Objective: Test day milk average somatic cell count is a frequently used indirect indicator of infectious status of mammary glands. Therefore, the aim of this study was to compare the efficiency of using cumulative milk yield or test day milk yield as a criterion to improve milk production based on measures of somatic cells in milk. Methodology: This study was carried out during the period extended from year 2008-2010 on 1739 dairy records for 858 cows by 86 sires US Holstein from Dina farms situated about 80 km in Cairo-Alexandria desert road. Variance components, heritability estimates, genetic, phenotypic and Spearmans rank correlations between breeding value for somatic cell score and both cumulative milk yield and test day milk yield in first six months of lactation period were analyzed by using a multi-trait animal model analysis. Results: According to the results of the study, there is a direct relationship between somatic cell count score and somatic cell count, the highest score (9th) was observed when somatic cells being 8517.36 cells mL1. Conversely, test day milk yield was inversely affected by somatic cell count score, the highest test day milk yield (50.63 kg) was obtained with the lowest score of somatic cells. Additive genetic variances based on somatic cells were low compare to permanent environmental variances. Thus, the possibility of improving these traits is small and takes a long period of time. Conclusion: Finally, it could be concluded that test day milk yield has the possibility of selection for milk yield based on somatic cell measures before the end of lactation mainly at the first two thirds of lactation season enabling inclusion of cows with incomplete lactations in the genetic evaluation which may resulted in improving generation interval, intensity of selection and enhance the genetic progress.
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The majority of the cells in a somatic cell count (SCC) are leukocytes plus some cells from the milk secreting epithelial cells1. The milk secreting cells are part of physiological body mechanisms which are shed to renew the normal body processes. The leukocytes act as a defense mechanism against any disease and they assist in repairing damaged cells2. Also, leukocytes depend on intensity of the cellular immune response as stated by Tsenkova et al.3.
Somatic cell count is a recognized standard indicator of cows health and milk quality with low levels in normal milk that high levels of these cells indicate abnormal conditions as reviewed by Feng and Zheng2.
As cited before, it is important to remember that selection for higher milk yield is a stressful for dairy cows and disturbs the body resistance of the cow especially of mammary gland tissues4. Increasing somatic cells reduces milk yield5, changes in bacteriological, technological traits and chemical composition of milk that reduced milk quality6, increases risk of early culling, labor and treatment costs3.
Milk somatic cells play a protective role against infectious disease in the bovine mammary gland. Several environmental and genetic factors affect the kinds and the numbers of leukocytes that account for the vast majority of somatic cells in milk. Neutrophils constitute the vast majority of somatic cells in mammary glands that are infected with mastitis pathogens1. Milk from healthy udders usually has somatic cells between 50,000 and 200,000 cells mL1 according to ICAR7.
The most important non genetic factors affecting somatic cells are age at calving8, lactation order9, herd and managerial factors10 and calving season11. Other effects include climatic conditions (temperature and humidity), milking frequency, milking interval and feeding program as pointed by Ivkic et al.4. However, the main factor affecting milk somatic cells is mammary gland infection12. Other genetic parameters are essential to study the somatic cell counts in milk. These parameters include heritability, genetic and phenotypic correlations13.
Range of undesirable effect of increasing somatic cells in milk varies in different population. A reduction of 1.30 and 1.09 kg milk yield by increasing somatic cells from 100,000-600,000 cells mL1 had been recorded in Iranian and France Holstein dairy cattle14. Roman et al.15 suggested the amount of additive genetic variance for somatic cells is small. Thus, changes resulting from selection could be obtained after a long period of time.
In a study by Santos et al.16, selection based on 305 days corrected milk would be efficient to the improvement milk yield after the end of lactation season. However, selection based on daily milk yield would be more efficient than 305 days milk yield as test day milk yield brings the possibility to improve milk yield before the end of lactation season mainly at first third part of lactation period.
The present study was undertaken to estimate variance components and genetic parameters for test day milk yield, cumulative milk yield, milk yield corrected in 305 days, days open, days in milk and their associations with somatic cells in milk and to reveal the most efficient selection criterion to improve milk production through decrease somatic cells in milk.
MATERIALS AND METHODS
This study was carried out through field survey of 1739 dairy records for 858 cows by 86 sires US Holstein belonging to Dina farms situated about 80 km in Cairo-Alexandria desert road during the period between 2008 and 2010. The animals were housed free in an open yards, supplied with a cool spraying system during hot climate. Animals had a free access to clean water. The cows were fed ad libitum on Total Mixed Ration (TMR) according to their production state. The ingredient composition of rations were formulated according to National Research Council (NRC, 1916) and kept constant around the year.
All cows were machine milked, 3 times a day with 8 h interval between milkings and 4 times for high producing cows and cows which have mastitis. Cows were dried-off about 2 months before the expected calving date or cows producing 7 kg day1 or less milk yield. Heifers and cows eligible for breeding were artificially inseminated using frozen semen from the best 100 total predicted index Holstein bulls in Canada and USA. Heifers were inseminated for the 1st time when they reached an average of 375-380 kg b.wt. Moreover, breeding after calving occurs after passing a voluntary waiting period of at least 50-60 days and bred cows are being liable to pregnancy diagnosis rectally, 45 days post insemination.
The US Holstein first, second and third lactations with six consecutive test day for both milk production and somatic cell count recorded were selected. Traits under study were cumulative milk yield (CMY, kg), milk corrected in 305 days (MY305, kg), test day milk yield (TDMY) for first six months of lactation period (TDMY1-TDMY6), days open (DO, days), days in milk (DIM, days), somatic cell count (SCC ×103 cells mL1), somatic cell count score (SCCS, U) which is a linear score that is assigned based upon the raw count of somatic cells with a range from 0-9 divisions according to Dairy Herd Improvement Association (DHIA) [0-18, 19-35, 36-71, 72-141, 142-283, 284-565, 566-1130, 1131-2262, 2263-4523 and 4524-9999 ×103 cells mL1, respectively]. The somatic cell was determined with a Fossomatic machine. The SCC determination was performed in the Dairy Services Unit, belonging to the Animal Production Research Institute, Sakha, Kafr El-Sheikh Governorate, Egypt.
The monthly test day SCC was log-transformed into monthly test day somatic cell count score (SCCS) as:
according to Ali and Shook17. To convert the skewed distribution of SCC into normally distributed data.
Data were analyzed statistically by REMAL using the package VCE-6 according to Groeneveld et al.18. Variance components and genetic correlations between traits were estimated using a multi-trait analysis. The model was used to estimate variance components of the studied traits as shown below:
y = Xb + Z1a + Z2c + e
where, y is a vector of records for studied traits; b, a, c and e are vectors of fixed, direct genetic effects, permanent environmental and the residual effects, respectively.
The X, Z1 and Z2 are corresponding design matrices associating the fixed, direct genetic and environmental effects to vector of y. With assumption of direct additive genetic, environmental and residual effects are normally. Standard errors of genetic correlations were obtained using the approximate formula as described by Robertson19 and Falconer and Mackay20. Also, regression model was used to estimate the direction and magnitudes of the relation between the somatic cell count (SCC) as (Y) and the variables that are considered to have effect on it like test day milk yield (TDMY), cumulative milk yield (CMY), milk yield corrected in 305 days (MY305), days open (DO) and days in milk (DIM).
A summary of descriptive statistics of data set and pedigree information of test day milk yield (TDMY), somatic cell count (SCC) ×103 cells mL1, somatic cell count score (SCCS), cumulative milk yield (CMY), milk yield corrected in 305 days (MY305), days open (DO) and days in milk (DIM) are given in Table 1. Adjusted means, standard deviations and coefficient of variations ranged from 2.915 and 0.105 kg and 3.613% for somatic cell score, respectively to 10369 and 2820 kg and 27.20% for milk yield corrected in 305 days, cumulative milk yield and somatic cell count ×103 cells mL1, respectively.
Descriptive statistics for test day milk yield, somatic cell count and score in first six months of lactation period are presented in Table 2. Values of TDMY, SCC and SCCS were significantly different as expected by the criteria selection of the animals. The trends of TDMY (40.26 kg) and SCC (360.15 and 348.78 ×103 cells mL1) were nearly the same to be high at the 6th month of lactation for TDMY, 5th and 6th months of lactation period for SCC, respectively. Moreover, the highest SCCS were observed at 4th and 5th months of lactation period being 2.96 and 2.95, respectively.
|Table 1:||Adjusted means, standard deviations and coefficients of variation for studied traits in US Holstein cows|
TDMY (kg): Test day milk yield per kg, SCC: Somatic cell count ×103 cells mL1, SCCS: Somatic cell count score, CMY (kg): Cumulative milk yield per kg, MY305: Milk yield corrected in 305 days kg1, DO (days): Days open per day, DIM (days): Days in milk per day, SD: Standard deviation and CV (%): Coefficient of variation
|Table 2:||Number of months, means and standard deviations of test day milk yield, somatic cell count ×103 cells mL1 and somatic cell count score for first six months of lactation period in US Holstein cows|
|N: Number of months, TDMY (kg): Test day milk yield per kg, SCC: Somatic cell count ×103 cells mL1, SCCS: Somatic cell count score, SD: Standard deviation and p<0.01|
|Table 3:||Effect of somatic cell count score on somatic cell count, test day milk yield, cumulative milk yield, milk yield corrected in 305 days, days open and days in milk in US Holstein cows|
SCCS: Somatic cell count score, N: Number of months, SCC: Somatic cell count ×103 cells mL1, TDMY (kg): Test day milk yield per kg, CMY (kg): Cumulative milk yield per kg, MY305: Milk yield corrected in 305 days per kg, DO (days): Days open per day, DIM (days): Days in milk per day, SD: Standard deviation, Reg.: Regression coefficient and p<0.01
Estimates of variance components, heritability coefficients and its respective standard errors for cumulative milk yield, days open and test day milk yields (TDMY1-TDMY6) in US Holstein cows
CMY: Cumulative milk yield, DO: Days open, TDMY1-TDMY6: Test day milk yield from 1st month of lactation up to 6th month, Additive genetic variance, Residual variance, Environmental permanent variance, Phenotypic variance, h2: Heritability coefficient and SE: Standard error
Conversely, the lowest were 38.62 kg for TDMY at the 3rd month of lactation, 258.70, 245.39 and 261.45 ×103 cells mL1 for SCC at the first three months of lactation and 2.87 for SCCS at the 1st month of lactation period. The range of standard deviations for the three traits were high that TDMY ranged from 11.09 kg (2nd month) to 11.61 kg (3rd month), SCC ranged from 756.84 ×103 cells mL1 (2nd month) to ×103 cells mL1 (5th month) and SCCS ranged from 0.61 (2nd and 3rd months) to 0.70 (6th month of lactation).
Effect of somatic cell count score on test day milk yield, cumulative milk yield, milk yield corrected in 305 days, days open and days in milk is summarized in Table 3. Somatic cell count score had a significant effect (p≤0.01) on all the previous traits, there is a direct relationship between SCCS and SCC that elevation of SCC (×103) cells mL1 associated by an increasing in score of somatic cells. The highest score (9th) was obtained when SCC approximately being 8517.36 cells mL1. However, test day milk yield (p≤0.01) was inversely affected by SCCS that the highest TDMY (50.63 kg) was obtained with the lowest score of somatic cells.
In regard to calculation of cumulative milk yield and days in milk (p≤0.01), the highest values obtained at the 5th somatic cell count score to be 10186 kg and 405.4 days, respectively. While the lowest values were 8407 kg and 303.6 days obtained at the lowest score, respectively. Days open (p≤0.01) nearly had the same pattern of CMY and DIM that the highest values were in the 4th (259.9 days), 5th (261.8 days) and 6th somatic cells score (256.1 days), however, the lowest was at the first score of somatic cells being 177.6 days.
The highest milk yield corrected in 305 days (p≤0.01) was in the seventh score of somatic cells but the lowest yields obtained at 2nd (10373 kg), 3rd (10062 kg), 4th (10095 kg) and 5th score of somatic cells (10083 kg). Referring to regression coefficient of somatic cell count on milk yield, days open and days in milk, each increase in somatic cells by 1000 cells would associated by decrease in all traits as TDMY by 0.67684 kg, CMY by 183.3 kg, MY305 by 72.37 kg, days open by 6.2518 days and DIM by 6.4787 days.
Estimates of variance components and heritability coefficients for cumulative milk yield, days open and test day milk yield for first six months of lactation period are shown in Table 4. Heritability estimates and additive genetic variances of TDMY tended to increase with the progress in days in milk. Both of heritabilities and additive genetic variances reached a maximum around the fifth month of lactation.
Heritabilities for TDMY ranged from 0.014±0.006 to 0.330±1.430 with the highest values at the 4th and 5th months of lactation period.
|Table 5:||Genetic and phenotypic correlation coefficients between somatic cell count score and both of cumulative milk yield and test day milk yield in first six months of lactation period in US Holstein cows|
|SCCS: Somatic cell count score, CMY (kg): Cumulative milk yield per kg and TDMY (kg): Test day milk yield per kg|
Spearmans rank correlation coefficients between breeding value for somatic cell count score and both of cumulative milk yield and test day milk yield in first six months of lactation period in US Holstein cows
|SCCS: Somatic cell count score, CMY (kg): Cumulative milk yield per kg and TDMY (kg): Test day milk yield per kg|
The lowest heritability coefficients for TDMY were observed in 1st and 2nd months of lactation, showing a similar trend to that calculated for additive genetic variances of these traits. The trends of environmental and residual variances of TDMY are similar to each other. Variance components of days open and cumulative milk yield were high.
Genetic, phenotypic and Spearmans rank correlations between breeding value for somatic cell count score and both cumulative milk yield and test day milk yield in first six months of lactation are presented in Table 5 and 6. Present findings showed positive genetic, phenotypic and Spearmans rank correlations of SCCS with CMY and negative with TDMY at first six months of lactation period.
As a whole, large differences did exist between data set in their description than those reported by most of literatures may be due to different number of records and/or limited number of years covering the data of the present study. In general, wide range of both standard deviations and coefficient of variations among studied traits suggested possibility of selection and genetic improvement.
The present mean for cumulative milk yield was higher than the most those reported in the literatures [Shalaby et al.13 (6716 kg)] on Friesian cattle in Egypt. However, they calculated a lower mean for days open than the present study being 144.5 days in all lactations. The same trend was reported for days in milk (319.8 days) by the same researchers.
Referring to the somatic cell count in the present study, it was lower than the most those reported in the literatures [El-Arian and El-Awady21 (426 ×103 cells mL1), Fadlelmoula et al.22 (317 ×103 cells mL1) and Shalaby et al.13 (505.23 ×103 cells mL1)]. The present average of milk yield corrected in 305 days and TDMY were higher than those obtained by Santos et al.16 being 1783.20 kg for MY305 and ranged from 5.12 kg (TDMY10) to 8.39 kg (TDMY2) for TDMY. Usually high milk production associated by high level of somatic cells in milk due to stress effect of high production which resulted in an increasing in somatic cell score.
Reverse relationship between SCCS and TDMY is in accordance with the reports of Gaafar et al.23 and Radwan24 that during high test day milk yield there is a small amount of SCC in a large amount of milk (dilution effect). While if the same amount of somatic cells present in a small amount of milk appears as high somatic concentration and absence of dilution effect as reviewed by Miller et al.25. Moreover, Hagnestam-Nielsen et al.26 reported that daily milk loss at SCC of 500,000 cells mL1 ranged from 0.7-2.0 (3-9%) in primiparous cows according to lactation stage, while in multiparous cows, corresponding loss being 1.1-3.7 (4-18%) in Swedish Holstein cows.
The significant effect (p≤0.01) of SCCS on both cumulative milk yield and milk yield corrected in 305 days is in consonance with the finding of Radwan24 who obtained the highest total milk yield and 305 days mature equivalent at the highest SCC category. There is a substantial evidence to suggest that high milk yields are as related to high mastitis levels, although this relationship is complex and inter-relates genetics, feeding and management as revealed by Rajala and Grohn27. However, Kehrli and Shuster1 and Kiiman and Kaart28 indicated that milk production and milk quality are negatively impacted with the presence of inflammation in infected mammary glands.
Extension of days open as the result of elevation of somatic cells in milk is agreed with the reports of Schrick et al.29 who demonstrated that the onset of clinical mastitis and elevate the number of SCC in milk before first service increased the number of days to first service and extended calving-conception interval compared with cows free from clinical mastitis or cows with clinical mastitis after establishment of gestation. This may be due to the effect of mastitis on elevating concentrations of PGF2α, which associated with decrease in embryonic development and ultimately resulted in an increased number of services per conception and number of days open. Different results had been previously reported by El-Sayed30 who stated that estimates of partial linear and quadratic regression coefficients of somatic cell counts on days open were not significant.
Present results suggested that a selection program designed to improve milk yield would achieve days in milk either using cumulative milk yield and/or average daily milk yield as the criterion without using direct selection for days in milk. The previous indication is assured by the reports of Santos et al.16 in Guzerat cows and Madalena31 who indicated that selecting on the base of lactation length and yield would be more efficient for improving milk production than selecting on the base of lactation yield only in tropical cattle.
Regression of somatic cell count on milk yield, days open and days in milk is in agreement with the reports of El-Awady32 and Gaafar et al.23. Increasing SCC in milk causes decrease of total milk yield, 305 days mature equivalent and test day milk yield by 0.02, 0.01 and 0.13%, respectively and the regression coefficients were 0.04, 0.06 and 0.58 as reported by Radwan24.
Based on measures of somatic cells in milk, most results suggest that amount of additive genetic variances compared to environmental variances were low to medium. Thus, changes resulting from selection could be obtained over a long period of time. According to the result of this study, additive genetic, residual and phenotypic variances for CMY were higher than those obtained by El-Awady32 who calculated them to be 1789, 2796 and 4585 kg. Also, they calculated the same variance components for SCC being 1138, 4864, 6002 ×103 cells mL1, respectively in lactating Egyptian buffalo.
Present findings were in the same line with Santos et al.16 who reported that variances of TDMY tended to decrease with days in milk until the 6th month of lactation period in Guzerat cows. However, heritability estimates and additive genetic variances reached a maximum at the 2nd month of lactation period. The maximum values of heritability estimate were not the same which may explain by presence of differences between shapes of the lactation curve between two breeds.
In a study involving the Holstein cattle in Brazil, De Melo et al.33 estimated heritability of TDMY being 0.36 and 0.22 by Bignardi et al.34 with the highest estimates at the 4th and 3rd months of lactation period. High variance components of days open and cumulative milk yield indicated wide variability among animals, presence of genetic variation which enables mass selection among animals.
Additive genetic variance, permanent environmental variance and heritability estimate for cumulative milk yield in the present study were higher than those obtained by Roman et al.15 being 44282 and 38986 kg and 0.18, respectively in Jersey cattle. This discrepancy may reflect variations in breed, number, sampling variation and statistical model. They also calculated the same previous parameters for SCC and SCCS to be 8662.34, 6281.77 cells mL1 and 0.07 for SCC and 0.0509, 0.0533 and 0.07 for SCCS, respectively.
Conflicting results were recorded by [Juozaitiene and Juozaitis35 (-0.35), Roman and Wilcox36 and Miglior et al.37 (-0.22)] who reported negative phenotypic correlations between milk yield and SCCS. This finding suggested high milk yield is linked to high somatic cell count and high mastitis level, because cows with high production are more susceptible to infection, which would activate cows natural immune system leading to increase somatic cell concentration in milk as a protective mechanism.
Negative phenotypic and genetic associations between TDMY and SCCS explained as increasing milk yield may associated by decreasing SCC (dilution effect) or decreasing milk yield may associated by increasing SCC which diagnosed as a pathological condition. Positive genetic correlation between SCCS and milk yield in the current study was in agreement with the findings of Carlen et al.38 (0.17) and Radwan24 (0.01). Conversely, Al-Seaf et al.39 being -0.45 and Roman and Wilcox36 were -0.22 and -0.13 for both genetic and environmental correlations, respectively.
Furthermore, Jamrozik et al.40 reviewed phenotypic relationships between milk and SCCS in the first three lactations seem to be driven by a combination of two mechanisms. An infection effect caused a decrease in milk yield for cows with a higher SCCS and the stress effect resulted in an increase of SCCS for higher producing cows in Canadian Holstein.
Negative phenotypic correlation between TDMY and SCCS was in consonance with the reports of Radwan24 (-0.62). Daily milk yield phenotypically and genetically antagonistic with SCCS which reflected both true biological effects of udder inflammation and a dilution effect. However, the same researcher calculated positive genetic correlation (0.58) between TDMY and SCCS in Holstein-Friesian cows in Egypt.
Although this findings suggest that selection on the base of cumulative milk yield would be more efficient as a criterion to the improvement milk yield in the Holstein breed. It can be concluded that the use of daily milk yield brings the possibility of selecting for milk yield before the end of lactation period mainly at the first two thirds of lactation season allowing inclusion of cows with incomplete lactations in the genetic evaluation which may affect genetic improvement as the bulls evaluation would include more daughters, so more animals would available as replacements resulted in improving generation interval, intensity, accuracy of selection and rapid genetic progress.
We would like to express our sincere thanks to Prof. Dr. Nazem Abdel Rhman Shalaby, Professor of Animal Breeding, Faculty of Agriculture, Mansoura University for his kind help, keen guidance and assistance during data analysis of this study.
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