WO2019119547A1 - 奶牛分类方法和装置 - Google Patents

奶牛分类方法和装置 Download PDF

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Publication number
WO2019119547A1
WO2019119547A1 PCT/CN2018/072000 CN2018072000W WO2019119547A1 WO 2019119547 A1 WO2019119547 A1 WO 2019119547A1 CN 2018072000 W CN2018072000 W CN 2018072000W WO 2019119547 A1 WO2019119547 A1 WO 2019119547A1
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Prior art keywords
cow
weight
cows
dairy
daily
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PCT/CN2018/072000
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English (en)
French (fr)
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王忠山
周毕兴
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深圳市沃特沃德股份有限公司
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Publication of WO2019119547A1 publication Critical patent/WO2019119547A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
    • A—HUMAN NECESSITIES
    • A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01K—ANIMAL HUSBANDRY; AVICULTURE; APICULTURE; PISCICULTURE; FISHING; REARING OR BREEDING ANIMALS, NOT OTHERWISE PROVIDED FOR; NEW BREEDS OF ANIMALS
    • A01K29/00—Other apparatus for animal husbandry
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/02—Agriculture; Fishing; Forestry; Mining

Definitions

  • the invention relates to the technical field of dairy farming management, in particular to a dairy cattle classification method and device.
  • Milk is known as "the closest perfect food” because of its nutrient-rich, easy to digest and absorb, good quality and low price, convenient to eat, etc., and its related industries have gradually become a sunrise industry.
  • the level of development of the dairy industry has become an important symbol of the development level of modern agriculture, especially animal husbandry.
  • the dairy farming industry has gradually moved from traditional decentralized farming to modern scale. Chemical farming transformation.
  • the milk yield of single-headed cows is directly related to the economic benefits of the farm. Therefore, in large-scale farming, it is necessary to classify cows, select cows with high milk yield, eliminate cows with low milk yield, and eliminate cows. Updated to improve the economics of dairy farming. However, in traditional dairy farming, the elimination of dairy cows is mainly based on the manual selection of the breeders. There is no quantitative indicator, which is not only time-consuming and laborious, but also easy to cause selection errors.
  • the main object of the present invention is to provide a dairy cow classification method and device, which aims to realize the classification of dairy cows by using quantitative indicators, so as to more scientifically and accurately measure the economic benefits of dairy cows.
  • an embodiment of the present invention provides a dairy cow classification method, and the method includes the following steps:
  • the cows are classified according to the daily body weight of the unit body weight.
  • the step of classifying the cow according to the daily body weight of the unit body weight comprises:
  • the cow's unit weight per day milk yield is less than or equal to the first threshold, the cow is classified as a low-yield cow.
  • the step of classifying the cow according to the daily body weight of the unit body weight comprises:
  • the cows are sorted out in a preset proportion and the cows are classified as low-yielding cows.
  • the method further comprises:
  • the low-yield cow is further classified as a beef cattle when the weight gain rate is greater than or equal to a second threshold.
  • the step of determining whether the weight growth rate is greater than or equal to the second threshold further comprises: when the weight growth rate is less than the second threshold, further classifying the low-yield cow as a pre-empted cow Or eliminate cows.
  • the first threshold is 0.05-0.1.
  • the preset ratio is 15%-25%.
  • the step of obtaining the daily weight and milk yield of the cow comprises:
  • Receiving the weight and identity information of the cows sent by the weight measuring device receiving the milk yield and identity information of the cows sent by the milking device, and counting the total milk yield of the same cow in one day;
  • the daily weight and milk yield of each cow are recorded based on the identity information.
  • the identity information of the cow is encoded information stored in an electronic tag, and the electronic tag is disposed on the cow.
  • the electronic tag is disposed on a leg and/or a head of the cow.
  • the embodiment of the invention simultaneously proposes a cow classification device, the device comprising:
  • the statistical module is set to count the daily milk yield per unit weight of each cow in the same milking cycle
  • the classification module is configured to classify the cows according to the daily milk yield per unit weight.
  • the classification module includes:
  • a first determining unit configured to determine whether the milk weight per unit body weight of the cow is less than or equal to a first threshold
  • the first categorizing unit is configured to classify the cow as a low-yield cow when the daily body weight of the cow's body weight is less than or equal to a first threshold.
  • the classification module includes:
  • a sorting unit that sorts the cows in descending order of daily milk yield per unit weight
  • the second categorizing unit is configured to select cows that are arranged at a later preset ratio and classify the cows as low-yielding cows.
  • the classification module further includes:
  • a statistical unit configured to count the growth rate of the low-yield cow in the most recent period of time
  • a second determining unit configured to determine whether the weight growth rate is greater than or equal to a second threshold
  • the third categorizing unit is configured to further classify the low-yield cow as a beef cattle when the weight growth rate is greater than or equal to a second threshold.
  • the classification module further includes a fourth categorization unit, where the fourth categorization unit is configured to further classify the low-yield cow as a pre-emption when the weight growth rate is less than a second threshold Cows or cows are eliminated.
  • the obtaining module includes:
  • a first obtaining unit configured to receive the weight and identity information of the cow sent by the weight measuring device
  • a second obtaining unit configured to receive the milk yield and identity information of the cows sent by the milking device, and count the total milk yield of the same cow in one day;
  • the recording unit is configured to record the daily weight and milk yield of each cow according to the identity information.
  • Embodiments of the present invention also provide a computer device including a memory, a processor, and at least one application stored in the memory and configured to be executed by the processor, the application being configured to be used for Perform the aforementioned cow classification method.
  • a cow classification method is adopted, and the daily weight and milk yield of the cow are obtained, and the daily milk yield per unit weight of each cow in the same milking cycle is counted, and finally the milk is produced according to the unit weight of the cow.
  • the classification of dairy cows has enabled the use of quantitative indicators to classify cows, which is both efficient and accurate. Because the quantitative index of daily milk yield per unit weight fully takes into account the difference in body weight of different cows, it can accurately reflect the milk production capacity of dairy cows, so that the economic benefits of dairy cows can be measured more scientifically, accurately and efficiently, and then accurately eliminated. Cows with lower economic benefits will help maximize the economic benefits of the farm.
  • 1 is a flow chart of an embodiment of a dairy cow classification method of the present invention
  • FIG. 2 is a block diagram showing an example of a system for implementing the cow classification method of the present invention
  • Figure 3 is a block diagram showing an embodiment of a dairy cow sorting apparatus of the present invention.
  • FIG. 4 is a block diagram of the acquisition module of FIG. 3;
  • FIG. 5 is a block diagram of the classification module of Figure 3;
  • FIG. 6 is another block diagram of the classification module of FIG. 3;
  • Figure 7 is another block diagram of the classification module of Figure 3;
  • FIG. 8 is a block diagram of still another module of the classification module of FIG.
  • terminal and terminal device used herein include both a wireless signal receiver device, a device having only a wireless signal receiver without a transmitting capability, and a receiving and transmitting hardware.
  • Such devices may include cellular or other communication devices having a single line display or a multi-line display or a cellular or other communication device without a multi-line display; PCS (Personal Communications Service), which may combine voice, data Processing, fax, and/or data communication capabilities; PDA (Personal Digital Assistant), which can include radio frequency receivers, pagers, Internet/Intranet access, web browsers, notepads, calendars, and/or GPS (Global Positioning System (Global Positioning System) receiver; conventional laptop and/or palmtop computer or other device having a conventional laptop and/or palmtop computer or other device that includes and/or includes a radio frequency receiver.
  • PCS Personal Communications Service
  • PDA Personal Digital Assistant
  • terminal may be portable, transportable, installed in a vehicle (aviation, sea and/or land), or adapted and/or configured to operate locally, and/or Run in any other location on the Earth and/or space in a distributed form.
  • the "terminal” and “terminal device” used herein may also be a communication terminal, an internet terminal, a music/video playing terminal, and may be, for example, a PDA, a MID (Mobile Internet Device), and/or have a music/video playback.
  • Functional mobile phones can also be smart TVs, set-top boxes and other devices.
  • the server used herein includes, but is not limited to, a computer, a network host, a single network server, a plurality of network server sets, or a cloud composed of a plurality of servers.
  • the cloud is composed of a large number of computers or network servers based on Cloud Computing, which is a kind of distributed computing, a super virtual computer composed of a group of loosely coupled computers.
  • communication can be implemented by any communication means between the server, the terminal device and the WNS server, including but not limited to, mobile communication based on 3GPP, LTE, WIMAX, and computer network communication based on TCP/IP and UDP protocols. And short-range wireless transmission based on Bluetooth and infrared transmission standards.
  • the cow classification method of the embodiment of the invention is mainly applied to a computer device, and the computer device mainly refers to a server, and of course, may also be a terminal device such as a mobile phone, a tablet, a personal computer or the like.
  • the server obtains the daily weight and milk yield of each cow within a certain period of time (such as one year, several months, etc.). It should be understood that the daily weight and milk yield of the cows are not limited to the daily weight and milk production of the cows, or the day of the cows may be obtained one day or at least two days apart. Weight and milk production.
  • an example of a system for implementing the dairy cow classification method of the present invention includes a server, a weight measuring device (such as a scale), and a milking device, and the weight measuring device and the milking device are wired or wirelessly.
  • a weight measuring device such as a scale
  • a milking device such as a milking device
  • the weight measuring device and the milking device are wired or wirelessly.
  • WIFI/BT/2G/3G/4G/5G/EMTC/NB-IoT, etc. establish a communication connection with the server.
  • the server receives the weight and identity information of the cow sent by the weight measuring device. When a cow sends at least two weights a day, the average is taken as the weight of the day; and the milk yield and identity of the cow sent by the milking device are received.
  • the server then records the daily weight and milk yield of each cow based on the identity information of the cow.
  • electronic labels can be placed on the cows, such as sticking the electronic labels on the legs of the cows (such as the ankles, hooves, etc.) and/or the heads (such as cattle ears, horns, etc.), the identity information of the cows. That is, the encoded information stored in the electronic tag.
  • the electronic tag also known as the RFID (Radio Frequency Identification) tag, is preferably a passive RFID tag, which is required to be waterproof, corrosion resistant, and not easily damaged.
  • the chip inside the electronic tag preferably adopts an ultra-high frequency segment, and internally stores information representing the unique identity of the cow (such as enterprise code/national livestock code, etc.) for establishing an individual electronic breeding file of the cow.
  • the electronic label is preferably molded with a high-grade material to make the product waterproof, anti-fouling, and resistant to long-term outdoor use, and the product design life can reach more than 5 years.
  • a reader is installed on each of the weight measuring device and the milking device.
  • the weight measuring device can be installed in the cow's must.
  • the weight measuring device detects the electronic tag on the cow through the reader, and reads the encoded information in the electronic tag as the identity information of the cow.
  • the cow's weight is measured, and the average value can be measured continuously for several times, and the identity information and weight of the cow are sent to the server.
  • the milking device detects the electronic tag on the cow through the reader, reads the coded information in the electronic tag as the identity information of the cow, and detects the milk yield of the cow through the flow sensor. When the milking is over, send the identity information and milk yield of the cow to the server.
  • the weight measuring device and/or the milking device can also be arranged separately from the respective readers, in which case the reader needs to establish a communication connection with the server by wired or wireless communication.
  • the weight measuring device needs to establish a communication connection with the reader through wired or wireless communication.
  • the reader reads the encoded information of the electronic tag as the identity information of the cow and sends it to the server, that is, the server receives the identity information of the cow and the milking device respectively sent by the reader.
  • the measured cow's weight and milk yield and the cow's identity information may also be manually entered into the server by the user, and the server records the daily weight and milk yield of each cow based on the input information.
  • the user manually inputs the measured cow's weight and milk yield and the identity information of the cow into the terminal device, and the terminal device sends the input information to the server, and the server records the daily weight of each cow according to the information sent by the terminal device. Milk production.
  • Cows generally go through three stages within a year, namely the milk-stopping period, the peak period and the milking period, and the peak period and the light milk period are the milking cycles.
  • the milking period is generally about 90 days before the cows squat, during which no milk is produced at all.
  • the peak period is generally about 3 months after the cows are squatting. During this period, the milk yield of a cow is generally more than 25 kg a day, and a better cow can reach 40 kg.
  • the time outside the milking period and the peak period is the light milk period, during which a cow's milk production is generally between 5 kg and 20 kg per day.
  • the server counts the daily milk yield per unit body weight of each cow in the same milking period (such as peak period or light milk period).
  • the daily milk yield per unit weight introduced in the embodiment of the invention takes into account the difference in body weight of different cows, and can more accurately reflect the milk production capacity of the cow, thereby better measuring the economic benefit of the cow.
  • the server calculates the daily milk yield per unit of milk for a period of time during the whole milking period or during the milking period (using the milk yield of the day divided by the weight of the day), and then obtaining The average of the calculated milk yields per unit weight is used as the daily milk yield per unit of body weight of the cow during a certain milking cycle.
  • the server calculates the average of the body weight and the average daily milk yield of the cow during the whole milking period or the milking period, and then divides the average of the daily milk yield by the average of the body weight.
  • the quotient is the daily milk yield per unit of body weight of the cow during a milking cycle.
  • the cows are classified according to the daily milk yield per unit body weight of the cows.
  • the server directly compares the milk yield per unit body weight of each cow with a first threshold value, and determines whether the daily body weight of the unit weight is less than or equal to the first threshold.
  • the cow's unit weight per day milk yield is less than or equal to the first threshold, the cow is classified as a low-yield cow.
  • the cow's unit weight per day milk yield is greater than the first threshold, the cow is classified as a high-yield milk cow.
  • the size of the first threshold may be set according to actual needs. For example, when the milking period is the light milk period, the first threshold may be set between 0.05 and 0.1, preferably set to 0.08; when the milking period is the peak period , the first threshold can be set higher than the light milk period.
  • the server first sorts the cows according to the order of the daily milk yield per unit weight, and then selects the cows that are ranked at a predetermined ratio, and classifies them as low-yielding cows, and the rest. Classified as a high-yield milk cow, this method is equivalent to the last elimination system.
  • the preset ratio can be set according to actual needs, and can be set between 15% and 25%. For example, the cows ranked in the back 20% are classified as low-yield cows. For example, suppose there are 100 cows, and the 20 (100*20%) head cows (ie, cows ranked 81-100) that are ranked later are classified as low-yielding cows.
  • cows with low milk yield can be further classified.
  • the server counts the weight growth rate of each low-yield cow in the most recent period of time, and compares the weight growth rate and the second threshold to determine whether the weight growth rate is greater than or equal to the second threshold; when the weight of the low-yield cow is When the growth rate is greater than or equal to the second threshold, it indicates that the weight growth rate is relatively high.
  • the milk yield is low, but the body is healthy, the meat production is relatively high, and there is still certain economic benefit. Therefore, the low-yield cow is classified as Beef cattle.
  • the size of the second threshold can be set according to actual needs.
  • the server can directly classify it as a low-cost cow that is eliminated, and directly eliminate it. .
  • the server can also classify it as a pre-empted cow, and screen it out to improve the feed for a period of time before determining whether the unit weight and daily body weight and body weight growth rate are up to standard, when still not up to standard (such as unit If the daily milk yield is less than or equal to the first threshold, the ranking is within the preset ratio or the weight growth rate is less than the second threshold, then it is classified as a cow with low economic efficiency and eliminated.
  • the server can also directly eliminate low-yield cows as cows.
  • the dairy cow classification method obtains the daily body weight and the milk yield of the cow, and counts the daily milk yield per unit weight of each cow in the same milking cycle, and finally performs the cow milk according to the daily milk yield per unit body weight of the cow.
  • Classification the use of quantitative indicators to classify cows, both efficient and accurate. Because the quantitative index of daily milk yield per unit weight fully takes into account the difference in body weight of different cows, it can accurately reflect the milk production capacity of dairy cows, so that the economic benefits of dairy cows can be measured more scientifically, accurately and efficiently, and then accurately eliminated. Cows with lower economic benefits will help maximize the economic benefits of the farm.
  • the device includes an acquisition module 10, a statistics module 20, and a classification module 30, wherein: the acquisition module 10 is configured to acquire the daily weight and milk yield of the cow; The statistics module 20 is configured to count the daily milk yield per unit weight of each cow in the same milking cycle; the classification module 30 is configured to classify the cows according to the daily milk yield per unit weight of the milk.
  • the acquisition module 10 obtains the daily weight and milk yield of each cow for a period of time (eg, one year, several months, etc.). It should be understood that the daily weight and milk yield of the cows are not limited to the daily weight and milk production of the cows, or the day of the cows may be obtained one day or at least two days apart. Weight and milk production.
  • the obtaining module 10 includes a first obtaining unit 11, a second obtaining unit 12, and a recording unit 13, wherein: the first obtaining unit 11 is configured to receive the weight of the cow sent by the weight measuring device and Identity information, when a cow sends at least two weights a day, the average is taken as the weight of the day; the second obtaining unit 12 is configured to receive the milk yield and identity information of the cows sent by the milking device, and count The total milk production of the same cow in one day, such as the sum of at least two milk yields sent by one cow a day as the milk yield of the day; the recording unit 13 is set to record each cow daily according to the identity information of the cows. Weight and milk production.
  • electronic labels can be placed on the cows, such as sticking the electronic labels on the legs of the cows (such as the ankles, hooves, etc.) and/or the heads (such as cattle ears, horns, etc.), the identity information of the cows. That is, the encoded information stored in the electronic tag.
  • the electronic tag also known as the RFID (Radio Frequency Identification) tag, is preferably a passive RFID tag, which is required to be waterproof, corrosion resistant, and not easily damaged.
  • the chip inside the electronic tag preferably adopts an ultra-high frequency segment, and internally stores information representing the unique identity of the cow (such as enterprise code/national livestock code, etc.) for establishing an individual electronic breeding file of the cow.
  • the electronic label is preferably molded with a high-grade material to make the product waterproof, anti-fouling, and resistant to long-term outdoor use, and the product design life can reach more than 5 years.
  • a reader is installed on each of the weight measuring device and the milking device.
  • the weight measuring device can be installed in the cow's must.
  • the weight measuring device detects the electronic tag on the cow through the reader, and reads the encoded information in the electronic tag as the identity information of the cow.
  • the weight of the cow is measured, and the average value can be measured continuously for a plurality of times, and the identity information and the body weight of the cow are sent to the first acquisition unit 11.
  • the milking device detects the electronic tag on the cow through the reader, reads the coded information in the electronic tag as the identity information of the cow, and detects the milk yield of the cow through the flow sensor.
  • the identity information and the milk yield of the cow are sent to the second obtaining unit 12.
  • the weight measuring device and/or the milking device can also be arranged separately from the respective readers, in which case the reader needs to establish a communication connection with the server by wired or wireless communication.
  • the weight measuring device needs to establish a communication connection with the reader through wired or wireless communication.
  • the encoded information of the electronic tag is read as the identity information of the cow and sent.
  • the first acquisition unit 11 is simultaneously activated or notified to measure the weight of the cow, that is, the first acquisition unit 11 receives the identity information of the cow sent by the reader and the weight of the cow sent by the weight measuring device, respectively.
  • the reader When the cow is milking beside the milking device, the reader reads the coded information of the electronic tag as the identity information of the cow and sends it to the second obtaining unit 12, that is, the second obtaining unit 12 receives the message sent by the reader respectively.
  • the measured cow's weight and milk yield and the cow's identity information may also be manually entered into the server by the user, and the acquisition module 10 records the daily weight and milk yield of each cow according to the input information.
  • the user manually inputs the measured weight and milk yield of the cow and the identity information of the cow into the terminal device, and the terminal device sends the input information to the acquisition module 10, and the acquisition module 10 records each cow according to the information sent by the terminal device.
  • Day weight and milk production may also be manually entered into the server by the user, and the acquisition module 10 records the daily weight and milk yield of each cow according to the input information.
  • Cows generally go through three stages within a year, namely the milk-stopping period, the peak period and the milking period, and the peak period and the light milk period are the milking cycles.
  • the milking period is generally about 90 days before the cows squat, during which no milk is produced at all.
  • the peak period is generally about 3 months after the cows are squatting. During this period, the milk yield of a cow is generally more than 25 kg a day, and a better cow can reach 40 kg.
  • the time outside the milking period and the peak period is the light milk period, during which a cow's milk production is generally between 5 kg and 20 kg per day.
  • the statistical module 20 counts the daily milk yield per unit of body weight of each cow in the same milking cycle (eg, peak or light milk period). Compared with the daily milk yield, the daily milk yield per unit weight introduced in the embodiment of the present invention takes into account the difference in body weight of each cow, and can more accurately reflect the milk production capacity of the cow, thereby better measuring the economic benefit of the cow. .
  • the statistic module 20 calculates the daily milk yield per unit of milk for a period of time during the whole milking period or the milking period (using the milk yield of the day divided by the weight of the day), and then The average value of the calculated milk yield per unit weight is obtained, and the average value is taken as the daily milk yield per unit body weight of the cow in a certain milking cycle.
  • the statistic module 20 calculates the average of the body weight and the average daily milk yield of the cow during the whole milking period or the milking period, and then divides the average of the daily milk yield by the average of the body weight.
  • the quotient obtained from the value is the daily milk yield per unit of body weight of the cow during a certain milking cycle.
  • the classification module 30 classifies the cows according to the daily milk yield per unit body weight of the cows.
  • the classification module 30 includes a first determining unit 31 and a first categorizing unit 32, as shown in FIG. 5, wherein: the first determining unit 31 is configured to compare the daily milk yield per unit cow and the first The size of the threshold is determined whether the daily milk yield per unit body weight of the cow is less than or equal to the first threshold; the first categorizing unit 32 is configured to classify the cow as when the daily milk yield per unit body weight of the cow is less than or equal to the first threshold Low-yield milk cows. Further, when the daily milk yield per unit body weight of the cow is greater than the first threshold, the first categorizing unit 32 classifies the cow as a high-yield milk cow.
  • the size of the first threshold may be set according to actual needs. For example, when the milking period is the light milk period, the first threshold may be set between 0.05 and 0.1, preferably set to 0.08; when the milking period is the peak period , the first threshold can be set higher than the light milk period.
  • the classification module 30 includes a sorting unit 33 and a second categorizing unit 34, as shown in FIG. 6, wherein: the sorting unit 33 sorts the cows in descending order of milk yield per unit weight; The second categorizing unit 34 is arranged to select the cows which are arranged at a preset ratio, and classify them as low-yield milk cows, and the rest are classified as high-yield milk cows, which is equivalent to the last elimination system.
  • the preset ratio can be set according to actual needs, and can be set between 15% and 25%.
  • the cows ranked in the back 20% are classified as low-yield cows.
  • the second categorizing unit 34 classifies the 20 (100*20%) head cows (ie, cows ranked 81-100) in the back as low-yielding cows. .
  • a statistical unit 35, a second determining unit 36, and a third categorizing unit 37 are further included, wherein: the statistic unit 35 is configured to count the low-production cows in the latest period of time.
  • the second weight determining unit 36 is configured to compare the weight growth rate and the second threshold to determine whether the weight growth rate is greater than or equal to the second threshold; and the third categorizing unit 37 is configured to be a low-yield cow
  • the weight gain rate is greater than or equal to the second threshold, it indicates that the weight growth rate is relatively high.
  • the class is beef cattle.
  • the size of the second threshold can be set according to actual needs.
  • the classification module 30 may further include a fourth categorization unit 38 configured to further classify the low-yield cows when the weight growth rate of the low-yield cows is less than a second threshold To pre-empt cows or eliminate cows.
  • the unit weight and daily body weight and body weight growth rate are up to standard, when the standard is still not up to standard (such as the unit weight daily milk production is less than or equal to If the first threshold, the ranking is within a preset ratio range, or the weight growth rate is less than the second threshold, it is classified as a low-economically eliminated cow.
  • the classification module 30 can also directly eliminate low-yield dairy cows as dairy cows.
  • the cow sorting device of the embodiment of the invention obtains the daily body weight and the milk yield of the cow, and counts the daily milk yield per unit body weight of each cow in the same milking cycle, and finally carries out the cow milk according to the daily milk yield per unit body weight of the cow.
  • Classification the use of quantitative indicators to classify cows, both efficient and accurate. Since the quantitative index of the daily milk yield per unit weight fully takes into account the difference in body weight of different cows, it can accurately reflect the milk production capacity of the cows, so that the economic benefits of the cows can be more scientifically and accurately measured, and the economy can be eliminated accurately. Cows with lower benefits are conducive to maximizing the economic benefits of the farm.
  • the invention also proposes a computer device comprising a memory, a processor and at least one application stored in the memory and configured to be executed by the processor, the application being configured to perform a cow classification method.
  • the dairy cow classification method comprises the steps of: obtaining the daily weight and milk yield of the cow; calculating the daily milk yield per unit weight of each cow in the same milking cycle; and classifying the cow according to the daily milk yield per unit body weight of the cow.
  • the cow classification method described in this embodiment is the cow classification method according to the above embodiment of the present invention, and details are not described herein again.
  • the present invention includes apparatus that is directed to performing one or more of the operations described herein. These devices may be specially designed and manufactured for the required purposes, or may also include known devices in a general purpose computer. These devices have computer programs stored therein that are selectively activated or reconfigured.
  • Such computer programs may be stored in a device (eg, computer) readable medium or in any type of medium suitable for storing electronic instructions and coupled to a bus, respectively, including but not limited to any Types of disks (including floppy disks, hard disks, optical disks, CD-ROMs, and magneto-optical disks), ROM (Read-Only Memory), RAM (Random Access Memory), EPROM (Erasable Programmable Read-Only Memory) , EEPROM (Electrically Erasable Programmable Read-Only Memory), flash memory, magnetic card or light card.
  • a readable medium includes any medium that is stored or transmitted by a device (eg, a computer) in a readable form.
  • each block of the block diagrams and/or block diagrams and/or flow diagrams and combinations of blocks in the block diagrams and/or block diagrams and/or flow diagrams can be implemented by computer program instructions. .
  • these computer program instructions can be implemented by a general purpose computer, a professional computer, or a processor of other programmable data processing methods, such that the processor is executed by a computer or other programmable data processing method.
  • steps, measures, and solutions in the various operations, methods, and processes that have been discussed in the present invention may be alternated, changed, combined, or deleted. Further, other steps, measures, and schemes of the various operations, methods, and processes that have been discussed in the present invention may be alternated, modified, rearranged, decomposed, combined, or deleted. Further, the steps, measures, and solutions in the prior art having various operations, methods, and processes disclosed in the present invention may also be alternated, changed, rearranged, decomposed, combined, or deleted.

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Abstract

一种奶牛分类方法，包括以下步骤：获取奶牛每日的体重和产奶量，统计各个奶牛在同一产奶周期内的单位体重日产奶量，根据单位体重日产奶量对奶牛进行分类，实现了利用量化指标对奶牛进行分类。

Description

奶牛分类方法和装置 技术领域
本发明涉及奶牛养殖管理技术领域，特别是涉及到一种奶牛分类方法和装置。
背景技术
牛奶以其营养丰富、容易消化吸收、物美价廉、食用方便等优点而被誉为“最接近完美的食品”，其相关产业也逐渐成为朝阳产业。随着世界畜牧业的快速发展，乳业发展水平的高低已成为现代农业特别是畜牧业发展水平的重要标志，同时伴随着科技水平的不断提高，奶牛养殖业逐渐从传统的分散养殖向现代化的规模化养殖转变。
单头奶牛的产奶量直接关系到养殖场的经济效益，因此在规模化养殖中，需要对奶牛进行分类，挑选出产奶量高的奶牛，淘汰掉产奶量低的奶牛，实现奶牛的淘汰更新，从而提高奶牛养殖的经济效益。但传统的奶牛养殖中，奶牛的分类淘汰主要依靠饲养人员根据经验进行人工挑选，没有一个量化的指标，不仅费时费力，还容易造成挑选失误。
由此可见，传统的奶牛分类方法无法科学、准确的衡量奶牛的经济效益，不利于实现养殖场的经济效益最大化。
技术问题
本发明的主要目的为提供一种奶牛分类方法和装置，旨在实现利用量化指标对奶牛进行分类，以更加科学、准确的衡量奶牛的经济效益。
技术解决方案
为达以上目的，本发明实施例提出一种奶牛分类方法，所述方法包括以下步骤：
获取奶牛每日的体重和产奶量；
统计各个奶牛在同一产奶周期内的单位体重日产奶量；
根据所述单位体重日产奶量对所述奶牛进行分类。
可选地，所述根据所述单位体重日产奶量对所述奶牛进行分类的步骤包括：
判断所述奶牛的单位体重日产奶量是否小于或等于第一阈值；
当所述奶牛的单位体重日产奶量小于或等于第一阈值时，将所述奶牛归类为低产奶量奶牛。
可选地，所述根据所述单位体重日产奶量对所述奶牛进行分类的步骤包括：
根据单位体重日产奶量从高到低的顺序对所述奶牛进行排序；
挑选出排在后面预设比例的奶牛，将所述奶牛归类为低产奶量奶牛。
可选地，所述将所述奶牛归类为低产量奶牛的步骤之后还包括：
统计所述低产量奶牛最近一段时间内的体重增长率；
判断所述体重增长率是否大于或等于第二阈值；
当所述体重增长率大于或等于第二阈值时，将所述低产量奶牛进一步归类为肉牛。
可选地，所述判断所述体重增长率是否大于或等于第二阈值的步骤之后还包括：当所述体重增长率小于第二阈值时，将所述低产量奶牛进一步归类为预淘汰奶牛或淘汰奶牛。
可选地，所述第一阈值为0.05-0.1。
可选地，所述预设比例为15％-25％。
可选地，所述获取奶牛每日的体重和产奶量的步骤包括：
接收体重测量设备发送的奶牛的体重和身份信息；接收挤奶设备发送的奶牛的产奶量和身份信息，并统计同一个奶牛一日内总的产奶量；
根据所述身份信息记录各个奶牛每日的体重和产奶量。
可选地，所述奶牛的身份信息为存储于电子标签内的编码信息，所述电子标签设置于所述奶牛身上。
可选地，所述电子标签设置于所述奶牛的腿部和/或头部。
本发明实施例同时提出一种奶牛分类装置，所述装置包括：
获取模块，设置为获取奶牛每日的体重和产奶量；
统计模块，设置为统计各个奶牛在同一产奶周期内的单位体重日产奶量；
分类模块，设置为根据所述单位体重日产奶量对所述奶牛进行分类。
可选地，所述分类模块包括：
第一判断单元，设置为判断所述奶牛的单位体重日产奶量是否小于或等于第一阈值；
第一归类单元，设置为当所述奶牛的单位体重日产奶量小于或等于第一阈值时，将所述奶牛归类为低产奶量奶牛。
可选地，所述分类模块包括：
排序单元，用根据单位体重日产奶量从高到低的顺序对所述奶牛进行排序；
第二归类单元，设置为挑选出排在后面预设比例的奶牛，将所述奶牛归类为低产奶量奶牛。
可选地，所述分类模块还包括：
统计单元，设置为统计所述低产量奶牛最近一段时间内的体重增长率；
第二判断单元，设置为判断所述体重增长率是否大于或等于第二阈值；
第三归类单元，设置为当所述体重增长率大于或等于第二阈值时，将所述低产量奶牛进一步归类为肉牛。
可选地，所述分类模块还包括第四归类单元，所述第四归类单元设置为：当所述体重增长率小于第二阈值时，将所述低产量奶牛进一步归类为预淘汰奶牛或淘汰奶牛。
可选地，所述获取模块包括：
第一获取单元，设置为接收体重测量设备发送的奶牛的体重和身份信息；
第二获取单元，设置为接收挤奶设备发送的奶牛的产奶量和身份 信息，并统计同一个奶牛一日内总的产奶量；
记录单元，设置为根据所述身份信息记录各个奶牛每日的体重和产奶量。
本发明实施例还提出一种计算机设备，其包括存储器、处理器和至少一个被存储在所述存储器中并被配置为由所述处理器执行的应用程序，所述应用程序被配置为用于执行前述奶牛分类方法。
有益效果
本发明实施例所提供的一种奶牛分类方法，通过获取奶牛每日的体重和产奶量，并统计各个奶牛在同一产奶周期内的单位体重日产奶量，最后根据奶牛的单位体重日产奶量对奶牛进行分类，实现了利用量化指标对奶牛进行分类，既高效又准确。由于单位体重日产奶量这一量化指标充分的考虑到了不同奶牛的体重差异，因此能够准确的体现奶牛的产奶能力，从而能够更加科学、准确、高效的衡量奶牛的经济效益，进而准确的淘汰掉经济效益较低的奶牛，有利于实现养殖场的经济效益最大化。
附图说明
图1是本发明的奶牛分类方法一实施例的流程图；
图2是实现本发明的奶牛分类方法的系统一实例的模块示意图；
图3是本发明的奶牛分类装置一实施例的模块示意图；
图4是图3中的获取模块的模块示意图；
图5是图3中的分类模块的模块示意图；
图6是图3中的分类模块的又一模块示意图；
图7是图3中的分类模块的又一模块示意图；
图8是图3中的分类模块的又一模块示意图。
本发明目的的实现、功能特点及优点将结合实施例，参照附图做进一步说明。
本发明的最佳实施方式
应当理解，此处所描述的具体实施例仅仅用以解释本发明，并不用于限定本发明。
下面详细描述本发明的实施例，所述实施例的示例在附图中示出，其中自始至终相同或类似的标号表示相同或类似的元件或具有相同或类似功能的元件。下面通过参考附图描述的实施例是示例性的，仅用于解释本发明，而不能解释为对本发明的限制。
本技术领域技术人员可以理解，除非特意声明，这里使用的单数形式“一”、“一个”、“所述”和“该”也可包括复数形式。应该进一步理解的是，本发明的说明书中使用的措辞“包括”是指存在所述特征、整数、步骤、操作、元件和/或组件，但是并不排除存在或添加一个或多个其他特征、整数、步骤、操作、元件、组件和/或它们的组。应该理解，当我们称元件被“连接”或“耦接”到另一元件时，它可以直接连接或耦接到其他元件，或者也可以存在中间元件。此外，这里使用的“连接”或“耦接”可以包括无线连接或无线耦接。这里使用的措辞“和/或”包括一个或更多个相关联的列出项的全部或任一单元和全部组合。
本技术领域技术人员可以理解，除非另外定义，这里使用的所有术语(包括技术术语和科学术语)，具有与本发明所属领域中的普通技术人员的一般理解相同的意义。还应该理解的是，诸如通用字典中定义的那些术语，应该被理解为具有与现有技术的上下文中的意义一致的意义，并且除非像这里一样被特定定义，否则不会用理想化或过于正式的含义来解释。
本技术领域技术人员可以理解，这里所使用的“终端”、“终端设备”既包括无线信号接收器的设备，其仅具备无发射能力的无线信号接收器的设备，又包括接收和发射硬件的设备，其具有能够在双向通信链路上，执行双向通信的接收和发射硬件的设备。这种设备可以包括：蜂窝或其他通信设备，其具有单线路显示器或多线路显示器或没有多线路显示器的蜂窝或其他通信设备；PCS(Personal Communications Service，个人通信系统)，其可以组合语音、数据处理、传真和/或数据通信能力；PDA(Personal Digital Assistant，个人 数字助理)，其可以包括射频接收器、寻呼机、互联网/内联网访问、网络浏览器、记事本、日历和/或GPS(Global Positioning System，全球定位系统)接收器；常规膝上型和/或掌上型计算机或其他设备，其具有和/或包括射频接收器的常规膝上型和/或掌上型计算机或其他设备。这里所使用的“终端”、“终端设备”可以是便携式、可运输、安装在交通工具(航空、海运和/或陆地)中的，或者适合于和/或配置为在本地运行，和/或以分布形式，运行在地球和/或空间的任何其他位置运行。这里所使用的“终端”、“终端设备”还可以是通信终端、上网终端、音乐/视频播放终端，例如可以是PDA、MID(Mobile Internet Device，移动互联网设备)和/或具有音乐/视频播放功能的移动电话，也可以是智能电视、机顶盒等设备。
本技术领域技术人员可以理解，这里所使用的服务器，其包括但不限于计算机、网络主机、单个网络服务器、多个网络服务器集或多个服务器构成的云。在此，云由基于云计算(Cloud Computing)的大量计算机或网络服务器构成，其中，云计算是分布式计算的一种，由一群松散耦合的计算机集组成的一个超级虚拟计算机。本发明的实施例中，服务器、终端设备与WNS服务器之间可通过任何通信方式实现通信，包括但不限于，基于3GPP、LTE、WIMAX的移动通信、基于TCP/IP、UDP协议的计算机网络通信以及基于蓝牙、红外传输标准的近距无线传输方式。
本发明实施例的奶牛分类方法，主要应用于计算机设备，所述计算机设备主要指服务器，当然也可以是手机、平板、个人电脑等终端设备。
参照图1，提出本发明的奶牛分类方法一实施例，所述方法包括以下步骤：
S11、获取奶牛每日的体重和产奶量。
本发明实施例中，服务器获取各个奶牛一段时间内(如一年、几个月内等)每日的体重和产奶量。应当理解，这里所述的获取奶牛每日的体重和产奶量，并非限定为必须连续每天都要获取一次奶牛当天的体重和产奶量，也可能是间隔一天或至少两天获取一次奶牛当天的 体重和产奶量。
如图2所示，为实现本发明的奶牛分类方法的系统一实例，该系统包括服务器、体重测量设备(如地磅秤)和挤奶设备，体重测量设备和挤奶设备通过有线或无线通信方式(如WIFI/BT/2G/3G/4G/5G/EMTC/NB-IoT等)与服务器建立通信连接。服务器接收体重测量设备发送的奶牛的体重和身份信息，当一个奶牛一天发送了至少两次体重时，则求取平均值作为当天的体重；同时接收挤奶设备发送的奶牛的产奶量和身份信息，并统计同一个奶牛一日内总的产奶量，如求取一个奶牛一天发送的至少两次产奶量之和作为当天的产奶量。然后，服务器根据奶牛的身份信息记录各个奶牛每日的体重和产奶量。
具体实施时，可以在奶牛身上设置电子标签，如将电子标签粘贴在奶牛的腿部(如脚踝、牛蹄上等)和/或头部(如牛耳朵、牛角上等)，奶牛的身份信息即为存储于电子标签内的编码信息。电子标签又称RFID(Radio Frequency Identification，射频识别)标签，优选无源RFID标签，要求此标签防水、防腐蚀、不易损坏脱落。电子标签内部的芯片优选采用超高频率段，内部存储了代表奶牛唯一身份的编码(如企业编码/国家牲畜编码等)信息，用于建立奶牛个体电子养殖档案。电子标签优选以高级材料塑封，以使产品防水、防污、耐受长期户外使用，产品设计使用寿命可以达到5年以上。
当有新的奶牛时，为新的奶牛分配编码，并写入电子标签的芯片，将电子标签粘贴于奶牛身上，将奶牛的编码与电子标签的芯片ID号在数据库中绑定，也可以通过修改功能，解除绑定关系。当由于电子标签遗失或漏读等因素引起无法识读，还可以支持人工输入或者修改电子标签的芯片ID号的功能。
同时，在体重测量设备和挤奶设备上各自安装阅读器。体重测量设备可以安装在奶牛的必经之地，当奶牛经过体重测量设备时，体重测量设备通过阅读器检测到奶牛身上的电子标签，则读取电子标签中的编码信息作为奶牛的身份信息，同时测量奶牛的体重，可以连续测量多次取平均值，并将奶牛的身份信息和体重发送给服务器。当奶牛 在挤奶设备旁边挤奶时，挤奶设备通过阅读器检测到奶牛身上的电子标签，则读取电子标签中的编码信息作为奶牛的身份信息，同时通过流量传感器检测奶牛的产奶量，当挤奶结束时，将奶牛的身份信息和产奶量发送给服务器。
可选地，体重测量设备和/或挤奶设备也可以与各自的阅读器分体设置，此时阅读器需通过有线或无线通信方式与服务器建立通信连接。体重测量设备需通过有线或无线通信方式与阅读器建立通信连接，当奶牛经过体重测量设备，阅读器检测到奶牛身上的电子标签时，则读取电子标签的编码信息作为奶牛的身份信息并发送给服务器，同时启动或通知体重测量设备测量奶牛的体重，即此时服务器分别接收到阅读器发送的奶牛的身份信息以及体重测量设备发送的奶牛的体重。当奶牛在挤奶设备旁边挤奶时，阅读器则读取电子标签的编码信息作为奶牛的身份信息并发送给服务器，即此时服务器分别接收到阅读器发送的奶牛的身份信息和挤奶设备发送的奶牛的产奶量。
在某些实施例中，也可以由用户将测量的奶牛的体重和产奶量以及奶牛的身份信息人工输入服务器，服务器则根据输入的信息记录各个奶牛每日的体重和产奶量。或者由用户将测量的奶牛的体重和产奶量以及奶牛的身份信息人工输入终端设备，终端设备再将输入的信息发送给服务器，服务器则根据终端设备发送的信息记录各个奶牛每日的体重和产奶量。
S12、统计各个奶牛在同一产奶周期内的单位体重日产奶量。
奶牛一年之内一般会经历三个阶段，即停奶期、高峰期和淡奶期，高峰期和淡奶期为产奶周期。停奶期一般在奶牛下崽前的90天左右，在此期间完全不产奶。高峰期一般在奶牛下崽后的3个月左右，在此期间，一头奶牛一天的产奶量一般在25公斤以上，好一点的奶牛能达到40公斤左右。停奶期和高峰期以外的时间则为淡奶期，在此期间，一头奶牛一天的产奶量一般在5公斤到20公斤之间。
本步骤S12中，服务器统计各个奶牛在同一产奶周期(如高峰期或淡奶期)内的单位体重日产奶量。相对于日产奶量，本发明实施例引入的单位体重日产奶量这一指标，考虑到了不同奶牛的体重差异， 能够更加准确的体现奶牛的产奶能力，进而更好的衡量奶牛的经济效益。
可选地，服务器分别计算出奶牛在整个产奶周期内或产奶周期的一段时间内每日的单位体重产奶量(利用当日的产奶量除以当日的体重得出)，然后求取计算出的多个单位体重产奶量的平均值，将平均值作为该奶牛在某个产奶周期内的单位体重日产奶量。
可选地，服务器分别计算出奶牛在整个产奶周期内或产奶周期的一段时间内体重的平均值和日产奶量的平均值，然后将日产奶量的平均值除以体重的平均值得到的商值，作为该奶牛在某个产奶周期内的单位体重日产奶量。
S13、根据奶牛的单位体重日产奶量对奶牛进行分类。
在某些实施例中，服务器直接比较每头奶牛的单位体重日产奶量与第一阈值的大小，判断单位体重日产奶量是否小于或等于第一阈值。当奶牛的单位体重日产奶量小于或等于第一阈值时，则将该奶牛归类为低产奶量奶牛。当奶牛的单位体重日产奶量大于第一阈值时，则将该奶牛归类为高产奶量奶牛。第一阈值的大小可以根据实际需要设定，如当产奶周期为淡奶期时，可以设定第一阈值在0.05-0.1之间，优选设定为0.08；当产奶周期为高峰期时，则可以将第一阈值设定得比淡奶期高一些。
在另一些实施例中，服务器先根据单位体重日产奶量从高到低的顺序对奶牛进行排序，再挑选出排在后面预设比例的奶牛，将其归类为低产奶量奶牛，其余的归类为高产奶量奶牛，这种方式相当于末位淘汰制。预设比例可以根据实际需要设定，可以设定在15％-25％之间，如将排在后面20％的奶牛归类为低产奶量奶牛。举例而言，假设有100头奶牛，则将排在后面的20(100*20％)头奶牛(即排列在第81-100位的奶牛)归类为低产奶量奶牛。
进一步地，还可以对低产奶量奶牛进行进一步分类。可选地，服务器统计每个低产量奶牛最近一段时间内的体重增长率，并比较体重增长率和第二阈值的大小，判断体重增长率是否大于或等于第二阈值；当低产量奶牛的体重增长率大于或等于第二阈值时，说明其体重增长 率比较高，虽然产奶量低，但身体健康，产肉量比较高，尚有一定的经济效益，故将该低产量奶牛归类为肉牛。第二阈值的大小可以根据实际需要设定。
当低产量奶牛的体重增长率小于第二阈值时(增长速度慢或负增长时)，说明其身体可能不太健康，服务器可以直接将其归类为经济效益低的淘汰奶牛，直接将其淘汰掉。可选地，服务器也可以将其归类为预淘汰奶牛，将其筛选出来通过改善饲料调养一段时间后再判断其单位体重日产奶量和体重增长率是否达标，当仍然不达标时(如单位体重日产奶量小于或等于第一阈值、排序排在后面预设比例范围内或体重增长率小于第二阈值)，则将其归类为经济效益低的淘汰奶牛予以淘汰。
在某些实施例中，服务器也可以直接将低产奶量奶牛当作淘汰奶牛予以淘汰。
本发明实施例的奶牛分类方法，通过获取奶牛每日的体重和产奶量，并统计各个奶牛在同一产奶周期内的单位体重日产奶量，最后根据奶牛的单位体重日产奶量对奶牛进行分类，实现了利用量化指标对奶牛进行分类，既高效又准确。由于单位体重日产奶量这一量化指标充分的考虑到了不同奶牛的体重差异，因此能够准确的体现奶牛的产奶能力，从而能够更加科学、准确、高效的衡量奶牛的经济效益，进而准确的淘汰掉经济效益较低的奶牛，有利于实现养殖场的经济效益最大化。
参照图3，提出本发明的奶牛分类装置一实施例，所述装置包括获取模块10、统计模块20和分类模块30，其中：获取模块10，设置为获取奶牛每日的体重和产奶量；统计模块20，设置为统计各个奶牛在同一产奶周期内的单位体重日产奶量；分类模块30，设置为根据牛奶的单位体重日产奶量对奶牛进行分类。
获取模块10获取各个奶牛一段时间内(如一年、几个月内等)每日的体重和产奶量。应当理解，这里所述的获取奶牛每日的体重和产奶量，并非限定为必须连续每天都要获取一次奶牛当天的体重和产奶量，也可能是间隔一天或至少两天获取一次奶牛当天的体重和产奶 量。
可选地，获取模块10如图4所示，包括第一获取单元11、第二获取单元12和记录单元13，其中：第一获取单元11，设置为接收体重测量设备发送的奶牛的体重和身份信息，当一个奶牛一天发送了至少两次体重时，则求取平均值作为当天的体重；第二获取单元12，设置为接收挤奶设备发送的奶牛的产奶量和身份信息，并统计同一个奶牛一日内总的产奶量，如求取一个奶牛一天发送的至少两次产奶量之和作为当天的产奶量；记录单元13，设置为根据奶牛的身份信息记录各个奶牛每日的体重和产奶量。
具体实施时，可以在奶牛身上设置电子标签，如将电子标签粘贴在奶牛的腿部(如脚踝、牛蹄上等)和/或头部(如牛耳朵、牛角上等)，奶牛的身份信息即为存储于电子标签内的编码信息。电子标签又称RFID(Radio Frequency Identification，射频识别)标签，优选无源RFID标签，要求此标签防水、防腐蚀、不易损坏脱落。电子标签内部的芯片优选采用超高频率段，内部存储了代表奶牛唯一身份的编码(如企业编码/国家牲畜编码等)信息，用于建立奶牛个体电子养殖档案。电子标签优选以高级材料塑封，以使产品防水、防污、耐受长期户外使用，产品设计使用寿命可以达到5年以上。
当有新的奶牛时，为新的奶牛分配编码，并写入电子标签的芯片，将电子标签粘贴于奶牛身上，将奶牛的编码与电子标签的芯片ID号在数据库中绑定，也可以通过修改功能，解除绑定关系。当由于电子标签遗失或漏读等因素引起无法识读，还可以支持人工输入或者修改电子标签的芯片ID号的功能。
同时，在体重测量设备和挤奶设备上各自安装阅读器。体重测量设备可以安装在奶牛的必经之地，当奶牛经过体重测量设备时，体重测量设备通过阅读器检测到奶牛身上的电子标签，则读取电子标签中的编码信息作为奶牛的身份信息，同时测量奶牛的体重，可以连续测量多次取平均值，并将奶牛的身份信息和体重发送给第一获取单元11。当奶牛在挤奶设备旁边挤奶时，挤奶设备通过阅读器检测到奶牛身上的电子标签，则读取电子标签中的编码信息作为奶牛的身份信息， 同时通过流量传感器检测奶牛的产奶量，当挤奶结束时，将奶牛的身份信息和产奶量发送给第二获取单元12。
可选地，体重测量设备和/或挤奶设备也可以与各自的阅读器分体设置，此时阅读器需通过有线或无线通信方式与服务器建立通信连接。体重测量设备需通过有线或无线通信方式与阅读器建立通信连接，当奶牛经过体重测量设备，阅读器检测到奶牛身上的电子标签时，则读取电子标签的编码信息作为奶牛的身份信息并发送给第一获取单元11，同时启动或通知体重测量设备测量奶牛的体重，即此时第一获取单元11分别接收到阅读器发送的奶牛的身份信息以及体重测量设备发送的奶牛的体重。当奶牛在挤奶设备旁边挤奶时，阅读器则读取电子标签的编码信息作为奶牛的身份信息并发送给第二获取单元12，即此时第二获取单元12分别接收到阅读器发送的奶牛的身份信息和挤奶设备发送的奶牛的产奶量。
在某些实施例中，也可以由用户将测量的奶牛的体重和产奶量以及奶牛的身份信息人工输入服务器，获取模块10则根据输入的信息记录各个奶牛每日的体重和产奶量。或者由用户将测量的奶牛的体重和产奶量以及奶牛的身份信息人工输入终端设备，终端设备再将输入的信息发送给获取模块10，获取模块10则根据终端设备发送的信息记录各个奶牛每日的体重和产奶量。
奶牛一年之内一般会经历三个阶段，即停奶期、高峰期和淡奶期，高峰期和淡奶期为产奶周期。停奶期一般在奶牛下崽前的90天左右，在此期间完全不产奶。高峰期一般在奶牛下崽后的3个月左右，在此期间，一头奶牛一天的产奶量一般在25公斤以上，好一点的奶牛能达到40公斤左右。停奶期和高峰期以外的时间则为淡奶期，在此期间，一头奶牛一天的产奶量一般在5公斤到20公斤之间。
统计模块20统计各个奶牛在同一产奶周期(如高峰期或淡奶期)内的单位体重日产奶量。相对于日产奶量，本发明实施例引入的单位体重日产奶量这一指标，考虑到了每头奶牛的体重差异，能够更加准确的体现奶牛的产奶能力，进而更好的衡量奶牛的经济效益。
可选地，统计模块20分别计算出奶牛在整个产奶周期内或产奶 周期的一段时间内每日的单位体重产奶量(利用当日的产奶量除以当日的体重得出)，然后求取计算出的多个单位体重产奶量的平均值，将平均值作为该奶牛在某个产奶周期内的单位体重日产奶量。
可选地，统计模块20分别计算出奶牛在整个产奶周期内或产奶周期的一段时间内体重的平均值和日产奶量的平均值，然后将日产奶量的平均值除以体重的平均值得到的商值，作为该奶牛在某个产奶周期内的单位体重日产奶量。
分类模块30则根据奶牛的单位体重日产奶量对奶牛进行分类。
可选地，分类模块30如图5所示，包括第一判断单元31和第一归类单元32，其中：第一判断单元31，设置为比较每头奶牛的单位体重日产奶量与第一阈值的大小，判断奶牛的单位体重日产奶量是否小于或等于第一阈值；第一归类单元32，设置为当奶牛的单位体重日产奶量小于或等于第一阈值时，将奶牛归类为低产奶量奶牛。进一步地，当奶牛的单位体重日产奶量大于第一阈值时，第一归类单元32则将该奶牛归类为高产奶量奶牛。第一阈值的大小可以根据实际需要设定，如当产奶周期为淡奶期时，可以设定第一阈值在0.05-0.1之间，优选设定为0.08；当产奶周期为高峰期时，则可以将第一阈值设定得比淡奶期高一些。
可选地，分类模块30如图6所示，包括排序单元33和第二归类单元34，其中：排序单元33，用根据单位体重日产奶量从高到低的顺序对奶牛进行排序；第二归类单元34，设置为挑选出排在后面预设比例的奶牛，将其归类为低产奶量奶牛，其余的归类为高产奶量奶牛，这种方式相当于末位淘汰制。预设比例可以根据实际需要设定，可以设定在15％-25％之间，如将排在后面20％的奶牛归类为低产奶量奶牛。举例而言，假设有100头奶牛，第二归类单元34则将排在后面的20(100*20％)头奶牛(即排列在第81-100位的奶牛)归类为低产奶量奶牛。
进一步地，在另一些实施例中，还可以对低产奶量奶牛进行进一步分类。在如图7、图8所示的分类模块30中，还包括统计单元35、第二判断单元36和第三归类单元37，其中：统计单元35，设置为统 计低产量奶牛最近一段时间内的体重增长率；第二判断单元36，设置为比较体重增长率和第二阈值的大小，判断体重增长率是否大于或等于第二阈值；第三归类单元37，设置为当低产量奶牛的体重增长率大于或等于第二阈值时，说明其体重增长率比较高，虽然产奶量低，但身体健康，产肉量比较高，尚有一定的经济效益，故将该低产量奶牛进一步归类为肉牛。第二阈值的大小可以根据实际需要设定。
进一步地，该分类模块30还可以包括第四归类单元38，该第四归类单元38设置为：当低产奶量奶牛的体重增长率小于第二阈值时，将该低产量奶牛进一步归类为预淘汰奶牛或淘汰奶牛。
当归类为预淘汰奶牛，可以将其筛选出来通过改善饲料调养一段时间后再判断其单位体重日产奶量和体重增长率是否达标，当仍然不达标时(如单位体重日产奶量小于或等于第一阈值、排序排在后面预设比例范围内或体重增长率小于第二阈值)，则将其归类为经济效益低的淘汰奶牛予以淘汰。
在某些实施例中，分类模块30也可以直接将低产奶量奶牛当作淘汰奶牛予以淘汰。
本发明实施例的奶牛分类装置，通过获取奶牛每日的体重和产奶量，并统计各个奶牛在同一产奶周期内的单位体重日产奶量，最后根据奶牛的单位体重日产奶量对奶牛进行分类，实现了利用量化指标对奶牛进行分类，既高效又准确。由于单位体重日产奶量这一量化指标充分的考虑到了不同奶牛的体重差异，因此能够准确的体现奶牛的产奶能力，从而能够更加科学、准确的衡量奶牛的经济效益，进而准确的淘汰掉经济效益较低的奶牛，有利于实现养殖场的经济效益最大化。
本发明同时提出一种计算机设备，其包括存储器、处理器和至少一个被存储在存储器中并被配置为由处理器执行的应用程序，所述应用程序被配置为用于执行奶牛分类方法。所述奶牛分类方法包括以下步骤：获取奶牛每日的体重和产奶量；统计各个奶牛在同一产奶周期内的单位体重日产奶量；根据奶牛的单位体重日产奶量对奶牛进行分类。本实施例中所描述的奶牛分类方法为本发明中上述实施例所涉及的奶牛分类方法，在此不再赘述。
本领域技术人员可以理解，本发明包括涉及用于执行本申请中所述操作中的一项或多项的设备。这些设备可以为所需的目的而专门设计和制造，或者也可以包括通用计算机中的已知设备。这些设备具有存储在其内的计算机程序，这些计算机程序选择性地激活或重构。这样的计算机程序可以被存储在设备(例如，计算机)可读介质中或者存储在适于存储电子指令并分别耦联到总线的任何类型的介质中，所述计算机可读介质包括但不限于任何类型的盘(包括软盘、硬盘、光盘、CD-ROM、和磁光盘)、ROM(Read-Only Memory，只读存储器)、RAM(Random Access Memory，随机存储器)、EPROM(Erasable Programmable Read-Only Memory，可擦写可编程只读存储器)、EEPROM(Electrically Erasable Programmable Read-Only Memory，电可擦可编程只读存储器)、闪存、磁性卡片或光线卡片。也就是，可读介质包括由设备(例如，计算机)以能够读的形式存储或传输信息的任何介质。
本技术领域技术人员可以理解，可以用计算机程序指令来实现这些结构图和/或框图和/或流图中的每个框以及这些结构图和/或框图和/或流图中的框的组合。本技术领域技术人员可以理解，可以将这些计算机程序指令提供给通用计算机、专业计算机或其他可编程数据处理方法的处理器来实现，从而通过计算机或其他可编程数据处理方法的处理器来执行本发明公开的结构图和/或框图和/或流图的框或多个框中指定的方案。
本技术领域技术人员可以理解，本发明中已经讨论过的各种操作、方法、流程中的步骤、措施、方案可以被交替、更改、组合或删除。进一步地，具有本发明中已经讨论过的各种操作、方法、流程中的其他步骤、措施、方案也可以被交替、更改、重排、分解、组合或删除。进一步地，现有技术中的具有与本发明中公开的各种操作、方法、流程中的步骤、措施、方案也可以被交替、更改、重排、分解、组合或删除。
以上所述仅为本发明的优选实施例，并非因此限制本发明的专利范围，凡是利用本发明说明书及附图内容所作的等效结构或等效流程 变换，或直接或间接运用在其他相关的技术领域，均同理包括在本发明的专利保护范围内。

Claims (20)

  1. 一种奶牛分类方法，包括以下步骤：
    获取奶牛每日的体重和产奶量；
    统计各个奶牛在同一产奶周期内的单位体重日产奶量；
    根据所述单位体重日产奶量对所述奶牛进行分类。
  2. 根据权利要求1所述的奶牛分类方法，其中，所述根据所述单位体重日产奶量对所述奶牛进行分类的步骤包括：
    判断所述奶牛的单位体重日产奶量是否小于或等于第一阈值；
    当所述奶牛的单位体重日产奶量小于或等于第一阈值时，将所述奶牛归类为低产奶量奶牛。
  3. 根据权利要求1所述的奶牛分类方法，其中，所述根据所述单位体重日产奶量对所述奶牛进行分类的步骤包括：
    根据单位体重日产奶量从高到低的顺序对所述奶牛进行排序；
    挑选出排在后面预设比例的奶牛，将所述奶牛归类为低产奶量奶牛。
  4. 根据权利要求2所述的奶牛分类方法，其中，所述将所述奶牛归类为低产量奶牛的步骤之后还包括：
    统计所述低产量奶牛最近一段时间内的体重增长率；
    判断所述体重增长率是否大于或等于第二阈值；
    当所述体重增长率大于或等于第二阈值时，将所述低产量奶牛进一步归类为肉牛。
  5. 根据权利要求4所述的奶牛分类方法，其中，所述判断所述体重增长率是否大于或等于第二阈值的步骤之后还包括：
    当所述体重增长率小于第二阈值时，将所述低产量奶牛进一步归类为预淘汰奶牛或淘汰奶牛。
  6. 根据权利要求2所述的奶牛分类方法，其中，所述第一阈值为0.05-0.1。
  7. 根据权利要求3所述的奶牛分类方法，其中，所述预设比例为15％-25％。
  8. 根据权利要求1所述的奶牛分类方法，其中，所述获取奶牛每日的体重和产奶量的步骤包括：
    接收体重测量设备发送的奶牛的体重和身份信息；接收挤奶设备发送的奶牛的产奶量和身份信息，并统计同一个奶牛一日内总的产奶量；
    根据所述身份信息记录各个奶牛每日的体重和产奶量。
  9. 根据权利要求8所述的奶牛分类方法，其中，所述奶牛的身份信息为存储于电子标签内的编码信息，所述电子标签设置于所述奶牛身上。
  10. 根据权利要求9所述的奶牛分类方法，其中，所述电子标签设置于所述奶牛的腿部和/或头部。
  11. 一种奶牛分类装置，包括：
    获取模块，设置为获取奶牛每日的体重和产奶量；
    统计模块，设置为统计各个奶牛在同一产奶周期内的单位体重日产奶量；
    分类模块，设置为根据所述单位体重日产奶量对所述奶牛进行分类。
  12. 根据权利要求11所述的奶牛分类装置，其中，所述分类模块包括：
    第一判断单元，设置为判断所述奶牛的单位体重日产奶量是否小于或等于第一阈值；
    第一归类单元，设置为当所述奶牛的单位体重日产奶量小于或等于第一阈值时，将所述奶牛归类为低产奶量奶牛。
  13. 根据权利要求11所述的奶牛分类装置，其中，所述分类模块包括：
    排序单元，用根据单位体重日产奶量从高到低的顺序对所述奶牛进行排序；
    第二归类单元，设置为挑选出排在后面预设比例的奶牛，将所述奶牛归类为低产奶量奶牛。
  14. 根据权利要求13所述的奶牛分类装置，其中，所述分类模块还包括：
    统计单元，设置为统计所述低产量奶牛最近一段时间内的体重增长率；
    第二判断单元，设置为判断所述体重增长率是否大于或等于第二阈值；
    第三归类单元，设置为当所述体重增长率大于或等于第二阈值时，将所述低产量奶牛进一步归类为肉牛。
  15. 根据权利要求14所述的奶牛分类装置，其中，所述分类模块还包括第四归类单元，所述第四归类单元设置为：当所述体重增长率小于第二阈值时，将所述低产量奶牛进一步归类为预淘汰奶牛或淘汰奶牛。
  16. 根据权利要求12所述的奶牛分类装置，其中，所述第一阈值为0.05-0.1。
  17. 根据权利要求13所述的奶牛分类装置，其中，所述预设比 例为15％-25％。
  18. 根据权利要求11所述的奶牛分类装置，其中，所述获取模块包括：
    第一获取单元，设置为接收体重测量设备发送的奶牛的体重和身份信息；
    第二获取单元，设置为接收挤奶设备发送的奶牛的产奶量和身份信息，并统计同一个奶牛一日内总的产奶量；
    记录单元，设置为根据所述身份信息记录各个奶牛每日的体重和产奶量。
  19. 根据权利要求18所述的奶牛分类装置，其中，所述奶牛的身份信息为存储于电子标签内的编码信息，所述电子标签设置于所述奶牛身上。
  20. 根据权利要求19所述的奶牛分类装置，其中，所述电子标签设置于所述奶牛的腿部和/或头部。
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Publication number Priority date Publication date Assignee Title
CN113197116A (zh) * 2021-05-07 2021-08-03 青岛不愁网信息科技有限公司 生猪健康监测及出栏时间评估方法、终端设备及存储介质

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101120376A (zh) * 2004-11-29 2008-02-06 嘉吉有限公司 动物管理系统
CN101404874A (zh) * 2006-03-17 2009-04-08 德拉瓦尔控股股份有限公司 用于公共挤奶中心的挤奶系统、方法和畜群管理系统
CN103106564A (zh) * 2013-02-01 2013-05-15 内蒙古自治区科学技术信息研究所 基于rfid技术的育肥牛质量安全饲养管理方法及系统
CN104036383A (zh) * 2014-05-09 2014-09-10 天津梦得集团有限公司 一种奶牛繁殖管理系统及奶牛繁殖管理方法
CN203930933U (zh) * 2014-03-13 2014-11-05 李威娜 一种奶牛生产性能测定装置
CN105844534A (zh) * 2016-04-08 2016-08-10 北京农业信息技术研究中心 奶牛体况自动评分方法及装置
CN105960164A (zh) * 2013-12-08 2016-09-21 以色列国家农业和农村发展农业研究组织沃尔坎尼中心 用于监控家畜动物的食物摄取的方法和系统
CN107316141A (zh) * 2017-06-22 2017-11-03 中国农业科学院农业信息研究所 一种农产品供需平衡调节方法及系统

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR100591549B1 (ko) * 2004-07-23 2006-06-19 주식회사 케이티프리텔 유무선 통신망을 이용한 젖소 검정 및 관리 서비스 제공시스템과 그 방법
CN101114372A (zh) * 2006-07-26 2008-01-30 天津市天农科技有限公司 基于rfid技术的奶牛养殖管理信息系统及其工作方法
CN103782954B (zh) * 2014-01-25 2016-03-02 广东燕塘乳业股份有限公司 基于rfid技术的奶牛精细化养殖方法
CN104322450A (zh) * 2014-11-24 2015-02-04 李文才 一种奶肉牛快速繁育杂交方法

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101120376A (zh) * 2004-11-29 2008-02-06 嘉吉有限公司 动物管理系统
CN101404874A (zh) * 2006-03-17 2009-04-08 德拉瓦尔控股股份有限公司 用于公共挤奶中心的挤奶系统、方法和畜群管理系统
CN103106564A (zh) * 2013-02-01 2013-05-15 内蒙古自治区科学技术信息研究所 基于rfid技术的育肥牛质量安全饲养管理方法及系统
CN105960164A (zh) * 2013-12-08 2016-09-21 以色列国家农业和农村发展农业研究组织沃尔坎尼中心 用于监控家畜动物的食物摄取的方法和系统
CN203930933U (zh) * 2014-03-13 2014-11-05 李威娜 一种奶牛生产性能测定装置
CN104036383A (zh) * 2014-05-09 2014-09-10 天津梦得集团有限公司 一种奶牛繁殖管理系统及奶牛繁殖管理方法
CN105844534A (zh) * 2016-04-08 2016-08-10 北京农业信息技术研究中心 奶牛体况自动评分方法及装置
CN107316141A (zh) * 2017-06-22 2017-11-03 中国农业科学院农业信息研究所 一种农产品供需平衡调节方法及系统

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