Comprehensive selection index formulation and genetic progress prediction method based on multivariate pig breeding system

Abstract

The invention discloses a comprehensive selection index formulation and genetic progress prediction method based on a multivariate pig breeding system. The method comprises the following steps: 1) establishing a bioeconomics model; 2) selecting breeding target characters; 3) constructing a total profit equation of different systems; 4) calculating a character expression discount value by adopting a gene flow method; 5) establishing a character economic value sensitivity analysis method; 6) calculating a relative economic weight and a standardized selection index of the character; and 7) establishing a long-term genetic progress prediction method. According to the method, the breeding target is determined for the selected proper bioeconomics model, the comprehensive selection index is formulated, the comprehensive selection index calculation requirement of a production enterprise under most conditions is met, meanwhile, a long-term genetic progress prediction method is provided, reference can be provided for the expected achievement of a breeding plan in advance, and the method is suitable for large-scale popularization and application. The method provides help for reduction of wrong selection of breeding targets and scientific formulation of selection indexes, and is beneficial to acceleration of genetic improvement of pigs.

Description

Technical Field

[0001] The present invention belongs to the technical field of pig breeding, and in particular relates to a method for formulating a comprehensive selection index and predicting genetic progress based on a multiple pig breeding system. Background Art

[0002] In pig breeding, it is usually necessary to genetically improve multiple traits at the same time. The comprehensive selection index can comprehensively consider the advantages and disadvantages of multiple traits of candidate individuals and maximize economic benefits, so it is widely used.

[0003] The comprehensive selection index is a linear equation consisting of the sum of the estimated breeding value (EBV) and economic weight (w) of each trait. The comprehensive selection index is expressed as follows:

[0004] in, Representative The economic weight of the traits, Representative Estimated breeding values ​​for individual traits.

[0005] Estimated breeding values ​​can be obtained through algorithms such as BLUP (Best Linear Unbiased Estimation) and GBLUP (Genome Best Linear Unbiased Estimation), and there are mature calculation tools. The economic weight of a trait is expressed as the product of the economic value of the trait and the discounted value of the trait performance, and there is still a lack of general calculation tools.

[0006] At present, when formulating the comprehensive selection index of pigs, the method of establishing a bioeconomic model for the terminal commercial pig production system is usually adopted to calculate the economic weight of each trait in the comprehensive selection index. The specific implementation of this method comprehensively considers the production process of breeding sows from use to complete elimination and the entire process of offspring commercial pigs from birth to sale, and establishes a bioeconomic model based on this process. Then, according to the model, the costs and incomes of the entire production process are considered, the total profit of the entire production process is calculated, and then the marginal economic value of each trait is calculated. The marginal economic value of the trait is then used as the economic weight to calculate the comprehensive selection index, which usually lacks the calculation of the discounted value of trait performance.

[0007] In the existing technology, the method of establishing a bioeconomic model for the terminal commercial pig production system does not comprehensively consider the complexity of different pig breeding systems (such as pure line breeding system, binary hybrid system, ternary hybrid system, etc.), lacks the use of gene flow method to calculate the discounted value of trait performance to measure the frequency and time of expression of different traits on the economic value of traits, and lacks a universal user-friendly method and technology that includes all selection index calculation processes, which will have a certain impact on the accuracy of economic weights. At the same time, it is impossible to predict the expected genetic progress of the comprehensive selection index that breeders are more concerned about, which increases the risk in the breeding process and hinders the formulation of the comprehensive selection index and the prediction of genetic progress of pigs. Summary of the invention

[0008] The purpose of the present invention is to overcome the shortcomings of the prior art and to provide a method for formulating a comprehensive selection index and predicting genetic progress based on a multiple pig breeding system, so as to comprehensively consider the complexity of different pig breeding systems, formulate a bioeconomic model and a comprehensive selection index method suitable for different breeding systems, and predict genetic progress based on the calculation results, so as to improve the scientificity and rationality of the formulation of the pig comprehensive selection index.

[0009] The object of the present invention is achieved through the following technical scheme: a method for formulating a comprehensive selection index and predicting genetic progress based on a multivariate pig breeding system, characterized in that it includes the following steps: 1) Use bioeconomic modeling to establish four bioeconomic models: terminal commercial pig production system, pure line breeding system, binary hybrid system and ternary hybrid system; 2) According to the growth process and breeding needs of pigs, growth traits, reproductive traits and carcass traits that are closely related to economy are selected as breeding target traits; 3) Based on the established bioeconomic model, the total profit equations of different systems are constructed to calculate the marginal economic value of traits, among which the total profit of the terminal commercial pig production system is expressed as: ; The total profit equation for pure line breeding system, binary hybrid system and ternary hybrid system is expressed as: ; After establishing the total profit equation of each model, the marginal economic value is calculated based on the population mean of the target trait. The marginal economic value of the target trait is expressed as the change in profit when the trait changes by one unit. The marginal economic value calculation formula is: ; represents the marginal economic value, represents the mean value of the target trait, It represents the profit when the trait mean value increases by 0.1%, It represents the profit when the mean value of the trait decreases by 0.1%. In this case, the marginal economic value of the target trait is approximately equal to the result of partial derivative calculation, and then the marginal economic value of the target trait is obtained; 4) Calculate the discounted value of trait performance using the gene flow method; 5) Establish a sensitivity analysis method for the economic value of traits, increase the feed price parameters, non-feed price parameters and selling price parameters required in the bioeconomic model by 10%, 20%, 30%, 40%, 50% in sequence, and repeatedly use the aforementioned bioeconomic model and economic value calculation method to calculate the economic weight of traits when the price is increased by different percentages, so as to compare the impact of changes in market price parameters on economic weights; 6) After obtaining the economic weight of the trait, the relative economic weight and standardized selection index of the trait are calculated according to the genetic standard deviation of the target trait. The relative economic weight calculation formula is as follows: ; ; in, is the standardized economic weight of trait i, is the genetic standard deviation of trait i, is the relative economic weight of trait i; Then calculate the comprehensive selection index: ; in, is the mean value of the standardized selection index, is the variance-covariance matrix of the selected traits, is the economic weight vector of the trait, Select the standard deviation of the index for normalization; 7) Establish a long-term genetic progress prediction method: To simulate the pig selection and breeding process, QMSim software was first used to simulate and generate genotype data. The genotype data were then preprocessed to remove homozygous sites to obtain the required data. The simulated selection process for breeding pigs was then established based on the genotype data. This process was constructed according to the breeding process for breeding pigs in actual production, and population genetic parameters and comprehensive selection index were used as input parameters to construct the additive effect value of the initial generation of individuals. The next generation of individuals was then selected in a simulated manner, and the genotype data of the next generation of individuals were generated based on the selection results. The breeding value and comprehensive selection index of the offspring were calculated using the genotype data. In each generation, the individual with the highest comprehensive selection index was selected as the offspring. The number of individuals in each generation was set to 3,000 by default, with a male-to-female ratio of 1:1. The breeding values ​​and comprehensive selection index of all generations were stored in the calculation. After the simulated selection was completed, the breeding values ​​and comprehensive selection index of individual traits for the next ten generations were calculated.

[0010] In step 1), the steps to establish the bioeconomic model of the terminal commercial pig production system are as follows: 1. Divide each parity of the breeding process of the breeding sow into a cycle, and each cycle is divided into five processes: insemination, pregnancy, delivery, lactation, and mating interval; 2. According to the initial number of sows and the mortality rate and culling rate of different processes, the number of pigs in all processes is calculated to obtain the change in the number of pigs; 3. According to the number of breeding sows, litter size, and litter live piglets in different cycles, the number of offspring piglets is obtained; 4. The growth process of the offspring piglets is divided into three different periods: lactation period, nursery period, and fattening period. Different growth stages, according to the actual breeding process, the nursery period and fattening period are divided into one to three different stages, and the number of offspring in different stages is calculated according to the mortality rate in different stages; 5. The cost of sows and the income from sow culling are calculated according to the number of sows in each process and the growth, management cost, feed cost and reproduction cost in the breeding process; 6. The growth cost and sales income of piglets are calculated according to the number of piglets in each stage and the feed cost, management cost, production performance and selling price of each stage; 7. The total income and total cost of the model are obtained according to the cost and income of each link.

[0011] In step 1), the steps for establishing a bioeconomic model of a pure-line breeding system are as follows: 1. Divide each parity in the reproductive process of the breeding sow into a cycle, and each cycle is divided into five processes: insemination, pregnancy, delivery, lactation, and mating interval. The interval from the transfer of the breeding sow to the first insemination is divided into a growth process; 2. The growth process of the offspring piglets is divided into three different growth stages: lactation, nursery, and fattening. According to the actual breeding process, the nursery and fattening periods are divided into one to three different stages respectively; during the fattening period, according to the growth performance of the offspring piglets, the better quality offspring are divided into breeding groups, and growth performance measurement and breeding work is carried out. Some offspring with poor growth performance are divided into fattening groups, and the two groups are raised in different fattening units; 3. The source of the reserve pigs for the breeding sows is set to come from The better pigs among the offspring are transferred in or purchased from populations outside the model, and the remaining offspring are sold in various forms; 4. The number of breeding sows in all processes is calculated based on the initial number of sows and the mortality rate and culling rate in different processes. The number of offspring in different stages is calculated based on the number of breeding sows in different cycles, the number of piglets born in a litter, the number of live piglets born in a litter and the mortality rate in different stages; 5. The cost required for sows and the income from sow culling are calculated based on the number of sows in each process and the growth, management cost, feed cost and breeding cost during the feeding process; 6. The growth cost and sales income of piglets are calculated based on the number of piglets in each stage and the feed cost, management cost, production performance and selling price of each stage. The sale of offspring can be divided into different forms such as the sale of breeding pigs and the slaughter and sale of commercial pigs; 7. The total income and total cost of the model are obtained based on the cost and income of each link.

[0012] In step 1), the steps for establishing a bioeconomic model of a binary hybrid system are as follows: 1. The binary hybrid system is divided into two pure line breeds and a breeding group for producing hybrid offspring, a total of three populations, of which one of the two pure line breeds is a maternal breed and the other is a paternal breed, and both are bred using artificial insemination technology; 2. In the three populations, each parity of the breeding process of the breeding sow is divided into a cycle, and each cycle is divided into five processes: insemination, pregnancy, delivery, lactation, and mating interval. The interval from the transfer of the breeding sow to the first insemination is divided into a growth process; 3. The growth process of the offspring piglets is divided into three different growth stages: lactation, nursery and fattening. According to the actual breeding process, the nursery and fattening periods are divided into one to three different stages respectively; in the fattening period of the two pure line breeds, according to the growth performance of the offspring piglets, the better quality offspring are divided into breeding groups, and growth performance determination and breeding work can be carried out. Some offspring with poor growth performance are divided into fattening groups, and the two groups can be used in different breeding stages. The breeding groups are raised in the fattening units, but there is no such division in the breeding groups; 4. In the two pure line breeds, the source of the reserve pigs for breeding sows is set to be transferred from the more excellent pigs in the offspring, or purchased from the population outside the model, and some offspring are allowed to be sold. The source of the reserve pigs for breeding sows in the breeding group is set to be from the offspring of the maternal breed; 5. The number of breeding sows in all processes is calculated based on the initial number of sows and the mortality rate and culling rate in different processes. The number of offspring in different stages is calculated based on the number of breeding sows in different cycles, the number of piglets born in a litter, the number of live piglets born in a litter and the mortality rate in different stages; 6. The cost required for sows and the income from sow culling are calculated based on the number of sows in each process and the growth, management cost, feed cost and breeding cost during the feeding process; 7. The growth cost and sales income required for piglets are calculated based on the number of piglets in each stage and the feed cost, management cost, production performance and selling price of each stage. The sale of offspring can be divided into different forms of breeding pigs and commercial pigs slaughtered and sold; 8. The total income and total cost of the model are obtained based on the cost and income of each link.

[0013] In step 1), the steps for establishing the bioeconomic model of the three-way hybrid system are as follows: 1. Divide the three-way hybrid system into three pure line breeds and two breeding groups for producing hybrid offspring, a total of five populations, of which the three pure line breeds include the maternal breed, the first paternal breed and the terminal paternal breed, and the two breeding groups include the breeding group A for producing binary hybrids and the breeding group A×B for producing three-way hybrid offspring, both of which are bred using artificial insemination technology; 2. In the five populations, each parity of the breeding process of the breeding sows is divided into a cycle, and each cycle is divided into insemination, pregnancy, The five processes of parturition, lactation and mating interval are divided into the interval from the transfer of breeding sows to the first insemination as the growth process; 3. The growth process of offspring piglets is divided into three different growth stages: lactation, nursery and fattening. According to the actual breeding process, the nursery and fattening periods are divided into one to three different stages respectively; in the fattening period of the three pure breeds, according to the growth performance of offspring piglets, the better offspring are divided into breeding groups, and growth performance measurement and breeding work can be carried out. Some offspring with poor growth performance are divided into fattening groups. The two groups They can be raised in different fattening units, but there is no such division for breeding groups; 4. In the three pure breeds, the source of the breeding sows is set to be the transfer of the better pigs from the offspring, or purchased from the population outside the model, and some offspring are allowed to be sold; the source of the breeding sows in breeding group A is set to be the offspring of the maternal breed, and the source of the breeding sows in breeding group A×B is set to be the offspring of breeding group A; 5. The number of breeding sows in all processes is calculated based on the initial number of sows and the mortality rate and elimination rate of different processes, and the number of breeding sows in different cycles is calculated based on the number of breeding sows , litter size, litter live piglets and mortality rate at different stages to calculate the number of offspring at different stages; 6. According to the number of sows in each process and the growth, management cost, feed cost and reproduction cost during the breeding process, the cost of sows and the income from sow culling are calculated; 7. According to the number of piglets in each stage and the feed cost, management cost, production performance and selling price at each stage, the growth cost and sales income of piglets are calculated. The sale of offspring can be divided into different forms of breeding pigs and commercial pigs; 8. The total income and total cost of the model are obtained according to the cost and income of each link.

[0014] In step 2), the growth traits include the average weight of piglets at weaning, the average daily weight gain before weaning, the weight at the end of the nursery period, the average daily weight gain during the nursery period, the average daily weight gain during the growing period, the number of days in the growing period, the lifetime average daily weight gain, the age at reaching the target weight, the feed conversion rate during the nursery period, the feed conversion rate during the growing period, the survival rate during the nursery period and the survival rate during the growing period.

[0015] In step 2), the reproductive traits include total piglet number, number of live piglets born per litter, number of weaned piglets, survival rate at birth, survival rate before weaning, age at first mating of gilts, average conception rate, interval from weaning to conception and average productive life span of sows.

[0016] In step 2), the carcass traits include dressing percentage, lean meat percentage, backfat thickness, loin depth and loin area.

[0017] Step 4) includes the following steps: first, according to the structure of different breeding systems, livestock are divided into different age-sex groups with half a year as the time unit, and the corresponding transmission matrix P is constructed, in which the rows represent all age-sex groups at time t, the columns represent all age-sex groups at time t-1, and the elements of each row satisfy the sum of 1. The matrix describes the growth and reproduction process of livestock, and then the vector m is defined to calculate the gene transmission process in each age-sex group. The formula is as follows:

[0018] For each trait, a realization vector h is defined, whose elements represent the proportion of the number of sows expressed in different age-sex groups of a given trait to the total number of sows. Assuming that the trait realization vector h remains unchanged, the discounted value of trait expression is calculated using the following formula:

[0019] In the formula, represents the discounted value of trait performance of trait i in sex group j, D is the breeding investment period, is the realization vector of trait i, is the gene probability vector of sex group j at time t, r is the discount factor, and t is the time of trait expression; Then multiply the discounted value of trait performance by the marginal economic value of the trait to obtain the economic weight of the trait:

[0020] in is the economic weight of trait i, is the marginal economic value of trait i; in the binary hybrid system and the ternary hybrid system, the economic weights of two or three varieties are calculated at the same time, and the economic weights of multiple varieties are obtained at the same time.

[0021] The beneficial effects of the present invention are as follows: the present invention determines breeding objectives and formulates a comprehensive selection index for a selected appropriate bioeconomic model, thereby meeting the comprehensive selection index calculation needs of production enterprises in most cases. At the same time, the present invention provides a long-term genetic progress prediction method, which can provide a reference for the expected results of the breeding plan in advance, help reduce the erroneous selection of breeding objectives and the scientific formulation of selection indices, and help accelerate the genetic improvement of pigs. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 It is the structural framework of the bioeconomic model of the ternary hybrid system; Figure 2 It is a flowchart of the long-term genetic progress prediction method; Figure 3 It is a block diagram of software function modules constructed based on the method of the present invention; Figure 4 The present invention is a flowchart of a method for using the software constructed based on the method of the present invention. DETAILED DESCRIPTION

[0023] The present invention is described in detail below in conjunction with the accompanying drawings.

[0024] Example 1 Comprehensive selection index formulation and genetic progress prediction method based on multivariate pig breeding system A method for formulating a comprehensive selection index and predicting genetic progress based on a multivariate pig breeding system comprises the following steps: 1) Use bioeconomic model methods to establish four bioeconomic models: terminal commercial pig production system, pure line breeding system, binary hybrid system and ternary hybrid system.

[0025] The pig bioeconomic model refers to dividing the production system into different stages according to the production process, and through economic benefit analysis, the income and expenditure of each component are considered separately, and expressed in the form of a group of equations, so as to obtain the marginal benefits of each trait. The terminal commercial pig production system is a system that includes the growth and reproduction of breeding sows and the growth process of their offspring commercial pigs. The pure line breeding system is a system that includes the growth and reproduction process of one breed. The binary hybrid system is a system that includes the growth and reproduction of two breeds and the growth and reproduction process of their hybrid offspring. The ternary hybrid system is a system that includes the growth and reproduction of three breeds and the growth and reproduction process of their binary hybrid offspring and ternary hybrid offspring. Artificial insemination technology is used between all breeds to ensure that the profits of the entire system can be calculated. At the same time, the data required in the model construction process are used as the input parameters of the model.

[0026] The details of establishing different bioeconomic models are as follows: The steps to establish a bioeconomic model for the terminal commercial pig production system are as follows: 1. Divide each parity of the breeding process of the breeding sow into a cycle, and each cycle is divided into five processes: insemination, pregnancy, delivery, lactation, and mating interval; 2. According to the initial number of sows and the mortality rate and culling rate of different processes, the number of pigs in all processes is calculated to obtain the change in the number of pigs; 3. According to the number of breeding sows, litter size, and litter live piglet number in different cycles, the number of offspring piglets is obtained; 4. The growth process of the offspring piglets is divided into three different life periods: lactation period, nursery period, and fattening period. 1. In the long stage, according to the actual breeding process, the nursery period and fattening period are divided into one to three different stages, and the number of offspring in different stages is calculated according to the mortality rate in different stages; 5. The cost of sows and the income from sow culling are calculated according to the number of sows in each process and the growth, management cost, feed cost and reproduction cost in the breeding process; 6. The growth cost and sales income of piglets are calculated according to the number of piglets in each stage and the feed cost, management cost, production performance and selling price of each stage; 7. The total income and total cost of the model are obtained according to the cost and income of each link.

[0027] The steps to establish a bioeconomic model for a pureline breeding system are as follows: 1. Divide each parity in the reproductive process of the breeding sow into a cycle. Each cycle is divided into five processes: insemination, pregnancy, delivery, lactation, and mating interval. The interval from the transfer of the breeding sow to the first insemination is divided into a growth process; 2. Divide the growth process of the offspring piglets into three different growth stages: lactation, nursery, and fattening. According to the actual breeding process, the nursery and fattening periods are divided into one to three different stages respectively; during the fattening period, according to the growth performance of the offspring piglets, the better quality offspring are divided into breeding groups, and growth performance measurement and breeding work is carried out. Some offspring with poor growth performance are divided into fattening groups, and the two groups are raised in different fattening units; 3. The source of the reserve pigs for the breeding sows is set as the offspring. The more outstanding pigs are transferred in or purchased from populations outside the model, and the remaining offspring are sold in various forms; 4. The number of breeding sows in all processes is calculated based on the initial number of sows and the mortality rate and culling rate in different processes; the number of offspring in different stages is calculated based on the number of breeding sows in different cycles, the number of piglets born in a litter, the number of live piglets born in a litter and the mortality rate in different stages; 5. The cost required for sows and the income from sow culling are calculated based on the number of sows in each process and the growth, management cost, feed cost and breeding cost during the feeding process; 6. The growth cost and sales income of piglets are calculated based on the number of piglets in each stage and the feed cost, management cost, production performance and selling price of each stage. The sale of offspring can be divided into different forms such as the sale of breeding pigs and the slaughter and sale of commercial pigs; 7. The total income and total cost of the model are obtained based on the cost and income of each link.

[0028] The steps to establish a bioeconomic model for a binary hybrid system are as follows: 1. Divide the binary hybrid system into two pure line breeds and a breeding group for producing hybrid offspring, a total of three populations, of which one of the two pure line breeds is a maternal breed and the other is a paternal breed, and both are bred using artificial insemination technology; 2. In the three populations, each parity of the breeding process of the breeding sow is divided into a cycle, and each cycle is divided into five processes: insemination, pregnancy, delivery, lactation, and mating interval. The interval from the transfer of the breeding sow to the first insemination is divided into a growth process; 3. The growth process of the offspring piglets is divided into three different growth stages: lactation, nursery and fattening. According to the actual breeding process, the nursery and fattening periods are divided into one to three different stages respectively; in the fattening period of the two pure line breeds, according to the growth performance of the offspring piglets, the better quality offspring are divided into breeding groups, and growth performance determination and breeding work can be carried out. Some offspring with poor growth performance are divided into fattening groups, and the two groups can be carried out in different fattening units. 4. In the two pure line breeds, the source of the reserve pigs for breeding sows is set to be transferred from the more excellent pigs in the offspring, or purchased from the population outside the model, and some offspring are allowed to be sold, and the source of the reserve pigs for breeding sows in the breeding group is set to be from the offspring of the maternal breed; 5. The number of breeding sows in all processes is calculated according to the initial number of sows and the mortality rate and culling rate in different processes, and the number of offspring in different stages is calculated according to the number of breeding sows in different cycles, the number of piglets born in a litter, the number of live piglets born in a litter and the mortality rate in different stages; 6. The cost required for sows and the income from sow culling are calculated according to the number of sows in each process and the growth, management cost, feed cost and breeding cost during the feeding process; 7. The growth cost and sales income of piglets are calculated according to the number of piglets in each stage and the feed cost, management cost, production performance and selling price of each stage. The sale of offspring can be divided into different forms of breeding pigs and commercial pigs slaughtered and sold; 8. The total income and total cost of the model are obtained according to the cost and income of each link.

[0029] See also Figure 1The steps to establish the bioeconomic model of the ternary hybrid system are as follows: 1. Divide the ternary hybrid system into three pure line breeds and two breeding groups for producing hybrid offspring, a total of five populations, of which the three pure line breeds include the maternal breed A, the first paternal breed B and the terminal paternal breed C, and the two breeding groups (expansion breeding groups) include the breeding group A after producing binary hybrids and the breeding group A×B for producing ternary hybrid offspring, all of which are bred using artificial insemination technology; 2. In the five populations, each parity of the breeding process of the breeding sows is divided into a cycle, and each cycle is divided into insemination, pregnancy, and 1. The growth process of offspring piglets is divided into three different growth stages: lactation, nursery and fattening. According to the actual breeding process, the nursery and fattening periods are divided into one to three different stages respectively. During the fattening period of the three pure-line breeds, the offspring with better quality are divided into breeding groups according to the growth performance of the offspring piglets, and growth performance measurement and breeding work can be carried out. Some offspring with poorer growth performance are divided into fattening groups, and the two groups are divided into breeding groups. The groups can be raised in different fattening units, but there is no such division for breeding groups; 4. In the three pure breeds, the source of the breeding sows is set to be the transfer of the better pigs from the offspring, or purchased from the population outside the model, and some offspring are allowed to be sold; the source of the breeding sows in breeding group A is set to be the offspring of the maternal breed, and the source of the breeding sows in breeding group A×B is set to be the offspring of breeding group A; 5. The number of breeding sows in all processes is calculated based on the initial number of sows and the mortality rate and elimination rate of different processes, and the number of breeding sows in different cycles is calculated based on the number of breeding sows , litter size, litter live piglets and mortality rate at different stages to calculate the number of offspring at different stages; 6. According to the number of sows in each process and the growth, management cost, feed cost and reproduction cost during the breeding process, the cost of sows and the income from sow culling are calculated; 7. According to the number of piglets in each stage and the feed cost, management cost, production performance and selling price at each stage, the growth cost and sales income of piglets are calculated. The sale of offspring can be divided into different forms of breeding pigs and commercial pigs; 8. The total income and total cost of the model are obtained according to the cost and income of each link.

[0030] 2) According to the growth process and breeding needs of live pigs, growth traits, reproductive traits and carcass traits that are closely related to the economy are selected as breeding target traits.

[0031] Growth traits include average weaning weight of piglets, average daily weight gain before weaning, weight at the end of the nursery period, average daily weight gain in the nursery period, average daily weight gain in the growing period, number of days in the growing period, lifetime average daily weight gain, age at reaching target weight, feed conversion rate in the nursery period, feed conversion rate in the growing period, survival rate in the nursery period and survival rate in the growing period.

[0032] Reproductive traits include total piglet size, litter size alive, number of piglets weaned, survival at birth, pre-weaning survival, age at first mating of gilts, average conception rate, weaning-to-conception interval and average productive life span of sows.

[0033] Carcass traits include dressing percentage, lean meat percentage, backfat thickness, loin depth and loin area.

[0034] Among the above 26 breeding target traits, growth traits reflect the growth potential of animals. The improvement of such traits can reduce the cost in the production process and is necessary in the formulation of the selection index. Reproductive traits reflect the reproductive ability of sows. The improvement of such traits can reduce the reproductive cost in large-scale breeding and play an important role in the genetic improvement of specialized maternal lines. The improvement of carcass traits helps to increase the lean meat content and improve the quality of pork.

[0035] The above 26 different growth, reproduction and carcass traits are provided for users to choose from. Users can freely select the required traits according to breeding needs.

[0036] 3) Based on the established bioeconomic model, the total profit equations of different systems are constructed to calculate the marginal economic value of traits, among which the total profit of the terminal commercial pig production system is expressed as: ; The total profit equation for pure line breeding system, binary hybrid system and ternary hybrid system is expressed as: ; After establishing the total profit equation of each model, the marginal economic value is calculated based on the population mean of the target trait. The marginal economic value of the target trait is expressed as the change in profit when the trait changes by one unit. The marginal economic value calculation formula is: ; represents the marginal economic value, represents the mean value of the target trait, It represents the profit when the trait mean value increases by 0.1%, It represents the profit when the mean value of the trait decreases by 0.1%. In this case, the marginal economic value of the target trait is approximately equal to the result of the partial derivative calculation, and then the marginal economic value of the target trait is obtained.

[0037] 4) Calculate the discounted value of trait performance using the gene flow method: First, according to the structure of different breeding systems, livestock are divided into different age-sex groups with half a year as the time unit, and the corresponding transmission matrix P is constructed, where the rows represent all age-sex groups at time t, and the columns represent all age-sex groups at time t-1. The elements of each row satisfy the sum of 1. The matrix describes the growth and reproduction process of livestock, and then defines the vector m to calculate the gene transmission process in each age-sex group. The formula is as follows:

[0038] For each trait, a realization vector h is defined, whose elements represent the proportion of the number of sows expressed in different age-sex groups of a given trait to the total number of sows. Assuming that the trait realization vector h remains unchanged, the discounted value of trait expression is calculated using the following formula:

[0039] In the formula, represents the discounted value of trait performance of trait i in sex group j, D is the breeding investment period, is the realization vector of trait i, is the gene probability vector of sex group j at time t, r is the discount factor, and t is the time of trait expression; Then multiply the discounted value of trait performance by the marginal economic value of the trait to obtain the economic weight of the trait:

[0040] in is the economic weight of trait i, is the marginal economic value of trait i; in the binary hybrid system and the ternary hybrid system, the economic weights of two or three varieties are calculated at the same time, and the economic weights of multiple varieties are obtained at the same time.

[0041] 5) Establish a sensitivity analysis method for economic values ​​of traits, increase the feed price parameters, non-feed price parameters and selling price parameters required in the bioeconomic model by 10%, 20%, 30%, 40% and 50% respectively, and repeatedly use the aforementioned bioeconomic model and economic value calculation method to calculate the economic weights of traits when the prices are increased by different percentages, so as to compare the impact of changes in market price parameters on the economic weights.

[0042] 6) After obtaining the economic weight of the trait, the relative economic weight and standardized selection index of the trait are calculated according to the genetic standard deviation of the target trait. The relative economic weight calculation formula is as follows:

[0043]

[0044] in, is the standardized economic weight of trait i, is the genetic standard deviation of trait i, is the relative economic weight of trait i; Then calculate the comprehensive selection index:

[0045] in, is the mean value of the standardized selection index, is the variance-covariance matrix of the selection index, is the economic weight vector of the trait, Select the standard deviation of the index for normalization.

[0046] 7) Establish long-term genetic progress prediction methods: e.g. Figure 2 As shown in the figure, to simulate the pig selection breeding process, the QMSim software is first used to simulate and generate genotype data, and then the genotype data is preprocessed to remove homozygous sites to obtain the required data. Then, the pig simulation selection process is established based on the genotype data. The process is constructed according to the pig selection process in actual production, and the population genetic parameters and comprehensive selection index are used as input parameters to construct the additive effect value of the initial generation of individuals. Then, the next generation of individuals are selected by simulation, and the genotype data of the next generation of individuals are generated according to the selection results. The breeding value and comprehensive selection index of the offspring are calculated using the genotype data. In each generation, the individual with the highest comprehensive selection index is selected as the offspring. The number of individuals in each generation is 3000 by default, and the male-to-female ratio is 1:1. The breeding values ​​and comprehensive selection index of all generations are stored in the calculation. After the simulation selection is completed, the breeding values ​​and comprehensive selection index of individual traits of the next ten generations are calculated.

[0047] Example 2 Constructing software function modules based on the method of the present invention like Figure 3 As shown, the software function modules constructed based on the method of the present invention include: User: used to select target traits and input parameters required by the bioeconomic model, including growth traits, reproductive traits and carcass traits, as well as growth performance parameters, management parameters and market economic parameters; used to input genetic parameters of target traits; used to display calculation results; Bioeconomic model module: contains four bioeconomic models of different breeding systems. All bioeconomic models comprehensively consider the costs and incomes of the entire system and establish a total profit equation to calculate the marginal economic value; Trait performance discounted value calculation module: used to calculate the trait performance discounted value of traits during the breeding investment period, using the gene flow method; Trait economic weight and sensitivity analysis calculation module: Calculate the economic value of the target trait through the bioeconomic model, and multiply it with the corresponding trait performance discount value to obtain the economic weight; calculate the economic weight when the market price parameter is increased by a certain percentage; Relative economic weight and standardized comprehensive selection index calculation module: calculate the relative economic weight of traits and display the results in the form of tables and graphs; calculate the standardized comprehensive selection index and display the results.

[0048] Long-term genetic progress calculation module: used to calculate the genetic progress trend and comprehensive selection index change trend of each trait in the next ten generations under the current comprehensive selection index and population parameters.

[0049] After the user inputs the data, the bioeconomic model module is first called to calculate the marginal economic value of the trait, and then the trait performance discounted value calculation module is called to calculate the trait performance discounted value. After that, the calculation results of the two modules are transmitted to the trait economic weight and sensitivity analysis calculation module to calculate the trait economic weight and sensitivity analysis. After obtaining the appropriate economic weight, the relative economic weight and standardized comprehensive selection index calculation module is called to calculate the relative economic weight and the standardized comprehensive selection index, and the results are transmitted to the user end to display the results. According to the results, you can choose whether to call the long-term genetic progress calculation module to calculate the genetic progress trend and comprehensive selection index change trend of each trait in the next ten generations.

[0050] Example 3 Specific use of the software constructed based on the method of the present invention like Figure 4 As shown, the specific method of using the software constructed based on the method of the present invention includes the following steps: 1) Select an appropriate bioeconomic model according to the breeding plan. Users need to select the most appropriate model from the four bioeconomic models based on the breeding plan and actual use. The terminal commercial pig production system model has a relatively simple structure and requires less production data. It has good support for calculating the selection index of a certain variety in a complex breeding system. Different breeding systems can use this model to calculate economic weights. The pure line breeding system model is only applicable to the formulation of a comprehensive selection index in the breeding process of a single pure line variety, and the binary hybrid system model is only applicable to the formulation of a comprehensive selection index for a binary hybrid breeding system. The ternary hybrid system model is only applicable to the most common ternary hybrid breeding system in China. This bioeconomic model can be used to calculate the comprehensive selection index of three core group varieties at the same time. The calculation of the comprehensive selection index of the entire system and the prediction of long-term genetic progress can be completed in one calculation, and the calculated economic weight is more realistic.

[0051] 2) Select breeding target traits. The selectable target traits change dynamically according to the bioeconomic model selected in the first step. If the terminal commercial pig model and pureline breeding system model are selected, 26 different growth, reproduction and carcass traits are displayed for users to choose. If the binary hybrid system model is selected, the maternal breeds display 26 different growth, reproduction and carcass traits for users to choose. Considering that the paternal breeds generally do not select reproductive traits, the paternal breeds display 17 different growth and carcass traits for users to choose. If it is a ternary hybrid system model, the maternal and first sires display 26 different growth, reproduction and carcass traits for users to choose, and the terminal sires display 17 different growth and carcass traits for users to choose. The target traits need to be selected according to actual breeding needs.

[0052] 3) Input the parameters required for the model. The parameters required for the model need to be collected by the user according to the actual production process. The required parameters include growth performance parameters, management parameters and market economic parameters. All parameters are necessary parameters for constructing the total profit equation of the bioeconomic model and calculating the marginal economic value of traits. Growth performance parameters refer to the death elimination rate at each stage, daily feed intake and other parameters that measure growth performance. Management parameters refer to parameters that indicate management level, such as population size and the number of growth days at each stage. Market economic parameters refer to price parameters such as feed prices, fixed costs and medical costs. These data can be classified and summarized before being input to the user end.

[0053] 4) Calculate economic weights and sensitivity analysis and display the results. The user clicks the "Calculate" button to start the calculation program, calculate the economic weight of the selected target trait, and calculate the economic weight when the feed price, non-feed price and selling price increase by a certain percentage (10%, 20%, 30%, 40%, 50%), and display the calculation results in the form of tables and graphs for users to analyze the economic weight of the target trait. Specifically, first determine the calculation model according to the selected bioeconomic model type, and then use the input parameters to calculate the total profit of the entire breeding system. According to the selection order of the selected traits, calculate the marginal economic value of the traits in turn. After the economic value calculation of the selected traits is completed, call the trait performance discount value calculation module to calculate the trait performance discount value of the selected traits. Multiply the marginal economic value of the selected trait by the corresponding trait performance discount value to obtain the economic weight of the selected trait. Then change the feed price, non-feed price and selling price parameters by a certain proportion in turn, repeat the calculation process, and obtain the changed economic weight; 5) Input the genetic parameters of the target trait. According to the selected target trait, input the variance-covariance matrix of the trait to provide parameters for the next step of calculating the relative economic weight of the trait and the standardized selection index; 6) Calculate the relative economic weight and standardized comprehensive selection index and display the results. The user specifies the mean and standard deviation of the standardized selection index. The default mean is 100 and the standard deviation is 25. Then click the "Calculate" button to start the calculation program to calculate the relative economic weight and standardized comprehensive selection index of the trait. The relative economic weight is expressed in the form of a table plus a graph, and the comprehensive selection index is expressed in the form of a calculation formula. Specifically, first calculate the standard deviation of the trait based on the input genetic parameters, and then calculate the ratio of the product of the economic weight of the trait and the genetic standard deviation to the sum of the products of the economic weights of all traits and the genetic standard deviation, that is, the relative economic weight of the trait. Then calculate the standardized comprehensive selection index based on the input mean and standard deviation of the selection index; 7) Calculate the long-term genetic progress and display the results. In this embodiment, the user clicks the "Calculate" button to start the calculation program. If the binary hybrid system and the ternary hybrid system are selected, the long-term genetic progress of different varieties needs to be calculated separately. This step uses the parameters input in the above step and the calculated comprehensive selection index as input parameters, simulates the selection process of the next ten generations, and calculates the average value of the breeding value and selection index of each generation, and displays the results in the form of a line graph.

[0054] Finally, it should be noted that the above content is only used to illustrate the technical solution of the present invention, rather than to limit the scope of protection of the present invention. Simple modifications or equivalent substitutions of the technical solution of the present invention by ordinary technicians in this field do not deviate from the essence and scope of the technical solution of the present invention.

Claims

1. A method for formulating a comprehensive selection index and predicting genetic progress based on a multivariate pig breeding system, characterized in that The steps include: 1) Use bioeconomic modeling to establish four bioeconomic models: terminal commercial pig production system, pure line breeding system, binary hybrid system and ternary hybrid system; 2) According to the growth process and breeding needs of pigs, growth traits, reproductive traits and carcass traits that are closely related to economy are selected as breeding target traits; 3) Based on the established bioeconomic model, the total profit equation of different systems is constructed to calculate the marginal economic value of traits, among which the total profit of the terminal commercial pig production system is expressed as: ; The total profit equation for pure line breeding system, binary hybrid system and ternary hybrid system is expressed as: ; After establishing the total profit equation of each model, the marginal economic value is calculated based on the population mean of the target trait. The marginal economic value of the target trait is expressed as the change in profit when the trait changes by one unit. The marginal economic value calculation formula is: ; represents the marginal economic value, represents the mean value of the target trait, It represents the profit when the trait mean value increases by 0.1%, It represents the profit when the mean value of the trait decreases by 0.1%. In this case, the marginal economic value of the target trait is approximately equal to the result of partial derivative calculation, and then the marginal economic value of the target trait is obtained; 4) Calculate the discounted value of trait performance using the gene flow method; 5) Establish a sensitivity analysis method for the economic value of traits, increase the feed price parameters, non-feed price parameters and selling price parameters required in the bioeconomic model by 10%, 20%, 30%, 40%, 50% in sequence, and repeatedly use the aforementioned bioeconomic model and economic value calculation method to calculate the economic weight of traits when the price is increased by different percentages, so as to compare the impact of changes in market price parameters on economic weights; 6) After obtaining the economic weight of the trait, the relative economic weight and standardized selection index of the trait are calculated according to the genetic standard deviation of the target trait. The relative economic weight calculation formula is as follows: ; ； in, is the standardized economic weight of trait i, is the genetic standard deviation of trait i, is the relative economic weight of trait i; Then calculate the comprehensive selection index: ； in, is the mean value of the standardized selection index, is the variance-covariance matrix of the selected traits, is the economic weight vector of the trait, Select the standard deviation of the index for normalization; 7) Establish a long-term genetic progress prediction method: To simulate the pig selection and breeding process, QMSim software was first used to simulate and generate genotype data. The genotype data were then preprocessed to remove homozygous sites to obtain the required data. The simulated selection process for breeding pigs was then established based on the genotype data. This process was constructed according to the breeding process for breeding pigs in actual production, and population genetic parameters and comprehensive selection index were used as input parameters to construct the additive effect value of the initial generation of individuals. The next generation of individuals was then selected in a simulated manner, and the genotype data of the next generation of individuals were generated based on the selection results. The breeding value and comprehensive selection index of the offspring were calculated using the genotype data. In each generation, the individual with the highest comprehensive selection index was selected as the offspring. The number of individuals in each generation was set to 3,000 by default, with a male-to-female ratio of 1:

1. The breeding values ​​and comprehensive selection index of all generations were stored in the calculation. After the simulated selection was completed, the breeding values ​​and comprehensive selection index of individual traits for the next ten generations were calculated.

2. The method for formulating a comprehensive selection index and predicting genetic progress based on a multivariate pig breeding system according to claim 1, characterized in that: In step 1), the steps to establish the bioeconomic model of the terminal commercial pig production system are as follows:

1. Divide each parity of the breeding process of the breeding sow into a cycle, and each cycle is divided into five processes: insemination, pregnancy, delivery, lactation, and mating interval; 2. Calculate the number of pigs in all processes based on the initial number of sows and the mortality and culling rates in different processes, and obtain the change in the number of pigs; 3. The number of offspring piglets is obtained according to the number of sows, litter size, and live piglets in different cycles; 4. The growth process of offspring piglets is divided into three different growth stages: lactation, nursery, and fattening. According to the actual breeding process, the nursery and fattening periods are divided into one to three different stages respectively, and the number of offspring in different stages is calculated according to the mortality rate in different stages; 5. Calculate the cost of sows and the income from sow culling based on the number of sows in each stage and their growth, management cost, feed cost and reproduction cost during the breeding process; 6. Calculate the cost of piglet growth and sales income based on the number of piglets in each stage and the feed cost, management cost, production performance and sales price at each stage; 7. Obtain the total revenue and total cost of the model based on the cost and revenue of each link.

3. The method for formulating a comprehensive selection index and predicting genetic progress based on a multivariate pig breeding system according to claim 1, characterized in that: In step 1), the steps for establishing a bioeconomic model of a pure-line breeding system are as follows:

1. Divide each parity of the breeding process of breeding sows into a cycle, and divide each cycle into five processes: insemination, pregnancy, parturition, lactation, and mating interval. Divide the interval from the transfer of breeding sows to the first insemination into the growth process; 2. The growth process of offspring piglets is divided into three different growth stages: lactation, nursery and fattening. According to the actual breeding process, the nursery and fattening periods are divided into one to three different stages respectively; during the fattening period, according to the growth performance of offspring piglets, the better-quality offspring are divided into breeding groups, and growth performance measurement and breeding work are carried out. Some offspring with poor growth performance are divided into fattening groups, and the two groups are raised in different fattening units; 3. The source of reserve pigs for breeding sows is set to be transferred from the better pigs in the offspring, or purchased from populations outside the model, and the remaining offspring are sold in various forms; 4. The number of breeding sows in all processes is calculated based on the initial number of sows and the mortality rate and culling rate in different processes. The number of offspring in different stages is calculated based on the number of breeding sows, litter size, litter size alive, and mortality rate in different stages in different cycles; 5. Calculate the cost of sows and the income from sow culling based on the number of sows in each process and their growth, management cost, feed cost and reproduction cost during the breeding process; 6. Calculate the growth cost and sales income of piglets based on the number of piglets in each stage and the feed cost, management cost, production performance and sales price at each stage. The sales of offspring can be divided into different forms: sales of breeding pigs and sales of commercial pigs; 7. Obtain the total revenue and total cost of the model based on the cost and revenue of each link.

4. The method for formulating a comprehensive selection index and predicting genetic progress based on a multivariate pig breeding system according to claim 1, characterized in that: In step 1), the steps of establishing the bioeconomic model of the binary hybrid system are as follows:

1. Divide the binary hybrid system into two pure-line varieties and a breeding group for producing hybrid offspring, a total of three populations, of which one of the two pure-line varieties is a maternal variety and the other is a paternal variety, and both are bred using artificial insemination technology; 2. In the three populations, each parity of the breeding process of the breeding sows is divided into a cycle, and each cycle is divided into five processes: insemination, pregnancy, delivery, lactation, and mating interval. The interval from the transfer of the breeding sows to the first insemination is divided into the growth process; 3. The growth process of the offspring piglets is divided into three different growth stages: lactation period, nursery period and fattening period. According to the actual breeding process, the nursery period and fattening period are divided into one to three different stages respectively; in the fattening period of the two pure breeds, according to the growth performance of the offspring piglets, the better quality offspring are divided into breeding groups, and growth performance measurement and breeding can be carried out. Some offspring with poor growth performance are divided into fattening groups. The two groups can be raised in different fattening units, and there is no such division in the breeding group; 4. In the two pure line breeds, the source of the breeding sows' replacement pigs is set to be the transfer of the better pigs from the offspring, or purchased from the population outside the model, and some offspring are allowed to be sold. The source of the breeding sows' replacement pigs in the breeding group is set to be the offspring of the maternal breed; 5. The number of breeding sows in all processes is calculated based on the initial number of sows and the mortality rate and culling rate in different processes. The number of offspring in different stages is calculated based on the number of breeding sows, litter size, litter size alive, and mortality rate in different stages in different cycles; 6. Calculate the cost of sows and the income from sow culling based on the number of sows in each process and their growth, management cost, feed cost and reproduction cost during the breeding process; 7. Calculate the growth cost and sales income of piglets based on the number of piglets in each stage and the feed cost, management cost, production performance and sales price at each stage. The sales of offspring can be divided into different forms: sales of breeding pigs and sales of commercial pigs; 8. Obtain the total revenue and total cost of the model based on the cost and revenue of each link.

5. According to claim 1, a method for formulating a comprehensive selection index and predicting genetic progress based on a multi-element pig breeding system is characterized in that: in step 1), the steps of establishing a bioeconomic model of a three-way hybrid system are as follows:

1. The three-way hybrid system is divided into three pure line breeds and two breeding groups for producing hybrid offspring, a total of five populations, wherein the three pure line breeds include a maternal breed, a first paternal breed and a terminal paternal breed, and the two breeding groups include a breeding group A for producing binary hybrids and a breeding group A×B for producing three-way hybrid offspring, both of which are bred using artificial insemination technology; 2. In the five populations, each parity in the breeding process of the breeding sow is divided into a cycle, and each cycle is divided into five processes of insemination, pregnancy, delivery, lactation, and mating interval. The interval from the transfer of the breeding sow to the start of the first insemination is divided into Growth process; 3. The growth process of offspring piglets is divided into three different growth stages: lactation, nursery and fattening. According to the actual breeding process, the nursery and fattening periods are divided into one to three different stages respectively; in the fattening period of the three pure line breeds, according to the growth performance of the offspring piglets, the better quality offspring are divided into breeding groups, and growth performance measurement and breeding work can be carried out. Some offspring with poor growth performance are divided into fattening groups. The two groups can be raised in different fattening units, and there is no such division for breeding groups; 4. In the three pure line breeds, the source of the reserve pigs of the breeding sows is set to be transferred from the more outstanding pigs in the offspring, or purchased from the population outside the model, and some offspring are allowed to be sold; the source of the reserve pigs of the breeding sows in the breeding group A is set to be from the offspring of the maternal breed, and the source of the reserve pigs of the breeding sows in the breeding group A×B is set to be from the offspring of the breeding group A; 5. The number of breeding sows in all processes is calculated based on the initial number of sows and the mortality rate and culling rate in different processes. The number of offspring in different stages is calculated based on the number of breeding sows, litter size, litter size alive, and mortality rate in different stages in different cycles; 6. Calculate the cost of sows and the income from sow culling based on the number of sows in each process and their growth, management cost, feed cost and reproduction cost during the breeding process; 7. Calculate the growth cost and sales income of piglets based on the number of piglets in each stage and the feed cost, management cost, production performance and sales price at each stage. The sales of offspring can be divided into different forms: sales of breeding pigs and sales of commercial pigs; 8. Obtain the total revenue and total cost of the model based on the cost and revenue of each link.

6. The method for formulating a comprehensive selection index and predicting genetic progress based on a multivariate pig breeding system according to claim 1, characterized in that: In step 2), the growth traits include the average weight of piglets at weaning, the average daily weight gain before weaning, the weight at the end of the nursery period, the average daily weight gain during the nursery period, the average daily weight gain during the growing period, the number of days in the growing period, the lifetime average daily weight gain, the age at reaching the target weight, the feed conversion rate during the nursery period, the feed conversion rate during the growing period, the survival rate during the nursery period and the survival rate during the growing period.

7. The method for formulating a comprehensive selection index and predicting genetic progress based on a multivariate pig breeding system according to claim 1, characterized in that: In step 2), the reproductive traits include total piglet number, number of live piglets born per litter, number of weaned piglets, survival rate at birth, survival rate before weaning, age at first mating of gilts, average conception rate, interval from weaning to conception and average productive life span of sows.

8. The method for formulating a comprehensive selection index and predicting genetic progress based on a multivariate pig breeding system according to claim 1, characterized in that: In step 2), the carcass traits include dressing rate, lean meat rate, back fat thickness, loin depth and loin area.

9. The method for formulating a comprehensive selection index and predicting genetic progress based on a multivariate pig breeding system according to claim 1, characterized in that: Step 4) includes the following steps: first, according to the structure of different breeding systems, livestock are divided into different age-sex groups with half a year as the time unit, and the corresponding transmission matrix P is constructed, in which the rows represent all age-sex groups at time t, the columns represent all age-sex groups at time t-1, and the elements of each row satisfy the sum of 1. The matrix describes the growth and reproduction process of livestock, and then the vector m is defined to calculate the gene transmission process in each age-sex group. The formula is as follows: ; For each trait, a realization vector h is defined, whose elements represent the proportion of the number of sows expressed in different age-sex groups of a given trait to the total number of sows. Assuming that the trait realization vector h remains unchanged, the discounted value of trait expression is calculated using the following formula: ; In the formula, represents the discounted value of trait performance of trait i in sex group j, D is the breeding investment period, is the realization vector of trait i, is the gene probability vector of sex group j at time t, r is the discount factor, and t is the time of trait expression; Then multiply the discounted value of trait performance by the marginal economic value of the trait to obtain the economic weight of the trait: ; in is the economic weight of trait i, is the marginal economic value of trait i; in the binary hybrid system and the ternary hybrid system, the economic weights of two or three varieties are calculated at the same time, and the economic weights of multiple varieties are obtained at the same time.

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