Abstract
OBJECTIVE
Quantify the minimum individual cow colostral immunoglobulin G (IgG) concentration required for pooling to achieve adequate transfer of passive immunity in calves.
ANIMALS
201 Jersey cows.
METHODS
Colostrum was collected from 28 pools and heat treated before being fed to calves or stored. Parity, total number of cows contributing to the pool, individual cow colostral volume contributions, and total volume of each colostrum pool were recorded. Colostrum IgG concentrations in individual and pooled (pre- and post-heat treatment) samples were analyzed by radial immunodiffusion and Brix refractometry. Colostral IgG concentration of ≥ 50g/L was considered the current recommended dairy industry standard for acceptable colostrum quality. Multivariable models were performed to determine factors affecting pooled colostral IgG concentrations. The minimum colostral IgG concentration required for pooling to achieve the recommended total mass of at least 200g IgG to be fed to a calf was calculated.
RESULTS
Total pool volume and the number of cows contributing to the pool were significant factors affecting IgG concentration. Colostrum pools from ≤ 7 cows, with a minimum pool IgG concentration of 70.4 g/L (22.9% Brix) or colostrum pool volume ≤ 40 L, with a minimum pool IgG concentration of 66.2 g/L (21.8% Brix) achieved the recommended total mass of at least 200g IgG in 4L of colostrum.
CLINICAL RELEVANCE
When feeding pooled colostrum, IgG concentrations higher than the industry standard of 50 g/L is recommended to reduce the risk of failure of transfer of passive immunity in calves.
Introduction
Calves are born agammaglobulinemic and rely on colostrum ingestion to absorb essential immunoglobulins for defense against disease.1 Adequate transfer of passive immunity (ATPI) through colostrum is dependent on; 1) whether the calf ingests a sufficient mass of immunoglobulin G (IgG), which is dependent on the volume, and IgG concentration of the colostrum fed;2 and 2) the efficiency with which this IgG is absorbed which is dependent on the time postpartum at which colostrum is ingested.3 Pooling colostrum has benefits including being both labor reducing and an efficient way to feed a large number of calves. It is still a common practice on over 50% of large US dairies4 but its effect on transfer of passive immunity is debated and not well investigated. Although it has been reported that pooling colostrum has a minimal effect on dairies with cows producing colostrum with relatively high mean IgG concentrations,5-6 pooling might increase the likelihood of failure of transfer of passive immunity (FTPI) by decreasing colostral IgG concentrations on farms with low to average (up to the anecdotal recommendation of 50g/L IgG) colostral IgG concentrations.7 The minimum concentration of 50g/L of IgG in colostrum to achieve ATPI is an arbitrary, anecdotal recommendation that assumed that first lactation cows produce 2 kg of colostrum with 5% IgG concentration in 1970.8 The average dairy cow milk and colostrum yield has drastically increased since the 70s,9 therefore applying a minimum concentration of 50 g/L IgG may be inaccurate in defining high quality colostrum.
To the authors’ knowledge, no peer reviewed studies are reported describing the minimum individual cow colostral IgG concentrations required for pooling to achieve ATPI in calves, nor investigating if calculated mean pool IgG is similar to measured pool IgG. Therefore, our objectives were to: 1) quantify the minimum individual cow colostral IgG concentrations required for pooling colostrum to achieve ATPI in calves and 2) compare the accuracy of calculating mean pool IgG concentration based on individual cow colostral IgG concentrations with the measured pool IgG concentration. We hypothesized that: 1) minimum required colostral IgG for pooling is higher than the current industry recommendation of 50 g/L IgG; and 2) predicted mean pool colostral IgG based on individual cow IgG concentrations will be similar to the measured pool IgG.
Methods
Farms of study
A prospective cross-sectional study was performed on 2 conventional Jersey dairy farms located in Merced County, California. The 2 farms were within 1 km of each other and were managed by the same personnel. Both farms milked cows 3 times a day: at 5am, 12pm, and 5pm. Farm A milked 1,800 cows, whereas Farm B milked 1,300 cows. The 2 farms had separate milking parlors, but they processed colostrum from both farms in 1 single colostrum processing kitchen. Colostrum from the single colostrum processing kitchen was fed to calves born from both farms. Calves from both farms were housed in hutches located on the same physical area.
Sample size was based on the farms’ mean individual colostral IgG concentration of 67 ± 3.3 g/L (range, 33 to 72 g/L).10 Given that calves on this farm were fed 4 L of colostrum with an average concentration of 67 g/L of IgG, then an average of 268 g (67 X 4) IgG, with a range of 132 g (33 X 4) to 288 g (72 X 4) was fed to the calf. Assuming a minimum of 150 g to 200 g of IgG is required for adequate transfer of immunity11 sample size was calculated to detect a difference of 2 g to 18 g (150 to 132) of IgG among the colostrum pools, a standard deviation of 3.3,10 power of 80%, and a type-1 error of 5%, using a statistical software (JMP Pro v16; SAS Institute). A sample size of 24 colostrum pools was required. To account for a 10% dropout proportion from lost samples, the total sample size required was at least 27 colostrum pools. The study was performed from June 2021 to October 2021 and approved by the University of California-Davis Institutional Animal Care and Use Committee (#22251).
Cows
Cows were monitored for pending parturition by farm personnel and housed in individual calving pens after the first stage of labor. After parturition, cows were milked to collect colostrum on the next scheduled milking, that is, at 5am, or 12pm, or 5pm. Identity (radiofrequency identification ear tags), parity, and volume of first milking colostrum for each cow were recorded. A composite colostrum sample (50 mL) was collected into a tube (Conical Centrifuge tube; Thermo Fisher Scientific) from each individual cow for subsequent IgG concentration analysis. Data and samples were collected by the research investigators.
Colostrum processing
Each colostrum pool was mixed in a custom made on-farm 80-liter capacity pasteurizer tank prior to heat treatment. Colostrum was heated in the pasteurizer tank with continuous agitation until a temperature of 60 °C was reached over approximately a 1-hour period. The colostrum was then collected after cooling to 27 °C. Two samples of colostrum were collected per pool; one 50 mL sample was collected prior to and one 50 mL sample was collected after heat treatment for subsequent IgG concentration and bacterial culture. Colostrum was then frozen at –20 °C until feeding time. Colostrum was defrosted in a warm water bath and then immediately fed to the calves. Only colostrum frozen and stored for up to 72 hours was fed to the newborn calves by oroesophageal intubation whereas colostrum frozen for more than 72 hours was added to milk and bottle fed to calves older than 24 hours.
Sample analysis
Colostrum samples were analyzed for IgG concentrations using single radial immunodiffusion (Triple J Farms) according to the manufacturer’s recommendations, and as previously described.6 The radial immunodiffusion (RID) assay was considered the reference method for determining colostral IgG concentrations. Assessment using a Brix refractometer (Digital Brix Refractometer MA871, Milwaukee Instruments Inc) was performed on colostrum according to the manufacturer’s recommendations. Bacterial counts in colostrum samples were determined pre- and post-heat treatment. All colostrum samples were examined for standard plate count (SPC) to enumerate coliforms, Staphylococcus spp, Bacillus spp, Streptococcus spp, and Pseudomonas spp. Bacteriologic analysis of colostrum samples was performed at the California Animal Health and Food Safety Laboratory (CAHFS), Tulare, California.
Statistical analysis
Data was checked for normality using the Shapiro-Wilk test. Mean ± SEM were reported when data were normally distributed whereas median and range were reported when data was not normally distributed. Descriptive statistics calculated for cows included the number of cows enrolled, parity, individual first milking colostrum volume and IgG concentrations, pool colostrum volume and number of cows contributing to a pool, pooled colostral IgG concentrations before and after heat treatment, and Brix refractometry for individual cow colostrum, as well as Brix refractometry before and after heat treatment for pooled colostrum.
First milking colostral volume and IgG concentrations among cows in the first, second, and third or greater lactation were compared using a Kruskal-Wallis test. Pool colostral IgG concentrations before and after heat treatment were compared using a Wilcoxon matched pairs signed rank test. Comparison of predicted pool IgG concentration (calculated based on individual cow IgG concentrations and colostral volume produced by individual cows) and measured pool IgG using RID before and after heat treatment were compared using a Wilcoxon matched pairs signed rank test.
Predictors of pool colostral IgG concentrations before and after heat treatment were determined using a multivariable mixed model. Prior to considering the variables in the model, univariate analysis was performed. Variables with a P < .2 to enter were considered in the model. The model estimates were fitted using the restricted maximum likelihood method. The fitness of the final model was checked using the F-test. In the models, number of cows contributing colostrum to a pool, pool volume, parity, individual cow colostrum volume, and individual cow colostral IgG were considered fixed effects, whereas timing of collection of colostrum (morning or afternoon) and source of colostrum (Farm A or B) were considered random effects. Multicollinearity in the multivariable model were assessed using the coefficient of determination (R2) for each variable with other variables and the variance inflation factor (1/[1-R2]). Values of R2 > .75 and variable inflation factors > 4 indicated multicollinearity.12 Predictor variables that were significantly correlated were not included in the same model. When applicable, first order interactions between variables were considered. After the variables that predicted pool IgG were determined, the minimum colostral IgG concentration (g/L) required to provide at least 200 g of IgG in 4 L of colostrum was determined. The 200 g of IgG was considered based on previous studies that reported that at least 200 g of IgG in colostrum is recommended for adequate transfer of passive immunity in dairy calves.2,11 The endpoint of 200 g total IgG was chosen for our study because it was based on studies that evaluated the interactions between colostral IgG concentrations, frequency of colostrum feeding, dam parity, calf birth weight, age at first feeding colostrum, colostrum volume, and time of colostrum collection.11
The Brix refractometer is an on-farm, cow-side, indirect screening testing method for assessing colostrum quality by estimating colostral IgG concentrations. For the purpose of the study, the Brix refractometer was used to estimate colostral quality in individual and pooled colostrum samples and compared to the reference method, radial immunodiffusion. The diagnostic sensitivity and specificity with 95% CI of the Brix refractometer measurement was determined at the minimum pool colostral IgG concentrations required to provide 200 g of IgG in 4 L using 2 X 2 frequency tables. Sensitivity of the Brix refractometer was defined as a positive test result indicating an inadequate pool colostral IgG concentration (less than the calculated minimum pool colostral IgG) as determined by RID. Specificity of the Brix refractometer was defined as a negative test result indicative of an adequate pool colostral IgG concentrations (≥ the calculated minimum pool colostral IgG) as determined by RID. The endpoint of the Brix refractometer that maximized sensitivity and specificity was determined using receiver operating characteristics curves. In our study, a colostrum sample with inadequate colostral IgG from an individual cow or pool would not be considered for the first feeding in calves.
Bacterial counts were not normally distributed, and logarithmic transformation was performed to approximate normal distribution. Log reduction of bacterial counts was calculated by log10 (cfu/mL before heat treatment) – log10 (cfu/mL after heat treatment). Percentage log reduction was calculated by:
100 X [log10 (cfu/mL before heat treatment) – log10 (cfu/mL after heat treatment)]/ log10 (cfu/mL before heat treatment).
Percentage reduction for pool samples with a zero count before heat-treatment could not be determined.
In all analyses JMP Pro v16 (SAS Institute) and Graph Pad Prism v9.0 (Graph Pad Software) were used. P < .05 was considered significant.
Results
Cows and colostrum pools
Two hundred and one cows were enrolled and contributed to 28 pools of colostrum. One hundred and ten cows were enrolled from farm A whereas 91 cows were enrolled from farm B. The number of cows contributing to each pool ranged from 4 to 10. This number was dictated by the number of cows that calved on a given day and the pasteurizer size of 80 L. Median (range) individual first milking colostrum volume was 6.8 L (range, 0.3 to 27.2 L). Median (range) pool volume was 55.6 L (range, 26.6 to 70.7 L). Of the cows enrolled 79, 38, and 84 were in the first, second, and third or greater lactation, respectively. Median (range) individual colostral IgG concentration for all cows was 74.4 g/L (range, 1.8 to 131.7 g/L). Median colostral IgG concentrations for cows in the first, second, and third or greater lactation were 74.0 g/L (range, 24.8 to 131.7 g/L), 76.4 g/L (range, 16.4 to 119.3 g/L), and 79.2 g/L (range, 1.9 to 130.2 g/L), respectively. There was no significant difference (P = .672) in the colostral IgG concentrations among the cows in the first, second, third or greater lactation. Median (range) pool colostral IgG concentrations before and after heat treatment were 84.7 g/L (range, 44.7 to 126.8 g/L) and 70.4 g/L (range, 40.7 to 106.7 g/L), respectively. Median decrease in pool colostral IgG concentrations after heat treatment was 9 g/L (P < .0001). Median (range) colostral Brix refractometer measurement for individual cows was 22.8% (range, 10% to 31.5%). Median (range) pool colostral Brix refractometer measurement before and after heat treatment was 22.9% (range, 20.5% to 25.2%) and 22.3% (range, 20.5% to 25.4%), respectively. There was no significant difference (P =.092) between the Brix refractometer measurements before and after heat treatment.
Predictors of pool IgG concentrations
Median (range) predicted pool IgG concentration calculated based on individual cow IgG concentrations and colostral volume produced by each cow preheat treatment was 75.1 g/L (range, 56.7 to 87.3 g/L). Predicted pool IgG concentrations were lower than the measured (by RID) preheat treated pool IgG concentrations (75.1 vs 84.7 g/L; P = .03). Predicted pool IgG concentrations were not significantly different from measured post heat treated pool colostrum IgG concentrations (75.1 vs 70.4 g/L; P = .465).
Pool volume and number of cows contributing to a pool were significantly correlated (r = .71; P < .001), therefore the 2 variables were not included in the same model. The number of cows contributing colostrum in a pool (P = .346), pool volume (P = .180), parity (P = .316), individual cow colostrum volume (P = .308), individual cow colostral IgG (P = .430), timing of collection of colostrum (P = .537), and source (farm A vs farm B) of colostrum (P = .602) were not significant predictors of preheat treated colostrum IgG concentrations.
Number of cows contributing to a colostrum pool (P < .0001), pool volume (P = .0011), and source of colostrum (P = .037) were significant predictors of pool colostral IgG concentrations after heat treatment of colostrum. Two models predicting pool colostral IgG concentrations after heat treatment were determined, and are summarized below:
Model 1 = When number of cows contributing to the pool variable was entered into the model:
Pool IgG concentration (g/L) = 98.2 – 3.98 X number of cows contributing to a pool.
Model 2 = When total pool volume variable was entered into the model:
Pool IgG concentration (g/L) = 83.1 – 0.36 X total pool volume – 2.51 X Farm B.
The predicted minimum colostral IgG concentrations to deliver a total of 200g IgG in 4L of colostrum based on models 1 and 2 were calculated (Tables 1 and 2, respectively). Based on Model 1, and considering the lower limits of the 95% CI, the minimum pool IgG concentrations required was 70.4 g/L, and ≤ 7 was the optimal number of cows required to contribute to the pool to deliver a total of 200 g IgG in 4 L of colostrum. Based on Model 2, and considering the lower limits of the 95% CI, the minimum pool IgG concentrations required was 66.2 g/L and ≤ 40 L was the optimal pool volume of required colostrum to deliver a total of 200 g IgG in 4 L of colostrum (Table 2). Parity (P = .977), individual cow colostrum volume (P = .267), individual cow colostral IgG (P = .577), and timing of collection of colostrum (P = .597) were not significant predictors of colostral pool IgG concentration after heat treatment.
Calculation of minimum colostral immunoglobulin G (IgG) concentrations post heat treatment to deliver a total of 200 g of IgG in 4 L based on the number of cows contributing to a pool using model 1.
| Number of cows contributing to a colostrum pool | Calculated (95% CI) IgG concentration in a pool (g/L) | Calculated (95% CI) total IgG in 4 L of colostrum (g) |
|---|---|---|
| 4 | 82.3 (61.7, 102.9) | 329.2 (246.9, 411.6) |
| 5 | 78.3 (57.8, 98.9) | 313.2 (231.0, 395.7) |
| 6 | 74.4 (53.8, 94.9) | 297.6 (215.1, 379.8) |
| 7 | 70.4 (49.8, 100.0) | 281.6 (199.2, 363.9) |
| 8 | 66.4 (45.8, 87.0) | 265.6 (183.3, 348.0) |
| 9 | 62.4 (41.8, 83.0) | 249.6 (167.4, 332.1) |
| 10 | 58.5 (37.9, 79.0) | 234.0 (151.5, 316.1) |
Model 1 = Pool IgG concentration (g/L) = 98.2 – 3.98 X number of cows contributing to a pool.
The minimum and maximum numbers of cows contributing to each in this study were 4 and 10, respectively.
Calculation of minimum colostral immunoglobulin G (IgG) concentrations post heat treatment to deliver a total of 200 g of IgG in 4 L based on pool volume, using model 2.
| Total colostral pool volume (L) | Calculated (95% CI) IgG concentration in a pool (g/L) | Calculated (95% CI) total IgG in 4 L of colostrum (g) |
|---|---|---|
| 26.6 | 71.0 (54.6, 92.5) | 284.0 (218.5, 369.9) |
| 30 | 69.8 (53.4, 91.2) | 279.2 (213.6, 365.0) |
| 35 | 68.0 (51.6, 89.4) | 272.0 (206.4, 357.8) |
| 40 | 66.2 (49.8, 87.6) | 264.8 (199.2, 350.6) |
| 45 | 64.4 (48.0, 85.8) | 257.6 (192.0, 343.3) |
| 50 | 62.6 (46.2, 84.0) | 250.4 (184.8, 336.1) |
| 55 | 60.8 (44.4, 82.2) | 243.2 (177.6, 328.9) |
| 60 | 59.0 (42.5, 80.4) | 236.0 (170.4, 321.7) |
| 65 | 57.2 (40.8, 8.6) | 228.8 (163.2, 314.5) |
| 70 | 55.4 (39.0, 76.8) | 221.6 (156.0, 307.3) |
| 70.7 | 55.2 (38.7, 76.6) | 220.8 (155.0, 306.3) |
Model 2 = Pool IgG concentration (g/L) = 83.1 – 0.36 X total pool volume – 2.51 X Farm B.
The minimum and maximum numbers of pool volumes were 26.6 and 70.7 L, respectively.
The sensitivity (95% CI) and specificity (95% CI) of the Brix refractometry at the 70.4 g/L endpoint (Model 1) was 0.78 (0.68, 0.86) and 0.49 (0.39, 0.59), respectively, with Brix refractometer measurement of 22.9% maximizing both sensitivity and specificity. The sensitivity and specificity of the Brix refractometry at the 66.2 g/L endpoint (Model 2) was 1.0 (0.97, 1) and 0.47 (0.37, 0.58), respectively, with a Brix refractometer measurement of 21.8% maximizing both sensitivity and specificity.
Bacterial counts in colostrum before and after heat treatment
Descriptive statistics of bacterial counts (cfu/mL) before and after heat treatment are summarized (Table 3). Log reduction and percent log reduction in bacterial counts after heat treatment are summarized (Table 4). Two pooled colostrum samples with zero counts before heat treatment, for which Staphylococcus spp was identified after heat-treatment were excluded from analysis. Bacillus spp was identified in a single pooled sample and was excluded from analysis.
Bacterial counts (cfu/mL) before and after heat treatment in 28 colostrum pools in 201 Jersey dairy cows.
| Bacteria identity | Mean ± SD | Median (range) |
|---|---|---|
| Coliforms | ||
| Before heat treatment | 927,147 ± 1,535,817 | 140,000 (100–4,400,100) |
| After heat treatment | 3,333 ± 12,910 | 0 |
| Staphylococcus spp | ||
| Before heat treatment | 432,771 ± 1,628,779 | 7,000 (0–7,500,000) |
| After heat treatment | 51,167 ± 131,789 | 1,000 (0–530,000) |
| Streptococcus spp | ||
| Before heat treatment | 15,282,929 ± 21,663,296 | 1,350,000 (20,000–66,000,000) |
| After heat treatment | 6,931,693 ± 11,522,305 | 650,000 (4,500–38,500,000) |
| Pseudomonas spp | ||
| Before heat treatment | 1,240,536 ± 2,199,563 | 265,000 (3000–10,000,000) |
| After heat treatment | 0 | 0 |
Bacillus spp were only identified in 1 sample (1,000 cfu/mL before heat treatment and 0 cfu/mL after treatment) and were excluded from the analysis.
Log reduction and percentage reduction of bacterial counts after heat treatment in 28 pooled colostral samples from 201 Jersey cows.
| Bacteria identification | No. of samplesc | Log reductiona | Percentage log reductionb | P value |
|---|---|---|---|---|
| Coliforms | 15 | 4.5 | 94.3 | < .001 |
| Staphylococcus spp | 19 | 1.9 | 44.9 | < .001 |
| Streptococcus spp | 28 | 0.3 | 4.3 | .047 |
| Pseudomonas spp | 14 | 5.4 | 100 | —d |
aLog reduction = log10 (cfu/mL before heat treatment) – log10 (cfu/mL after heat treatment).
bPercentage log reduction = 100 X [log10 (cfu/mL before heat treatment) – log10 (cfu/mL after heat treatment)]/ log10 (cfu/mL before heat treatment).
cNumber of samples represents the number of pooled colostrum samples for which the specific bacteria were identified.
dP value for reduction in bacterial counts for Pseudomonas could not be calculated because the variance was equal to zero. Bacterial counts for Pseudomonas after heat treatment was equal to zero in all pooled colostrum samples.
Percentage reduction for pool colostrum samples (2 samples for which Staphylococcus was identified after heat treatment) with a zero count before heat treatment could not be determined.
Discussion
The minimum pooled colostral IgG concentrations required to deliver the recommended 200 g total IgG to the calf was higher than the recommended 50 g/L8 consistent with our hypothesis. Total volume of the colostrum pool and number of cows contributing to the pool affected colostrum quality. Colostrum pools from ≤ 7 cows, with a minimum IgG concentration of 70.4 g/L or colostrum pool volume ≤ 40 L, with a minimum IgG concentration of 66.2 g/L were determined to achieve the recommended mass of 200 g fed to the calf. As the number of cows contributing to the pool or pool volume increased, the required colostral IgG concentration that would deliver 200 g total IgG also increased. This suggests that there may be a dilution effect with larger pool volumes. Predicted pool IgG concentrations based on individual cow colostral IgG were not different from measured post heat treated pooled colostrum IgG concentrations consistent with our hypothesis. This result remains unexpected and unexplained because if results for our first hypothesis suggested a dilution effect and heat-treatment significantly decreased pool IgG concentrations, a lower measured pool IgG concentration would be expected compared to the predicted IgG concentrations based on individual cow colostral IgG. In contrast, the predicted IgG concentrations based on individual cow colostral IgG were significantly lower than the preheat treatment colostral pool IgG. The reason for this difference remains unknown. One consideration would be the effectiveness of the custom-made pasteurizer and whether denaturing of colostral IgG varied more when heat treating larger volumes of colostrum. This suggests that comparing predicted colostral IgG concentrations based on individual colostral IgG and measured pool IgG might be inconsistent and may depend on other colostral management practices such as heat treatment of colostrum.
In our study, we also assessed the accuracy of the Brix refractometer, an on-farm method to assess colostrum quality, at the determined endpoints of 66.2 and 70.4 g/L IgG. The endpoints of 22.9%13 when number of cows are considered, and 21.8%14 when pool volume is considered are consistent with previous recommendations at the current minimum recommendation of 50 g/L. It should be noted that heat treatment of colostrum did not significantly change the test results of assessment by the Brix refractometer. This result is expected because the Brix refractometer is not sensitive to temperature changes of the colostrum.15 The sensitivity (0.78 and 1) of the Brix refractometer in identifying colostrum pools with inadequate IgG concentrations was consistent with previous studies.16 However, specificity of the Brix refractometer at the determined endpoints were low suggesting that some colostral samples with the recommended IgG concentrations may be classified as having insufficient colostral IgG concentrations. Practically, most farms are unlikely to discard colostrum perceived to be of low IgG concentration but rather add to the milk to be fed to calves older than 24 hours similar to our farms of study or feed the colostrum as the second feeding for calves < 24 hours. Therefore, the consequence of misclassifying pools with sufficient IgG concentration as insufficient will have minimal impact in achieving ATPI in calves. It is important to note that the sensitivity of the Brix refractometer is higher when pool volume rather than the number of cows contributing to the pool is considered. This result has practical implications because it is more practical to measure the pool volume prior to heat-treatment or feeding to calves compared to predicting the number of cows calving and their first milking colostrum volume. Consequently, we recommend using the Brix refractometer endpoints for testing on pools ≤ 40 L.
Although the median colostral IgG concentration for all cows was relatively high (74.4 g/L), the range was wide (range, 1.8 to 131.7 g/L). The wide range of colostral IgG and higher volume of colostrum pools in our study could explain the suggestion of a dilution effect in contrast to previous studies5,6 that reported a non-significant effect of pooling on colostral IgG. There were no significant differences in colostral IgG concentrations among cows in the first, second, and third or greater lactations, in contrast to previous studies17,18 that reported higher colostral IgG concentrations in third or greater lactations compared to first or second lactation cows. However, the comparison of colostral IgG concentration results among cows in the second and third lactations were similar to other studies performed in a similar geographical area.19 Therefore, consistent with current recommendations, exclusion of colostrum samples for feeding calves should be based on the quality testing rather than parity.
In our study, heat treatment of colostrum reduced but did not eliminate all organisms (Tables 3 and 4) consistent with previous studies.20 Although there are no peer-reviewed guidelines for evaluating bacteriological quality of colostrum, guidelines have been proposed for raw bulk tank milk21; standard plate count ≤ 5,000 cfu/mL, environmental Streptococci ≤ 500 cfu/mL, coagulase negative Staphylococcus ≤ 500 cfu/mL, coliforms ≤ 50 cfu/mL, gram-negative non-coliforms ≤ 200 cfu/mL; Staphylococcus aureus and Streptococcus agalactiae should not be detected. Based on these recommendations, heat treatment effectiveness against the specific pathogens was variable in our study. However, the recommendations for milk are not directly applicable to colostrum because microbiological quality assessment for milk are based on standards for human consumption.22 Heat treatment resulted in a median decrease in pool colostral IgG concentration of 9 g/L, consistent with previous studies that determined that pasteurization’s effect on IgG concentrations23,24 does not increase the risk of FTPI.25,26 Although the colostrum heat treatment process (60 °C for 60 minutes) was appropriate and consistent with previous studies,20 it is important to note that the pasteurizer used was custom-made to handle large volumes of colostrum.
Our study had limitations. Only Jersey cows were enrolled in our study and therefore our study results may have limited external validity for other dairy breeds. The results of our study are applicable to farms that pool and heat treat colostrum. The impact of heat treatment on IgG concentrations when handling larger volumes of colostrum in this study is unclear. Therefore, future studies should consider enrolling farms that do not perform heat treatment of colostrum. Additionally, our results are applicable to farms that pool colostrum from 4 to10 cows or produce pool volumes ranging from 26 to 70 L. Future studies could also investigate calf transfer of passive immunity status after following the aforementioned guidelines for colostrum pools ≤ 7 cows and ≤ 40 L. Colostrum pools from ≤ 7 cows, with a minimum IgG concentration of 70.4 g/L or colostrum pool volume ≤ 40 L, with a minimum IgG concentration of 66.2 g/L were determined to achieve the recommended mass of 200 g fed to the calf and are recommended. When the Brix refractometer is used to assess the quality of colostrum at the determined colostral IgG concentrations, endpoints of 22.9% when number of cows are considered, and 21.8% when the volume of colostrum pool is considered, are recommended. Predicted pool IgG concentrations based on individual cow colostral IgG are not different from measured post heat treated pool colostrum IgG, but this association might be inconsistent.
Acknowledgments
The authors thank all the staff at the farms of study for their assistance.
Disclosures
The authors have nothing to disclose. No AI-assisted technologies were used in the generation of this manuscript.
Funding
The study was supported by a grant from the National Institute of Food and Agriculture (CALV-AH-412), a Ross University School of Veterinary Medicine intramural grant (#42002-2022), and the University of California-Davis Student Training in Advanced Research funds. Funding sources did not have any involvement in the study design, data analysis and interpretation, or writing and publication of the manuscript.
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