The College of Agriculture, Food and Rural Enterprise (CAFRE) at Enniskillen Campus has several mares foaling down each year within the college’s equine breeding unit.
The diverse group of Irish Sport Horse, National Hunt and Flat racing broodmares are put in foal with the hope of a safe delivery the following season.
Students at the college get firsthand experience of every aspect of breeding, from choosing the stallion, to caring for the mare through to night watch and naming the foal once it is safely on the ground.
Foaling can be a nerve-wracking time for all involved with several potential issues that can occur for both the mare and foal. Gestation length can vary considerably and there are a wide range of internal and external variables.
The accepted average gestation length of 335 to 342 days can be affected by the season. Mares due to foal in late winter and early spring can carry their foals anywhere from five to ten days longer than those foaling later in the breeding season.
Behavioural changes
Traditionally we have relied upon a range of physical indicators which suggest that foaling is imminent including physical and behavioural changes.
However, it can be a very inexact science with a wide range of variance between mares noted.
Closely monitoring the mare and sitting up overnight are often required to ensure that there is support available when she does start the foaling process.
At CAFRE, the students sit up and observe the mares overnight when required with support from college staff.
Often students haven’t previously had the opportunity to be directly involved in the foaling process, so this provides an invaluable experience for them, with expert support on hand.
Equine enterprise
Part of the education provided at the college focuses on preparing graduates to encounter and work with a wide range of new technologies in the industry. Being familiar with these technologies and being able to evaluate their value within an equine enterprise is a very important skill to have.
Last year, a new camera-based Artificial Intelligence (AI) technology for foaling was trialed at the college. It shows signs of being extremely beneficial within breeding enterprises.
AI is becoming widely used and has an immense array of potential applications within every area of life. There are now AI cameras which are available and tailored for use within equine establishments for monitoring equine behaviour.
Mare and foal behaviour is monitored closely at CAFRE by staff and students and via AI Cameras to detect issues as early as possible.
The cameras can be set up and connected to Wi-Fi within the stabling/housing area where they can be calibrated by tracking the behaviour of one horse over a seven to 15-day period. With that, it can establish what that horse’s normal parameters are within the environment. Once these parameters are known, the system can then identify if abnormal behaviour is detected, sending alerts straight to an app on multiple mobile devices.
The system can indicate upcoming foaling one to three days prior and can then send alerts 30/10 minutes before the foal is born via SMS or a phone call.
New environment
Recently updated features include the ability to detect the early signs of colic in a mare post foaling and the monitoring of the foal’s activity in addition to that of the mare. The mobile app allows the video live stream to be checked as well as a 24 hour recap of the mare’s activity.
This form of AI uses continuous self-learning which captures up to 4 million data points per day per horse. One camera is used for each horse – however, the camera can easily be moved to different locations as required. However, if the camera is moved, the 7-day training period will need to be carried out again for the new environment. If the location is unchanged the system can become active for the next mare within 12 hours.
Students at CAFRE learn about breeding and stock management during their studies and actively taking a part in operating the campus breeding unit.
Last year, the system was used at CAFRE Enniskillen Campus to assist with some of the mares foaling. Each time the system did provide early notification that there was a change in the mare’s behaviour prior to foaling.
Although CAFRE is only in the initial stages of using a system like this, the results so far are promising. The findings have been fed back to the developers to enable them to gather more information on the user experience. As the use of AI becomes more widespread there will inevitably be further exciting developments in the use of AI cameras to monitor horse behaviour.
Hopefully these systems will provide valuable solutions to the equine industry going forward.
The College of Agriculture, Food and Rural Enterprise (CAFRE) at Enniskillen Campus has several mares foaling down each year within the college’s equine breeding unit.
The diverse group of Irish Sport Horse, National Hunt and Flat racing broodmares are put in foal with the hope of a safe delivery the following season.
Students at the college get firsthand experience of every aspect of breeding, from choosing the stallion, to caring for the mare through to night watch and naming the foal once it is safely on the ground.
Foaling can be a nerve-wracking time for all involved with several potential issues that can occur for both the mare and foal. Gestation length can vary considerably and there are a wide range of internal and external variables.
The accepted average gestation length of 335 to 342 days can be affected by the season. Mares due to foal in late winter and early spring can carry their foals anywhere from five to ten days longer than those foaling later in the breeding season.
Behavioural changes
Traditionally we have relied upon a range of physical indicators which suggest that foaling is imminent including physical and behavioural changes.
However, it can be a very inexact science with a wide range of variance between mares noted.
Closely monitoring the mare and sitting up overnight are often required to ensure that there is support available when she does start the foaling process.
At CAFRE, the students sit up and observe the mares overnight when required with support from college staff.
Often students haven’t previously had the opportunity to be directly involved in the foaling process, so this provides an invaluable experience for them, with expert support on hand.
Equine enterprise
Part of the education provided at the college focuses on preparing graduates to encounter and work with a wide range of new technologies in the industry. Being familiar with these technologies and being able to evaluate their value within an equine enterprise is a very important skill to have.
Last year, a new camera-based Artificial Intelligence (AI) technology for foaling was trialed at the college. It shows signs of being extremely beneficial within breeding enterprises.
AI is becoming widely used and has an immense array of potential applications within every area of life. There are now AI cameras which are available and tailored for use within equine establishments for monitoring equine behaviour.
Mare and foal behaviour is monitored closely at CAFRE by staff and students and via AI Cameras to detect issues as early as possible.
The cameras can be set up and connected to Wi-Fi within the stabling/housing area where they can be calibrated by tracking the behaviour of one horse over a seven to 15-day period. With that, it can establish what that horse’s normal parameters are within the environment. Once these parameters are known, the system can then identify if abnormal behaviour is detected, sending alerts straight to an app on multiple mobile devices.
The system can indicate upcoming foaling one to three days prior and can then send alerts 30/10 minutes before the foal is born via SMS or a phone call.
New environment
Recently updated features include the ability to detect the early signs of colic in a mare post foaling and the monitoring of the foal’s activity in addition to that of the mare. The mobile app allows the video live stream to be checked as well as a 24 hour recap of the mare’s activity.
This form of AI uses continuous self-learning which captures up to 4 million data points per day per horse. One camera is used for each horse – however, the camera can easily be moved to different locations as required. However, if the camera is moved, the 7-day training period will need to be carried out again for the new environment. If the location is unchanged the system can become active for the next mare within 12 hours.
Students at CAFRE learn about breeding and stock management during their studies and actively taking a part in operating the campus breeding unit.
Last year, the system was used at CAFRE Enniskillen Campus to assist with some of the mares foaling. Each time the system did provide early notification that there was a change in the mare’s behaviour prior to foaling.
Although CAFRE is only in the initial stages of using a system like this, the results so far are promising. The findings have been fed back to the developers to enable them to gather more information on the user experience. As the use of AI becomes more widespread there will inevitably be further exciting developments in the use of AI cameras to monitor horse behaviour.
Hopefully these systems will provide valuable solutions to the equine industry going forward.
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