Sectional management method for safe and efficient production of large-scale boar station

Abstract

The invention relates to the technical field of breeding management, and discloses a partition management method for safe and efficient production of a large-scale boar station, and the method comprises the following steps: 1, obtaining health data of all boars, breeding data at all time points, and environment data of all partitions, and carrying out the classification to form a data set; 2, setting a monitoring period with a fixed time length, analyzing the health state of each breeding pig, and generating an index data set and a stress coefficient; 3, the health state of each breeding pig is judged, whether stress risks exist or not is judged, corresponding early warning signals and management suggestions are generated, and individual differences are accurately evaluated; 4, analyzing the hybridization coefficient of each pair of hybridization combinations; and step 5, setting a temperature threshold value, a humidity threshold value, a noise threshold value and a breeding threshold value in a fixed range, analyzing and generating a monitoring data set, evaluating the environment level of each partition and the degree of adaptation of each pair of breeding combinations, and outputting corresponding evaluation results and management suggestions, so that the intelligent optimization breeding efficiency is high.

Description

Technical Field

[0001] The present invention relates to the technical field of breeding management, and specifically to a zoning management method for safe and efficient production in a large-scale boar station. Background Art

[0002] A boar station is a professional institution established specifically for the management and breeding services of breeding boars in the pig industry. Through intensive management and technical support, the boar station plays an important role in improving the production performance of the pig herd, reducing breeding costs, and ensuring the quality of pork. The boar station strictly screens individual breeding boars, selects breeding boars suitable for breeding from high-quality pig breeds according to indicators such as genetic performance, health status, and production capacity, and regularly conducts feeding management, disease monitoring, and quality inspection to ensure that their breeding ability and health level meet industry standards. With the help of advanced gene technology and breeding tools, the boar station can accurately evaluate the genetic value of breeding boars. Through a centralized management model, excellent varieties are effectively promoted, and the growth rate, disease resistance, and meat quality of the pig herd are improved. In addition, the boar station also provides technical training to farms, including services such as insemination operation guidance, breeding plan formulation, and pig herd management consultation. This not only helps to improve the production efficiency of live pigs but also plays a key role in protecting and utilizing live pig germplasm resources. In the context of the sustainable development of modern agriculture, the boar station has made positive contributions to ensuring food safety, meeting market demand, and promoting ecological breeding by promoting efficient and environmentally friendly breeding methods.

[0003] At present, the zoning management method adopted by traditional boar stations usually divides areas according to the age, species, or body size of breeding pigs, often ignoring the differences in the stress levels of individual breeding pigs, especially the aggressiveness and personality differences of boars, which easily lead to problems such as fighting and injury, resulting in low management efficiency, thus affecting the production efficiency of boar breeding and the health of pigs. Summary of the Invention

[0004] (I) Technical Problems to be Solved In view of the deficiencies of the prior art, the present invention provides a zoning management method for safe and efficient production in a large-scale boar station, which has the advantages of accurately evaluating individual differences and highly intelligent optimization of breeding efficiency, and solves the problems of ignoring the differences in the stress levels of individual breeding pigs and low management efficiency in the traditional zoning management method.

[0005] (II) Technical Solutions To achieve the above object, the present invention provides the following technical solutions: A zoning management method for safe and efficient production in a large-scale boar station, including the following steps: Step 1: Connect the breeding management system and the monitoring device through the network, obtain the health data of all breeding pigs, the breeding data at all time points, and the environmental data of all partitions, and classify and form a health data set, a breeding data set, and an environmental data set; Step 2: Set a monitoring period with a fixed duration , and then, in combination with the health data set, analyze the health status of each breeding pig and generate a corresponding index data group and stress coefficient ; Step 3: Set body temperature thresholds, heart rate thresholds, drinking water thresholds, feeding thresholds, excretion thresholds, shouting thresholds, and stress thresholds within a fixed range , heart rate thresholds , drinking water thresholds , feeding thresholds , excretion thresholds , shouting thresholds , and stress thresholds , and then, in combination with the index data group and stress coefficient , judge the health status of each breeding pig and whether there is a stress risk, and generate corresponding warning signals and management suggestions; Step 4: Analyze the breeding coefficient of each breeding combination according to the breeding data set and the environmental data set ; Step 5: Set temperature thresholds, humidity thresholds, noise thresholds, and breeding thresholds within a fixed range , humidity thresholds , noise thresholds , and breeding thresholds , and then, in combination with the environmental data set and the breeding coefficient , analyze and generate a corresponding monitoring data group , evaluate the environmental level of each area and the suitability of each breeding combination, and output corresponding evaluation results and management suggestions.

[0006] Preferably, in the above Step 1, the expression of the health data set is , to are the health data of the first to the th breeding pigs respectively. The health data includes body temperature, heart rate, drinking water volume, feeding volume, excretion times, and shouting times, represents the number of the area where each breeding pig is located.

[0007] Preferably, in the above Step 1, the expression of the breeding data set is , to are the breeding data of the first to the th breeding combinations respectively. The breeding data includes boar age, sow age, and breeding times, represents the specific time point for obtaining the breeding data of each breeding combination.

[0008] Preferably, in the above Step 1, the expression of the environmental data set is , to respectively the environmental data of the first to the nth partition, and the environmental data includes spatial dimension, temperature, humidity and noise level, indicating the specific time point for obtaining the environmental data of each partition.

[0009] Preferably, in the second step, the index data group is calculated as follows: According to the health data set, extract the health data of the ith breeding pig within the monitoring period, and mark the body temperature of the ith th breeding pig as , mark the heart rate of the ith th breeding pig as , mark the water intake of the ith th breeding pig as , mark the food intake of the ith th breeding pig as ,

[0010] In the formula, and are respectively the maximum value and the minimum value of the body temperature of the ith th breeding pig within the monitoring period, represents the body temperature range, denoted as , and are respectively the maximum value and the minimum value of the heart rate of the ith th breeding pig within the monitoring period, represents the heart rate range, denoted as , and are respectively the maximum value and the minimum value of the water intake of the ith th breeding pig within the monitoring period, represents the water intake range, denoted as , and are respectively the maximum value and the minimum value of the food intake of the ith th breeding pig within the monitoring period, represents the food intake range, denoted as , and are the monitoring period Within, the highest and lowest values of the excretion times of the th breeding pig, , and are the monitoring period Within, the highest and lowest values of the shouting times of the th breeding pig, .

[0011] Preferably, in the second step, the stress coefficient is calculated as follows:

[0012] In the formula, represents the evaluation weight for the body temperature range, represents the evaluation weight for the heart rate range, represents the evaluation weight for the water intake range, represents the evaluation weight for the food intake range, represents the evaluation weight for the excretion times range, represents the evaluation weight for the shouting times range, , represents according to , , , , and weights, calculate the stress coefficient of the th breeding pig within the monitoring period .

[0013] Preferably, in the third step, in the index data group , the body temperature range exceeds the body temperature threshold , the heart rate range exceeds the heart rate threshold , the water intake range exceeds the water intake threshold , the food intake range exceeds the food intake threshold , the excretion times range exceeds the excretion threshold , the shouting times range exceeds the shouting threshold or the stress coefficient exceeds the stress threshold When, it means the The health status of the breeding pigs is not good, there is a stress risk, stress warning signals are generated, and it is recommended to isolate them separately.

[0014] Preferably, in the fourth step, the breeding coefficient The calculation process is as follows: Extract the breeding data of the breeding combination in the breeding dataset, and the age of the boar in the breeding combination is marked as , and the age of the sow in the breeding combination is marked as , and the number of breeding times of the breeding combination is marked as ; According to the environmental dataset, extract the environmental data of the area where the breeding combination is located, and the spatial area of the area where the breeding combination is located is marked as ;

[0015] In the formula, represents the absolute difference in age between the boar and the sow in the breeding combination, represents the ratio of the absolute age difference to the number of breeding times, represents the evaluation weight for the ratio of the absolute age difference to the number of breeding times, represents the ratio of the partition spatial area to the number of breeding times, represents the evaluation weight for the ratio of the partition spatial area to the number of breeding times, , represents according to and weights, to obtain the breeding coefficient of the breeding combination .

[0016] Preferably, in the fifth step, the monitoring data group The calculation process is as follows: According to the environmental dataset, extract the environmental data of the th partition within the monitoring period, and the temperature of the th partition is marked as , the humidity of the th partition is marked as ;

[0017] In the formula, and are respectively the minimum value and the maximum value of the temperature threshold , represents comparing the temperature of the th partition within the monitoring period with the temperature threshold , and are respectively the minimum value and the maximum value of the humidity threshold , represents comparing the humidity of the th partition within the monitoring period with the humidity threshold , and are respectively the minimum value and the maximum value of the noise threshold , represents comparing the noise level of the th partition within the monitoring period with the noise threshold .

[0018] Preferably, in the fifth step, if any value in the monitoring data group exceeds the threshold, it indicates that the environmental level of this partition is poor, and it is recommended to optimize the environmental conditions of this partition. If the breeding coefficient is lower than the breeding threshold , it indicates that the fitness of this breeding combination is low, and it is recommended to replace the breeding pigs.

[0019] Compared with the prior art, the present invention provides a zoning management method for safe and efficient production of a large-scale boar station, which has the following beneficial effects: 1. The present invention connects the breeding management system and the monitoring device through the network, obtains the health data of all breeding pigs, the breeding data at all time points, and the environmental data of all partitions, classifies and forms a health data set, a breeding data set, and an environmental data set, sets a monitoring period with a fixed duration , and then combines the health data set to analyze the health status of each breeding pig and generate the corresponding index data group and the stress coefficient , timely discovers potential health problems and prevents the spread of diseases. There are set temperature thresholds , heart rate thresholds , drinking water thresholds , feeding thresholds , excretion thresholds , shouting thresholds , and stress thresholds within a fixed range, and then combines the index data group and the stress coefficient Judge the health status of each breeding pig, as well as whether there is a stress risk, and generate corresponding warning signals and management suggestions. Breeding pigs with a high stress coefficient often affect the breeding effect and overall production efficiency. Identifying and handling possible stress risks in advance can effectively reduce breeding losses and accurately evaluate individual differences.

[0020] 2. The present invention analyzes the breeding coefficient of each breeding combination to scientifically evaluate the breeding suitability of each pair of breeding pigs, ensure the best pairing of breeding pigs, thereby improving the breeding efficiency of breeding pigs. There are set temperature thresholds within a fixed range , humidity thresholds , noise thresholds and breeding thresholds . Then, combined with the environmental data set and the breeding coefficient , analyze and generate corresponding monitoring data sets , evaluate the environmental level of each partition and the suitability of each breeding combination. If any value in the monitoring data set exceeds the threshold, it indicates that the environmental level of the partition is poor, and it is recommended to optimize the environmental conditions of the partition. If the breeding coefficient is lower than the breeding threshold , it indicates that the suitability of the breeding combination is low, and it is recommended to replace the breeding pigs. Through the specific data analysis of each breeding pig, each breeding combination and each partition, personalized and accurate management suggestions are provided for managers, which can effectively improve the operation efficiency and intelligently optimize the breeding efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a flowchart of the method steps of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0022] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0023] Since the partition management method adopted by traditional boar stations usually partitions according to the age, species or body size of breeding pigs, it often ignores the differences in the individual stress levels of breeding pigs, especially the aggressiveness and personality differences of boars, and problems such as fighting and injury are likely to occur, resulting in low management efficiency, thus affecting the production efficiency of boar breeding and the health of pigs. Therefore, a partition management method for safe and efficient production of large-scale boar stations is provided. Please refer to Figure 1 , a partition management method for safe and efficient production of large-scale boar stations, including the following steps: Step 1: Connect the breeding management system and the monitoring device through the network to obtain the health data of all breeding pigs, the breeding data at all time points, and the environmental data of all partitions, and classify them into a health data set, a breeding data set, and an environmental data set; The expression of the health data set is , to are the health data of the first to the th breeding pigs respectively. The health data includes body temperature, heart rate, water intake, food intake, excretion frequency, and shouting frequency. represents the number of the partition where each breeding pig is located. Comprehensively monitoring the health status of breeding pigs helps to detect the stress behavior of breeding pigs in a timely manner later; The expression of the breeding data set is , to are the breeding data of the first to the th breeding combinations respectively. The breeding data includes boar age, sow age, and breeding times. represents the specific time point when the breeding data of each breeding combination is obtained. Comprehensively monitoring the breeding status of multiple breeding combinations effectively reduces the pressure of manual management; The expression of the environmental data set is , to are the environmental data of the first to the th partitions respectively. The environmental data includes space size, temperature, humidity, and noise level. represents the specific time point when the environmental data of each partition is obtained. Multidimensionally monitoring environmental parameters helps to accurately evaluate the environmental level of each partition later; Step 2: Set a monitoring period with a fixed duration , and then combine it with the health data set to analyze the health status of each breeding pig and generate a corresponding index data group and a stress coefficient ; The calculation process of the index data group is as follows: According to the health data set, extract the health data of the th breeding pig within the monitoring period , and mark the body temperature of the th breeding pig as , mark the heart rate of the th breeding pig as , mark the water intake of the th breeding pig as , mark the food intake of the th breeding pig as , mark the excretion frequency of the The excretion frequency of the breeding pigs is marked as , and the shouting frequency of the th breeding pig is marked as .

[0024] In the formula, and are respectively the maximum and minimum values of the body temperature of the th breeding pig within the monitoring period . represents the body temperature range, denoted as . and are respectively the maximum and minimum values of the heart rate of the th breeding pig within the monitoring period . represents the heart rate range, denoted as . and are respectively the maximum and minimum values of the water intake of the th breeding pig within the monitoring period . represents the water intake range, denoted as . and are respectively the maximum and minimum values of the food intake of the th breeding pig within the monitoring period . represents the food intake range, denoted as . and are respectively the maximum and minimum values of the excretion frequency of the th breeding pig within the monitoring period . represents the excretion frequency range, denoted as . and are respectively the maximum and minimum values of the shouting frequency of the th breeding pig within the monitoring period . represents the shouting frequency range, denoted as . Timely detect potential health problems and prevent the spread of diseases; Stress coefficient The calculation formula is as follows:

[0025] In the formula, represents the evaluation weight for the body temperature range, represents the evaluation weight for the heart rate range, Represents the evaluation weight for extremely poor water intake, Represents the evaluation weight for extremely poor food intake, Represents the evaluation weight for extremely poor excretion frequency, Represents the evaluation weight for extremely poor shouting frequency, , Represents according to , , , , and weights, calculate the stress coefficient of the th breeding sow within the monitoring period. High-stress breeding sows often affect reproductive performance and overall production efficiency. Identifying potential stress risks in advance and dealing with them can effectively reduce breeding losses; Step 3: Set body temperature thresholds with a fixed range,heart rate thresholds , water intake thresholds , food intake thresholds , excretion thresholds , shouting thresholds and stress thresholds . Then, combined with the index data set and the stress coefficient , judge the health status of each breeding sow and whether there is a stress risk, and generate corresponding warning signals and management suggestions; In the index data set , when the body temperature range exceeds the body temperature threshold , the heart rate range exceeds the heart rate threshold , the water intake range exceeds the water intake threshold , the food intake range exceeds the food intake threshold , the excretion frequency range exceeds the excretion threshold , the shouting frequency range exceeds the shouting threshold or the stress coefficient exceeds the stress threshold , it indicates that the health status of the th breeding sow is poor and there is a stress risk. Generate a stress warning signal and recommend separate isolation to accurately evaluate individual differences, effectively control stress, avoid problem deterioration, and improve the accuracy and pertinence of production management; Step 4: Analyze the breeding coefficient of each breeding combination according to the breeding data set and the environmental data set , and its calculation process is as follows: Extract the breeding data of the breeding combination in the breeding dataset, and mark the age of the boar in the breeding combination as , and mark the age of the sow in the breeding combination as , and mark the breeding times of the breeding combination as ; , and mark the age of the sow in the breeding combination as ; ; According to the environmental dataset, extract the environmental data of the partition where the breeding combination is located, and mark the spatial area of the partition where the breeding combination is located as ;

[0026] In the formula, represents the absolute difference in age between the boar and the sow in the breeding combination, represents the ratio of the absolute age difference to the breeding times, represents the evaluation weight for the ratio of the absolute age difference to the breeding times, represents the ratio of the partition spatial area to the breeding times, represents the evaluation weight for the ratio of the partition spatial area to the breeding times, , represents according to and weights, to obtain the breeding coefficient of the breeding combination, , scientifically evaluate the breeding suitability of each pair of breeding pigs, ensure the optimality of breeding pig pairing, and thus improve the breeding efficiency of breeding pigs; Step Five: Set temperature thresholds , humidity thresholds , noise thresholds and breeding thresholds within a fixed range, and then combine the environmental dataset and the breeding coefficient to analyze and generate corresponding monitoring data groups , evaluate the environmental level of each partition and the suitability of each breeding combination, and output corresponding evaluation results and management suggestions; The calculation process of the monitoring data group is as follows: According to the environmental dataset, extract the environmental data of the th partition within the monitoring period, and mark the temperature of the th partition as ; , mark the humidity of the th partition as , mark the noise level of the th partition as ;

[0027] In the formula, and are respectively the minimum and maximum values of the temperature threshold , represents comparing the temperature of the th partition within the monitoring period with the temperature threshold , and are respectively the minimum and maximum values of the humidity threshold , represents comparing the humidity of the th partition within the monitoring period with the humidity threshold , and are respectively the minimum and maximum values of the noise threshold , represents comparing the noise level of the th partition within the monitoring period with the noise threshold , timely detect unqualified environmental conditions and adjust them to optimize the growth and reproduction environment of breeding pigs; If in the monitoring data group , any value exceeds the threshold, it means that the environmental level of this partition is poor. It is recommended to optimize the environmental conditions of this partition. If the breeding coefficient is lower than the breeding threshold , it means that the fitness of this breeding combination is low. It is recommended to replace the breeding pigs. Analyze the specific data of each breeding pig, each breeding combination and each partition, provide personalized and accurate management suggestions for the manager, can effectively improve the operation efficiency, and intelligently optimize the breeding efficiency.

[0028] Example 1: In this experiment, a boar was selected as the experimental object. After testing, within one day, the maximum body temperature of the boar was 39.5 °C, the minimum body temperature was 38.0 °C, the maximum heart rate was 110 beats per minute, the minimum heart rate was 90 beats per minute, the maximum water intake was 20 L, the minimum water intake was 10 L, the maximum food intake was 15 kg, the minimum food intake was 8 kg, the maximum number of pig excretions was 12 times, the minimum number of pig excretions was 6 times, the maximum number of shouting times was 30 times, and the minimum number of shouting times was 15 times. The index data group of this boar The calculation formula is as follows:

[0029] In the formula, 1.5°C represents the range of body temperature, 20 times / minute represents the range of heart rate, 10 L represents the range of water intake, 7 kg represents the range of food intake, 6 times represents the range of excretion frequency, and 15 times represents the range of shouting frequency.

[0030] Example 2: In this experiment, a sow was selected as the experimental subject. After detection, within one day, the range of the sow's body temperature was 1.5°C, the range of heart rate was 10 times / minute, the range of water intake was 2 L, the range of food intake was 3 kg, the range of excretion frequency was 1 time, and the range of shouting frequency was 5 times. The stress coefficient of the sow The calculation formula is as follows:

[0031] In the formula, represents the evaluation weight for the range of body temperature, represents the evaluation weight for the range of heart rate, represents the evaluation weight for the range of water intake, represents the evaluation weight for the range of food intake, represents the evaluation weight for the range of excretion frequency, represents the evaluation weight for the range of shouting frequency, , according to , , , , and weights, within one day, the stress coefficient of the sow is .

[0032] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A zoning management method for safe and efficient production of large-scale boar stations, characterized by: The following steps are involved: Step 1: Connect the breeding management system and monitoring device through the network to obtain the health data of all breeding pigs, the breeding data at all time points and the environmental data of all partitions, and classify them into health data set, breeding data set and environmental data set; Step 2: Set a fixed monitoring period , combined with the health data set, analyze the health status of each breeding pig and generate the corresponding indicator data set and stress coefficient ; Step 3: Set a fixed range of body temperature thresholds , heart rate threshold , drinking water threshold , feeding threshold , excretion threshold , Shouting Threshold and stress threshold , combined with the indicator data set and stress coefficient , determine the health status of each breeding pig, whether there is a stress risk, and generate corresponding early warning signals and management suggestions; Step 4: Analyze the breeding coefficient of each breeding combination based on the breeding data set and environmental data set ; Step 5: Set a fixed temperature threshold , humidity threshold , Noise Threshold and breeding threshold , combined with the environmental data set and the breeding coefficient , analyze and generate the corresponding monitoring data set , evaluate the environmental level of each partition and the suitability of each pair of breeding combinations, and output corresponding evaluation results and management recommendations.

2. The zoning management method for safe and efficient production of large-scale boar stations according to claim 1 is characterized by: In step 1, the expression of the health data set is: , to The first to the The health data of each breeding pig includes body temperature, heart rate, water intake, food intake, number of excretions and number of calls. Indicates the number of the partition where each breeding pig is located.

3. The zoning management method for safe and efficient production of large-scale boar stations according to claim 2 is characterized by: In step 1, the expression of the breeding data set is: , to The first pair to the The breeding data of the breeding combination includes the age of the boar, the age of the sow and the number of breedings. Indicates the specific time point for obtaining the breeding data of each pair of breeding combinations.

4. The zoning management method for safe and efficient production of large-scale boar stations according to claim 3 is characterized by: In step 1, the expression of the environmental data set is: , to The first to the Environmental data for each partition, including space dimensions, temperature, humidity, and noise level. Indicates the specific time point for obtaining the environment data of each partition.

5. The zoning management method for safe and efficient production of large-scale boar stations according to claim 4 is characterized by: In step 2, the indicator data set The calculation process is as follows: Extract monitoring cycles based on health data sets within, no. The health data of the breeding pigs will be The temperature of the breeding pigs is marked as , will The heart rate of the pigs is marked as , will The water intake of each breeding pig is marked as , will The feed intake of each breeding pig is marked as , will The number of excretions of each breeding pig is marked as , will The number of times a pig calls is marked as , In the formula, and The monitoring cycle within, no. The highest and lowest values ​​of the body temperature of breeding pigs, Indicates extreme temperature difference, recorded as , and Monitoring cycle within, no. The highest and lowest heart rates of breeding pigs, Indicates that the heart rate is extremely poor, recorded as , and The monitoring cycle within, no. The maximum and minimum water consumption of breeding pigs, Indicates that the water intake is extremely poor, recorded as , and The monitoring cycle within, no. The maximum and minimum feed intake of breeding pigs. Indicates that the food intake is very poor, recorded as , and Monitoring cycle within, no. The highest and lowest values ​​of excretion frequency of breeding pigs, Indicates that the number of excretions is extremely poor, recorded as , and The monitoring cycle within, no. The highest and lowest values ​​of the number of times the breeding pigs cry, Indicates that the number of shouting is extremely poor, recorded as .

6. A zoning management method for safe and efficient production of large-scale boar stations according to claim 5, characterized in that: In the step 2, the stress coefficient The calculation formula is as follows: In the formula, represents the evaluation weight for the extreme difference in body temperature, represents the evaluation weight for the extreme heart rate difference, represents the assessment weight for extremely poor water intake, represents the evaluation weight for extremely poor food intake, represents the evaluation weight for the extremely poor excretion frequency, represents the evaluation weight for the extremely poor number of shouting times, , Indicates according to , , , , and Weight, calculate the monitoring period within, no. Stress index of breeding pigs .

7. A zoning management method for safe and efficient production of large-scale boar stations according to claim 6, characterized in that: Step 3: Index data group Medium, extreme temperature difference Exceeding the temperature threshold , very poor heart rate Heart rate threshold exceeded , Poor water intake Exceeding drinking threshold , Poor food intake Exceeding the feeding threshold , extremely poor excretion frequency Exceeding the discharge threshold , the number of shouting is very poor Exceeding the shouting threshold or stress coefficient Exceeding the stress threshold When The health condition of the breeding pigs is poor, there is a risk of stress, and stress warning signals are generated. It is recommended to isolate them separately.

8. The zoning management method for safe and efficient production of large-scale boar stations according to claim 7 is characterized by: In step 4, the breeding coefficient The calculation process is as follows: Extract the breeding data set The breeding data of the breeding combination will be The age of the boars in the breeding combination is marked as , will The age of sows in the breeding combination is marked as , will The mating times of the mating combination are marked as ; According to the environmental data set, extract the The environmental data of the partition where the breeding combination is located, and the The spatial area of ​​the partition where the breeding combination is located is marked as ; In the formula, Indicates For the absolute difference in age between boars and sows in the breeding combination, It represents the ratio of the absolute difference in age to the number of matings. represents the evaluation weight for the ratio of the absolute difference in age to the number of matings, It represents the ratio of the partition space area to the number of breeding times. Represents the evaluation weight for the ratio of partition space area to breeding times, , Indicates according to and Weight, get The breeding coefficient of the breeding combination .

9. A zoning management method for safe and efficient production of large-scale boar stations according to claim 8, characterized in that: In step 5, the monitoring data set The calculation process is as follows: Extract monitoring cycles based on environmental data sets within, no. The environmental data of each partition and The temperature of each zone is marked as , will The humidity of each zone is marked as , will The noise level of each partition is marked as ; In the formula, and The temperature thresholds The minimum and maximum values ​​of Indicates that the monitoring cycle within, no. Temperature of each partition compared to the temperature threshold , and The humidity threshold The minimum and maximum values ​​of Indicates that the monitoring cycle within, no. Humidity vs. humidity threshold for each zone , and The noise threshold The minimum and maximum values ​​of Indicates that the monitoring cycle within, no. Noise level of each partition compared to the noise threshold .

10. A zoning management method for safe and efficient production of large-scale boar stations according to claim 9, characterized in that: In step 5, if the monitoring data set If any value exceeds the threshold, it means that the environmental level of the partition is poor. It is recommended to optimize the environmental conditions of the partition. Below breeding threshold , indicating that the adaptability of this breeding combination is low, and it is recommended to replace the breeding pigs.

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