WO2018111179A1 - Procédé, unité de commande et système de détermination d'heure d'insémination - Google Patents

Procédé, unité de commande et système de détermination d'heure d'insémination Download PDF

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Publication number
WO2018111179A1
WO2018111179A1 PCT/SE2017/051255 SE2017051255W WO2018111179A1 WO 2018111179 A1 WO2018111179 A1 WO 2018111179A1 SE 2017051255 W SE2017051255 W SE 2017051255W WO 2018111179 A1 WO2018111179 A1 WO 2018111179A1
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WIPO (PCT)
Prior art keywords
animal
time
insemination
control unit
threshold limit
Prior art date
Application number
PCT/SE2017/051255
Other languages
English (en)
Inventor
Charlotte HALLÉN SANDGREN
Bohao Liao
Original Assignee
Delaval Holding Ab
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.)
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Publication date
Application filed by Delaval Holding Ab filed Critical Delaval Holding Ab
Priority to EP17817934.7A priority Critical patent/EP3568008A1/fr
Priority to CA3073927A priority patent/CA3073927A1/fr
Publication of WO2018111179A1 publication Critical patent/WO2018111179A1/fr

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Classifications

    • A—HUMAN NECESSITIES
    • A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01K—ANIMAL HUSBANDRY; CARE OF BIRDS, FISHES, INSECTS; FISHING; REARING OR BREEDING ANIMALS, NOT OTHERWISE PROVIDED FOR; NEW BREEDS OF ANIMALS
    • A01K11/00—Marking of animals
    • A01K11/006—Automatic identification systems for animals, e.g. electronic devices, transponders for animals
    • A—HUMAN NECESSITIES
    • A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01K—ANIMAL HUSBANDRY; CARE OF BIRDS, FISHES, INSECTS; FISHING; REARING OR BREEDING ANIMALS, NOT OTHERWISE PROVIDED FOR; NEW BREEDS OF ANIMALS
    • A01K29/00—Other apparatus for animal husbandry
    • A01K29/005—Monitoring or measuring activity, e.g. detecting heat or mating
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B10/00—Other methods or instruments for diagnosis, e.g. instruments for taking a cell sample, for biopsy, for vaccination diagnosis; Sex determination; Ovulation-period determination; Throat striking implements
    • A61B10/0012—Ovulation-period determination
    • 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
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/74—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving hormones or other non-cytokine intercellular protein regulatory factors such as growth factors, including receptors to hormones and growth factors
    • G01N33/743—Steroid hormones
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B10/00—Other methods or instruments for diagnosis, e.g. instruments for taking a cell sample, for biopsy, for vaccination diagnosis; Sex determination; Ovulation-period determination; Throat striking implements
    • A61B10/0012—Ovulation-period determination
    • A61B2010/0029—Ovulation-period determination based on time measurement

Definitions

  • This document discloses a method, a control unit and a system. More particularly, a method a control unit and a system are described, for assisting a user in determining insemination time of an animal.
  • the time difference between detected low progesterone and ovulation has big uncertainty, which depends on the biological process of the animal, age, health status, energy balance, breed etc.
  • the milking interval of the animal influence the time difference. Consequently, the probability of inseminating the animal in the right time interval based on the recommended time is low. The probability is below 40% when progesterone level of the animal is measured.
  • manual observations by the farmer are therefore needed in order to confirm heat signs of animals. This is however time consuming and it would be desired to reduce the time spent on this daily routine, as it multiplies over time.
  • a control unit for assisting a user in determining an insemination time interval of an animal.
  • the control unit is configured to obtain a progesterone level of a milk sample of the animal. Further, the control unit is configured to detect, at a first moment in time, that the obtained progesterone level is lower than a first threshold limit.
  • the control unit is also configured to obtain an activity level of the animal.
  • control unit is also configured to detect that the obtained activity level exceeds a second threshold limit at a second moment in time, within a predetermined first time period from the first moment of detecting that the progesterone level is lower than the first threshold limit. Furthermore, the control unit is configured to determine the insemination time interval of the animal to be a second time period from the moment of detecting the activity level exceeding the second threshold limit. The control unit is configured to generate a command signal to a user equipment to output information to the user, comprising the determined insemination time interval of the animal.
  • this objective is achieved by a method exe- cuted in a control unit for assisting a user in determining an insemination time interval of an animal.
  • the method comprises obtaining a progesterone level of a milk sample of the animal.
  • the method also comprises detecting, at a first moment in time, that the obtained progesterone level is lower than a first threshold limit.
  • the method also comprises obtaining an activity level of the animal.
  • the method in addition comprises detecting that the obtained activity level exceeds a second threshold limit at a second moment in time, within a predetermined first time period from the first moment of detecting that the progesterone level is lower than the first threshold limit.
  • the method also comprises determining the insemination time interval of the animal to be a second time period from the moment of detecting the activity level exceeding the second threshold limit. Furthermore, the method in addition com- prises outputting information to the user, comprising the determined insemination time interval of the animal.
  • this objective is achieved by a system for assisting a user in determining an insemination time interval of an animal.
  • the system comprises a control unit according to the first aspect. Further the system comprises a progesterone measurement unit, configured to obtain a progesterone level of a milk sample of the animal.
  • the system in addition comprises an activity measurement unit, configured to obtain an activity level of the animal.
  • the system also comprises a user equipment, configured to output information to the user.
  • Figure 1 illustrates an example of a system for assisting a human in detecting an animal in heat, according to an embodiment of the invention
  • Figure 2 illustrates the egg fertilisation process of an animal, according to an example
  • Figure 3A illustrates an example of distribution of probability of fertilisation after high activity detection
  • Figure 3B is a histogram illustrating time difference between high activity detection and low progesterone detection for animals at Farm A;
  • Figure 3C is a histogram illustrating time difference between high activity detection and low progesterone detection for animals at Farm B;
  • Figure 3D is a histogram illustrating time difference between high activity detection and low progesterone detection for animals at Farm C;
  • Figure 3E is a histogram illustrating difference between high activity detection and low progesterone detection for animals at Farm D;
  • Figure 3F is a histogram illustrating time difference between high activity detection and low progesterone detection for animals at Farm E;
  • Figure 4 is a flow chart illustrating an embodiment of a method
  • Figure 5 is an illustration depicting a system according to an embodiment.
  • Embodiments of the invention described herein are defined as a control unit, a method, and a system, which may be put into practice in the embodiments described below. These em- bodiments may, however, be exemplified and realised in many different forms and are not to be limited to the examples set forth herein; rather, these illustrative examples of embodiments are provided so that this disclosure will be thorough and complete.
  • Figure 1 illustrates a scenario with an animal 100 which may be comprised in a herd of animals at a dairy farm.
  • An activity measurement unit 110 may be attached to the animal 100 in some embodiments, e.g. in a necklace around the neck of the animal 100, under the hide of the animal 100, as ear tagAs, around the tail of the animal 100 and/ or around any, some or all of the legs of the animal 100.
  • the activity measurement unit 110 may comprise an accelerometer for detecting and measurement movements of the animal, possibly also a processor for data processing and a memory for intermittent data storage, and a transmitter for transmitting measurement data to a control unit 120.
  • the activity measurement unit 110 may comprise a pedometer in some embodiments. In yet some other embodiments, the activity measurement unit 110 may be configured to determine the position of the animal 100 and interpret determined changes in position as movements.
  • Animal may be any arbitrary type of domesticated animal; however, the herein provided non-limiting examples primarily relates to milk and/ or meat producing animals such as cow, goat, sheep, camel, dairy buffalo, yak, etc.
  • the milk of the animal may pass a progesterone measurement unit 115 e.g. during regular milking of the animal, or when taking a sample according to a schedule, or at any arbitrary moment in time.
  • the activity measurement unit 110 and/ or the progesterone measurement unit 115 may emit wired or wireless signals which may be received by the control unit 120.
  • the control unit 120 may repeatedly receive information from various sources and sensors, including the activity measurement unit 110 and the progesterone measurement unit 115. Various measured data associated with the animal 100, and possibly all animals of the herd may thus be continuously stored, e.g. with a time stamp, in a database 140, such as e.g. milk yields, activity, progesterone level in the milk, rumination, resting, feed intake, etc. The control unit 120 may then deduce when the animal 100 is possibly in heat and prepared for insemination, as will be further explained later in Figure 2 and the corresponding text sequence.
  • a database 140 such as e.g. milk yields, activity, progesterone level in the milk, rumination, resting, feed intake, etc.
  • control unit 120 is connected to a transceiver 125, configured to transmit and receive signals to/ from a User Equipment (UE) 150 which may belong to a human such as e.g. a farmer or other person working at a farm; or a veterinarian, agronomist, dietician, biologist, zoologist, ecologist, mammo!ogist, domestic animal researcher, zookeeper or other similar human, temporarily or permanently visiting the farm.
  • the "farm" as herein used may be a barn, a ranch, a stable or other similar agricultural structure for keeping animals.
  • the transceiver 125 may in some embodiments transmit and receive signals to/ from the activity measurement unit 110 and/ or the progesterone measurement unit 115 in some embodiments, e.g. transmit requests for data samples.
  • the communication of the transceiver 125 may be made over a wired or wireless communi- cation interface.
  • Such wireless communication interface may comprise, or at least be inspired by wireless communication technology such as Wi-Fi, Wireless Local Area Network (WLAN), Ultra Mobile Broadband (UMB), Bluetooth (BT) to name but a few possible examples of wireless communications in some embodiments.
  • the communication may alternatively be made over a wireless interface comprising, or at feast being inspired by radio access technologies such as e.g.
  • TDMA Time Division Multiple Access
  • FDMA Frequency Division Multiple Access
  • OFDMA Orthogonal FDMA
  • SC-FDMA Single-Carrier FDMA
  • the UE 150 may be e.g. a cellular mobile telephone, a stationary or portable computing device, a pair of intelligent glasses, a smart contact lens, an augmented reality device, a smart watch or similar device having a user interface and wireless communication ability.
  • a message may be outputted on the UE 150, e.g. as visual information, as an audio message, as a tactile signal or a combination thereof, encouraging the user to prepare for insemination of the animal 100 at the recommended time period.
  • a broadcast may be made to the plurality of humans/ farmers and their respective associated UEs.
  • further information may be provided in the message in order to enable the user to identify the animal 100, such as a name/ id number, etc.
  • Figure 2 illustrates a probability distribution of ovulation time 215 for a population at a farm, based on a detected low progesterone level. Also, a probability distribution of ovulation time 225 for the population at the farm, based on a detected increased activity of the animal 100.
  • the spread in time of the probability distribution of ovulation time 215 for different individual animals 100 based on the detected low progesterone level is much broader than the probability distribution of ovulation time 225, based on a detected increased activity. Besides this uncertainty, time resolution in progesterone measurement is also limited by the milking interval.
  • the milking interval may vary between a few hours and up to more than 15 hours.
  • an individual animal 100 may have a low progesterone level, i.e. a progesterone level lower than a threshold limit, right after a milking event. This will however not be detected until the subsequent milking event, about perhaps 15 hours later.
  • Increased activity of the animal 100 is thus a more precise tool for determining whether the animal 100 is in heat or not.
  • Activity level of the animal 100 may be sampled e.g. once every hour, every half an hour, or more frequently in different embodiments.
  • increased animal activity may have various other reasons beside that the animal 100 is in heat.
  • the particular animal 100 may e.g. be irritated or aggressive for some reason that is not correlated with ovulation.
  • Other reasons for increased activity may be when the animal 100 enters a pasture with fresh grass; or when feed is about to be distributed in the barn, for example.
  • the progesterone level in the milk extracted from the animal 100 is lower than a first threshold limit, related to progesterone level in milk. Such moment may also be referred to as a low progesterone heat alerts 210.
  • This detection of low progesterone level may trigger activity sampling, e.g. activate the sampling or sample at an intensified frequency in comparison with previously used frequency.
  • a moment in time 220 of detecting the activity level exceeding a second threshold limit, related to activity of the animal 100 may be detected. Such moment may also be re- ferred to as an activity alert 220.
  • the increased activity of the animal 100 may comprise mounting activity, and/ or attempts to mount other animals.
  • the animal 100 may also be more restless and alert to the surroundings when in heat, and spend less time on resting on the ground, than when not in heat.
  • the second threshold limit may be selected based on a compromise between sensitivity and specificity of heat detection.
  • a time interval between the activity alert 220 and ovulation may be assumed to be 21 hours with a standard deviation of 7.8 hours.
  • the moment 220 of detected increased activity has to occur within a predetermined first time period 240 from the moment in time 210 when the decreased progesterone level was detected.
  • the moment in time 220 of detecting increased activity level occur after the predetermined first time period 240, it is considered invalid, i.e. a false heat sign alert.
  • one in particular reliable heat sign is when the animal 100, after a moment of detected high activity, has an activity level that is very low, i.e. falls below a third threshold limit.
  • This state of the animal 100 may sometimes be referred to as standing oes- trus, and this sign may in some embodiments be used to determine the activity alert 220.
  • the insemination time interval 230 of the animal 100 is determined to be performed at a second time period 250 from the moment 220 of detecting the activity level exceeding the second threshold limit.
  • the insemination time interval 230 may comprise a first point in time, initiating the insemination time interval 230 and a second point in time, closing the insemination time interval 230.
  • the first and second points in time may be separated by a time period corresponding e.g. to the egg fertile life time, which may be estimated to about 10 hours, in some embodiments.
  • the first and second points in time may be separated by another time period, such as a couple of hours or five hours.
  • the first and second points in time may occur simultaneously in yet some other embodiments.
  • the first and second points in time of the insemination time interval 230 may be situated symmetrically around a central point in time 235, situated at the second time period 250 from the moment 220 of detecting the activity level exceeding the second threshold limit, in some embodiments.
  • sperm viability time 270 time may be about 24-34 hours, according to some different studies. It is for that reason obviously desired to plan the insemination time interval 230 so that all, or as big part as possible of the probability distribution of ovulation time 225 is situated before the sperm viability time 270.
  • the egg fertile life time may be estimated to about approximately 10 hours, in some embodiments. Ideally, in order to ensure efficient insemination, an over-lap of sperm viability and egg fertile life is desired. In some embodiments, such overlap may be e.g. 5 hours, or at least 5 hours.
  • the time difference between the heat signs 210, 220 and the ovulation may depend on many factors: like age of the animal 100, parity, breed, health status, nutrition status, etc., besides the biological process in the animal 100.
  • information obtained concerning a particular animal 100 of a control system/ herd management system like breed, Days In Milk (DIM), parity, Body Condition Scoring (BCS), and/ or health records to give a more accurate recommended insemination time interval 230.
  • the second time period 250 from the moment 220 of detecting the activity level exceeding the second threshold limit to the insemination time interval 230 may be adjusted based on any, some or all of the above enumerated factors in some embodiments.
  • a model of the herd in the farm, or the individual animal 100 may be used to achieve an optimal insemination time interval 230 and optimal time window, based on various (e.g. two) parameters of an individual animal 100 in some embodiments.
  • the model may be used to give these parameters for the animal 100.
  • the model may optionally be trained by data from farms or experiments. These parameters may be estimated by the control unit 120 based on collected data related to animal activity and progesterone level measurements and possibly also other data associated with the identity of the animal 100, such as e.g.
  • the probability of an ovulated egg is fertilised in the fertilisation window can be calculated as follows:
  • T is the insemination time interval 230
  • ⁇ is the standard deviation of time difference between low progesterone heat alert 210 and ovulation (in some embodiments 17.8 hours)
  • ⁇ is mean time difference between the low progesterone heat alert 210 and ovulation (in some embodiments 58 hours).
  • a similar model as [1] may be used by the control unit 110 for estimating an optimal time interval 230 for insemination based on the activity heat alarm 220.
  • the distribution of time from the activity heat alarm 220 to the ovulation may be:
  • ⁇ is the standard deviation of time difference between activity heat alarm 220 and ovulation (in some embodiments 7.8 hours) and ⁇ is mean time difference between activity heat alarm 220 and ovulation (in some embodiments 21 hours).
  • the time difference 250 between the activity heat alarm 220 and insemination time interval 230 may be set to 10 hours in some embodiments.
  • the time interval 230, or time window for insemination may be about 6-14 hours, with a probability better than 90% of the maximum probability (better than 63%) in some embodi- ments.
  • one way of combining the heat signs 210, 220 may be:
  • the animal 100 gets a low progesterone heat alert 210 which is confirmed by an activity heat alert 220 within the predetermined first time period 240, which may be set to e.g. 3 days: inseminate the animal 100 at a time interval 230, within the second time period 250, which may be e.g. 10 hours in some embodiments, from the activity heat alert 220.
  • the animal 100 gets a low progesterone heat alert 210 but no activity heat alert 220 within the predetermined first time period 240: inseminate the animal 100 about 47 hours after the low progesterone heat alert 210.
  • the animal 100 gets an activity heat alert 220 but no iow progesterone heat alert 210: do not inseminate the animal 100.
  • Figure 3A graphically illustrates probability of successful fertilisation of an animal 100, at different moments in time after an activity heat alert 220.
  • This probability may be calculated by the control unit 120 when a low progesterone heat alert 210 has been confirmed by the activity heat alert 220, in some embodiments, and corresponding information may be outputted to the user equipment 150 of the user.
  • An obvious problem for the farmer is that the determined ideal insemination time interval 230 of the animal 100 may occur out of regular working hours, such as e.g. 2 A.M. on a Sunday morning. Even when the insemination time interval 230 is determined to be within regular working hours, the farmer may be occupied with other more critical tasks, such as e.g. retrieving cattle on the run, assisting at a delivery, etc.
  • a relevant question of the farmer in such situation is to determine if it is any point in inseminating the animal 100 at another point in time, e.g. a later point in time, than the determined ideal insemination time interval 230.
  • the probability of fertilisation to the user, he/ she is enabled to determine if it is fruitful to inseminate the animal 100 at any different point in time. It is thereby avoided that semen and also time and working efforts associated with insemination activity is wasted on the animal 100 at a time when she with high probability is not fertile.
  • the information may be outputted to the user as a graph, a diagram, a list of example prob- ability values, a recommended time span of insemination, or as an interactive app where the user may input a suggested time, and may retrieve a probability of successful fertilisation, etc.
  • Figures 3B-3F illustrates data collected from five different farms, Farm A- Farm E, all having an automatic robotic milking system and all of them are collecting activity data and progesterone data of the animals 100.
  • the collected data at the different farms form statistics forming a base for developing probability curves 215, 225, and for determining the second time period 250 and thereby the interval for insemination 230.
  • Table 1 illustrates a summary of the data collection from the five farms and Table 2 present collected statistical data.
  • FIGS 3B-3F demonstrate a time difference between a moment 210 of detecting that the progesterone level is lower than the first threshold limit, and a moment 220 of detecting activity level exceeding the second threshold limit.
  • Figure 3B illustrates the time difference in Farm A
  • Figure 3C illustrates the time difference in Farm B
  • Figure 3D illustrates the time difference in Farm C
  • Figure 3E illustrates the time difference in Farm D
  • Figure 3F illustrates the time difference in Farm E.
  • the time difference between heat alert 210 based on low progesterone level and heat alert 220 based on high activity may be estimated to: 37 hours, with a standard deviation of 16 hours.
  • the mean value and standard deviation of dT3 can be estimated by: From the data from the above mentioned 5 farms, the best sensitivity of activity heat detection is about 65% using progesterone heat alert 210 as reference. The time difference between the heat alert 210 based on low progesterone level and ovulation may be estimated to: 58 hours with a standard deviation of 17.8 hours.
  • a centre point in time of an optimal time interval 230 for insemination, based on a combination of heat alert 210 based on low progesterone level and heat alert 220 based on high activity may be estimated to: 47 hours and 10 hours after respective heat alert 210, 220.
  • a model may be used to estimate the probability of the egg ovulates in the right time interval: 34.7% ⁇ based on low progesterone level heat alert 210) and 70% (based on high activity heat alert 220). It is estimated that by combining low progesterone level heat alert 210 and high activity heat alert 220, the probability of determining a correct time interval 230 for successfully inseminating an animal 100 based on sensor information is improved from 34.7% to 57.6%. Thereby a 22.9% improvement is achieved.
  • Figure 4 illustrates an example of a method 400 according to an embodiment.
  • the flow chart in Figure 4 shows the method 400 executed in a control unit 120 for assisting a user in determining an insemination time interval 230 of an animal 100.
  • the method 400 may comprise a number of steps 401-408. However, some of these steps 401- 408 may be performed solely in some alternative embodiments, like e.g. steps 405 and/ or step 407. Further, the described steps 401-408 may be performed in a somewhat different chronological order than the numbering suggests.
  • the method 400 may comprise the subsequent steps: Step 401 comprises obtaining a progesterone level of a milk sample of the animal 100.
  • the progesterone level may be measured by a progesterone measurement unit 115 e.g. during regular milking of the animal, or when taking a sample. Typically, milking (and thus also progesterone level sampling) may be made once in early morning and once in the even- ing. However, milking intervals may vary between 5 and 15 hours.
  • Step 402 comprises detecting, at a first moment in time 210, that the obtained 401 progesterone level is lower than a first threshold limit. This first moment in time 210 may also be referred to as a low progesterone heat alert.
  • the detection that the progesterone level is lower than the first threshold limit may trigger high frequency activity level samplings of the animal 100 during the predetermined first time period 240. Such high frequency activity level samplings may be made e.g. every hour, every half an hour, every quarter of an hour, every five minutes, etc.
  • An advantage with not continuously make high frequency activity level samplings is that energy is saved.
  • Step 403 comprises obtaining an activity level of the animal 100.
  • the activity level measurements may be triggered, or high frequency activity level samplings may be triggered by the detection 402 of that the progesterone level is lower than the first threshold limit.
  • the activity level of the animal 100 may be measured by an activity measurement unit 110 of the animal 100 in some embodiments.
  • Step 404 comprises detecting that the obtained 403 activity level exceeds a second threshold limit at a second moment in time 220, within a predetermined first time period 240 from the first moment 210 of detecting 402 that the progesterone level is lower than the first thresh- old limit.
  • This second moment in time 220 may also be referred to as an activity heat alert.
  • the second threshold limit may be predetermined or configurable in different embodiments, based on statistics related to the animal 100, the herd, the breed, and similar parameters.
  • Step 405, which only may be performed in some particular embodiments, comprises detecting that the obtained 403 activity level after having exceeded the second threshold limit, falls below a third threshold limit.
  • this moment 220 may be determined to be the second moment in time 220, or activity heat alert, which confirms the ovulation of the animal 100.
  • the animal 100 When the activity of the animal 100 falls below the third threshold limit, the animal 100 becomes very passive and stands to be mounted by other animals. This is often referred to as standing heat and may be regarded as a reliable heat sign.
  • Step 406 comprises determining the insemination time interval 230 of the animal 100, or a central point in time 235 of the insemination time interval 230, to be situated at a second time period 250 from the moment 220 of detecting 404 the activity level exceeding the second threshold limit.
  • the second time period 250 may be determined based on at least one animal status related parameter in some embodiments.
  • the animal status related parameter may comprise any, some or all of e.g.: breed, parity, energy balance, Days in Milk, milk production, Body Condition Scoring, age, shape of a se- ries of progesterone level measurements over time, and/ or historically used time period 250 between the moment 220 of detecting the increased activity level and the insemination time interval 230.
  • Step 407 comprises calcu- lating a probability of successful insemination of the animal 100 at different moments in time within a time interval comprising the determined 406 second time period 250.
  • the user thereby becomes aware of probabilities of successful fertilisation of the animal 100 in cases when insemination cannot be made at the determined 406 insemination time interval 230, but eventually may be made earlier/ later.
  • Step 408 comprises outputting information to the user, comprising the determined 406 insemination time interval 230 of the animai 100, together with an identification of the animal 100.
  • the user thereby becomes aware about when in time to inseminate the animal 100.
  • the indication may be outputted on the user equipment 150 i.e. by an audio signal, a voice message, a tactile signal, a visual message on the dis- play, or a combination thereof.
  • the information outputted to the user may comprise the calculated 407 probability of successful insemination of the animal 100 at different moments in time in a time interval.
  • Figure 5 illustrates an embodiment of a system 500 for assisting a user in determining an insemination time interval 230 of an animal 100.
  • the system 600 comprises a control unit 120.
  • the control unit 120 is configured to perform at least some of the previously described steps 401-408 according to the method 400 described above and illustrated in Figure 4.
  • the control unit 120 is thereby configured to obtain a progesterone level of a milk sample of the animal 100.
  • the control unit 120 is further configured to detect, at a first moment in time 210, that the obtained progesterone level is lower than a first threshold limit.
  • the control unit 120 is configured to obtain an activity level of the animal 100.
  • the control unit 120 is configured to detect that the obtained activity level exceeds a second threshold limit at a second moment in time 220, within a predetermined first time period 240 from the first moment 210 of detecting that the progesterone level is lower than the first threshold limit.
  • the control unit is furthermore configured to determine the insemination time interval 230 of the animal 100 to be a second time period 250 from the moment 220 Of detecting the activity level exceeding the second threshold limit.
  • the control unit is also configured to generate a command signal to a user equipment 150 to output information to the user, comprising the determined insemination time interval 230 of the animal 100.
  • the control unit 120 may be further configured to trigger high frequency activity level samplings of the animal 100 during the predetermined first time period 240, when it is detected that the progesterone level is lower than the first threshold limit.
  • control unit 120 may be configured to detect that the obtained activity level after having exceeded the second threshold limit, falls below a third threshold limit.
  • the second time period 250 may be determined based on at feast one animal status related parameter, such as e.g. breed, parity, energy balance, Days In Milk, milk production, Body Condition Scoring, age, shape of a series of progesterone level measurements over time, historically used time period 250 between the moment 220 of detecting the increased activity level and the insemination time interval 230.
  • the control unit 120 may also be configured to calculate a probability of successful insemination of the animal 100 at different moments in time within a time interval comprising the determined second time period 250, in some embodiments. Further, the control unit 120 may be configured to output information to the user further comprising the calculated probability of successful insemination of the animal 100 at different moments in time in the time interval.
  • the system 500 further comprises a progesterone measurement unit 115, configured to ob- tain a progesterone level of a milk sample of the animal 100.
  • the system 500 also comprises an activity measurement unit 110, configured to obtain an activity level of the animal 100.
  • the system 500 comprises a user equipment 150, configured to output information to the user, such as e.g. a cellular telephone or similar communication device.
  • the system 500 may in some embodiments also comprise a database 140, configured to store animal status related parameters.
  • the control unit 120 may comprise a receiver 510 configured to receive information from the transceiver 125, from the activity meter 110 and/ or from the progesterone measurement unit 115.
  • the control unit 120 also comprises a processing circuit 520 configured for performing various calculations for conducting the method 400 according to at least some of the previously described steps 401-408.
  • Such processing circuit 520 may comprise one or more instances of a processing circuit, i.e. a Central Processing Unit (CPU), a processing unit, a processing circuit, a processor, an Application Specific Integrated Circuit (ASIC), a microprocessor, or other processing logic that may interpret and execute instructions.
  • a processing circuit i.e. a Central Processing Unit (CPU), a processing unit, a processing circuit, a processor, an Application Specific Integrated Circuit (ASIC), a microprocessor, or other processing logic that may interpret and execute instructions.
  • CPU Central Processing Unit
  • ASIC Application Specific Integrated Circuit
  • microprocessor may thus represent a processing circuitry comprising a plurality of processing circuits, such as, e.g., any, some or all of the ones enumerated above.
  • control unit 120 may comprise a memory 525 in some embodiments.
  • the optional memory 525 may comprise a physical device utilised to store data or programs, i.e., sequences of instructions, on a temporary or permanent basis.
  • the memory 525 may comprise integrated circuits comprising silicon-based transis- tors.
  • the memory 525 may comprise e.g. a memory card, a flash memory, a USB memory, a hard disc, or another similar volatile or non-volatile storage unit for storing data such as e.g. ROM (Read-Only Memory), PROM (Programmable Read-Only Memory), EPROM (Erasable PROM), EEPROM (Electrically Erasable PROM), etc. in different embodiments.
  • control unit 120 may comprise a signal transmitter 530.
  • the signal transmitter 530 may be configured for transmitting signals via a wired or wireless communication inter- face to the transceiver 125 and/ or the database 140.
  • the system 500 may comprise additional units for performing the method 500 according to steps 401-408.
  • the above described steps 401-408 to be performed in the control unit 120 may be implemented through the one or more processing circuits 520 within the control unit 120, together with a computer program for performing at least some of the functions of the steps 401-408.
  • the computer program comprises instructions which, when the computer program is executed by the control unit 120 in the system 500, cause the control unit 120 to carry out the method 400 according to at least some of steps 401 -408.
  • the computer program mentioned above may be provided for instance in the form of a computer-readable medium, i.e. a data carrier carrying computer program code for performing at least some of the steps 401-408 according to some embodiments when being loaded into the one or more processing circuits 520 of the control unit 120.
  • the data carrier may be, e.g., a hard disk, a CD ROM disc, a memory stick, an optical storage device, a magnetic storage device or any other appropriate medium such as a disk or tape that may hold machine readable data in a non-transitory manner.
  • the computer program may furthermore be provided as computer program code on a server and downloaded to the control unit 120 remotely, e.g. over an Internet or an intranet connection.
  • the term "and/ or” comprises any and all combinations of one or more of the associated listed items.
  • the term "or * as used herein, is to be interpreted as a mathematical OR, i.e., as an inclusive disjunction; not as a mathematical exclusive OR (XOR), unless expressly stated otherwise.
  • the singular forms "a”, “an” and “the” are to be interpreted as “at least one”, thus also possibly comprising a plurality of entities of the same kind, unless expressly stated otherwise.

Abstract

La présente invention concerne un procédé (400), une unité de commande (120) et un système (500) destinés à aider un utilisateur à déterminer un intervalle de temps d'insémination (230) d'un animal (100). L'unité de commande (120) est conçue pour : obtenir un taux de progestérone d'un échantillon de lait de l'animal (100) ; détecter que le taux de progestérone est inférieur à une première limite de seuil à un premier moment (210) ; obtenir un niveau d'activité de l'animal (100) ; détecter que le niveau d'activité dépasse une seconde limite de seuil à un second moment (220), dans une première période de temps (240) à partir du premier moment (210) ; déterminer l'intervalle de temps d'insémination (230) de l'animal (100) comme étant une seconde période de temps (250) à partir du moment (220) où il est détecté que le niveau d'activité dépasse la seconde limite de seuil ; et générer un signal de commande à destination d'un équipement utilisateur (150) pour que celui-ci délivre des informations à l'utilisateur, comprenant l'intervalle de temps d'insémination (230).
PCT/SE2017/051255 2016-12-15 2017-12-12 Procédé, unité de commande et système de détermination d'heure d'insémination WO2018111179A1 (fr)

Priority Applications (2)

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EP17817934.7A EP3568008A1 (fr) 2016-12-15 2017-12-12 Procédé, unité de commande et système de détermination d'heure d'insémination
CA3073927A CA3073927A1 (fr) 2016-12-15 2017-12-12 Procede, unite de commande et systeme de determination d'heure d'insemination

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SE1651652-8 2016-12-15
SE1651652 2016-12-15

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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111034642A (zh) * 2019-11-25 2020-04-21 秒针信息技术有限公司 一种管理待配种的雌性牲畜的方法和装置
WO2022074509A1 (fr) * 2020-10-05 2022-04-14 Lely Patent N.V. Procédé de gestion d'un troupeau et dispositif de traite pour appliquer le procédé
NL1043809B1 (nl) * 2020-10-06 2022-06-03 Lely Patent Nv Werkwijze voor beheren van een kudde, en een melkinrichting voor uitvoeren van de werkwijze

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20020124803A1 (en) * 2001-03-07 2002-09-12 Fei Chen System for optimising the production performance of a milk producing animal herd
WO2009011641A1 (fr) * 2007-07-13 2009-01-22 Delaval Holding Ab Procédé pour détecter un comportement oestrale d'un animal à lait

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20020124803A1 (en) * 2001-03-07 2002-09-12 Fei Chen System for optimising the production performance of a milk producing animal herd
WO2009011641A1 (fr) * 2007-07-13 2009-01-22 Delaval Holding Ab Procédé pour détecter un comportement oestrale d'un animal à lait

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
A. SCULLY ET AL: "The Use of On-Farm Software for Automatic Interpretation of Milk Progesterone Data: An Aid to Dairy Fertility Management", NOTTINGHAM CATTLE FERTILITY CONFERENCE 2000, 1 October 2000 (2000-10-01), XP055088080 *

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111034642A (zh) * 2019-11-25 2020-04-21 秒针信息技术有限公司 一种管理待配种的雌性牲畜的方法和装置
WO2022074509A1 (fr) * 2020-10-05 2022-04-14 Lely Patent N.V. Procédé de gestion d'un troupeau et dispositif de traite pour appliquer le procédé
NL1043809B1 (nl) * 2020-10-06 2022-06-03 Lely Patent Nv Werkwijze voor beheren van een kudde, en een melkinrichting voor uitvoeren van de werkwijze

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