A breeding method that comprehensively selects meat geese based on feed conversion efficiency and subcutaneous fat properties.

Abstract

This invention discloses a selection method for meat geese that comprehensively considers feed conversion efficiency and subcutaneous fat properties, relating to the field of poultry genetics and breeding. The method includes the following steps: S1 determining feed conversion efficiency of meat geese; S2 determining subcutaneous fat properties of meat geese; S3 calculating the family mean values ​​for each trait; S4 analyzing the correlation and heritability of each trait; S5 constructing a comprehensive selection index for feed conversion efficiency and subcutaneous fat properties of meat geese; and S6 selecting breeding geese with high comprehensive selection indices. This invention utilizes individual measurements and single-cage determination of feed conversion efficiency in meat geese, establishes a three-point method for accurately measuring subcutaneous fat thickness, and constructs a comprehensive selection index for residual feed intake, subcutaneous fat percentage, and subcutaneous fat thickness. It provides a selection method that comprehensively considers feed conversion efficiency and subcutaneous fat properties in geese, simultaneously improving feed efficiency and reducing subcutaneous fat properties, achieving simultaneous selection and synergistic improvement of multiple traits, and significantly enhancing breeding efficiency.

Description

Technical Field

[0001] This invention relates to the field of poultry genetics and breeding, and in particular to a selection method for meat geese that comprehensively selects based on feed conversion efficiency and skin fat properties. Background Technology

[0002] my country accounts for over 94% of the global goose slaughter volume, making the goose industry a vital sector of my country's distinctive livestock industry, playing a significant role in rural revitalization and increasing farmers' income. Livestock and poultry feeding costs account for 70% of total breeding costs, and feed conversion efficiency greatly impacts production costs. However, measuring individual feed intake in geese is difficult, and individual cage-rearing measurements are lacking. Furthermore, the feed conversion efficiency of geese has not been systematically selected, resulting in a feed conversion ratio (3.0–3.3:1) that differs significantly from that of broilers and ducks (1.6–2.0:1). In addition, the replacement of traditional free-range farming with pen-raising has led to excessive fat deposition in geese, resulting in decreased feed efficiency, meat yield, and product quality, which does not align with the modern consumer trend towards low-fat, healthy diets. Therefore, it is necessary to strengthen the selection of fat traits.

[0003] Currently, feed conversion efficiency and subcutaneous fat properties are rarely used in the breeding of meat geese, and effective selection methods are lacking. Firstly, meat geese are mainly raised in large flocks, lacking individual measurement equipment and data, making it difficult to systematically select for feed conversion efficiency. While feed conversion efficiency is usually measured by feed conversion ratio (FCR), FCR is a ratioistic trait and has a complex correlation with body weight and weight gain, requiring independent evaluation using indicators that do not affect body weight or weight gain. Secondly, subcutaneous fat properties of meat geese are rarely measured, especially subcutaneous fat thickness, for which no measurement standards have been established. Furthermore, there are no reference thresholds for subcutaneous fat percentage and thickness, making effective selection based on subcutaneous fat properties difficult. Thirdly, selection of meat geese based on phenotypic traits mainly relies on independent culling. A comprehensive optimization of feed conversion efficiency and subcutaneous fat properties requires the establishment of an index to improve the accuracy and efficiency of selection. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention utilizes individual single-cage measurements of feed conversion efficiency in meat geese, establishes a three-point method for accurately measuring skin fat thickness in meat geese, and constructs a comprehensive selection index for residual feed intake, skin fat percentage, and skin fat thickness in meat geese. This provides a breeding method that comprehensively selects geese based on feed conversion efficiency and skin fat performance. By establishing a breeding method centered on residual feed intake and skin fat performance, and utilizing individual single-cage measurements of feed conversion efficiency in meat geese, a three-point method for accurately measuring skin fat thickness in meat geese has been established. A comprehensive selection index for residual feed intake, skin fat percentage, and skin fat thickness in meat geese has been constructed. This allows for simultaneous selection of feed conversion efficiency and skin fat performance in meat geese, achieving optimized selection and synergistic improvement of multiple traits, and enhancing breeding efficiency.

[0005] The technical solution adopted by this invention to solve its technical problem is: a breeding method for selecting meat geese that comprehensively considers feed conversion efficiency and subcutaneous fat properties, comprising the following steps:

[0006] S1 was used to determine the feed conversion efficiency of meat geese.

[0007] S2 was used to determine the properties of goose skin fat;

[0008] S3 calculates the pedigree mean for each trait;

[0009] S4 analysis of the correlation and heritability of each trait;

[0010] S5 constructs a comprehensive selection index for feed conversion efficiency and skin fat performance in meat geese;

[0011] S6 selects breeding goose families with high comprehensive selection index.

[0012] Preferably, in step S1,

[0013] The initial weight, final weight, initial feed weight, and final feed weight of meat geese were measured.

[0014] Calculate the average daily feed intake, daily weight gain, feed conversion ratio, and mid-term metabolic weight of meat geese during the measurement period;

[0015] Based on the measured body weight and weight gain data of meat geese, the remaining feed intake is estimated, and the adjusted R is calculated using the remaining feed intake estimation model. 2 To accurately estimate the remaining feed intake.

[0016] Preferably, step S2, measuring traits includes the skin fat percentage and skin fat thickness of the geese at the end of the measurement period.

[0017] Preferably, in step S3, the average residual feed intake, subcutaneous fat percentage, and subcutaneous fat thickness of a meat goose family during the testing period are statistically analyzed to obtain the family averages of the above traits.

[0018] Preferably, in step S4, the phenotypic correlation coefficients among the remaining feed intake, subcutaneous fat percentage, and subcutaneous fat thickness of the meat goose during the testing period are calculated. Based on genome resequencing, SNPs are identified, and the genomic heritability of the remaining feed intake, feed conversion ratio, subcutaneous fat percentage, and subcutaneous fat thickness during the testing period is estimated to determine the weighting coefficients for constructing the comprehensive selection index for meat geese.

[0019] Preferably, in step S5, based on the family mean values ​​of each trait calculated in step S3 and the correlation and heritability parameters of each trait calculated in step S4, weighting coefficients are set for residual feed intake, subcutaneous fat percentage, and subcutaneous fat thickness to establish a comprehensive selection index for feed conversion efficiency and subcutaneous fat performance of meat goose families.

[0020] I = 100 - a × RFI - b × sebum percentage - c × sebum thickness

[0021] Where a, b, and c are the weighting coefficients for residual feed intake (RFI), subcutaneous fat percentage, and subcutaneous fat thickness of the meat goose family, respectively.

[0022] The remaining feed intake, sebum percentage, and sebum thickness are standardized data based on the family means calculated in step S3.

[0023] Data standardization uses Z-score standardization, and the calculation formula is as follows: In the formula For standardized data, This is the original data. This is the mean of the original data. This represents the standard deviation of the original data.

[0024] Preferably, in step S6, based on the comprehensive selection index constructed in step S5, the feed conversion efficiency and skin fat performance of the breeding flock of meat geese are selected, and the families ranked from high to low according to the comprehensive selection index value are retained for breeding.

[0025] The beneficial effects of this invention are:

[0026] This selection method yields high-quality meat geese with high feed conversion ratio, low skin fat percentage, and low skin fat thickness. This method is superior to the traditional independent culling method, resulting in significant genetic progress in feed conversion ratio and skin fat performance. This approach overcomes the disadvantage of traditional breeding methods where increased body weight leads to increased skin fat percentage and thickness in meat geese. It simultaneously improves feed conversion ratio and reduces skin fat performance, achieving simultaneous selection and synergistic improvement of multiple traits, thus significantly enhancing breeding efficiency. Attached Figure Description

[0027] Figure 1 A flowchart summarizing the overall invention;

[0028] Figure 2 This is a detailed flowchart of the present invention;

[0029] Figure 3 This is a schematic diagram of the three-point method for measuring sebum thickness according to the present invention. Detailed Implementation

[0030] To enhance understanding of the present invention, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. These embodiments are only used to explain the invention and do not limit the scope of protection of the invention.

[0031] A breeding method for selecting meat geese that comprehensively considers feed conversion efficiency and skin fat properties includes the following steps:

[0032] Using the paternal line of the Yuzhou White Goose breeding system selected by the Chongqing Poultry Research Base as the subject, hatching eggs of the core breeding geese were collected by family and incubated according to pedigree. Multiple batches of breeding geese were retained for breeding, with at least one batch serving as the test group. From each family in the test group, at least 3 male geese or at least 3 male and 3 female geese were selected.

[0033] Place the meat geese into individual cages for measurement (cage dimensions: length 1.0 meter, width 0.6 meters, height 0.8 meters, bottom area 0.6 square meters, bottom slope 6°, equipped with feed trough and nipple drinker).

[0034] The body weight of meat geese at 3 weeks of age, 10 weeks of age, feed intake weight at 3 weeks of age, and remaining feed weight at 10 weeks of age were measured.

[0035] Calculate the average daily feed intake (ADFI), daily weight gain (ADG), feed conversion ratio (FCR), and mid-cycle metabolic weight of meat geese aged 3-10 weeks.

[0036] Estimate remaining feed intake and accuracy based on measured growth and feed conversion efficiency data.

[0037] The residual feed intake (RFI) for 3-10 weeks of age is the difference between the actual feed intake and the expected feed intake for 3-10 weeks of age. The expected feed intake for 3-10 weeks of age is obtained based on a linear regression equation of the average daily feed intake for 3-10 weeks of age, mid-3-10 week metabolic body weight, and daily weight gain for 3-10 weeks of age. The accuracy of the residual feed intake (RFI) is determined by adjusting the R0 of this equation. 2 Numerical value.

[0038] The linear regression equation and RFI calculation are as follows: RFI = ADFI - (a + b1 * MBW) 0.75 +b2*ADG)

[0039] ADFI represents the average daily feed intake of infants aged 3–10 weeks; MBW 0.75 The mid-metabolical weight (MBW) represents the weight of geese aged 3-10 weeks, which is the 0.75th power of the arithmetic mean of their weight at 3 weeks and 10 weeks; ADG represents the average daily weight gain (ADG) from 3-10 weeks; 'a' represents the intercept; and 'b1' and 'b2' are the mean weight gain (MBW). 0.75 The partial regression coefficients of ADG with respect to ADFI.

[0040] Step (1) After the feed conversion efficiency of meat geese is determined, the skin fat properties of meat geese are measured, including the skin fat rate and skin fat thickness of meat geese at 10 weeks of age. The method for measuring and calculating skin fat thickness is as follows: The total thickness of skin and subcutaneous fat in three different areas of meat geese (the area to the left of the midpoint of the keel, the area to the left of the midpoint of the back midline, and the area to the left of the abdomen midline along the end of the keel) is measured using vernier calipers. The average value of the measurement results in the three different areas is the skin fat thickness.

[0041] Based on the residual feed intake (RFI) of the flock of meat geese measured in step (1) and the skin fat percentage and skin fat thickness of meat geese measured in step (2), the average residual feed intake (RFI), skin fat percentage and skin fat thickness of meat geese at 3-10 weeks of age and 10 weeks of age were statistically analyzed within a family, and the family averages of these traits were obtained.

[0042] Based on the estimated residual feed intake (RFI) in step (1) and the sebum performance data measured in step (2), the phenotypic correlation coefficients between RFI at 3-10 weeks of age and sebum percentage and thickness at 10 weeks of age, and between sebum percentage and thickness at 10 weeks of age, were calculated for meat geese. After the feed conversion efficiency of meat geese was measured in step (1), blood samples were collected from individual geese, genome resequencing was performed, SNPs were identified, and the genomic heritability of residual feed intake (RFI), feed conversion ratio (FCR) at 3-10 weeks of age, sebum percentage and thickness at 10 weeks of age were estimated for meat geese.

[0043] The phenotypic correlation coefficients and heritability estimates for each trait are obtained based on the analysis of accumulated phenotypic measurement data from multiple generations. Genomic heritability is estimated using genomic SNPs and GCTA software, primarily employing the GREML (Genome Restricted Maximum Likelihood) method. This involves fitting a random-effects model to determine how much phenotypic variation among individuals can be explained by genomic SNPs. First, genotype and phenotypic data are prepared. Genotype data requires PLINK binary format files, including a .bed file storing genotypes, a .bim file storing SNP information, and a .fam file storing individual information. Second, genomic relationships between individuals are calculated, for example, using the command "gcta64 --bfile your_data --make-grm --out grm_matrix", where --bfile specifies the PLINK file prefix, --make-grm instructs the construction of the GRM, and --out sets the output file prefix. Finally, run REML analysis to estimate variance components and heritability. For example, use the command "gcta64 --grm grm_matrix --pheno trait.phen --reml --out trait_h2". --grm specifies the GRM file prefix, --pheno specifies the phenotype file, and --reml indicates that the REML method is used. If covariates exist, the --covar and --qcovar parameters need to be added.

[0044] Based on the pedigree mean of each trait calculated in step (3), the correlation and heritability parameters of each trait estimated in step (4), weight coefficients for residual feed intake (RFI), subcutaneous fat percentage and subcutaneous fat thickness are set to construct a comprehensive selection index for feed conversion ratio and subcutaneous fat performance of meat goose families:

[0045] I = 100 - a × RFI - b × sebum percentage - c × sebum thickness

[0046] Where a, b, and c are the weighting coefficients for family RFI, sebum percentage, and sebum thickness, respectively. RFI, sebum percentage, and sebum thickness are the standardized family mean data calculated in step (3). Data standardization is performed using Z-score standardization (standard deviation standardization), and the calculation formula is as follows: In the formula For standardized data, This is the original data. This is the mean of the original data. This represents the standard deviation of the original data.

[0047] In addition to protecting the constructed comprehensive selection index, this patent also protects the weighting coefficients based on the RFI comprehensive selection index.

[0048] Based on the residual feed intake (RFI) comprehensive selection index constructed in step (5), the feed conversion efficiency and skin fat performance of the breeding flock of meat geese are selected. The meat goose families with high comprehensive selection index values ​​are selected for breeding, and the top 50% of the families are selected for breeding.

[0049] This embodiment uses the core group of the sixth generation paternal line of the Yuzhou White Goose breeding system selected by the Chongqing Poultry Research Base as material, and selects one batch of offspring from the core group of breeding geese as the test group. This embodiment measures the feed conversion efficiency of the test group of meat geese and constructs a comprehensive selection index.

[0050] 1. Determine the feed conversion efficiency of meat geese.

[0051] Goslings were selected for breeding and placed in individual cages: 806 goslings (405 males and 401 females) were selected as the test group and raised under unified feeding and management with free access to feed. 3-4 males and 44 females were selected from each family, totaling 543 geese (283 males and 260 females) to be placed in individual cages for individual testing (single cage dimensions: length 1.0 meter, width 0.6 meters, height 0.8 meters, bottom area 0.6 square meters, bottom slope 6°, equipped with feed troughs and nipple drinkers).

[0052] Body weight and feed conversion efficiency (RFI) determination: The experiment lasted 49 days, from 22 days to 70 days of age. Body weight at 22 days and 70 days of age, feed intake at 22 days of age, and uneaten feed weight at 70 days of age were measured. The average daily gain (ADG), average daily feed intake (ADFI), and feed conversion ratio (FCR) of meat geese from 22 to 70 days of age were calculated, and the correlation between RFI and each trait was analyzed.

[0053] The results of the determination of goose flock weight and feed conversion efficiency are shown in Table 1:

[0054] gender Weight at 22 days old (g) Weight at 70 days old (g) ADG (g) for children aged 22-70 days ADFI (g) for children aged 22-70 days FCR in children aged 22-70 days male goose 1001±95 4480±402 71.6±6.4 262.5±28.4 3.68±0.52 Mother goose 985±93 3914±388 60.3±5.6 223.1±26.9 3.73±0.60 Residual Feed Intake (RFI) Estimation: Based on the growth and feed conversion efficiency data obtained in step 1, the RFI of meat geese is estimated using the following equation:

[0055] RFI = ADFI - (a + b1 * MBW) 0.75 +b2*ADG)

[0056] In the formula: ADFI represents the average daily feed intake of infants aged 22–70 days; MBW 0.75 The mid-cycle metabolic weight is the 0.75th power of the arithmetic mean of the body weights of geese at 22 and 70 days of age; ADG represents the average daily weight gain from 22 to 70 days of age; 'a' represents the intercept; and 'b1' and 'b2' are the mean weight gain (MBW). 0.75 The partial regression coefficients of ADG with respect to ADFI.

[0057] RFI accuracy estimation: Adjustment of R during RFI estimation model estimation 2 Numerical value.

[0058] RFI estimation results: The RFI estimation results of the goose flock are shown in Table 2. 2 Higher RFI values ​​indicate better accuracy in RFI estimation. Adjustments for male and female geese are needed. 2 The average value was 0.426, indicating good accuracy in RFI estimation and demonstrating the effectiveness of the individual cage measurement model for meat geese.

[0059] The estimated values ​​of a, b1, and b2 for the RFI of the goose flock were 2596.489, 18.771, and 0.843, respectively. The estimation results are shown in Table 2.

[0060] gender RFI Mean RFI Standard Deviation RFI coefficient of variation <![CDATA[Adjust R 2 <!-- 4 -->]]> male goose 0.08 15.78 19725 0.433 Mother goose -0.25 14.9 5960 0.420 Correlation analysis: The phenotypic correlation coefficients between RFI and growth and feed conversion efficiency traits are shown in Table 3. The results showed that RFI was strongly correlated with ADFI and FCR, but not with initial body weight at 22 days of age, market body weight at 70 days of age, and daily weight gain from 22 to 70 days of age, indicating that RFI can be used as an effective indicator for evaluating feed conversion efficiency in meat geese.

[0061] Properties ADFI for 22-70 days FCR in children aged 22-70 days 22-day-old weight Weight at 70 days ADG for 22-70 days 22-70 day old RFI 0.689** 0.572** 0.029 0.006 0.006 2. Determination of the sebum properties of meat geese

[0062] Trait testing: After the production performance test at 70 days of age, the above-mentioned meat geese were subjected to slaughter tests, including the slaughter performance indicators of 70-day-old skin fat weight, 70-day-old skin fat thickness, and 70-day-old eviscerated weight.

[0063] Methods for determining and calculating traits:

[0064] Fully eviscerated weight: The weight of the cavity remaining after slaughtering, bleeding, defecation, and removal of the trachea, esophagus, crop, intestines, spleen, pancreas, heart, liver, proventriculus, gizzard, abdominal fat, and reproductive organs in the experimental geese.

[0065] Thickness of subcutaneous fat: The total thickness of skin and subcutaneous fat in three different areas of the experimental geese (the area to the left of the midpoint of the keel, the area to the left of the midpoint of the back midline, and the area to the left of the abdomen midline 5 cm down from the end of the keel) was measured using vernier calipers. The mean of the results measured in the three different areas was the thickness of subcutaneous fat.

[0066] Skin fat weight: The total weight of the skin, subcutaneous fat, and abdominal fat of a goose after it has been stripped of its skin.

[0067] Skin fat percentage: The percentage of the sum of skin weight, subcutaneous fat weight, and abdominal fat weight of a meat goose relative to the sum of the total eviscerated weight and abdominal fat weight.

[0068] Results of skin fat performance testing: The average eviscerated weight and skin fat performance of the goose flock are shown in Table 4. The test results show that the skin fat percentage and skin fat thickness of meat geese vary greatly, with a range of more than 20%, indicating a large selection range.

[0069] Table 4. Results of the determination of skin lipid properties in 70-day-old geese Correlation analysis of three-point sebum thickness and sebum percentage: The correlation results between sebum thickness and sebum percentage are shown in Table 5. The results show that the mean sebum thickness in the three different regions of back, chest and abdomen has the highest correlation with sebum percentage (correlation coefficient of 0.425), indicating that the mean sebum thickness at three points is more representative of the sebum thickness of meat geese than that at a single site.

[0070] Determining properties Thick sebum (back) Thick sebum (chest) Thick sebum (abdomen) Thick (even) sebum Sebum percentage 0.298 0.408 0.219 0.425 3. Calculate the family mean for each trait.

[0071] Based on the RFI of the flock of meat geese measured in step 1 and the skin fat percentage and skin fat thickness measured in step 2, the average values ​​of RFI, skin fat percentage and skin fat thickness at 70 days of age for 6-8 geese in each family were statistically analyzed to obtain the family average values ​​of each trait. The results are shown in Table 6.

[0072] Table 6 Results of feed conversion efficiency and skin fat properties in meat geese 4. Analyze the correlation and heritability of each trait.

[0073] Correlation analysis: Following step 1, the feed conversion ratio (RFI) of the geese was measured; in step 2, the skin fat percentage and skin fat thickness were measured. Using accumulated data from multiple generations, regression analysis was performed in EXCE1 software to obtain partial regression coefficients and intercepts, calculating the phenotypic correlation coefficients between RFI and skin fat percentage and skin fat thickness, and between skin fat percentage and skin fat thickness. The results showed that the correlation coefficients between RFI and skin fat percentage and skin fat thickness at 70 days of age were 0.534 and 0.228, respectively, and the correlation coefficient between skin fat percentage and skin fat thickness at 70 days of age was 0.425. These results indicate that RFI has a moderate correlation with skin fat percentage and a low correlation with skin fat thickness. Skin fat percentage and skin fat thickness are moderately correlated, suggesting that skin fat percentage selection can improve feed conversion efficiency in geese, and that skin fat percentage and skin fat thickness can be improved simultaneously. When formulating a comprehensive selection index, the weighting index should be based on RFI, followed by skin fat percentage, and then skin fat thickness.

[0074] Heritability estimation: Blood samples were collected from individual geese in the feed conversion efficiency (FCE) determination group in step 1. After accumulating data from multiple generations of the determination group, genome resequencing was performed, followed by genotyping, genotypic and phenotypic quality control. GCTA software and standard parameters were used to estimate the genomic heritability of each trait. The estimated heritability parameters for FCE and subcutaneous fat traits in the determination group are shown in Table 7. The results showed that subcutaneous fat thickness had low heritability, while RFI, FCR, and subcutaneous fat percentage had moderate to moderately high heritability, which could be improved through systematic selection.

[0075] project 22-70 day old RFI FCR in children aged 22-70 days 70-day-old sebum percentage Thicker sebum at 70 days of age Heredity 0.35 0.31 0.42 0.15 5. Construct a comprehensive selection index for feed conversion efficiency and skin fat performance in meat geese.

[0076] Comprehensive selection index formulation: Based on the results in step 4 showing a high correlation between RFI and skin fat percentage and a low correlation between RFI and skin fat thickness in meat geese, and the heritability estimation results of each trait, a comprehensive selection index for RFI, skin fat percentage, and skin fat thickness in meat goose families is established: I = 100 - 0.5 × RFI - 0.3 × Skin Fat Percentage - 0.2 × Skin Fat Thickness, where 0.5, 0.3, and 0.2 are the weighting coefficients for RFI, skin fat percentage, and skin fat thickness, respectively. RFI, skin fat percentage, and skin fat thickness are standardized data based on family means. Data standardization uses Z-score standardization (standard deviation standardization), and the calculation formula is as follows: In the formula For standardized data, This is the original data. SD is the original data mean, and SD is the original data standard deviation.

[0077] In addition to protecting the constructed comprehensive selection index, this patent also protects the weighting coefficients based on the RFI comprehensive selection index.

[0078] Results of the comprehensive selection index: As shown in Table 8, the highest comprehensive selection index is 30% higher than the average, and the difference between the highest and lowest comprehensive selection index values ​​is 56.8%. This fully demonstrates that the comprehensive selection index has a large gradient, which can reflect the differences in the selection groups of meat geese and is a good basis for breeding.

[0079] project Comprehensive selection index mean The highest value of the comprehensive selection index The lowest value of the comprehensive selection index Comprehensive selection index standard deviation Index value 100 130.17 83.04 7.84 Example 2: Selection of meat geese based on feed conversion efficiency and subcutaneous fat properties

[0080] Following the determination of feed conversion efficiency and the construction of a comprehensive selection index for a pair of meat geese in the example, feed conversion efficiency and skin fat performance were selected for meat geese in the half-sib breeding group to which the test group belonged. In this example, feed conversion efficiency and skin fat performance were selected for the 5th to 7th generations of the Yuzhou White Goose paternal breeding group, and the selection results and progress were analyzed for the 6th to 8th generations.

[0081] 1. Select breeding goose families with high overall selection index.

[0082] Family selection: At 13-18 weeks of age, each batch of breeding geese is selected based on feed conversion efficiency and skin fat performance. The top 50% of families are selected for breeding according to the comprehensive selection index from high to low.

[0083] Re-selection at 25 weeks of age: Before laying eggs at 25 weeks of age, male and female geese are re-selected. Individuals whose body shape and appearance conform to the breed characteristics are selected, and individuals with poor growth and development are eliminated. The reproductive organs of male geese are examined, and individuals with poor development are eliminated.

[0084] Family formation: After the above selection, the breeding geese are caged and tested according to a male-to-female ratio of 1:4, and all individuals in the family are kept away from half-siblings and full-siblings.

[0085] 2. Results of breeding selection based on feed conversion efficiency and subcutaneous fat properties

[0086] Selection was conducted on feed conversion efficiency and skin fat properties of meat geese across three generations (5-7). Significant selection differences were observed in the RFI, FCR, skin fat percentage, and skin fat thickness of male and female geese aged 4-10 weeks in each generation (Tables 9 and 10). For example, for the 6th generation breeding male and female geese, the selection differences in RFI at 4-10 weeks were -279.68 g and -168.94 g, respectively, indicating that the RFI of the breeding male and female geese at 4-10 weeks was reduced by -279.68 g and -168.94 g compared to before selection, ensuring genetic progress. The selection difference refers to the difference between the family pedigree mean of the breeding male and female geese and the measured individual family pedigree mean.

[0087] Table 9. Selection results of residual feed intake and feed conversion ratio of generations 5-7 at 4-10 weeks of age. Table 10. Selection results of sebum percentage and sebum thickness of generations 5-7 at 4-10 weeks of age. 3. Progress in generational selection for feed conversion efficiency and sebum performance

[0088] Starting from generation 5, feed conversion efficiency and skin fat properties of meat geese were measured and selected using a comprehensive selection index. The breeding progress achieved in generations 6-8 is shown in Table 11. As shown in Table 11, after three generations of meat geese were selected using the comprehensive selection index, by generation 8, the average feed conversion ratio at 0-10 weeks of age, skin fat percentage at 10 weeks of age, and skin fat thickness at 10 weeks of age for both male and female geese decreased by 0.13, 0.65%, and 0.23 mm, respectively, indicating significant genetic progress.

[0089] Table 11. Breeding progress of feed conversion ratio and skin fat performance of paternal lines in the 5th-8th generations of Yuzhou White Goose. Comparative Analysis: A Comparison of the Comprehensive Selection Index Method and Traditional Selection Methods

[0090] The differences in selection effectiveness between the comprehensive selection index method and the traditional selection method (independent culling method) under different family retention rates were compared. The comprehensive selection index I = 100 - 0.5 × RFI - 0.3 × skin fat percentage - 0.2 × skin fat thickness. Geese were selected for breeding based on their comprehensive selection index from highest to lowest. The independent culling method selected geese based on their RFI value from lowest to highest. The selection results are shown in Table 12. The results showed that the decrease in skin fat performance of meat geese increased significantly with the decrease in the retention rate. When the family retention rate was 0.2%, the comprehensive selection index method improved the FCR (Frequency Rate) at 4-10 weeks of age, skin fat percentage at 10 weeks of age, and skin fat thickness at 10 weeks of age by 0.77%, 4.61%, and 2.38%, respectively, compared to the traditional method. Therefore, compared to the traditional method, the comprehensive selection index method resulted in lower skin fat percentage and skin fat thickness in meat geese, and simultaneously reduced the feed conversion ratio.

[0091] Table 12 Comparison of selection results between the comprehensive selection index method and the independent elimination method The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0092] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A method for selecting a meat goose feed conversion efficiency and skin fat performance, characterized in that, It includes the following steps: S1 Determine the feed conversion efficiency of meat geese: The待测 meat geese are fed individually in cages during the measurement period; S2 Determine the sebum performance of meat geese: including the sebum rate at 10 weeks of age and the sebum thickness at 10 weeks of age of meat geese. The measurement and calculation method of sebum thickness are as follows: Use a vernier caliper to measure the total thickness of the skin and subcutaneous fat in 3 different areas of the meat geese. The three different areas respectively include the left area at the midpoint of the keel, the left area at the midpoint of the dorsal midline, and the left area 5 cm below the end of the keel along the ventral midline. The average value of the measurement results in the 3 different areas is the sebum thickness; S3 Calculate the family means of each trait; S4 Analyze the correlations and heritabilities of each trait; In step S4, calculate the phenotypic correlation coefficient among the residual feed intake during the measurement period of meat geese, the sebum rate at the end of the measurement period, and the sebum thickness at the end of the measurement period. Based on genome resequencing to identify SNPs, estimate the genomic heritabilities of the residual feed intake during the measurement period of meat geese, the feed-to-weight ratio during the measurement period, the sebum rate at the end of the measurement period, and the sebum thickness at the end of the measurement period, so as to determine the weighting coefficients for constructing the comprehensive selection index of meat geese; S5 Construct a comprehensive selection index for the feed conversion efficiency and sebum performance of meat geese; In step S5, based on the family means of each trait calculated in step S3 and the correlation and heritability parameters of each trait calculated in step S4, set the weighting coefficients of the residual feed intake, sebum rate, and sebum thickness, and establish a comprehensive selection index for the feed conversion efficiency and sebum performance of the meat goose family: I = 100 - a×RFI - b×sebum rate - c×sebum thickness where a, b, and c are respectively the weighting coefficients of the residual feed intake (RFI), sebum rate, and sebum thickness of the meat goose family, where a = 0.5, b = 0.3, and c = 0.2; The residual feed intake, sebum rate, and sebum thickness are the standardized data of the family means calculated in step S3, Data standardization adopts Z-score standardization, and the calculation formula is as follows: In the formula, is the standardized data, is the original data, is the mean of the original data, is the standard deviation of the original data; S6 Select and retain the meat goose families with high comprehensive selection indexes.

2. A method for selecting breeding geese by comprehensively selecting the feed conversion efficiency and sebum performance of meat geese according to claim 1, wherein: In step S1, Measure the initial weight, final weight, initial feeding weight, and remaining feed weight at the end of the meat geese; Calculate the average daily feed intake, daily weight gain, feed-to-weight ratio, and mid-term metabolic weight of the meat geese during the measurement period; The residual feed intake was estimated from the measured body weight and weight gain data of the meat geese, and the adjusted R was calculated by using the residual feed intake estimation model to estimate the accuracy of the residual feed intake. 2 The accuracy of the residual feed intake was estimated.

3. A method for selecting breeding geese by comprehensively selecting the feed conversion efficiency and sebum performance of meat geese according to claim 1, wherein: In step S2, the measured traits include the sebum rate and sebum thickness of the meat geese at the end of the measurement period.

4. A method for selecting breeding geese by comprehensively selecting the feed conversion efficiency and sebum performance of meat geese according to claim 1, wherein: In step S3, taking the family as a unit, statistically calculate the mean values of the residual feed intake of the meat geese in a family during the measurement period, the sebum rate at the end of the measurement period, and the sebum thickness at the end of the measurement period, so as to obtain the family means of the above-mentioned traits.

5. A method for selecting breeding geese by comprehensively selecting the feed conversion efficiency and sebum performance of meat geese according to claim 1, wherein: In step S6, according to the comprehensive selection index constructed in step S5, select the breeding geese for the feed conversion efficiency and sebum performance of the meat geese in the breeding population, sort them from high to low according to the comprehensive selection index values, and retain the top 50% of the families for breeding.

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