Breeding method for improving yield and quality of chicken
By precisely measuring the total number of muscle fibers in 1-day-old chicks and using genetic parameter estimation and the deep learning tool MyoV, combined with ABLUP or ssGBLUP models, the problem of limited chicken yield and quality improvement in traditional breeding methods has been solved, achieving a rapid and accurate breeding process.
Patent Information
- Application Number
- CN202511357647.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-09-22
- Publication Date
- 2025-12-23
AI Technical Summary
Traditional breeding methods are difficult to accurately determine the total number of muscle fibers in chicken meat on a large scale and at high throughput, which limits the improvement of chicken meat yield and quality. Existing methods are time-consuming, labor-intensive, and produce inconsistent data.
By precisely measuring the total number of muscle fibers in 1-day-old chicks, high-throughput and automated analysis was performed using genetic parameter estimation and the deep learning tool MyoV, and selection was carried out in conjunction with ABLUP or ssGBLUP models to optimize the breeding process.
It enables rapid and accurate early selection, significantly improving chicken yield and quality, and enhancing breeding efficiency and selection accuracy.
Smart Images
Figure CN121190239A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of poultry breeding technology, and in particular relates to a breeding method for improving chicken yield and quality. Background Technology
[0002] With the development of breeding technology, broiler breeding methods have evolved from relying on phenotypes and experience in the early stages to the large-scale application of genomic selection today. These advancements have led to rapid improvements in traits such as growth rate and feed conversion ratio in commercial broilers. However, as consumers demand higher meat quality and more refined requirements for different muscle cuts, traditional breeding strategies are showing significant limitations in balancing yield and quality.
[0003] Chicken yield and quality are closely related to muscle fiber characteristics, particularly the total number and cross-sectional area of muscle fibers, which directly determine the total volume and weight of the muscle. The total number of muscle fibers is mainly determined during embryonic development and muscle growth occurs after birth through muscle fiber hypertrophy. Although its importance has long been recognized in the industry, the total number of muscle fibers has not been used as a direct breeding indicator for a long time. The fundamental reason is that traditional muscle fiber counting methods are not only time-consuming, labor-intensive, and costly, but also difficult to guarantee the accuracy and consistency of the data, completely failing to meet the requirements of large-scale, high-throughput phenotyping for modern breeding. Therefore, past breeding practices have had to focus on more easily measurable macroeconomic traits such as growth rate and body weight, while neglecting the direct improvement of the key internal trait of total muscle fiber count. Summary of the Invention
[0004] In view of this, the purpose of this invention is to provide a breeding method to improve chicken yield and quality. By accurately measuring the total number of muscle fibers in 1-day-old chicks, and through genetic parameter estimation and early selection, the aim is to breed new broiler breeds with higher meat yield and better meat quality, thereby enhancing market competitiveness and promoting the sustainable development of the broiler industry.
[0005] To achieve the above-mentioned objectives, the present invention provides the following technical solution: A breeding method for improving chicken yield and quality includes the following steps: (1) After hatching, the chicks are divided into a test group and a candidate group; (2) The total number of pectoral muscle fibers (PTNM) and gastrocnemius muscle fibers (GTNM) of 1-day-old chicks in the test group were determined. (3) The candidate population is subjected to restricted feeding in preparation for breeding; (4) Based on pedigree records and / or genomic information, and the PTNM and GTNM phenotypic data obtained in step (2), estimate the genetic parameters using the ABLUP model and / or ssGBLUP model, and solve for the estimated breeding values of PTNM and GTNM for each individual in the candidate population. (5) Standardize the estimated breeding values of PTNM and GTNM obtained in step (4), and calculate the comprehensive breeding value of each individual based on the weighting coefficients; (6) In the candidate group, the first selection is carried out, and individuals with higher comprehensive breeding value are selected to continue restricted feeding until the egg-laying period. Then, the second selection is carried out, and roosters and hens with higher comprehensive breeding value are selected to form families. (7) After the family line is established, breed the next generation. After hatching, eliminate weak chicks and individuals whose body shape and appearance do not conform to the breed selection characteristics. Repeat (1) to (6) until the chicken yield and quality are improved.
[0006] Preferably, in step (1), the breeding flock undergoes at least two batches of hatching per year; If two batches are hatched each year, the first batch is the test group and the second batch is the candidate group; if more than two batches are hatched each year, the first batch and some subsequent batches of 1-day-old chicks are selected to form the test group, and the remaining batches or some individuals within the batches are the candidate group. Furthermore, after hatching, weak chicks and individuals whose body shape and appearance do not conform to the breed selection characteristics must be culled.
[0007] Preferably, the specific process for determining PTNM and GTNM in step (2) includes: sample collection and fixation, paraffin section preparation, HE staining, panoramic digital scanning of sections, and muscle fiber counting using MyoV software.
[0008] Preferably, the calculation methods for PTNM and GTNM are as follows: G ; P ; Where n is the number of images obtained by cutting the pectoralis major and gastrocnemius muscle tissue slices using MyoV software after panoramic scanning, and k is the number of muscle fiber targets counted by MyoV software in each image.
[0009] Preferably, in step (4), the genetic parameter estimation uses a multi-trait animal model, and the model expression is: ; Where y is the vector of phenotypic observations, b is the vector of fixed effects, a is the vector of additive genetic effects, e is the vector of residuals, and X and Z are the design matrices for fixed effects and additive genetic effects, respectively. The variance-covariance structure of random effects is as follows: ; in, and Let G and I represent the additive genetic variance and residual variance, respectively; G represents the genome relation matrix constructed based on SNP markers; and I is the identity matrix.
[0010] Preferably, in step (5), the standardized execution method is as follows: Standardized breeding value = Estimated breeding value / σ; Where σ is the genetic standard deviation of the corresponding trait; The calculation method for the comprehensive breeding value is as follows: Overall breeding value = D×Y1 + E×Y2; Where D is the standardized PTNM estimated breeding value, E is the standardized GTNM estimated breeding value, and Y1 and Y2 are weighting coefficients.
[0011] Preferably, in step (6), the retention rate for the first selection is 15%~20% for roosters and 45%~55% for hens, and only individuals with higher comprehensive breeding values are selected.
[0012] Preferably, in step (6), the retention rate for the second selection is 10%~15% for roosters and 45%~55% for hens; hens with less than 10 eggs laid in the last four weeks are excluded, and it is ensured that more than 30% of the rooster families have offspring selected.
[0013] Preferably, in step (6), when forming the family line, the kinship coefficient between the rooster and hen to be paired is <6.25%.
[0014] Preferably, in step (7), the elimination criteria for weak chicks include individuals with poor umbilical cord healing, low weight, hair loss, unstable standing posture, and obvious physiological deformities; the elimination criteria for individuals whose body shape and appearance do not conform to the breed selection characteristics include individuals with obvious deviations in color and body structure.
[0015] Compared with the prior art, the present invention has the following beneficial effects: (1) By measuring the total number of muscle fibers in chicks at 1 day old, this invention significantly shortens the phenotypic measurement cycle of key traits from several weeks to several days, achieving precise ultra-early selection, effectively accelerating the breeding process, and significantly improving the overall breeding efficiency.
[0016] (2) The total number of muscle fibers directly affects muscle yield and quality. By precisely selecting this trait, this invention can effectively increase the total number of muscle fibers in the main muscle parts of broilers, namely the pectoral and leg muscles, thereby improving the overall chicken yield and quality.
[0017] (3) This invention utilizes the deep learning tool MyoV to perform high-throughput, automated, and intelligent analysis of the total number of muscle fibers, overcoming the shortcomings of traditional manual measurement which is time-consuming and laborious, and ensuring the accuracy and consistency of phenotypic data.
[0018] (4) This invention utilizes genetic parameter estimation and pedigree-based best linear unbiased prediction (ABLUP) or one-step genome best linear unbiased prediction (ssGBLUP) models to accurately assess the breeding value of individuals, effectively control the bias caused by population structure and sample correlation, and improve the accuracy of selection.
[0019] (5) By selecting the total number of pectoral muscle fibers (PTNM) of 1-day-old chicks, this invention utilizes the characteristic that it has a moderate to high genetic positive correlation with body weight and meat yield, which can effectively predict and improve the later growth performance in the early stage. Attached Figure Description
[0020] Figure 1 This is a technical roadmap of the breeding method of the present invention; Figure 2 A technical roadmap for histological analysis and quantification of muscle fibers; Figure 3 A comparison of the morphology and density of muscle fibers in the pectoralis major muscle (left) and gastrocnemius muscle (right) of a broiler chicken. Detailed Implementation
[0021] This invention provides a breeding method for improving chicken yield and quality based on the total number of muscle fibers (technical route as follows). Figure 1 As shown), the specific steps include the following: (1) The chicks hatched from the breeding flock were divided into a test group and a candidate group; The present invention preferably involves hatching at least two batches of breeding chickens each year, with the first batch of 1-day-old chicks serving as the test group. After slaughter and defecation, the total number of muscle fibers in the pectoralis major and gastrocnemius muscles of each chicken is measured.
[0022] This invention preferably culls weak chicks and individuals whose body shape and appearance do not conform to the breed selection characteristics after each batch of hatching. Further selection criteria for weak chicks include individuals with poor umbilical cord healing, low weight, hair loss, unstable standing posture, and obvious physiological deformities; further selection criteria for individuals whose body shape and appearance do not conform to the breed selection characteristics include individuals with obvious deviations in color and body structure.
[0023] Depending on the hatching batch, this invention preferably uses two batches of chicks hatched per year in the breeding flock. The first batch of chicks is recorded as the test group, and the second batch of chicks is recorded as the candidate group for restricted feeding and selection. Preferably, when the breeding flock hatches more than two batches per year, chicks from the first batch onwards are selected, and some batches or individuals within each batch are selected according to the flock size. These are fed and the total number of muscle fibers in the pectoralis major and gastrocnemius muscles of each chicken is measured. Together with the first batch of chicks, they are recorded as the test group. The remaining batches or individuals are restrictedly fed for selection and recorded as the candidate group.
[0024] (2) Determine the total number of pectoral muscle fibers (PTNM) and gastrocnemius muscle fibers (GTNM) of the 1-day-old chicks in the test group; specifically, after slaughtering and defecation of the 1-day-old chicks in the test group, determine the total number of muscle fibers in the pectoral muscle and gastrocnemius muscle, and calculate the total number of muscle fibers (PTNM) and GTNM of each individual according to Formula I. G ; P ; (Formula I); Where n is the number of images after segmentation, and k is the number of muscle fiber targets in each image.
[0025] The specific method includes the following steps: (2.1) First, sample collection and fixation are carried out. After the chicks hatch, healthy chicks with good vitality are selected and euthanized by decapitation. Samples of the pectoralis major and gastrocnemius muscles are collected quickly and fixed in 100mL plastic bottles containing 4% paraformaldehyde for later use. At the same time, blood samples are quickly collected into 1.5mL anticoagulant centrifuge tubes and thoroughly mixed, and stored at -20℃ for later use. Specifically, the skin of the chicken's chest is torn open, and the pectoral muscle tissue is completely dissected from the lower edge of the sternum upwards to the junction of the coracoid bone and scapula. The skin of the leg is dissected, and complete calf muscle samples are cut along the joint of the femur and tibia (upper end) and the joint of the tibia and metatarsal bone (lower end).
[0026] (2.2) Next, paraffin section preparation is performed. This process includes trimming, that is, taking chest and leg samples fixed for 48 hours, and transversely cutting the left pectoral muscle and gastrocnemius muscle along the direction perpendicular to the muscle fibers to obtain the observation section (e.g. Figure 2(As shown). Dehydration is then performed by placing the embedding cassette into a dehydrator. The specific steps are: 75% alcohol for 4 hours, 85% alcohol for 2 hours, 90% alcohol for 2 hours, 95% alcohol for 1 hour, anhydrous ethanol I for 30 minutes, anhydrous ethanol II for 30 minutes, benzene for 5-10 minutes, xylene I for 5-10 minutes, and xylene II for 5-10 minutes. Next, paraffin infiltration is performed by immersing the dehydrated sample in molten paraffin I, II, and III at 65℃ for 1 hour each. Then, embedding is performed by embedding the paraffin-infiltrated tissue in an embedding machine. First, the molten paraffin is placed into the embedding frame. Before the paraffin solidifies, the tissue is removed from the dehydration cassette. The sample section is placed with the bottom of the embedding frame flush against the sample surface and labeled accordingly. The frame is then cooled at -20℃. After the paraffin solidifies, the paraffin block is removed from the embedding frame and trimmed. Next, the prepared paraffin blocks are cooled on a -20°C freezing stage. The cooled blocks are then sectioned using a paraffin microtome, with a preferred thickness of 4µm. After sectioning, the sections are spread by floating them on a 40°C warm water spreader to flatten the tissue. The tissue is then retrieved onto a glass slide and labeled with the sample ID. Finally, the slides are baked in a 60°C oven. After baking, they are removed and stored at room temperature for later use.
[0027] (2.3) Next, HE staining was performed. First, the paraffin sections were dewaxed to water, then immersed in xylene I for 20 min, xylene II for 20 min, anhydrous ethanol I for 5 min, anhydrous ethanol II for 5 min, and 75% ethanol for 5 min, followed by washing with tap water. Then, hematoxylin staining was performed, with hematoxylin staining solution for 3-5 min, followed by washing with tap water, differentiation solution, washing with tap water, and blueing solution, followed by rinsing with running water. Next, eosin staining was performed, with sections immersed in 85% ethanol for 5 min, 95% ethanol for 5 min, and eosin staining solution for 5 min. Afterwards, dehydration was performed, with sections immersed in anhydrous ethanol I for 5 min, anhydrous ethanol II for 5 min, anhydrous ethanol III for 5 min, xylene I for 5 min, and xylene II for 5 min. Finally, mount the slide, remove the slide from xylene II, wipe off any excess liquid from the slide, drop an appropriate amount of neutral resin onto the tissue slide, gently cover the tissue with a coverslip and remove any excess air bubbles, let it dry, and then examine it under a microscope.
[0028] (2.4) Then, perform a panoramic digital scan of the sections. Open the section scanner (such as the Pannoramic MIDI from 3DHISTECH, Hungary) and the pannoramic scanner software. Place the prepared HE-stained paraffin sections on the scanner's section tray. Use the pannoramic scanner software to select bright-field scanning mode and load the sections into the scanner. Automatically or manually identify the scanning area, click "Start Scan," and the scanner will automatically focus and acquire composite images. After scanning, name each image according to the section number.
[0029] (2.5) Finally, slice observation and processing were performed. CaseViewer 2.4 and ASAP 1.9 software were used for preprocessing of the panoramic scan slices. The tissue areas to be counted were selected, and MyoV software was used to cut the images of the selected tissue areas. The total number of muscle fibers in the cut images was then counted (e.g., Figure 3 (As shown). Specific operations include preparing the files to be cut. Install CaseViewer 2.4 on a Windows computer. Open the original folder of the scan results to view the MRXS format scan files. On the computer, you can observe and crop images of any part of the tissue section at any magnification (1-400x). Open the .mrxs format file using ASAP 1.9, outline the area to be counted, form a closed loop after outlining, and click the save button to save it in the original folder as a .xml file. Move the original folder, the .mrxs format file, and the .xml format file (all three files for the same section) to the same folder. This folder contains the slice processing results for one individual. After preparing the files to be cut, cut the panoramic slice. Use MyoV to cut the slice into 512×512 images. All images cut from the same slice are automatically generated in the same folder. Finally, perform muscle fiber count detection. After the panoramic slice is cut, set the input and output paths, select the Early Stage model and choose the scale, and then count the number of muscle fibers in the images. MyoV automatically generates an Excel result file named after the individual's ID. The result file contains the image name and the number of targets. The total number of targets for all image samples of each individual is summed to obtain TNM (Total Number of Muscle Fibers).
[0030] For instructions on operating the MyoV software, please refer to [MyoV: a deep learning-based tool for the automated quantification of muscle fibers. Gu et al., 2024]. This software, developed by the inventors, utilizes convolutional neural networks to achieve automatic segmentation and feature extraction of muscle fibers. Based on the Mask R-CNN architecture and combined with ResNet-101 and FPN networks, MyoV achieves accurate identification of muscle fibers in muscle slices of different sizes and at different stages. After training on a dataset of over 660,000 manually labeled muscle fibers, MyoV achieves an accuracy of 0.93–0.96 and a precision of 0.91–0.97 on panoramic tissue sections (WSI), significantly outperforming manual methods and previously used algorithms. Especially for ultra-large slice images, MyoV can automatically complete image cutting, fiber segmentation, area calculation, and labeling without manual parameter adjustment, processing entire slices containing hundreds of thousands of fibers within minutes.
[0031] (3) Restrict feeding of candidate groups for breeding. Restricted feeding can prevent excessive obesity from affecting breeding performance, and conventional techniques in the field can be used. As one possible implementation method, feed twice or three times a day according to different growth weeks. The daily feed amount should refer to the standard in the breed's feeding manual and be dynamically adjusted in combination with weekly weighing results to ensure that the weight gain curve meets the breeding target.
[0032] (4) Based on pedigree records and / or genomic information, and the PTNM and GTNM phenotypic data obtained in step (2), estimate the genetic parameters of the total number of muscle fibers in the breeding flock using the ABLUP model (best linear unbiased prediction based on pedigree) or the ssGBLUP model (one-step best linear unbiased prediction based on genomics), and solve for the estimated breeding values of PTNM (total number of pectoralis major muscle fibers) and GTNM (total number of pectoralis major muscle fibers) for each individual in the candidate population.
[0033] This invention does not impose any special requirements on the evaluation methods and tools of ABLUP or ssGBLUP; evaluation methods and tools well known to those skilled in the art can be used. In this embodiment, the AIREML algorithm of the HIBLUP software (v1.5.0) is preferably used for multi-trait model analysis.
[0034] The following are multi-trait animal models: (Formula II); Where y represents the vector of phenotypic observations; b represents the vector of fixed effects; a represents the vector of additive genetic effects; e represents the vector of residuals; and X and Z are the design matrices for fixed effects and additive genetic effects, respectively.
[0035] This invention only considers gender as a fixed effect and does not include maternal effects or other environmental effects.
[0036] The variance-covariance structure of random effects is as follows: (Formula III); in, and represents additive genetic variance and residual variance, respectively; G represents the Genomic Relationship Matrix (GRM) constructed based on SNP markers; I represents the identity matrix; The method for constructing GRMs is based on the method described in [Estimating additive and non-additive genetic variations and predicting genetic merits using genome-wide dense single nucleotide polymorphism markers. Su et al., 2012].
[0037] (5) After standardizing the estimated breeding values of each trait (PTNM and GTNM) of each individual obtained in step (4) according to formula IV, the comprehensive breeding value of each individual is calculated using formula V and according to the weighting coefficient. Standardized breeding value = Estimated breeding value / σ (Equation IV); Where σ is the genetic standard deviation of each trait; Comprehensive breeding value = D × Y1 + E × Y2 (Equation V); Where D is the standardized breeding value of the total number of pectoralis major muscle fibers, and E is the standardized breeding value of the total number of gastrocnemius muscle fibers; Y1 and Y2 are the weighting coefficients of the corresponding traits, which can be adjusted according to the breeding objectives in conjunction with the Smith-Hazel index. b = P -1 Ga (Formula VI); Where b is the exponential weight vector (i.e., Y1, Y2), P -1 G is the inverse of the phenotypic variance-covariance matrix, G is the genetic variance-covariance matrix, and a is the economic weight vector (a1, a2).
[0038] (6) The first selection is carried out in the candidate group, and individuals with higher comprehensive breeding value are selected to continue to be fed with restricted feed; the retention rate of roosters selected in the first selection is 15%~20%, and the retention rate of hens is 45%~55%. The individuals selected in the first selection are raised to the egg-laying period. In the second selection, individuals with higher comprehensive breeding value are selected, and hens with less than 10 eggs laid in the last four weeks are removed. It is also ensured that 30% of the rooster families have individuals selected. The roosters and hens selected in the second selection are used to form families; the retention rate of roosters selected in the second selection is 10%~15%, and the retention rate of hens is 45%~55%; when forming the preferred families, the co-parenting coefficient of the roosters and hens to be paired is <6.25% to avoid inbreeding depression.
[0039] (7) After the family line is established, breed the next generation. After hatching, eliminate weak chicks and individuals whose body shape and appearance do not conform to the breed selection characteristics. Repeat (1) to (6) until the chicken yield and quality are improved.
[0040] The breeding method provided by this invention targets the market demand for broiler chicken yield and quality. Following the principles of genetics, it achieves the selection of traits related to chicken yield and quality through precise phenotypic determination of total muscle fiber count, accurate estimation of breeding values, and rational selection and mating methods. While ensuring growth rate, slaughter weight, and feed conversion ratio, it effectively improves chicken yield and quality, meeting the market demand for high-quality chicken.
[0041] The technical solutions provided by the present invention will be described in detail below with reference to the embodiments, but they should not be construed as limiting the scope of protection of the present invention.
[0042] Example 1 The experimental population used in this embodiment was a purebred broiler breeder from Beijing Huadu Yukou Poultry Industry Co., Ltd. This purebred breeder was used as the paternal line for white-feathered broilers and was raised using a three-dimensional cage rearing method.
[0043] This embodiment provides a breeding method for improving chicken meat yield and quality based on the total number of muscle fibers in 1-day-old chicks, specifically including the following steps: (1) The breeding core group of chickens is hatched in two batches each year. The first batch of chicks is recorded as the test group and the second batch of chicks is recorded as the candidate group for restricted feeding for selection. After the 1-day-old chicks of the test group are euthanized, samples of the pectoralis major muscle and gastrocnemius muscle are quickly collected and the total number of muscle fibers (TNM) is determined according to the detailed measurement method described in this invention. The candidate group of chicks is restricted feeding for breeding.
[0044] (2) At the time of hatching of each batch of chicks, weak chicks with poor umbilical cord healing, low weight, feather loss, unstable standing posture, obvious physiological deformities, etc., as well as individuals that do not meet the breed characteristics, such as obvious deviations in color and body structure. Healthy chicks that meet the breeding requirements are sexed, tagged with wing tags, and raised in the same environment.
[0045] (3) For the pectoralis major and gastrocnemius muscle samples collected from 1-day-old chickens in the test group, paraffin sections were prepared, HE stained, panoramic digital scanning was performed (using the 3DHISTECH Pannoramic MIDI scanner and pannoramic scanner software from Hungary) and the sections were observed and processed (using CaseViewer 2.4 and ASAP 1.9 software for preprocessing, and MyoV software for cutting and counting muscle fibers). The total number of pectoralis major muscle fibers (PTNM) and the total number of gastrocnemius muscle fibers (GTNM) for each individual were calculated, as shown in Table 1.
[0046] Table 1. Descriptive statistics of the total number of muscle fibers in the pectoralis major and gastrocnemius muscles.
[0047] (4) Based on the pedigree records of all individuals and the phenotypic results of each trait determined in step (3), multi-trait model analysis was performed using the AIREML algorithm of HIBLUP software (v1.5.0) to estimate the genetic parameters of PTNM and GTNM for all individuals and to estimate the breeding value (EBV). The variance components and genetic parameters of each trait are shown in Table 2. The genetic variance σ of each trait was extracted. 2 EBV of individuals in the candidate population.
[0048] Table 2. Heritability of Total Number of Muscle Fibers in the Pectoralis Major and Gastrocnemius Muscles
[0049] Meanwhile, through the above multi-trait model analysis, the phenotypic and genetic correlation results of PTNM and GTNM were also obtained, as shown in Table 3. The upper right shows the genetic correlation, and the lower left shows the phenotypic correlation. As shown in Table 3, the genetic correlation between the total number of pectoralis major muscle fibers and the total number of gastrocnemius muscle fibers is negative (-0.36), indicating that these two traits have an antagonistic relationship during the breeding process and need to be weighed in breeding. This provides a basis for the flexible setting of weight coefficients in the subsequent comprehensive breeding value calculation.
[0050] Table 3. Correlation results of total number of muscle fibers in the pectoralis major and gastrocnemius muscles.
[0051] (5) After standardizing the EBV (EBV / σ) of PTNM and GTNM, calculate the comprehensive breeding value of all male and female chickens in the candidate population according to the weight of the total number of pectoralis major muscle fibers (PTNM) and the total number of gastrocnemius muscle fibers (GTNM), for example, 2:1.
[0052] (6) Based on the comprehensive breeding value, the candidates were selected for the first breeding. The male and female chickens with the higher comprehensive breeding value were selected and continued to be restricted in their feeding. The breeding rate of male chickens was 15% to 20%, and the breeding rate of female chickens was 45% to 55%.
[0053] (7) When the chickens are raised to the egg-laying period, a second selection is carried out to select individuals with higher comprehensive breeding value. The retention rate of roosters is 10% to 15%, and the retention rate of hens is 45% to 55%. Hens that have laid less than 10 eggs in the past four weeks are removed, and individuals are ensured to be selected in 30% of the rooster families. The roosters and hens selected in the second selection are used to form families.
[0054] (8) After the family line is established, the next generation is bred. The above steps (1) to (7) are repeated. After multiple generations of testing, selection and pure breeding, the chicken yield and quality (such as the total number of muscle fibers) are significantly improved.
[0055] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.
Claims
1. A breeding method for improving chicken yield and quality, characterized in that, Includes the following steps: (1) After hatching, the chicks are divided into a test group and a candidate group; (2) The total number of pectoral muscle fibers (PTNM) and the total number of gastrocnemius muscle fibers (GTNM) of 1-day-old chicks in the test group were determined. (3) The candidate population is subjected to restricted feeding in preparation for breeding; (4) Based on pedigree records and / or genomic information, and the PTNM and GTNM phenotypic data obtained in step (2), estimate the genetic parameters using the ABLUP model and / or ssGBLUP model, and solve for the estimated breeding values of PTNM and GTNM for each individual in the candidate population. (5) Standardize the estimated breeding values of PTNM and GTNM obtained in step (4), and calculate the comprehensive breeding value of each individual based on the weighting coefficients; (6) In the candidate group, the first selection is carried out, and individuals with higher comprehensive breeding value are selected to continue restricted feeding until the egg-laying period. Then, the second selection is carried out, and roosters and hens with higher comprehensive breeding value are selected to form families. (7) After the family line is established, breed the next generation. After hatching, eliminate weak chicks and individuals whose body shape and appearance do not conform to the breed selection characteristics. Repeat (1) to (6) until the chicken yield and quality are improved.
2. The breeding method according to claim 1, characterized in that, In step (1), the breeding flock undergoes at least two batches of hatching each year; If two batches are hatched each year, the first batch is the test group and the second batch is the candidate group; if more than two batches are hatched each year, the first batch and some subsequent batches of 1-day-old chicks are selected to form the test group, and the remaining batches or some individuals within the batches are the candidate group. Furthermore, after hatching, weak chicks and individuals whose body shape and appearance do not conform to the breed selection characteristics must be culled.
3. The breeding method according to claim 1, characterized in that, In step (2), the specific process for determining PTNM and GTNM includes: sample collection and fixation, paraffin section preparation, HE staining, panoramic digital scanning of sections, and muscle fiber counting using MyoV software.
4. The breeding method according to claim 1, characterized in that, The calculation methods for PTNM and GTNM are as follows: G ； P ； Where n is the number of images obtained by cutting the pectoralis major or gastrocnemius muscle tissue slices using MyoV software after panoramic scanning, and k is the number of muscle fiber targets counted by MyoV software in each image.
5. The breeding method according to claim 1, characterized in that, In step (4), the genetic parameter estimation uses a multi-trait animal model, and the model expression is: ； Where y is the vector of phenotypic observations, b is the vector of fixed effects, a is the vector of additive genetic effects, e is the vector of residuals, and X and Z are the design matrices for fixed effects and additive genetic effects, respectively. The variance-covariance structure of random effects is as follows: ; in, and Let G and I represent the additive genetic variance and residual variance, respectively; G represents the genome relation matrix constructed based on SNP markers; and I is the identity matrix.
6. The breeding method according to claim 1, characterized in that, In step (5), the standardized execution method is as follows: Standardized breeding value = Estimated breeding value / σ; Where σ is the genetic standard deviation of the corresponding trait; The calculation method for the comprehensive breeding value is as follows: Overall breeding value = D×Y1 + E×Y2; Where D is the standardized PTNM estimated breeding value, E is the standardized GTNM estimated breeding value, and Y1 and Y2 are weighting coefficients.
7. The breeding method according to claim 1, characterized in that, In step (6), the retention rate for the first selection is 15%~20% for roosters and 45%~55% for hens, with only individuals with higher comprehensive breeding values being selected.
8. The breeding method according to claim 1, characterized in that, In step (6), the retention rate for the second selection is 10%~15% for roosters and 45%~55% for hens; hens with less than 10 eggs laid in the last four weeks are excluded, and it is ensured that more than 30% of the rooster families have offspring selected.
9. The breeding method according to claim 1, characterized in that, In step (6), when forming a family, the kinship coefficient between the rooster and hen to be paired is <6.25%.
10. The breeding method according to claim 1, characterized in that, In step (7), the elimination criteria for weak chicks include individuals with poor umbilical cord healing, low weight, hair loss, unstable standing posture, and obvious physiological deformities; the elimination criteria for individuals whose body shape and appearance do not conform to the breeding characteristics include individuals with obvious deviations in color and body structure.