Contemporary Breeding Selection Criteria and Genomic Evaluation Strategies in Dairy Cattle

4. Effects of Local Environmental Factors and Morphological Traits on Milk Yield

In addition to global standardization models, understanding the local dynamics of genotype × environment interactions (GxE) is essential for regional adaptation and productivity. Regional studies examining how environmental variance operates at the local level and how specific physical conformation traits relate to production provide important feedback when applying global indices to local populations.

4.1 Studies at the Bahri Dagdas International Agricultural Research Institute

In Turkey, long-term studies conducted on Brown Swiss cattle by Mehmet Colak and his research team at the Bahri Dagdas International Agricultural Research Institute provide noteworthy findings in this context. In analyses of lactation records from Brown Swiss cattle raised under institute conditions between 1987 and 1999, the heritability of 305-day milk yield was estimated at 0.23 for first lactation and 0.19 across all lactations (Tilki, Colak & Sari, 2009).

4.2 The Relationship Between Udder Morphology and Milk Production

The same research group also examined in detail the relationships between udder morphology and phenotypic milk production. In studies investigating the effect of teat shape on milk yield and milking characteristics, teat shape was classified as cylindrical, funnel-shaped, and bottle-shaped (Tilki, Inal, Colak & Garip, 2005).

In another study, 400 teat canals were examined by ultrasonography, and 20% were found to have a crooked course while 80% followed a linear course. This anatomical variation did not produce a statistically significant difference in final milk yield. Measurements such as front and rear teat length, teat diameter, and post-milking udder height showed statistically significant changes across lactation order (P < 0.001).

4.3 Environmental Correction Factors: Comparing Turkish and Global Literature

Environmental correction coefficients derived from Bahri Dagdas studies show high agreement (90%+) with current global literature, including CDCB 305-AA, ICAR 2024, and JDS 2025:

Parity Coefficient (Base = 3rd-4th lactation = 1.00)

Age-at-Calving Coefficient (Base = 37-48 months = 1.00)

Season Coefficient (Base = Spring = 1.00)

5. Restructuring Economic Selection Indices: The NM$ 2025 Revision

The main mechanism through which genotypic data become actionable in the field is the economic selection index. In the United States, the principal national index is the Lifetime Net Merit Index (NM$), which estimates the net profit, in U.S. dollars, generated over the lifetime of the average daughter of a dairy animal. The NM$ formula includes approximately 40 economically relevant traits:

5.1 The Rise of Butterfat Value and the Relative Decline of Protein

In the 2025 economic model, the fat price per pound for Class III milk was increased from $2.10 to $2.80, while the protein price was kept fixed at $2.60:

5.2 Livability Versus Productive Life

Because the financial gap between a cow going to slaughter (economic recovery) and a cow dying on the farm (total loss) has widened, Cow Livability (LIV) and Heifer Livability (HLIV) now carry much greater weight. The overall emphasis on Productive Life (PL) has been reduced from 11.0% to 8.0%.

5.3 The Weight Tax

The old assumption that "a bigger cow produces more milk" has given way, in the genomic era, to the concept of metabolic efficiency. Increasing feed cost from $0.11 to $0.12 per pound, maintenance dry-matter requirement per lactation from 4.50 to 5.50 lb, and heifer-rearing cost from $0.75 to $0.85/lb has made large cows more expensive to maintain. A +1.0-point increase in BWC corresponds to -$57 in lifetime NM$, expressed economically as a "weight tax."

5.4 Innovations in Fertility Algorithms

The spread of sexed semen and beef-on-dairy crossbreeding has fundamentally changed reproductive economics. The 2025 model abandons the historical assumption of 100% conventional dairy semen and instead incorporates the use of 60% sexed dairy semen (at $25 per dose) and 40% conventional beef semen (at $10 per dose).

5.5 Relative NM$ Economic Weights by Breed (April 2025)

Table data: USDA ARR NM$9 2025 revision. RFI data are currently available only for Holsteins; because they are not measured in other breeds, the weights of other traits increase proportionally.

6. Feed-Efficiency Paradigms: Feed Saved (FSAV) and RFI

In dairy farming, more than half of total operating costs come directly from feed expenses. The Feed Saved (FSAV) trait, incorporated into genetic evaluations by CDCB in December 2020, is one of the central components of the "Income Over Feed Cost (IOFC)" optimization paradigm.

6.1 Definitions of FSAV and RFI

FSAV is a composite index synthesized from two components: Body Weight Composite (BWC) and Residual Feed Intake (RFI).

7. Genomic Adaptation to the Climate Crisis: Heat Tolerance

Rising environmental temperatures driven by global climate change are among the greatest biological risks threatening dairy production. Modeling studies project that uncontrolled heat stress could impose an annual economic burden of US$30 billion on the global dairy industry by 2050.

7.1 The Physiological Cascade of Heat Stress

Once THI exceeds the threshold, cows redirect blood flow from internal organs toward peripheral tissues in order to dissipate body heat. This results in the following pattern:

7.2 Reaction-Norm Models and Heat-Tolerance GEBVs

Zoetis and other genetic-research consortia have developed specific heat-tolerance genomic breeding values (GEBVs) by combining millions of test-day records with weather data. These evaluations focus on two traits: resistance to pregnancy-rate decline at increasing THI (CFS_THI) and resistance to milk-yield decline (MILK_THI). Validation studies have clinically confirmed that cows with high CFS_THI and MILK_THI transmitting abilities can maintain rectal temperatures below 39°C even during severe heat waves (≥25°C).

7.3 Molecular Biomarkers and the SLICK Variant

Genome-wide association studies (GWAS) have demonstrated that QTL on chromosomes BTA 3, 6, 14, and 17 are directly associated with heat tolerance. Transcriptomic analyses have shown that, under thermal stress, the expression of lactation-related genes in mammary tissue (α-casein, β-lactoglobulin) declines by 30-40%, while mitochondrial-fusion genes such as Mfn2 are downregulated.

8. Environmental Sustainability: Genomic Evaluation of Methane Emissions

Ruminant livestock production is responsible for approximately 14.5% of global greenhouse-gas emissions attributable to human activity. A major share of this comes from methane (CH₄), whose global warming potential is 28 times higher than that of CO₂. Methanogenic Archaea in the rumen combine metabolic hydrogen with CO₂ generated during fermentation to synthesize methane. This enteric methane represents an irreversible loss of 4-7% of the gross energy consumed by the animal.

8.1 ICAR Section 20: Framework for Genetic Evaluation of Methane

Through its Section 20 guidelines, the International Committee for Animal Recording (ICAR) has established the global technical framework for standard genetic evaluation of methane emissions in dairy cattle. Scientific studies have shown that methane production (MeP — g/day), methane intensity (MeI — g CH₄/kg milk), and methane yield (MeY — g CH₄/kg DMI) are measurable traits with heritability estimates ranging from h² = 0.12 to 0.35.

8.2 Methodologies for Measuring Methane

8.3 Milk MIR Spectroscopy: A Transformative Phenotypic Proxy

Because it is impossible to test millions of cows directly with measurement devices on a national scale, milk mid-infrared (MIR) spectroscopy has become the most important phenotypic proxy. During routine milk analysis, MIR devices read the absorption patterns of infrared light passing through milk samples and generate detailed spectral data. Partial least squares (PLS) regression models and artificial-intelligence algorithms combine these MIR spectra with milk yield, DIM, and parity information to estimate a cow's daily enteric methane production with an accuracy of R² = 0.60-0.70.

8.4 Canada’s Leadership: The Methane Efficiency (MEF) GEBV Model

The first country to integrate this technology into a national breeding program was Canada (the Lactanet consortium). After processing more than 13 million milk MIR records, Lactanet officially released a Methane Efficiency (MEF) GEBV for Holsteins in April 2023.

9. Herd-Level Sustainability Recording Traits (ICAR Section 22)

As of July 2023, ICAR has published Section 22, the guideline for "Sustainability Recording Traits." This framework defines 43 standardized traits that organizations can use to build their own sustainability indices. To eliminate climatic and seasonal bias statistically, nearly all of these traits are calculated over a 365-day rolling window.

9.1 Dry-Matter Intake and Methane Prediction Equations

For situations in which collecting actual feed-intake or methane-emission data at the farm level is impossible, ICAR provides comprehensive biomathematical prediction equations. The dry-matter intake estimate based on NASEM (formerly NRC) modeling is:

In high-forage scenarios, more complex regression equations based on dietary fiber and fat proportions are used for enteric methane (eCH₄), such as the Escobar-Bahamondes model. These formula sets allow genetic selection to be integrated with farm-management software and make sustainability targets statistically trackable.

10. Advanced Genomic Modeling: The Architecture of Single-Step Genomic BLUP (ssGBLUP)

In modern dairy cattle, single-step genomic BLUP (ssGBLUP) models have become the industry standard for converting phenotypic data into genetic merit (GEBV). The revolutionary feature of this methodology is its ability to combine pedigree records, phenotypic data, and SNP profiles from both genotyped and nongenotyped animals within one massive simultaneous system of equations.

10.1 The H Matrix: Combining Pedigree and Genomic Information

In classical BLUP, the genetic variance-covariance structure is modeled solely by the pedigree-based numerator relationship matrix (A). However, this approach cannot capture the fact that full siblings receive different gene combinations through Mendelian sampling. ssGBLUP merges the pedigree matrix (A) and genomic matrix (G) to create a composite combined relationship matrix (H):

10.2 Blending and Scaling

The incompatibility between A and G arises because pedigrees typically cover only a few generations, whereas SNP markers reflect mutation history over thousands of years. This mismatch in base population can lead to overprediction in the genomic values of young bulls. The blending operation is:

10.3 Unknown Parent Groups (UPG) and Metafounders

To address problems caused by incomplete pedigree data, Unknown Parent Groups (UPG) and the more advanced concept of Metafounders (MF) are integrated into the H⁻¹ matrix. These concepts account for the genetic level of the generation to which missing ancestors belong, preventing animals with unknown parents from collapsing to zero in the model and distorting the genetic trend. Modern computational software solves multiple traits and data from tens of millions of animals through these matrix structures, forming the statistical foundation of the genomic era.

11. Practical Breeding-Selection Criteria and Next-Generation Traits

After reviewing the theoretical background and global indices, it is necessary to present, in hierarchical order, the concrete criteria that determine a cow's breeding potential at the field level. The table below summarizes the main criteria that should be considered in modern dairy-cattle breeding decisions, in order of priority:

11.1 Milk-Protein Genetic Variants: A2A2 and κ-Casein BB

The beta-casein A2A2 genotype means that the β-casein protein in milk contains only the A2 variant. Epidemiological studies have suggested that the A1 variant releases the bioactive peptide beta-casomorphin-7 (BCM-7) during digestion and may be associated with gastrointestinal discomfort in some individuals. The global A2 milk market is expanding rapidly, and cows with the A2A2 genotype can provide a premium-pricing advantage for producers.

The kappa-casein (κ-CN) BB genotype is critically important for cheese manufacture. Compared with milk from AA cows, milk from BB cows has better coagulation properties and increases cheese yield by 5-10%. Given the share of cheese production in Turkey's total milk utilization, selection for κ-CN BB carries clear strategic economic value.

11.2 Integration of Genomic Testing

12. Breeding Selection Practice and Institutional Infrastructure in Turkey

In Turkey, dairy-cattle breeding is coordinated by the Central Association of Cattle Breeders of Turkey (DSYMB) and its provincial associations. The milk-recording system captures milk yield, fat, and protein percentages using A4 (monthly recording) and AT (alternate testing) methods. Herdbook records are maintained in accordance with ICAR standards.

12.1 Current Situation and Challenges in Turkey

12.2 Practical Recommendations

13. Conclusion and Future Perspective

Breeding selection in dairy cattle is no longer simply a matter of choosing "the bull that produces the most milk." It is now a multidimensional decision process that integrates biological efficiency, environmental sustainability, animal welfare, and economic optimization. The spread of genomic technologies, the update of phenotypic standardization through 305-AA, the restructuring of economic indices such as NM$ 2025, and the rise of advanced statistical models such as ssGBLUP as industry standards are the core pillars of this transformation.

The dairy cow of the future will be an "eco-sustainable" animal that produces milk rich in fat and protein, consumes less feed (negative RFI), emits less methane, resists heat stress, remains healthy, and lives longer. Achieving this goal will only be possible through the integrated application of accurate phenotypic data collection, reliable genomic evaluation, and science-based selection decisions.

14. References