A method for detecting the sex of hatching eggs in the early stage

Abstract

The present invention discloses a method for detecting the sex of hatching eggs in the early stage. The method includes: extracting allantoic fluid from hatching eggs in the early stage through an extraction device; obtaining the allantoic fluid metabolite characteristics after metabolomics analysis of the allantoic fluid, and performing bioinformatics analysis combined with in vitro cell culture to confirm sex-differentiated metabolites; further concentrating and fractionating the allantoic fluid to obtain low-abundance allantoic fluid containing sex-differentiated metabolites; performing spectral comparison analysis on the allantoic fluid to be detected, thereby constructing a multi-machine learning allantoic fluid sex classification model; detecting the sex of hatching eggs in the early stage through the model to achieve rapid detection of the sex of eggs. The full-chain process of "early minimally invasive sampling - differential metabolite screening - low-abundance component enrichment - multi-spectral machine learning" designed by the present invention realizes breakthroughs in multiple dimensions such as time window, accuracy, and cost controllability for poultry egg sex detection.

Description

Technical Field

[0001] The present invention relates to a method for detecting the sex of eggs, belonging to the technical field of agricultural and livestock product detection, and particularly to a method for detecting the sex of hatching eggs in the early stage of incubation. Background Art

[0002] Eggs are an important agricultural product and a major source of staple food nutrients and protein in daily life. The egg production has always accounted for a major proportion of the poultry egg production. However, a key problem plaguing the egg chicken industry is that every year, several-day-old roosters are prematurely eliminated due to their inability to lay eggs and poor market applicability. Facing the problems of resource waste and animal welfare, the core of the research is to perform early, accurate, and rapid sex identification of chicken embryos. Allantoic fluid, as an exogenous sample of the embryo, has the characteristics of relatively easy sampling, low invasiveness, and high hatching rate. At present, some scholars extract allantoic fluid from hatching eggs on the 7th to 10th day of incubation, measure the concentration of estrone sulfate in the allantoic fluid, and use the enzyme immunoassay method ELISA (Enzyme-Linked ImmunoSorbent Assay) to determine the concentration of estrone sulfate, and then use it to determine the sex of the chicken embryo in the hatching egg. There are also scholars who have designed a method for identifying the sex of eggs, including the collection, transportation, pretreatment of chicken embryo allantoic fluid, and the detection of estrogen concentration in the allantoic fluid. This provides valuable information for understanding the sex determination of chicken embryos. However, the allantoic fluid itself has complex components and is dynamic. The existing research foundation on allantoic fluid is relatively weak, especially facing major challenges in balancing costs, rapid detection, and low invasiveness requirements. Therefore, it is of great significance to explore the sex difference information of allantoic fluid and construct an efficient and accurate rapid detection model based on this. Summary of the Invention

[0003] In order to solve the problems existing in the background art, the present invention provides a method for detecting the sex of hatching eggs in the early stage. After performing metabolomics analysis on allantoic fluid, the present invention method obtains the allantoic fluid metabolite characteristics, and combines bioinformatics analysis with in vitro cell culture to confirm the sex-differentiated metabolites; then performs concentration and fractionation treatment on the allantoic fluid to obtain low-abundance allantoic fluid containing sex-differentiated metabolites; performs spectral contrast analysis on the multi-component allantoic fluid to be detected, thereby constructing a multi-component - multi-machine learning allantoic fluid sex classification model to achieve rapid classification of the sex of chicken embryos.

[0004] The technical solution adopted by the present invention is as follows:

[0005] The method for detecting the sex of hatching eggs in the early stage of the present invention includes:

[0006] Step 1: Build an extraction device, and extract allantoic fluid from several hatching eggs with known sex in the early stage of incubation through the extraction device.

[0007] Step 2: Confirm sex-differential metabolites after performing metabolomics analysis and bioinformatics analysis on the allantoic fluid of each hatching egg in sequence.

[0008] Step 3: Perform concentration and fractionation treatment on the allantoic fluid of each hatching egg to obtain allantoic fluid containing sex-differential metabolites.

[0009] Step 4: Obtain fingerprint spectral feature data of the allantoic fluid containing sex-differential metabolites of each hatching egg and add their respective known sex labels, thereby constructing a training set and inputting it into multiple machine learning models for training, testing, and verification to obtain a trained multiple machine learning allantoic fluid sex classification model.

[0010] Step 5: Extract the allantoic fluid of the hatching eggs in the early stage of incubation to be detected through an extraction device, then perform the same processing as in Steps 3 and 4 to obtain fingerprint spectral feature data of the allantoic fluid containing sex-differential metabolites to be detected, and input it into the multiple machine learning allantoic fluid sex classification model. After processing, obtain the sex of the hatching eggs in the early stage of incubation to be detected, realizing rapid sex detection of hatching eggs in the early stage of incubation.

[0011] In the aforementioned Step 1, the extraction device includes a light source, an extractor, a laser hole opener, and an egg tray. After cleaning the hatching eggs in the early stage of incubation, place them vertically on the egg tray. Place the light source on the eggshell on the top surface of the hatching eggs in the early stage of incubation and vertically downward towards the inside of the hatching eggs in the early stage of incubation to penetrate the positions of the allantoic fluid, chicken embryos, blood vessels, egg yolks, and air chambers inside the hatching eggs in the early stage of incubation, so as to avoid other parts and facilitate the extraction of allantoic fluid. When extracting allantoic fluid, the hatching eggs in the early stage of incubation are in a dark environment. Penetrate the position of the allantoic fluid of the hatching eggs in the early stage of incubation through the light source, then perform laser hole opening on the eggshell of the hatching eggs in the early stage of incubation through the laser hole opener to connect to the position of the allantoic fluid, and finally extract the allantoic fluid from the hatching eggs through the extractor. Finally, it is also necessary to seal the micropores with liquid wax to ensure the normal incubation of the chicken embryos.

[0012] In the aforementioned Step 1, the early stage of incubation specifically refers to 5 - 10 days of hatching of the hatching eggs.

[0013] In the aforementioned Step 2, for metabolomics analysis of the allantoic fluid of each hatching egg, first obtain each metabolite in the allantoic fluid of each hatching egg with a known sex through the liquid chromatography and tandem mass spectrometry method LC-MS / MS (Liquid Chromatography-Tandem Mass Spectrometry) in metabolomics analysis, and then screen out sex-differential metabolites from each metabolite in the allantoic fluid according to each metabolite in the allantoic fluid with a known sex using bioinformatics analysis methods.

[0014] In the aforementioned Step 2, the sex-differential metabolites include L-ornithine, proline, cytidine, etc.

[0015] In step 3, the allantoic fluid of the hatching eggs to be detected is first concentrated, and then classified according to abundance to obtain high-abundance allantoic fluid, medium-abundance allantoic fluid, and low-abundance allantoic fluid. The low-abundance allantoic fluid is the allantoic fluid containing sex-differential metabolites, so as to enrich the metabolite information of the low-abundance allantoic fluid.

[0016] In step 4, for the allantoic fluid containing sex-differential metabolites of each hatching egg, the allantoic fluid is enriched on the surface of a crystal or a glass slide and then spectral scanning is performed for acquisition, so as to obtain the fingerprint spectral characteristic data of the allantoic fluid.

[0017] The minimally invasive allantoic fluid extraction device designed by the method of the present invention can not only ensure the hatching rate of chicken embryos, but also achieve rapid collection. In the early stage of hatching egg incubation, the method also confirmed the sexual dimorphism of allantoic fluid metabolites and sex-differential metabolites of chicken embryos through the combination of liquid chromatography and tandem mass spectrometry technology LC-MS / MS and bioinformatics analysis. The designed concentration and classification strategy effectively enriches the low-abundance substances in the allantoic fluid, constructs a multi-component and multi-machine learning spectral sex classification model, and the results prove the contribution of the fingerprint spectral characteristics of low-abundance molecules in the allantoic fluid to sex classification, realizing the rapid classification of chicken embryo gender.

[0018] The early-stage hatching egg sex detection system of the present invention includes:

[0019] A data acquisition unit, configured to confirm the allantoic fluid containing sex-differential metabolites, obtain the fingerprint spectral characteristic data of the allantoic fluid containing sex-differential metabolites and add sex labels, so as to construct a training set.

[0020] A model training unit, configured to construct a multi-machine learning model and train it through the training set to obtain a trained multi-machine learning allantoic fluid sex classification model.

[0021] A sex detection unit, configured to detect the fingerprint spectral characteristic data of the allantoic fluid containing sex-differential metabolites to be detected through the multi-machine learning allantoic fluid sex classification model, obtain the sex of the hatching eggs in the early stage to be detected, and display it on a display.

[0022] The electronic device of the present invention includes: a memory and a processor coupled to each other, wherein the memory stores program data, and the processor calls the program data to execute the method as described above.

[0023] The computer-readable storage medium of the present invention stores program data thereon, and when the program data is executed by a processor, the method as described above is implemented.

[0024] The beneficial effects of the present invention are:

[0025] The present invention for the first time identifies L-ornithine, proline, and cytidine in allantoic fluid as sex dimorphism markers (the area under the curve value AUC (Area Under the Curve) reaches 0.87), and verifies their function of regulating sex gene expression through in vitro gonadal cell culture, providing a molecular basis for sex identification.

[0026] By integrating allantoic fluid metabolomics and infrared fingerprint spectroscopy, the present invention systematically reveals sex-specific metabolite characteristics, and the construction of sex-specific spectral fingerprints makes up for the deficiency of metabolomics in analyzing the global chemical composition.

[0027] The present invention fuses concentration and fractionation methods, spectral technology, and machine learning to construct a sex classification model for multi-component allantoic fluid, proving the effectiveness of the fingerprint spectral characteristics of low-abundance substances in allantoic fluid in sex classification, which is helpful for rapid sex detection in the early stage of chicken embryo incubation.

[0028] The full-chain process of "early minimally invasive sampling - differential metabolite screening - low-abundance component enrichment - multi-spectral machine learning" designed by the present invention realizes breakthroughs in multiple dimensions such as time window, accuracy, and cost controllability for poultry egg sex detection. Description of the Drawings

[0029] Figure 1 is the flow chart of the method for detecting the sex of the breeding eggs of the present invention;

[0030] Figure 2 is the schematic diagram of the minimally invasive extraction device of the present invention;

[0031] Figure 3 is the classification result diagram of allantoic fluid metabolomics of the present invention;

[0032] Figure 4 is the sex difference metabolite module and receiver operating characteristic curve ROC (Receiver Operating Characteristic Curve) diagram of the present invention;

[0033] Figure 5 is the result diagram of the multi-machine learning sex classification model of the present invention;

[0034] In the figure: 1. Light source, 2. Breeding egg, 201. Allantoic fluid, 202. Chicken embryo, 203. Eggshell, 204. Blood vessel, 205. Egg yolk, 206. Air chamber, 3. Extractor, 4. Laser hole opener, 5. Egg tray. Detailed Embodiments

[0035] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0036] As Figure 1As shown in the figure, the method for detecting the sex of early-stage incubated breeding eggs of the present invention is as follows:

[0037] First, build an extraction device. As Figure 2 shown, the extraction device includes a light source 1, an extractor 3, a laser hole opener 4, and an egg tray 5. After cleaning the early-stage incubated breeding egg 2, place it vertically on the egg tray 5. Place the light source 1 on the eggshell 203 of the top surface of the early-stage incubated breeding egg 2 and vertically downward towards the inside of the early-stage incubated breeding egg 2 to perspective the positions of the allantoic fluid 201, chicken embryo 202, blood vessels 204, egg yolk 205, and air chamber 206 inside the early-stage incubated breeding egg 2, so as to avoid other parts and facilitate the extraction of the allantoic fluid 201. When extracting the allantoic fluid 201, the early-stage incubated breeding egg 2 is in a dark environment. Through the light source 1, perspective the position of the allantoic fluid 201 of the early-stage incubated breeding egg 2, and then use the laser hole opener 4 to make a laser hole on the eggshell 203 of the early-stage incubated breeding egg 2 to connect to the position of the allantoic fluid 201. The angle range of the extractor 3 is controlled within the range of 30-120° of the micro-hole section. Finally, extract the allantoic fluid 201 from the breeding egg 2 through the extractor 3. Finally, liquid wax is also needed to seal the micro-holes to ensure the normal hatching of the chicken embryo 202. Extract the allantoic fluid 201 from several early-stage incubated breeding eggs 2 with known genders through the extraction device. The early stage is specifically 5-10 days after the breeding egg is incubated.

[0038] Then, perform metabolomics analysis and bioinformatics analysis on the allantoic fluid 201 of each breeding egg 2 in turn to confirm sex-differentiated metabolites. Perform metabolomics analysis on the allantoic fluid 201 of each breeding egg 2. First, obtain each metabolite in the allantoic fluid 201 of each breeding egg 2 with a known gender through the liquid chromatography and tandem mass spectrometry method LC-MS / MS in metabolomics analysis. Then, use bioinformatics analysis methods to screen out sex-differentiated metabolites from each metabolite in the allantoic fluid 201 according to each metabolite in the allantoic fluid 201 with a known gender. Metabolomics analysis is used to compare the metabolites of the allantoic fluid 201 of male and female chicken embryos 202, and then the machine learning and weighted gene co-expression network analysis methods are used to screen out the sex-differentiated metabolite module. The sex-differentiated metabolite module is L-ornithine, proline, cytidine, etc. The area under the curve value AUC of the sex-differentiated metabolite module for the sex classification result of the chicken embryo 202 is 0.87.

[0039] Then, verify the reliability of the sex-differentiated metabolites by in vitro culturing gonadal cells. Verifying by in vitro culturing gonadal cells means setting different concentrations of L-ornithine, proline, and cytidine for interfering with the gonads and mesonephric cells of the chicken embryo 202, culturing in vitro for 24-48 hours, and detecting the expression of sex-specific genes based on real-time quantitative polymerase chain reaction PCR (Polymerase Chain Reaction) to verify the effectiveness of the sex-differentiated metabolites. The sex-differentiated metabolites include L-ornithine, proline, cytidine, etc.

[0040] The allantoic fluid 201 of each hatching egg 2 is subjected to concentration and fractionation treatment. The allantoic fluid 201 of the hatching egg 2 to be detected is first concentrated, and the concentration includes, but is not limited to, evaporation concentration, ultrafiltration concentration, and dialysis concentration; then it is fractionated according to abundance to obtain high-abundance allantoic fluid, medium-abundance allantoic fluid, and low-abundance allantoic fluid, and the allantoic fluid 201 containing sex-differentiated metabolites is obtained, where the low-abundance allantoic fluid is the allantoic fluid 201 containing sex-differentiated metabolites to enrich the metabolite information of the low-abundance allantoic fluid. The high-abundance allantoic fluid is the allantoic fluid 201 with a molecular weight greater than 30 KDa, the medium-abundance allantoic fluid is the allantoic fluid 201 with a molecular weight between 30 KDa and 10 KDa, and the low-abundance allantoic fluid is the allantoic fluid 201 with a molecular weight lower than 10 KDa. The method for concentrating and fractionating the allantoic fluid 201 is an ultrafiltration concentration and fractionation strategy for the sample. Different components of the allantoic fluid 201 are pre-concentrated onto the surface of a crystal or a glass slide, and the optimal spectral parameters are determined to obtain the fingerprint spectrum. Specifically, during implementation, the infrared spectral fingerprint characteristic peak of the allantoic fluid 201 at 1650 cm - ⁻¹ is attributed to the amide I anti-parallel β-sheet, indicating the stretching vibration of the protein CO. The lipid-specific bands include the band at 1454 cm - ⁻¹, corresponding to the CH 2 bending in the lipid acyl chain, and 1390 cm - ⁻¹, representing the symmetric stretching of the COO - of fatty acids and amino acids. The band at 1210 cm - ⁻¹ is related to the asymmetric stretching of the PO 2 - in phospholipids and nucleic acids. The band at 1040 cm - ⁻¹ originates from the symmetric stretching of the PO 2 - in the diphosphate monoesters found in phosphorylated proteins and nucleic acids. The spectral region spanning 675 - 900 cm - ⁻¹ is the most prominent region for aromatic compounds. The spectral changes observed at approximately 918 cm - ⁻¹, 845 cm - ⁻¹, 676 cm - ⁻¹, and 486 cm - ⁻¹ can be attributed to the out-of-plane bending vibration of the CH groups in the substituted benzene ring, indicating aromatic compounds. In summary, the achieved classification accuracy can be attributed to the changes in protein conformation, the changes in lipid intensity, and the characteristics of amino acids and nucleic acids.

[0041] Then, allantoic fluid 201 containing sex-differentiated metabolites of each hatching egg 2 is obtained. After enrichment on the surface of a crystal or a glass slide, spectral scanning and acquisition are carried out. The spectrum includes spectral techniques such as infrared spectrum and Raman spectrum, so as to obtain the fingerprint spectral characteristic data of allantoic fluid 201. The infrared spectrum can provide in-depth understanding of molecular vibration, rotation, and stretching. The allantoic fluid concentration and fractionation strategy enriches low-abundance substances in allantoic fluid on the crystal surface, which helps to more deeply understand the absorption peaks unique to chicken embryo AF metabolites. During specific implementation, the infrared spectral differentiation region shows a correlation with the classification of identified metabolites. For example, protein-related metabolites: In the analysis on hatching days D8 and D9, amino acids such as proline, L-ornithine, and L-phenylalanine significantly increase in males. The protein structural characteristics of these amino acids can be reflected by the amide peak at 1650 cm - ⁻¹, indicating changes in protein conformation. Lipid-related metabolites: In the analysis on hatching day D9, 3-hydroxybutyric acid and D-(+)-malic acid significantly increase in males. The characteristics of these lipid metabolites can be reflected by the lipid characteristic peaks at 1454 cm - ⁻¹ and 1390 cm - ⁻¹, indicating sex differences in lipid metabolism. Nucleic acid-related metabolites: In the analysis on D10, uridine and cytidine significantly increase in females. The characteristics of these nucleic acid metabolites can be reflected by the PO - stretching vibration peaks at 1210 cm - ⁻¹ and 1040 cm 2 - ⁻¹, indicating sex differences in nucleic acid metabolism.

[0042] Then, the fingerprint spectral characteristic data is added with their respective known sex labels and constructed into a training set. The training set is input into a multi-machine learning model for training, testing, and verification, and a trained multi-machine learning allantoic fluid sex classification model is obtained.

[0043] In the specific implementation of the present invention, based on non-targeted metabolomics, the differential metabolites of allantoic fluid 201 of male and female chicken embryos 202 are studied. The allantoic fluid 201 extracted from Jinghong No. 1 hatching eggs 2 in an actual breeding scenario is selected as the test object of the example. First, liquid chromatography and tandem mass spectrometry technology LC-MS / MS are used to analyze the metabolites in allantoic fluid 201 of chicken embryos 202 at different hatching days. The classification results of orthogonal partial least squares discriminant analysis OPLS-DA (Orthogonal Partial Least Squares Discriminant Analysis) are as Figure 3 shown. The orthogonal component score values and principal component score values of males and females can be obtained. On the 9th day of hatching, the interpretation parameter R 2 = 0.997, and the prediction parameter Q 2= 0.779, indicating that the metabolites in the allantoic fluid 201 of chick embryo 202 have sexual dimorphism. Then, the results of permutation retention degree, interpretation parameters, and prediction parameters were obtained through 200 permutation tests. The interpretation parameter R 2 = 0.99, and the prediction parameter Q 2 = -0.0207, verifying the reliability of the model and ensuring no overfitting. The metabolites screened by weighted gene co-expression network analysis and orthogonal partial least squares discriminant analysis OPLS-DA were combined to construct a machine learning data set, and the results of the evaluation of the feature importance of metabolites were obtained, as Figure 4 shown. Metabolites with higher contribution degrees were selected as sex-differential metabolites, including L-ornithine, proline, cytidine, etc. The results of using sex-differential metabolites for sex classification showed that the area under the receiver operating characteristic curve ROC was 0.84.

[0044] Then, in vitro cell culture was used to verify the effectiveness of sex-differential metabolites. First, the gonad and mesonephros tissues of chick embryo 202 were extracted and cultured in a sterile environment. The gonad cells were treated with sex-differential candidate metabolites at different concentration gradients, and the cell counting kit CCK8 (Cell Counting Kit-8) was used to determine that the metabolite concentration most suitable for cell proliferation was 200 μM.

[0045] Based on real-time quantitative polymerase chain reaction (PCR) analysis, the differences in the expression of sex marker genes between gonadal cells treated with 200 μM L-ornithine, proline, and cytidine and untreated control cells were examined. The results showed that after treatment with cytidine (test result parameter P < 0.001) and L-ornithine (test result parameter P < 0.001), the expression of anti-Müllerian hormone (AMH) in gonadal cells of male and female chicken embryos 202 was significantly reduced, further expanding the difference in AMH expression between the two sexes. Treatment with cytidine (test result parameter P < 0.01) significantly downregulated the expression of DMRT1 (Double sex and mab-3 related transcription factor 1) in the gonads of male chicken embryos 202, while proline (test result parameter P < 0.05) induced an upregulation, further increasing the difference in DMRT1 expression between males and females. In the gonadal cells of female chicken embryos 202, both cytosine (test result parameter P < 0.01) and L-ornithine (test result parameter P < 0.01) significantly downregulated the expression of CYP19A1 (cytochrome P450, family 19, subfamily A, polypeptide 1), while proline upregulated its expression in male cells. Treatment with cytidine and proline attenuated the difference in CYP19A1 expression between the two sexes. Cytidine (test result parameter P < 0.01) and L-ornithine (test result parameter P < 0.01) also significantly downregulated the expression of FOXL2 (forkhead box L2) in female gonads, while proline upregulated its expression in males. These treatments also attenuated the difference in FOXL2 expression between the two sexes.

[0046] Such as Figure 5As shown, the present invention uses a variety of machine learning to construct a spectral classification model based on the fingerprint spectral data of multi-component allantoic fluid: random forest, support vector machine and extreme gradient boosting are deeply trained, and five parameters are used, including the area under the receiver operating characteristic curve ROC, classification accuracy, precision, recall rate, and receiver operating characteristic curve to comprehensively evaluate the classification performance of the spectrum. In specific implementation, the allantoic fluid 201 of male chicken embryos 202 is used as the experimental group and the female is used as the control group. The gender support vector machine SVM (Support Vector Machine) classification results of the chicken embryos 202 under different concentration and classification parameters are as follows: 1) low abundance: precision: 88%, recall rate: 92%, accuracy: 88%, area under the ROC curve AUC: 0.96; 2) medium abundance: precision: 78%, recall rate: 83%, accuracy: 80%, area under the ROC curve AUC: 0.92; 3) high abundance: precision: 70%, recall rate: 73%, accuracy: 68%, area under the ROC curve AUC: 0.79. The results show that: the high-abundance substances in the allantoic fluid 201 will mask the spectral signals of the low-abundance substances, thereby limiting their contribution to the gender classification spectrum. When there are only spectral signals of low-molecular-weight substances in the allantoic fluid 201, the spectral classification results are significantly improved. The research results of the present invention emphasize that the spectral classification results of the low-abundance allantoic fluid 201 after ultrafiltration concentration are better than the spectral classification results of the untreated and high-abundance allantoic fluid 201.

[0047] Finally, the allantoic fluid 201 of the early-incubation breeding eggs 2 to be tested is extracted by the extraction device, and its fingerprint spectral feature data is obtained, which is then input into the multi-machine learning allantoic fluid gender classification model for processing to obtain the gender of the early-incubation breeding eggs 2 to be tested, thereby realizing rapid gender detection of the early-incubation breeding eggs 2.

[0048] The use of non-targeted metabolomics methods combined with bioinformatics analysis proved the sex dimorphism of allantoic fluid 201 metabolites in chicken embryo 202, providing a reference for the feasibility of using low-abundance substances for sex classification. The significant effect of sex-differentiated metabolites on sex marker genes was verified by in vitro cell culture experiments. In view of the complexity of allantoic fluid 201 samples, designing a concentration and classification strategy during the early incubation process can effectively simplify complex mixtures such as allantoic fluid 201, enrich low-abundance substances, and ensure the characteristic spectral contribution of low-abundance substances in allantoic fluid 201. The present invention realizes high-precision and non-destructive detection of early sex of breeding eggs through innovative minimally invasive sampling, sex-differentiated metabolite screening and multimodal data analysis technology, which has both scientific value and industrial application prospects, and provides technical solutions for improving the efficiency of poultry farming and ethical disputes (such as eliminating male chicks).

[0049] The present invention also establishes a sex detection system for hatching early-stage breeding eggs, which includes a data acquisition unit, a model training unit, and a sex detection unit. The data acquisition unit is used to confirm the allantoic fluid 201 containing sex-differentiated metabolites, obtain the fingerprint spectral feature data of the allantoic fluid 201 containing sex-differentiated metabolites, and add sex labels, so as to construct a training set. The model training unit is used to construct multiple machine learning models and train them through the training set to obtain a trained multiple machine learning allantoic fluid sex classification model. The sex detection unit is used to detect the fingerprint spectral feature data of the allantoic fluid 201 containing sex-differentiated metabolites to be detected through the multiple machine learning allantoic fluid sex classification model, obtain the sex of the breeding eggs 2 in the early stage of hatching to be detected, and display it on a display.

[0050] The method of the present invention reveals the sexual dimorphism of allantoic fluid metabolites. The designed concentration and fractionation method combined with multiple machine learning proves the contribution of the spectral features of low-abundance substances in allantoic fluid to sex classification. This research method can also provide new insights for the development of sex identification technology for poultry eggs.

[0051] Those skilled in the art should understand that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of the present application can be implemented in various computer languages. The present application is described according to the flowcharts of the methods, systems, and computer program products of the embodiments of the present application.

[0052] Although the preferred embodiments of the present application have been described, those skilled in the art can make additional changes and modifications to these embodiments once they know the basic creative concepts. Therefore, the present invention is intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0053] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the equivalent technology of the present invention, the present application also intends to include these changes and modifications.

Claims

1. A method for detecting the sex of early hatching eggs, characterized in that: include: Step 1: constructing an extraction device, and using the extraction device to extract the allantoic fluid (201) from a number of early hatching eggs (2) of known gender; Step 2: performing metabolomics analysis and bioinformatics analysis on the allantoic fluid (201) of each egg (2) to confirm the metabolites with gender differences; Step 3: Concentrating and fractionating the allantoic fluid (201) of each breeding egg (2) to obtain the allantoic fluid (201) containing sex-differentiated metabolites; Step 4: Obtain the fingerprint spectral feature data of the allantoic fluid (201) containing sex-differentiated metabolites of each breeding egg (2) and add the labels of their respective known sexes, thereby constructing a training set, inputting it into a multi-machine learning model for training, and obtaining a trained multi-machine learning allantoic fluid sex classification model; Step 5: extracting the allantoic fluid (201) of the early hatching breeding eggs (2) to be tested by an extraction device, and then performing the same processing as in steps 3 and 4 to obtain the fingerprint spectral feature data of the allantoic fluid (201) to be tested containing gender-differentiated metabolites, and inputting the data into a multi-machine learning allantoic fluid gender classification model, and obtaining the gender of the early hatching breeding eggs (2) to be tested after processing, thereby realizing rapid gender detection of the early hatching breeding eggs (2); In the step 2, the sex-differentiated metabolites include L-ornithine, proline and cytidine.

2. The method for detecting sex of early hatching eggs according to claim 1, wherein: In the step 1, the extraction device comprises a light source (1), an extractor (3), a laser hole opener (4) and an egg tray (5). The early incubation breeding egg (2) is vertically placed on the egg tray (5), and the light source (1) is placed on the eggshell (203) on the top surface of the early incubation breeding egg (2) and vertically downward toward the interior of the early incubation breeding egg (2). When extracting the allantoic fluid (201), the early incubation breeding egg (2) is in a dark environment, and the position of the allantoic fluid (201) of the early incubation breeding egg (2) is seen through the light source (1). Then, the laser hole opener (4) is used to perform a laser hole opening on the eggshell (203) of the early incubation breeding egg (2) to connect the position of the allantoic fluid (201). Finally, the allantoic fluid (201) is extracted from the breeding egg (2) by the extractor (3).

3. The method for detecting sex of early hatching eggs according to claim 1, wherein: In step 1, the early incubation period specifically refers to the 5-10 days of incubation of the eggs.

4. The method for detecting sex of early hatching eggs according to claim 1, wherein: In the step 2, a metabolomics analysis is performed on the allantoic fluid (201) of each breeding egg (2). First, each metabolite in the allantoic fluid (201) of each breeding egg (2) of known sex is obtained by liquid chromatography and tandem mass spectrometry (LC-MS / MS) in metabolomics analysis. Then, based on each metabolite in the allantoic fluid (201) of each known sex, a bioinformatics analysis method is used to screen out sex-differentiated metabolites in the allantoic fluid (201).

5. The method for detecting sex of early hatching eggs according to claim 1, wherein: In the step 3, the allantoic fluid (201) of the breeder eggs (2) to be tested is first concentrated, and then graded according to the abundance to obtain high-abundance allantoic fluid, medium-abundance allantoic fluid and low-abundance allantoic fluid, wherein the low-abundance allantoic fluid is the allantoic fluid (201) containing sex-differentiated metabolites.

6. The method for detecting sex of early hatching eggs according to claim 1, wherein: In the step 4, for the allantoic fluid (201) containing sex-differentiated metabolites of each breeding egg (2), the allantoic fluid (201) is enriched on a crystal or a glass slide surface and then spectral scanning and collection is performed, thereby obtaining fingerprint spectral characteristic data of the allantoic fluid (201).

7. A system for detecting sex of early hatching eggs according to any one of claims 1 to 6, characterized in that: include: A data acquisition unit is used to confirm the allantoic fluid (201) containing gender-differentiated metabolites, obtain fingerprint spectral feature data of the allantoic fluid (201) containing gender-differentiated metabolites and add gender labels, thereby constructing a training set; A model training unit, used for constructing a multi-machine learning model and training it through a training set to obtain a trained multi-machine learning allantoic fluid gender classification model; The sex detection unit is used to detect the fingerprint spectral feature data of the allantoic fluid (201) containing sex-differentiated metabolites to be detected by using a multi-machine learning allantoic fluid sex classification model, obtain the sex of the early hatching eggs (2) to be detected and display it on a display.

8. An electronic device, characterized in that: include: A memory and a processor coupled to each other, wherein the memory stores program data, and the processor calls the program data to execute the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having program data stored thereon, characterized in that: When the program data is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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