• 专利附录
  • 专利说明
  • 权利要求
  • 类似技术
  • 同族专利
  • 引用文献
  • 法律状态
  • 优先权
    • 专利摘要:
    Apparatus and Method for Identifying Important Biological States in an Animal The present apparatus and method provides automated real-time, non-invasive infrared thermography information of an animal to be used for both thermal and behavioral measurement, thus providing earlier prediction and more accurate onset of disease action, growth states or reproductive states in the animal. more specifically, the present system and method provide the use of thermal imaging (taken, for example, at a water station) to obtain both temperature and behavioral information about one or more animals at a time and use this information to determine health , growth or reproductive status of the animal. the combination of thermal biometric data, such as radio frequency identification infrared thermography information and behavioral biometrics, such as behavioral concerns, can be used to detect early onset of action of these biologically stable and unstable states in animals.
    公开号:BR112013024948B1
    申请号:R112013024948-0
    申请日:2012-03-28
    公开日:2021-06-15
    发明作者:Clover Bench；Allan Schaefer
    申请人:Clover Bench；Allan Schaefer；
    IPC主号:
    专利说明:

    TECHNICAL FIELD
    [0001] A non-invasive apparatus and method of identifying biologically important conditions in animals are provided. More specifically, an apparatus and method of combining real-time, non-invasive ethological behavioral information with infrared scanning to identify agriculturally important states, such as disease, growth, or reproductive states, in animals such as farm animals, is provided. FUNDAMENTALS OF THE INVENTION
    [0002] Farm animals are often subjected to significant exposure to transport and handling, batching, auctioning, and occasionally without food and water. Collectively, these events can slow the immune system and can result in a significant incidence of disease. Such events can have considerable economic impact, for example, on the agricultural industry, both in terms of health care costs and animal performance. Recent research has resulted in a greater understanding of the importance of animal control factors, such as transport and ante-mortem handling, in influencing both the animal's well-being and the quality of food from such animals. It is known that disease and stress can have a dramatic negative impact on the parameters of animal welfare and performance, as well as on meat quality and yield and, consequently, on the economy of animal industries.
    [0003] As skilled in the art will notice, numerous diseases, such as Bovine Viral Diarrhea (BVD) type 1 and 2, Infectious Bovine Rhinotracheitis (IBR), Corona Virus, Bovine Para-Influenza (PI3) and Bovine Respiratory Syncytial Virus (BRSV) , can impact farm animal populations. One such complex disease, known as bovine respiratory disease (BRD), refers to a host of complex diseases and is generally used to refer to an animal that has an undifferentiated fever and/or other clinical signs ( eg respiratory distress, lethargy and loss of appetite).
    [0004] The presence of BRD in intensively reared calves has caused a reliance on antibiotic treatment (including mass treatments) which, in turn, has led to a concern about promoting antibiotic resistant microbes. Certainly, the ability to treat BRD in cattle is becoming more difficult due to the emergence of resistant microbes (for example, pneumonia) or new zoonotic diseases in cattle herded from multiple sources. In addition, recent reports have shown substantial contamination of carcass and meat products with antibiotic resistant strains of bacteria such as E. coli.
    [0005] The effectiveness of treating farm animal diseases, such as BRD, may depend on the ability to detect, diagnose and prematurely treat affected animals. The ability to achieve initial detection will depend on the information available and the reliability of this information. For example, when used alone, traditional clinical signs of illness provide poor diagnostic results because clinical symptoms often occur later in the course of the illness. Additionally, many diagnostic techniques, such as the use of acute phase proteins or hematology assessment, require invasive in vivo capture and collection of biological samples, which results in significant cost of analysis and time. The requirement to capture (and therefore retain) the animal in order to collect a biological sample causes tension and the process itself therefore introduces inaccuracies in the collected data.
    [0006] Recent research has focused on alternative approaches to non-invasively determine early identification and onset of disease action in cattle. One such approach is infrared thermography, which can be used as a means of detecting heat dissipation in animals. Thermography operates on the principle that infrared radiation can be used to observe radiated heat loss and provide an early indicator of fever, because up to -60% of an animal's heat loss can occur in infrared bands. The technology has been shown to be effective in non-invasively identifying transport stressors and other environmental stressors that can alter an animal's heat loss.
    [0007] Another approach to non-invasive disease analysis is the commonly used "pen inspection" approach, in which the animal caretaker observes the animal daily to detect any abnormal behavioral patterns or clinical signs of illness (eg, decline in feeding due to loss of appetite; see Table 1 for additional examples of behavioral reference patterns). Although non-invasive, pen inspection is highly imprecise, particularly during the onset of disease stage, and leads to false positive and false negative results by virtue of being dependent on caretaker practice and observations. Additionally, it is known that animals often do not exhibit overt signs of disease (which would be detectable by a caretaker) until later in disease progression, resulting in a greater risk of infection of healthy animals in a population, particularly where animals share a food and water source. TABLE 1 - PRIOR TECHNOLOGY Clinical scores commonly used in early detection of bovine respiratory disease (BRD)


    [0008] It is also known that the identification of non-diseased states in animals is important for the agricultural industry, as well as for zoo and wildlife biological environments. There are many biological events in an animal's life that influence a plethora of measurements and expressed biometric characteristics. Some of these events are normal biological functions that an animal will exhibit, such as when they adapt to a change in environmental temperature, a change in growing season, or a change in an endocrine event, including puberty or heat. Other events are less common and will include the onset of an unhealthy state. In both unhealthy and non-unhealthy states the animal will be considered to be in a biologically important non-steady state during these periods. These biologically important states can have, for example, agriculturally important consequences and implications.
    [0009] Growth efficiency in animals is often defined as the gain in a particular tissue type such as muscle or milk compared to the input of resources such as food and water. In addition to disease states, growth efficiency is an important attribute in animal agriculture as competition for limited resources increases. However, measuring growth efficiency has always been a challenge. One of the most accurate methods to monitor growth efficiency is to use indirect calorimetry that measures exactly the amount of oxygen and energy used by an animal for a given increase in the gain of a specific tissue, while noting that the metabolism will also give off heat ( Kleiber, M. 1961. The fire of life - an introduction to animal energetics. John Wiley & Sons, Inc). Alternatively, growth efficiency can be monitored by measuring the actual food consumed by an animal and the resulting growth, or by measuring the so-called gain-to-food ratio (Kleiber, M. 1961. The fire of life - an introduction to animal energetics John Wiley & Sons, Inc).
    [00010] A more recent approach to monitoring growth efficiency has been to monitor the so-called residual food intake (RFI) which is fundamentally a comparison of measured feed for gain against a known estimate for feed for gain based on scientifically accepted formulas ( Basarab et al. 2003, 2007 see below). However, the latter method, while reasonably accurate, requires an extended feeding monitoring period of seventy days or more, which is both expensive and impractical.
    [00011] It is also known that the identification of reproductive states in animals is important for biology in general and for the agricultural industry specifically. For example, reproductive states such as onset of puberty and heat are important to identify for the purposes of reproductive efficiency and therefore agricultural efficiency. In technology, it is known that the onset of puberty and heat are characterized by behavioral heat that includes greater restlessness in the animal.
    [00012] Therefore, there is a need for non-invasive, early action and accurate means of identifying biologically important states in animals. Furthermore, there is a need for a non-invasive means of detection that is capable of identifying sick animals, even in populations where there is a low prevalence of the disease. SUMMARY OF THE INVENTION
    [00013] The present apparatus and method provide automated, non-invasive real-time infrared thermography information of an animal to be used for both behavioral and thermal measurements and thereby providing an early and more accurate predictor of onset of state action of growth or reproductive disease states in these animals. More specifically, the present system and method allow the use of thermal images (taken, for example, at a water station) to obtain both temperature and behavioral information about one or more animals at a time and to use this information to determine the health, growth or reproductive status of the animal. The combination of thermal biometric data such as radio frequency identification infrared thermography and behavioral biometric information such as behavioral concerns can be used to detect early-stage onset of these steady-state and non-steady biological states in animals.
    [00014] Generally speaking, an apparatus is provided for identifying important biological states in an animal, the apparatus comprising: an attachment for receiving the animal therein; animal identification device mounted in the enclosure and connected to a reader to identify when an animal is received in the enclosure; at least one infrared thermography camera mounted in the attachment to photograph the animal to obtain infrared thermography and animal behavioral information; and a processor in communication with the reader and camera to receive and process information from the camera and reader; where the information processed by the processor identifies important biological states in the animal.
    [00015] Generally speaking, a method of identifying important biological states in an animal is provided, the method comprising: providing an attachment that receives the animal therein; receive an animal inside the annex; identify the animal; photograph the animal to obtain infrared thermography images and animal behavioral information; process infrared thermography images and behavioral information; and identify important biological states in the animal as a result of the processing of infrared thermography images and behavioral information.
    [00016] All documents and references referred to herein are incorporated by reference in their entirety. FIGURES
    [00017] Figure 1 represents a modality of an apparatus to combine non-invasive, real-time ethological behavioral information with infrared scanning to identify biologically important states;
    [00018] Figure 2 shows a schematic diagram of the modality of figure 1, image published in Schaefer et al. 2011. Research in Veterinary Science. In Press;
    [00019] Figure 3 shows a graphical representation of behavior data for calves suffering from BRD, in which sick (sick) calves “restless” more per drink compared to healthy (non-sick) calves;
    [00020] Figure 4 shows a graphical representation of behavior data for calves suffering from BRD, in which sick (sick) calves generally “uneasy” more than healthy (non-sick) calves;
    [00021] Figure 5 shows a graphical representation of infrared thermography data vs time of calves with true positive BRD (disease) and true negative (healthy);
    [00022] Figure 6 shows a graphical representation of infrared thermography data plotted against time for calves with true positive (disease) and true negative (healthy) BRD; and
    [00023] Figure 7 shows a graphical representation of a comparison of thermal infrared values in a true negative healthy animal (TN) and a true positive sick animal (TP) for comparison. Data show the radiated thermal value (y-axis) vs the study day (x-axis). DESCRIPTION OF THE MODALITIES OF THE INVENTION
    [00024] An apparatus and method for initial detection of biologically important states in animals such as farm animals is described. In some embodiments, biologically important states may have agriculturally important states.
    [00025] More specifically, an apparatus and method of combining thermal and behavioral biometric information for the initial identification of disease, growth efficiency, puberty or heat is provided. Infrared thermography (IRT) and ethological reference marks can be combined to provide an initial and automated identification system. Although the present disclosure generally relates to beef cattle, those skilled in the art should understand that the apparatus and methods provided herein can be used to detect disease in any animal, such as farm animal species, including, but not limited to, cattle. of milk, pigs and poultry.
    [00026] In the present apparatus and method, automated thermal and ethological data can be collected simultaneously using at least one IRT camera and software system. Thermal data can be used in conjunction with infrared diagnostic or predictive values, along with ethological (behavioral) predictors called "disquiet" (ie, the "disquiet factor"), in which both infrared and restlessness values are both determined to from IRT thermal camera image data. Infrared thermography information
    [00027] An embodiment of the present scanning apparatus is shown in figure 1. Figure 1 depicts an embodiment of an automated radio frequency identification (RFID) driven multi-calf infrared scanning apparatus, which can be attached to a water trough and can comprise a data storage unit (A), camera housing (B) and a water system with an RFID antenna (C).
    [00028] With reference to figure 2, the automated scanning apparatus may comprise: • An attachment, to receive the animal therein, in which the attachment may be, for example, a water or food station. In some arrangements the attachment could be fenced, in other arrangements the attachment could simply be a pasture area. As those skilled in the art would understand, an attachment can comprise any area or structure that performs the functions described herein.
    [00029] In the present modality, a water station with two side panels (1) was designed, involving a design of two commercially available floating water vats, (2) from Ritchie Water Systems (Ritchie Cattle Fountains, Conrad IA, USA) and optionally separated by a partition between them. This annex may allow access to the water station from two or more directions. It should be noted that a water station was used in this modality because, during the illness, it is known that animals stop eating, due to loss of appetite, before they stop drinking. It should also be noted that any attachment or other means of reducing the overall movement of an animal, in a tension-free manner, so that an image of the animal can be made, could be used and is contemplated;
    [00030] Extension panels (3) can be placed on either side of the water tubs to “center” or adjust the position of the animal's head and to help keep the animal's head at the proper focal length. A panel (1) on one side of the water tubs can be modified to facilitate a window (4) in order to observe the animal while at the water station. The window can measure, for example, approximately 30 cm square;
    [00031] At least two phased frame antennas (5), to receive information from the animal's radio frequency identification (RFID) tag, or other animal identification device such as this, as applicable, may be mounted on the panels (1 ) adjacent to (or close to) the water tubs (2) and connected to an Allflex PNL-OEM-MODLE-3 RFID (6) control module or "reader" system (Allflex EID, Allflex Canada Inc. St-Hyacinthe , BECAUSE).;
    [00032] At least one infrared thermography camera (8). The camera (8) may, for example, be capable of taking at least 1 - 60 images/second such as a FLIR S60 wideband camera (FLIR Comp., Boston, MA), which can be rotationally mounted adjacent to windows or close to them (4). Means for electronically rotating the camera (8), such as a geared head motor, can be connected to the camera to trigger the rotation of the camera. The camera can be used to obtain radiated temperatures, for example, around the orbital area (eye plus one centimeter surrounding the eye) of animals. The orbital area of the eye was chosen in the present system because it is known to provide an accurate peripheral temperature reading, thereby providing a measurement that is sensitive to both strain and the onset of disease action. Although the thermal (eye) orbital is described here, it is understood that any area on the animal that provides an accurate and adequate peripheral thermal reading of the animal's temperature can be used; and
    [00033] A control system or processor (9), to receive and process information from the camera (8) and the RFID antenna/reader (5, 6). For example, the processor can be programmed to control camera positioning, acquire the infrared image, perform image data analysis and store the acquired information in a database. The information can be collected and received automatically upon the animal's entry into the enclosure and the processor can collect the information via wireless transmission so that the information can be monitored remotely. Instrument integration and the hardware and software used in such a thermal station was designed and developed, in part, at the Lacombe Research Centre, Lacombe, Alberta, Canada.
    [00034] In one embodiment, an optional electromagnetic shield (7) can be exposed to the containment pen on the side of the panels (1) to prevent improper reading of RFID tags on animals that are not within the attachment.
    [00035] In operation, the present apparatus and methods allow that, when an animal enters the annex, the RFID antenna system (5, 6) can receive the animal's identification from the RFID tags and can signal the control system ( 9) to rotate the camera (8), if necessary, towards the animal and start capturing images of the animal's head when it becomes visible through the window (4) on the panel (1). In one embodiment, the camera/motor assembly (8) can be enclosed in a protective cover and can be located medially between the two observation windows (4) at a distance that provides an observation field to cover most head positions of an animal.
    [00036] It is understood that mounting the infrared camera on an engine capable of rotating at least two different scanning windows (4) signaled by the RFID reader can provide the ability to obtain information from at least two animals at once. For example, the system can be designed to accommodate a second attachment/thermography station located parallel to the first station with the camera located centrally between the two stations, thereby at least doubling the animal handling capabilities of the system.
    [00037] The present devices and project can allow to know methods of correcting thermography techniques, namely, a fixed focal length and angle with an image still close, thereby providing accurate thermal data collection. The system can additionally provide non-invasive means of obtaining both thermal and behavioral biometric information (discussed below) without the need to restrict or capture animals. It is understood that any similar system capable of providing correct thermography information is contemplated, without the need to capture and retain the animal.
    [00038] Ethological Information (Behavioral)
    [00039] The present apparatus and methods may also provide the use of the IRT information obtained from the animals as a behavioral predictive measure of disease onset or other biologically important states in animals. For example, thermal images taken at the water station, as described herein, can be further used to obtain behavioral information about the animal, thereby providing a means for combining thermal biometric information (temperature) with behavioral biometric information to provide earlier and more accurate detection and identification of the disease state in the animal.
    [00040] Each time-stamped image taken by the automated IRT system can be classified as a behavioral "event". For example, animal movement at the water station may cause the camera (8) to have to re-establish thermal contrasts between two or more IRT pixels, thereby automatically causing a new image to be taken and time-tagged, and the animal's postural adjustment or "restlessness" is recorded. As such, depending on how much restlessness the animal has at the water station, more or less pictures can be taken of one animal compared to another. The images can then be used to calculate behavioral factors such as, for example, the total time the animal spends drinking, the number of drinking bouts, the duration of each drinking bout, the average number of drinking bouts. drink per day and the number of "events" (ie, restlessness) recorded (eg, the number of thermal scans taken during a single drinking bout). The information can then be used, along with thermal information, to determine "true positive" (ie, disease) and true-negative (ie, not diseased) illness. Consequently, an ethological predictor of disease, referred to here as a “distress factor” can provide an additional benchmark for detecting and identifying the non-invasive disease state.
    [00041] It should be noted that different animals may be more or less restless than others in the population and that restlessness can additionally be altered due to a growing state or reproductive disease state. It should be known that the processor may be able to use all infrared thermography images of each animal (eg, orbital (ocular), mouth, nose, ear, shoulder and body images have all been included in the behavior dataset) in order to process the fidgeting behavior.
    [00042] Thus, the present apparatus and method can provide the use of infrared thermography images to be used to detect the peripheral temperature of the animal as well as the behavioral activity of the same animal, thereby providing detection and identification of the initial disease state and more accurate. It is understood that the present apparatus and methods can provide two distinct sets of data or information to be generated in parallel or in series. It will also be apparent that these two sets of biometric data consisting of both infrared and disquiet information can be used in numerous statistical evaluation procedures including multiple regression and correlation indices, classification and prediction to allow for more accurate identification of true positive and true negative animal. .
    [00043] Such means of detection and identification are likely to be applicable in a variety of environments, including, for example, in biosecurity and biosurveillance circumstances.
    [00044] The following examples are provided to help understand the present disclosure, the true scope of which is set forth in the claims. It is understood that modifications can be made to the system and methods presented without departing from their spirit or scope, as defined here.EXAMPLESExample 1Animals
    [00045] In this example, forty (40) calves from auctioned recipients, commercial from multiple sources, separated into batches and transported, that were exposed to viral and bacterial infection for respiratory viruses including BVD, PI3, IBR, Corona and BRSV and forty ( 40) Retained possession calves were used. Calves were weighed, monitored for core and orbital thermal properties, blood sampled and placed in conventional cereal grain silage with access to shelter and clean water.
    [00046] Twenty (20) of these calves were obtained from the herd without BVD and IBR antibody at the Animal Diseases Research Institute at Lethbridge, Alberta, Canada. These calves were Angus x Hereford crosses and were weaned approximately one week prior to transport to Lacombe, Alberta, Canada. The calves averaged 550 lbs, were raised on native grass pasture and received a deworming medication two weeks before weaning.
    [00047] The calves were transported in a conventional disinfected horse trailer. Upon arrival at Lacombe Research Station, a transport time of approximately 5 hours, the calves were batched with 20 calves auctioned from multiple sources and separated into batches. All calves were monitored continuously for 3 weeks. It was observed that all calves had continuous contact with each other touching their snouts as well as sharing the same water vat, salt shaker, trough and forage. infrared thermography
    [00048] Automatic infrared thermography (IRT) images were collected using an Inframetrics S60 portable broadband infrared scanner (FLIR® Inframetrics S60, Boston, MA, USA). All images were taken of animals as they entered the automated infrared scanning station at the common water station located in the pen (see Figures 1A, B and C). In the present experiment, specific images for the orbital area of each calf were used to collect thermal data.
    [00049] All calves were thus monitored with respect to the mean of the maximum daily temperatures (including change in temperature) and for the mean ratio (MR) values. The mean ratio which was calculated as the mean maximum daily irradiated temperature for a given animal divided by the mean daily maximum value for the group of calves. Thermal data were verified by comparison with blood serology and virology parameters. Ethology - "Carelessness"
    [00050] Using the time tag (which provides the hour, minute, second and date of the image taken by means of a stopwatch or clock), for each image taken by the automated IRT system, each image was defined as a behavioral "event". that triggered the image to be registered. During the present example, a 4-minute interval between drinking events (known as the burst criterion interval; BCI) was used to determine the end or completion of one drinking bout and the start of another. Consequently, the same infrared images were used in analyzing both thermal and ethological datasets, however, the ethological dataset included "all images", while the thermography dataset included only "orbital images". Results
    [00051] In the forty (40) commercial calves from multiple sources and separated into lots, 10 animals were taken from the 40 identified as “sick” (true animal positive). This identification was made by virtue of presenting clinical scores of 3 or more (see Table 2) and by orbital infrared values of 35.1 °C compared to healthy animals (or true negative animal) with a temperature of 34.8 °C. Clinical illness was verified by statistically significant hematological values. Furthermore, sick calves demonstrated an increase of approximately 40% in blood cortisol values (deviating from an average of 52 nmol/L in healthy calves to above 70 nmol/L in sick calves). Results demonstrated that hematological data for the forty (40) retained possession control calves exhibited normal hematological values.
    [00052] It is known that four to six days before the display of clinical signs and laboratory verification of disease, infrared orbital scans can be 71% effective (true positive and true negative values combined) in early identification of sick animals compared to both clinical scores alone (55% efficiency) for rectal temperatures alone (59% efficiency). This is supported in the present example where non-invasive collection of infrared orbital temperatures alone was 73% efficient in identifying sick animals 2-7 days before clinical symptoms detectable by "pen check".
    [00053] Further analysis of all thermal images recorded via the automated IRT system and, based on a 4-minute drink burst interval, results show that true positive or "sick" animal has a tendency to "restless" greater than "not sick" true negative animal (Figures 4 and 5) It was observed that sick animals (true positive) have a large number of IRT images taken during each drinking bout.This is despite the general drinking behavior , which includes the duration of drinking and the number of outbreaks of drinking, being the same in sick and healthy animals (true negative). Based on the average number of concerns (events) per outbreak in sick and healthy animals, a behavioral predictor or “restlessness factor” of 4 restlessness per drinking bout was determined as a possible indicator of illness.
    [00054] False negative and false positive animals were not included in this dataset as the analysis focused only on true sick and true healthy animals.TABLE 2Mean ±SD of hematological values for the forty calves from multiple sources separated in batches. White blood cells (WBC) and all other differential cells = cells X 10, Red blood cells (RBC) = cells X 10 12, hgb = g/L


    [00055] Statistical separation based on least squares analysis (two-tailed t-test). *N/L ratio for sick animals was either very high or very low. Hematological, Endocrine, and Serology Data
    [00056] With respect to laboratory analysis, salivary and serum cortisol was analyzed using a known enzyme assay from the collected samples. Hematology analysis and differential counts were conducted on a Cell-Dyne 3700 model hematology analyzer (Abbott Labs™, Mississauga, Ontario). Serology assessment was conducted by Prairie Diagnostic Services™ (Saskatoon Saskatchewan) and assessment was performed for BRD virus, Bovine viral diarrhea (BVD) types 1 and 2, as well as infectious bovine rhinotracheitis (IBR) through neutralization tests. serum.
    [00057] Further evaluation for Corona virus, Bovine Para-Influenza (PI3) and Bovine Respiratory Syncytial Virus (BRSV) was conducted by ELISA using methods known to those skilled in the art. Antibody concentrations (units) for BVD, IBR, BRSV, PI3 and Corona were obtained as follows:
    [00058] ((sample mean net optical density - mean net optical density of fetal bovine serum) / (mean net optical density of positive standard - mean net optical density of fetal bovine serum)) X 100
    [00059] The classification of antibody titer scores was as follows: for BVD and IBR 0-2 = negative, 3-13:1 = doubtful, 14-40:1 = low, 41-80:1 = moderate , >80:1 = high. For BRSV, PI3 and Corona <10 = negative, 1 1-13 = doubtful, 14-50 = low, 51 =100 = moderate, > 100 = high.Example 2Animals
    [00060] In this example, additional experiments were conducted on 100 commercial calves from multiple sources, separated into lots, transported and weaned. These calves were sourced from two primary sources with 17 from the ADRI herd in Lethbridge, Alberta, Canada and 83 sourced from commercial auction facilities. These calves were in turn purchased through auction from two separate locations.
    [00061] The calves were taken to the Lacombe Research Center (LRC) Beef Research unit, weighed, blood sample collected, core temperatures recorded and then placed in clean recipient pens with wood shavings forage and no access to water and silage. cereal grain. Methods
    [00062] Continuous infrared and automatic behavioral data were captured in all animals for a period of three weeks (except when the power supply or solar equipment caused a system failure), as described in example 1. Results
    [00063] In the present example, thirty-seven animals were identified "at risk" for BRD by the technique of "pen check". Of those animals, 24 were subsequently verified by objective laboratory data as a true positive (TP) and 13 were identified as a false positive. Consequently, the incidence of false negatives and positives is again comparatively high when clinical pen-check scores alone are used to identify BRD.
    [00064] In calves identified as true positive for BRD, the IRT temperatures were on average 36.7 °C compared to the true negative animal at the same time at 35.6 °C (P<0.05). Figures 6 and 7 demonstrate the relationship between true positive and true negative animal for calves with the most complete clinical score and infrared data and show the infrared scores detected in animals that had BRD several days before the clinical "pen check" scores .
    [00065] Using the “disquiet factor” predictor generated and defined in example 1 to detect sick animals (an average of 4 concerns per bout of drinking over a 24-hour period), no significant difference was observed in the present Example 2. Some possible clarifications may include both the need to change the beverage intake spurt interval and due to the high rate of false negatives in a calf group. The present example also experienced greater than usual electrical problems, which they may have made the ethological dataset less robust. Current research on the fit of the BCI and the predictive value of restlessness is required and continues.
    [00066] In the present Example 3, investigations were carried out on a total of sixty-five (65) recipient calves. These calves consisted of 54 animals with a low incidence of disease, held by the Lacombe Research Center (LRC) Beef Research of a natural parturition herd and eleven (11) calves of the closed herd with high health, located at the Animal Disease Research Institute ( ADRI) in Lethbridge, Alberta, Canada. ADRI calves were unique in that they exhibited no antibodies to either the BVD virus or IBR and therefore would be susceptible to viruses that cause BRD. Calves from both herds were commercial crossbred cattle of the British X Continental breed. All calves were weaned and transported to the LRC Beef Unit prior to the study. Animals weighed 220 kg at baseline. Methods
    [00067] To encourage typical market conditions all calves were separated into lots and transported to a local auction facility within one hour of the LRC Beef Unit. The calves were then unloaded and kept in pens overnight without food or water. The cattle were loaded onto a commercial transporter and returned to Lacombe, Alberta, Canada the next day for processing.
    [00068] Upon arrival at the LRC Beef Unit the calves were weighed, subjected to a blood sample, core temperature recorded, clinically classified and then placed in recipient pens containing straw forage and without access to water and a cereal grain silage. The calves were subsequently "penned inspected" daily for signs of illness and IRT values were continuously recorded using the present system and method as defined herein. The "events" and/or behavioral concerns were monitored and an alternative "disease factor" for illness was determined based on various intervals between bouts of drinking (eg, 3 or 5 minutes instead of the 4 minutes used in the Example 1) Furthermore, preliminary life observations were conducted to determine which specific facial movements induced IRT images to be recorded as events (ie, to define the specific mechanisms of a “restlessness”). could be further improved by classifying and defining the actual fidgeting behavior, eg by video analytics.
    [00069] Hematology values for all animals were evaluated on a CellDyn™ hematology analyzer. Clinical scores were assessed using a point system (see figure 2) and core or rectal temperatures were recorded using a digital temperature probe on the side of the trough. Results
    [00070] Based on the corral check information, two of the sixty-five calves were considered to be at risk for BRD. Taken together with data available at the time of processing (core temperatures of 40 °C or more) four of the sixty-five animals would have been diagnosed as true positive for BRD. However, two of these animals were subsequently determined to be false positives by hematology analysis (white blood cell numbers and neutrophil/lymphocyte ratios), core temperature and clinical score. Using the same analysis would also have classified eleven (11) of the calves as true positive (TP) and 20 as true negative (TN) with the remaining 34 as intermediate health. Three of the (TP) true positive animals were from the ADRI herd without BVD and IBR antibody and 8 from the LRC herd. The mean values for these animals both at the beginning and at the end of the evaluation period are shown in table 3.

    [00071] Infrared Values
    [00072] In excess of 20,000 thermal data points were collected from the 65 calves during the two week assessment period using the automated thermal station located in the livestock water system. The average value of irradiated temperature for all calves during this period was typically between 33-35 °C. The overall thermal irradiated value for true negative calves for the entire observation period was 34.7 °C ± 0.57 °C and the value for true positive calves 35.4 °C ± 0.58 °C (see Figure 9) .
    [00073] Life behavioral observations were also performed in this example 3 to increase understanding of why true positive calves generated greater numbers of IRT images (when all images were included) compared to true negative calves. These observations suggest that changes in posture or position, eye blinking, leg movements, rapid tongue movements, and restless ear can cause the IRT pixels to recalculate contrasts, thereby determining that it is time to take a new image.
    [00074] Relative to the data per se, the calves used in the present study had comparatively low strain and expressed a low incidence of BRD of approximately 17%. Of interest, however, was the observation that standard industry practice of using pen checking as the primary tool to identify BRD would have identified only two animals and, even with the addition of core temperature data at the time of processing, only four animals were identified at risk for BRD, and of these, two were subsequently identified as false positive identifications. In other words, one of the primary challenges with conventional corral checking or clinical scoring methods to detect BRD is with the incidence of false negatives.Example 4Cortisol data
    [00075] Salivary and serum cortisol analysis was performed for all animals in previous examples 1 - 3 (see Table 4). An ELISA assay system, developed at the Lacombe Research Center, was used.
    [00076] In all three datasets in the example cattle were identified as true positive (TP) for bovine respiratory disease (BRD) or true negative (TN) using the hematology, core temperature, and clinical score criteria identified in each one of the sections of the previous method. Least squares analysis (t tests) for cortisol data was also performed.
    [00077] Cortisol assays were conducted on blood and saliva samples collected when cattle arrived at the Lacombe Beef Research Center and when an animal was identified as suspected of BRD. Cortisol data exhibited considerable variation both within studies and between studies performed in Examples 1 - 3. Part of this variation is primarily due to variation in animal populations, acquisition procedures, and animal history between groups. There is also likely to be some variation in stress susceptibility across groups of cattle from experiment to experiment.
    [00078] Table 4 represents overall means for animals, uncorrected for the present dataset for animals showing health aberrations for non-BRD reasons such as transport stress, mechanical insults such as lameness or other metabolic reasons such as dehydration. There have been some of these animals identified and they could arguably cause some bias in the dataset. However, cattle identified as TP for BRD also showed a trend towards this, or a real statistical increase in cortisol values. Some animals observed also tended to fall into an intermediate group for BRD identification. Again, as described in the methods section, a true negative animal would have exhibited a score value of 0 or 1 for temperature values > 40 °C, WBC counts of > 10 or <7 X 103 /pL, an N/L ratio of < 0.1 or > 0.8 and a clinical score of < 3. A true positive animal would exhibit a value of 3 or 4 of these criteria and intermediate animals would exhibit a value of 2. As with the other laboratory criteria, these Intermediate animals also tended to exhibit an intermediate cortisol value (data not shown).TABLE 4 Salivary and serum cortisol values in weaned calves and recipients identified as true positive (TP) or true negative (TN) for BRD

    [00079] These results demonstrate that animals presenting BRD demonstrated a greater infrared irradiated temperature and a greater degree of variation associated with this temperature. Cortisol data are also consistent with this observation, showing that animals with BRD in general exhibit a higher cortisol value with greater variation.Example 5 Restlessness value and growth efficiency
    [00080] As an alternative to the methods discussed in the background section of the previous invention, evidence has been reported that demonstrates the use of infrared thermography to classify animals into more efficient and less efficient growth categories (Schaefer, AL, Basarab, J., Scott, S., Colyn, J., McCartney, D., McKinnon, J., Okine, E. and Tong, AKW 2005. The relationship between infrared thermography and residual feed intake in cows J Anim Sci 83(Suppl. 1):263). It is known that animals that are more efficient in growth can exhibit less heat loss to the environment. However, the components that make up or account for this difference in efficiency and energy loss are less apparent. To this end, the present apparatus and methods can be used to show what behavior or so-called "restlessness" of the animal may be partially responsible for this differential energy use. As such, measuring these "concerns" would be useful in differentiating animals with different growth efficiencies. This Example 5 is provided as a non-limiting example of implementing this principle.
    [00081] Eight mature crossbred cows were used in the present example to test whether a restlessness measurement also ranked as both a growth efficiency measure (Residual feed intake, RFI) and an energy loss measure (infrared thermography). The cattle were fed a diet based on a balanced alfalfa cube that met 1.25 times the nutritional requirement for sustenance for these animals. The cows were housed in pens outside with free access to fresh water and a straw stratified area.
    [00082] The relative growth efficiency for these animals, referred to as residual feed intake, was previously determined using a feed trough monitoring system to record accurate feed intake and weight gain as described by Basarab et al (Basarab , JA, McCartney, D., Okine, EK and Baron, VS 2007. Relationships Between residual progeny feed intake and dam productivity traits Canadian Journal of Animal Science 87(4):489-502: Basarab, JA, Price, MA, Aalhus, J.L, Okine, EK, Snelling, WM and Lile, KL 2003. Residual feed intake and body composition in young growing cattle. Canadian Journal of Animal Science 83(2):189-204).
    [00083] For infra-red measurements and restlessness the cows were monitored post pandrially between a 24-hour feeding period. In other words, the animals were without food during the monitoring time. However, all the animals had free access to a water station, and when the cows found the water station, they fired an infrared scanning system that included a radio frequency identification tag (RFID) therethrough, recording both their frequency of service of the station and its infra-red facial characteristics.
    [00084] The mean daily values for the infrared scans for the half of the animals with the lowest efficiency and the half of the animals with the highest value are summarized and shown in table 5 along with the known RFI feed efficiency values for the cow group of 8 animals. The RFI values basically report what an individual animal's actual food intake was (as measured by trough monitoring systems) compared to what this animal's predicted food intake would be based on its body weight and growth. For example, as explained by Basarab et al (2003), an animal with an RFI value of -1 represents a cow that consumed 1 kg per day less food than would be expected and an RFI value of +1 represents an animal who consumed 1 kg of food more than expected. Lower RFI values may represent more efficient cows. In addition to what is shown in table 5, the values of restlessness or number of triggering events of the thermal station were also collected. These data are expressed as the total number of concerns per animal per day in four-minute bouts of drinking.
    [00085] Using conventional ranking statistics (Spearman Ranking: Tuckman. 1978. Conducting Educational Research, Second Ed. Harcourt Brace Jovanovich Inc. New York) the animals in the present study exhibited a significant rank order (P<0.05) of thermal values against known RFI values. Animals with the lowest thermal values also exhibited the lowest RFI values and the lowest number of restlessness events. This example demonstrates that a restlessness value can be useful in identifying animals with different production (growth) efficiencies.
    Example 6 Restlessness and heat
    [00086] In technology, it is known that there is a link between restless behavior and heat in animals.
    [00087] Behavioral indicators of estrus are the primary devices in which producers determine whether dairy cows are in estrus (ie, have ovulated or are ready to ovulate). Behavioral indicators of heat include increased activity, such as mounting, step/gait events, as well as general restless behavior (eg, lying down and getting up, stepping, walking and shifting, but also include many other more subtle behaviors; Pollock, WE and Hurnick, LF 1979. Effect of two confinement systems on estrus 436 Detection and and dietrus behavior in dairy cows. Can. J. Anim. Sci. 59: 799-803.; Walton, JS and King, GJ 1986. Indicators of estrus in Holstein cow housed in 468 tie stalls. J. Dairy Sci. 69: 2966-2973).
    [00088] Cows housed in open stables exhibit 4 times more activity and restless behavior during heat (Kiddy, CA 1977. Variation in physical activity as an indication of estrus in dairy 414 cows. J. Dairy Sci. 60: 235-243) . Cows housed in confined stables exhibit 2.75 times more activity and restless behavior during heat (when compared to cows not in behavioral heat). Similar findings have been reported when pedometers were used to measure activity and restless behavior during heat in free stables (Roelofs, JB, van Eerdenburg, FJCM, Soede, NM and Kemp, B. 2005. time of ovulation in dairy 452 cattle. Theriogenology. 64: 1690-1703; Roelofs, J., Lopez-Gatius, F., Hunter, RHF, van Eerdenburg, FJCM and 447 Hanzen, C. 2010. When is a cow in estrus Clinical and practical aspects. 448 Theriogenology. 74: 327-344). Although pedometers in cows continuously confined in stables were unable to detect behavioral estrus based on gait activity measured alone (Felton, CA, Colazo, MG, Ponce-Barajas, P., Bench, CJ and Ambrose, DJ 2012. Housed cows). continuously confined could not manifest activity changes during heat Can. J. Anim. Sci. (in press), the use of a more subtle behavioral biometric of restless behavior has the ability to capture behavioral estrus even in confined cows.
    [00089] Because the restlessness biometric, as described in this specification, can be an accurate and reliable measure of restless behavior when an animal is standing in a confined space, the use of this type of restlessness measure also has the device of capture restless behavior exhibited during heat. As such, the apparatus and methods described here can identify reproductive states such as estrus.Example 7Additional restlessness data (sample ED08/09)
    [00090] Calculations are included in a bovine calf respiratory disease (BRD) dataset referred to as ED08/09 (calves analyzed in 2008 and 2009).
    [00091] Briefly, a true positive animal (TP) was one that exhibited 3 or 4 out of 4 for a high white blood cell count, a high neutrophil/lymphocyte ratio, a high clinical score, and an elevated core temperature ( rectal). These criteria are defined in publications known in the technology. In contrast, a true negative animal (TN) was one that exhibited a score of both 0 and 1 out of 4.
    [00092] From the ED08/09 dataset for 21 animals, 11 of the calves met a TP criterion and 10 met a TN criterion. In other words, the prevalence of BRD in this dataset was 52%. This result is very similar to that of calves separated into lots, transported and weaned from multiple sources studied anywhere and is typical for calves of this type in general.
    [00093] The biometric data collected from the ED08/09 animals to predict the early onset of disease action included the absolute infrared value for the maximum eye determination, the average ratio of the individual calf maximum eye value compared to the average maximum value. of the group, the so-called MR value and thirdly, the restlessness value for those animals calculated from the same infrared image dataset. The information restlessness/outbreak/calf/day of five minutes was used. The data used were for the day the animals were checked as TP or TN (so called test day) and the four days before that time.
    [00094] One approach to determining the relative contribution a given dataset has to an overall prediction or classification of variables is to use a multiple regression approach and also a discriminant analysis (sometimes called step-by-step regression) or regression analysis. logistics. Different statistical programs will use different names, for example SAS uses discriminant analysis and MedCalc™ uses the term logistic regression.
    [00095] Using ED08/09 data, the correct value for TP vs. TN using a single biometric measurement was between 57-68%. However, combining all three biometric measurements increased the overall correct identification of animals in the disease class (both TP and TN) to 83.5%. This improvement in correct grading is significant and also provides the ability to identify BRD prior to race day different from prior technology methods.
    [00096] One method to rank the relative importance of each biometric measurement in a multiple regression model is to obtain the r value (correlation value), extract the square root of this value and multiply by 100 to obtain the relative percentage importance of a biometric measure or the proportion of variance that a particular biometric value can represent. For example, with a situation such as calving difficulty in steers (dystocia) it was determined that the relative ranking of the importance of factors would be as follows; calf birth weight and pelvic width = 30%, calf age 10%, calf birth weight = 7% and so on. With the previous BRD model the highest rating (value to predict the onset of BRD action) for every day was the 33% absolute infrared orbital value, then the 16% restlessness value and the MR value to 10%.
    [00097] The scope of claims should not be limited by the preferred embodiments presented in the examples, but should be assigned the broad interpretation consistent with the description as a whole.
    权利要求:
    Claims (19)
    [0001]
    1. Apparatus for identifying important biological states in an animal in real time, characterized in that the apparatus comprises: an attachment to receive the animal in it; means for identifying the animal mounted in the attachment and connected to a reader to identify when an animal is received in the annex; at least one infrared thermography camera mounted in the annex to obtain images of the animal, the images simultaneously obtaining both infrared thermography information and animal agitation information, the obtaining of images being triggered by the agitation behavior of the animal; and a processor for receiving and processing the animal identification information, the infrared thermography information and the agitation information to determine an agitation factor for the animal, or the agitation factor indicative of the biological state of the animal, the biological states being selected from the group consisting of a disease state, a period of non-stable growth state, the onset of puberty, and the onset of heat.
    [0002]
    2. Apparatus according to claim 1, characterized in that the apparatus is automated.
    [0003]
    3. Apparatus according to claim 1, characterized in that the attachment further comprises a water station or food station to be accessed by the animal.
    [0004]
    4. Apparatus according to claim 3, characterized in that the attachment is configured to allow access to the water station or food station by one or more directions.
    [0005]
    5. Apparatus according to claim 1, characterized in that the attachment further comprises panels to position the animal's head in front of the camera and to help keep the animal's head at the appropriate focal length from the camera.
    [0006]
    6. Apparatus according to claim 1, characterized in that the means for identifying the animal comprise at least two phase-back antennas to receive information from a radio frequency identification tag (RFID) on the animal.
    [0007]
    7. Apparatus according to claim 1, characterized in that the camera is capable of obtaining images at a rate of at least 1 - 60 images/second.
    [0008]
    8. Apparatus according to claim 1, characterized in that the camera is rotationally mounted in the attachment.
    [0009]
    9. Apparatus according to claim 1, characterized in that the processor is in communication with the reader and camera through wireless transmission, to receive the animal identification information, the infrared thermography information and the wirelessly shaking information.
    [0010]
    10. Device according to claim 1, characterized in that the processor can monitor the reader and camera remotely.
    [0011]
    11. Method to identify important biological states in an animal in real time, characterized by the fact that the method comprises: providing an attachment to receive the animal therein; receiving an animal within the attachment; identifying the animal; capturing images of the animal with a infrared thermography camera, the images simultaneously obtaining infrared thermography information and agitation information about the animal, the capture of the images being triggered by the agitation behavior of the animal; processing the animal identification information, the infrared thermography information and the agitation information to generate a agitation factor, the agitation factor being indicative of the biological state of the identified animal, the infrared thermography images and behavioral information; where biological status is a predictor of disease onset, growth states, and reproductive states of the animal.
    [0012]
    12. Method according to claim 11, characterized in that the method is automated.
    [0013]
    13. Method according to claim 11, characterized in that it further comprises signaling a control system to rotate the camera towards the animal.
    [0014]
    14. Method according to claim 11, characterized in that it further comprises obtaining radiated temperatures around the orbital area of the animal.
    [0015]
    15. Method according to claim 11, characterized in that the identification of the animal is performed by an RFID antenna system mounted in the attachment to receive the identification of an RFID tag on the animal.
    [0016]
    16. Method according to claim 11, characterized in that it further comprises using both infrared and agitation information in statistical estimation procedures to generate a factor indicative of agitation of the biological states in the animal.
    [0017]
    17. Method according to claim 16, characterized in that the biological state is selected from the group consisting of a disease state, a period of non-stable state growth, the onset of puberty and the onset of heat.
    [0018]
    18. Method according to claim 11, characterized in that it further comprises obtaining infrared thermography and postprandial agitation information.
    [0019]
    19. Method according to claim 18, characterized in that the postprandial period is between a 24-hour feeding period.
    类似技术:
    公开号 | 公开日 | 专利标题
    BR112013024948B1|2021-06-15|APPARATUS AND METHOD FOR IDENTIFYING IMPORTANT BIOLOGICAL STATES IN AN ANIMAL
    Halachmi et al.2019|Smart animal agriculture: application of real-time sensors to improve animal well-being and production
    Schaefer et al.2012|The non-invasive and automated detection of bovine respiratory disease onset in receiver calves using infrared thermography
    Battini et al.2014|Invited review: Animal-based indicators for on-farm welfare assessment for dairy goats
    Losada-Espinosa et al.2018|Pre-slaughter cattle welfare indicators for use in commercial abattoirs with voluntary monitoring systems: A systematic review
    Frost et al.1997|A review of livestock monitoring and the need for integrated systems
    US9961883B2|2018-05-08|Rapid and automatic determination of metabolic efficiency in livestock
    Brito et al.2020|Large-scale phenotyping of livestock welfare in commercial production systems: A new frontier in animal breeding
    Jorquera-Chavez et al.2019|Computer vision and remote sensing to assess physiological responses of cattle to pre-slaughter stress, and its impact on beef quality: A review
    Neave et al.2019|Individual characteristics in early life relate to variability in weaning age, feeding behavior, and weight gain of dairy calves automatically weaned based on solid feed intake
    EFSA Panel on Animal Health and Welfare |2012|Scientific Opinion on the use of animal‐based measures to assess welfare of dairy cows
    Jaeger et al.2019|Associations between precision sensor data with productivity, health and welfare indicator traits in native black and white dual-purpose cattle under grazing conditions
    Jones et al.2009|Camelid herd health
    Toaff-Rosenstein et al.2018|The sickness response at and before clinical diagnosis of spontaneous bovine respiratory disease
    Stachowicz et al.2021|Do we automatically detect health-or general welfare-related issues? A framework
    Nakagawa et al.2016|Measurement of udder surface temperature in cows using infrared thermometer
    Lowe et al.2021|Effect of milk allowance on the suitability of automated behavioural and physiological measures as early disease indicators in calves
    Clouard et al.2011|Development of approach and handling tests for the assessment of reactivity to humans of sows housed in stall or in group
    Goharshahi et al.2021|Monitoring selected behaviors of calves by use of an ear-attached accelerometer for detecting early indicators of diarrhea
    Mincu et al.2021|Effects of milking temperament of dairy cows on production and reproduction efficiency under tied stall housing
    NZ615942B2|2016-02-02|Apparatus and method for using infrared thermography and behaviour information for identification of biologically important states in animals
    Ruiz2019|Behavioral biomarkers for calf health
    CA2854345A1|2015-12-16|Rapid and automatic determination of metabolic efficiency in livestock
    Caplen et al.2021|Changes in Behavior and Salivary Serum Amyloid A in cows with Subclinical Mastitis
    Caplen et al.2021|Subclinical Mastitis in Dairy Cows is Associated with Changes in Salivary Serum 3 Amylase-A, Social Behavior and Activity Profiles 4
    同族专利:
    公开号 | 公开日
    EP2690948B1|2017-12-06|
    US9565837B2|2017-02-14|
    WO2012129657A1|2012-10-04|
    NZ615942A|2015-10-30|
    EP2690948A1|2014-02-05|
    CA2831152C|2019-06-25|
    US20140015945A1|2014-01-16|
    AU2012234743A1|2013-10-17|
    DK2690948T3|2018-03-12|
    EP2690948A4|2015-07-29|
    CA2831152A1|2012-10-04|
    BR112013024948A2|2017-07-18|
    AU2012234743B2|2017-02-02|
    引用文献:
    公开号 | 申请日 | 公开日 | 申请人 | 专利标题
    EP0618526A3|1993-03-31|1995-09-27|Us West Advanced Tech Inc|Method and apparatus for multi-level navigable video environment.|
    NL1001336C1|1995-02-24|1996-08-28|Maasland Nv|Construction with a device for milking animals.|
    US7277744B2|1999-03-22|2007-10-02|Schaefer Allan L|Early detection of inflammation and infection using infrared thermography|
    NL1017354C2|2001-02-13|2002-08-14|Lely Entpr Ag|Device and method for milking an animal, device for monitoring an animal.|
    EP1395664A4|2001-05-15|2004-11-03|Psychogenics Inc|Systems and methods for monitoring behavior informatics|
    NZ528756A|2003-12-22|2006-10-27|Dexcel Ltd|Oestrus detection system|
    NL1025874C2|2004-04-02|2005-10-05|Nedap Agri B V|Animal condition monitoring method for e.g. cows, uses observation station to automatically identify and measure size of animal to generate condition score|
    CN101141915A|2004-08-05|2008-03-12|拜奥伊奎德公司|Monitoring system for animal husbandry|
    US7966971B2|2008-05-23|2011-06-28|C-Lock Inc.|Method and system for monitoring and reducing ruminant methane production|WO2014083433A2|2012-12-02|2014-06-05|Agricam Ab|Systems and methods for predicting the outcome of a state of a subject|
    WO2014201039A2|2013-06-11|2014-12-18|Horse Sense Shoes, Llc|Bovine rumination and estrus prediction systemand method|
    WO2014210176A2|2013-06-25|2014-12-31|The General Hospital Corporation|High-resolution thermal imaging system, apparatus, method and computer accessible medium|
    SG10201501052XA|2014-02-11|2015-09-29|Agency Science Tech & Res|Method And System For Monitoring Activity Of An Animal|
    KR101471906B1|2014-03-28|2014-12-11|차병권|System, apparatus and method for sensing estrus of animal|
    WO2015187984A1|2014-06-05|2015-12-10|Trax Right, LLC|Apparatus and method to identify morbid animals|
    US9961883B2|2014-06-16|2018-05-08|Allan Schaefer|Rapid and automatic determination of metabolic efficiency in livestock|
    US9955672B2|2014-06-16|2018-05-01|Nigel Cook|Infrared thermography and behaviour information for identification of biologically important states in animals|
    US10195008B2|2015-03-03|2019-02-05|Farrowtech Aps|System, device and method for observing piglet birth|
    EP3342280A4|2015-08-25|2019-04-17|Sony Corporation|Livestock registration system and livestock registration method|
    JP6677473B2|2015-09-24|2020-04-08|株式会社Ｃｓソリューション|Body temperature measurement system for non-contact measurement of target animal body temperature|
    JP6644311B2|2015-11-06|2020-02-12|国立研究開発法人農業・食品産業技術総合研究機構|Livestock condition monitoring device, information processing device, livestock condition monitoring method, and livestock condition monitoring program|
    CN105830936B|2016-06-08|2021-11-16|江苏电子信息职业学院|Full-intelligent piglet infrared heating control system|
    SE541890C2|2017-03-24|2020-01-02|Bmp Innovation Ab|Systems and methods for identifying individual animals in a group of animals|
    IT201700069751A1|2017-06-22|2018-12-22|Luca Agostini|SYSTEM FOR DETECTION OF SPECIFIC CONDITIONS OF BREEDING ANIMALS|
    PL234432B1|2018-02-28|2020-02-28|Smart Soft Solutions Spolka Z Ograniczona Odpowiedzialnoscia|Device, method and the system for animal temperature monitoring|
    US11166437B2|2019-03-21|2021-11-09|International Business Machines Corporation|Overhead camera system to gauge livestock development|
    KR102319823B1|2019-09-11|2021-11-01|주)엠트리센|System and Method for Monitoring Activity and Forecasting Healthcare of Livestock|
    WO2021207853A1|2020-04-17|2021-10-21|The Governors Of The University Of Alberta|Apparatus and methodologies for improved detection of important biological states in animals|
    CN111972307B|2020-07-20|2022-03-01|武汉工程大学|Animal food intake monitoring method and system and intelligent ear tag|
    法律状态:
    2018-02-20| B06F| Objections, documents and/or translations needed after an examination request according [chapter 6.6 patent gazette]|
    2018-05-22| B11E| Dismissal acc. art. 34 of ipl - requirements for examination incomplete|
    2018-08-07| B12C| Appeal: appeal against dismissal|
    2019-05-28| B15N| Others concerning applications: notification of judicial decision|Free format text: VARA: 25A VARA FEDERAL DO RIO DE JANEIROPROCESSO N.O 5022017-09.2019.4.02.5101) - NUP: 00408.027367/2019-14IMPETRANTE: KASZNAR LEONARDOS ADVOGADOSIMPETRADO: PRESIDENTE DO INSTITUTO NACIONAL DA PROPRIEDADE INDUSTRIAL - INPI?ANTE O EXPOSTO, DENEGO O MANDADO DE SEGURANCA E JULGO EXTINTO O PROCESSO SEM RESOLUCAO DO MERITO, COM FULCRO NO ARTIGO 6O, 5O, DA LEI NO 12.016/2009 C/C ARTIGO 485, VI DO CODIGO DE PROCESSO CIVIL.? |
    2020-07-07| B06U| Preliminary requirement: requests with searches performed by other patent offices: procedure suspended [chapter 6.21 patent gazette]|
    2020-12-08| B07A| Technical examination (opinion): publication of technical examination (opinion) [chapter 7.1 patent gazette]|
    2021-04-06| B09A| Decision: intention to grant [chapter 9.1 patent gazette]|
    2021-06-15| B16A| Patent or certificate of addition of invention granted|Free format text: PRAZO DE VALIDADE: 20 (VINTE) ANOS CONTADOS A PARTIR DE 28/03/2012, OBSERVADAS AS CONDICOES LEGAIS. |
    优先权:
    申请号 | 申请日 | 专利标题
    US201161468492P| true| 2011-03-28|2011-03-28|
    US61/468,492|2011-03-28|
    PCT/CA2012/000279|WO2012129657A1|2011-03-28|2012-03-28|Apparatus and method for using infrared thermography and behaviour information for identification of biologically important states in animals|
    [返回顶部]