Introduction
The Australian Wagyu Association’s (AWA) transition from BREEDPLAN Estimated Breeding Values (EBVs) to Wagyu Breeding Values (WBVs) is not a simple rebranding of genetic outputs. It is the result of a deliberate, multi-year investment in data infrastructure, genomic capability, statistical modelling, and governance that now allows AWA to independently deliver a Wagyu-specific genetic evaluation.
Here we outline the technical foundations that make this transition possible and explains why this capability did not exist previously.
The Scale and Maturity of Wagyu Data
Genetic evaluation systems are fundamentally limited by the quantity, quality, and structure of available data. Over the past six years, AWA’s Wagyu dataset has expanded at a pace that fundamentally changed what is technically feasible.
AWA now delivers the largest Wagyu genetic evaluation in the world, analysing more than 400,000 animals from breeders across 42 countries, with data volumes continuing to increase on a fortnightly basis
Compared with earlier BREEDPLAN parameter updates, the available data has:
- Nearly tripled in total animal numbers
- More than quadrupled the amount of animal performance records
- Increased genomic coverage by more than 600%
- Seen the largest growth in carcase traits, driven primarily by AWA’s MIJ camera program
This scale of Wagyu-specific data allows genetic parameters, heritabilities and trait correlations to be more accurately estimated directly for Wagyu.
Genomics as a Structural Foundation
Unlike many beef breeds where genomics is a smaller relative input into genetic evaluations, genomics has become foundational to the Wagyu genetic evaluation. AWA’s analysed dataset now includes close to half a million genotypes, spanning fullblood, purebred, and crossbred animals.
This genomic depth enables:
- Single-step genomic evaluation across animals with differing Wagyu content
- Effective utilisation of crossbred data, particularly F1–F3 carcase records
- Higher prediction accuracy earlier in an animal’s life
- Improved stability of breeding values as new data accumulates
The volume and structure of this genomic information is a critical enabler of WBVs. The vast amount of genomic data across a narrow population base delivers great improvements in reliability and accuracy.
Wagyu-Specific Trait Definitions and Measurement
A further constraint of earlier EBV systems was the need to operate within generic trait definitions. As Wagyu production evolves, this becomes increasingly limiting through the ability to update parameters within AWA’s genetic evaluation and to understand new traits and develop genetic estimates for these.
AWA is now able to move to WBVs because it controls:
- Trait definitions
- Measurement standards
- Data pipelines from collection to analysis
A key example is marbling fineness. The introduction of the MIJ New Fineness Index reflects a fundamentally different trait from earlier fineness measures, particularly at modern high marble scores (often >DMS 9). The volume of new fineness data now available makes it statistically valid to re-parameterise this trait within a Wagyu-specific model
Similarly, the redefinition of the Milk EBV into a Maternal Weaning Weight WBV and redefinition of the Eye Muscle Area trait reflects improved biological understanding and more accurate modelling based solely on Wagyu data rather than legacy assumptions
Independent Genetic Evaluation Capability
A critical enabler of the EBV to WBV transition is AWA’s ability to operate its own genetic evaluation pipeline.
Between 2021 and 2025, AWA undertook a structured system renewal program that included:
- A board-level review of genetic and databasing capabilities
- Competitive assessment of service providers
- Development of an independent evaluation pipeline
- Integration with AWA’s Helical member database
This infrastructure allows AWA to:
- Update genetic parameters when data volumes justify it
- Introduce new traits without external dependency
- Run evaluations weekly rather than on longer cycles
- Rapidly deliver results following DNA testing and registration
Statistical Justification for Transition
Comparative analyses between EBVs and WBVs demonstrate that the transition is statistically robust. For most traits, particularly growth, Carcase Weight, and Marble Score, WBVs are strongly correlated with EBVs, with correlations exceeding 0.9.
Where significant data is available for animals such as proven sires, we see very high relatedness between EBVs and WBVs, with most correlations exceeding 0.95.
Where greater re-ranking occurs (notably Maternal Weaning Weight and Eye Muscle Area), the differences are explained by:
- Corrected Wagyu-specific trait relationships
- Improved multi-trait modelling
- Removal of legacy parameter constraints
Governance and Risk Management
The AWA Board established a clear mandate to ensure that investment in genetic services:
- Maximises member value
- Reduces reliance on external systems
- Minimises long-term operational risk
WBVs represent the execution of that mandate, supported by staged delivery, member communication, and training prior to EBVs being retired in February 2026.
Conclusion
AWA is able to move from EBVs to WBVs because the Wagyu industry has reached a point of data maturity, genomic scale, and analytical capability that did not previously exist. WBVs are the natural outcome of:
- Substantially larger and richer Wagyu datasets
- Genomics as a core evaluation input
- Wagyu-specific trait definitions
- Independent, modern genetic evaluation infrastructure
The transition positions AWA to continue refining genetic tools as data grows, ensuring that Wagyu breeders have access to the most accurate, relevant, and future-proof genetic information available.