Related Experiment Video
Updated: Mar 2, 2026
05:56
Demonstrating a Linear Relationship Between Vascular Endothelial Growth Factor and Luteinizing Hormone in Kidney Cortex Extracts
Published on: January 22, 2020
5.3K
Modelling female fertility traits in beef cattle using linear and non-linear models
H Naya1,2, F Peñagaricano3,4, J I Urioste2
1Unidad de Bioinformática, Institut Pasteur de Montevideo, Montevideo, Uruguay.
Summary
Accurate modeling of beef cattle fertility is crucial for genetic improvement. Non-linear models better capture genetic variation for calving success and failed oestrus, while linear models suit days from first calving.
Area of Science:
- Animal Genetics and Breeding
- Quantitative Genetics
- Livestock Production Systems
Background:
- Beef cattle fertility traits are vital for profitability but challenging to measure accurately in extensive systems.
- Limited and incomplete fertility records, coupled with strong environmental influences, hinder genetic improvement efforts.
- Novel approaches to model genetic variation in female fertility are essential for advancing breeding strategies.
Purpose of the Study:
- To evaluate the performance of different statistical models for analyzing beef cattle female fertility traits.
- To compare linear and non-linear modeling approaches for endpoints like calving success, days from first calving, and failed oestrus.
- To assess the impact of model choice on heritability estimates and the selection of superior sires.
Main Methods:
- Assessed linear (Gaussian, Poisson) and non-linear (probit, censored Poisson, censored Gaussian) models.
- Applied models to three distinct fertility endpoints: calving success (CS), days from first calving (CD), and failed oestrus (FE).
- Compared model fit, heritability and repeatability estimates, and sire selection consistency across models and endpoints.
Main Results:
- Non-linear models provided a better fit for failed oestrus (FE) and calving success (CS) endpoints.
- Linear models were more appropriate for analyzing days from first calving (CD).
- Non-linear models yielded substantially higher heritability and repeatability estimates compared to linear models.
Conclusions:
- The choice of statistical model significantly impacts the estimation of genetic parameters and sire rankings for beef cattle fertility.
- Non-linear models are recommended for endpoints like FE and CS, while linear models are suitable for CD.
- Accurate endpoint selection and appropriate modeling are critical for effective genetic improvement of female fertility in beef cattle.
Related Concept Videos
01:29Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
375
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
375
01:25Modeling with Differential Equations
129
Population dynamics can be described mathematically by considering the population size P(t) as a function of time. The rate of change of the population is then represented by the derivative of P(t). A simple assumption is that the rate of growth is proportional to the size of the population itself. This leads to an exponential growth model, where the population increases rapidly without bound. While this is a useful first approximation, it does not reflect realistic long-term...
129
01:15Model Approaches for Pharmacokinetic Data: Physiological Models
326
Physiological models in pharmacokinetics are instrumental in understanding the distribution and elimination of drugs within the body. These models describe the drug concentration within target organs, influenced by factors such as drug uptake, tissue volume, and blood flow. Drug uptake is governed by the partition coefficient, which signifies the drug concentration ratio in tissue to that in the blood. The blood flow rate to a specific tissue is expressed as Qt, and the rate of change in tissue...
326
01:23Mechanistic Models: Compartment Models in Individual and Population Analysis
310
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
310
01:13Parameters Affecting Nonlinear Elimination: Zero-Order Input, First-Order Absorption and Two-Compartment Model
377
Drugs administered through various routes can lead to nonlinear elimination, resulting in complex pharmacokinetic behaviors crucial to understanding efficacious drug dosing.
When a drug is administered through a constant intravenous infusion and eliminated via nonlinear pharmacokinetics, it follows zero-order input. For example, oral drugs undergo first-order absorption upon administration and are eliminated through nonlinear pharmacokinetics.
In the case of subcutaneously administered drugs,...
When a drug is administered through a constant intravenous infusion and eliminated via nonlinear pharmacokinetics, it follows zero-order input. For example, oral drugs undergo first-order absorption upon administration and are eliminated through nonlinear pharmacokinetics.
In the case of subcutaneously administered drugs,...
377
01:22Nonlinear Pharmacokinetics: Causes of Nonlinearity
815
Nonlinearity in drug pharmacokinetics is caused by various factors influencing how a drug is absorbed, distributed, metabolized, and excreted. Understanding these nonlinear processes is crucial for predicting drug behavior in the body and optimizing drug dosing regimens.
Nonlinear drug absorption can occur when the process is rate-limited by solubility, carrier-mediated transport systems, or saturation of the presystemic gut wall or hepatic metabolism. For instance, high doses of riboflavin...
Nonlinear drug absorption can occur when the process is rate-limited by solubility, carrier-mediated transport systems, or saturation of the presystemic gut wall or hepatic metabolism. For instance, high doses of riboflavin...
815