Heat detection in dairy cattle - Veterinary Practice
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Heat detection in dairy cattle

When looking at fertility performance of a dairy herd, it is good to remember that heat detection can be challenging, but investment in time or automation can help to improve performance

Most dairy farmers in the United Kingdom breed their cows when they are detected to be in heat. These heats are identified either through visual detection or with the help of an aid. The production of milk and beef is reliant on cows producing a calf regularly. Therefore, fertility performance is a massive driver for profitability for every cattle farmer.

Assessment of fertility performance

One of the indicators to assess fertility performance in a herd is the pregnancy rate. Typically, the pregnancy rate is calculated as the percentage of eligible cows that become pregnant in a 21-day period. A cow doesn’t become eligible for breeding until the voluntary waiting period (VWP) has finished. The VWP needs to be set after uterine involution has taken place and the cow has resumed regular oestrus cycles (Inchaisri et al., 2011). It is advised to set the minimum VWP at 42 days. The pregnancy rate can also be calculated by multiplying the submission rate with the conception rate. The conception rate is the number of eligible cows that conceive in a 21-day period and the submission rate is the percentage of eligible cows bred in a 21-day period.

The pregnancy rate can also be calculated by multiplying the submission rate with the conception rate

The submission rate is one of the main indices to calculate if sufficient heat detection takes place in a herd. Generally, in year-round-calving herds a submission rate of 70 percent or more is excellent. Depending on conception rates achieved, most year-round dairy farms need a submission rate in the region of 60 percent. In tight-block calving herds, a submission rate of 90 percent or more is the target (Cockcroft, 2015).

National performance

Unfortunately, these targets are often not met by UK dairy farmers. The 500 study herds of the National Milk Records (NMR), which are mostly year-round-calving herds, had a median submission rate of 42 percent in 2021. This figure has improved significantly (it was 27 percent in 2010), but improvement of this figure has slowed down a lot in the last few years (Hanks and Kossaibati, 2021). The national submission rate shows that when the fertility performance of a herd is analysed and assessed, it is always essential to assess heat detection performance as this is often an area where improvements can be made. Some of the questions that need to be asked are: Are enough cows bred? Are cows bred in a timely manner? Are cows bred accurately? When analysis shows that submissions are unsatisfying, one needs to come up with ideas and solutions for improvement.

Expression of oestrus

The hormone that is responsible for oestrus behaviour is oestradiol (Senger, 1999). How well cows express heat is partly dependent on the level of this hormone. Some other environmental factors that influence the expression of oestrus are, for example, housing and lameness.

Cows have a whole repertoire of oestrus behaviours, but traditionally standing to be mounted is the most reliable and primary sign of heat (Williamson et al., 1972). Many studies have been done to assess the interval between standing heat and ovulation, and it has been shown that optimal insemination time is between 12 and 24 hours before ovulation (Trimberger, 1948; Roelofs et al., 2006). These figures are important to determine, as artificial insemination means that breeding times are a lot less flexible than when a bull is always available.

Oestrus behaviours

In the last 40 years, standing heats have reduced in many dairy herds. It has been shown that higher milk production reduces the length of oestrus and oestrus behaviour (Lopez et al., 2004). This has had an impact on heat detection and pregnancies generated; however, it doesn’t mean that more productive cows have more difficulty conceiving when they are seen in standing heat (LeBlanc, 2013). Research has shown that standing heat is only expressed by about 50 percent of cows in oestrus, and that this behaviour lasts for about five to seven hours (Roelofs et al., 2005; Sveberg et al., 2011). This means that standing heat can easily be missed by visual heat detection.

Research has shown that standing heat is only expressed by about 50 percent of cows in oestrus, and that this behaviour lasts for about five to seven hours

To combat this, a lot of research has been done to come up with strategies to improve oestrus detection.

Efficient heat detection can be carried out by visual observation and with aids. It is generally easier to spot cows in oestrus in larger herds compared to smaller herds as the more cows in oestrus around the same time, the easier it is to visually identify them. To simplify breeding times for artificial insemination, in 1948 Trimberger developed the am-pm rule, which means that if a cow is seen in standing heat in the morning, she needs to be bred in the afternoon and vice versa (Table 1) (Trimberger, 1948).

Oestrus first observedBest time to breedToo late for good results
MorningSame dayNext forenoon
Forenoon* (9am – 12 noon)Late same day or early the next dayAfter 10am the next day
AfternoonNext forenoonAfter 2pm the next day
TABLE (1) Time between first oestrus observation and breeding (adapted from Trimberger, 1948).
*Trimberger (1948) notes that it is sometimes an advantage to omit this small group when the timetable is given to farmers in artificial farming

To be able to detect oestrus without standing heat and to increase the sensitivity of visual heat detection, Van Eerdenburg et al. developed a scoring system to aid with oestrus detection which looks at the type and number of behaviours a cow displays. Table 2 gives an overview of the different primary and secondary behaviours and their associated score (Van Eerdenburg et al., 1996).

Visual heat detection alone is improved by observing more frequently and by increasing the length of observation time at quiet times of the day. It is shown that when both primary and secondary behaviours (Table 2) are taken into account, visual heat detection of 30 minutes three times a day can detect 90 percent of heats (Roelofs et al., 2005).

Mucous vaginal discharge3
Being mounted but not standing10
Sniffing vagina of other cow10
Resting with chin on other cow15
Mounting (or attempting to mount) other cow35
Mounting head side of other cow45
Standing heat100
TABLE (2) Scoring system with primary and secondary oestrus behaviours (adapted from Van Eerdenburg et al., 1996). This scoring system is cumulative during a 24-hour period. When observed 12 times per day for 30 minutes and a score of 100 points is reached, the animal is considered to be in heat and can be inseminated if desired. When the cows are observed two or three times per day for 30 minutes, a threshold of 50 points can be applied.

Oestrus detection aids

To decrease observation time, different aids that are based on mounting behaviour have been developed. The most commonly used ones are tail paint, heat mount detectors and oestrus detection patches. All three products are applied on the tail head. When a cow with tail paint is mounted, the bright paint is rubbed off. With the other two products, a cow in oestrus that has been mounted by another cow displays a bright colour on the tail head. For all these products, rubbing for other reasons than oestrus can give false-positive results, while limited mounting behaviour will increase the number of false negatives in the herd. All these aids work best in conjunction with visual detection. For aids applied to the tail head to work, it is essential that they are checked and topped up daily to reduce the number of false-positive and false-negative heats. As all these methods include visual inspection, a lack of labour can be a restricting factor for success.

Automated oestrus detection

Oestrus is associated with increased activity in cows (Koelsch et al., 1994). To make use of this, and to reduce the reliance on labour, a whole range of different activity monitors have been developed. The most commonly used activity monitors are either pedometers, which detect an increase in walking activity, or accelerometers, which measure acceleration in three dimensions to assess changes in physical activity associated with oestrus (Adenuga et al., 2020). These systems can be attached to a leg, attached to the neck with a collar or in an eartag. Most of these systems store data in two-hour intervals that are read out at milking time near the parlour. Complicated mathematical algorithms are then used to separate normal feeding behaviour from increased activity due to oestrus.

It is good to remember that even with these automated systems, it will help to use some visual heat detection and common sense to get the best out of them

These automated systems have progressed a lot in the last 20 years and, provided they are set up properly and cows are kept to their routine, these devices can work very well. The literature reports oestrus detection rates varying from 60 to 90 percent for different kinds of devices (Holman et al., 2011; Pfeiffer et al., 2020).

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