Comparative evaluation of exterior linear traits in Holstein cows under the conditions of the Republic of Kazakhstan

Avaliação comparativa de características lineares externas em vacas holandesas na República do Cazaquistão

Abstract

The research aims to determine the selection parameters of Holstein cattle bred in the Republic of Kazakhstan, to conduct a linear assessment of the exterior of Holstein cows according to 18 indicators. It was established that the dairy productivity of first-calf heifers of AF Rodina LLC amounted to 9,520 kg in milk yield, 3.6% in fat, 3.1% in protein, ICE LLC - 9,800 kg in milk yield, 3.7% in fat, 3.2% in protein, Bayserke-Agro LLC - 8,830 kg in milk yield, 3.7% in fat, 3.6% in protein, in RZA - Asyl Tulik LLC - milk yield - 8,147 kg, fat - 3.5%, protein - 3.3%. The conducted studies showed that the dairy productivity of cows of the 2nd, 3rd, and 4th lactation in AF Rodina LLP averaged 10,932 kg of milk with fat content in milk of 4%, and protein content in milk of 3.1%, respectively. In ICE, the milk yield was 10,700 kg, fat was 3.9%, and protein was 3.3%. In Baiserke-Agro dairy productivity was 8,436 kg, fat - 3.7%, protein - 3.4. In RZA- Asyl Tulik milk yield averaged 8,500 kg, fat - 3.5%, protein - 3.2%. It was found that the average exterior indicators of Holstein cows from the base farms differed significantly from the optimal scores, while most of the exterior indicators of ICE LLC were within the range close to the desired values.

Keywords:
holstein breed; productivity; linear assessment; exterior; milk yield; fat; protein

Resumo

A pesquisa teve como objetivo determinar os parâmetros de seleção de bovinos da raça Holandesa criados no Cazaquistão, realizando uma avaliação linear das características externas das vacas Holandesas de acordo com 18 indicadores. Constatou-se que a produtividade leiteira de novilhas de primeira cria da AF Rodina LLC foi de 9.520 kg de leite, 3,6% de gordura e 3,1% de proteína; da ICE LLC, 9.800 kg de leite, 3,7% de gordura e 3,2% de proteína; da Bayserke-Agro LLC, 8.830 kg de leite, 3,7% de gordura e 3,6% de proteína; e da RZA-Asyl Tulik LLC, 8.147 kg de leite, 3,5% de gordura e 3,3% de proteína. Os estudos realizados demonstraram que a produtividade leiteira de vacas na 2ª, 3ª e 4ª lactações na AF Rodina LLP atingiu em média de 10.932 kg de leite, com teor de gordura de 4% e teor de proteína de 3,1%. Na ICE, a produção de leite foi de 10.700 kg, com 3,9% de gordura e 3,3% de proteína. Na Baiserke-Agro, a produtividade leiteira foi de 8.436 kg, com 3,7% de gordura e 3,4% de proteína. Na RZA-Asyl Tulik, a produção média de leite foi de 8.500 kg, com 3,5% de gordura e 3,2% de proteína. Constatou-se que os indicadores externos médios das vacas da raça Holandesa das fazendas de base diferiram significativamente dos valores ótimos, enquanto a maioria dos indicadores externos da ICE LLC estava dentro da faixa próxima aos valores desejados.

Palavras-chave:
raça holandesa; produtividade; avaliação linear; exterior; produção de leite; gordura; proteína

1. Introduction

In Kazakhstan, the Holstein Black-and-White breed occupies a leading position in milk productivity among dairy cattle breeds (Chindaliyev et al., 2023; Bekenov et al., 2019; Bissembayev et al., 2023a; Baimukanov et al., 2024a).

Due to high milk productivity rates associated with the use of high genetics of Holstein cattle, adaptive qualities, and suitability for intensive use, this breed is widespread in the world and Kazakhstan (Shamshidin et al., 2024; Semenov et al., 2021a, b).

To develop and substantiate methods for estimated breeding value for dairy cattle based on breeding traits using the BLUP AM (Best Linear Unbiased Prediction - Animal Model) and weighting economic coefficients, as well as the creation of software products, it is necessary, firstly - to limit selectable traits that affect the dairy cattle productivity (e.g. milk yield, fat, protein and other factors) (Yelemesov and Baimukanov, 2020), secondly – about the assessment of the economic significance of traits: conducting an analysis of the economic efficiency of each breeding trait and determining weighting factors depending on their contribution to overall productivity and profitability (Chindaliyev et al., 2021), thirdly – collection and systematization of data on livestock productivity, health, breeding record and other characteristics of breeding significance (Baimukanov et al., 2021), fourthly – development of the BLUP AM model, taking into account the genetic structure of the population and the use of methods for assessing the best linear unbiased predictions to obtain estimates of genetic parameters (Zhumanov and Baimukanov, 2020). As a result – creating software products for automating the calculation of estimated breeding value based on BLUP AM for the Kazakhstani cattle population.

When creating high-productivity herds, it is necessary to take into account the genetic potential of both bulls and cows, depending on the breed characteristics and conditions in the zone. To assess the genetic value of animals, it is most appropriate to use the BLUP methodology. The accuracy of predicting the breeding value of animals using the best linear unbiased forecasts exceeds 80%. This approach allows achieving an economic effect in cattle herds much earlier than traditional selection methods and contributes to selection progress in the population (Bissembayev et al., 2023b, c, d). Numerous studies demonstrate high efficiency in predicting a breeding value in both bulls and cows of different breeds (Bissembayev et al., 2024; Baimukanov et al., 2024b).

In Kazakhstan, the assessment of the characteristics of dairy cattle herds and populations is based on the phenotypic indicators of milk productivity of cows, so studies comparing the genetic value of animals based on their phenotypic indicators are relevant.

1.1. The aim of the research

To determine the selection parameters of Holstein cattle bred in the Republic of Kazakhstan, to conduct a linear assessment of the exterior of Holstein cows based on 18 indicators.

2. Materials and Methods

The object of the study is a population of cows of the Holstein black-and-white breed in the Republic of Kazakhstan.

The formation of an array of productive indicators (milk yield, kg, % fat and protein, somatic cells) for each animal being assessed was carried out based on downloading the database of the Republican Livestock System “Information and Analytical System” (Chindaliyev et al., 2021).

2.1. Main criteria for linear evaluation

The breeding value of dairy cows and bulls is determined by milk yield, milk fat, and milk protein, and is calculated as follows: a) for cows – after the completion of lactation; b) for bulls – when data on the productivity of daughters over 305 days of lactation are available.

The calculation of estimated breeding value (EBV) of dairy cows and bulls is carried out based on the BLUP AM method.

Composite and specific selection indices are calculated taking into account: a) breeding value (EBV) for milk yield, milk fat, and milk protein; b) weighting coefficients for milk yield, milk fat, and milk protein in accordance with the methodologies applied in breeding work in the member states; c) information on population averages and standard deviations of selection indicators published on the websites of the authorized bodies of the member states in the field of animal breeding (Eurasian Economic Commission, 2020).

The linear assessment of the exterior of first-calf heifers was carried out following the rules (Kazakhstan, 2023), the Methodological Guide for the linear assessment of the exterior of Holstein cows (Kazakh Research Institute of Animal Husbandry and Feed Production, 2017) and ICAR recommendations (ICAR, 2023) for at least 18 individual exterior indicators (Yelemesov and Baimukanov, 2020).

The results of the linear assessment of exterior indicators were uploaded to the database of the Republican Livestock System “Information and Analytical System” (Republican Livestock System, 2026).

Observers and standardization to ensure consistency in the evaluation of selected animals were carried out in accordance with the requirements of experimental practice in animal husbandry (Baimukanov et al., 2024a).

Classification of cows according to a set of body type characteristics:

1. General view

To the classification feature Dairy Strength, the following individual linear traits of animals are related: rib structure, chest width, stature, body depth, rump angle, and rump width specific weight of the classification feature “Dairy Strength” in the structure of the general complex class of animals is 40%.

Description of cows that have an ideal "general appearance" according to individual characteristics:

The head is proportional to the body;

The middle part is relatively concerning to the height of the animal, giving the body volume, strength, and, power;

The shoulder blade is long and deep, positioned evenly to the chest, and withers;

The chest is deep and broad with good sprung front ribs. The base of the chest is wide with sufficient distance between the legs;

The chest volume is large, full in the area of the scapular fossa and elbow joint;

The back is strong and straight;

The loin is broad and slightly arched. The middle part is barrel-shaped;

The rump is long and wide;

The hip bones are wide, clearly protruding, but not sticking out;

The hip joints are high and wide, located in the center between the hip bones and the ischial tuberosities;

The ischial tuberosities are widely spaced;

The ribs are elastic, and widely spaced with a wide intercostal space, especially between the last two ribs;

The sigh is deep and clearly expressed;

The thighs are lean, flat, broad, and set wide apart, providing adequate space for the udder and its attachment;

The body type characteristics during classification must correspond to the assessment given by the boniter when considering the linear characteristics.

The specific weight of linear exterior features in the structure of the classification feature «Dairy Strength»:

Rib Structure (RS) – 30%;

Chest Width (CW) – 15%;

Stature (St) – 15%;

Body Depth (BD) – 15%;

Rump Angle (RA) – 15%;

Rump Width (RW) – 10%.

2. Mammary

The "Mammary" linear features include: udder depth, fore udder attachment, central ligament, rear udder height, rear udder wide, front teat position, rear teat position, and teat length. The specific weight of the classificatory feature " Mammary " in the structure of the general complex class is 40%.

Description of cows with ideal " udders " according to individual characteristics:

The udder is long, wide, and firmly attached to the body;

The udder bottom is horizontal and located 4- 5 cm above the hock joint.

The central ligament is strong, clearly dividing the udder into halves;

The udder is visible from the side of the mirror, deepening downwards towards the rear teats;

The udder consistency is soft to the touch, elastic, and falls off well after milking;

The rear udder is wide, high, and firmly attached, slightly rounded towards the base of the bottom;

The fore udders are firmly and smoothly connected to the body and are slightly pushed forward;

Teats of equal size, moderate length and diameter, cylindrical in shape, positioned vertically in the center of each quarter when viewed from the side;

The milk veins are long, tortuous and branched;

The udder characteristics during classification must correspond to the assessment given by the boner when considering individual linear characteristics.

The proportion of linear features in the structure of the classification feature "Mammary":

Udder Depth (UD) – 16%;

Fore Udder Attachment (FUA) – 18%;

Central Ligament (CL) – 16%;

Rear Udder Height (RUH) – 15%;

Rear Udder Widht (RUW) – 13%;

Front Teat Position (FTP) – 10%;

Rear Teat Position (RTP) – 8%;

Teat Length (TL) – 4%.

3. Legs/feet

The classification feature "Legs/Feet" includes the linear features: rear legs set, rear legs rear view, hock development, and foot angle. The specific weight of the qualification feature “Legs/Feet” in the structure of the general complex class is 20%.

Description of a cow with ideal "Legs/Feet" according to individual characteristics:

The hooves are short, and rounded with a deep back wall and a flat sole;

Pasterns are strong, medium length, flexible but elastic;

Forelegs are straight and wide apart with straight hooves;

The rear legs, when viewed from the side, are springy, slightly bent at the hock. When viewed from behind, they are straight, wide and parallel;

The hock joint is well-defined, free from roughness and swelling, and dry, the bones are even, strong, and durable with well-defined tendons;

The most important feature in the characterization of the limbs is the condition of the hooves. With a low score on the linear system for “foot angle” the classification score for legs and hooves cannot be high;

“Legs/Feet” features during classification must correspond to the assessment given by the classifier when considering individual linear features.

The proportion of linear features in the structure of the classification feature “Legs/Feet”:

Rear Legs Set (RLS) – 20%;

Rear Legs Rear View (RLV) – 25%;

Hock Development (HD) – 10%;

Foot Angle (FA) – 45%.

4. The general analysis and calculations based on the estimated values were interpreted into a comprehensive classification of the cow body type on a 100-point scale, following the Methodological Guide for the linear assessment of the exterior of Holstein cows (Tleulenov et al., 2017), according to improved Formulas 1 and 2 for calculating three groups of classification features (Dairy strength, mammary, legs/feet), which allow calculating the result of the assessment of a group of classification features of the cow's exterior and exclude exceeding 100 points.

$I_G={\displaystyle \sum }_i^n\left(E{S}_{G,i}\times k_{G,i}-100\right)$ (1)

where: I_G – Final assessment of a group of classification features (Dairy strength, mammary, legs/feet); k_G,i – the contribution coefficient of the i -th exterior indicator to the G -th group of classification features; ES_G,i – is calculated using the following formula:

$E{S}_{G,i}=100\%-\frac{\left|X_i-X_{opt,i}\right|}{4+\left|X_{opt,i}-5\right|}\times 100\%$ (2)

where: ES_G,i – classification score for the exterior feature; X_i – assigned score for the exterior feature; X_opt,i – optimal score for the exterior feature.

The calculation of the final score (points) for the cow's exterior can be presented in the form of the following Formula 3:

$I_E={{\displaystyle \sum }}_{G=1}^3{I}_G*K_G$ (3)

where, I_E – final score for the cow’s exterior; K_G – contribution coefficient of the G -th group.

5. To develop statistical models of the development of selective traits in a population, mixed-type models will be used according to Formula 4:

$y_{ij}=h_i+a_{ij}+e_{ij}$ (4)

where: y_ij – indicator of the trait of the j- th animal in the i-th environmental conditions; h_i – effects of environmental conditions (fixed); a_ij – additive genetic effect o the j-th animal in i-th environmental conditions (EBV) (randomized); e_ij – the effect of factors not taken into account in the model (randomized).

To calculate the estimated breeding value of cows and bulls of the dairy productivity direction according to the developed optimal statistical models, the following was used: equation of the form BLUP AM according to Formula 5.

$\text{y = Xb + Za + e}$ (5)

where: y = n×1 – vector of observations (assessments) (n – number of records); b = p×1 – vector of fixed effects (p – number of levels of fixed effects); a = q×1 – vector of random effects of probands (q – number of levels of random effects); e = n×1 – vector of random effects; X is the pore order matrix that relates animal scores to fixed effects; Z is a matrix of nxq order that relates the animal score to the random effects.

The implementation of software products for estimated breeding value indices was carried out in the C++ programming language (version C++17) using the standard template library of the C++ language (STL C++), in the Microsoft Visual Studio 2019 development environment.

3. Results and Discussion

The following selection traits for Holstein cattle have been determined: milk yield (kg), fat (kg, %), protein (kg, %), somatic cells (thousand units), and linear assessment of cow exterior (score).

The data on the productivity of 1011 cows (Table 1) and information on ancestors (Table 2) were analyzed.

Table 1
Milk productivity of first-calf cows.

No.	Indicators	Name of the farm
		AF Rodina LLP	ICE LLC	Baiserke-Agro LLP	RZA- Asyl Tulik LLP
1	Number of animals	311	102	109	354
2	Milk yield, kg	9 520	9 800	8 830	8 147
3	Fat, %	3.6	3.7	3.7	3.5
4	Protein, %	3.1	3.2	3.6	3.3
Total		1011

Table 2
Dairy productivity of cows.

No.	Indicators	Name of the farm
		AF Rodina LLP				ICE LLC			Baiserke-Agro LLP			RZA- Asyl Tulik LLP
		Lactation
		1	2	3	1		2	3	1	2	3	1	2	3
1	Number of animals	964	404	150	341		268	131	139	15	X	187	46	25
2	Milk yield, kg	10 828	11069	11 882	10 900		10 950	10 500	8 322	8 550	X	8 664	8 655	8 320
3	Fat, %	3.9	4.1	4.0	4.0		3.9	3.8	3.7	3.7	X	3.6	3.5	3.4
4	Protein, %	3.1	3.1	3.1	3.2		3.4	3.2	3.4	3.4	X	3.3	3.2	3.3

It was established that the milk productivity of first-calf heifers of AF Rodina LLC amounted to 9,520 kg, in milk yield - 3.6% in fat, 3.1% in protein, Ice LLC - 9,800 kg in milk yield, 3.7% in fat, 3.2% in protein, Bayserke-Agro LLC - 8,830 kg in milk yield, 3.7% in fat, 3.6% in protein, RZA - Asyl Tulik LLC - milk yield 8,147 kg, fat 3.5%, protein 3.3%.

Dairy productivity of farm animals depends on various factors: hereditary conditions; physiological state; nature of the ontogenesis; conditions of maintenance, feeding and other factors. Animal productivity has a high degree of variability within the breed and its structural elements.

Statistical processing of the research data was performed according to the common method of statistical analysis using the Microsoft Excel program. The reliability of differences between the mean values ​​of the studied indicators was assessed using Student’s t-test in accordance with generally accepted biometric methods (Vishnevets et al., 2011).

The conducted studies showed that dairy productivity of cows of the 2nd, 3rd, and 4th lactation in AF Rodina farm averaged 10,932 kg of milk with a fat content in milk of 4%, and protein in milk of 3.1%, respectively. In ICE LLC, the milk yield was 10,700 kg, fat - 3.9%, protein - 3.3%. In Baiserke-Agro milk productivity was 8,436 kg, fat 3.7%, protein 3.4. In RZA- Asyl Tulik milk yield averaged 8,500 kg, fat 3.5%, protein 3.2%.

The assessment of the exterior of the analyzed livestock was performed visually according to the following parameters: stature, body depth, chest width, rump angle, rump width, rib structure, rear legs set, foot angle, rear legs rear view, hock development, fore udder attachment, rear udder height, rear udder width, central ligament, udder depth, front teat position, teats length, rear teat position.

Each of the listed features was estimated separately from the others on a linear scale from 1 to 9 points under the recommendations of the international non-governmental non-profit organization ICAR and the World Holstein Friesian Federation (WHFF), adopted in most countries with developed dairy cattle breeding. In this case, the number 5 was defined as the average score, and the numbers 1 and 9 mean extreme deviations of the feature in one direction or another from the average value. Along with this, for each exterior feature, the optimal (desirable) score was determined for each of the estimated features, and special attention was paid to constitution defects. All the shortcomings were brought out into separate groups of additional characteristics that have an impact on the result of the assessment of certain described exterior indicators.

The cows evaluated were between 30 and 150 days of lactation, with work carried out one to two hours before milking to assess udder characteristics.

Based on the obtained data, an analysis of the exterior indicators of 1011 Holstein first-calf heifers of the Holstein breed was performed in 4 base farms (AF Rodina of Akmola region, ICE LLC of Aktobe region, Bayserke-Agro LLP of Almaty region, RZA- Asyl Tulik of Kyzylorda region), the results are presented in Table 3.

Table 3
Average exterior indicators assessment of dairy cattle of the base farms.

Item No.	Indicator	Optimum. Score	AF Rodina (n=311)			ICE (n=102)			Baiserke-Agro (n= 244)			RZA- Asyl Tulik » (n=354)
			M	±m	Cv	M	±m	Cv	M	±m	Cv	M	±m	Cv
1	stature	8	6.7	0.041	10.88	8.5	0.058	6.99	6.6	0.063	15.04	7.2	0.054	14.04
2	body depth	7	5.3	0.067	22.38	7.2	0.050	6.93	6.1	0.053	13.46	6.1	0.061	18.78
3	chest width	7	5.1	0.067	23.16	6.9	0.048	7.05	5.7	0.057	15.57	4.8	0.044	17.25
4	rib structure	8	6.7	0.054	14.27	7.8	0.038	4.90	6.5	0.059	14.25	7.7	0.049	11.96
5	rump angle	5	5.6	0.062	19.59	5.1	0.076	15.10	5.1	0.067	20.46	4.8	0.062	24.43
6	rump width	8	5.7	0.072	22.42	6.8	0.081	12.07	6.0	0.058	15.07	6.1	0.046	14.09
7	rear legs set	5	4.6	0.069	26.13	5.2	0.084	16.44	4.9	0.087	27.82	6.5	0.062	17.99
8	foot angle	6	4.9	0.070	24.90	5.4	0.095	17.95	4.6	0.085	28.82	4.4	0.061	26.05
9	rear legs rear view	9	4.2	0.060	25.55	7.9	0.078	10.00	6.1	0.050	12.69	6.0	0,050	15.75
10	hock development	9	7.0	0.045	11.32	8.7	0.048	5.50	6.8	0.066	15.24	7.4	0,040	10.13
11	fore udder attachment	7	5.4	0.046	14.97	6.9	0.098	14.36	4.9	0.063	19.82	5.3	0.043	15,16
12	rear udder height	7	6.0	0.062	18:30	6.6	0.090	13.79	5.3	0.079	23.12	5.8	0.056	18.11
13	rear udder width	9	6.3	0.059	16.60	8.6	0.065	7.64	5.0	0.089	28.14	5.4	0,060	20.75
14	central ligament	7	4.9	0.056	20.24	7.5	0.133	17.94	4.3	0.087	31.47	4.2	0,071	31.98
15	udder depth	5	4.9	0.067	23.99	6.3	0.117	18.78	5.1	0.089	27.33	5.5	0,060	20.27
16	front teat position	6	6.4	0.060	16.61	5.1	0.117	23.07	4.6	0.042	14.13	5.0	0.038	14.32
17	teat length	5	4.3	0.070	28.68	4.9	0.079	16.50	3.9	0.063	25.45	4.0	0.053	24.94
18	rear teat position	5	6.0	0.056	16.27	6.9	0.128	18.84	5.8	0.064	17.15	6.4	0.057	16.58
Overall score:			69.1	0.208	5.31	84.8	0.449	5.35	68.4	0.280	6.39	69.4	0.200	5.43

Based on the linear assessment data of cows, linear profiles of the average indicators of the assessed Holstein herds were constructed, which look as follows; the results are presented in Table 3 and Figures 1 -4.

Figure 1
Linear profiles of average exterior indicators of cows of AF Rodina LLC.

Figure 2
Linear profiles of average exterior indicators of cows of RZA- Asyl tulik.

Figure 3
Linear profiles of average exterior indicators of cows of ICE LLC.

Figure 4
Linear profiles of average exterior indicators of cows of Bayserke Agro LLC.

As can be seen from the presented images from Figures 1 -4, the linear profiles of the average exterior indicators of cows in AF Rodina, ICE and RZA- Asyl Tulik are close to the average population estimates of the Holstein breed in Kazakhstan, while the average linear profile of cows of Bayserke Agro LLC shows an approach to optimal values.

Figure 3 shows a summary estimated bar graph of the results of the assessment of the exterior of cows (example of ICE LLC).

It was established that the average exterior indicators of Holstein cows from the base farms differed significantly from the optimal scores, while most of the exterior indicators of ICE LLC were within the range close to the desired values.

It should be noted that various conditions of housing and feeding animals also affected the estimated indicators, for example, the digital value of the foot angle indicator depends on the health of the cows and the amount of time that has passed since the date of the last hoof treatment by the time of the animal's assessment. It was noted that excessively overgrown hooves reduced the foot angle assessment score during visual assessment.

The indicators of this feature were distorted in the presence of problems with the condition of hooves on farms. In this regard, we proposed to consider the feasibility of studying the issue of planning the time of animal hoof treatment on farms concerning the plan of their mating and insemination, and therefore to the time of the linear assessment.

The research results showed that the main differences were in the following indicators: body depth, chest width and stature. The last two indicators depended both on the general development of the animal and directly on its height.

In the analysis of the exterior indicators, data from Holstein cows from the base farms of AF Rodina LLC (n=311), ICE LLC (n=102), Bayserke-Agro LLC (n=244) and RZA- Asyl Tulik LLC (n=354) were used.

4. Conclusion

The international system of Holstein cattle breeders’ associations is represented worldwide by two organizations: the European Holstein and Red Holstein Confederation (EHRC) and the World Holstein Friesian Federation (WHFF). The EHRC was established in 1966 (Petukhova, 2015). Kazakhstan has recently become a full member of the WHFF.

The effectiveness of single-step genomic BLUP (ssGBLUP) compared to traditional BLUP has been demonstrated for improving milk yield in Thai-Holstein dairy cows (Senarath et al., 2022).

Genomic prediction in dairy cattle breeding has proven effective for Holstein cattle (Mota et al., 2024).

Genomic predictions of the breeding value of traits in the Kazakhstani Holstein population, included in selection indices, are of primary importance for optimizing genetic progress in breeding populations. This is consistent with similar studies conducted by other researchers (Shi et al., 2025; Zhao et al., 2025).

Development and justification of methods for estimated breeding value indices for dairy cattle based on breeding characteristics and their weighting economic coefficients using the BLUP AM methodology with the creation of corresponding software products:

• base farms for conducting scientific research have been identified, including AF Rodina (Akmola region), ICE (Aktobe region), Baiserke-Agro (Almaty region) and RZA- Asyl Tulik (Kyzylorda region);

• the breeding traits for Holstein cattle were studied and determined, including: milk yield (kg), fat (kg, %), protein (kg, %), and somatic cells (thousand units), where the average milk productivity of cows in the first lactation was from 8,147 kg to 9,800 kg, from 3.5% to 3.7% fat, from 3.1% to 3.6%, while the milk yield for cows in 2-4 lactations was from 8,320 kg to 11,882 kg, milk fat content from 3.4% to 4.1% fat and from 3.1% to 3.4% protein;

• a linear exterior assessment of first-lactation cows of the base farms (n=1011) was carried out, where the average overall score for the exterior for AF Rodina was 69.1 points, ICE - 84.8 points, Bayserke-Agro - 68.4 points and RZA- Asyl tulik - 69.4 points;

• methods for estimated breeding value in dairy cattle breeding have been studied and work has begun on developing a methodology for estimating breeding value indices for dairy cattle based on selection traits and their weighting coefficients using the BLUP AM method, including dairy productivity (milk yield, % fat and % protein) and udder health (number of somatic cells).

Acknowledgements

The research was conducted in accordance with the priority specialized area of the Department of Agricultural Sciences of the JSC “National Academy of Sciences of the Republic of Kazakhstan” under the President of the Republic of Kazakhstan and the Russian Academy of Sciences within the framework of the Eurasian Economic Union.

The authors express their gratitude and thanks for assistance in preparing this article and developing mathematical Formulas 1, 2 and 3 to mathematician and programmer Zhanat Maratovich Kasenov (Kazakhstan) and expert in the field of assessing the exterior of Holstein cattle Boris Anatolyevich Servakh (Russia). The research was conducted under the program of targeted financing of the Ministry of Agriculture of the Republic of Kazakhstan for 2024-2026 BR 22886157 “Management, conservation and rational use of genetic resources of dairy cattle through selection-technological and molecular genetic methods "Project name "Management, conservation and rational use of genetic resources of dairy cattle breeds by means of selection and technological methods".

Data Availability Statement

The entire data set that supports the results of this study will be published in the article itself.

References

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Edited by

• Editor:
  Takako Matsumura Tundisi

Publication Dates

• Publication in this collection
  07 Aug 2026
• Date of issue
  2026

History

• Received
  19 May 2026
• Accepted
  16 June 2026