CN110367189B - Breeding method for screening high-yield dairy cow core group based on pedigree relationship and phenotypic data - Google Patents
Breeding method for screening high-yield dairy cow core group based on pedigree relationship and phenotypic data Download PDFInfo
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Abstract
The breeding method comprises the steps of measuring the production performance of all cows in a preset farm, and acquiring pedigree data, propagation data and phenotype data of individual cows; screening out a daughter mother pair according to pedigree data of the cow individual, and storing the daughter individual of which the CM305 of the mother is larger than the ACM305 into an alternative high-yield cow data set; CM305 is the individual 305-day milk yield correction value, and ACM305 is the average of the 305-day milk yield correction values of the whole group of dairy cow individuals; the CM305 and ACM305 are obtained by calculation according to propagation data and phenotype data; judging that individuals with the Ddm larger than or equal to ADdm + STDDdm in the alternative high-yield cow data set belong to high-yield core group individuals; wherein, the Ddm is the difference of the 305-day milk yield correction value between each daughter individual and the corresponding mother in the alternative high-yield cow data set; ADdm is the mean value of all the Ddm in the alternative high-yield cow data set, and STDDdm is the standard deviation of all the Ddm in the alternative high-yield cow data set; and breeding the cows by utilizing the high-yield core group individuals.
Description
Technical Field
The disclosure belongs to the field of high-yield cow core group screening and breeding, and particularly relates to a breeding method for screening a high-yield cow core group based on pedigree relationship and phenotype data.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
Milk is an important nutrient for humans. The breeding of high-yield individuals and the further improvement of the production level of the population are always the goals pursued by dairy cattle breeders continuously. The core population is a population composed of strictly selected individuals in the cattle population who are particularly excellent and healthy in certain traits. The excellent core group can drive the production level of the whole dairy herd to be continuously improved. How to accurately select a high-yielding cow core group within a cow group is one of the hot issues of great concern in the dairy industry today.
The inventor finds that the selection of the core group of cows is based on the 305-day milk yield of the fetuses calculated by phenotype record at present, the selection is carried out according to the 305-day milk yield, the method only considers the phenotype production level of individuals, the inheritance is not considered, and the selection accuracy is not high. Secondly, based on breeding value selection, although the accuracy of selection can be improved, the complexity of genetic evaluation technology makes it difficult for cattle farm workers to obtain individual breeding values in time, and the breeding value selection is inconvenient for production and application in time.
Disclosure of Invention
In order to solve the above problems, the present disclosure provides a breeding method for screening a core group of high-yielding cows based on pedigree relationship and phenotypic data, which considers the influence of calving year, calving season, calving age on the 305-day milk yield of an individual cow, corrects the phenotypic value, and considers the inheritance of generations at the same time, so as to improve the reliability of the high-yielding performance of the selected individual.
In order to achieve the purpose, the following technical scheme is adopted in the disclosure:
a breeding method for screening a high-yield cow core group based on pedigree relationship and phenotype data comprises the following steps:
measuring the production performance of all dairy cows in a preset farm, and acquiring pedigree data, propagation data and phenotype data of individual dairy cows;
screening out a daughter mother pair according to pedigree data of the cow individual, and storing the daughter individual of which the CM305 of the mother is larger than the ACM305 into an alternative high-yield cow data set; wherein CM305 is the correction value of the milk yield of individual 305 days, ACM305 is the mean value of the correction values of the milk yield of individual 305 days of the whole group of cows; the CM305 and ACM305 are obtained by calculation according to propagation data and phenotype data;
judging that individuals with the Ddm larger than or equal to ADdm + STDDdm in the alternative high-yield cow data set belong to high-yield core group individuals; wherein, the Ddm is the difference of the 305-day milk yield correction value between each daughter individual and the corresponding mother in the alternative high-yield cow data set; ADdm is the mean value of all the Ddm in the alternative high-yield cow data set, and STDDdm is the standard deviation of all the Ddm in the alternative high-yield cow data set;
and breeding the cows by utilizing the high-yield core group individuals.
Further, the pedigree data comprises a birth date, a parent number and a mother number of the individual; phenotypic data include daily milk yield.
Further, the breeding data includes calving year, calving season, calving age and fetal number.
Further, the calving year is the year of the individual calving date, and the category of the calving year is set not to exceed a preset number; calving season is divided into 4 types according to 1 type from 12 months to next year 2 months, 3 months-5 months, 6 months-8 months and 9 months-11 months of calving date; calving age is calculated according to month number between calving date and birth date, and is divided into 4 types according to 1 type of 21-24 months age, 25-28 months age, 29-32 months age, 33 months age and above.
Further, the formula for the individual 305-day milk yield correction value CM305 is:
CM305＝M305+CLLMi+CSLMk+CALMl；
wherein M305 is the individual 305 day milk yield; CLLMi、CSLMk、CALMlRespectively, the corrected value of the milk yield of the individual 305 days in the ith calving year, the corrected value of the milk yield of the individual 305 days in the kth calving season and the corrected value of the milk yield of the individual 305 days in the ith calving age, wherein i, k and l are positive integers.
Further, using the formula CLLMi＝LM-LLMiCalculating correction value of each calving year by using formula CSLMk＝LM-SLMkCalculating correction value of each calving season, and using formula CALMl＝LM-ALMlCalculating a correction value of each calving age group; wherein, LLMi、SLMk、ALMlRespectively is the least square mean value of the milk yield of the 305-day dairy cow at each calving year, calving season and calving age; LM is the least squares mean of the 305 day milk production of all cows on the farm.
Further, using model yikl＝Yi+Sk+Agel+eiklCalculating by combining with the GLM process of SAS software, and calculating the least square mean value of the 305-day milk yield of the cows at each calving year, calving season and calving age and the least square mean value of the 305-day milk yields of all the cows in the farm; wherein y isiklA record of the 305-day milk production phenotype for individuals of the ith calving year, the kth calving season, and the l calving age group; y isiFor the stationary effect in the ith calving year, SkA fixation effect for the kth calving season; agelFor the fixed effect of the first calving age group, eiklAnd (3) carrying out random residual errors on the milk yield of 305 days of the individuals of the ith calving year, the kth calving season and the l calving age group.
The beneficial effects of this disclosure are:
(1) according to the method, statistical analysis shows that the calving year, the calving season and the calving age have influence on the 305-day milk yield of the individual dairy cow. The calf year and the calf season have very significant influence on the 305-day milk yield of the dairy cow individual (P <0.001), and the calf age has significant influence on the 305-day milk yield of the dairy cow individual (P is 0.002). If these fixed effects (environmental factors) are not considered, selecting high yielding individuals directly from phenotypic values alone will result in a substantial reduction in accuracy of selection. Statistically obtaining the effect values of the environmental factors and correcting the form values can improve the accuracy of seed selection.
(2) The Ddm value is screened, the inheritance of the generation is considered, and the reliability of the high yield performance of the selected individual can be improved. According to the method, daily production management data are applied to large-group screening, the workload of the actual production process of a cattle farm is greatly reduced, high-yield individuals in the cattle group can be screened quickly and accurately, and then a high-yield core group is established.
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The accompanying drawings, which are included to provide a further understanding of the disclosure, illustrate embodiments of the disclosure and together with the description serve to explain the disclosure and are not to limit the disclosure.
Fig. 1 is a flowchart of a breeding method for screening a core group of high producing cows based on pedigree relationship and phenotypic data according to an embodiment of the disclosure.
Detailed Description
The present disclosure is further described with reference to the following drawings and examples.
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present disclosure. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
Fig. 1 shows a flow chart of a breeding method for screening a core group of high-producing cows based on pedigree relationship and phenotypic data according to an embodiment of the disclosure.
As shown in fig. 1, the breeding method for screening the core group of high-producing cows based on pedigree relationship and phenotypic data of the embodiment includes:
s101: and measuring the production performance of all the cows in the preset farm, and acquiring pedigree data, propagation data and phenotype data of the individual cows.
In the specific implementation, daily pedigree, reproduction and recording and measuring work of the milk yield of individual cows are carried out, wherein the work comprises cow number, father number, mother number, birth date, calving date and individual daily milk yield measurement;
according to individual breeding records, fixed effect data of calving year, calving season and calving age are obtained. Wherein the calving year is the year of the calving date of the individual, and the number of classes is recorded for some years, but generally does not exceed 10 classes, namely, the data of the last 10 years is used for selection; calving season is divided into 4 types according to calving date, and 1 type from 12 months to next year 2 months, 3 months-5 months, 6 months-8 months, 9 months-11 months of calving date; calving age is calculated according to month number between calving date and birth date, and is divided into 4 types according to 1 type of 21-24 months age, 25-28 months age, 29-32 months age, 33 months age and above.
Classifying the individuals according to the calving date and the calving age, the calving year, the calving season and the calving age.
S102: screening out a daughter mother pair according to pedigree data of the cow individual, and storing the daughter individual of which the CM305 of the mother is larger than the ACM305 into an alternative high-yield cow data set; wherein CM305 is the correction value of the milk yield of individual 305 days, ACM305 is the mean value of the correction values of the milk yield of individual 305 days of the whole group of cows; the CM305 and ACM305 are obtained by calculation according to propagation data and phenotype data;
according to the formula M305 ═ I1×M1+I2×(M1+M2)/2+In-1×(Mn-1+Mn)/2+In×MnCalculating the milk yield M305 of the individual 305 days;
wherein, I is a measuring interval and the unit is day; i is1For the 1 st measurement interval, the number of days between the calving date and the 1 st measurement date, I2The 2 nd measurement interval is the number of days from the 1 st measurement date to the 2 nd measurement date, and so on. I isnFor the last day between the days of determination to dry milk, it is generally calculated as 305 days postpartum. M is the milk yield on the day of the measurement, MnThe nth milk yield was determined.
Calculating and obtaining the least square mean value of 305-day milk yield of the cows at each calving year, calving season and calving age and the least square mean value of 305-day milk yield of all the cows in a preset farm by using a SAS software GLM program, and respectively recording the least square mean values as LLMi、SLMk、ALMlAnd an LM.
Using model yikl＝Yi+Sk+Agel+eiklCalculating by combining with the GLM process of SAS software, and calculating the least square mean value of the 305-day milk yield of the cows at each calving year, calving season and calving age and the least square mean value of the 305-day milk yields of all the cows in the farm; wherein y isiklA record of the 305-day milk production phenotype for individuals of the ith calving year, the kth calving season, and the l calving age group; y isiFor the stationary effect in the ith calving year, SkA fixation effect for the kth calving season; agelFor the fixed effect of the first calving age group, eiklAnd (3) carrying out random residual errors on the milk yield of 305 days of the individuals of the ith calving year, the kth calving season and the l calving age group.
Subtracting the least square mean value of each year, season and age of calving from the least square mean value of all data to obtain the CLLM correction value of each year, season and age of calvingi、CSLMk、CALMl。
Checking the year of calving, season of calving and age of calving, and using corresponding correction value CLLMi、CSLMk、CALMlAdding the obtained product with the daily milk yield of individual 305 for correction to obtain individual correction value (CM305), i.e. CM305 ═ M305+ CLLMi+CSLMk+CALMl；
Calculate the mean ACM305 of the whole population CM305, find the daughter mother (femal) pair, and select the individual whose corrected milk yield of the mother is greater than that of ACM 305.
S103: judging that individuals with the Ddm larger than or equal to ADdm + STDDdm in the alternative high-yield cow data set belong to high-yield core group individuals; wherein, the Ddm is the difference of the 305-day milk yield correction value between each daughter individual and the corresponding mother in the alternative high-yield cow data set; ADdm is the mean of all the Ddm in the alternative high producing cow dataset and STDDdm is the standard deviation of all the Ddm in the alternative high producing cow dataset.
Specifically, in individuals whose corrected milk yield is greater than ACM305, the difference D of the maternal-maternal pair CM305 is calculateddm，Ddm＝CM305d-CM305mWherein CM305dFor the daughter 305 day milk yield correction, CM305mCorrected value of the milk yield of the mother in 305 days;
calculating D of an individualdmMean value AD ofdmAnd standard deviation STDDdm，DdmValue of AD or moredm+STDDdmThe individual of (a) is a high yielding core population.
S104: and breeding the cows by utilizing the high-yield core group individuals.
Research shows that the individual production capacity of the dairy cow is influenced by a plurality of environmental factors and heredity, and the selection is only carried out according to the individual table, so that the selection accuracy is inevitably low. Firstly, if the influence of individual environmental factors can be analyzed, the environmental factors of different individuals are considered or corrected, so that the accuracy of selection can be improved, wherein the calving year, calving season and calving age of an individual are the most important environmental factors, and relevant records are generally made in a cattle farm, so that the factor data can be conveniently obtained and analyzed. Secondly, genetic analysis can be carried out according to estimated breeding values and heritability, but the genetic analysis is too complex in production application, and the prior cattle farm hardly has the technical talent, so that the relationship can be analyzed from parent-child relationships such as mothers, and the workload can be reduced without losing the accuracy. This is the design idea of the present invention.
The breeding method of the present disclosure is described below with reference to specific embodiments:
first, data collection
Monthly milk production data were obtained from a certain cattle farm in Shandong for the first births of 2265 cattle between 10 years in 2009 and 2018. According to experience, data with daily milk yield larger than two standard deviations of the average value of the current lactation months of the group is judged as abnormal records, and the records are replaced by the average value of the two adjacent numerical values close to the abnormal records. The classification of three fixed effects of the calving year, the calving season and the calving age group is carried out according to the method. The individual 305-day milk yield was calculated according to equation (2).
Second, data statistics
The influence of three fixed effects of the calving year, the calving season and the calving age group on the milk yield of the individual cattle in only 305 days is analyzed by using the GLM process of SAS software, and the influence of the calving year, the calving season and the calving age on the milk yield of the individual cattle in 305 days is found to be obvious (P <0.05) or extremely obvious (P <0.01), and the specific conditions are shown in Table 1.
TABLE 1 Effect of the fixation effects on the milk yield of individual cattle in 305 days
| Effect of fixation | Degree of autonomy | F value | P value |
| Year of calving | 9 | 46.89 | <.0001 |
| Calving season | 3 | 17.81 | <.0001 |
| Calving age group | 3 | 6.76 | 0.0002 |
Further using the model yikl＝Yi+Sk+Agel+eiklCalculating by combining with the GLM process of SAS software, and calculating the least square mean value of the 305-day milk yield of the cows at each calving year, calving season and calving age and the least square mean value of the 305-day milk yields of all the cows in the farm; wherein y isiklA record of the 305-day milk production phenotype for individuals of the ith calving year, the kth calving season, and the l calving age group; y isiFor the stationary effect in the ith calving year, SkA fixation effect for the kth calving season; agelFor the fixed effect of the first calving age group, eiklAnd (3) carrying out random residual errors on the milk yield of 305 days of the individuals of the ith calving year, the kth calving season and the l calving age group. The least square mean values of each calving year, calving season, and calving age are shown in tables 2, 3, and 4, respectively.
Using the formula CLLMi＝LM-LLMiCalculating correction value of each calving year by using formula CSLMk＝LM-SLMkCalculating correction value of each calving season, and using formula CALMl＝LM-ALMlCalculating a correction value of each calving age group; wherein, LLMi、SLMk、ALMlRespectively is the least square mean value of the milk yield of the 305-day dairy cow at each calving year, calving season and calving age; LM is the least squares mean of the 305 day milk production of all cows on the farm. The correction values of each calving year, calving season and calving age are shown in tables 2, 3 and 4 respectively.
TABLE 2 least squares mean and Effect values for each calving year
| Year of calving | Number of individuals | Least squares mean | Correction value |
| 2009 | 213 | 5800.03 | 1355.14 |
| 2010 | 231 | 7212.10 | -56.93 |
| 2011 | 272 | 7000.03 | 155.14 |
| 2012 | 191 | 6785.08 | 370.09 |
| 2013 | 309 | 6952.08 | 203.09 |
| 2014 | 229 | 7089.71 | 65.46 |
| 2015 | 193 | 7221.60 | -66.43 |
| 2016 | 184 | 6673.40 | 481.77 |
| 2017 | 210 | 8168.14 | -1012.97 |
| 2018 | 233 | 8649.49 | -1494.32 |
TABLE 3 least squares means and Effect values for classifications for each calving year
TABLE 4 least squares mean and Effect values for each calving season
| Calving season | Number of individuals | Least squares mean | Calibration value |
| 1 | 737 | 7386.89 | -231.72 |
| 2 | 280 | 7370.33 | -215.16 |
| 3 | 668 | 6740.56 | 414.61 |
| 4 | 580 | 7122.88 | 32.29 |
Using the formula CM305 ═ M305+ CLLMi+CSLMk+CALMlThe individual 305 day milk production values were corrected. For example, if the milk yield of a fetus in a certain individual is 7500 kg in 305 days of the head fetus, the date of birth is 2014, 7 and 10 days, and the date of calving is 2017, 8 and 15 days, the calving year is 2017, the calving season is 4, the calving age is 25.6 months, and the calving year group is 2. The correction value is: CM 305-7500-1012.97 + 32.29-6.35-6512.3 kg.
Calculate the mean of the milk production of the population, this example is 7178.8kg
Individuals with milk production greater than the population mean are selected, in this example 693.
The mean and standard deviation of the maternal-pair difference was calculated, which was-1044.4 + -1699.5 in this example.
Selecting individuals with a female mother-to-milk yield difference value larger than the average value plus 1 standard deviation, namely, larger than or equal to 655.1kg as a core group. In this example, 101 individuals were selected from 693 cows, and their average milk yield was 9272.9.1kg, 1406.8kg higher than the maternal mean 7856.1kg and 2093.1kg higher than the full-herd mean 7179.8.
The population is used as the high-yield core group of the field. Furthermore, the core group cattle selected by the invention can be utilized in a cattle farm to propagate by breeding technologies such as usability controlled frozen sperm breeding, superovulation, embryo transplantation and the like, so that the proportion of high-yield cattle is increased rapidly, and the breeding benefit of the cows is improved.
The above description is only a preferred embodiment of the present disclosure and is not intended to limit the present disclosure, and various modifications and changes may be made to the present disclosure by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present disclosure should be included in the protection scope of the present disclosure.
Claims (6)
1. A breeding method for screening a high-yield cow core group based on pedigree relationship and phenotype data is characterized by comprising the following steps:
measuring the production performance of all dairy cows in a preset farm, and acquiring pedigree data, propagation data and phenotype data of individual dairy cows;
screening out a daughter mother pair according to pedigree data of the cow individual, and storing the daughter individual of which the CM305 of the mother is larger than the ACM305 into an alternative high-yield cow data set; wherein CM305 is the correction value of the milk yield of individual 305 days, ACM305 is the mean value of the correction values of the milk yield of individual 305 days of the whole group of cows; the CM305 and ACM305 are obtained by calculation according to propagation data and phenotype data; calculating the average ACM305 of the whole group CM305, finding out the pair of the daughter mothers (femal mothers), and selecting the individuals with the corrected milk yield of the mothers larger than the ACM 305;
calculating and obtaining the least square mean value of 305-day milk yield of the cows at each calving year, calving season and calving age and the least square mean value of 305-day milk yield of all the cows in a preset farm by using a SAS software GLM program, and respectively recording the least square mean values as LLMi、SLMk、ALMlAnd LM;
the formula for the individual 305-day milk yield correction value CM305 is:
CM305＝M305+CLLMi+CSLMk+CALMl；
wherein M305 is the individual 305 day milk yield; CLLMi、CSLMk、CALMlRespectively correcting the milk yield of an individual 305 day in the ith calving year, the milk yield of an individual 305 day in the kth calving season and the milk yield of an individual 305 day in the ith calving age, wherein i, k and l are positive integers;
judging that individuals with the Ddm larger than or equal to ADdm + STDDdm in the alternative high-yield cow data set belong to high-yield core group individuals; wherein, the Ddm is the difference of the 305-day milk yield correction value between each daughter individual and the corresponding mother in the alternative high-yield cow data set; ADdm is the mean value of all the Ddm in the alternative high-yield cow data set, and STDDdm is the standard deviation of all the Ddm in the alternative high-yield cow data set;
and breeding the cows by utilizing the high-yield core group individuals.
2. A breeding method for screening high producing dairy cow core groups based on pedigree relationship and phenotype data as claimed in claim 1, wherein the pedigree data includes individual birth date, father number and mother number; phenotypic data include daily milk yield.
3. A breeding method for screening high producing dairy cow core groups based on pedigree relationship and phenotypic data as claimed in claim 1 wherein the breeding data includes year calving, season calving, age and number of births.
4. A breeding method for screening high producing cow core group based on pedigree relationship and phenotype data as claimed in claim 3, wherein the calving year is the year of the individual calving date, the category of the calving year is set not to exceed the preset number; calving season is divided into 4 types according to 1 type from 12 months to next year 2 months, 3 months-5 months, 6 months-8 months and 9 months-11 months of calving date; calving age is calculated according to month number between calving date and birth date, and is divided into 4 types according to 1 type of 21-24 months age, 25-28 months age, 29-32 months age, 33 months age and above.
5. The breeding method for screening high producing dairy cow core group based on pedigree relationship and phenotype data as claimed in claim 1, wherein formula CLLM is usedi＝LM-LLMiCalculating correction value of each calving year by using formula CSLMk＝LM-SLMkCalculating correction value of each calving season, and using formula CALMl＝LM-ALMlCalculating a correction value of each calving age group; wherein, LLMi、SLMk、ALMlRespectively is the least square mean value of the milk yield of the 305-day dairy cow at each calving year, calving season and calving age; LM is the least squares mean of the 305 day milk production of all cows on the farm.
6. A breeding method for screening high producing dairy cow core group based on pedigree relationship and phenotype data as claimed in claim 5, wherein model y is usedikl＝Yi+Sk+Agel+eiklCalculating by combining with the GLM process of SAS software, and calculating the least square mean value of the 305-day milk yield of the cows at each calving year, calving season and calving age and the least square mean value of the 305-day milk yields of all the cows in the farm; wherein y isiklA record of the 305-day milk production phenotype for individuals of the ith calving year, the kth calving season, and the l calving age group; y isiFor the stationary effect in the ith calving year, SkA fixation effect for the kth calving season; agelFor the fixed effect of the first calving age group, eiklAnd (3) carrying out random residual errors on the milk yield of 305 days of the individuals of the ith calving year, the kth calving season and the l calving age group.
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