Breeding method for sweet corn hybrid combination based on genetic regulation of sugar metabolism

Abstract

This application relates to the field of crop hybridization breeding technology, and discloses a method for breeding sweet corn hybrid combinations based on the genetic regulation of sugar metabolism, including obtaining detached leaf discs of sweet corn inbred lines, and incubating them with exogenous sugar substrates, abscisic acid, and plasma membrane H... + The induction buffer containing the ATPase inhibitor was vacuum permeated and cooled; samples were extracted at different times to determine the fructose and sucrose content, and the dynamic change rate of the ratio was calculated; the molecular marker genetic distance and average genetic distance between each inbred line were calculated; field agronomic trait data were obtained, and the dynamic change rate was used to weight the data to obtain weighted phenotypic data, which were then substituted into the genetic model to calculate the general and specific combining ability effects; inbred lines with positive combining ability and genetic distance greater than the average genetic distance were selected as male and female parents for hybridization. This invention eliminates interference from plant source-sink translocation, integrates metabolic characteristics with field yield, and ensures that the selected combinations have strong stress resistance and high heterosis.

Description

Technical Field

[0001] This invention relates to the field of crop hybrid breeding technology, specifically to a method for breeding sweet corn hybrid combinations based on genetic regulation of sugar metabolism. Background Technology

[0002] Sweet corn is significantly affected by changes in environmental temperature during its growth and development, and the stability of carbohydrate metabolism under cold stress is a key factor determining its final yield and quality. In the current breeding process of sweet corn hybrid combinations, parental evaluation mainly relies on field phenotypic surveys, combining ability determination, and molecular marker-assisted selection.

[0003] Conventional physiological and biochemical tests for stress resistance are usually conducted at the whole-plant level. However, carbohydrate metabolism within the plant is affected by complex source-sink relationships and long-distance phloem transport processes, making it impossible to quantify the basal conversion rate of local mesophyll cells under stress. Furthermore, in current breeding systems, macroscopic field agronomic traits and microscopic physiological metabolic indicators are independent. Existing statistical methods cannot isolate the indirect effects of other phenotypic traits on yield, and there is a lack of quantitative models that mathematically integrate microscopic dynamic characteristics of carbohydrate metabolism with macroscopic field yield.

[0004] Simply relying on combining ability data or molecular marker genetic distance for parental pairing cannot fully assess the biochemical metabolic potential of inbred lines under adverse conditions, making it difficult to combine nucleic acid sequence polymorphism with physiological metabolic advantages. As a result, the selected sweet corn hybrid combinations have weak environmental adaptability in complex cultivation environments, and it is difficult to achieve a coordinated and stable improvement in yield and quality. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a method for breeding sweet corn hybrid combinations based on genetic regulation of sugar metabolism. This method solves the problem that existing sweet corn breeding methods struggle to correlate microscopic physiological responses to sugar metabolism under stress with macroscopic field yield phenotypes, resulting in poor environmental adaptability of the bred hybrid combinations and difficulty in synergistically improving yield and quality.

[0006] To achieve the above objectives, the present invention provides the following technical solution: This invention provides a method for breeding sweet corn hybrid combinations based on genetic regulation of sugar metabolism, employing the following technical solution: To obtain detached leaf discs from sweet corn inbred line seedlings; The isolated leaf disc was immersed in an substrate containing exogenous sugar substrate, abscisic acid, and plasma membrane H. + Vacuum permeation treatment was performed in the induction buffer containing ATPase inhibitors and surfactants; The detached leaf discs that have undergone vacuum permeation treatment were placed in a low-temperature environment for cooling treatment; samples of the detached leaf discs were extracted at different time points, and the sucrose and fructose contents in the samples were measured respectively, and the dynamic change rate of the ratio of fructose content to sucrose content over time was calculated. Obtain the molecular marker genetic distances between each pair of sweet corn inbred lines, and calculate the average molecular marker genetic distances among all lines; Obtain field agronomic trait data for each sweet corn inbred line; The field agronomic trait data of the sweet corn inbred lines are weighted using the dynamic change rate to obtain weighted phenotypic data. The weighted phenotypic data are then substituted into the genetic model to calculate the general combining ability effect and the specific combining ability effect of each sweet corn inbred line. Two sweet corn inbred lines were selected as the male and female parents, respectively, with positive values ​​for both general and specific combining ability effects and a molecular marker genetic distance greater than the average molecular marker genetic distance.

[0007] By adopting the above technical solution, this invention integrates in vitro physiological and biochemical testing with macroscopic population genetic analysis, achieving the following effects: When sweet corn plants are subjected to low-temperature stress, their internal carbohydrate distribution and transport networks are reprogrammed. This invention quantifies the crop's stress-resistance metabolic potential by artificially intervening to block local transport and monitoring the hydrolysis process.

[0008] The specific mechanism of action can be divided into the following steps: The isolated leaf disc was placed in a specific induction buffer. The plasma membrane H in the induction buffer... + -ATPase inhibitors specifically bind to and inhibit proton pump activity. Under normal physiological conditions, the plasma membrane H... + The transmembrane proton gradient generated by ATPase hydrolysis of ATP is the core driving force for sucrose loading into the phloem via the apoplast pathway. Inhibiting the activity of this enzyme blocks sucrose loading and transport in the phloem at both physical and biochemical levels, forcibly confining exogenously absorbed sugar substrates within mesophyll cells and their apoplast space, forming an independent local metabolic assay system.

[0009] Abscisic acid in the induction buffer acts as an abiotic stress signaling molecule, activating the sucrose non-fermentative protein kinase signaling pathway in plant tissues. Under the synergistic effect of cold stress from cooling treatment, the activity of invertase in mesophyll cells changes, catalyzing the hydrolysis of sucrose.

[0010] The dynamic change rate of the fructose to sucrose ratio was continuously measured. As a direct product of sucrose hydrolysis, the rate of fructose monosaccharide conversion and accumulation reflects the basal metabolic response rate of plants in mobilizing and converting carbohydrates for intracellular osmotic regulation under abiotic signals and osmotic stress. The dynamic change rate directly corresponds to the responsiveness of the genetic regulatory network of sugar metabolism in each sweet maize inbred line.

[0011] Statistical models were used to separate the direct effect coefficient of dynamic change rate on yield per plant. This coefficient was then used to weight the original field phenotypic data, transforming microscopic physiological advantages at the metabolic level into macroscopic phenotypic evaluation indicators. Combining ability was calculated using an additive-dominant genetic model, and a predetermined molecular marker genetic distance threshold was superimposed to ensure that the final selected parental combinations possessed the necessary resistance to sugar metabolism and sufficient allele heterozygosity, thus mechanistically maximizing heterosis and phenotypic stability.

[0012] Preferably, the specific steps for obtaining the detached leaf disc of the sweet corn inbred line seedling are as follows: after germinating the seeds of the sweet corn inbred line to be tested, hydroponically culture them until the seedlings grow to the three-leaf-one-heart stage, collect the third fully unfolded leaf, and drill to obtain the detached leaf disc, avoiding the main leaf vein.

[0013] By adopting the above technical solution, the three-leaf-one-heart stage is a critical developmental node in maize seedlings, marking the transition from heterotrophic growth of seed endosperm to photosynthetic autotrophic growth. At this time, the source-sink relationship of the third fully unfolded leaf is established, and the expression of enzymes related to photosynthesis and sugar metabolism is active. Sampling away from the main leaf vein eliminates interference from the main vascular bundle system on local metabolic exchange, maintaining the homogeneity of the cell composition of the disc tissue of a single detached leaf.

[0014] Preferably, the exogenous sugar substrate is sucrose, and its concentration in the induction buffer is 150–180 mmol / L; the concentration of abscisic acid is 10–15 μmol / L. The plasma membrane H + - The ATPase inhibitor is sodium metavanadate, with a concentration of 0.1–0.5 mmol / L; The surfactant is Tween-20, with a volume percentage concentration of 0.05% to 0.10%.

[0015] By employing the above technical solutions, sucrose at 150–180 mmol / L provides a saturated biochemical metabolic substrate and generates appropriate extracellular osmotic pressure. Abscisic acid at 10–15 μmol / L is within the physiologically effective concentration range for stimulating stomatal closure and stress-related gene expression, maintaining the cascade amplification of intracellular stress signals. Sodium metavanadate at 0.1–0.5 mmol / L reaches biochemical saturation at enzyme binding sites, effectively inhibiting proton pump operation. Tween-20 at 0.05%–0.10% reduces liquid phase surface tension, weakens the hydrophobic barrier of the leaf epidermal wax layer, and promotes the entry of buffer solution into the intercellular spaces of mesophyll cells along stomatal channels.

[0016] Preferably, the base solvent of the induction buffer is a potassium 2-(N-morpholine) ethanesulfonate buffer with a concentration of 10-20 mmol / L, and the pH value of the induction buffer is 5.5-6.0.

[0017] By employing the above technical solution, potassium 2-(N-morpholine)ethanesulfonate possesses a stable in vitro buffering capacity. The weakly acidic environment of pH 5.5–6.0 matches the natural pH of the plant exosome space, maintaining the optimal catalytic conformation of cell wall-bound acid invertases, while simultaneously preventing sodium metavanadate from polymerizing and losing its inhibitory activity at unsuitable pH values.

[0018] Preferably, the specific operating parameters for the vacuum permeation treatment are: evacuate the system pressure to -0.06 to -0.08 MPa and maintain the pressure for 5 to 10 minutes; Then, the pressure was released at a constant rate to normal pressure within 30 to 60 seconds.

[0019] By employing the above technical solution, a negative pressure of -0.06 to -0.08 MPa forces the air free in the intercellular spaces of the mesophyll cells out of the tissue, and the pressure holding phase ensures the complete venting process. The uniform decompression process of 30 to 60 seconds allows the external induction buffer to be slowly perfused into the intercellular spaces under the physical action of atmospheric pressure, avoiding damage to the plasma membrane structure caused by the mechanical shear force generated by instantaneous decompression.

[0020] Preferably, the specific operating parameters for the cooling process are as follows: The initial ambient temperature was 25℃, and the temperature was linearly reduced to 8-12℃ at a cooling rate of 1.5-2.5℃ / h, and then kept constant at this temperature for 10-14 hours under dark conditions.

[0021] By adopting the above technical solution, a linear cooling rate of 1.5 to 2.5℃ / h simulates the nighttime temperature drop curve under natural geographical climate, gradually activating the cold acclimatization transcription network in plants, and avoiding intracellular ice crystal formation and irreversible freezing damage caused by rapid cold shock.

[0022] At temperatures between 8 and 12°C, which are above the physiological critical range for chilling injury in maize tissues, the basic enzymatic activity required for substrate transformation is maintained. Dark conditions interrupt the photoreaction and carbon assimilation pathways, eliminating data interference from newly synthesized carbohydrates, ensuring that changes in the concentration of measured metabolites are entirely attributed to the breakdown and recombination of existing sugars.

[0023] Preferably, the different time points include: The starting time of the cooling treatment, the 4th to 6th hour after the cooling treatment started, and the ending time of the constant temperature maintenance; the specific calculation method of the dynamic change rate is as follows: calculate the difference in the ratio of fructose content to sucrose content in the detached leaf disc sample between two adjacent time points, and divide it by the corresponding time interval to obtain the dynamic change rate.

[0024] By employing the above technical solution, a basal metabolic reference line is established at the start of cooling; the peak values ​​of acute transcriptional expression and metabolic response in response to temperature fluctuations are captured during the 4-6 hour period after cooling initiation, corresponding to the end of linear cooling; and the endpoint of the biochemical system reaching a new substrate equilibrium state is recorded at the end of isothermal control. The differences are calculated in stages and the time dimension is standardized to obtain continuous enzymatic kinetic parameters that accurately reflect the rate characteristics of metabolic channel responses.

[0025] Preferably, the step of determining the sucrose and fructose content in the sample includes: The sugar metabolism extract of the isolated leaf disc sample was prepared by boiling ethanol, and the extract was determined by high performance liquid chromatography after concentration.

[0026] By adopting the above technical solution, the high-temperature boiling ethanol breaks the protein hydrogen bonds the moment it comes into contact with the plant tissue, causing irreversible thermal denaturation of the endogenous metabolic enzymes, thereby immediately terminating all enzymatic reactions at the time of extraction and locking in the sugar component ratio.

[0027] High-performance liquid chromatography (HPLC) physically separates monosaccharides and disaccharides in a mixture based on the retention time of the column matrix, enabling precise qualitative and quantitative analysis of trace sugar metabolites.

[0028] Preferably, the field agronomic trait data includes at least the measurement indicators reflecting yield and quality, specifically: number of rows per ear, number of grains per row, 100-grain weight, yield per plant, total sugar content of grains, and husk and residue rate.

[0029] By adopting the above technical solutions, the number of rows per ear, the number of grains per row, and the weight of 100 grains constitute the basic geometric elements of the yield structure of a single plant; the yield of a single plant characterizes the final cumulative amount of photosynthetic products. The total sugar content of the kernels and the bran content constitute the decisive components for quantitatively evaluating the palatability of sweet corn for processing and consumption, providing a multi-dimensional agronomic evaluation matrix.

[0030] Preferably, the step of weighting the field agronomic trait data of sweet corn inbred lines using the dynamic change rate includes: constructing a multiple linear regression equation with yield per plant as the dependent variable and dynamic change rate and other field agronomic trait indicators as independent variables; separating the direct effect coefficient of dynamic change rate on yield per plant through path analysis; and using the direct effect coefficient to weight the original measured value of yield per plant. The step of selecting the male and female parents for hybridization is further defined as follows: The molecular marker genetic distance between the two selected sweet corn inbred lines was greater than 1.2 times the average molecular marker genetic distance, and the pairing was completed using an incomplete diallel cross design.

[0031] By employing the above technical solutions, a mathematical model combining multiple linear regression and path analysis was used to analyze the collinear associations that mask each other among complex physiological phenotypes.

[0032] The direct action coefficients separated by path analysis eliminated the indirect interference effects of other agronomic traits in plants, and purified the net contribution weight of sugar metabolism response to final biomass under environmental stress.

[0033] By using this purification coefficient to mathematically adjust the original yield data, the breeding data matrix is ​​transformed from a single yield evaluation into a comprehensive evaluation of metabolic conversion efficiency and absolute yield.

[0034] A molecular genetic distance greater than 1.2 times the average value sets a strict threshold for nucleic acid sequence polymorphism differences, forcing the selected hybrid parents to have deep genetic population experience and differentiation, increasing the probability of offspring acquiring complementary dominant alleles, and ensuring that the hybrid combinations exhibit strong heterosis from both genomic and biochemical metabolic mechanisms.

[0035] This invention provides a method for breeding sweet corn hybrid combinations based on the genetic regulation of sugar metabolism. It has the following beneficial effects: 1. This invention utilizes exogenous sugar substrates, abscisic acid, and plasma membrane H... + - The induction buffer of the ATPase inhibitor was vacuum-permeated onto the detached leaf disc and combined with linear cooling treatment, thus blocking the phloem loading and transport of sucrose at the physical and biochemical levels. This forced carbohydrate metabolism to be confined to the local mesophyll cell space, thereby eliminating interference from the whole-plant source-sink transport pathway and accurately quantifying the background sugar metabolism conversion rate of sweet corn plants under cold stress.

[0036] 2. This invention measures the dynamic change rate of the fructose to sucrose ratio at a specific time point and uses path analysis to separate the direct effect coefficient of this dynamic change rate on the yield of a single plant. This is then used to weight the original field phenotypic data, thus eliminating the indirect statistical interference of other agronomic traits on yield. This allows for an objective mathematical fusion of microscopic stress physiological metabolic characteristics and macroscopic field yield indicators.

[0037] 3. This invention limits the selection criteria for the final hybridization combination by requiring both the male and female parents to simultaneously meet the following conditions: the weighted combined ability effect must be positive and the molecular marker genetic distance between each pair must be greater than 1.2 times the average molecular marker genetic distance. Therefore, this invention ensures that the selected parents have sufficient allelic differences from two dimensions: nucleic acid sequence polymorphism and biochemical metabolic capacity. This guarantees that the selected hybrid combinations have high genetic heterozygosity and stable field yield performance. Attached Figure Description

[0038] Figure 1 This is a flowchart illustrating the breeding method provided in an embodiment of the present invention. Figure 2 This is a curve diagram illustrating the vacuum permeation and programmed cooling treatment conditions of the detached leaf disk provided in an embodiment of the present invention. Figure 3 This is a bar chart comparing the initial sucrose permeation in sweet corn leaf tissue under different treatment conditions provided in this embodiment of the invention. Figure 4 This is a comparison chart showing the impact of different analysis modes provided in the embodiments of the present invention on the results of heritability measurement; Figure 5 A field yield and quality comparison chart of the F1 generation hybrid combinations obtained from the breeding process provided in this embodiment of the invention. Detailed Implementation

[0039] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0040] The foregoing explanation: The specific algorithms and operational standards for molecular marker genotyping, path analysis, and genetic parameter calculation involved in this invention all adopt the following defined operational steps and mathematical models: Methods for calculating molecular marker genotyping and genetic distance The specific procedure for extracting genomic deoxyribonucleic acid (DNA) from leaves of sweet corn inbred lines was performed using the hexadecyltrimethylammonium bromide method.

[0041] Polymerase chain reaction amplification was performed using extracted genomic deoxyribonucleic acid.

[0042] Amplification was performed using 100 pairs of standard simple repetitive sequence core primers evenly distributed across the ten maize chromosomes, published in the International Maize Genome Database. The amplification products were separated by electrophoresis on an 8% polyacrylamide gel with constant voltage of 150V and an electrophoresis time of 1.5 hours.

[0043] After electrophoresis, silver nitrate staining was used for development.

[0044] Record the amplification bands of each primer pair in each sweet corn inbred line. Amplification bands are recorded as number 1, and no amplification bands are recorded as number 0. In this way, the electrophoresis results of all tested inbred lines are converted into a genotype number matrix composed of numbers 0 and 1.

[0045] Based on the aforementioned genotype numerical matrix, the Dice coefficient method was used to calculate the pairwise molecular marker genetic distances between each sweet corn inbred line. The formula for calculating molecular marker genetic distances is fixed as follows: ; in, This represents the molecular marker genetic distance between two sweet corn inbred lines. This represents the total number of bands amplified by sweet corn inbred line A. This represents the total number of bands amplified by sweet corn inbred line B. This represents the number of common bands shared by sweet corn inbred line A and sweet corn inbred line B.

[0046] Data path analysis and weighted model: The dynamic rate of change of the ratio of fructose to sucrose content over time, along with the number of panicle rows, number of grains per row, 100-grain weight, and husk / residue percentage measured in field surveys, were used as the independent variable set. The measured yield per plant was used as the final dependent variable to construct a multiple linear regression equation. The mathematical expression of the multiple linear regression equation is: ; in, Indicates yield per plant. Indicates the rate of dynamic change. Indicates the number of rows of ears of grain. Indicates the number of rows. This indicates the weight of 100 grains. Indicates the peel and residue rate. Indicates the total sugar content of the grains. Represents the regression constant. ~ Represents the partial regression coefficients, This represents the random residual.

[0047] By solving the correlation coefficient matrix and the path coefficient matrix, the direct effect coefficient of the dynamic change rate on the yield per plant was separated. ) and indirect effect coefficient ( ).

[0048] After obtaining the direct effect coefficient, the raw measured values ​​of single-plant yield were weighted using the following formula to obtain a weighted phenotypic data matrix: ; in, This represents weighted table data. This represents the original measured value of yield per plant. This is the direct action coefficient that has been separated.

[0049] Calculation models for combining ability and heritability: The weighted phenotypic data obtained above ( Substitute these values ​​into an additive-dominant inheritance model based on incomplete diallel cross design to calculate combining ability and heritability parameters. The linear statistical model used is fixed as follows: ; in, Indicates the first The father and the first The maternal hybrid combination in the first... Weighted phenotypic observations in each repetition This represents the average value of the entire test group. Indicates the first The general combining power effect of the paternal parent, Indicates the first The general combining ability effect of the parent plant, Indicates the first The father and the first The special combining power effect of individual parent combinations This indicates the effect of random environmental errors.

[0050] By performing analysis of variance on the above model, the additive variance was extracted and calculated. ), dominant variance ( ) and environmental variance ( ).

[0051] The formulas for calculating narrow-sense heritability and broad-sense heritability are fixed as follows: ; ; in, Indicates broad heritability. Indicates additive variance. Indicates dominant variance. This represents the variance of environmental errors.

[0052] The strict entry criteria for determining the validity of batch data from cold stress and vacuum permeation blocking treatments are as follows: .

[0053] Experimental materials description: The maize materials used in the experiment were 100 sweet maize inbred lines provided by the Special Maize Genetics and Breeding Laboratory of Jilin Agricultural University.

[0054] In this invention, the preparation of the induction buffer is a fundamental prerequisite for subsequent vacuum osmosis and cooling treatments. This buffer utilizes exogenous sugar substrates, abscisic acid, and plasma membrane H₂O. + The synergistic effect of ATPase inhibitors and surfactants is used to construct an independent metabolic environment in isolated leaf disc tissues. The specific preparation process is detailed below through three specific preparation examples.

[0055] Before implementing the following preparation example, prepare the following mother liquor in advance: Abscisic acid stock solution: Weigh the abscisic acid powder, dissolve it completely in anhydrous ethanol, prepare an abscisic acid stock solution with a concentration of 10 mmol / L, and store it at -20℃ in the dark.

[0056] Sodium metavanadate depolymerization mother liquor: Weigh sodium metavanadate powder and dissolve it in ultrapure water. Adjust the pH value to 10.0 repeatedly with sodium hydroxide solution and hydrochloric acid solution, and boil repeatedly at 100℃ until the solution changes from yellow to colorless and transparent monomer state. Make up the volume to prepare a sodium metavanadate depolymerization mother liquor with a concentration of 100 mmol / L, and store it at -20℃.

[0057] Preparation Example 1: This preparation example provides a method for preparing an induction buffer for the treatment of detached sweet corn leaf discs, including the following steps: Measure ultrapure water, add potassium 2-(N-morpholine)ethanesulfonate to a final concentration of 10 mmol / L, and adjust the pH to 5.5 using potassium hydroxide solution to obtain the basic buffer solution; Add sucrose to the basal buffer and stir until completely dissolved, so that the final concentration of sucrose in the system is 150 mmol / L; Sequentially transfer the corresponding volumes of abscisic acid mother liquor and sodium metavanadate depolymerization mother liquor into the above solution, so that the final concentration of abscisic acid is 10 μmol / L and the final concentration of sodium metavanadate is 0.1 mmol / L. After bringing the volume to the target volume using ultrapure water, add 0.05% Tween-20 by volume percentage, gently invert and mix to avoid generating bubbles, and prepare the required induction buffer solution. Store at 4°C in the dark for later use.

[0058] Preparation Example 2: This preparation example provides a method for preparing an induction buffer for the treatment of detached sweet corn leaf discs, including the following steps: Measure ultrapure water, add potassium 2-(N-morpholine)ethanesulfonate to a final concentration of 15 mmol / L, and adjust the pH to 5.8 using potassium hydroxide solution to obtain the basic buffer solution; Add sucrose to the basal buffer and stir until completely dissolved, so that the final concentration of sucrose in the system is 165 mmol / L; Sequentially transfer the corresponding volumes of abscisic acid mother liquor and sodium metavanadate depolymerization mother liquor into the above solution, so that the final concentration of abscisic acid is 12.5 μmol / L and the final concentration of sodium metavanadate is 0.3 mmol / L. After bringing the volume to the target volume using ultrapure water, add 0.08% Tween-20 by volume percentage, gently invert and mix to avoid generating bubbles, and prepare the required induction buffer solution. Store at 4°C in the dark for later use.

[0059] Preparation Example 3: This preparation example provides a method for preparing an induction buffer for the treatment of detached sweet corn leaf discs, including the following steps: Measure ultrapure water, add potassium 2-(N-morpholine)ethanesulfonate to a final concentration of 20 mmol / L, and adjust the pH to 6.0 using potassium hydroxide solution to obtain the basic buffer solution; Add sucrose to the basal buffer and stir until completely dissolved, so that the final concentration of sucrose in the system is 180 mmol / L; Sequentially transfer the corresponding volumes of abscisic acid mother liquor and sodium metavanadate depolymerization mother liquor into the above solution, so that the final concentration of abscisic acid is 15 μmol / L and the final concentration of sodium metavanadate is 0.5 mmol / L. After bringing the volume to the target volume using ultrapure water, add 0.10% Tween-20 by volume, gently invert and mix to avoid generating bubbles, and prepare the required induction buffer solution. Store at 4°C in the dark for later use.

[0060] Example 1: See attached document Figure 1 and 2 This embodiment provides a method for breeding sweet corn hybrid combinations based on genetic regulation of sugar metabolism, including the following steps: One hundred samples of sweet corn inbred lines were germinated at a constant temperature of 28℃, and then transferred to a greenhouse for hydroponic cultivation.

[0061] Once the seedlings have grown to the three-leaf stage, the third fully unfolded leaf of each sweet corn inbred line seedling is collected, and a hole punch is used to drill away from the main leaf vein to obtain the detached leaf disc.

[0062] The obtained isolated leaf discs were completely immersed in a culture dish containing the induction buffer solution from Preparation Example 2. The culture dish was placed in a vacuum drying oven, and the system pressure was evacuated to -0.07 MPa and maintained for 8 minutes. Then, the pressure was uniformly released to atmospheric pressure over 45 seconds to complete the vacuum permeation treatment. The isolated leaf discs were removed, and excess liquid on the surface was blotted dry with filter paper.

[0063] The vacuum-permeable disc was placed in a porous reaction plate and then placed in an artificial climate chamber for cooling. The initial ambient temperature of the artificial climate chamber was set at 25°C, and the temperature was linearly reduced at a cooling rate of 2.0°C / h until the ambient temperature dropped to 10°C. The chamber was then kept at a constant temperature for 12 hours under dark conditions.

[0064] Extracted leaf disc samples were taken at the start of the cooling process, 5 hours after the start of the cooling process, and at the end of the constant temperature maintenance.

[0065] Sugar metabolism extracts from isolated leaf disc samples were prepared using boiling ethanol. After concentration, reconstitution with ultrapure water, and filtration through a 0.22 μm microporous membrane, the sucrose and fructose contents of each sample were determined by high performance liquid chromatography.

[0066] Calculate the difference in the ratio of fructose to sucrose content in the detached leaf disc samples between two adjacent time points, divide it by the corresponding time interval, obtain the dynamic change rate of the ratio of fructose to sucrose content in each time period, and take the average value as the final dynamic change rate of the inbred line.

[0067] Following the method described above, the molecular marker genetic distances between each pair of sweet corn inbred lines were obtained, and the average molecular marker genetic distances among all 100 sweet corn inbred lines were calculated.

[0068] One hundred sweet corn inbred lines were planted in a field environment and field surveys were conducted according to conventional cultivation management to obtain field agronomic traits data such as number of rows per ear, number of kernels per row, 100-kernel weight, yield per plant, total sugar content of kernels, and husk and residue rate.

[0069] A multiple linear regression equation is constructed according to the aforementioned method. The direct effect coefficient of the final dynamic change rate on the yield per plant is separated by path analysis. The final dynamic change rate is weighted using the direct effect coefficient to obtain the corrected dynamic change rate. The corrected dynamic change rate is then used to weight other field agronomic traits to generate weighted phenotypic data.

[0070] By substituting the weighted phenotypic data into the aforementioned additive-dominant genetic model, the general combining ability effect and the specific combining ability effect between each sweet corn inbred line were calculated.

[0071] Parental selection was carried out based on combining ability and genetic distance data, and sweet corn inbred lines with negative combining ability effects were eliminated. Among the remaining sweet corn inbred lines, two sweet corn inbred lines with positive specific combining ability and molecular marker genetic distance values ​​greater than 1.2 times the average molecular marker genetic distance were selected as the male and female parents, respectively, and field hybridization was completed using an incomplete diallel hybridization design.

[0072] Example 2: This embodiment provides a method for breeding sweet corn hybrid combinations based on genetic regulation of sugar metabolism, including the following steps: One hundred samples of sweet corn inbred lines were germinated at a constant temperature of 28℃, and then transferred to a greenhouse for hydroponic cultivation.

[0073] Once the seedlings have grown to the three-leaf stage, the third fully unfolded leaf of each sweet corn inbred line seedling is collected, and a hole punch is used to drill away from the main leaf vein to obtain the detached leaf disc.

[0074] The obtained detached leaf discs were completely immersed in a culture dish containing the induction buffer solution from Preparation Example 1. The culture dish was placed in a vacuum drying oven, the system pressure was evacuated to -0.06 MPa, maintained for 5 min, and then the pressure was uniformly released to atmospheric pressure over 30 s to complete the vacuum permeation treatment.

[0075] Remove the detached leaf disc and blot off any excess liquid from the surface with filter paper.

[0076] The detached leaf disc, which has undergone vacuum permeation treatment, is placed in a porous reaction plate and then placed in an artificial climate chamber for cooling.

[0077] The initial ambient temperature of the artificial climate chamber was set at 25℃, and it was linearly cooled at a cooling rate of 1.5℃ / h until the ambient temperature dropped to 12℃. Then, it was kept at a constant temperature for 10 hours under dark conditions.

[0078] Extracted leaf disc samples were taken at the start of the cooling process, 4 hours after the start of the cooling process, and at the end of the constant temperature maintenance.

[0079] Sugar metabolism extracts from isolated leaf disc samples were prepared using boiling ethanol. After concentration, reconstitution with ultrapure water, and filtration through a 0.22 μm microporous membrane, the sucrose and fructose contents of each sample were determined by high performance liquid chromatography.

[0080] Calculate the difference in the ratio of fructose to sucrose content in the detached leaf disc samples between two adjacent time points, divide it by the corresponding time interval, obtain the dynamic change rate of the ratio of fructose to sucrose content in each time period, and take the average value as the final dynamic change rate of the inbred line.

[0081] Following the method described above, the molecular marker genetic distances between each pair of sweet corn inbred lines were obtained, and the average molecular marker genetic distances among all 100 sweet corn inbred lines were calculated.

[0082] One hundred sweet corn inbred lines were planted in a field environment and field surveys were conducted according to conventional cultivation management to obtain field agronomic traits data such as number of rows per ear, number of kernels per row, 100-kernel weight, yield per plant, total sugar content of kernels, and husk and residue rate.

[0083] A multiple linear regression equation is constructed according to the aforementioned method. The direct effect coefficient of the final dynamic change rate on the yield per plant is separated by path analysis. The final dynamic change rate is weighted using the direct effect coefficient to obtain the corrected dynamic change rate. The corrected dynamic change rate is then used to weight other field agronomic traits to generate weighted phenotypic data.

[0084] By substituting the weighted phenotypic data into the aforementioned additive-dominant genetic model, the general combining ability effect and the specific combining ability effect between each sweet corn inbred line were calculated.

[0085] Parental selection was carried out based on combining ability and genetic distance data, and sweet corn inbred lines with negative combining ability effects were eliminated. Among the remaining sweet corn inbred lines, two sweet corn inbred lines with positive specific combining ability and molecular marker genetic distance values ​​greater than 1.2 times the average molecular marker genetic distance were selected as the male and female parents, respectively, and field hybridization was completed using an incomplete diallel hybridization design.

[0086] Example 3: This embodiment provides a method for breeding sweet corn hybrid combinations based on genetic regulation of sugar metabolism, including the following steps: One hundred samples of sweet corn inbred lines were germinated at a constant temperature of 28℃, and then transferred to a greenhouse for hydroponic cultivation.

[0087] Once the seedlings have grown to the three-leaf stage, the third fully unfolded leaf of each sweet corn inbred line seedling is collected, and a hole punch is used to drill away from the main leaf vein to obtain the detached leaf disc.

[0088] The obtained detached leaf discs were completely immersed in a culture dish containing the induction buffer for Preparation Example 3.

[0089] Place the petri dish in a vacuum drying oven, evacuate the system pressure to -0.08 MPa, maintain the pressure for 10 minutes, and then release the pressure to normal pressure at a uniform rate within 60 seconds to complete the vacuum permeation treatment.

[0090] Remove the detached leaf disc and blot off any excess liquid from the surface with filter paper.

[0091] The detached leaf disc, which has undergone vacuum permeation treatment, is placed in a porous reaction plate and then placed in an artificial climate chamber for cooling.

[0092] The initial ambient temperature of the artificial climate chamber was set at 25℃, and it was linearly cooled at a cooling rate of 2.5℃ / h until the ambient temperature dropped to 8℃. Then, it was kept at a constant temperature for 14 hours under dark conditions.

[0093] Extracted leaf disc samples were taken at the start of the cooling process, 6 hours after the start of the cooling process, and at the end of the constant temperature maintenance.

[0094] Sugar metabolism extracts from isolated leaf disc samples were prepared using boiling ethanol. After concentration, reconstitution with ultrapure water, and filtration through a 0.22 μm microporous membrane, the sucrose and fructose contents of each sample were determined by high performance liquid chromatography.

[0095] Calculate the difference in the ratio of fructose to sucrose content in the detached leaf disc samples between two adjacent time points, divide it by the corresponding time interval, obtain the dynamic change rate of the ratio of fructose to sucrose content in each time period, and take the average value as the final dynamic change rate of the inbred line.

[0096] Following the method described above, the molecular marker genetic distances between each pair of sweet corn inbred lines were obtained, and the average molecular marker genetic distances among all 100 sweet corn inbred lines were calculated.

[0097] One hundred sweet corn inbred lines were planted in a field environment and field surveys were conducted according to conventional cultivation management to obtain field agronomic traits data such as number of rows per ear, number of kernels per row, 100-kernel weight, yield per plant, total sugar content of kernels, and husk and residue rate.

[0098] A multiple linear regression equation is constructed according to the aforementioned method. The direct effect coefficient of the final dynamic change rate on the yield per plant is separated by path analysis. The final dynamic change rate is weighted using the direct effect coefficient to obtain the corrected dynamic change rate. The corrected dynamic change rate is then used to weight other field agronomic traits to generate weighted phenotypic data.

[0099] By substituting the weighted phenotypic data into the aforementioned additive-dominant genetic model, the general combining ability effect and the specific combining ability effect between each sweet corn inbred line were calculated.

[0100] Parental selection was carried out based on combining ability and genetic distance data, and sweet corn inbred lines with negative combining ability effects were eliminated. Among the remaining sweet corn inbred lines, two sweet corn inbred lines with positive specific combining ability and molecular marker genetic distance values ​​greater than 1.2 times the average molecular marker genetic distance were selected as the male and female parents, respectively, and field hybridization was completed using an incomplete diallel hybridization design.

[0101] Comparative Example 1: Compared with Example 1, the difference is that: instead of obtaining detached leaf discs, the roots of the entire sweet corn seedling at the three-leaf-one-heart stage were directly immersed in the induction buffer for vacuum permeation and cooling treatment, and the middle section of the third fully unfolded leaf was cut off at the corresponding time point as a sample for measurement. All other aspects are the same.

[0102] Comparative Example 2: The difference from Example 1 is that sodium metavanadate was not added to the induction buffer solution used, but all other aspects are the same.

[0103] Comparative Example 3: Compared with Example 1, the difference is that after immersing the obtained isolated leaf disc in the induction buffer, no vacuum permeation treatment was performed. Instead, it was simply soaked for 8 minutes under normal pressure and temperature conditions. After being taken out, it was directly subjected to cooling treatment. All other aspects were the same.

[0104] Comparative Example 4: Compared with Example 1, the difference is that: no cooling treatment was performed. After the detached leaf disc that had undergone vacuum permeation treatment was placed in an artificial climate chamber, it was kept at a constant temperature of 25°C and protected from light for 19.5 hours. Samples were extracted according to the corresponding time points. Everything else was the same.

[0105] Comparative Example 5: Compared with Example 1, the difference is that: the detached leaf discs, vacuum infiltration treatment, cooling treatment and sugar metabolism biochemical determination of sweet corn seedlings are not performed. After obtaining agronomic trait data in the field survey, path analysis and data weighting are not performed. The original single-plant yield measurement value is directly substituted into the additive-dominant genetic model to calculate the combining ability effect and to carry out parental selection. All other aspects are the same.

[0106] Test Example 1: Leaf tissue samples were taken from Examples 1, 2, and 3, as well as Comparative Examples 1 and 3, at the start of the cooling treatment. To ensure data reliability, three biological replicates were independently set up for each treatment group.

[0107] The collected leaf tissue samples were immediately placed in ultrapure water and rinsed three times consecutively, with each rinse lasting 30 seconds. After rinsing, the surface moisture of the tissue was blotted dry with filter paper to remove any residual induction buffer adhering to the leaf epidermis and cut surfaces.

[0108] Accurately weigh 0.1 g of the treated leaf tissue sample into a centrifuge tube, add 1 mL of boiling ethanol, and extract in an 80℃ constant temperature water bath for 20 min. After extraction, cool to room temperature, centrifuge at 12000 r / min for 10 min, and collect the supernatant.

[0109] The collected supernatant was transferred to a vacuum centrifuge and concentrated to dryness, then reconstituted with 0.5 mL of ultrapure water. The reconstituted solution was filtered through a 0.22 μm microporous membrane and injected into a high-performance liquid chromatograph to determine the absolute sucrose content. The measured data for each replicate group were recorded, and the average value was calculated.

[0110] Table 1. Initial sucrose permeation in sweet maize leaf tissues under different treatments (mg / gFW)

[0111] in conclusion: According to Table 1 and Appendix Figure 3 According to the data, the initial sucrose permeation in the leaf tissues of Examples 1 to 3 was higher than that of Comparative Examples 1 and 3. Comparing Example 1 and Comparative Example 1, Comparative Example 1 used a whole-plant rhizosphere administration method, and its sucrose content in the leaf tissues was at a lower level.

[0112] The long-distance transport of plant vascular bundles is subject to natural physical barriers, and the Casparian strip of the root endodermis has a filtering and hindering effect on macromolecular solutes, which prevents high-tonicity substrates from reaching the target leaf tissue in a short time, resulting in obvious mass transfer obstruction.

[0113] Compared to Example 1, Comparative Example 3, which involved immersing detached leaf discs under normal pressure, had an initial sucrose permeation rate of only about 12.8% of that in Example 1. Under normal pressure, the hydrophobic cuticle tension on the plant leaf surface and the air trapped in the intercellular spaces of the mesophyll cells hindered the entry of external buffer solution into the tissue. Examples 1-3 used a negative pressure vacuum permeation process to treat detached leaf discs. Under a set negative pressure condition, the gas inside the intercellular spaces was evacuated. The pressure difference generated during the subsequent depressurization process forced the induction buffer solution containing a high concentration of sucrose to instantly overcome surface tension and rush into the mesophyll tissue.

[0114] This physical infiltration process enables instantaneous high-flux introduction of substrates, providing a sufficient substrate basis for the operation of sugar metabolism pathways in the subsequent cooling treatment stage, and ensuring that leaf tissues can form independent and high-concentration substrate metabolic pools under the condition of cutting off the supply from the parent vascular bundle.

[0115] Test Example 2: Basic measurement data of 100 sweet corn inbred lines involved in Example 1, Comparative Example 2, Comparative Example 4, and Comparative Example 5 under an incomplete diallel cross design were obtained. Weighted phenotypic data obtained by path analysis were extracted from Example 1, Comparative Example 2, and Comparative Example 4, and raw field yield data per plant were extracted from Comparative Example 5.

[0116] The data from each group were substituted into an additive-dominant genetic model designed based on incomplete diallel crosses.

[0117] An analysis of variance was performed on the model to calculate and extract the additive variance, dominant variance, and environmental variance values ​​for each group of population data.

[0118] Based on the extracted variance component values, calculate the total phenotypic variance (the sum of additive variance, dominant variance, and environmental variance). Divide the additive variance by the total phenotypic variance to obtain the narrow-sense heritability parameter (%). Divide the sum of additive variance and dominant variance by the total phenotypic variance to obtain the generalized heritability parameter (%), and summarize all the calculation results.

[0119] Table 2. Variance components and heritability calculation results under different measurement and analysis modes

[0120] in conclusion: According to Table 2 and Appendix Figure 4 Based on the data, Example 1 showed a narrow-sense heritability of 65.32% and a broad-sense heritability of 92.43%. Comparative Example 5, using the direct field assay, showed a narrow-sense heritability of only 29.36%. Generally, combining ability is determined by additive gene effects and is controlled by narrow-sense heritability.

[0121] Comparative Example 5 uses field-measured yield as the sole evaluation indicator. However, field plants are affected by external factors such as micro-plot soil fertility, light shading, and water distribution, resulting in environmental variance accounting for an excessively large proportion of the overall variance. This environmental noise masks the true phenotypic variation controlled by additive genes, leading to a low calculated narrow-sense heritability. Therefore, the general combining ability calculated based on this data lacks reference value.

[0122] Example 1 establishes a path analysis model to extract the dynamic change rate of sugar metabolism under in vitro conditions as a direct action coefficient, and then performs mathematical weighting on the measured values ​​of field agronomic traits.

[0123] This method uses biochemical indicators to correct field phenotypic data, eliminating heterogeneous environmental errors in the field, reducing the interference of environmental variance, and restoring the expression of additive variance to the true level. This provides solid data support for the subsequent accurate removal of inferior parents with negative combining ability.

[0124] Compared with Comparative Example 2, Comparative Example 2 lacked sodium metavanadate in its induction buffer, resulting in a decrease in narrow-sense and broad-sense heritability to 47.44% and 71.59%, respectively. Plant mesophyll cells exhibit a physiological response of sugar efflux under adverse temperatures; without the addition of sodium metavanadate, the plasma membrane H on the cell membrane surface... +-ATPase remains active, driving the transmembrane electrochemical gradient of protons, causing intracellular sucrose and fructose to leak into the apoplast interstitial space.

[0125] This transmembrane loss causes fluctuations in the concentration of endogenous sugars during extraction, introducing measurement errors. Example 1: The addition of sodium metavanadate suppressed plasma membrane H... + - The phosphorylation site of ATPase interrupts the substrate outflow pathway, forming a closed-loop metabolic space within the mesophyll tissue. The dynamic transformation of intracellular sugar content is freed from transmembrane transport interference and is controlled by the genetic expression activity of endogenous converting enzymes, thus blocking the interference of random physiological errors in the measurement of heritability parameters.

[0126] Compared with Example 1, Comparative Example 4 was not subjected to cooling treatment and was maintained at room temperature throughout, with a narrow-sense heritability of 36.92%. At room temperature, the sugar metabolism of detached sweet corn leaf tissue was in a basal maintenance state, and the internal regulatory genes related to stress resistance and carbohydrate allocation were not induced to express.

[0127] The sugar conversion rates of the different inbred lines at room temperature showed no significant difference, which limited the expression of additive variance and increased the relative weight of environmental variance. Example 1 used programmed cooling treatment, using temperature gradient as a physical inducing factor, to stimulate different responses in the sugar metabolism pathway in different inbred lines, transforming hidden genetic diversity into quantifiable biochemical phenotypic differences, thus ensuring the sensitivity and effectiveness of heritability parameter measurement.

[0128] Test Example 3: The F1 generation hybrids obtained by finally selecting and combining the hybrids from Example 1 and Comparative Example 5 were used. Among them, Example 1 represents the hybrid combination obtained through environmental noise stripping and combining ability screening, while Comparative Example 5 represents the hybrid combination obtained by direct screening based solely on field phenotypic measured values.

[0129] The two groups of F1 hybrids were randomly planted in the same standard field environment, with four replicate blocks, each with a planting area of ​​20m². 2 The field water, fertilizer, and pest and disease management are carried out in a unified manner according to the conventional cultivation and management model.

[0130] During the milk stage of maize, the middle two rows of plants in each block were harvested for yield measurement. The total yield of each plot was calculated and converted into yield per hectare.

[0131] Fifteen standard ears of grain were randomly selected from each block, and kernel samples were collected. After drying and pulverizing, the total sugar content of the kernels was determined using the anthrone colorimetric method. Test data were recorded and the mean was calculated.

[0132] Table 3. Field yield and quality test results of F1 generation hybrid combinations under different breeding methods

[0133] Note: "-" indicates blank data.

[0134] in conclusion: According to Table 3 and Appendix Figure 5 According to the data, the F1 hybrid combination bred in Example 1 showed higher yield per unit area and higher total sugar content in grains than the F1 hybrid combination in Comparative Example 5. Combined with the calculation results of Test Example 2, the basal phenotypic data of Comparative Example 5 showed lower narrow-sense heritability due to the lack of environmental noise filtering. Narrow-sense heritability is a direct indicator of additive effects, which determine the true level of general combining ability.

[0135] Comparative Example 5 calculated combining ability based on low narrow-sense heritability, resulting in serious distortion of the prediction. The so-called superior parents selected were actually phenotypic illusions superimposed with microenvironmental advantages, and could not stably pass on the superior traits to the F1 generation.

[0136] Example 1 used a genetic regulation assessment system for sugar metabolism to correct field phenotypic data, obtaining a data base with high narrow-sense heritability, thus ensuring the accuracy of general combining ability calculations.

[0137] Supported by genetic data, Example 1 accurately identified and eliminated inferior inbred lines lacking substantial additive effects during the initial parental screening stage, while retaining the true parents with excellent genetic background. Combined with subsequent high-standard special combining ability and genetic distance screening, the final F1 generation achieved the transformation of additive effects and heterosis in real field production, verifying the technical effectiveness of this scheme in solving the problem of phenotypic selection distortion.

Claims

1. A method for breeding sweet corn hybrid combinations based on genetic regulation of sugar metabolism, characterized in that, Includes the following steps: To obtain detached leaf discs from sweet corn inbred line seedlings; The isolated leaf disc was immersed in an induction buffer solution for vacuum permeation treatment. The induction buffer solution contained exogenous sugar substrate, abscisic acid, and plasma membrane H2O. + -ATPase inhibitors and surfactants; The detached leaf disk that has undergone vacuum permeation treatment is placed in a low-temperature environment for cooling treatment; Extract detached leaf disc samples at at least two different time points, measure the sucrose and fructose content in the samples, and calculate the dynamic rate of change of the ratio of fructose content to sucrose content over time. Obtain the molecular marker genetic distances between each pair of sweet corn inbred lines, and calculate the average molecular marker genetic distances among all lines; Obtain field agronomic trait data for each sweet corn inbred line; The field agronomic trait data of the sweet corn inbred lines were weighted using the dynamic change rate to obtain weighted phenotypic data. The weighted phenotypic data were then substituted into the additive-dominant genetic model to calculate the general combining ability effect and the specific combining ability effect of each sweet corn inbred line. Two sweet corn inbred lines were selected as the male and female parents, respectively, with positive values ​​for both general and specific combining ability effects and a molecular marker genetic distance greater than the average molecular marker genetic distance.

2. The method for breeding sweet corn hybrid combinations based on genetic regulation of sugar metabolism according to claim 1, characterized in that, The specific steps for obtaining the detached leaf discs of sweet corn inbred line seedlings are as follows: After germinating the seeds of the sweet corn inbred line to be tested, they were hydroponically cultured until the seedlings grew to the three-leaf-one-heart stage. The third fully unfolded leaf was collected, and the detached leaf disc was obtained by drilling, avoiding the main leaf vein.

3. The method for breeding sweet corn hybrid combinations based on genetic regulation of sugar metabolism according to claim 1, characterized in that, The exogenous sugar substrate is sucrose, and the concentration of the exogenous sugar substrate in the induction buffer is 150–180 mmol / L; The concentration of the abscisic acid is 10–15 μmol / L; The plasma membrane H + -ATPase inhibitor is sodium metavanadate, the plasma membrane H + - The concentration of ATPase inhibitors is 0.1–0.5 mmol / L; The surfactant is Tween-20, and the volume percentage concentration of the surfactant is 0.05% to 0.10%.

4. The method for breeding sweet corn hybrid combinations based on genetic regulation of sugar metabolism according to claim 3, characterized in that, The base solvent of the induction buffer is a potassium 2-(N-morpholine)ethanesulfonate buffer solution with a concentration of 10-20 mmol / L, and the pH value of the induction buffer solution is 5.5-6.

0.

5. The method for breeding sweet corn hybrid combinations based on genetic regulation of sugar metabolism according to claim 1, characterized in that, The specific operating parameters for the vacuum permeation treatment are as follows: Pump the system pressure down to -0.06 to -0.08 MPa and hold the pressure for 5 to 10 minutes. Then, the pressure was released at a constant rate to normal pressure within 30 to 60 seconds.

6. The method for breeding sweet corn hybrid combinations based on genetic regulation of sugar metabolism according to claim 1, characterized in that, The specific operating parameters for the cooling process are as follows: the initial ambient temperature is 25℃, and the temperature is linearly reduced to 8-12℃ at a cooling rate of 1.5-2.5℃ / h, and then kept constant at this temperature for 10-14 hours under conditions of darkness.

7. The method for breeding sweet corn hybrid combinations based on genetic regulation of sugar metabolism according to claim 6, characterized in that, The different time points include: The start time of the cooling treatment, the 4th to 6th hour after the start of the cooling treatment, and the end time of the constant temperature maintenance; The specific calculation method for the dynamic rate of change is as follows: The dynamic change rate is obtained by calculating the difference in the ratio of fructose content to sucrose content in the detached leaf disc sample between two adjacent time points and dividing it by the corresponding time interval.

8. The method for breeding sweet corn hybrid combinations based on genetic regulation of sugar metabolism according to claim 1, characterized in that, The steps for determining the sucrose and fructose content in the sample include: The sugar metabolism extract of the isolated leaf disc sample was prepared by boiling ethanol, and the extract was determined by high performance liquid chromatography after concentration.

9. The method for breeding sweet corn hybrid combinations based on genetic regulation of sugar metabolism according to claim 1, characterized in that, The field agronomic trait data shall include at least the measurement indicators reflecting yield and quality, specifically: Number of rows per ear, number of grains per row, 100-grain weight, yield per plant, total sugar content of grains, and husk and residue rate.

10. The method for breeding sweet corn hybrid combinations based on genetic regulation of sugar metabolism according to claim 9, characterized in that, The step of weighting the field agronomic trait data of sweet maize inbred lines using the dynamic change rate includes: A multiple linear regression equation was constructed with yield per plant as the dependent variable and the dynamic change rate and other field agronomic traits as independent variables. Path analysis was used to separate the direct effect coefficient of the dynamic change rate on yield per plant. The original measured values ​​of the dynamic change rate were weighted using the direct effect coefficient to obtain the corrected dynamic change rate. The corrected dynamic change rate was then used to weight other field agronomic trait data to generate the weighted phenotypic data. In the step of selecting the male and female parents for hybridization, the molecular marker genetic distance between the two selected sweet corn inbred lines is greater than 1.2 times the average molecular marker genetic distance, and the hybridization is completed using an incomplete diallel cross design.

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