EP2879615A1 - Method for identifying the probability of an estrus - Google Patents
Method for identifying the probability of an estrusInfo
- Publication number
- EP2879615A1 EP2879615A1 EP13736828.8A EP13736828A EP2879615A1 EP 2879615 A1 EP2879615 A1 EP 2879615A1 EP 13736828 A EP13736828 A EP 13736828A EP 2879615 A1 EP2879615 A1 EP 2879615A1
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- 238000000034 method Methods 0.000 title claims abstract description 41
- 230000012173 estrus Effects 0.000 title claims abstract description 18
- 241001465754 Metazoa Species 0.000 claims abstract description 65
- 230000000694 effects Effects 0.000 claims abstract description 22
- 238000011156 evaluation Methods 0.000 claims abstract description 8
- 238000001514 detection method Methods 0.000 claims description 7
- 230000003287 optical effect Effects 0.000 claims description 7
- 238000012545 processing Methods 0.000 claims description 5
- 239000011159 matrix material Substances 0.000 claims description 2
- 239000003550 marker Substances 0.000 claims 3
- 238000012544 monitoring process Methods 0.000 claims 3
- 241000283707 Capra Species 0.000 claims 1
- 241001494479 Pecora Species 0.000 claims 1
- 230000015572 biosynthetic process Effects 0.000 abstract description 8
- 230000001419 dependent effect Effects 0.000 abstract description 3
- 241000283690 Bos taurus Species 0.000 description 7
- RJKFOVLPORLFTN-LEKSSAKUSA-N Progesterone Chemical compound C1CC2=CC(=O)CC[C@]2(C)[C@@H]2[C@@H]1[C@@H]1CC[C@H](C(=O)C)[C@@]1(C)CC2 RJKFOVLPORLFTN-LEKSSAKUSA-N 0.000 description 6
- 239000008267 milk Substances 0.000 description 5
- 210000004080 milk Anatomy 0.000 description 5
- 235000013336 milk Nutrition 0.000 description 5
- 238000005259 measurement Methods 0.000 description 3
- 229960003387 progesterone Drugs 0.000 description 3
- 239000000186 progesterone Substances 0.000 description 3
- 230000000007 visual effect Effects 0.000 description 3
- 239000008280 blood Substances 0.000 description 2
- 210000004369 blood Anatomy 0.000 description 2
- 235000013365 dairy product Nutrition 0.000 description 2
- 230000009027 insemination Effects 0.000 description 2
- 230000006399 behavior Effects 0.000 description 1
- 238000009395 breeding Methods 0.000 description 1
- 230000001488 breeding effect Effects 0.000 description 1
- 230000009194 climbing Effects 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 230000035558 fertility Effects 0.000 description 1
- 239000003205 fragrance Substances 0.000 description 1
- 230000009191 jumping Effects 0.000 description 1
- 210000003097 mucus Anatomy 0.000 description 1
- 238000000059 patterning Methods 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
- 230000011273 social behavior Effects 0.000 description 1
- 208000024891 symptom Diseases 0.000 description 1
- 238000004861 thermometry Methods 0.000 description 1
Classifications
-
- 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
Definitions
- 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.
- WO2009 / 01 1641 AI describes a method with which the activity of the animal is referred to the heat.
- 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. 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.
- 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 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.
- 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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- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Veterinary Medicine (AREA)
- Biophysics (AREA)
- Pregnancy & Childbirth (AREA)
- Engineering & Computer Science (AREA)
- Animal Husbandry (AREA)
- Wood Science & Technology (AREA)
- Zoology (AREA)
- Animal Behavior & Ethology (AREA)
- General Health & Medical Sciences (AREA)
- Public Health (AREA)
- Investigating Or Analysing Biological Materials (AREA)
Abstract
Description
Verfahren zur Erkennung der Wahrscheinlichkeit einer Brunst Method for detecting the probability of estrus
Die Erfindung betrifft ein Verfahren zur Erkennung der Wahlschein lichkeit einer Brunst bei einem weiblichen, nicht-humanen Säugetier, insbesondere bei einem Rind. The invention relates to a method for detecting the Wahlschein probability of estrus in a female, non-human mammal, especially in a cattle.
Die Qualität der Brunsterkennung hat einen großen Einfluss 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. 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 DE 10 2005 032 240 A I , die Messung des Progesterongehalts in Milch und Blut, die Detektion von brunstspezifischen Duftstoffen sowie die Pedometrie in unterschiedlichen Varianten. Eine Übersicht gibt Becker et al. (2005)„Vor- und Nachteile einzelner Methoden der Brunsterkennung beim Rind", Züchtungskunde 77 (2-3), 140- 150. 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.
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 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.
Die WO2009/01 1641 A I beschreibt ein Verfahren, mit dem über die Aktivität des Tieres auf die Brunst rückgeschlossen wird. Hierbei werden die Schritte des Tieres gezählt (Pedometrie) und die Daten sporadisch (meist beim Melken) aus den Sensoren ausgelesen. In der genannten Druckschrift wird auch die Berücksichtigung anderer Ereignisse zur Feststellung der Brunst beschrieben, z.B. der Tag der letzten Kalbung oder die Messung des Progesterongehalts in der Milch. Hierbei handelt es sich um Faktoren, welche nur sehr ungefähre Rückschlüsse auf den Zeitpunkt der Brunst erlauben oder aber im täglichen Einsatz auf einem Bauernhof ungeeignet sind. 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 der WO2005/060867 AI wird der Aufsprung (das Besteigen) eines Tieres durch ein anderes Tier der Gruppe beschrieben und ausgewertet. Die Daten sind mit erheblichen Fehlerraten behaftet. Ferner handelt es sich bei dem Aufsprung bzw. vielmehr der Duldung des Aufsprung nur um punktuelle Ereignisse, nicht aber um die Begleitung des Sozialverhaltens der Tiere über einen längeren Zeitraum. Hierdurch ist auch die Aussagekraft in Bezug auf die Ermittlung der Wahrscheinlichkeit einer Brunst reduziert, weil das gelegentliche Aufspringen bzw. Besteigen zum normalen Verhalten der Tiere zählt und keinen zuverlässigen Rückschluss auf das Vorliegen einer Brunst erlaubt. 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.
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. Gelöst wird diese Aufgabe mit den kennzeichnenden Merkmalen des Anspruchs 1. Vorteilhafte Ausgestaltungen sind den Unteransprüchen entnehmbar. 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.
Ein Ausführungsbeispiel der Erfindung wird im Folgenden näher erläutert. 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. 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.
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. 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. 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 Auswerteeinheit den Aufenthaltsort jedes einzelnen Tieres innerhalb des Laufstalls zu jedem Zeitpunkt zuverlässig feststellen kann. 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.
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 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.
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. 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. 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.
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
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 |
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EP2879615A1 true EP2879615A1 (en) | 2015-06-10 |
EP2879615B1 EP2879615B1 (en) | 2016-09-14 |
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EP13736828.8A Not-in-force EP2879615B1 (en) | 2012-08-01 | 2013-07-02 | Method for identifying the probability of an estrus |
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EP (1) | EP2879615B1 (en) |
DE (1) | DE102012107012A1 (en) |
DK (1) | DK2879615T3 (en) |
IL (1) | IL237002A0 (en) |
LT (1) | LT2879615T (en) |
WO (1) | WO2014019791A1 (en) |
Cited By (14)
Publication number | Priority date | Publication date | Assignee | Title |
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US10986816B2 (en) | 2014-03-26 | 2021-04-27 | Scr Engineers Ltd. | Livestock location system |
US10986817B2 (en) | 2014-09-05 | 2021-04-27 | Intervet Inc. | Method and system for tracking health in animal populations |
US11071279B2 (en) | 2014-09-05 | 2021-07-27 | Intervet Inc. | Method and system for tracking health in animal populations |
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US11832584B2 (en) | 2018-04-22 | 2023-12-05 | Vence, Corp. | Livestock management system and method |
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US11960957B2 (en) | 2020-11-25 | 2024-04-16 | Identigen Limited | System and method for tracing members of an animal population |
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JPH11514470A (en) * | 1995-10-27 | 1999-12-07 | アルファ ラヴァル アーグリ アクチエボラゲット | Color analysis in images for 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 |
NZ528756A (en) * | 2003-12-22 | 2006-10-27 | Dexcel Ltd | 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 |
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 |
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2012
- 2012-08-01 DE DE102012107012.1A patent/DE102012107012A1/en not_active Ceased
-
2013
- 2013-07-02 EP EP13736828.8A patent/EP2879615B1/en not_active Not-in-force
- 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 DK DK13736828.8T patent/DK2879615T3/en active
-
2015
- 2015-01-29 IL IL237002A patent/IL237002A0/en unknown
Non-Patent Citations (1)
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See references of WO2014019791A1 * |
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US12144320B2 (en) | 2019-02-08 | 2024-11-19 | Allflex Australia Pty Ltd | Electronic animal identification tag reader synchronisation |
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US11832587B2 (en) | 2020-06-18 | 2023-12-05 | S.C.R. (Engineers) Limited | Animal tag |
USD990063S1 (en) | 2020-06-18 | 2023-06-20 | S.C.R. (Engineers) Limited | Animal ear tag |
US12099893B2 (en) | 2020-07-01 | 2024-09-24 | S.C.R. (Engineers) Limited | Device assignment system and method |
US11960957B2 (en) | 2020-11-25 | 2024-04-16 | Identigen Limited | System and method for tracing members of an animal population |
US12213449B2 (en) | 2021-01-24 | 2025-02-04 | S.C.R. (Engineers) Limited | Animal marking control system and method |
Also Published As
Publication number | Publication date |
---|---|
DK2879615T3 (en) | 2017-01-02 |
DE102012107012A1 (en) | 2014-02-06 |
IL237002A0 (en) | 2015-03-31 |
WO2014019791A1 (en) | 2014-02-06 |
LT2879615T (en) | 2016-11-25 |
EP2879615B1 (en) | 2016-09-14 |
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