Subclinical Ketosis Monitoring Options

During the transition period, the cow's body experiences drastic metabolic changes. After calving, lactating dairy cows naturally decrease dry matter intake (DMI) due to the advanced stage of gestation. The lower DMI typically leads to a negative energy balance (NEB). This plays a significant role in Subclinical Ketosis (SCK) development during just a few weeks. Thus, it is crucial to monitor these sensitive times of the cows' productive lives.

Dairy producers have a choice of direct and indirect monitoring for SCK. For direct or on-the-cow level monitoring, they can use cow-side tests for urine or milk to directly test for ketone bodies which, in elevated numbers, are indicators of SCK or ketotic condition. Cow-side tests are quick, simple to use, and provide real-time results. However, they are not accurate as they yield high variability caused by diurnal variation, high levels of somatic cells in the milk, temperature, and time of reading, and can be misinterpreted (Krogh, 2011; Oetzel, 2015).

Another cow-side test is a blood test where a blood sample is placed on a test strip and inserted into a reader. This test is much more accurate than the milk and urine tests. All these tests require a little investment for the test strips and the reader. Also, they are not suitable for whole herd monitoring.

For the indirect monitoring, fat and protein percentages reported in the DHIA 202 Herd Summaries have been used as a good monitoring tool to assess possible SCK on the herd level. In addition, the fat-to-protein ratio can be calculated from the fat and protein percentages.

The changes in fat and protein percentages and fat-to-protein ratio between different DIM within and across lactations have been regarded as good indicators for abnormalities. With little effort, producers can monitor the long-term trends in these milk components. With the help of herd management software, they can also determine the prevalence of SCK in the herd and which group of cows is affected most.

The DHIA 202 Herd Summary 'Stage of Lactation Profile' table provides managers with data that can be used to monitor SCK. These include test day averages for the number of milking cows, average daily milk production, percent of fat and protein, and average somatic cell count (actual and score) for three lactation groups (first, second, and third and later lactation cows for the current lactation) and five days in milk periods (40 days or less, 41 to 100 days, 101 to 199 days, 200 to 305 days, and 306 days and greater).

Table 1. Stage of Lactation Profile, DHIA - 202 Herd Summary

This milk period partition enables producers to track trends across lactation and indicate whether the herd follows a normal lactation curve, peak milk, somatic cells, etc., and determine possible abnormalities.

It is important to note; however, that these values represent averages for the test day only. For this reason, it is important to follow the long-term trends of the herd for a concise picture. When evaluating these metrics, producers should also consider the number of cows in each group as a small number of cows listed may yield an unreliable average.

What is not so obvious, however, is that producers can use the percentages for fat and protein to calculate the Fat-to-Protein Ratio (FPR), a benchmark that is used to indirectly monitor subclinical ketosis in the herd and not on individual cow level (Duffield, 1997. Oetzel, 2013). However, that can change in the future with new technologies (Antanaitis et al, 2023).

Fat-to-Protein Ratio (FPR) is simply calculated as the percent of fat divided by the percent of protein.

                                        Fat to Protein Ratio (FPR) = Fat Percent / Protein Percent

For example, when fat is 5.4 percent and protein 3.0 percent the FPR for the first lactation cows during the first 40 days in milk (DIM) would be 1.8, for the second lactation 1.31, and for the third+ lactation 1.7 (Table 1).

The first test FPR can be used as an indirect herd-level indicator of subclinical ketosis (early metabolic problems in the herd.) For Holstein healthy cows, researchers consider the optimal range of the FPR between 1.2 and 1.4 (Oetzel, 2013). 

A lower FPR, below 1.1, would indicate fat inversion or subclinical rumen acidosis. However, it is suggested that the FPR is not the best tool to assess the ruminal acidosis problem as the effect of ruminal acidosis on milk protein is unknown (Oetzel et al., 2006).

A ratio over 1.4 suggests energy deficit and possible subclinical ketosis on the herd level when the number of cows with FPR >1.4 in the measured group exceeds more than 40 percent of total cows in the measured group (Oetzel G. et al., 2006).

Producers can use the fat and protein percentages for different lactations and DIM periods, transfer them into a MS Excel spreadsheet, and calculate the FPR which can be depicted in a graph (Table 2 and Graph 1).

We can see that Lactation 2 (green line) is within the FPR ‘safe zone’ of 1.2 – 1.4. However, there are only four cows in this group and the low FPR at the 1-40 DIM could be just a coincidence. Lactation 1 (blue line) and 3+ (red line) cows are well above the recommended FPR upper threshold of 1.4 during the 1-40 DIM and then it decreases to desired levels.

 In addition, the Lact 1 and 3+ cows drop fat percentages between 1-40 DIM and 41-100 DIM from 5.4 to 4.3 and 5.1 to 4.3, or 0.9 and 0.8 percent, respectively (Table 1), which is suggestive of excessive body weight loss. These two observations could indicate the possibility of SCK or possible metabolic disorder.

This graph is a depiction of one test day and averages of different DIM groups across lactations only. Similar calculations can be performed for past test days which would provide the producer with a picture of trends of the FPR for different lactations over time and possibly locate changes in trends.

Although Table 1 provides us with the number of cows in each location and DIM it says nothing about the proportion, or the number of cows with FPR >1.4 in each lactation group or for the herd, so it cannot be assessed whether this is a herd or individual cow problem.

PC-Dart Dairy Management software provides such information. A manager can go into the 'Cow Graphs' section and plot the Fat: Protein Ratio (FPR) against the DIM graph in the 'User Defined Graph' section. When the graph is plotted, he/she has the option to filter the herd using DIM, lactation number, breed, groups, etc. Using the cows’ ID and crosshairs options, the graphs can be divided into four quarters based on the desired level of the FPR and DIM and have depicted the cows’ numbers. The number of cows and respective percentages for each of the quarters are depicted in the right lower corner of the graphs.

 For example, in another herd, the PC-Dart graph below (Graph 2) shows the distribution of cows and heifers with less than 100 DIM. The X axis is DIM, ranging from 2 to 80 DIM, and the Y axis is FPR, ranging from 0.9 to 3.9. The crosshairs divide the graphs into four quarters at 40 DIM and an FPR of 1.4 The number of cows in each quarter is in the lower right corner.

The focus is the two quarters on the left, cows with < 40 DIM. There is a total of 70 cows and heifers of all lactations in these two sections. Thirty-one cows of FPR > 1.4 are found in the upper left quarter, which is 44 percent of the 1-40 DIM group. This can be just a single-time occurrence following management changes or seasonal effects. If such a proportion of the herd above 1.4 is found in the previous months and/or continues it could be worthwhile to conduct further investigation.

Another indication of possible SCK problems is to examine the number of cows during the first 40 DIM with butterfat higher than 4.5 – 5 percent. PC-Dart graph Fat Percent vs. DIM for the same herd can be plotted to find out whether the number of cows in the group is >10 percent (Graph 3). The X axis is DIM, ranging from 2 to 80 DIM, and the Y axis is a fat percentage, ranging from 2.8 to 9.2. The crosshairs divide the graphs into four quarters at 40 DIM and five percent fat. The number of cows in each quarter is in the lower right corner.

For example, in the two left quarters of the graph above, twenty-two cows of a total of 66 cows are above the five percent butterfat level. That represents 33 percent of the cows in the group. If we use a cut-off point of 4.5 percent, the number of cows would increase to 38, or 57 percent. It is also worth noticing that most of the cows with fat > 4.5 to 5 percent occur during the first 16 to 18 DIM. Producers should monitor whether this could be a one-time occurrence or a trend.

References

Amaral-Phillips, D. M. Early Detection of Potential Nutrition and Management Problems in Dairy Herds Using DHI-Monthly Milk Production and Composition Data. U Kentucky Extension, 2012

Antanaitis, R., Džermeikaitė, K., Januškevičius, V., Šimonytė, I., Baumgartner, W. 2023. In-Line Registered Milk Fat-to-Protein Ratio for the Assessment of Metabolic Status in Dairy Cows. Animals, 13(20):3293.

Duffield, T.F.; Kelton, D.F.; Leslie, K.E.; Lissemore, K.D.; Lumsden, J.H. Use of test day milk fat and milk protein to detect subclinical ketosis in dairy cattle in Ontario. Can. Vet. J. 1997, 38, 713–718.

Krogh M. A., Toft N., and Enevoldsen C. 2011. Latent class evaluation of a milk test, a urine test, and the fat-to-protein percentage ratio in milk to diagnose ketosis in dairy cows. J. Dairy Sci. 94:2360–2367

PC-DART Herd Manager 8.2.0. Dairy Records Management Systems. 2024