Effects of non-genetic factors on milk yield and chemical
composition of milk from Holstein-Friesian cows
Efectos de factores no genéticos en la composición química y producción de leche en vacas
Holstein-Friesian
Efeitos de fatores não genéticos na composição química e na produção de leite em vacas da raça
Holandesa-Frísia
Onur Şahin* .
Department of Animal Production and Technologies, Muş Alparslan University, Muş, Türkiye.
To cite this article:
Şahin O. Effects of non-genetic factors on milk yield and chemical composition of milk from Holstein-Friesian cows. Rev Colomb
Cienc Pecu 2024; 37(2):73–87. https://doi.org/10.17533/udea.rccp.v37n2a3
Abstract
Background: It is necessary to determine the extent and direction of environmental factors to accurately assess cow
performance in terms of milk yield and milk components. Although many studies have explored environmental factors affecting
milk yield, there is not enough information about the effects and direction of environmental factors on milk composition.
Objective: To determine the effects of non-genetic factors, such as calving season, lactation number, lactation stage, animal
age, and herd size on milk yield, chemical composition of raw milk, and Somatic Cell Count (SCC) in Holstein-Friesian cows.
Methods: Data were obtained from 15,354 raw milk samples of 5,118 Holstein-Friesian cows at 276 dairy farms in Türkiye.
The data analysis was performed using the General Linear Model (GLM) feature of the SPSS statistics program. Results: Mean
fat (F), protein (P), dry matter (DM), lactose (L), urea (U), and Log10SCC values of milk were 3.74 ± 0.01, 3.19 ± 0.01, 11.36 ±
0.03, 4.32 ± 0.01%, 21.57 ± 0.28 mg/dL, and 5.244 ± 0.01 cells/mL, respectively. Peak milk yield (PMY), lactation milk yield
(LMY), 305-day milk yield (305-d MY), and SCC values were 33.7 ± 0.13, 8,538.33 ± 89.64 kg, 6,479.42 ± 168.96 kg, and
224,164.34 ± 4,402.79 cells/mL, respectively. Conclusion: Dairy farms in Türkiye should improve protein, dry matter, and urea
contents in milk and investigate in detail the relationship between raw milk urea, subclinical mastitis, and reproductive features.
Keywords: cow; Holstein-Friesian; milk composition; milk yield; non-genetic factors; phenotypic correlation; somatic
cell count.
Received: November 12, 2022. Accepted: September 20, 2023
*Corresponding author. Department of Animal Production and Technologies, Muş Alparlan University, 49250, Muş, Türkiye.
Phone:+905458757765. E-mail: o.sahin@alparslan.edu.tr
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, which permits unrestricted reuse,
distribution, and reproduction in any medium, provided the original work is properly cited.
eISSN: 2256-2958 Rev Colomb Cienc Pecu 2023; 37(2, Apr-Jun):73–87
https://doi.org/10.17533/udea.rccp.v37n2a3
© 2024 Universidad de Antioquia. Publicado por Universidad de Antioquia, Colombia.

Rev Colomb Cienc Pecu 2024; 37(2, Apr-Jun):73-8774
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Resumen
Antecedentes: Para determinar con precisión el desempeño de las vacas en términos de producción y componentes lacteos,
es necesario conocer la cantidad y dirección de los factores ambientales. Aunque existen muchos estudios sobre los factores
ambientales que afectan la producción de leche, no hay suficiente información sobre los efectos y la dirección de los factores
ambientales en la composición de la leche. Objetivo: Determinar los efectos de factores no genéticos, tales como temporada
de parto, orden de lactancia, etapa de lactancia, edad, tamaño del rebaño sobre la producción de leche, la composición química
de la leche cruda y el recuento de células somáticas (SCC) en vacas Holstein-Friesian. Métodos: El material del estudio
estuvo compuesto por 15.354 muestras de leche cruda de 5.118 vacas Holstein-Friesian en 276 granjas lecheras en Turquía. El
análisis de datos se realizó utilizando la función de modelo lineal general (GLM) del programa estadístico SPSS. Resultados:
Los valores medios de grasa (F), proteína (P), materia seca (DM), lactosa (L), urea (U), Log10SCC de la leche fueron 3,74 ±
0,01, 3,19 ± 0,01, 11,36 ± 0,03, 4,32 ± 0,01%, 21,57 ± 0,28 mg/dL, 5.244 ± 0,01 células/mL, respectivamente. La producción
máxima de leche (PMY), producción de leche de lactancia (LMY), producción de leche a los 305 días (305-d MY) y los valores
de SCC fueron 33,7 ± 0,13, 8.538,33 ± 89,64, 6.479,42 ± 168,96 kg, y 224.164,34 ± 4.402,79 células/mL, respectivamente.
Conclusiones: Se recomienda tomar medidas para mejorar el contenido de proteína, materia seca y urea de la leche en las
granjas lecheras de Turquía e investigar en detalle la relación entre contenido de urea en leche cruda, mastitis subclínica y
características reproductivas.
Palabras clave: composición de la leche; correlación fenotípica; factores no genéticos; Holstein-Friesian; producción de
leche; recuento de células somáticas; vaca.
Resumo
Antecedentes: Para determinar com precisão o desempenho das vacas em termos de produção de leite e componentes
do leite, é necessário conhecer a quantidade e a direção dos fatores ambientais. Embora existam muitos estudos sobre fatores
ambientais que afetam a produção de leite, não há informações suficientes sobre os efeitos e a direção dos fatores ambientais
na composição do leite. Objetivo: Determinar os efeitos de fatores não genéticos como estação de parto, ordem de lactação,
estágio de lactação, idade, tamaño de la manada na produção de leite, composição química do leite cru e contagem de células
somáticas (SCC) em vacas da raça Holandês-Frísia. Métodos: O material do estudo foi composto por 15.354 amostras de leite
cru de 5.118 vacas da raça Holandesa-Frísia em 276 fazendas leiteiras na Turquia. A análise dos dados foi realizada utilizando
o recurso General Linear Model (GLM) do programa estatístico SPSS. Resultados: Os valores médios de gordura (F), proteína
(P), matéria seca (DM), lactose (L), uréia (U) e Log10SCC do leite de vaca foram encontrados como 3,74 ± 0,01, 3,19 ± 0,01,
11,36 ± 0,03, 4,32 ± 0,01%, 21,57 ± 0,28 mg/dL e 5.244 ± 0,01 células/mL, respectivamente. Pico de produção de leite (PMY),
produção de leite de lactação (LMY), produção de leite em 305 dias (305-d MY) e valores de SCC foram determinados como
33,7 ± 0,13, 8.538,33 ± 89,64, 6.479,42 ± 168,96 kg e 224.164,34 ± 4.402,79 células/mL, respectivamente. Conclusões:
Recomenda-se tomar medidas para melhorar o teor de proteína, matéria seca e uréia do leite em fazendas leiteiras na Turquia e
investigar em detalhes a relação entre o teor de uréia do leite cru, mastite subclínica e características reprodutivas.
Palavras-chave: composição do leite; contagem de células somáticas; correlação fenotípica; fatores não genéticos;
Holstein-Frísia; produção de leite; vaca.

75Rev Colomb Cienc Pecu 2024; 37(2, Apr-Jun):73-87
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Introduction
Milk is composed of water, protein, amino
acids, vitamins, lipids, fatty acids, and minerals.
It is affected by factors such as breed or genetic
group, milk production, stage of lactation, parity,
feeding, and season of calving. Knowledge on the
relative effects of genetic and environmental factors
affecting milk components allows for changes in
milk composition (Simões et al., 2014; Boro et al.,
2016). Milk yield, milk chemical composition,
and somatic cell count (SCC) can be affected
by multiple genetic and non-genetic interrelated
factors, such as parity, stage of lactation, calving
season, herd, and calving year (Erdem et al., 2007;
Bertocchi et al., 2014; Atasever and Stadnik, 2015;
Sobczuk-Szul et al., 2015; Boujenane, 2021).
Practices that help breeders gain information on
how to obtain quality raw milk and improve milk
quality for milk products (cheese, yogurt, cream,
etc.) in different regions of Türkiye are also needed
(Şahin and Yıldırım, 2012). The SCC in cow’s
milk should be less than 200,000 cells/mL. When
this number exceeds 200,000 cells/mL the udder
lobe is most likely infected (Querengasser et al.,
2002). In addition, the SCC in milk is an indicator
of both resistance and sensitivity of animals to
mastitis, which can be used to monitor the level
or formation of subclinical mastitis in herds or
individual animals (Malik et al., 2018).
Milk urea nitrogen (MUN) is not in the protein
structure and represents total nitrogen in milk.
Urea passes into the milk from the secretory cells
of the mammary glands and indicates the amount
of degradable protein in the rumen. The MUN
value is determined directly by the amount of
urea in milk. MUN values between 10 and 14 mg/
dL are considered normal. Daily dry matter and
protein consumption affect MUN concentration in
milk. While MUN values in milk below 10 mg/
dL indicate insufficient dry matter and protein
consumption, MUN values above 14 mg/dL
indicate the opposite (Keser et al., 2019).
The purpose of this study was to determine
the effects of non-genetic factors (calving season,
lactation number, lactation stage, and animal age)
on milk yield, chemical composition of raw milk,
and SCC in Holstein-Friesian cows.
Materials and Methods
Data were obtained from 15,354 raw milk
samples of 5,118 Holstein-Friesian cows from
276 dairy cattle farms in Türkiye. An average of
three raw milk samples per cow was used. Based
on EU standards, raw milk samples were taken
from each cow three times a year to determine
the SCC (Anonymous, 2006). Raw milk samples
were taken equally from the beginning to the end
of the milking process using a special sampling
tool (Izmirbirlik Süt Numune Alma Aparatı,
Izmir, Türkiye). The raw milk sampler consists of
two parts: a pipe system in a spiral structure that
separates the samples from the milk output, and
a 500 mL container for collecting milk samples
(Figure 1).
Figure 1. Raw milk sampler (Izmirbirlik Süt Numune Alma Aparatı, Izmir, Türkiye).

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SCC and chemical components (fat, protein, dry
matter, lactose, and urea) of the collected raw milk
were analyzed using the milk analyzer (Bentley
Combi FTS, Maroeuil, France) (Figure 2). This
analyzer was suitable and met the requirements of
the International Committee for Animal Recording
standards (ICAR, 2017).
The Bentley FTS, which represents the latest
technology for automated milk analysis, can
analyze 400 samples per hour. This piece of
equipment was engineered in accordance with
Bentley Instruments’ rigorous design principles
and provides precise and accurate measurements.
It uses a Fourier Transform Spectrometer (FTIR)
to analyze the milk composition, including dry
matter, fat, protein, lactose, urea, and SCC. After
the first stirring, the milk is drawn from a sample
vial and delivered to the measurement module.
The sampling, sequencing, and identification of
the sample vials are performed using the auto
sampler. No chemicals are used in the analysis
(Figure 2).
The Bentley FTS meets the standards set by the
International Dairy Federation (IDF), International
Committee of Animal Recording (ICAR), and
Association of Official Agricultural Chemists
(AOAC) (BENTLEY, 2023).
The following data were collected for each
animal sampled: fat, dry matter, lactose, protein,
SCC, animal age, number of milking days, the
highest daily milk yield, lactation milk yield, 305-
day milk yield, season in which samples were
taken, and lactation number. This information was
obtained from the herd-book system of the Cattle
Breeders’ Association of Türkiye.
Milk yield and milk components
In this study, the effects of calving season,
lactation number, lactation stage, and animal age
on fat (F), protein (P), dry matter (DM), lactose
(L), urea (U), SCC, lactation milk yield (LMY),
305-day milk yield (305-d MY), and peak-day
milk yield (PDMY) were investigated (Tables 1,
2, and 3).
Seasons were grouped into the following four
classes: 1) Winter (December, January, February),
2) Spring (March, April, May), 3) Summer (June,
July, August), and 4) Fall (September, October,
November). Regarding lactation number, cows
were categorized as 1 through 7 and above. Animal
age was classified in months, as follows: 24-36,
37-48, 49-60, 61-72, 73-84, 85-96, and 97 and
above. Herd size was grouped into the following
five classes: <51, 51-100, 101-500, 501-1000, and
>1000 animals.
Figure 2. Bentley milk analyzer (Bentley Combi, FTS, Maroeuil, France).

77Rev Colomb Cienc Pecu 2024; 37(2, Apr-Jun):73-87
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Lactation stage was divided into six groups, as
follows: Lactation-I (<46 days), early Lactation-II
(46-90 days), mid-Lactation (91-180 days), late
lactation-I (181-270 days), and late Lactation-II
(>270 days) (Table 4).
Statistical analysis
Data analysis was performed with the SPSS
statistics program (SPSS 25.0; 2021). Analysis of
variance (ANOVA) was used for data analysis. The
statistical model evaluated the effect of calving
season, lactation number, animal age, and herd
size on milk yield, milk components, and SCC.
Since repeated milk samples were taken randomly
on different lactation days, the effect of repeated
measurements was included in the error variance.
The following statistical model was used:
Yijkl=μ+ ai +bj +ck+dl+eijkl
Where:
μ = Overall mean
ai = Effect of ith season at calving (1-4)
bj = Effect of jth lactation number (1-7)
ck = Effect of kth animal age (1-7)
dl = Effect of lth herd size (1-5)
eijkl = Random error
Duncan’s multiple range test (p<0.05) was used
to compare the mean values of groups. Correlations
among milk yield and milk components were also
calculated with the SPSS program (SPSS 25.0,
2021).
Results
The mean standard deviation and median
results of F, P, DM, L, U, SCC, PDMY, LMY, and
305-d MY are provided in Table 1.
Although the effect of calving season on P
and DM was not statistically significant (p>0.05),
the effect of calving season on L (p<0.05), F
(p<0.01), and SCC (p<0.01) was significant. The
effect of lactation number on F (p>0.05) was not
significant, while its effect on P, DM, L, and SCC
was significant (p<0.01) (Table 2). The effect of
animal age and herd size on F, P, DM, L, and SCC
was significant (p<0.01) (Table 2).
The effect of calving season and herd size on
LMY, 305-d MY, Urea, and PDMY was significant
(p<0.01). Although the effect of lactation number
on LMY and 305-d MY was not significant
(p>0.05), the effects on U (p<0.05) and PDMY
(p<0.01) were significant. In addition, the effect of
animal age on 305-d MY (p<0.05), LMY, U, and
PDMY (p<0.01) were significant (Table 3).
Although the F component had the highest
value in the mid-lactation stage (91-180
days), it showed the lowest in the second
late lactation stage (≥270 days). Difference
between lactation stages in terms of the F
component was statistically significant (p<0.01).
Table 1. Descriptive statistics for milk yield, raw milk components, and SCC.
Parameter Unit N X ± SE SD Median
F % 1,490 3.74 ± 0.01 0.56 3.68
P % 1,490 3.19 ± 0.01 0.31 3.16
DM % 1,490 11.36 ± 0.03 1.02 11.33
L % 1,490 4.32 ± 0.01 0.35 4.30
U mg/dL 1,133 21.57 ± 0.28 9.43 19.00
PDMY kg 5,118 33.70 ± 0.14 9.64 33.00
LMY kg 974 8,538.33 ± 89.64 2,797.43 8,526.50
305-d MY kg/305 974 6,479.42 ± 168.96 5,273.01 7,666.50
SCC cells/mL 1,490 224,164.34 ± 4,401.80 169,911.59 174,250.00
N: Sample size, X: Least square mean, SE: Standard error, SD: Standard deviation, F: Fat, P: Protein, DM: Dry matter, L: Lactose,
U: Urea, PDMY: Peak-day milk yield, LMY: Lactation milk yield, 305-d MY: 305-day milk yield, SCC: Somatic cell count.

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Table 2. Least square means of raw milk components according to factors.
Factors P DM L SCC
N X ± SE X ± SE X ± SE X ± SE X ± SE
Herd size (head) ** ** ** ** **
<51 473 3.60 ± 0.02ab 3.13 ± 0.01b 11.20 ± 0.05b 4.25 ± 0.02a 249,611.07 ± 6,940.80bc
51-100 254 3.69 ± 0.03bc 3.23 ± 0.02c 11.25 ± 0.06b 4.26 ± 0.02a 275,973.03 ± 9,937.08c
101-500 380 3.76 ± 0.03c 3.23 ± 0.01c 11.75 ± 0.05c 4.43 ± 0.18a 225,614.92 ± 8,632.51b
501-1000 187 3.56 ± 0.05a 3.40 ± 0.03d 11.91 ± 0.07c 4.51 ± 0.03b 162,564.17 ± 18,677.82a
>1000 196 4.29 ± 0.03d 2.98 ± 0.01a 10.64 ± 0.06a 4.21 ± 0.02c 151,573.98 ± 2,748.76a
Calving season ** NS NS * **
Winter 286 3.76 ± 0.03b 3.16 ± 0.02a 11.32 ± 0.06 a 4.29 ± 0.02a 239,304.23 ± 9,162.12bc
Spring 233 3.58 ± 0.03a 3.20 ± 0.02 a 11.48 ± 0.06 a 4.36 ± 0.02b 216,238.24 ± 11,072.04ab
Summer 463 3.64 ± 0.02a 3.19 ± 0.01 a 11.33 ± 0.05 a 4.31 ± 0.02ab 245,631.99 ± 9,167.40c
Autumn 508 3.89 ± 0.03c 3.19 ± 0.01 a 11.37 ± 0.05 a 4.33 ± 0.02ab 199,711.00 ± 6,518.58a
Lactation number NS ** ** ** **
1 279 3.72 ± 0.04a 3.31 ± 0.02c 11.78 ± 0.06c 4.51 ± 0.02d 185,468.32 ± 13,235.68a
2 367 3.69 ± 0.03a 3.18 ± 0.02ab 11.39 ± 0.05b 4.35 ± 0.02c 210,707.06 ± 7,898.99ab
3 400 3.80 ± 0.03a 3.17 ± 0.01ab 11.30 ± 0.05ab 4.28 ± 0.02abc 226,615.05 ± 7,546.44abc
4 213 3.70 ± 0.04a 3.10 ± 0.02a 11.04 ± 0.06a 4.20 ± 0.02a 250,654.18 ± 10,716.77bcd
5 133 3.74 ± 0.05a 3.13 ± 0.03a 11.15 ± 0.09ab 4.24 ± 0.03ab 278,076.54 ± 15,401.94d
6 55 3.88 ± 0.08a 3.16 ± 0.04ab 11.36 ± 0.13b 4.30 ± 0.04bc 228,090.91 ± 14,978.54abc
7+ 43 3.77 ± 0.09a 3.22 ± 0.04b 11.29 ± 0.15ab 4.24 ± 0.05ab 264,302.33 ± 21,308.18cd
Animal age (months) ** ** ** ** **
24-36 31 3.76 ± 0.13b 3.43 ± 0.06c 12.20 ± 0.17d 4.64 ± 0.07d 274,451.61 ± 55,247.65b
37-48 277 3.60 ± 0.03a 3.31 ± 0.02b 11.71 ± 0.06c 4.49 ± 0.02c 176,780.36 ± 13,119.01a
49-60 229 3.70 ± 0.03ab 3.17 ± 0.02a 11.49 ± 0.06bc 4.37 ± 0.02bc 214,898.38 ± 8,934.86ab
61-72 365 3.84 ± 0.03b 3.16 ± 0.02a 11.30 ± 0.06ab 4.29 ± 0.02ab 216,177.26 ± 75,59.11ab
73-84 236 3.73 ± 0.03ab 3.14 ± 0.02a 11.14 ± 0.06a 4.22 ± 0.02a 249,793.81 ± 10,483.25bc
85-96 163 3.73 ± 0.05ab 3.11 ± 0.02a 11.10 ± 0.08a 4.21 ± 0.02a 247,558.22 ± 11,371.27bc
97≤ 189 3.79 ± 0.05b 3.16 ± 0.02a 11.20 ± 0.07a 4.24 ± 0.02a 260,049.77 ± 4,404.63bc
NS: Not significant (p>0.05), *: Significant at the level of p<0.05, **: Significant at the level of p<0.01.
Different superscript letters (a, b, c, d) within the same column indicate significant difference between means.
N: Sample size, SD: Standard deviation, X: Least square mean, SE: Standard error, F: Fat (%), P: Protein (%), DM: Dry matter
(%), L: Lactose (%), U: Urea (mg/dL), SCC: Somatic cell count (cells/mL).
However, while the P component presented
the highest value within the first late lactation
stage (181-270 days), it showed the lowest
value during mid-lactation (91-180 days). The
difference between lactation stages in terms of the
P component was significant (p<0.05) (Table 4).
For DM and L components, the highest
values were observed within the first stages of
late lactation (181-270 days) and the first stages
of early lactation (<45 days), respectively.
However, the lowest values were determined
in the second early lactation (46-90 days) and
mid-lactation (91-180 days) stages for the DM
component as well as in the second late lactation
stage for the L component. Differences between
lactation stages were not statistically significant
for DM (p=0.065) nor L components (p=0.111)
(Table 4).
The U component had the highest value in the
middle stage of lactation (91-180 days) although

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Table 3. Least square means for milk yield characteristics and urea according to factors.
Factors LMY 305-d MY U PDMY
N X ± SE X ± SE N X ± SE N X ± SE
Herd size (head) 974 ** ** 1,133 ** 5,118 **
<51 121 7,025.08 ± 189.91b 6,409.88 ± 400.80a 387 19.28 ± 0.40a 601 28.48 ± 0.29a
51-100 65 6,835.49 ± 256.47ab 5,550.38 ± 507.32a 206 19.74 ± 0.56a 292 29.91 ± 0.38b
101-500 252 8,856.00 ± 179.54b 6,895.01 ± 330.04b 260 18,87 ± 0.49a 751 37.00 ± 0.39d
501-1,000 233 10,025.80 ± 207.28c 8,646.33 ± 372.05c 86 23.26 ± 1.60b 1,291 35.91 ± 0.30d
>1,000 303 8,099.88 ± 123.28a 6,694.55 ± 278.94b 194 30.97 ± 0.42c 2,183 33.21 ± 0.18c
Calving season 974 ** ** 1,133 ** 5,118 **
Winter 169 7,897.63 ± 238.71a 8,099.88 ± 123.28a 225 20.85 ± 0.55b 1,392 34.72 ± 0.24c
Spring 89 7,958.00 ± 297.82a 7,805.09 ± 645.36c 169 19.00 ± 0.53a 990 33.76 ± 0.31b
Summer 258 8,288.53 ± 157.59a 7,051.88 ± 330.45bc 351 20.83 ± 0.52b 1,246 32.03 ± 0.25a
Autumn 458 9,028.22 ± 128.01b 6,367.45 ± 243.22b 388 23.78 ± 0.52c 1,490 34.11 ± 0.27bc
Lactation number 974 NS NS 1,133 * 5,106 **
1 399 8,616.64 ± 116.57 a 6,818.04 ± 258.74 a 180 18.64 ± 0.47a 1,843 31.73 ± 0.21b
2 212 8,372.86 ± 200.14 a 6,437.45 ± 367.64 a 259 22.76 ± 0.61b 1,318 34.76 ± 0.25cd
3 229 8,798.81 ± 225.71 a 6,221.88 ± 372.27 a 322 22.33 ± 0.56b 1,078 35.95 ± 0.33d
4 84 8,346.35 ± 331.50 a 6,361.38 ± 541.44 a 175 21.41 ± 0.75ab 499 34.79 ± 0.45cd
5 29 7,756.93 ± 323.61 a 5,278.45 ± 840.34 a 112 21.53 ± 0.83ab 218 32.33 ± 0.62b
6 11 8,567.55 ± 759.31 a 5,964.36 ± 1,440.28 a 45 21.98 ± 1.52b 87 32.82 ± 0.89bc
≤7 10 6,802.8 ± 412.61 a 4,796.90 ± 1,336.07 a 40 21.29 ± 1.60ab 63 29.44 ± 0.87a
Animal age (months) 974 ** * 1,133 ** 5,112 **
24-36 54 8,653.34 ± 402.36b 6,534.51 ± 597.89b 14 16.61 ± 1.14a 593 31.67 ± 0.32a
37-48 312 8,578.20 ± 124.36b 6,905.61 ± 389.71b 151 19.00 ± 0.52ab 1,371 33.29 ± 0.25b
49-60 165 8,625.95 ± 237.12b 6,874.28 ± 439.37b 177 20.27 ± 0.63bc 948 33.63 ± 0.32b
61-72 212 9,007.64 ± 212.01b 6,574.12 ± 431.80b 283 23.61 ± 0.61c 899 36.20 ± 0.34c
73-84 120 8,599.79 ± 297.49b 6,220.31 ± 523.49b 199 22.57 ± 0.71bc 611 35.35 ± 0.42c
85-96 60 7,065.30 ± 380.29a 3,832.65 ± 552.25a 143 21.51 ± 0.88bc 327 32.10 ± 0.49a
≤97 51 7,497.41 ± 218.68a 6,054.20 ± 615.96b 166 20.97 ± 0.70bc 363 31.31 ± 0.46a
NS: Not significant (p>0.05), *: Significant at the level of p<0.05. **: Significant at the level of p<0.01.
Different superscript letters (a, b, c, d) within the same column indicate significant difference between means.
N: Sample size, X: Least square mean, SE: Standard error, LMY: Lactation milk yield (kg), 305-d MY: 305-day milk yield (kg),
PDMY: Peak-day milk yield (kg), U: Urea (mg/dL).
the lowest value was seen in Log10SCC within the
same stage. However, during the first late lactation
stage (181-270 days), Log10SCC had the highest
value, while the U component had the lowest
value. Differences between lactation stages for
Log10SCC and U components were statistically
significant (p<0.01) (Table 4).
A positive, significant (p<0.01) and strong
relationship between DM and L content was
observed in the present study. Additionally, there
was a positive, significant (p<0.01) and moderate
relationship between P and L contents between
305-d-MY and PDMY, and between DM and
P contents. However, significant and negative
correlations were found between SCC and all the
traits, except for the P component. The direction of
the relationship between SCC and P was positive,
whereas it was negative with the other traits
(PDMY, F, DM, L, U) (Table 5).

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Table 4. Least square means of raw milk components according to lactation stage.
Parameters P DM L Log10SCC U
N X ± SE X ± SE X ± SE X ± SE X ± SE X ± SE
Lactation Stage ** * NS NS ** **
1st early (≤ 45) 91 3.67 ± 0.06ab 3.20 ± 0.03b 11.49 ± 0.11a 4.37 ± 0.04a 5.22 ± 0.04a 21.43 ± 1.32a
2nd early (46-90) 188 3.76 ± 0.04b 3.17 ± 0.02ab 11.29 ± 0.07a 4.34 ± 0.03a 5.24 ± 0.02ab 23.72 ± 0.82b
Mid (91-180) 346 3.93 ± 0.03c 3.13 ± 0.02a 11.29 ± 0.06a 4.32 ± 0.02a 5.18 ± 0.02a 25.31 ± 0.62b
1st late (181-270) 285 3.78 ± 0.03b 3.22 ± 0.02b 11.50 ± 0.06a 4.36 ± 0.02a 5.28 ± 0.02b 19.27 ± 0.57a
2nd late (270≥) 580 3.62 ± 0.02a 3.20 ± 0.01b 11.35 ± 0.04a 4.30 ± 0.01a 5.27 ± 0.01b 19.67 ± 0.39a
Overall 1,490 3.74 ± 0.01 3.19 ± 0.01 11.36 ± 0.03 4.32 ± 0.01 5.24 ± 0.01 21.57 ± 0.28
NS: Not significant (p>0.05), *: Significant at the level of p<0.05, **: Significant at the level of p<0.01.
Different superscript letters (a, b, c, d) within the same column indicate significant difference between means.
N: Sample size, X: Least square mean, SE: Standard error, F: Fat (%), P: Protein (%), DM: Dry matter (%), L: Lactose (%), U:
Urea (mg/dL), Log10SCC: Value based on log10 for somatic cell count.
Table 5. Phenotypic correlations between milk yield, milk components, and SCC.
Characteristic PDMY F P DM L U SCC LMY
PDMY 1
F 0.078** 1
P 0.191** 0.051* 1
DM 0.232** 0.379** 0.678** 1
L 0.301** 0.182** 0.585** 0.841** 1
U 0.131** 0.256** 0.094** -0.147** -0.136** 1
SCC -0.207** -0.127** 0.096** -0.064* -0.143** -0.104** 1
LMY 0.340** -0.063 0.110* 0.084 0.149** 0.050 0.046 1
305-d MY 0.648** 0.046 0.218** 0.247** 0.289** 0.153** -0.043 0.443**
*: Significant at the level of p<0.05, **: Significant at the level of p<0.01.
F: Fat, P: Protein, DM: Dry matter, L: Lactose, U: Urea, SCC: Somatic cell count, PDMY: Peak-day milk yield, LMY: Lactation
milk yield, 305-d MY: 305-day milk yield.
r<0.3 none or very weak, 0.3<r<0.5 weak, 0.5<r<0.7 moderate, and 0.7 < r strong correlations.
Discussion
The mean F was 3.74 ± 0.01% (Table 1). In
previous studies, Hanus et al. (2010), Czajkowska
et al. (2014), Suárez et al. (2016), and Kul et al.
(2019) found mean F was 4.06, 3.73, 4.17, and
3.39, respectively. Önal et al. (2021) reported
that the lowest F by season was 3.44 ± 0.058% in
autumn and 3.72 ± 0.048% in summer. Visentin
et al. (2018) found that milk yield averaged 22.74
kg/d and mean F was 4.03 ± 0.61%. On the other
hand, El-Tarabany et al. (2018) reported that F
was 3.44% for Holstein-Friesian cows, while
Boujenane (2021) reported that average F was
3.54 ± 0.76%. Marshall et al. (2020) also found
that F was 5.12 and 6.52%, in early and late
lactation periods, respectively. In addition, while
F in raw milk was affected by herd size, calving
season, and animal age, it was not affected by
lactation number. The F component in raw milk
increased for <51, 51-100, and 101-500 herd
sizes (3.60 ± 0.02, 3.69 ± 0.03, 3.76 ± 0.03,
respectively). A decrease in F was observed for
herd sizes of 501-1,000 head (3.56 ± 0.05%). The
highest F component was obtained for herd size
greater than 1,000 heads (4.29 ± 0.03%).

81Rev Colomb Cienc Pecu 2024; 37(2, Apr-Jun):73-87
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The lowest F occurred during spring (3.58
± 0.03%) and increased during summer, autumn,
and winter (3.64 ± 0.02, 3.89 ± 0.03, and 3.76
± 0.03%, respectively). This difference is likely
related to sufficiency of roughage stocks in the
farms. The values obtained for summer and
autumn differ from the results (3.72 ± 0.06, and
3.44 ± 0.06%, respectively) reported by Önal
et al. (2021).
The P component was 3.19 ± 0.01% (Table 1).
In a similar study, mean P was 3.28%, ranging
from 3.19 to 3.33% (Aydin et al., 2010). In
other studies, P was 3.43, 3.53, 3.66, and 3.37%
(Suàrez et al., 2016; Visentin et al., 2018; El-
Tarabany et al., 2018; and Czajkowska et al.,
2014, respectively). In addition, Marshall et al.
(2020) and Boujenane (2021) reported that mean
P was 3.02 ± 0.34%. Sarıalioğlu and Laçin (2021)
reported that P in family dairy farms and modern
dairy farms was 3.49 ± 0.07 and 3.45 ± 0.01%,
respectively. Önal et al. (2021) reported that the
highest P for winter was 3.46 ± 0.031.
The P component in raw milk increased as
herd size increased to 1,000. For herd sizes
greater than 1,000, the P level in milk decreased.
Accordingly, P fluctuated depending on lactation
number and animal age, rather than steady
increasing or decreasing.
Önal et al. (2021) reported that the highest
milk DM (13.50% ± 0.103) was observed during
spring. Suàrez et al. (2016), El-Tarabany et al.
(2018), and Czajkowska et al. (2014) found
13.16, 12.80, and 12.61% DM, respectively. In
contrast, Boujenane (2021) reported that mean
DM was 8.72 ± 0.36%. Another study found DM
in family and modern dairy farms to be 9.64 ±
0.21 and 9.52 ± 0.05%, respectively (Sarialioğlu
and Laçin, 2021). Changes in DM in terms of
herd size, lactation number, and animal age
was consistent with changes in protein rates.
Therefore, fluctuations in DM may have been
due to differences in feeding levels among farms,
which is similar to protein rate.
The mean L component of milk was 4.32 ±
0.01% (Table 1). Ayaşan et al. (2011) found L
between 4.15 ± 0.06 and 4.34 ± 0.06%. Flipejova
and Kovacik (2009) reported that milk L ranged
from 4.02 to 4.99 with a mean value of 4.59,
and El-Tarabany et al. (2018) found mean L was
4.94%. In addition, Czajkowska et al. (2014)
found it to be 4.89 ± 0.21%, and Boujenane
(2021) reported that mean L was 4.89 ± 0.24%.
Moreover, Marshall et al. (2020) found L in the
early and late lactation periods to be 5.04 and
4.81%, respectively. It is known that L is not
markedly affected by feeding. In terms of herd
size, the L trend was similar to that of P and DM.
The L in milk decreased as animal age increased.
In terms of seasons, the lowest (4.29 ± 0.02%)
and highest (4.36 ± 0.02%) L percentages were
observed in winter and spring, respectively.
The mean SCC value (224,164.32 ± 4,401.80
cells/mL) was lower than that reported by
Flipejova and Kovacik (2009), and Suàrez et
al. (2016) (1,525,400 and 523,207 cells/mL,
respectively), but it was in line with the value
observed by Gürbulak et al. (2009) (226,800 ±
4,200 cells/mL).
Eyduran et al. (2005) reported that lactation
number and months had an effect on SCC in milk
from Holstein-Friesian cows, and mean SCC for
August and November was 1,311,761 ± 239,631
and 732,810 ± 146,264 cells/mL, respectively.
Böcekli (2015) assessed the effect of SCC on
milk yield, reporting that <200,000, 201,000-
500,000, and >501,000 cells/mL had a significant
effect on milk yield, with 28.75, 27.48, and 26.78
kg, respectively.
In a similar study, the highest SCC values
occurred during the summer months (Aytekin
and Boztepe, 2014). In a study conducted by
Önal et al. (2021), it was shown that lactation
number and season affected SCC. The authors
found that the highest SCC occurred during the
4th lactation (928.30 ± 117.93 × 103 cell/mL)
and milk with the lowest SCC occurred during
the 1st lactation (356.47 ± 50.55 × 103 cell/mL).
They also showed that SCC values descended
from 1,003.88 ± 83.53, 877.63 ± 97.43, 575.81
± 63.97, and 212.36 ± 17.94 × 103 cell/mL for
winter, spring, autumn, and summer, respectively

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https://doi.org/10.17533/udea.rccp.v37n2a3Effects of non-genetic factors on cow milk
(Önal et al., 2021). Sarialioğlu and Laçin (2021)
also reported that mean SCC in milk samples
were 4.23 ± 0.19 and 3.79 ± 0.16 Log10 for family
and modern dairy farms, respectively.
The SCC decreased with increasing herd size.
This result is thought to be related to investments
in modernization and automation. The highest
seasonal SCC values were observed in the
summer and winter seasons, respectively. This
result might be caused by high temperatures
during the summer and high humidity in winter,
related with unfavorable barn conditions.
When examining herd records and feed profile
of dairy farms, the nitrogen value of milk (U) is
used as the standard method since it provides
a practical approach for measurement and
evaluation (Roy et al., 2011). In the present study,
the U value was 21.57 ± 0.28 mg/dL. In addition,
U was significantly affected by lactation stage
(Table 4), calving season, and lactation number
(p<0.01), but it was not affected by animal age
(Table 3).
Milk urea nitrogen varies according to several
factors. If milk protein is 3.0 and 3.2%, then milk
urea nitrogen varies between 12 and 16 mg/dL;
since as P increases, urea nitrogen decreases. This
is because more nitrogen consumption is used for
milk protein (Abdouli et al., 2008).
Depatie (2000) reported that SCC did not
affect milk urea nitrogen. On the other hand,
Kwai-Hang et al. (1985) stated that increased
SCC increased milk urea nitrogen. Other studies
have reported that milk urea nitrogen is low in
milk with excess SCC. In those studies, milk urea
concentration had a positive relationship with
milk yield and a negative relationship with milk
F levels (Faust et al., 1997).
Abdouli et al. (2008) reported that milk urea
nitrogen of cows bred under Mediterranean
conditions was 30.39 mg/dL, while this value was
20.43-32.49, 11.15, 12.7-13.9, 20.64, and 11.75
mg/dL (Frank and Swensson, 2002; Arunvipas
et al., 2008; Meeske et al., 2009; Czajkowska et
al., 2014; and Zhang et al., 2018, respectively).
Marshall et al. (2020) also found that U during
the early and late lactation periods was 18.60 and
16.10 mg/dL, respectively. In contrast, Boujenane
(2021) found mean U was 17.6 ± 8.17 mg/dL.
The overall mean value (21.57 ± 0.28 mg/
dL) obtained in the present study was above
the accepted upper limit for milk urea nitrogen
(14 mg/dL). The mean U values were high for
herds with 501-1,000 and >1,000 heads (23.26 ±
1.60 and 30.97 ± 0.42 mg/dL, respectively). This
might be due to the use of high protein mixed
feeds for obtaining high milk yields per cow.
Mean PDMY, LMY, and 305-day MY values
in the present study were 33.70 ± 0.14, 8,538.33
± 89.64, and 6,479.42 ± 168.96 kg, respectively.
The effects of calving season on PDMY, LMY,
and 305-day MY were significant (p<0.01; Table
3). The effect of lactation number on PDMY was
not significant, while its effect on LMY and 305-
day MY was significant (p<0.01; Table 3). The
effect of cow age on PDMY and LMY was also
significant (p<0.01; Table 3).
In the present study, LMY was 8,538.33 ±
89.64 kg. In previous studies, LMY means were
5,929 ± 23, 7,700.02 ± 99.17, 4,716.1 ± 243,
3,032.41 ± 66.78, 5,720.00 ± 43.6, and 4,726.12
kg (Bakır and Kaygısız, 2013; Yıldırım et al.,
2018; Gamaniel et al., 2019; Kidane et al., 2019;
McClearn et al., 2020; and Sanad et al., 2021;
respectively). Thus, the present study found
higher LMY compared to all the mentioned
studies.
In the present study, the 305-day MY value
was 6,479.42 ± 168.96 kg. In similar studies
conducted in Holstein-Friesian cows this value
was 5,523 ± 27, 8,246 ± 1,194.6, 9,435 ±
156.12, 7,923.28 ± 80.92, 6,197.88 ± 1,681.35,
and 8,369.72 kg (Bakır and Kaygısız, 2013;
Van Eetvelde et al., 2017; Duru, 2018; Yıldırım
et al., 2018; Tutkun and Yener, 2018; and Habib
et al., 2020, respectively). Although LMY in the
present study was higher than values reported by
Bakır and Kaygısız (2013) and Tutkun and Yener
(2018), it was lower than the values found by Van
Eetvelde et al. (2017), Duru (2018) and Yıldırım
et al. (2018). Since the mean of the lactation

83Rev Colomb Cienc Pecu 2024; 37(2, Apr-Jun):73-87
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period is different for each herd, the 305-day
MY is used instead of LMY to compare milk
yield among herds. Accordingly, the differences
observed for 305-day MY are thought to be due
to herd genetics, environment in which they were
raised, and different feeding plans.
In the present study, mean PDMY (33.70 ±
0.14 kg in Holstein-Friesian cows) was lower
than those found by Sönmez et al. (2018; 35.00
± 0.50) and Castaño et al. (2020; 39.77), but
higher than values reported by Serkan et al. (2013;
30.81 ± 0.83), Yılmaz and Kaygısız (2000; 21.5
± 0.60), Abosaq et al. (2017; 22.79) and Ghavi
and Zadeh (2019; 31.31). In terms of milk yield,
the 305-d MY was used as a basis for comparison
since lactation periods showed variation among
cows. Accordingly, milk yield in herd size
between 101 and 1,000 heads was higher than in
herds below 100 heads and above 1,000 heads.
In terms of season, the lowest 305-d MY was
found throughout autumn, and the highest during
winter. This situation is associated with increase in
winter and spring calving and increased roughage
and concentrate feed based on Türkiye climate.
Although there were fluctuations in the 305-d
MY values of lactation number and age groups, a
decreasing trend was observed in the 305-d MY
due to increased lactation number and age.
While F and U ratios increased during early
lactation (1-90 days), the P ratio decreased.
During mid-lactation (days 91-180) F and U
ratios reached their highest values, while the
P ratio saw its lowest levels. For late lactation
(>181 days) the F and U ratios decreased, while
the P ratio increased. Due to the use of body fat
reserves throughout the early lactation period and
the increase in the amount of feed according to
increased milk yield, the fat rate increased until
the end of the mid-lactation period.
Unlike fat, protein is not markedly affected
by feeding, but has a negative relationship with
milk yield. For this reason, protein is at the
lowest level during mid-lactation when milk
yield is at the highest. However, protein in early
and late lactation stages is higher than in the
mid-lactation period.
Although SCC decreased during mid-lactation,
it increased in early and late lactation. This might
result from the increase in epithelial cell loss of
with as lactation period progresses and mastitis
during the dry period before early lactation.
The U component in milk was at the highest
level in mid-lactation and it was lower during
the early and late lactation periods. This is due
to increased offer of concentrated feed as milk
yield increases, as well as change in protein and
energy content of the feed. The U levels were
very high during all lactation stages considering
that accepted U in raw milk is 10-14 mg/dL.
In conclusion, the effects of calving season on
305-day MY, LMY, PDMY, U, L, F, and SCC;
the effect of lactation number on PDMY, P, DM,
L, and SCC; and the effect of animal age and herd
size on LMY, 305-day-old MY, PDMY, and all
milk components were statistically significant.
Although dairy farmers in this study are
conscious of milk yield and milk quality, they
nevertheless need to take measures to improve
P, DM, and U components of milk. In addition,
based on these results, detailed research should
be conducted on subclinical mastitis as well as
the relationship between MUN and reproduction
in dairy farms in Türkiye
Declarations
Acknowledgement
I would like to acknowledge The Cattle Breed-
ers’ Association of Türkiye (CBAT) for autho-
rizing the use of the data presented in this study
(Decision of the Board of Directors No. 2019/10;
21.08.2019).
Funding
This study was conducted with contributions
from the Cattle Breeders’ Association of Turkey
(CBAT).

Rev Colomb Cienc Pecu 2024; 37(2, Apr-Jun):73-8784
https://doi.org/10.17533/udea.rccp.v37n2a3Effects of non-genetic factors on cow milk
Conflicts of interest
The author declares he has no conflicts of
interest with regard to the work presented in this
report.
Author contributions
Study design, literature review, data analysis,
and manuscript writing were all conducted by OŞ.
Use of artificial intelligence (AI)
No AI or AI-assisted technologies were used
during the preparation of this work.
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