Saline-alkali stress response-based saline-alkali tolerant corn germplasm resource screening method

Abstract

The invention relates to the technical field of crop planting, and particularly discloses a saline-alkaline tolerance corn germplasm resource screening method based on saline-alkaline stress response, which comprises the following steps: step 1, performing classification preparation on selected corn germplasm resources according to early-stage field performance and yield measurement results of the germplasm resources; 2, on the basis of the selected saline-alkaline resistance identification concentration, the corn germplasm resources are cultivated and observed in the germination stage and the seedling stage; 3, recording experimental data of cultivation in the germination stage and the seedling stage at a set time point, and carrying out growth index measurement and index calculation; according to the method, the saline-alkaline mixed solutions with different concentrations are adopted to simulate stress culture situations in different saline-alkaline environments, the selected corn germplasm resources are screened, and the saline-alkaline tolerance of the corn germplasm resources is comprehensively evaluated by selecting multiple indexes including growth, morphology and physicochemistry. And the deep neural network is introduced to analyze the seedling image, so that a more accurate and more comprehensive analysis result can be provided.

Description

Technical Field

[0001] The invention belongs to the technical field of crop planting, and particularly relates to a method for screening salt-alkali tolerant corn germplasm resources based on salt-alkali stress response. Background Art

[0002] The presence of saline-alkali soil is a common soil problem in crop cultivation. Salt-alkali stress can restrict the growth and development of crops, leading to reduced yields and even crop death. Therefore, the identification and screening of crop salt-alkali tolerance has become crucial. Traditional methods for identifying crop salt-alkali tolerance are usually based on the observation of physiological and morphological characteristics, but these methods often require a lot of time and labor, and have problems of subjectivity and instability.

[0003] In recent years, with the development and utilization of saline-alkali soil, improving the salt tolerance of crops and breeding salt-tolerant varieties are one of the most economical and effective ways to increase crop yields in saline-alkali areas, and are also important means of biological improvement of saline-alkali land. The germination and seedling stages are the most critical periods for determining whether plants can grow in saline-alkali environments, and are also the starting point of the entire growth cycle of crops. Their response to saline-alkali stress determines the morphological construction and later growth and development of plants. A lot of research has been done at home and abroad on corn salt-alkali tolerant germplasm resources and identification of salt-alkali tolerance in the seedling stage, and mainly on neutral salt stress such as NaCl. However, there are few reports on alkaline stress mainly based on Na2CO3 in soda saline-alkali soil and the use of multiple identification indicators for salt-alkali tolerance in the early growth stage of corn. How to analyze the salt damage of different saline-alkali stresses on corn germplasm during the germination period and screen out corn germplasm with salt-alkali tolerance during the germination and seedling stages is of great significance for salt-alkali tolerant corn breeding.

[0004] Therefore, it is necessary to propose a method for screening salt-alkali tolerant corn germplasm resources based on salt-alkali stress response to solve the problem that the existing technology has a relatively single salt-alkali type and cannot comprehensively analyze the differential effects of different types of saline-alkali soils on the germination and growth of corn germplasm.

[0005] The above information disclosed in this background technology is only used to increase the understanding of the background technology of the present invention and therefore, it may include information that does not constitute the prior art known to a person of ordinary skill in the art. Summary of the invention

[0006] The object of the present invention is to provide a method for screening salt-alkali tolerant corn germplasm resources based on salt-alkali stress response, so as to solve the problems raised in the above background technology.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] The method for screening salt-alkali tolerant corn germplasm resources based on salt-alkali stress response includes:

[0009] Step 1: Classify and prepare the selected corn germplasm resources according to their previous field performance and yield measurement results;

[0010] Step 2: Based on the selected salt-alkaline tolerance identification concentration, the above-mentioned corn germplasm resources are cultivated and observed at the germination stage and the seedling stage;

[0011] Step 3: recording the experimental data of the germination and seedling cultivation at the set time points, and performing growth index determination and index calculation;

[0012] Step 4: Use a deep convolutional neural network to analyze the experimental data and introduce a fine-tuning architecture to identify growth changes under saline-alkali stress;

[0013] Step 5. Based on data analysis, select corn germplasm resources with good salt-alkali tolerance and excellent performance, and conduct repeated experiments to verify the selected salt-alkali tolerant resources.

[0014] Preferably, corn seeds of uniform size and full grains are selected, the selected corn seeds are grouped according to excellent field and yield performance, and the corn seeds are pretreated, such as disinfected, dried, etc.

[0015] Preferably, before the cultivation, representative corn seeds are selected for concentration screening preliminary experiments, and the concentrations at which the differences in various indicators among the corn seeds are relatively obvious are analyzed and calculated, and used as the appropriate stress concentration for evaluating the screening and identification of salt-alkali tolerance in the seedling stage; the above-mentioned appropriate stress concentration is used as a reference condition for the change in salt concentration, and the salt concentration division level of salt-alkali tolerance is determined, and the same salt concentration division level of salt-alkali tolerance is used for cultivation during the germination period.

[0016] Preferably, the mixed saline-alkali solution of NaCl and Na2CO3 of different concentrations is configured to simulate different saline-alkali stress conditions;

[0017] Cultivation during the germination period: The pretreated corn seeds were placed in a culture dish covered with a double-layer filter paper for germination test; 10 ml of mixed saline-alkali solution of different concentrations was added to each dish, with an equal volume of distilled water solution as the control, and each group was repeated 3 times; the corn seeds were placed in an incubator with a constant temperature of 25°C during the day and night, a light intensity of 6400LX, and a humidity of 60% (12h light, 12h dark); no saline-alkali solution was added during the test, and the Parafilm film was used to seal the dish, and it was not opened in the middle to prevent water dispersion loss.

[0018] Seedling cultivation: prepare a culture box (d×h=10cm×12cm) and fill it with nutrient soil of equal mass; place the culture box in a tray filled with clean water to allow the nutrient soil to absorb enough water; soak corn seeds in pure water at 25°C for 2h and then sow them in the culture box; sow 10 seeds in each culture box and place it in a constant temperature incubator at 28°C; after germination, move it into an artificial climate room with a day and night temperature of 28°C / 20°C and a light exposure time of 12h·d -1 , light intensity is 650 μmmol·m -2 ·s -1 ; Replenish water in time during the seedling raising period, and add 50 ml of 0.5 times MS nutrient solution after 7 days; When the corn seedlings grow to two leaves and one heart, they are transplanted, and 5 seedlings with consistent growth are retained in each box; Add equal amounts of mixed saline-alkali solutions of different concentrations to each box, and use equal volumes of distilled water solution as the control, and repeat each group 3 times.

[0019] Preferably, the observation and recording time intervals of the germination period and the seedling period are determined respectively, the growth conditions and physiological index data of corn are recorded, and after the experiment, the biomass of the root part and the seedling part of the corn plant are measured; Excel software is used for data statistics and collation, and SPSS software is used for multiple variance tests, correlation analysis, principal component analysis and cluster analysis based on the statistical data.

[0020] Preferably, the fine-tuning and tuning architecture integrates adapter tuning and side tuning, and trains a suitable edge network to be used together with ResNet, where ResNet contains n residual layers (L1, L2, ..., L n ), the edge network consists of n edge layers (S1, S2, ..., S n ), the forward propagation of ResNet is completely determined by itself. The edge network initially obtains the output L0 from ResNet and generates S1 corresponding to L1, and a gating mechanism is used to fuse the outputs of ResNet and edge network.

[0021] In addition, except for the first layer of the edge network, all subsequent layers are based on the output G of the previous gating module. i As input. The connection between ResNet and the edge network can be regarded as a form of gating selection. The gating mechanism formula used here is as follows:

[0022] G i =F i (L i ,S i )=max(L i ,L i ×S i )

[0023] Among them, for any 1≤i≤n, Fi represents the i-th gating module, L i and S i Represents the output of the corresponding residual layer and edge layer of the i-th layer. max() means comparing the pixel-level values ​​of the two tensors and constructing a new tensor with the maximum value.

[0024] Preferably, according to the analysis results obtained by using SPSS software, a comprehensive evaluation of salt-alkali tolerance is performed at the germination stage and the seedling stage, which is compared with the identified growth changes under salt-alkali stress, and finally corn germplasm resources with good salt-alkali tolerance and excellent performance are screened out.

[0025] Preferably, when conducting repeated experiments, in addition to recording experimental data at set time points, multiple sampling is performed at other different time points to observe the dynamic effects of salt-alkali stress on corn growth; and a recovery period is set after the stress is relieved to observe the recovery ability of corn after the stress is relieved, so as to further evaluate and screen the recovery of corn germplasm resources.

[0026] Preferably, the method further detects the gene expression levels of the selected corn germplasm resources related to salt-alkali tolerance through RT-PCR or gene chip technology to further confirm the molecular mechanism that is different from other selected corn germplasm resources.

[0027] Preferably, the method also displays key data and intermediate results in the screening process by means of data visualization, and outputs a detailed report of the entire screening process.

[0028] Compared with the prior art, the present invention has the following beneficial effects:

[0029] The present invention uses salt-alkali mixed solutions of different concentrations to simulate stress culture scenarios under different saline-alkali environments, screens the selected corn germplasm resources, selects multiple indicators including growth, morphology, and physicochemical properties to comprehensively evaluate the salt-alkali tolerance of corn germplasm resources, and introduces a deep neural network to analyze seedling images, which can provide more accurate and comprehensive analysis results and provide basic data support for the cultivation of salt-alkali tolerant corn germplasm resources.

[0030] The above summary is for illustrative purposes only and is not intended to be limiting in any way. In addition to the illustrative aspects, embodiments and features described above, further aspects, embodiments and features of the present invention will be readily apparent by reference to the accompanying drawings and the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 The present invention is a flow chart of the method for screening salt-alkali tolerant corn germplasm resources based on salt-alkali stress response. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0033] Embodiment 1:

[0034] See also Figure 1 As shown, the method for screening salt-alkali tolerant corn germplasm resources based on salt-alkali stress response includes:

[0035] Step 1: Classify and prepare the selected corn germplasm resources according to their previous field performance and yield measurement results;

[0036] Select uniform corn seeds with full grains, group them according to their excellent field and yield performance, and pre-treat the corn seeds, such as disinfection and drying.

[0037] Soak corn seeds in 1% sodium hypochlorite solution, then place them on a shaker at 180 rpm for 15 minutes, rinse them with running water for 3-5 minutes to disinfect the seeds. Soak the disinfected seeds in distilled water for 3-4 hours, and place the seeds on gauze to absorb moisture from the surface of the seeds before inoculation.

[0038] Step 2: Based on the selected salt-alkaline tolerance identification concentration, the above-mentioned corn germplasm resources are cultivated and observed at the germination stage and the seedling stage;

[0039] Before cultivation, representative corn seeds were selected for concentration screening pre-experiments, and the concentrations with relatively obvious differences in various indicators among corn seeds were analyzed and calculated, which were used as the appropriate stress concentration for screening and identification of salt-alkali tolerance in the seedling stage;

[0040] Example 1: Select representative corn seeds for preliminary screening of salt-alkali tolerance concentration. Take seedlings with consistent growth and transplant them to the planting bed. Apply 0 (CK), 50, 100, 150, 200mmol / L NaCl and Na2CO3 mixed solution for salt-alkali stress treatment. Strictly control the nutrients in the nutrient solution (Hoagland) and the content of NaCl and Na2CO3 to make the plants grow evenly. After 5 and 10 days, by measuring the plant height, root length, seedling fresh weight, root fresh weight, seedling dry weight and root dry weight, it is assumed that the differences in various indicators between the selected representative corn seeds under the salt-alkali stress of 150mmol / L NaCl and Na2CO3 mixed solution are relatively obvious, which can effectively reflect the differences of each corn seed in the seedling stage. The 150mmol / L NaCl and Na2CO3 mixed solution is used as the appropriate stress concentration for evaluating the screening and identification of salt-alkali tolerance in the seedling stage.

[0041] The above-mentioned suitable stress concentration is used as a reference condition for salt concentration changes to determine the salt concentration division level of salt-alkali resistance, and the same salt concentration division level of salt-alkali resistance is used in germination period cultivation.

[0042] Mixed saline-alkali solutions of NaCl and Na2CO3 with different concentrations were prepared to simulate different saline-alkali stress conditions;

[0043] Cultivation during the germination period: The pretreated corn seeds were placed in a culture dish covered with a double-layer filter paper for germination test; 10 ml of mixed saline-alkali solution of different concentrations was added to each dish, with an equal volume of distilled water solution as the control, and each group was repeated 3 times; the corn seeds were placed in an incubator with a constant temperature of 25°C during the day and night, a light intensity of 6400LX, and a humidity of 60% (12h light, 12h dark); no saline-alkali solution was added during the test, and the Parafilm film was used to seal the dish, and it was not opened in the middle to prevent water dispersion loss.

[0044] Seedling cultivation: prepare a culture box (d×h=10cm×12cm) and fill it with nutrient soil of equal mass; place the culture box in a tray filled with clean water to allow the nutrient soil to absorb enough water; soak corn seeds in pure water at 25°C for 2h and then sow them in the culture box; sow 10 seeds in each culture box and place it in a constant temperature incubator at 28°C; after germination, move it into an artificial climate room with a day and night temperature of 28°C / 20°C and a light exposure time of 12h·d -1 , light intensity is 650 μmmol·m -2 ·s -1 ; Replenish water in time during the seedling raising period, and add 50 ml of 0.5 times MS nutrient solution after 7 days; When the corn seedlings grow to two leaves and one heart, they are transplanted, and 5 seedlings with consistent growth are retained in each box; Add equal amounts of mixed saline-alkali solutions of different concentrations to each box, and use equal volumes of distilled water solution as the control, and repeat each group 3 times.

[0045] Step 3: recording the experimental data of the germination and seedling cultivation at the set time points, and performing growth index determination and index calculation;

[0046] Determine the observation and recording time intervals during the germination and seedling stages, record the growth and physiological index data of corn, and measure the biomass of the root and seedling parts of the corn plants after the experiment;

[0047] When salt-alkali stress was applied during the germination period, the presence of radicle and the length of the sprout equal to 1 / 2 of the seed length were used as the germination standard for seeds, and the germination potential, germination rate and germination index of seeds were determined.

[0048] Germination potential (Ge) = number of germinated seeds on the 3rd day / number of test seeds × 100

[0049] Germination rate (Gp) = number of germinated seeds on the 7th day / number of test seeds × 100

[0050] Germination index (Gi) = ∑(Gt / Dt), where Gt is the number of germinated seeds on day t and Dt is the corresponding number of germination days.

[0051] Salt damage index = [control germination rate (CK) - treatment germination rate] / control germination rate (CK) × 100%

[0052] After 10 days of salt-alkali stress treatment at the seedling stage, carefully and completely remove the plants, first rinse the roots with clean water, then quickly rinse the roots with distilled water, and then gently dry the surface water of the seedlings with absorbent paper. Measure the root length and seedling length with a ruler, measure the stem diameter with a caliper, and weigh the seedling fresh weight and root fresh weight with an electronic balance, then put them into numbered glass dishes, put them in a drying oven to dry to constant weight, and weigh the seedling dry weight and root dry weight respectively.

[0053] Physiological index determination: Leaves from the same part of the seedlings were taken, weighed, and placed in a sterilized hard plastic tube. After being placed in a liquid nitrogen tank, they were transported back to the laboratory and placed in a -78°C ultra-low temperature refrigerator for the determination of physiological indicators. Malondialdehyde content was determined by thiobarbituric acid method; free proline content was determined by sulfosalicylic acid method; superoxide dismutase activity was determined by tetrazolium blue (NBT) method; soluble protein was determined by Coomassie brilliant blue G-250 method.

[0054] Excel software was used for data statistics and collation, and SPSS software was used for multiple variance tests, correlation analysis, principal component analysis and cluster analysis based on the statistical data.

[0055] Step 4: Use a deep convolutional neural network to analyze the experimental data and introduce a fine-tuning architecture to identify growth changes under saline-alkali stress;

[0056] Fine-tuning the architecture integrates adapter tuning and side tuning, training a suitable edge network to be used with ResNet, where ResNet contains n residual layers (L1, L2, ..., L n ), the edge network consists of n edge layers (S1, S2, ..., S n ), the forward propagation of ResNet is completely determined by itself. The edge network initially obtains the output L0 from ResNet and generates S1 corresponding to L1, and a gating mechanism is used to fuse the outputs of ResNet and edge network.

[0057] Step 5. Based on data analysis, select corn germplasm resources with good salt-alkali tolerance and excellent performance, and conduct repeated experiments to verify the selected salt-alkali tolerant resources.

[0058] According to the analysis results obtained by using SPSS software, a comprehensive evaluation of salt-alkali tolerance was conducted at the germination stage and seedling stage, which was compared with the identified growth changes under salt-alkali stress, and finally corn germplasm resources with good salt-alkali tolerance and excellent performance were screened out.

[0059] Embodiment 2:

[0060] See also Figure 1 As shown, this embodiment is basically the same as the above embodiment, except that, when conducting repeated experiments, in addition to recording experimental data at set time points, multiple sampling is performed at other different time points to observe the dynamic effects of salt-alkali stress on corn growth; and a recovery period is set after the stress is relieved to observe the recovery ability of corn after the stress is relieved, so as to further evaluate and screen the recovery of corn germplasm resources.

[0061] This method also uses RT-PCR or gene chip technology to detect the gene expression levels related to salt-alkali tolerance of the screened corn germplasm resources, further confirming the molecular mechanism that is different from other selected corn germplasm resources; display the key data and intermediate results of the screening process through data visualization, and output a detailed report of the entire screening process.

[0062] From the above, it can be seen that the present invention uses salt-alkali mixed solutions of different concentrations to simulate stress culture scenarios under different saline-alkali environments, screens the selected corn germplasm resources, selects multiple indicators including growth, morphology and physical and chemical aspects to comprehensively evaluate the salt-alkali tolerance of corn germplasm resources, and introduces deep neural networks to analyze seedling images, which can provide more accurate and comprehensive analysis results and provide basic data support for the cultivation of salt-alkali tolerant corn germplasm resources.

[0063] Embodiment 3:

[0064] The embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, each process of the above-mentioned screening method embodiment is implemented, and the same technical effect can be achieved. To avoid repetition, it is not repeated here. Among them, the computer-readable storage medium, such as a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0065] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples" or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine different embodiments or examples described in this specification and the features of different embodiments or examples, unless they are contradictory.

[0066] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to generate a program, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A way to specify functions in one or more boxes.

[0067] In the drawings of the embodiments disclosed in the present invention, only the structures involved in the embodiments disclosed in the present invention are involved, and other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of the present invention can be combined with each other.

[0068] The flowcharts shown in the accompanying drawings are only examples and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may also be decomposed, combined or partially merged, so the actual execution order may change according to actual conditions.

[0069] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for screening salt-alkali tolerant corn germplasm resources based on salt-alkali stress response, characterized in that: The following steps are involved: Step 1: Classify and prepare the selected corn germplasm resources according to their previous field performance and yield measurement results; Step 2: Based on the selected salt-alkaline tolerance identification concentration, the above-mentioned corn germplasm resources are cultivated and observed at the germination stage and the seedling stage; Step 3: recording the experimental data of the germination and seedling cultivation at the set time points, and performing growth index determination and index calculation; Step 4: Use a deep convolutional neural network to analyze the experimental data and introduce a fine-tuning architecture to identify growth changes under saline-alkali stress; Step 5. Based on data analysis, select corn germplasm resources with good salt-alkali tolerance and excellent performance, and conduct repeated experiments to verify the selected salt-alkali tolerant resources.

2. The method for screening salt-alkali tolerant corn germplasm resources based on salt-alkali stress response according to claim 1, characterized in that: The selected corn germplasm resources are prepared according to their previous field performance and yield measurement results, including: Uniform corn seeds with full grains were selected, grouped according to their excellent field and yield performance, and pre-treated.

3. The method for screening salt-alkali tolerant corn germplasm resources based on salt-alkali stress response according to claim 2, characterized in that: The cultivation observation of the above-mentioned corn germplasm resources at the germination stage and the seedling stage based on the selected salt-alkali tolerance identification concentration includes: Before cultivation, representative corn seeds were selected for concentration screening pre-experiments, and the concentrations with relatively obvious differences in various indicators among corn seeds were analyzed and calculated, which were used as the appropriate stress concentration for screening and identification of salt-alkali tolerance in the seedling stage; The above-mentioned suitable stress concentration is used as a reference condition for salt concentration changes to determine the salt concentration classification level of salt-alkali resistance, and the same salt concentration classification level of salt-alkali resistance is used in germination period cultivation.

4. The method for screening salt-alkali tolerant corn germplasm resources based on salt-alkali stress response according to claim 3, characterized in that: The method of carrying out cultivation observation of the above-mentioned corn germplasm resources at the germination stage and the seedling stage based on the selected salt-alkali tolerance identification concentration also includes: Mixed saline-alkali solutions of NaCl and Na2CO3 with different concentrations were prepared to simulate different saline-alkali stress conditions; Germination stage cultivation: The pretreated corn seeds were placed in a petri dish covered with double-layer filter paper for germination test; 10 ml of mixed saline-alkali solution of different concentrations was added to each dish, with an equal volume of distilled water solution as control, and each group was repeated 3 times; The corn seeds were placed in an incubator with a constant temperature of 25°C day and night, a light intensity of 6400LX, and a humidity of 60%; During the test, no saline-alkali solution was added, and the container was sealed with Parafilm film and not opened in the middle to prevent water dispersion loss; Seedling cultivation: prepare a culture box (d×h=10cm×12cm) and fill it with nutrient soil of equal quality; Place the culture box in a tray filled with clean water to allow the nutrient soil to absorb enough water; Soak corn seeds in pure water at 25°C for 2 h and then sow them in a culture box; Ten seeds were sown in each culture box and placed in a constant temperature incubator at 28°C; After germination, the seedlings were moved into an artificial climate chamber with a day and night temperature of 28°C / 20°C and a light duration of 12h·d. -1 , light intensity is 650 μmmol·m -2 ·s -1 ; During the seedling raising period, water should be added in time, and 50 ml of 0.5 times MS nutrient solution should be added after 7 days; When the corn seedlings grow to two leaves and one heart, transplant them and keep 5 seedlings with the same growth in each box; An equal amount of mixed saline-alkali solution of different concentrations was added to each box, with an equal volume of distilled water solution as control, and each group was repeated 3 times.

5. The method for screening salt-alkali tolerant corn germplasm resources based on salt-alkali stress response according to claim 4, characterized in that: The step of recording the experimental data of the germination and seedling cultivation at the set time points, and performing growth index determination and index calculation includes: Determine the observation and recording time intervals during the germination and seedling stages, record the growth and physiological index data of corn, and measure the biomass of the root and seedling parts of the corn plants after the experiment; Excel software was used for data statistics and collation, and SPSS software was used for multiple variance tests, correlation analysis, principal component analysis and cluster analysis based on the statistical data.

6. The method for screening salt-alkali tolerant corn germplasm resources based on salt-alkali stress response according to claim 5, characterized in that: The fine-tuning and optimization architecture introduced in the deep convolutional neural network (ResNet) includes: Fine-tuning the architecture integrates adapter tuning and side tuning, training a suitable edge network to be used with ResNet, where ResNet contains n residual layers (L1, L2, ..., L n ), the edge network consists of n edge layers (S1, S2, ..., S n ), the forward propagation of ResNet is completely determined by itself. The edge network initially obtains the output L0 from ResNet and generates S1 corresponding to L1, and the gating mechanism is used to fuse the outputs of ResNet and edge network.

7. The method for screening salt-alkali tolerant corn germplasm resources based on salt-alkali stress response according to claim 6, characterized in that: The corn germplasm resources with good salt-alkali tolerance and excellent performance screened out according to data analysis include: According to the analysis results obtained by using SPSS software, a comprehensive evaluation of salt-alkali tolerance was conducted at the germination stage and seedling stage, which was compared with the identified growth changes under salt-alkali stress, and finally corn germplasm resources with good salt-alkali tolerance and excellent performance were screened out.

8. The method for screening salt-alkali tolerant corn germplasm resources based on salt-alkali stress response according to claim 7, characterized in that: In the method, in addition to recording experimental data at set time points during repeated experiments, multiple samplings are performed at other different time points to observe the dynamic effects of salinity-alkali stress on corn growth; A recovery period is also set up after the stress is relieved to observe the recovery ability of corn after the stress is relieved, and to further evaluate and screen the resilience of corn germplasm resources.

9. The method for screening salt-alkali tolerant corn germplasm resources based on salt-alkali stress response according to claim 8, characterized in that: The method also detects the gene expression levels of the selected corn germplasm resources related to salt-alkali tolerance through RT-PCR or gene chip technology, and further confirms the molecular mechanism that is different from other selected corn germplasm resources.

10. The method for screening salt-alkali tolerant corn germplasm resources based on salt-alkali stress response according to claim 9, characterized in that: The method also displays key data and intermediate results in the screening process by means of data visualization, and outputs a detailed report of the entire screening process.

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