View source for Section 25 – International Beef Evaluation and Validation

= International Beef Evaluation and Validation =

== Introduction ==
Advances in reproductive technologies—such as artificial insemination and embryo transfer—together with reduced costs for storing frozen genetic material, have transformed bovine genetic trade from a largely local activity into a global market. As genetic material increasingly moves across borders, breeders need reliable ways to compare animals from different countries and make well-informed selection decisions. 

International genetic evaluations were developed to address this need, first in dairy cattle and later in beef cattle. However, beef cattle present specific challenges: production systems vary widely within and between countries, trait definitions are not always aligned, and evaluation methods differ. These challenges are further compounded by the potential for genotype-by-environment interactions. 

During the 2000s, studies across European countries highlighted the need for international beef evaluations that could account for these differences. In response, the ICAR Interbeef Working Group was established in 2006 to promote collaboration and harmonise recording and evaluation practices. The first international evaluations were conducted by the Interbull Centre in 2015, and the service has continued to evolve since then. 

Today, Interbeef evaluations combine performance data from multiple countries using multi-trait, multi-country models that account for differences in national evaluation systems. This approach allows estimation of breeding values that are comparable across populations while remaining meaningful within each country. 

Ensuring that these models produce unbiased and reliable results requires robust validation. While well-established validation methods exist for dairy cattle evaluations, they cannot be directly applied to beef cattle. Beef evaluations typically involve smaller and less connected contemporary groups, fewer progeny per sire, and fewer highly proven sires, partly due to the lower use of artificial insemination. These factors make it necessary to develop or adapt validation methods specifically for beef cattle data. 

The guidelines that follow provide a practical framework for international evaluations and validations of beef cattle. They outline key principles and recommended practices that can be applied across different systems and initiatives, supporting the continued improvement of global genetic evaluation services. 

== Applying Interbull Method II to Beef Evaluations ==

=== Background ===
Genetic evaluations estimate the breeding value of the animals based on data from the individual, its relatives, or both. The accuracy of the estimates depends on the quality of the records and the models used for the evaluation. A major concern is the bias of the estimate, or, in other words, the difference between the animals' expected and actual breeding values. Biased breeding values can lead to incorrect selection decisions and inaccurate estimates of genetic trends, so detecting and removing bias are therefore crucial.

The methods used to detect and measure the bias in the genetic models are known as validation methods. Validation is a key point in international evaluations, where different data and models are received from several countries. Countries utilizing models or data producing biased results can, over time, compromise the accuracy of international evaluations.

Since the 1990s, Interbull has developed and updated validation methods for dairy evaluations. No specific validation methods were yet available for the beef international evaluations due, among other things, to the relatively young age of the service, as the first official evaluations was launched in 2015. Recognizing the need for validation and the differences between the dairy and beef industries, adapting or developing specific validation methods for beef evaluations is a crucial step. To this end, the Interbeef Working Group and Interbull Centre have worked together to identify suitable methods for implementing a model validation for beef genetic evaluations. Their work led to adapting the Interbull validation Method II to beef evaluations.

The Interbull Method II should be applied at the national level before submitting data to the international evaluation. The results will be used to provide feedback to the National Genetics Evaluation Centres on the robustness of their genetic models and decide whether the data is suitable for inclusion in an international evaluation.

== Interbull Method II ==
The Interbull Method II was initially developed for dairy cattle evaluation, focusing on the variation in daughter yield deviation (DYD) within individual bulls. The method can also examine the progeny yield deviation (PD) variation in beef cattle.

== Objectives ==
To implement a standardized validation method (lnterbull Method 11) at the national level for beef genetic evaluations, ensuring that submitted data is unbiased and suitable for inclusion in international evaluations.

* Validate data from countries participating in the Interbeef evaluation to determine their eligibility for inclusion. This process aims to improve the accuracy of the international evaluations.
* Establish standardized validation methods for models at the country level, allowing countries to demonstrate that their evaluations are unbiased and meet international standards.

=== Responsibility ===
Countries calculating PD must use this method prior to submitting data to the Interbeef genetic evaluation.

== Motivation ==
This approach assumes that PD is independent from environmental influences (Boichard et al., 1995), which allows for assessing whether yearly effects impact PD. The method investigates the non-genetic trend over the years, with deviations from zero indicating biases in the genetic trend estimation.

=== Data ===
The PD is calculated based on the most recent national genetic evaluation incorporated into international evaluations within a year. PD is determined for each observation by considering the breeding value of the dam and other influencing factors but excluding the progeny's breeding value, as follows:
[[File:Formula 1 Section 25.jpg|center|frameless|243x243px]]
where:
[[File:Formula 2 Section 25.jpg|left|frameless|399x399px]]







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The target bulls to include in the analysis should be A. I. bulls that following these criterias:

* Have offspring in at least '''three consecutive years.'''
* Have at least '''three progeny per year.'''
* The progeny is present in at least '''three herds per year.'''


=== Action ===
The following model is used to analyse progeny individual deviations:

PD<sub>jj</sub> = S<sub>i</sub> + b<sub>j</sub> + e<sub>jj</sub>

where: 

* PD<sub>jj</sub>  represents the progeny yield deviation for sire ''S<sub>i</sub>'' in year ''j.''
* S<sub>i</sub> is the sire ''i''
* b<sub>j</sub> is the regression coefficient for year ''j.''
* e<sub>ii</sub> is the residual term.

The reference year (''j'' = 0) corresponds to when the bull's first progenies are born. 

=== Criterion ===
The value of ''b'' indicates the yearly trend for bulls. If ''b'' differs from zero, it suggests the presence of an environmental trend not accounted for in the model. To establish a straightforward pass/fail criterion, the absolute value of ''b'' (│''b''│) should not exceed 1% of the trait's genetic standard deviation.

=== Remarks ===
If the ''b'' value is positive ''(b'' > 0), this may indicate that the genetic trend is being overestimated. Conversely, a negative ''b'' value ''(b'' < 0) suggests that the trend is underestimated.

=== Outcome ===
The validation process will follow specific criteria, such as population size and genetic diversity, ultimately resulting in a "yes/no" outcome.

=== Limitations ===
The estimation of PDs must be based on models that do not consider maternal effects. The test must be applied to at least 150 bulls that meet the requirements.

== References ==


Boichard, D., B. Bonaiti, A. Barbat, and S. Mattalia. 1995. Three Methods to Validate the Estimation of Genetic Trend for Dairy Cattle. Journal of Dairy Science 78:431-437. doi:10.3168/jds.S0022-0302(95)76652-8