and in vivo fiber passage profiles. The integration of digestion and passage is based on the concept that fibrous digesta in the rumen is heterogeneous (Vieira et al., 2007a,b,c).
Click here to go to the GnG1 web page
The in vitro gas production technique has been frequently used to assess biological values of feeds based on their pattern of accumulated gas during incubation with rumen fluid under anaerobic conditions. After data is collected, kinetic parameters that accurately describe the pattern of fermentation can be obtained. Several models have been described and used to fit in vitro gas production data to nonlinear functions (López et al., 1999). The GasFit System was developed to evaluate several nonlinear models in fitting gas production data.
Click here to go to the GasFit web page
A mechanistic model is presented to adjust the fractional rate of fermentation of available fiber based on the estimate of unavailable fiber and the computed theoretical unavailable fiber using lignin content. The object of this computer program is to generate a system by which values for rate of digestion and its retardation can be predicted and used in the field. At the present time there is no system for deriving digestion rates apart from those in the feed dictionary. Analytical values available in the field, include NDF, ADF, lignin, crude protein (CP) and sometimes in vitro digestibility at 24 or 30 h. Rates of digestion and DU will need to be predicted from these observations.
Click here to go to the NDF kd web page
The Meal Criterion Calculation (MCC) software was designed to analyze cattle feeding behavior data collected by the GrowSafe System to compute feedbunk visit interval (BVI) and meal criterion (MC). MC is the longest non-feeding time that defines a meal. It is calculated as the intersection of two distributions: the non-feeding time within a meal and the non-feeding time between meals. MCC works with different distribution forms (normal, gamma, log-normal, Weibull) and unlimited number of animals and data records. The R software is required and can be download here.
The Hay Game is a stand-alone computer software based on the Beer Game. The Beer Game was developed to introduce students, managers, and executives to concepts of system dynamics. The purpose of the game is to illustrate the key principle that "structure produces behavior." Players of the Hay Game experience system complexity and provides insights of the long-term effects during the course of the game. The objective of the Hay Game is to minimize the total cost of hay utilization in a farm.
Click here to go to the Hay Game web page
Nim is a classical, simple game of logic and strategy, but with finite possibilities. The rule is that you may remove as many matches within a row in one move. The looser is who removes the last match on the table. There are several variations of the Nim game, including different objects, rules (winner is the one that removes the last object), number of rows of objects, max number of objects that can be removed at a time, and amount of objects. Good luck!
Current Nim Game version is 1.5
Commonly used modeling terminology can be found here.