WO2014019791A1 - Method for identifying the probability of an estrus - Google Patents

Method for identifying the probability of an estrus Download PDF

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Publication number
WO2014019791A1
WO2014019791A1 PCT/EP2013/063960 EP2013063960W WO2014019791A1 WO 2014019791 A1 WO2014019791 A1 WO 2014019791A1 EP 2013063960 W EP2013063960 W EP 2013063960W WO 2014019791 A1 WO2014019791 A1 WO 2014019791A1
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WO
WIPO (PCT)
Prior art keywords
animal
method according
characterized
value
time
Prior art date
Application number
PCT/EP2013/063960
Other languages
German (de)
French (fr)
Inventor
Oliver Dietrich
Original Assignee
Oliver Dietrich
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority to DE102012107012.1 priority Critical
Priority to DE201210107012 priority patent/DE102012107012A1/en
Application filed by Oliver Dietrich filed Critical Oliver Dietrich
Publication of WO2014019791A1 publication Critical patent/WO2014019791A1/en

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Classifications

    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61DVETERINARY INSTRUMENTS, IMPLEMENTS, TOOLS, OR METHODS
    • A61D17/00Devices for indicating trouble during labour of animals ; Methods or instruments for detecting pregnancy-related states of animals
    • A61D17/002Devices for indicating trouble during labour of animals ; Methods or instruments for detecting pregnancy-related states of animals for detecting period of heat of animals, i.e. for detecting oestrus

Abstract

The invention relates to a method for identifying an estrus in a female, non-human mammal within a group of animals of the same kind, wherein, in a first method step, a parameter specific for the movement activity of the animal in dependence on the time is detected and the animal is selected for further evaluation, if said parameter lies above the average value of the parameter specific for the movement activity in the corresponding animal for a predetermined length of time. Similar methods which are currently known are unreliable and dependent on random events. The problem of designing a corresponding method which ensures a high degree of reliability is solved according to the invention in that, in a second method step, a parameter specific for the group formation of the animal by at least one additional animal of the same kind from the group is determined for the same length of time and, in a third method step, an output for the probability of an estrus of the animal in dependence on the value of the parameter specific for pair formation is produced.

Description

 Method for detecting the probability of estrus

The invention relates to a method for detecting the Wahlschein probability of estrus in a female, non-human mammal, especially in a cattle.

The quality of the heat detection has a great influence on the profitability of dairy cattle farms. Inadequacies in this area inevitably lead to worse fertility indicators and have a negative impact on the economic performance of the farm. It is becoming increasingly difficult for dairy farmers to recognize a heat and use it for successful insemination. On the one hand, the cows show increasingly fewer and shorter ostentatious symptoms due to the current husbandry conditions; on the other hand, farmers can often spend too little time on visual observation of oestrus due to the greatly altered working conditions. Therefore, a number of methods for detecting heat have been developed. These include, but are not limited to, visual observation, oestrus calendars, heatmount detectors, heatwatch systems, vaginal mucus electrical resistance measurement, thermometry, milk yield detection, vocalization event detection in accordance with DE 10 2005 032 240 AI, measurement of progesterone levels in milk and milk Blood, the detection of estrus-specific fragrances and the pedometry in different variants. An overview is given by Becker et al. (2005) "Advantages and disadvantages of individual methods of bovine oestrus detection", breeding 77 (2-3), 140-150.

None of these methods provides a reliable detection of the heat, because any known method is associated with considerable disadvantages and can play a role in random events, which preclude the reliability of the esthetics.

WO2009 / 01 1641 AI describes a method with which the activity of the animal is referred to the heat. Here, the steps of the animal are counted (pedometry) and the data sporadically (mostly when milking) read out of the sensors. The cited document also describes the consideration of other events for determining estrus, eg the day of the last calving or the measurement of the progesterone content in the milk. These are factors which only very approximate conclusions on the Allow time of heat or are unsuitable for daily use on a farm.

In WO2005 / 060867 AI the emergence of an animal by another animal of the group is described and evaluated. The data is subject to considerable error rates. Furthermore, the emergence, or rather the acquiescence, of the emergence is only a matter of isolated events, but not the accompaniment of the social behavior of the animals over a longer period of time. This also reduces the significance of determining the likelihood of estrus, because the occasional pouncing or climbing counts to the normal behavior of the animals and does not allow a reliable conclusion on the presence of heat.

It is therefore the object of a method for detecting a heat in such a way that a maximum reliability is ensured.

It should be emphasized that it does not matter if the heat is reported only a few hours later, as the insemination of the brünstigen animal usually takes place only twelve hours after the heat. This object is achieved with the characterizing features of claim 1. Advantageous embodiments are the dependent claims.

An embodiment of the invention will be explained in more detail below. The method according to the invention is initially based on the knowledge that a first measure of the presence of heat in the animals in question is their movement activity. This has, as studies have shown, directly related to the progesterone content in milk and blood, so that an observation of the movement activity allows a first conclusion on the probability of estrus.

According to the invention, however, a further parameter is evaluated for those animals in which an increased movement activity could be detected in a predetermined period of time, namely retrograde for the same period in which the increased movement activity was present. This second parameter stands for the group formation of the animal with at least one other, similar animal from the group. Group formation is also a property associated with the probability of estrus. One speaks in this respect of sexually active groups. If, according to the invention, only the animals precipitated during the movement activity are also examined with regard to their group formation and both parameters are conspicuous, this stands for a particularly high probability of estrus, whereby cross-correlation of both parameters can additionally be carried out. The method can be carried out for example in a cattle bovine, which is equipped with at least one, preferably with a plurality of video cameras for receiving the cattle from above. The outputs of the cameras are connected to a computerized image processing system. The image processing system is able to reliably detect each individual animal in the group of animals in the playpen. This can be done for example on the basis of a characteristic patterning of the coat of the animals or by applying a pattern to the back or neck area of the animals, in particular in the form of a two-dimensional matrix code. Other, non-optical methods, eg via RFID encoders and corresponding sensors, are also possible, including the combination of non-optical and optical methods. In any case, it must be ensured that the computer-aided evaluation unit can reliably determine the location of each individual animal within the playhouse at any time.

With the help of computer processing downstream of the image processing, the instantaneous movement activity is continuously determined for each individual animal of the group. The movement activity is in the simplest case the current speed of the animal or the determined over a certain period average speed of the same, so the distance traveled in a certain time path. This parameter can be readily determined and updated for each animal with the above-mentioned image processing methods and the associated computer-technical evaluation. In this way, a substantially constant average of the movement activity is created for each animal.

As soon as it is determined that this is a predetermined, percentage, over a longer period substantially constant average of the movement activity, above this If the mean limit value is exceeded, a selection of the corresponding animal is made for further evaluation. The factor by which the mean value of the movement activity is to be exceeded here can be between 10% and 2500% of the average movement activity. Preferably, the factor should be selected so high that a purely random exceeding of the limit does not result in a selection. When selecting the limit value, therefore, random deviations must also be taken into account, ie the "background noise" of the mean motive activity.The lower this background noise, the lower the limit value can be set, from which a selection of the animal takes place.

Once an animal has been selected in which the average of the movement activity has been above the threshold for a certain period of time, it is examined for the same animal for the same period on the basis of the stored movement data, if it has participated more than average in group formation. Decisive here can be the distance of the respective animal to at least one other, similar animal in the relevant period. In a first approximation, a predetermined distance value can be set and the parameters that are specific for the group formation of the animal can then be set to positive if this distance value is undershot. In the context of a more detailed evaluation, additional times may be taken into account during which the value of the distance is greater than the predetermined distance and a weighting takes place, after which proportionally a smaller, effective time is assigned to larger distances. In this way, a second, namely the group formation parameter, is set for the same animals that have already noticed positively in the first parameter directed to the movement activity.

Experiments have shown that the likelihood of estrus in animals that were conspicuous in both parameters during the same period is particularly high.

Finally, after defining the two parameters, it is possible to form a cross-correlation, ie to compare the value of the second parameter again with the value of the first parameter and to make the output of the probability of oestrus not only dependent on the animal in both cases Has noticed parameters, but how high the two parameters have each been above the specified limits. In a further embodiment of the method according to the invention, the farmer can check the video recording retrograde again following the fully automated procedure and visually check those animals in which an output for the probability of heat has been generated in the third method step. Based on his experience, the farmer immediately recognizes whether these animals are actually fervent, for example by analyzing additional visual parameters such as tolerance or jumping. This third process step can be made easier for the farmer by, in a fourth process step, visually highlighting, for example color-coded, the animals on which an output for the probability of heat has been generated on the video screen so that the farmer immediately recognizes which one Animals should be observed separately.

The method according to the invention can preferably be used in cattle but also in other cloven-hoofed animals. As part of the evaluation and to facilitate the work for the farmer, the probability of heat is preferably output as a percentage.

Claims

claims
1. A method of detecting a heat in a female, non-human
Mammal within a group of similar animals, wherein in a first method step, a parameter specific to the movement activity of the animal is detected as a function of time and the animal is selected for further evaluation, if this parameter is above a predetermined time, above the mean value of the animal over a predetermined period of time for the movement activity specific parameter lies at the corresponding animal lying limit value, characterized in that in a second method step for the same period of time, the period is determined, during which the distance of the animal to at least one other similar animal below a predetermined value, and in a third method step generates an output for the probability of an estrus of the animal as a function of this time duration.
2. The method according to claim 1, characterized in that the female, non-human mammal is a cloven-hoofed animal, in particular a cow, a pig, a goat, a sheep or a camelid.
3. Method according to one of the preceding claims, characterized in that the parameter specific to the movement activity of the animal is the path of the animal traveled in a certain time.
4. The method according to any one of the preceding claims, characterized in that the predetermined limit is a factor between 1.1 and 25 above the average value of the movement activity-specific parameter.
5. The method according to claim 1, wherein, in determining the value of the time duration, additional times are taken into account during which the value of the distance is greater than the predetermined distance, and a weighting takes place in such a way that larger distances are proportional to a smaller one , effective time is allocated.
6. The method according to any one of the preceding claims, characterized in that the group of similar animals with an optical monitoring system and subsequent computer-aided image processing is observed and each animal from the group a specific optical marker for
Detection carries.
A method according to claim 6, characterized in that the specific optical marker is the drawing of the coat of the animal.
8. The method according to claim 6, characterized in that the specific optical marker is a pattern applied to the animal, in particular a two-dimensional matrix code.
9. The method according to any one of the preceding claims, characterized in that the monitoring of the group of similar animals by (additional) RFID transmitter and sensors and subsequent computer-assisted evaluation takes place.
10. The method according to any one of the preceding claims, characterized in that for determining the probability of a heat of
In addition, the value of the parameter specific to the movement activity of the animal in the sense of a cross-correlation with the value of the time duration within the predetermined period in which the distance of the animal at least one further similar animal falls below a predetermined value is taken into account.
11. The method according to any one of the preceding claims, characterized in that the probability of an estrus of the animal is issued as a percentage.
12. The method according to any one of claims 6 to 11, characterized in that during the entire monitoring period, a video surveillance of all animals takes place and those animals in which an output for the probability of heat has been generated in a third process step, in the stored image data of Video surveillance graphically, eg be highlighted in color.
PCT/EP2013/063960 2012-08-01 2013-07-02 Method for identifying the probability of an estrus WO2014019791A1 (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
DE102012107012.1 2012-08-01
DE201210107012 DE102012107012A1 (en) 2012-08-01 2012-08-01 Method for detecting the probability of estrus

Applications Claiming Priority (4)

Application Number Priority Date Filing Date Title
DK13736828.8T DK2879615T3 (en) 2012-08-01 2013-07-02 Method of determining probability of rupture
EP13736828.8A EP2879615B1 (en) 2012-08-01 2013-07-02 Method for identifying the probability of an estrus
LTEP13736828.8T LT2879615T (en) 2012-08-01 2013-07-02 Method for identifying the probability of an estrus
IL237002A IL237002D0 (en) 2012-08-01 2015-01-29 Method for identifying the probability of an estrus

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WO2014019791A1 true WO2014019791A1 (en) 2014-02-06

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EP (1) EP2879615B1 (en)
DE (1) DE102012107012A1 (en)
DK (1) DK2879615T3 (en)
IL (1) IL237002D0 (en)
LT (1) LT2879615T (en)
WO (1) WO2014019791A1 (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2015184479A1 (en) 2014-06-05 2015-12-10 Mkw Electronics Gmbh Data network for monitoring animals

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2005060867A1 (en) 2003-12-22 2005-07-07 Dexcel Limited Oestrus detection system
DE102005032240A1 (en) 2005-07-01 2007-01-04 Forschungsinstitut Für Die Biologie Landwirtschaftlicher Nutztiere Method of detecting the heat
WO2009011641A1 (en) 2007-07-13 2009-01-22 Delaval Holding Ab Method for detecting oestrus behaviour of a milking animal
US20110298619A1 (en) * 2008-12-11 2011-12-08 Faire (Ni) Limited Animal monitoring system and method

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0858641B1 (en) * 1995-10-27 2002-02-20 Alfa Laval Agri Ab Analysis of colour tone in images for use in animal breeding
DE10016688C2 (en) * 2000-04-04 2003-12-24 Deutsch Zentr Luft & Raumfahrt Process for the detection of animals and / or nesting of breeders in their natural habitat and devices for carrying out the process
AT13366U1 (en) * 2010-12-15 2013-11-15 Mkw Electronics Gmbh A method of displaying information associated with an animal

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2005060867A1 (en) 2003-12-22 2005-07-07 Dexcel Limited Oestrus detection system
DE102005032240A1 (en) 2005-07-01 2007-01-04 Forschungsinstitut Für Die Biologie Landwirtschaftlicher Nutztiere Method of detecting the heat
WO2009011641A1 (en) 2007-07-13 2009-01-22 Delaval Holding Ab Method for detecting oestrus behaviour of a milking animal
US20110298619A1 (en) * 2008-12-11 2011-12-08 Faire (Ni) Limited Animal monitoring system and method

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
BECKER ET AL.: "Vor- und Nachteile einzelner Methoden der Brunsterkennung beim Rind", ZÜCHTUNGSKUNDE, vol. 77, no. 2-3, 2005, pages 140 - 150

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2015184479A1 (en) 2014-06-05 2015-12-10 Mkw Electronics Gmbh Data network for monitoring animals
US9980467B2 (en) 2014-06-05 2018-05-29 Smartbow Gmbh Data network for monitoring animals
RU2680707C2 (en) * 2014-06-05 2019-02-25 Смартбоу Гмбх Data network for monitoring animals

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DE102012107012A1 (en) 2014-02-06
EP2879615B1 (en) 2016-09-14
DK2879615T3 (en) 2017-01-02
EP2879615A1 (en) 2015-06-10
IL237002D0 (en) 2015-03-31
LT2879615T (en) 2016-11-25

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