An intelligent control method for the experiment of the effect of 25-hydroxyvitamin D3 on poultry

Abstract

The invention relates to the technical field of poultry experiments, and discloses an intelligent control method for an experiment on the influence of 25-hydroxyvitamin D3 on poultry, comprising: obtaining habit data and weight data of each poultry in a target environment, forming classification data, forming an experimental control group, performing a control experiment, and forming conclusion data. The intelligent control method for the experiment on the influence of 25-hydroxyvitamin D3 on poultry determines the living habits of each poultry according to the feeding time, feeding duration, and feeding times of each poultry in the same environment, determines the weight gain rate of each poultry according to the daily weight of each poultry in the same environment, and classifies all poultry in the same environment according to the living habits, weight gain rate, and current weight of each poultry in the same environment, thereby forming control groups for poultry of similar types to conduct experiments, thereby reducing deviation data generated by individual living habits and individual weight gain rates of poultry, and making the experimental conclusion more accurate.

Description

Technical Field

[0001] The invention relates to the technical field of poultry experiments, and in particular to an intelligent control method for an experiment on the influence of 25-hydroxyvitamin D3 on poultry. Background Art

[0002] As poultry ages, the secretion of estrogen and FSH decreases, and the number of newly formed follicles gradually decreases; the apoptosis rate of oviduct mucosal epithelial cells accelerates, and inflammation of the oviduct mucosa increases, which reduces the quality of eggshells and makes them more susceptible to oviduct inflammation, reduces egg production, increases egg weight, reduces immune resistance, increases the incidence of avian Escherichia coli disease, makes the intestines more susceptible to chronic inflammation, and increases the incidence of fatty liver, which results in an increase in the mortality rate of poultry, frequent nutritional metabolic diseases, and a decrease in the qualified rate of breeder eggs, hatchability, and chick quality;

[0003] 25-hydroxyvitamin D3 affects the egg-laying performance, reproductive performance, egg yolk nutrients and chick survival rate of poultry in the late egg-laying period, as well as the liver and oviduct functions, providing solutions to alleviate the production and physiological problems of poultry in the late egg-laying period. The biological functions of vitamin D include not only traditional functions such as calcium-phosphorus metabolism, calcium-phosphorus homeostasis, bone health and muscle development, but also non-traditional functions such as immune regulation, anti-inflammation, anti-infection, anti-virus, barrier protection and intestinal flora regulation. The biological potency of 25-hydroxyvitamin D3 is 1.8-5 times that of vitamin D3, and the absorption of 25-hydroxyvitamin D3 does not depend on the secretion of bile and the influence of other fat-soluble vitamins, so the biological utilization efficiency is high and the demand can be met faster.

[0004] The existing intelligent control method for experiments on the effects of 25-hydroxyvitamin D3 on poultry cannot judge the living habits of each poultry in the same environment based on the feeding time, feeding duration and feeding times of each poultry in the same environment. It cannot judge the weight gain rate of each poultry in the same environment based on the daily weight of each poultry in the same environment. It cannot classify all poultry in the same environment based on the living habits, weight gain rate and current weight of each poultry in the same environment, thereby forming control groups for similar types of poultry for experiments. There are certain deviations in the data, which may cause deviations in the experimental results and lead to inaccurate experimental conclusions. Its practicality has certain limitations. Summary of the invention

[0005] The present invention provides an intelligent control method for an experiment on the effect of 25-hydroxyvitamin D3 on poultry, which is used to promote the solution of the problems mentioned in the background technology.

[0006] The present invention provides the following technical solution: an intelligent control method for an experiment on the effect of 25-hydroxyvitamin D3 on poultry, comprising:

[0007] Through the habit collection strategy, the habit data of each bird in the target environment is obtained to obtain the individual living habits of each bird in the target environment, thereby classifying all birds in the target environment;

[0008] The weight data of each bird in the target environment is obtained through a weight collection strategy to obtain the daily weight change of each bird in the target environment, thereby classifying all birds in the target environment;

[0009] According to the habit data and weight data, through the data classification strategy, classification data is formed to classify all the birds in the target environment, so as to form an experimental control group and then conduct a control experiment;

[0010] According to the classification data, all birds in the target environment are classified and experimental control groups are formed. Control experiments are performed and conclusion data is formed based on the experimental results of each control group.

[0011] The habit collection strategy is specifically as follows:

[0012] There are several feeders in the target environment;

[0013] The feeder is provided with a positioning device and a peripheral infrared sensing device;

[0014] Set the sensing distance;

[0015] With the feeder as the center and the sensing distance as the radius, a sensing range is formed;

[0016] Each bird in the target environment is fitted with a collection leg collar;

[0017] The collection foot ring is provided with a positioning device;

[0018] The location of the bird is obtained through the collecting leg ring of the bird and is determined as the target location point;

[0019] If the target location point is not within the sensing range, it is determined that the bird is not in the feeding state;

[0020] If the target location point is within the sensing range, the feeding determination strategy is executed.

[0021] As an optional scheme of the intelligent control method for the experiment of the effect of 25-hydroxyvitamin D3 on poultry of the present invention, the feeding judgment strategy is specifically as follows:

[0022] S1. Obtain the position of the feeder through the positioning device of the feeder and set it as the reference position point;

[0023] Connect the target position point and the reference position point to form a target connection line;

[0024] Take the center point of the feeder as the starting point, the target connection line as the reference line, and make an extension line, which is named the auxiliary judgment line;

[0025] Obtain an infrared sensing device located on the auxiliary determination line at a bird's-eye view angle and define it as a determination device;

[0026] S2, the determination device collects the beak data of the bird;

[0027] S3. If the determination device is not blocked by the beak of the bird, it means that the determination device has not collected beak data, which is determined as the first result;

[0028] If the determination device is blocked by the beak of the bird, it means that the determination device has collected beak data, which is determined as the second result;

[0029] S4, obtaining an initial determination result of the determination device;

[0030] Get the judgment duration;

[0031] S5, if the initial determination result of the determination device is the first result, it is determined that the poultry is in a feeding state, the first result is identified as the initial determination result, and steps S4-S5 are repeated;

[0032] If the initial determination result of the determination device is the second result, and the determination result of the determination device does not change within the determination time, it is determined that the poultry is not in a feeding state, and the data error determination strategy is executed;

[0033] If the initial determination result of the determination device is the second result, and within the determination time, the determination result of the determination device changes to the first result, it is determined that the bird is in a feeding state, the second result is identified as the initial determination result, and steps S4-S5 are repeated;

[0034] S6, extracting the time point when the determination device first determines that the poultry is in a feeding state, and setting it as the initial time point;

[0035] The time point at which the extraction determination device initially determines that the poultry is not in a feeding state and is after the initial time point is determined as the termination time point;

[0036] S7, obtaining a determination cycle;

[0037] S8, extracting the number of poultry at the initial time point within the determination period, and the number is the number of times the poultry has ingested food;

[0038] Extract all initial time points under the feeding frequency to form a feeding set, and each element in the feeding set is the feeding time point of the bird in the determination period;

[0039] S9. Calculate the feeding time of the birds each time under the feeding frequency, where feeding time = end time point - initial time point.

[0040] As an optional scheme of the intelligent control method for the experiment of the effect of 25-hydroxyvitamin D3 on poultry described in the present invention, the data error judgment strategy is specifically as follows:

[0041] Get auxiliary distance;

[0042] With the feeder as the center and the auxiliary distance as the radius, an auxiliary determination range is formed;

[0043] obtaining an auxiliary determination line and a determination device;

[0044] Extract all target position points on the auxiliary determination line and set them as determination position points;

[0045] Obtain the number of determination position points, which is defined as the determination number;

[0046] If the judgment quantity = 1, it is judged that the bird is not in the feeding state;

[0047] If the number of determinations is greater than 1, all target position points on the auxiliary determination line within the sensing range are extracted and determined as valid position points;

[0048] Get the number of valid position points and set it as the valid number;

[0049] If the effective number = 1, the effective position point corresponding to the effective number is identified as the feeding position point;

[0050] If the effective number is greater than 1, the distance between the determination device and each effective position point corresponding to the effective number is extracted and determined as the effective distance;

[0051] The effective position point corresponding to the effective distance with the smallest value is identified as the feeding position point;

[0052] Execute the distance determination strategy.

[0053] As an optional scheme of the intelligent control method for the experiment of the effect of 25-hydroxyvitamin D3 on poultry described in the present invention, the distance determination strategy is specifically as follows:

[0054] Obtaining the detection distance initially collected by the determination device and setting it as the initial value;

[0055] The distance between the extraction determination device and the feeding position point is determined as the target distance;

[0056] Obtaining the distance between the determination device and each determination position point excluding the feeding position point, and setting it as a determination value;

[0057] If the initial value is greater than the target distance × (1 + 5%), or the initial value is less than the target distance × (1 - 5%), it means that the data is inaccurate and no judgment is made;

[0058] If the initial value is ≤ target distance × (1 + 5%), and the initial value is ≥ target distance × (1 - 5%), the data is determined to be accurate;

[0059] Obtain the detection distance of the determination device in real time and define it as the acquisition distance;

[0060] If the collection distance changes from the initial value to the determination value, it is determined that the bird is in the feeding state;

[0061] If the collection distance does not change from the initial value to the determination value, it is determined that the bird is not in a feeding state.

[0062] As an optional scheme of the intelligent control method for the experiment of the effect of 25-hydroxyvitamin D3 on poultry of the present invention, the weight collection strategy is specifically as follows:

[0063] Set the collection time point;

[0064] Obtain the daily weight of each bird in the target environment at the collection time point on the current date;

[0065] Calculate the date of the previous day, the date of the previous day = current date - 1;

[0066] Obtain the weight of each bird in the target environment collected at the collection time point of the previous day, and locate the weight of the previous day;

[0067] Calculate the weight gain of the day, which is the weight gain of the day = the weight of the day - the weight of the previous day;

[0068] Get the collection cycle;

[0069] Obtain the daily weight gain value of each bird in the target environment during the collection period;

[0070] Calculate the weight gain rate of each bird in the target environment during the collection period. Weight gain rate = the sum of the daily weight gain values ​​of each day in the collection period ÷ the number of days in the collection period.

[0071] As an optional scheme of the intelligent control method for the experiment of the effect of 25-hydroxyvitamin D3 on poultry described in the present invention, the data classification strategy is specifically as follows:

[0072] Obtain the feeding times, feeding sets and feeding duration of each bird in the target environment, which are defined as first classification data, second classification data and third classification data respectively;

[0073] Extract all first-category data and collect the number of categories of the first-category data;

[0074] Classify all birds in the target environment according to the first classification data to form a first classification set A, denoted as A1...An;

[0075] Extracting all second classification data and collecting the classification quantity of the second classification data;

[0076] For each element in the first classification set A, classify it according to the second classification data to form a second classification set B, which is recorded as A1B1, A1Bn...AnB1, AnBn;

[0077] Extract all third-category data and collect the classification quantity of the third-category data;

[0078] For each element in the second classification set B, classify it according to the third classification data to form a third classification set C, which is recorded as A1B1C1, A1B1Cn...AnBnC1, AnBnCn;

[0079] The weight classification strategy is performed on the third classification set C.

[0080] As an optional scheme of the intelligent control method for the experiment of the effect of 25-hydroxyvitamin D3 on poultry of the present invention, the weight classification strategy is specifically as follows:

[0081] Obtaining the weight gain rate and current weight of each bird in the target environment, which are defined as the fourth classification data and the fifth classification data respectively;

[0082] Extract all fourth-category data and collect the classification number of the fourth-category data;

[0083] Get the third classification set C;

[0084] For each element in the third classification set C, mark them as F1...Fn according to the original order in the third classification set C;

[0085] Each element in the third classification set C is classified according to the fourth classification data to form a fourth classification set D, which is recorded as F1D1, F1Dn...FnD1, FnDn;

[0086] Extract all fifth-category data and collect the classification quantity of the fifth-category data;

[0087] For each element in the fourth classification set D, classify it according to the fifth classification data to form fifth classification data E, which is recorded as F1D1E1, F1D1En...FnDnE1, FnDnEn;

[0088] The fifth classification data E is identified as the experimental classification set, and a control experiment is performed.

[0089] As an optional scheme of the intelligent control method for the experiment of the effect of 25-hydroxyvitamin D3 on poultry described in the present invention, the control experiment is specifically as follows:

[0090] Classify all birds in the target environment according to the elements in the experimental classification set;

[0091] Obtain the number of birds corresponding to each element in the experimental classification set, and define it as the number of element birds;

[0092] Obtain the number of control groups and the required added content of 25-hydroxyvitamin D3 for each control group under the number of control groups, and set the added content as the target content;

[0093] Calculate the number of poultry classifications corresponding to each element in the experimental classification set. The number of poultry classifications = the number of element poultry ÷ the number of control groups;

[0094] If the value of the number of poultry classifications contains a decimal point, extract the value before the decimal point, identify the value as the number of poultry classifications, and execute the experimental steps;

[0095] If the value for the number of bird species does not contain a decimal point, perform the experimental steps.

[0096] As an optional scheme of the intelligent control method for the experiment of the effect of 25-hydroxyvitamin D3 on poultry of the present invention, the experimental steps are specifically as follows:

[0097] Get the experimental period;

[0098] The poultry corresponding to each element in the experimental classification set is classified according to the number of poultry classifications, the number of classifications being the number of control groups, and the control groups formed after the classification are sorted from small to large according to the value of the target content, and are sequentially designated as the first control group, the second control group and the third control group;

[0099] During the experimental period, the target content of 25-hydroxyvitamin D3 was added to the feeders of each control group corresponding to each element in the experimental classification set every day;

[0100] Get the experiment start date;

[0101] Calculate the experiment end date, experiment end date = experiment start date + experiment period;

[0102] When the experiment ends, collect the experimental data of each control group corresponding to each element in the experimental classification set;

[0103] Generate an experimental report based on the elements in the experimental classification set, the control groups corresponding to the elements, and the experimental data of the control groups;

[0104] Automatically generate experimental conclusions based on the experimental report.

[0105] The present invention has the following beneficial effects:

[0106] 1. The intelligent control method for the experiment on the effect of 25-hydroxyvitamin D3 on poultry obtains the feeding time, feeding duration and feeding frequency of each poultry in the same environment through the infrared sensing device and positioning device of the feeder, so as to determine the living habits of each poultry, so as to classify all the poultry in the same environment, and form control groups for similar types of poultry for experiments, thereby reducing the deviation data caused by the individual living habits of poultry and making the experimental conclusions more accurate.

[0107] 2. The intelligent control method for the experiment on the effect of 25-hydroxyvitamin D3 on poultry collects the weight of each poultry in the same environment on the same day, calculates the weight gain rate of each poultry, and obtains the current weight of each poultry in the environment before the experiment begins, so as to classify all the poultry in the same environment, thereby forming control groups for similar types of poultry for experiments, reducing the deviation data caused by the weight gain rate of individual poultry, and making the experimental conclusions more accurate.

[0108] 3. The intelligent control method for the experiment on the effect of 25-hydroxyvitamin D3 on poultry obtains the living habits, weight gain rate and current weight of each poultry in the same environment, classifies all the poultry in the same environment, and forms an experimental classification set. The poultry corresponding to each element in the experimental classification set are similar types of poultry. Control groups are formed for the similar types of poultry to conduct experiments. During the experiment, different amounts of 25-hydroxyvitamin D3 are added to the daily feeding of the control group corresponding to the similar types of poultry. After the experimental period ends, the experimental data are collected and the experimental report is automatically generated to reduce the deviation data caused by the individual living habits and individual weight gain rates of the poultry, so as to make the experimental conclusion more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0109] Figure 1 This is a flow chart of the intelligent control method for the experiment on the effect of 25-hydroxyvitamin D3 on poultry of the present invention;

[0110] Figure 2 This is a schematic diagram of the sensing range of the present invention;

[0111] Figure 3 This is a schematic diagram of the target connection line of the present invention;

[0112] Figure 4 This is a schematic diagram of the auxiliary determination range of the present invention;

[0113] Figure 5 It is a schematic diagram of the feeding position of the present invention. DETAILED DESCRIPTION

[0114] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0115] Example 1, an intelligent control method for the experiment of the effect of 25-hydroxyvitamin D3 on poultry, see Figure 1-Figure 2 ,include:

[0116] Through the habit collection strategy, the habit data of each bird in the target environment is obtained to obtain the individual living habits of each bird in the target environment, thereby classifying all birds in the target environment;

[0117] The weight data of each bird in the target environment is obtained through a weight collection strategy to obtain the daily weight change of each bird in the target environment, thereby classifying all birds in the target environment;

[0118] According to the habit data and weight data, classified data is formed through data classification strategy to classify all the poultry in the target environment, so as to form an experimental control group and then conduct a control experiment. The poultry in the control experiment is laying hens.

[0119] According to the classification data, all birds in the target environment are classified and experimental control groups are formed. Control experiments are performed and conclusion data is formed based on the experimental results of each control group.

[0120] The habit collection strategy is specifically as follows:

[0121] There are several feeders in the target environment;

[0122] The feeder is provided with a positioning device and a peripheral infrared sensing device;

[0123] Setting the sensing distance, which is the farthest distance that the birds can stand while eating;

[0124] With the feeder as the center and the sensing distance as the radius, the sensing range is formed, such as Figure 2 As shown;

[0125] Each bird in the target environment is fitted with a collection leg collar;

[0126] The collection foot ring is provided with a positioning device;

[0127] The location of the bird is obtained through the collecting leg ring of the bird and is determined as the target location point;

[0128] If the target location point is not within the sensing range, it is determined that the bird is not in the feeding state;

[0129] If the target location point is within the sensing range, the feeding determination strategy is executed.

[0130] Through the above method, the living habits of each poultry in the same environment are judged according to the feeding time, feeding duration and feeding times of each poultry in the same environment; the weight gain rate of each poultry in the same environment is judged according to the daily weight of each poultry in the same environment; all poultry in the same environment are classified according to the living habits, weight gain rate and current weight of each poultry in the same environment, so as to form control groups for similar types of poultry for experiments, reduce the deviation data caused by individual living habits and individual weight gain rates of poultry, and make the experimental conclusions more accurate.

[0131] Embodiment 2: This embodiment is an improvement made on the basis of embodiment 1. Figure 3-Figure 5 The intelligent control method of the experiment on the effect of 25-hydroxyvitamin D3 on poultry, the feeding judgment strategy, is specifically:

[0132] S1. Obtain the position of the feeder through the positioning device of the feeder and set it as the reference position point, such as Figure 3 As shown;

[0133] Connect the target position point and the reference position point to form a target connection line, such as Figure 3 As shown;

[0134] Take the center point of the feeder as the starting point, the target connection line as the reference line, and make an extension line, named the auxiliary judgment line, such as Figure 3 As shown;

[0135] Obtain the infrared sensing device located on the auxiliary determination line at the top-down angle and define it as the determination device, such as Figure 3 As shown;

[0136] S2, the determination device collects the beak data of the bird. If the bird is not eating, the determination device is blocked by the beak of the bird, that is, the determination device collects the beak data of the bird. If the bird is eating, the determination device loses the blockage of the beak of the bird, that is, the determination device cannot collect the beak data of the bird.

[0137] S3. If the determination device is not blocked by the beak of the bird, it means that the determination device has not collected beak data, which is determined as the first result;

[0138] If the determination device is blocked by the beak of the bird, it means that the determination device has collected beak data, which is determined as the second result;

[0139] S4, obtaining an initial determination result of the determination device, wherein the initial determination result is a result of the determination device determining for the first time whether beak data is collected;

[0140] Obtaining a determination time, wherein the determination time is the interval time between obtaining data again and determining whether the determination device has collected beak data;

[0141] S5, if the initial determination result of the determination device is the first result, it is determined that the poultry is in a feeding state, the first result is identified as the initial determination result, and steps S4-S5 are repeated;

[0142] If the initial determination result of the determination device is the second result, and the determination result of the determination device does not change within the determination time, it is determined that the poultry is not in a feeding state, and the data error determination strategy is executed;

[0143] If the initial determination result of the determination device is the second result, and within the determination time, the determination result of the determination device changes to the first result, it is determined that the bird is in a feeding state, the second result is identified as the initial determination result, and steps S4-S5 are repeated;

[0144] S6, extracting the time point when the determination device first determines that the poultry is in a feeding state, and setting it as the initial time point;

[0145] The time point at which the extraction determination device initially determines that the poultry is not in a feeding state and is after the initial time point is determined as the termination time point;

[0146] S7, obtaining a determination period, wherein the determination period is 24 hours;

[0147] S8, extracting the number of poultry at the initial time point within the determination period, and the number is the number of times the poultry has ingested food;

[0148] Extract all initial time points under the feeding frequency to form a feeding set, and each element in the feeding set is the feeding time point of the bird in the determination period;

[0149] S9. Calculate the feeding time of the birds each time under the feeding frequency, where feeding time = end time point - initial time point.

[0150] The data error determination strategy is specifically as follows:

[0151] Obtaining the auxiliary distance, which is the farthest distance at which the infrared sensing device of the feeder can collect data. If the object blocks the infrared sensing device within the auxiliary distance, the infrared sensing device can collect data. If the object blocks the infrared sensing device outside the auxiliary distance, the infrared sensing device cannot collect data.

[0152] With the feeder as the center and the auxiliary distance as the radius, an auxiliary judgment range is formed, such as Figure 4 As shown;

[0153] obtaining an auxiliary determination line and a determination device;

[0154] Extract all target position points on the auxiliary judgment line and define them as judgment position points, such as Figure 4-Figure 5 As shown;

[0155] Obtain the number of determination position points, which is defined as the determination number;

[0156] If the judgment quantity = 1, it is judged that the bird is not in the feeding state;

[0157] If the number of determinations is greater than 1, all target position points on the auxiliary determination line within the sensing range are extracted and defined as valid position points, such as Figure 4-Figure 5 As shown;

[0158] Get the number of valid position points and set it as the valid number;

[0159] If the effective number = 1, the effective position point corresponding to the effective number is identified as the feeding position point, such as Figure 4 As shown;

[0160] If the effective number is greater than 1, the distance between the determination device and each effective position point corresponding to the effective number is extracted and determined as the effective distance;

[0161] Then the effective position point corresponding to the minimum effective distance is identified as the feeding position point, such as Figure 5 As shown;

[0162] Execute the distance determination strategy.

[0163] The distance determination strategy is specifically as follows:

[0164] Obtaining the detection distance initially collected by the determination device and setting it as the initial value, wherein the detection distance is the distance between the determination device and the object collected by the determination device. If an object blocks the determination device within the auxiliary distance, the detection distance is the distance between the determination device and the object. If no object blocks the determination device within the auxiliary distance, the detection distance is 0;

[0165] The distance between the extraction determination device and the feeding position point is determined as the target distance;

[0166] Obtaining the distance between the determination device and each determination position point excluding the feeding position point, and setting it as a determination value;

[0167] If the initial value is greater than the target distance × (1 + 5%), or the initial value is less than the target distance × (1 - 5%), it means that the data is inaccurate and no judgment is made;

[0168] If the initial value is ≤ target distance × (1 + 5%), and the initial value is ≥ target distance × (1 - 5%), the data is determined to be accurate;

[0169] Obtain the detection distance of the determination device in real time and define it as the acquisition distance;

[0170] If the collection distance changes from the initial value to the determination value, it is determined that the bird is in the feeding state;

[0171] If the collection distance does not change from the initial value to the determination value, it is determined that the bird is not in a feeding state.

[0172] This embodiment also provides that the weight collection strategy is specifically:

[0173] Setting a collection time point, where the collection time point is a fixed time point for weighing each poultry in the target environment, such as the collection time point is 20:00;

[0174] Obtain the daily weight of each bird in the target environment at the collection time point on the current date;

[0175] Calculate the date of the previous day, the date of the previous day = current date - 1;

[0176] Obtain the weight of each bird in the target environment collected at the collection time point of the previous day, and locate the weight of the previous day;

[0177] Calculate the weight gain of the day, which is the weight gain of the day = the weight of the day - the weight of the previous day;

[0178] Obtain a collection period, which is 30 days;

[0179] Obtain the daily weight gain value of each bird in the target environment during the collection period;

[0180] Calculate the weight gain rate of each bird in the target environment during the collection period. Weight gain rate = the sum of the daily weight gain values ​​of each day in the collection period ÷ the number of days in the collection period.

[0181] Embodiment 3: This embodiment is an improvement made on the basis of Embodiment 2. In this embodiment, the data classification strategy is specifically as follows:

[0182] Obtain the feeding times, feeding sets and feeding duration of each bird in the target environment, which are defined as first classification data, second classification data and third classification data respectively;

[0183] Extract all first classification data and collect the classification number of the first classification data. For example, if the first classification data are 2 times and 3 times respectively, the classification number of the first classification data is 2;

[0184] Classify all birds in the target environment according to the first classification data to form a first classification set A, recorded as A1...An, where n is the number of classifications of the first classification data. If the number of classifications of the first classification data is 2, then An is A2;

[0185] Extract all the second classification data and collect the classification quantity of the second classification data. Take the feeding frequency of 2 times as an example. If the first classification data is 2 times and the number of poultry corresponding to the first classification data is 8, the second classification data are (10:00, 5:00), (11:00, 6:00), (10:00, 5:00), (11:00, 6:00), (11:00, 6:00)(10:00, 5:00), (10:00, 5:00), (10:00, 5:00), then the classification quantity of the first classification data is 2;

[0186] Each element in the first classification set A is classified according to the second classification data to form a second classification set B, which is recorded as A1B1, A1Bn...AnB1, AnBn, where n is the number of categories of the second classification data corresponding to each element in the first classification set A. For example, if the number of categories of the second classification data corresponding to the element A1 is 2, then A1Bn is A1B2. If An is A2, and the number of categories of the second classification data corresponding to the element An is 4, then AnBn is A2B4.

[0187] Extract all the third classification data and collect the classification quantity of the third classification data. Take the feeding frequency of 2 times and the feeding set of (10:00, 5:00) as an example. If the first classification data is 2 times, the second classification data is (10:00, 5:00), and the number of poultry corresponding to this element is 5, the third classification data are (10min, 5min), (15min, 10min), (10min, 5min), (15min, 10min), (10min, 5min), and the classification quantity of the third classification data is 2.

[0188] Each element in the second classification set B is classified according to the third classification data to form a third classification set C, which is recorded as A1B1C1, A1B1Cn...AnBnC1, AnBnCn, where n is the number of categories of the third classification data corresponding to each element in the second classification set B. For example, if the number of categories of the third classification data corresponding to the element A1B1 is 2, then A1B1Cn is A1B1C2. For example, if AnBn is A2B4, and the number of categories of the third classification data corresponding to the element AnBn is 6, then AnBnCn is A2B4C6.

[0189] The weight classification strategy is performed on the third classification set C.

[0190] This embodiment also provides that the weight classification strategy is specifically:

[0191] Obtaining the weight gain rate and current weight of each bird in the target environment, which are defined as the fourth classification data and the fifth classification data respectively;

[0192] Extract all the fourth classification data and collect the classification quantity of the fourth classification data. Take the feeding times as 2 times, the feeding set as (10:00, 5:00), and the feeding time as (10min, 5min) as an example. If the first classification data is 2 times, the second classification data is (10:00, 5:00), the third classification data is (10min, 5min), and the number of poultry corresponding to the element is 8, the fourth classification data are 2g, 3g, 2g, 3g, 2g, 3g, 2g, 2g, respectively, then the classification quantity of the third classification data is 2;

[0193] Get the third classification set C;

[0194] For each element in the third classification set C, according to the original order in the third classification set C, one-to-one correspondence is marked as F1...Fn, where n is the total number of all elements in the third classification set C. For example, the third classification set C is A1B1C1, A1B1Cn...AnBnC1, AnBnCn, and the total number of all elements in the third classification set C is 20, then after integration, they are marked one-to-one as F1, F2...F19, F20;

[0195] Each element in the third classification set C is classified according to the fourth classification data to form a fourth classification set D, which is recorded as F1D1, F1Dn...FnD1, FnDn, where n is the classification number of the fourth classification data corresponding to each element in the third classification set C. For example, if the element A1B1C1 is marked as F1, and the classification number of the fourth classification data corresponding to A1B1C1 is 2, then F1Dn is F1D2; if the element AnBnCn is marked as Fn, Fn is F20, and the classification number of the fourth classification data corresponding to AnBnCn is 6, then FnDn is F20D6;

[0196] Extract all fifth-category data and collect the number of categories of the fifth-category data. Take the feeding times as 2 times, the feeding set as (10:00, 5:00), the feeding time as (10min, 5min), and the weight gain rate as 2g as an example. If the first-category data is 2 times, the second-category data is (10:00, 5:00), the third-category data is (10min, 5min), and the fourth-category data is 2g, and the number of poultry corresponding to the element is 5, the fifth-category data are 3kg, 4kg, 3kg, 4kg, and 3kg respectively, then the number of categories of the third-category data is 2;

[0197] For each element in the fourth classification set D, classify according to the fifth classification data to form fifth classification data E, which is recorded as F1D1E1, F1D1En...FnDnE1, FnDnEn, where n is the number of categories of the fifth classification data corresponding to each element in the fourth classification set D. For example, if the number of categories of the fifth classification data corresponding to the element F1D1 is 2, then F1D1En is F1D1E2. For example, if FnDn is F20D6, and the number of categories of the fourth classification data corresponding to the element FnDn is 6, then FnDnEn is F20D6E6.

[0198] The fifth classification data E is identified as the experimental classification set, and a control experiment is performed.

[0199] Embodiment 4: This embodiment is an improvement made on the basis of embodiment 3. In this embodiment, the control experiment is specifically as follows:

[0200] Classify all birds in the target environment according to the elements in the experimental classification set;

[0201] Obtain the number of birds corresponding to each element in the experimental classification set, and define it as the number of element birds;

[0202] Obtain the number of control groups and the required 25-hydroxyvitamin D3 addition content of each control group under the number of control groups, and set the addition content as the target content, wherein the number of control groups is 3, and the target content of each control group is 0, 50ug / kg and 75ug / kg respectively;

[0203] Calculate the number of poultry classifications corresponding to each element in the experimental classification set. The number of poultry classifications = the number of element poultry ÷ the number of control groups;

[0204] If the value of the number of poultry classifications contains a decimal point, the value before the decimal point is extracted and identified as the number of poultry classifications, and the experimental steps are performed, and the excess poultry are assigned to any control group for the experiment;

[0205] If the value for the number of bird species does not contain a decimal point, perform the experimental steps.

[0206] The experimental steps are specifically as follows:

[0207] Obtaining an experimental period, wherein the experimental period is 10 weeks;

[0208] The poultry corresponding to each element in the experimental classification set is classified according to the number of poultry classifications, the number of classifications being the number of control groups, and the control groups formed after the classification are sorted from small to large according to the value of the target content, and are sequentially designated as the first control group, the second control group and the third control group;

[0209] During the experimental period, the target content of 25-hydroxyvitamin D3 was added to the feeders of each control group corresponding to each element in the experimental classification set every day;

[0210] Get the experiment start date;

[0211] Calculate the experiment end date, experiment end date = experiment start date + experiment period;

[0212] When the experiment ends, collect the experimental data of each control group corresponding to each element in the experimental classification set;

[0213] Generate an experimental report based on the elements in the experimental classification set, the control groups corresponding to the elements, and the experimental data of the control groups;

[0214] Automatically generate experimental conclusions based on the experimental report.

[0215] In this embodiment, the living habits of each poultry in the same environment are judged according to the feeding time, feeding duration and feeding times of each poultry in the same environment, and the weight gain rate of each poultry in the same environment is judged according to the daily weight of each poultry in the same environment. According to the living habits, weight gain rate and current weight of each poultry in the same environment, all poultry in the same environment are classified, so as to form control groups for similar types of poultry for experiments, thereby reducing the deviation data caused by the individual living habits and individual weight gain rates of the poultry, and making the experimental conclusions more accurate.

Claims

1. An intelligent control method for an experiment on the effect of 25-hydroxyvitamin D3 on poultry, characterized in that: include: Through the habit collection strategy, the habit data of each bird in the target environment is obtained to obtain the individual living habits of each bird in the target environment, thereby classifying all birds in the target environment; The weight data of each bird in the target environment is obtained through a weight collection strategy to obtain the daily weight change of each bird in the target environment, thereby classifying all birds in the target environment; According to the habit data and weight data, through the data classification strategy, classification data is formed to classify all the birds in the target environment, so as to form an experimental control group and then conduct a control experiment; According to the classification data, all birds in the target environment are classified and experimental control groups are formed. Control experiments are performed and conclusion data is formed based on the experimental results of each control group. The habit collection strategy is specifically as follows: There are several feeders in the target environment; The feeder is provided with a positioning device and a peripheral infrared sensing device; Set the sensing distance; With the feeder as the center and the sensing distance as the radius, a sensing range is formed; Each bird in the target environment is fitted with a collection leg collar; The collection foot ring is provided with a positioning device; The location of the bird is obtained through the collecting leg ring of the bird and is determined as the target location point; If the target location point is not within the sensing range, it is determined that the bird is not in the feeding state; If the target location point is within the sensing range, the feeding determination strategy is executed; The feeding determination strategy is specifically as follows: S1. Obtain the position of the feeder through the positioning device of the feeder and set it as the reference position point; Connect the target position point and the reference position point to form a target connection line; Take the center point of the feeder as the starting point, the target connection line as the reference line, and make an extension line, which is named the auxiliary judgment line; Obtain an infrared sensing device located on the auxiliary determination line at a bird's-eye view angle and define it as a determination device; S2, the determination device collects the beak data of the bird; S3. If the determination device is not blocked by the beak of the bird, it means that the determination device has not collected beak data, which is determined as the first result; If the determination device is blocked by the beak of the bird, it means that the determination device has collected beak data, which is determined as the second result; S4, obtaining an initial determination result of the determination device; Get the judgment duration; S5, if the initial determination result of the determination device is the first result, it is determined that the poultry is in a feeding state, the first result is identified as the initial determination result, and steps S4-S5 are repeated; If the initial determination result of the determination device is the second result, and the determination result of the determination device does not change within the determination time, it is determined that the poultry is not in a feeding state, and the data error determination strategy is executed; If the initial determination result of the determination device is the second result, and within the determination time, the determination result of the determination device changes to the first result, it is determined that the bird is in a feeding state, the second result is identified as the initial determination result, and steps S4-S5 are repeated; S6, extracting the time point when the determination device first determines that the poultry is in a feeding state, and setting it as the initial time point; The time point at which the extraction determination device initially determines that the poultry is not in a feeding state and is after the initial time point is determined as the termination time point; S7, obtaining a determination cycle; S8, extracting the number of poultry at the initial time point within the determination period, and the number is the number of times the poultry has ingested food; Extract all initial time points under the feeding frequency to form a feeding set, and each element in the feeding set is the feeding time point of the bird in the determination period; S9, calculating the feeding time of the birds each time under the feeding frequency, feeding time = end time point - initial time point; The data error determination strategy is specifically as follows: Get auxiliary distance; With the feeder as the center and the auxiliary distance as the radius, an auxiliary determination range is formed; obtaining an auxiliary determination line and a determination device; Extract all target position points on the auxiliary determination line and set them as determination position points; Obtain the number of determination position points, which is defined as the determination number; If the judgment quantity = 1, it is judged that the bird is not in the feeding state; If the number of determinations is greater than 1, all target position points on the auxiliary determination line within the sensing range are extracted and determined as valid position points; Get the number of valid position points and set it as the valid number; If the effective number = 1, the effective position point corresponding to the effective number is identified as the feeding position point; If the effective number is greater than 1, the distance between the determination device and each effective position point corresponding to the effective number is extracted and determined as the effective distance; The effective position point corresponding to the effective distance with the smallest value is identified as the feeding position point; Execute distance determination strategy; The distance determination strategy is specifically as follows: Obtaining the detection distance initially collected by the determination device and setting it as the initial value; The distance between the extraction determination device and the feeding position point is determined as the target distance; Obtaining the distance between the determination device and each determination position point excluding the feeding position point, and setting it as a determination value; If the initial value is greater than the target distance × (1 + 5%), or the initial value is less than the target distance × (1 - 5%), it means that the data is inaccurate and no judgment is made; If the initial value is ≤ target distance × (1 + 5%), and the initial value is ≥ target distance × (1 - 5%), the data is determined to be accurate; Obtain the detection distance of the determination device in real time and define it as the acquisition distance; If the collection distance changes from the initial value to the determination value, it is determined that the bird is in the feeding state; If the collection distance does not change from the initial value to the determination value, it is determined that the bird is not in a feeding state.

2. The intelligent control method for the experiment of the effect of 25-hydroxyvitamin D3 on poultry according to claim 1, characterized in that: The weight collection strategy is specifically as follows: Set the collection time point; Obtain the daily weight of each bird in the target environment at the collection time point on the current date; Calculate the date of the previous day, the date of the previous day = current date - 1; Obtain the weight of each bird in the target environment collected at the collection time point of the previous day, and locate the weight of the previous day; Calculate the weight gain of the day, which is the weight gain of the day = the weight of the day - the weight of the previous day; Get the collection cycle; Obtain the daily weight gain value of each bird in the target environment during the collection period; Calculate the weight gain rate of each bird in the target environment during the collection period. Weight gain rate = the sum of the daily weight gain values ​​of each day in the collection period ÷ the number of days in the collection period.

3. The intelligent control method for the experiment of the effect of 25-hydroxyvitamin D3 on poultry according to claim 1 is characterized in that: The data classification strategy is specifically: Obtain the feeding times, feeding sets and feeding duration of each bird in the target environment, which are defined as first classification data, second classification data and third classification data respectively; Extract all first-category data and collect the number of categories of the first-category data; Classify all birds in the target environment according to the first classification data to form a first classification set A, denoted as A1...An; Extracting all second classification data and collecting the classification quantity of the second classification data; For each element in the first classification set A, classify it according to the second classification data to form a second classification set B, which is recorded as A1B1, A1Bn...AnB1, AnBn; Extract all third-category data and collect the classification quantity of the third-category data; For each element in the second classification set B, classify it according to the third classification data to form a third classification set C, which is recorded as A1B1C1, A1B1Cn...AnBnC1, AnBnCn; The weight classification strategy is performed on the third classification set C.

4. The intelligent control method for the experiment of the effect of 25-hydroxyvitamin D3 on poultry according to claim 3 is characterized in that: The weight classification strategy is specifically: Obtain the weight gain rate and current weight of each bird in the target environment, which are defined as the fourth classification data and the fifth classification data respectively; Extract all fourth-category data and collect the classification number of the fourth-category data; Get the third classification set C; For each element in the third classification set C, mark them as F1...Fn according to the original order in the third classification set C; For each element in the third classification set C, classify it according to the fourth classification data to form a fourth classification set D, which is recorded as F1D1, F1Dn...FnD1, FnDn; Extract all fifth-category data and collect the classification quantity of the fifth-category data; For each element in the fourth classification set D, classify it according to the fifth classification data to form fifth classification data E, which is recorded as F1D1E1, F1D1En...FnDnE1, FnDnEn; The fifth classification data E is identified as the experimental classification set, and a control experiment is performed.

5. The intelligent control method for the experiment of the effect of 25-hydroxyvitamin D3 on poultry according to claim 4 is characterized in that: The control experiment is specifically as follows: Classify all birds in the target environment according to the elements in the experimental classification set; Obtain the number of birds corresponding to each element in the experimental classification set, and define it as the number of element birds; Obtain the number of control groups and the required added content of 25-hydroxyvitamin D3 for each control group under the number of control groups, and set the added content as the target content; Calculate the number of poultry classifications corresponding to each element in the experimental classification set. The number of poultry classifications = the number of element poultry ÷ the number of control groups; If the value of the number of poultry classifications contains a decimal point, extract the value before the decimal point, identify the value as the number of poultry classifications, and execute the experimental steps; If the value for the number of bird species does not contain a decimal point, perform the experimental steps.

6. The intelligent control method for the experiment of the effect of 25-hydroxyvitamin D3 on poultry according to claim 5, characterized in that: The experimental steps are specifically as follows: Get the experimental period; The poultry corresponding to each element in the experimental classification set is classified according to the number of poultry classifications, the number of classifications being the number of control groups, and the control groups formed after the classification are sorted from small to large according to the value of the target content, and are sequentially designated as the first control group, the second control group and the third control group; During the experimental period, the target content of 25-hydroxyvitamin D3 was added to the feeders of each control group corresponding to each element in the experimental classification set every day; Get the experiment start date; Calculate the experiment end date, experiment end date = experiment start date + experiment period; When the experiment ends, collect the experimental data of each control group corresponding to each element in the experimental classification set; Integrate and generate an experimental report based on the elements in the experimental classification set, the control groups corresponding to the elements, and the experimental data of the control groups; Automatically generate experimental conclusions based on the experimental report.

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