Do suckler calves absorb enough antibodies from colostrum?
In this study, around 1 in 7 calves sampled had FPT i.e. had not received any colostral antibodies, whilst 1 in 3 calves had PPT i.e. had not received enough colostral antibodies. These findings are concerning because they indicate that at least 1 in 5 of the calves in these herds have received insufficient antibodies from their dam’s colostrum. On two farms sampled, over half the calves sampled were suffering from FPT, however it was not clear why these herds were suffering with such severe FPT. The good news is that five of the farms sampled had optimal passive transfer in all of the calves sampled, indicating that there are examples of excellent practice in the industry.
The metabolic profile results are also highly significant. Many livestock farmers continue to be concerned regarding mineral status, however the results of the testing in this study indicate that on the vast majority of farms sampled, mineral status was generally good. The one exception to this was magnesium status, which was poor in nearly 1 in 3 cows sampled.. Many herds were either not supplementing with magnesium or were using buckets. Buckets are problematic due to the uneven intakes across the group.
The most significant findings from the metabolic profile results were the high rates of negative energy balance (over 1 in 3 cows sampled) and very poor short term protein status (nearly 2 in 3 cows sampled). These cows are at risk of uterine inertia (failure to progress during calving), exhaustion during calving, uterine prolapse, retained fetal membranes, delayed return to cycling after calving, ruminal impaction and clinical ketosis (slow fever). The results of this study indicate that for energy, a significant proportion of cows were not having their needs met, whilst for protein, the majority of suckler cows were deficient.
This project has therefore identified a significant need for a coordinated knowledge exchange effort to improve genetic selection with respect to calving ease, and discouraging the use of nutritional restriction in late gestation to control calf size.
The following were demonstrated to increase the risk of FPT and/or PPT:
- Assisted calving
- Assistance with colostrum feeding
- Bull calves
- Being born to a heifer
- Being born a twin
- Poor herd energy balance (elevated cow BOHB levels prior to calving)
This is the first time that poor energy balance in the run up to calving has been associated with an increased risk of FPT and highlights the importance of good maternal nutrition in late pregnancy.
About this project
Ruminants are born immunologically naïve and are reliant on passive transfer of colostral antibodies from the dam for protection from disease in early life. The high prevalence of failure of passive transfer (FPT) in dairy calves has driven the investigation of risk factors for and strategies to reduce FPT in dairy herds (Beam et al. 2009) however understanding in beef suckler herds is limited.
The Dairy Herd Health and Productivity Service (DHHPS) have anecdotally linked FPT in Scottish beef herds with nutritional restrictions in late gestation. Notably Effective Rumen Degradable Protein (ERDP) restriction in late gestation has been linked to 2 disease outbreaks from FPT in suckler herds (Corbishley et al. 2017).
It is therefore suggested that the simplistic message to “ensure calves have sucked colostrum” is insufficient and that nutritional and other factors under the control of the stockperson may have significant impacts on the prevalence of FPT.
This study determined the prevalence of and risk factors for FPT across 40 English suckler herds during the 2018 spring calving season.
Aims and Objectives:
The aim of the project was to define the prevalence of and risk factors for Failure of Passive Transfer (FPT) in English suckler herds.
Specific objectives were:
1) To understand the prevalence of FPT in suckler calves under typical English husbandry conditions
2) To identify risk factors of FPT in suckler calves under typical English husbandry conditions
3) To gain a clearer understanding of the relationship between nutritional status (including iodine status) during late gestation and FPT in suckler calves
A continuation of work already started as a residency project at the Royal (Dick) School of Veterinary Science where Scottish suckler farms have been investigated. This project extended the work across English farms.
10 veterinary practices were recruited in England to collect data from 40 English beef suckler farms during the Spring 2018 calving period. Vets visited each farm 3 times during the study;
- 1 week before calving starts, at this visit blood samples for metabolic profiling and pooled inorganic iodine were taken from 6 pregnant cows. The cows were body condition scored and had live weight recorded with a weigh tape. Information on the farm and the rations fed were collected and forage samples taken.
- 3 weeks into calving, another 6 pregnant cows were blood sampled for metabolic profiling and pooled inorganic iodine. Body condition score and live weight were recorded for these cows also. 8 x 2-5 day old calves were blood sampled for total protein (TP) and Gamma-glutamyltransferase (GGT).
- 6 weeks into calving, 7 x 2-5 day old calves were blood sampled for TP and GGT. TP and GGT can be used as indicators of FPT; TP is an indirect measure of the number of antibodies in the blood whilst GGT is an enzyme found in large quantities in colostrum so can be used as an indirect measure of colostrum consumption.
- Metabolic profiles are an accepted methodology for the assessment of nutritional and metabolic status, broadly assessing energy, protein and mineral status. This was conducted on individual blood samples, hence providing information relating to the metabolic status of individual animals within the group. Iodine status was assessed as recent press coverage suggests over-supplementation could be a risk factor for FPT. Pooled samples were ran for each group of cows sampled due to cost.
Results from the metabolic profiles were fed back to the vet and farmer. All data from the English farms was analysed alongside the Scottish data, this allowed risk factors to be identified. Comparisons were also made between English and Scottish farms to identify any differences.