EP2879615B1 - Method for identifying the probability of an estrus - Google Patents
Method for identifying the probability of an estrus Download PDFInfo
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- EP2879615B1 EP2879615B1 EP13736828.8A EP13736828A EP2879615B1 EP 2879615 B1 EP2879615 B1 EP 2879615B1 EP 13736828 A EP13736828 A EP 13736828A EP 2879615 B1 EP2879615 B1 EP 2879615B1
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61D—VETERINARY INSTRUMENTS, IMPLEMENTS, TOOLS, OR METHODS
- A61D17/00—Devices for indicating trouble during labour of animals ; Methods or instruments for detecting pregnancy-related states of animals
- A61D17/002—Devices 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
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- the invention relates to a method for detecting the likelihood of estrus in a female non-human mammal, in particular a bovine.
- 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.
- the WO2009 / 011641 A1 describes a method of inferring the activity of the animal on the oestrus.
- 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.
- 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.
- 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.
- 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 e.g. RFID sensors and corresponding sensors are also possible, as well as the combination of non-optical and optical methods. In any case, it must be ensured that the computerized evaluation unit can reliably determine the location of each individual animal within the playhouse at all times.
- 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.
- 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.
- the factor should be selected so high that a purely random exceeding of the limit does not result in a selection.
- random deviations must also be taken into account, ie the "background noise" of the average movement activity. The lower this background noise, the lower the limit can be set, from which a selection of the animal takes place.
- an animal 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.
- 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.
- the probability of heat is preferably output as a percentage.
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Description
Die Erfindung betrifft ein Verfahren zur Erkennung der Wahrscheinlichkeit einer Brunst bei einem weiblichen, nicht-humanen Säugetier, insbesondere bei einem Rind.The invention relates to a method for detecting the likelihood of estrus in a female non-human mammal, in particular a bovine.
Die Qualität der Brunsterkennung hat einen großen Eintluss auf die Wirtschaftlichkeit von Milchviehbetrieben. Unzulänglichkeiten auf diesem Gebiet führen zwangsläufig zu schlechteren Fruchtbarkeitskennzahlen und wirken sich negativ auf das wirtschaftliche Ergebnis des Betriebs aus. Dabei wird es für die Milchviehhalter immer schwieriger, eine Brunst zu erkennen und für eine erfolgreiche Besamung zu nutzen. Einerseits zeigen die Kühe aufgrund der heutigen Haltungsbedingungen zunehmend weniger und kürzere Brunstsymptome, andererseits können die Landwirte durch die stark veränderten Arbeitsbedingungen oftmals zu wenig Zeit für eine visuelle Brunstbeobachtung aufwenden.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.
Es sind daher eine Reihe von Verfahren zur Brunsterkennung entwickelt worden. Hierzu gehören unter anderem die visuelle Beobachtung, der Brunstkalender, Heatmount Detektoren, Heatwatch Systeme, die Messung des elektrischen Widerstandes des Vaginalschleims, die Thermometrie, die Milchleistungserfassung, die Detektion von Vokalisationsereignissen gemäß
Keine dieser Methoden liefert eine zuverlässige Erkennung der Brunst, weil jede bekannte Methode mit erheblichen Nachteilen behaftet ist und Zufallsereignisse eine Rolle spielen können, welche der Zuverlässigkeit des Brunstnachweises entgegenstehen.None of these methods provides a reliable detection of oestrus, because any known method is associated with significant disadvantages and may play a role in random events, which preclude the reliability of estrus.
Die
In der
In der
Es besteht daher die Aufgabe, ein Verfahren zum Nachweis einer Brunst so auszubilden, dass eine maximale Zuverlässigkeit gewährleistet wird.It is therefore the object of a method for detecting a heat in such a way that a maximum reliability is ensured.
Hervorzuheben ist, dass es hierbei keine Rolle spielt, wenn die Brunst erst einige Stunden später gemeldet wird, da die Besamung des brünstigen Tieres in der Regel erst zwölf Stunden nach der Brunst stattfindet.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 oestrus.
Gelöst wird diese Aufgabe mit den kennzeichnenden Merkmalen des Anspruchs 1. Vorteilhafte Ausgestaltungen sind den Unteransprüchen entnehmbar.This object is achieved with the characterizing features of claim 1. Advantageous embodiments are the dependent claims.
Ein Ausführungsbeispiel der Erfindung wird im Folgenden näher erläutert.An embodiment of the invention will be explained in more detail below.
Das erfindungsgemäße Verfahren beruht zunächst auf der Erkenntnis, dass ein erstes Maß für das Vorliegen einer Brunst bei den in Rede stehenden Tieren deren Bewegungsaktivität ist. Diese steht, wie Studien ergeben haben, in unmittelbarem Zusammenhang mit dem Progesterongehalt in Milch und Blut, so dass eine Beobachtung der Bewegungsaktivität einen ersten Rückschluss auf die Wahrscheinlichkeit einer Brunst erlaubt.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.
Erfindungsgemäß wird jedoch ein weiterer Parameter für diejenigen Tiere evaluiert, bei welchen sich in einem vorgegebenen Zeitabschnitt eine erhöhte Bewegungsaktivität nachweisen ließ, und zwar retrograd für den gleichen Zeitabschnitt, in welchem die erhöhte Bewegungsaktivität vorlag. Dieser zweite Parameter steht für die Gruppenbildung des Tieres mit mindestens einem weiteren, gleichartigen Tier aus der Gruppe. Auch bei der Gruppenbildung handelt es sich um eine Eigenschaft, die mit der Wahrscheinlichkeit einer Brunst im Zusammenhang steht. Man spricht insoweit von sexuell aktiven Gruppen.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.
Wenn erfindungsgemäß nur die bei der Bewegungsaktivität aufgefallenen Tiere auch hinsichtlich Ihrer Gruppenbildung untersucht werden und beide Parameter auffällig sind, steht dies für eine besonders hohe Wahrscheinlichkeit einer Brunst, wobei zusätzlich eine Kreuzkorrelation beider Parameter durchgeführt werden kann.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.
Das Verfahren kann beispielsweise in einem Laufstall für Rinder durchgeführt werden, welcher mit mindestens einer, vorzugsweise mit mehreren Videokameras zur Aufnahme der Rinder von oben ausgestattet ist. Die Ausgänge der Kameras sind mit einem computergestützten Bildverarbeitungssystem verbunden. Das Bildverarbeitungssystem ist in der Lage, jedes einzelne Tier in der Gruppe der in dem Laufstall befindlichen Tiere zuverlässig zu erkennen. Dies kann beispielsweise aufgrund einer charakteristischen Musterung des Fells der Tiere erfolgen oder durch Aufbringen eines Musters auf den Rücken bzw. Halsbereich der Tiere, insbesondere in Gestalt eines zweidimensionalen Matrixcodes. Andere, nicht-optische Methoden, z.B. über RFID-Geber und entsprechende Sensoren sind ebenfalls möglich, auch die Kombination nicht-optischer mit optischen Methoden. In jedem Fall muss gewährleistet werden, dass die computergestützte Auswertereinheit den Aufenthaltsort jedes einzelnen Tieres innerhalb des Laufstalls zu jedem Zeitpunkt zuverlässig feststellen kann.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, e.g. RFID sensors and corresponding sensors are also possible, as well as the combination of non-optical and optical methods. In any case, it must be ensured that the computerized evaluation unit can reliably determine the location of each individual animal within the playhouse at all times.
Mit Hilfe der der Bildverarbeitung nachgeschalteten Computerauswertung wird laufend für jedes einzelne Tier der Gruppe dessen momentane Bewegungsaktivität ermittelt. Die Bewegungsaktivität ist im einfachsten Falle die momentane Geschwindigkeit des Tieres bzw. die über einen bestimmten Zeitraum ermittelte Durchschnittsgeschwindigkeit desselben, also der in einer bestimmten Zeit zurückgelegte Weg. Dieser Parameter lässt sich mit den oben genannten Bildverarbeitungsmethoden und der daran angeschlossenen computertechnischen Auswertung ohne weiteres für jedes Tier laufend ermitteln und aktualisieren. Auf diese Weise entsteht für jedes Tier ein im Wesentlichen konstanter Mittelwert der Bewegungsaktivität.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.
Sobald nun festgestellt wird, dass dieser über einen längeren Zeitabschnitt im Wesentlichen konstante Mittelwert der Bewegungsaktivität einen vorgegebenen, prozentualen, über diesem Mittelwert liegenden Grenzwert überstreitet, erfolgt eine Selektion des entsprechenden Tiers zur weiteren Auswertung. Der Faktor, um welchen der Mittelwert der Bewegungsaktivität hierbei zu überschreiten ist, kann zwischen 10% und 2500% der mittleren Bewegungsaktivität liegen. Vorzugsweise sollte der Faktor so hoch gewählt werden, dass ein rein zufallsbedingtes Überschreiten des Grenzwertes noch nicht zu einer Selektion führt. Bei der Auswahl des Grenzwerts sind daher auch zufallsbedingte Abweichungen zu berücksichtigen, also das "Grundrauschen" der mittleren Bewegungsaktivität. Je geringer dieses Grundrauschen ist, desto geringer kann der Grenzwert festgesetzt werden, ab welchem eine Selektion des Tieres erfolgt.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, therefore, random deviations must also be taken into account, ie the "background noise" of the average movement activity. The lower this background noise, the lower the limit can be set, from which a selection of the animal takes place.
Sobald ein Tier selektiert worden ist, bei welchem der Mittelwert der Bewegungsaktivität über einen bestimmten Zeitabschnitt oberhalb des Grenzwerts lag, wird für dasselbe Tier für den gleichen Zeitabschnitt aufgrund der gespeicherten Bewegungsdaten untersucht, ob es sich überdurchschnittlich stark an Gruppenbildung beteiligt hat. Maßgebend kann hierbei der Abstand des jeweiligen Tieres zu mindestens einem weiteren, gleichartigen Tier im relevanten Zeitraum sein. In einer ersten Näherung kann ein vorgegebener Abstandswert festgelegt werden und der für die Gruppenbildung des Tiers spezifische Parameter dann auf positiv gestellt werden, wenn dieser Abstandswert unterschritten wird. Im Rahmen einer genaueren Auswertung können zusätzlich Zeiten berücksichtigt werden, während denen der Wert des Abstands größer ist als der vorbestimmte Abstand und eine Gewichtung stattfinden, wonach größeren Abständen proportional eine kleinere, effektive Zeit zugeordnet wird. Auf diese Weise wird ein zweiter, nämlich der Gruppenbildungsparameter, für die gleichen Tiere festgelegt, die bereits bei dem ersten, auf die Bewegungsaktivität gerichteten Parameter positiv aufgefallen sind.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.
Versuche haben ergeben, dass die Wahrscheinlichkeit einer Brunst bei Tieren, welche im gleichen Zeitraum bei beiden Parametern auffällig waren, besonders hoch ist.Experiments have shown that the likelihood of estrus in animals that were conspicuous in both parameters during the same period is particularly high.
Schließlich ist es möglich, nach Festlegung der beiden Parameter eine Kreuzkorrelation zu bilden, also den Wert des zweiten Parameters noch einmal mit dem Wert des ersten Parameters zu vergleichen und die Ausgabe der Wahrscheinlichkeit einer Brunst nicht nur davon abhängig zu machen, dass das Tier bei beiden Parametern aufgefallen ist, sondern wie hoch die beiden Parameter jeweils über den vorgegebenen Grenzwerten gelegen haben.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 einer weiteren Ausgestaltung des erfindungsgemäßen Verfahrens kann der Landwirt im Anschluss an das vollautomatisiert durchgeführte Verfahren noch einmal die Videoaufzeichnung Retrograd überprüfen und hierbei diejenigen Tiere visuell überprüfen, bei denen in dem dritten Verfahrensschritt eine Ausgabe für die Wahrscheinlichkeit einer Brunst erzeugt worden ist. Der Landwirt erkennt hierbei aufgrund seiner Erfahrung sofort, ob diese Tiere tatsächlich brünstig sind, beispielsweise in dem er zusätzliche visuelle Parameter wie die Duldung oder auf Aufspringen analysiert. Dieser dritte Verfahrensschritt kann dem Landwirt dadurch erleichtert werden, dass in einem vierten Verfahrensschritt diejenigen Tiere, bei denen eine Ausgabe für die Wahrscheinlichkeit einer Brunst erzeugt worden ist, auf dem Videobildschirm visuell hervorgehoben, beispielsweise farblich markiert werden, so dass der Landwirt sofort erkennt, welche Tiere er gesondert beobachten sollte.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.
Das erfindungsgemäße Verfahren kann vorzugsweise bei Rindern, jedoch auch bei anderen Paarhufern eingesetzt werden. Im Rahmen der Auswertung und zur Erleichterung der Arbeit für den Landwirt wird die Wahrscheinlichkeit der Brunst vorzugsweise als Prozentsatz ausgegeben.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 (12)
- A method for detecting heat in a female, non-human mammal within a group of animals of the same type, whereby in a first step of the method a parameter specific for the movement activity of the animal is recorded as a function of time and the animal is selected for further evaluation, provided this parameter exceeds during a predefined period of time the average value of the parameter specific for the movement activity, relating to the threshold value of the respective animal, characterized in that in a second step of the method the period of time is ascertained for the same time segment, during which the distance of the animal to at least one other animal of the same type falls below a predefined value, and in a third step of the method an indication of the likelihood of heat in the animal, which depends on this period of time, is produced.
- A method according to Claim 1, characterized in that the female, non-human mammal is an even-toed ungulate, particularly a cow, a hog, a goat, a sheep or a camelid.
- A method according to one of the above claims, characterized in that the parameter specific for the movement activity of the animal is the distance traveled by the animal in a certain period of time.
- A method according to one of the above claims, characterized in that the given threshold value exceeds by a factor between 1.1 and 25 the average value of the parameter specific for the movement activity.
- A method according to one of the above claims, characterized in that when determining the value of the period of time, periods of time are additionally taken into consideration, during which the value of the distance is larger than the given distance, and weighting is made in such a manner that a smaller, effective period of time is proportionally assigned to larger distances
- A method according to one of the above claims, characterized in that the group of animals of the same kind is watched by means of an optical monitoring system with computer-aided image processing linked to it, and each animal in the group carries a specific optical marker for identification.
- A method according to Claim 6, characterized in that the specific optical marker is the pattern of the skin of the animal.
- A method according to Claim, characterized in that the specific optical marker is a pattern applied to the animal, particularly a 2-dimensional matrix code.
- A method according to one of the above claims, characterized in that monitoring of the group of animals of the same kind is performed by (additional) RFID-givers and sensors followed by computer-aided evaluation.
- A method according to one of the above claims, characterized in that for determining the likelihood of heat in the animal, additionally taken into consideration is the value of the parameter specific for the movement activity of the animal in terms of a cross correlation to the value of the period of time within the given time frame in which the distance of the animal to at least one other animal of the same kind falls below a given value.
- A method according to one of the above claims, characterized in that the likelihood of heat in the animal is indicated by a percentage rate.
- A method according to one of the Claims 6 to 11, characterized in that during the entire period of monitoring, video monitoring of all the animals is performed, and those animals, for which in a third step of the method, an indication is produced for the likelihood of heat, are highlighted graphically, e.g. by colors, in the image data stored.
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| DE102012107012.1A DE102012107012A1 (en) | 2012-08-01 | 2012-08-01 | Method for detecting the probability of estrus |
| PCT/EP2013/063960 WO2014019791A1 (en) | 2012-08-01 | 2013-07-02 | Method for identifying the probability of an estrus |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| EP2879615A1 EP2879615A1 (en) | 2015-06-10 |
| EP2879615B1 true EP2879615B1 (en) | 2016-09-14 |
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Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| EP13736828.8A Not-in-force EP2879615B1 (en) | 2012-08-01 | 2013-07-02 | Method for identifying the probability of an estrus |
Country Status (6)
| Country | Link |
|---|---|
| EP (1) | EP2879615B1 (en) |
| DE (1) | DE102012107012A1 (en) |
| DK (1) | DK2879615T3 (en) |
| IL (1) | IL237002A0 (en) |
| LT (1) | LT2879615T (en) |
| WO (1) | WO2014019791A1 (en) |
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| CA2692699C (en) * | 2007-07-13 | 2017-03-21 | Ole Lind | Method for detecting oestrus behaviour of a milking animal |
| GB0822580D0 (en) * | 2008-12-11 | 2009-01-14 | Faire Ni Ltd | An animal monitoring system and method |
| AT510923A1 (en) * | 2010-12-15 | 2012-07-15 | Mkw Electronics Gmbh | METHOD FOR DISPLAYING INFORMATION MADE TO ANIMAL |
-
2012
- 2012-08-01 DE DE102012107012.1A patent/DE102012107012A1/en not_active Ceased
-
2013
- 2013-07-02 LT LTEP13736828.8T patent/LT2879615T/en unknown
- 2013-07-02 WO PCT/EP2013/063960 patent/WO2014019791A1/en active Application Filing
- 2013-07-02 EP EP13736828.8A patent/EP2879615B1/en not_active Not-in-force
- 2013-07-02 DK DK13736828.8T patent/DK2879615T3/en active
-
2015
- 2015-01-29 IL IL237002A patent/IL237002A0/en unknown
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102020103742A1 (en) | 2020-02-13 | 2021-08-19 | Cattledata Gmbh | Procedure for tracking the whereabouts of farm animals |
| US12133507B2 (en) | 2023-11-16 | 2024-11-05 | S.C.R. (Engineers) Limited | Livestock dry off method and device |
Also Published As
| Publication number | Publication date |
|---|---|
| DE102012107012A1 (en) | 2014-02-06 |
| EP2879615A1 (en) | 2015-06-10 |
| LT2879615T (en) | 2016-11-25 |
| DK2879615T3 (en) | 2017-01-02 |
| WO2014019791A1 (en) | 2014-02-06 |
| IL237002A0 (en) | 2015-03-31 |
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