Screening method and application of low-temperature-resistant sorghum germplasm resources
By screening sorghum germplasm at 15℃ and combining the unified measurement and comprehensive evaluation of SOD and POD physiological indicators, the problem of poor adaptability of sorghum to low-temperature planting was solved. This enabled efficient screening and evaluation of low-temperature resistant sorghum germplasm resources and provided high-quality germplasm for the breeding of cold-resistant varieties.
Patent Information
- Application Number
- CN202511752121.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-26
- Publication Date
- 2026-01-09
AI Technical Summary
In existing technologies, sorghum has poor adaptability to low-temperature environments. Traditional screening methods have poor repeatability and low accuracy, making it impossible to quickly screen out low-temperature resistant sorghum germplasm resources. Furthermore, the lack of unified standards for the determination of physiological indicators leads to insufficient reliability of screening results.
15℃ was selected as the suitable temperature for cold tolerance identification during germination. A unified measurement standard for physiological indicators such as SOD and POD was established. The cold tolerance of sorghum germplasm was comprehensively evaluated through membership function method and stepwise regression analysis, and high-quality germplasm was screened out.
This technology enables rapid screening and evaluation of sorghum germplasm resources, improves screening efficiency, reduces costs, provides low-temperature resistant sorghum germplasm for cold-resistant variety breeding, and fills the gap in brewing sorghum in Southwest China.
Abstract
Description
Technical Field
[0001] This invention relates to the field of crop genetics and breeding and seed engineering technology, specifically to a method for screening low-temperature resistant sorghum germplasm resources and its application. Background Technology
[0002] Sorghum, the world's fifth largest food crop, has multiple uses, including food, feed, brewing, and bioenergy, and plays a vital role in my country's food security and the development of its specialty industries. Although sorghum has strong resilience, it originated in the tropics and adapts poorly to high-altitude or high-temperature regions with lower temperatures. For example, Southwest my country is a prime growing area for brewing sorghum, where the unique climate and soil conditions have fostered abundant local sorghum germplasm resources. However, the spring climate in Southwest China is complex and changeable, with frequent late spring frosts. During the sowing season in March and April, the average daily temperature often drops to 10-15℃, with extreme minimum temperatures reaching below 5℃. This low-temperature stress affects sorghum growth in multiple ways, leading to reduced germination potential and rate, uneven emergence, gaps in rows, slow seedling growth, and weakened resilience.
[0003] To address the aforementioned issues, there is an urgent need for cold-resistant sorghum germplasm resources and standardized screening techniques. Traditional cold resistance assessments often rely on a single indicator or a single test scenario, using only the ratio of germination rates at room temperature and low temperature as the evaluation criterion. However, the germination rate only reflects the cold resistance potential during the seed germination stage and cannot reflect the cold resistance characteristics during the seedling growth period. Other studies have evaluated cold resistance through field phenotypic observations (such as emergence rate and plant height), but the field environment is affected by multiple factors such as temperature, precipitation, and soil fertility, resulting in poor repeatability and low accuracy of the assessment results. Furthermore, the process takes as long as 3-4 months, which cannot meet the need for rapid screening of germplasm resources.
[0004] Existing studies have confirmed that superoxide dismutase (SOD) and peroxidase (POD), as core components of the antioxidant enzyme system, directly affect the plant's ability to scavenge reactive oxygen species and are closely related to cold tolerance. Malondialdehyde (MDA) content reflects the degree of cell membrane damage, while relative water content (RWC) and chlorophyll (Chl) content are directly related to plant water status and photosynthetic capacity. These physiological indicators can reflect the cold tolerance of sorghum at the mechanistic level. However, the measurement of these indicators currently lacks unified technical standards. Different studies use different low-temperature treatment temperatures, treatment times, and sampling sites, leading to a lack of comparability of indicator data. Furthermore, a multi-indicator comprehensive evaluation model has not been established; judging cold tolerance based solely on a single physiological indicator is insufficient to comprehensively reflect the true cold tolerance potential of germplasm, resulting in unreliable screening results. Therefore, a standardized screening method with comprehensive evaluation indicators for low-temperature tolerant sorghum germplasm resources is urgently needed. Summary of the Invention
[0005] The present invention aims to provide a screening method for low-temperature resistant sorghum germplasm resources and its application, and to provide a screening method for low-temperature resistant sorghum germplasm resources with comprehensive screening method standards and evaluation indicators.
[0006] To achieve the above objectives, this application provides the following technical solution: A method for screening low-temperature resistant sorghum germplasm resources includes the following steps: S1. Place the sorghum germplasm to be tested under low temperature and constant temperature conditions for germination test, measure germination potential, germination rate, plumule and radicle length and weight, and calculate the cold tolerance coefficient CTC of each index. CTC = index value at low temperature / index value at normal temperature control. S2. Take functional leaves of seedlings to determine physiological indicators, including superoxide dismutase activity, peroxidase activity, malondialdehyde content, relative water content and chlorophyll content. S3. The cold tolerance coefficient of step S1 and the physiological indicators of step S2 are standardized using the membership function method. The membership values of each physiological indicator are calculated, and the weighted average is used to obtain the comprehensive cold tolerance evaluation value D. Germplasm with a D value greater than 0.6 is identified as cold-resistant sorghum. Stepwise regression analysis is performed with the comprehensive field cold tolerance evaluation value D as the dependent variable and the cold tolerance coefficient of each physiological indicator as the independent variable. The optimal stepwise regression equation is: D = -2.261 + 2.459SOD - 0.596POD.
[0007] Working principle and beneficial effects of the present invention: This application confirms 15℃ as the suitable temperature for cold tolerance assessment during germination, establishes unified measurement standards for physiological indicators such as SOD and POD, and achieves quantitative integration of multiple indicators through membership function method and stepwise regression analysis, transforming cold tolerance evaluation from qualitative description to quantitative analysis. A systematic evaluation of the cold tolerance of 71 local sorghum germplasms in the Chishui River Basin was conducted, and a number of high-quality germplasms with strong cold tolerance, including No.12, No.22, and No.2, were screened. Among them, germplasm No.12 showed a germination rate ≥85% at 15℃, a comprehensive cold tolerance evaluation value D>0.6, an emergence rate ≥97% under severe low temperature (late February) early sowing conditions, and a single ear grain weight more than 66% higher than sensitive germplasms, with grain quality meeting brewing requirements. These germplasms fill the gap in cold-resistant backbone parents of brewing sorghum in Southwest China, provide high-quality genetic resources for the breeding of cold-resistant varieties, and solve the problem of insufficient cold tolerance in existing germplasms.
[0008] Furthermore, SOD and POD activities were identified as the core indicators for predicting the cold tolerance performance of sorghum in the field (r=0.976). P<0.01This discovery makes rapid initial screening possible. By simply measuring the SOD and POD activities of seedlings after low-temperature treatment, the cold tolerance potential of germplasm can be preliminarily determined without the need for complex multi-index measurements and field trials. This significantly reduces screening costs and improves screening efficiency, making it particularly suitable for rapid screening in large-scale germplasm resource banks.
[0009] As an alternative, step S4 is also included: setting up two treatment groups, namely, early sowing with mild low temperature and early sowing with severe low temperature, and a control group with conventional sowing, and investigating agronomic traits such as emergence rate and single ear grain weight of each treatment group to verify the reliability of the screening results.
[0010] As a preferred option, step S1 is performed at a low-temperature constant temperature of 15°C, while the room temperature is 25°C.
[0011] As a preferred approach, stepwise regression analysis confirmed that SOD and POD activities are key physiological indicators for predicting field performance.
[0012] Application of a sorghum germplasm in the breeding of cold-resistant sorghum varieties.
[0013] Application of a sorghum germplasm in cold-resistant breeding or early spring sowing cultivation. Detailed Implementation
[0014] The following detailed description illustrates the specific implementation method: Source of sorghum germplasm resources to be tested: Seventy-one sorghum germplasm samples were collected, including mutant strains from the Chishui River Basin, local Guizhou cultivars, and commercial varieties. They were propagated at the Luban Sorghum Research Base of Maotai College. After harvesting, the samples were air-dried at 35℃ until the grain moisture content was ≤12%, and stored at 6℃ and 30% relative humidity. Healthy and intact seeds were selected for testing.
[0015] Example: A method for screening low-temperature resistant sorghum germplasm resources, comprising the following steps: S1, Indoor Screening Two temperature treatments were set up: 15℃ (mild low temperature) and 25℃ (control room temperature). An artificial climate chamber was used to control the environment with 8 hours of light / 16 hours of darkness and 60% humidity for 10 consecutive days. After sterilization, 25 seeds were placed in each petri dish, with 5 replicates. Germination rate and seed viability were recorded starting from day 3, and sterile water was added every two days. On day 10, 5 seedlings were randomly selected from each petri dish to measure the following indicators: germination potential (germination rate on day 3), germination rate (germination rate on day 10), plumule length, radicle length, plumule fresh weight, radicle fresh weight, and root-to-bud ratio (length to weight). The cold tolerance coefficient (CTC) for each indicator was calculated, where CTC = indicator value at low temperature / indicator value at room temperature (control). S2. The cold resistance of sorghum was comprehensively evaluated using the membership function method in fuzzy mathematics (de Oliveira, 1999). The calculation formula is as follows: U(X ij ） =( X ij - X jmin ) / ( X jmax - X jmin (1) U(X ij ） =1-( X ij - X jmin ) / ( X jmax - X jmin (2) (3) In the formula, U(Xij) is the cold resistance membership function value of the j-th index of the i-th resource, Xij represents the j-th index value of the i-th resource; Xjmax represents the maximum value of the j-th index in each resource, Xjmin represents the minimum value of the j-th index in each resource, Di is the mean of the fuzzy membership function of the i-th resource, n is the number of indexes, and the interval of the fuzzy membership function value is [0, 1]. If the index is positively correlated with cold resistance, the fuzzy membership function value is calculated using formula (1). If the index is negatively correlated with cold resistance, the fuzzy membership function value is calculated using formula (2). Finally, the mean of the fuzzy membership function is calculated using formula (3). The larger Di is, the stronger the cold resistance of the resource.
[0016] Based on the D value, sorghum varieties are classified into: cold-resistant (D>0.6), moderately cold-resistant (0.4≤D<0.6), moderately sensitive (0.2<D<0.4), and sensitive (D<0.2).
[0017] Based on the D value, No.12 and No.22 were selected as cold-resistant (D>0.6), and No.17 was selected as sensitive (D<0.2).
[0018] S3, Field Screening and Verification Twenty-five germplasm accessions were selected and planted at the Luban Base of Maotai College. Three treatment groups were established: conventional sowing (March 25th, average daily temperature >15℃), early sowing under severe low temperature conditions (February 15th, average daily temperature ≤10℃), and early sowing under mild low temperature conditions (March 5th, average daily temperature ≈15℃). Eight holes were planted per row, with a plant spacing of 40cm and a row spacing of 70cm, and the treatment was repeated three times. Using conventional sowing as a control, membership function analysis was performed on the emergence rate and cold tolerance coefficient of single ear grain weight of each sorghum resource under severe low temperature early sowing and mild low temperature early sowing. The 25 sorghum resources were divided into 4 categories: Category I is low temperature resistant, including 6 resources numbered 12, 22 and 95; Category II is moderately low temperature resistant, including 9 resources numbered 1, 2 and 30; Category III is moderately sensitive, including 6 resources numbered 10, 51 and 92; and Category IV is temperature sensitive, including 4 resources numbered 15 and 17.
[0019] II. Evaluation Test of Physiological Cold Tolerance of Potted Seedlings Four low-temperature resistant materials (12, 95, 2, 22), three low-temperature intolerant materials (13, 3, 1), and two temperature-sensitive materials (17, 15) were screened, totaling nine resources. After sowing in pots, the seedlings were allowed to grow to 4-5 true leaves. A 10℃ low-temperature stress group (light intensity 250-300 μmol m⁻² s⁻¹, 12h photoperiod, humidity 60%-70%) and a 25℃ control group were set up. After 10 days of stress, eight physiological indicators, including relative water content, chlorophyll, malondialdehyde, SOD, and POD, were measured.
[0020] The physiological index of cold tolerance coefficient was calculated. Through membership function analysis and clustering, it was confirmed that No. 12 was a strong cold-resistant type, while No. 15 and No. 17 were not cold-resistant types.
[0021] Using the comprehensive field cold tolerance evaluation value (D) as the dependent variable and the cold tolerance coefficients of various physiological indicators as independent variables, stepwise regression analysis was performed. The optimal stepwise regression equation was: D = -2.261 + 2.459SOD - 0.596POD (R² = 0.954, P < 0.001). The equation shows that among the eight physiological indicators (POD, SS, SP, PMP, etc.), POD and SOD have a significant impact on the cold tolerance of different sorghum resources.
[0022] The physiological index values of nine sorghum resources for liquor production were substituted into a stepwise regression equation to obtain the predicted cold tolerance D value. Finally, the correlation between the field cold tolerance D value and the predicted cold tolerance D value was analyzed. The correlation between the field cold tolerance D value and the predicted D value was extremely significant (P<0.01), with an r value of 0.976, indicating that the stepwise regression equation constructed using physiological indexes can evaluate the cold tolerance of different sorghum resources for liquor production.
[0023] It should be noted that those skilled in the art can make various modifications and improvements without departing from the technical solution of this invention. These modifications and improvements should also be considered within the scope of protection of this invention, and will not affect the effectiveness of the invention or the practicality of the patent. The scope of protection claimed in this application shall be determined by the content of its claims, and the specific embodiments described in the specification can be used to interpret the content of the claims.
Claims
1. A method for screening low-temperature resistant sorghum germplasm resources, characterized in that, Includes the following steps: S1. Place the sorghum germplasm to be tested under low temperature and constant temperature conditions for germination test, measure germination potential, germination rate, plumule and radicle length and weight, and calculate the cold tolerance coefficient CTC of each index. CTC = index value at low temperature / index value at normal temperature control. S2. Take functional leaves of seedlings to determine physiological indicators, including superoxide dismutase activity, peroxidase activity, malondialdehyde content, relative water content and chlorophyll content. S3. The cold tolerance coefficient of step S1 and the physiological indicators of step S2 are standardized using the membership function method. The membership values of each physiological indicator are calculated, and the weighted average is used to obtain the comprehensive cold tolerance evaluation value D. Germplasm with a D value greater than 0.6 is identified as cold-resistant sorghum. Stepwise regression analysis is performed with the comprehensive field cold tolerance evaluation value D as the dependent variable and the cold tolerance coefficient of each physiological indicator as the independent variable. The optimal stepwise regression equation is: D = -2.261 + 2.459SOD - 0.596POD.
2. The method for screening low-temperature resistant sorghum germplasm resources according to claim 1, characterized in that, The process also includes step S4: setting up two treatment groups, namely, early sowing with mild low temperature and early sowing with severe low temperature, and a control group with conventional sowing, and investigating agronomic traits such as emergence rate and grain weight per ear in each treatment group to verify the reliability of the screening results.
3. The method for screening low-temperature resistant sorghum germplasm resources according to claim 2, characterized in that, Step S1 is performed at a low temperature constant temperature of 15℃, while the normal temperature is 25℃.
4. The method for screening low-temperature resistant sorghum germplasm resources according to claim 3, characterized in that, Stepwise regression analysis confirmed that SOD and POD activities are key physiological indicators for predicting field performance.
5. The application of sorghum germplasm obtained by the methods described in claims 1 to 4 in the breeding of cold-resistant sorghum varieties.
6. The application of sorghum germplasm obtained by the method described in claims 1 to 4 in cold-resistant breeding or early spring sowing cultivation.