A method for identifying heat tolerance of guava

Abstract

The application discloses a method for identifying heat tolerance of guavas, and belongs to the technical field of plant variety identification. The technical steps of the application comprise the following steps: (1) heat treatment; (2) index detection; (3) calculation of a relative heat tolerance index; (4) heat tolerance sorting; (5) heat tolerance grade division; and (6) heat tolerance grade evaluation. The application can more accurately identify the heat tolerance of guavas by means of high-temperature treatment and normal-temperature control treatment and the determination of multiple physiological and growth indexes (relative conductivity, soluble protein content, soluble sugar content, antioxidant enzyme activity, pollen germination rate, fruit number per plant and fruit setting rate). The relative heat tolerance index S value is calculated according to the above indexes, the heat tolerance of the varieties is sorted and evaluated according to the relative heat tolerance index S value, the heat tolerance of the guava varieties or germplasm resources can be objectively and accurately evaluated, and the new heat-tolerant varieties can be bred and the application of the dominant heat-tolerant varieties can be promoted.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of plant variety identification, and particularly relates to a guava heat tolerance identification method. BACKGROUND

[0002] Guava is an important tropical and subtropical fruit tree in southern China. Due to its unique fragrance, advantages in fresh eating and processing, short planting cycle and fast yield, guava has been planted in Guangxi since its first introduction in 1985. With government guidance and spontaneous planting, guava has been developed on a large scale since around 2012. Up to now, the planting area and yield of guava in Guangxi have reached 432,000 mu and 361,000 tons respectively, ranking first in China and becoming an advantageous and characteristic fruit industry in Guangxi.

[0003] However, while the planting scale is rapidly expanding, there are still some outstanding problems in guava planting, such as limited flowering and fruit setting in summer due to frequent occurrence of extremely high temperature weather, and low yield. From the adaptability of conventional guava varieties to climate, the largest amount of flowers and fruits is in October and November; there is a certain amount of flowers and fruits in April and May and September, but there is a large uncertainty; there is very little or even no flowers and fruits in the high-temperature season from June to August; and there is no flowers and fruits from December to the following March. Due to the large amount of branches and the small amount of flowers in summer, and the large amount of flowers and the long maturation time of fruits in autumn and winter, the fruits are small and of poor quality, resulting in low yield of the main cultivars of guava in Guangxi. Therefore, the current increase in the yield of guava commodity fruits needs to break through the bottleneck of low flower and fruit amount in the high-temperature season. With the global temperature rise and the increase in extreme weather caused by the greenhouse effect, the entire planting industry will continue to face the challenge of high temperature.

[0004] In the traditional method, the heat tolerance of guava varieties is usually identified by observing the flowering and fruit setting traits of plants in the field in the high-temperature season and identifying the heat tolerance of guava varieties. The normal flowering and fruit setting of plants in the high-temperature period (daily maximum temperature > 35℃) is used as the basis for identifying the heat tolerance of varieties. This identification method is relatively rough, is easily affected by factors such as planting time and different flowering periods, lacks a non-high-temperature control, and can only observe phenotypic agronomic traits, so the stress response of plants to heat damage cannot be judged. Therefore, the application of the traditional method to identify the heat tolerance of guava is not comprehensive. Therefore, it is urgent to screen, identify and breed guava varieties with heat tolerance in guava production, but there is still a lack of technical standards for identifying and evaluating the heat tolerance of guava, which restricts the breeding of new heat-tolerant varieties and the promotion and application of superior heat-tolerant varieties. SUMMARY

[0005] In view of the above problems, the present application provides a guava heat tolerance identification method to solve the problem of the lack of heat tolerance identification and evaluation system in the process of variety breeding and germplasm screening of guava.

[0006] The present application is achieved by the following technical solutions:

[0007] A method for identifying heat tolerance of guava, comprising the following steps:

[0008] (1) heat treatment: setting high temperature treatment and normal temperature control treatment for guava varieties to be identified, the high temperature treatment is high temperature stress treatment in a plastic temperature increasing shed, and the normal temperature control treatment is normal treatment under natural climate conditions;

[0009] (2) index detection: after the heat treatment, the indexes of relative conductivity, soluble protein content, soluble sugar content, superoxide dismutase activity, peroxidase activity and catalase activity of plant leaves are determined;

[0010] and the indexes of pollen germination rate, fruit number per plant and fruit setting rate are determined;

[0011] (3) calculation of relative heat tolerance index: the indexes determined in step (2) are substituted into the following formula to calculate the relative heat tolerance index S value of the varieties to be identified:

[0012]

[0013] F(Xi)=1-(Xi-Xmin) / (Xmax-Xmin);

[0014] F(Xi)=(Xi-Xmin) / (Xmax-Xmin);

[0015] S=∑F(Xi) / 9(i=1,2,3,4,5,6,7,8,9);

[0016] In the formula, H is the average value of the i th index of the variety under high temperature stress treatment; is the average value of the i th index of all varieties to be identified under high temperature stress treatment; CK is the average value of the i th index of the variety under normal temperature control treatment; Xi is the heat tolerance coefficient of the i th index of the variety; Xmin is the minimum value of the heat tolerance coefficient of the i th index among all varieties to be identified; Xmax is the maximum value of the heat tolerance coefficient of the i th index among all varieties to be identified;

[0017] (4) heat tolerance ranking: ranking the relative heat tolerance index S value of the varieties to be identified calculated in step (3), that is, corresponding to the heat tolerance of the varieties;

[0018] (5) heat tolerance grade division: based on the relative heat tolerance index S value of guava varieties with known heat tolerance, the guava heat tolerance evaluation system is divided into four grades, and the grade division is as follows:

[0019]

[0020] (6) heat tolerance grade evaluation: matching the relative heat tolerance index S value of the guava variety to be identified calculated in step (3) with the heat tolerance grade in step (5), and evaluating the heat tolerance grade of the variety to be identified.

[0021] Further, in step (1), the high-temperature treatment is: daily maximum temperature 38-45 DEG C, daily average temperature 30-31 DEG C, daily temperature duration of 4-6 h, and humidity in the shed > 30%.

[0022] Further, in step (1), the normal-temperature control treatment is: daily maximum temperature < 37 DEG C, daily average temperature < 28.5 DEG C, and daily temperature duration of < 2 h.

[0023] Further, in step (2), the relative conductivity of the leaf is measured by the soaking method; the soluble protein content of the leaf is measured by the Coomassie brilliant blue G-250 method; the soluble sugar content of the leaf is measured by the anthrone colorimetric method or the kit method; the superoxide dismutase activity of the leaf is measured by the chloronitro tetrazolium blue photoreduction method or the kit method; the peroxidase activity of the leaf is measured by the guaiacol method or the kit method; and the catalase activity of the leaf is measured by the ultraviolet spectrophotometry method or the kit method.

[0024] Further, the leaf is the first full-expansion leaf of a newly-born branch.

[0025] Further, in step (2), the pollen germination rate is measured by collecting flower buds of the high-temperature treatment and the normal-temperature control treatment plants on the same day, taking off the anthers in a 24-26 DEG C environment, and placing them in a ventilated and dry place for 1.5-2 h, then sweeping the pollen with a brush and mixing it well, and then uniformly scattering it into a liquid medium and mixing it well, and then dark-culturing it in a 24-26 DEG C environment for 2.5-3 h.

[0026] Further, the formula of the liquid medium comprises: 350-400 mg / mL Ca(NO3)2·4H2O, 80-100 g / L sucrose, 15-20 mg / L boric acid, and 130-150 g / L PEG-4000.

[0027] Further, in step (6), H36 and MT are identified as high-heat-tolerance-type varieties, H3, P5, P7 and Xiaji are identified as medium-heat-tolerance-type varieties, P1, Dongliu and Yuanshao are identified as intermediate-type varieties, and Huangyou No. 2 and DN are identified as heat-sensitive-type varieties.

[0028] Compared with the prior art, the application has the following advantages and beneficial effects:

[0029] 1. The method of the present application can evaluate the heat tolerance of guava varieties or germplasm resources, which is helpful for breeding and popularizing heat-tolerant varieties. The present application can more accurately identify the heat tolerance of guava by high temperature treatment and normal temperature control treatment, combined with the determination of multiple physiological and growth indexes (such as relative conductivity, soluble protein content, soluble sugar content, antioxidant enzyme activity and pollen germination rate, fruit number per plant, fruit setting rate), and the relative heat tolerance index S value is calculated from the above indexes, and the heat tolerance of the varieties is sorted and evaluated according to the size of the relative heat tolerance index S value. Thus, the heat tolerance of guava varieties or germplasm resources can be objectively and accurately evaluated, thereby helping to breed new heat-tolerant varieties and popularize and apply superior heat-tolerant varieties.

[0030] 2. The present application designs a two-factor split plot test, sets high temperature treatment and normal temperature control treatment as the main plot factor, and sets the varieties to be identified as the split plot factor, determines multiple physiological and growth indexes of guava, and calculates the relative heat tolerance index S value of the varieties to be identified by the above indexes by using the membership function value method, wherein the heat tolerance coefficient Xi of the i th index of the variety is calculated by using the formula , which can effectively avoid the deviation of the heat tolerance evaluation of the variety when the index value under high temperature treatment is higher than the control value but much lower than the average level of the group, and can more accurately identify the heat tolerance of guava.

[0031] 3. The classification of the heat tolerance grade of guava in the present application is mainly based on the size of the relative heat tolerance index S value, and the reasons are as follows: (1) the greater the S value, the stronger the heat tolerance, and the heat tolerance of the tested variety can be sorted according to the S value; (2) it can be known from Figure 3 that the heat tolerance classification of the variety is consistent with the classification result of the cluster analysis, which proves the reliability of the grade parameter and the classification; (3) in the examples, a total of 12 varieties are tested, and the S value and the grade parameter obtained under the test conditions are also based on the actual application results, and can be applied to the heat tolerance grade evaluation of the varieties under the same test conditions.

[0032] 4. The present application refers to the classified heat tolerance grade of guava, matches the relative heat tolerance index S value of the known heat-tolerant varieties with the heat tolerance grade of guava, and the classification result corresponds to the heat tolerance of the known varieties, which proves the reliability and accuracy of the identification method of the present application. BRIEF DESCRIPTION OF DRAWINGS

[0033] Figure 1 It is a small area distribution schematic diagram.

[0034] Figure 2 It is a small area plane schematic diagram.

[0035] Figure 3 It is a system cluster analysis pedigree based on the relative heat tolerance index S value of the tested varieties. DETAILED DESCRIPTION

[0036] The application will be further described in detail by the following examples, which are only used to illustrate the application and do not limit the protection scope of the application.

[0037] Examples

[0038] In 2022, 50 guava variety (germplasm) resources planted in the open field were preliminarily screened for heat tolerance in the Lijian Scientific Research Base of Guangxi Academy of Agricultural Sciences in the ASEAN Economic Development Zone of Nanning, Guangxi. The screening standard was to observe the heat damage of guava plants and the flowering and fruit setting traits under high temperature conditions above 35°C. Because the number of plants for heat tolerance identification was large in the observation of guava hybrid offspring, preliminary screening of heat tolerance can reduce the workload in the later identification. Weak heat tolerance was manifested as weak plant growth or even wilting, and normal flowering and fruit setting; moderate heat tolerance was manifested as medium plant growth, low flower quantity and low fruit setting rate; strong heat tolerance was manifested as vigorous plant growth, normal flowering and fruit setting. The 12 variety (germplasm) resources of MT, Huangyou No. 2, H36 (known as high heat tolerance type), Donghuisu, Tainong No. 1 (known as moderate heat tolerance type), Xiaji, P1, P5, P7, H3, Yuanniao and DN entered the second stage of heat tolerance identification.

[0039] Among the above known heat tolerance types, Tainong No. 1 is a main cultivar of purple fruit guava and is a moderate heat tolerance type recognized in the art, serving as a reference variety. H36 is evaluated for heat tolerance according to the “8.2 Heat Tolerance” of “8 Stress Resistance” in the “DB 46 / T 530-2021 Description Specification for Guava (Passion Fruit) Germplasm Resources” of Hainan Provincial Local Standard, and the method is as follows:

[0040] “Observe the mature plants grown for more than 6 months, and record their heat tolerance under natural conditions or high temperature stress environment, which is divided into:

[0041] —Weak (30% of the plants appear wilting under high temperature conditions above 35°C);

[0042] —Medium (leaf scorch and severe flower and fruit drop of plants under high temperature conditions above 35°C);

[0043] —Strong (normal flowering and fruit setting of plants under high temperature conditions above 35°C).”

[0044] H36 meets the planting performance of strong heat tolerance, and the inventors have observed that its plant growth is vigorous and its flowering and fruit setting traits are obviously better than those of other varieties in the high temperature period for two consecutive years, so it is classified as a high heat tolerance type in the preliminary screening of heat tolerance.

[0045] In 2023, 12 varieties of passion fruit were selected for the second phase of heat tolerance identification test. Two-factor split-plot experiment design was adopted, with temperature treatment as the main zone factor, including high temperature treatment and normal temperature control treatment, and variety as the split zone factor. Planting was done on March 30th, with 3 varieties per plot, 2-3 plants per variety, planting row spacing of 1.8m and plant spacing of 1.4m. High temperature treatment and normal temperature control were set up, with 3 repetitions for each variety, a total of 14 plants for each variety. High temperature treatment and normal temperature control were set up. High temperature treatment method: a high temperature treatment growth shed frame with length x width x height of 12.0m x 2.0m x 4.0m was made of steel pipe and fixed on the ditch surface. When the high temperature treatment started, the temperature was raised by covering the plastic film (transmittance more than 95%) around the growth shed frame. A 20cm high gap was left on both sides of the top of the greenhouse for gas exchange. After the high temperature treatment ended, the film was raised, and the post-management and field microclimate were consistent with the control. The plot distribution diagram is shown in Figure 1 Two-factor split-plot experiment design was adopted, with A1 as heat treatment and A2 as normal temperature control treatment as the main zone factor; B1-B4 as the split zone factor. The plot plan diagram is shown in Figure 2 A1 is the heat treatment of plastic warming shed, and A2 is the normal temperature control treatment; the plastic warming shed is 2m wide and 12m long, with an interval of 1.5m between adjacent warming sheds, a planting row width of 1.0m, and a hedge-style planting.

[0046] Before the heat treatment, the warming shed was in an open state, and the control was in the same natural environment conditions. When the second-stage tendril of the plant was pulled out, the high temperature heat stress treatment was started, the top and side film of the warming shed was put down, and the temperature in the shed was monitored in real time until the high temperature set value was reached, i.e. the daily maximum temperature was 38-45℃, the daily average temperature was 30-31℃, the daily temperature ≥ 35℃ lasted for 4-6h, and the humidity in the shed was > 30%. The natural control daily maximum temperature was < 37℃, the daily average temperature was < 28.5℃, and the daily temperature ≥ 35℃ lasted for < 2h. The heat treatment ended after 40d.

[0047] Leaf relative conductivity determination: after the heat stress treatment ended, sampling was done, the sampling site was the first full-expansion leaf of the new shoots, the immersion method was used to determine the relative conductivity of the leaf, sampling was done at a time when spraying was avoided, and sampling and determination were done 3 times for each treatment. After the leaf was collected, it was taken back to the laboratory in an ice box, avoiding the leaf margin and leaf vein, the leaf was cut and immediately weighed about 0.2g of sample, placed in a 20mL graduated test tube, added 20mL of deionized water with a pipette, and the leaf was pressed into the deionized water with a filter paper to submerge it, the plastic film was sealed, and it was soaked at room temperature of about 26℃ for 16h. The next day, the filter paper was taken out and the liquid in the test tube was mixed several times, part of the liquid was poured into a clean 10mL centrifuge tube, the initial conductivity was measured, and after the measurement was completed, it was poured back into the original test tube, and the complete conductivity was measured after being cooled to room temperature in a 100℃ boiling water bath. Relative conductivity = initial conductivity / complete conductivity * 100%. The results are shown in the table below:

[0048] Table 1 Relative electrical conductivity (%) and membership function value F(Xi)

[0049]

[0050]

[0051] Note: H is the measured value under heat stress treatment, CK is the measured value of the control, and the same below.

[0052] Soluble protein content determination: each treatment was measured 3 times, and the sampling site was the first fully expanded leaf of the new shoots. The Coomassie Brilliant Blue G-250 method was used to determine the soluble protein content of the leaves. Fresh leaves were quickly weighed 0.1 g, placed in a mortar, and 1 mL of distilled water was added to grind to homogenate. All were transferred to a centrifuge tube and centrifuged at 4000 r / min for 20 min. The supernatant was taken for measurement. Add 20 μL of extract to the centrifuge tube, mix well, and let stand for 10 min. Use a 1 cm cuvette to adjust the zero at 595 nm, and measure the absorbance of each tube. Standard curve preparation: take 0, 0.2, 0.4, 0.6, 0.8, and 1.0 mL of standard protein solution (100 μg / mL), add distilled water to a total volume of 1.0 mL, and add 5 mL of G-250 reagent to each tube. Mix well, cover, and let stand for 10 min. Use a 1 cm cuvette to adjust the zero at 595 nm, and measure the absorbance of each tube. Take the protein content (μg) as the x-axis and the absorbance A 595 of each tube as the y-axis to draw the standard curve and calculate the regression equation. Soluble protein content (mg / g fresh weight) = (x × V 提取 ) / (W × V 样 ). In the formula, x is the soluble protein content read from the standard curve, V 提取 is the total volume of the sample extract, V 样 is the volume of the sample extract taken for measurement, and W is the fresh weight of the sample. The results are as follows:

[0053] Table 2 Absorbance values of each tube of the soluble protein content standard curve

[0054] Serial number Protein content / μg A 595 ]]> 1 0 0 2 20 0.158 3 40 0.285 4 60 0.398 5 80 0.498 6 100 0.636

[0055] Standard curve: y = 0.0062x + 0.0211 (R 2 = 0.9953)

[0056] Table 3 Soluble protein content (mg / g fresh weight) and membership function value F(Xi)

[0057]

[0058]

[0059] Soluble sugar content determination (kit method): each treatment was sampled 3 times, and the sampling site was the first fully expanded leaf of the new shoot. The plant soluble sugar content kit (item number JC0401-M, Nanjing Jimeisu Biological Technology Co., Ltd.) was used for determination. 0.05 g of fresh leaf sample was weighed, 1 mL of distilled water was added, and homogenate was prepared. The homogenate was poured into a covered centrifuge tube, 95°C water bath for 10 min (cover tightly to prevent water loss), and then cooled. After cooling, 8000g, 25°C centrifugation for 10 min, and then the supernatant was taken for determination (dilution was paid attention to). The enzyme marker was preheated for more than 30 min, the wavelength was adjusted to 620 nm, and distilled water was adjusted to zero. The water bath was adjusted to 95°C. The reagent was added as follows:

[0060] Table 4 reagent addition

[0061] Reagent (μL) Blank tube Determination tube Standard tube Sample 40 Standard solution 40 Distilled water 80 40 40 Working solution 20 20 20 Concentrated sulfuric acid 200 200 200

[0062] After mixing, 95°C water bath for 10 min (cover tightly to prevent water loss), naturally cool to room temperature, 200uL transfer to enzyme marker plate, record the determination absorbance value A at 620nm wavelength, calculate ΔA 标准 = A 标准管 -A 空白管 , ΔA = A 测定管 -A 空白管 . (The blank tube only needs to be done 1-2 times).

[0063] Preparation of standard curve: with different concentrations of glucose standard solution as x axis, ΔA standard as y axis, draw the standard curve y = kx + b. The absorbance values of each tube of the standard curve are as follows:

[0064] Table 5 absorbance values of each tube of the standard curve

[0065]

[0066]

[0067] Standard curve: y = 3.6265x + 0.0176, R 2 = 0.9986

[0068] Put ΔA determination into the equation to get x value (mg / mL). Soluble sugar content (mg / g fresh weight) = x × V 提取 ÷ W × dilution multiple = x ÷ W × dilution multiple. X is the soluble sugar content read on the standard curve; V 提取 is the total volume of sample extract, 1mL; W is the fresh weight of the sample, and the dilution multiple is 20 times. The results are as follows:

[0069] Table 6 Soluble sugar content (mg / g fresh weight) and membership function value F(Xi)

[0070] Variety (germplasm) H CK Xi Xmax Xmin F(Xi) MT 27.50 27.99 0.99 1.33 0.79 0.37 Huangyou No. 2 24.11 26.77 0.89 1.33 0.79 0.18 H36 24.04 27.90 0.87 1.33 0.79 0.14 Dongli honey 24.89 22.89 0.99 1.33 0.79 0.38 Taigeng No. 1 29.81 18.93 1.33 1.33 0.79 1.00 Xiaji 26.78 24.12 1.04 1.33 0.79 0.47 P1 32.45 35.35 1.05 1.33 0.79 0.48 P5 32.09 30.85 1.10 1.33 0.79 0.58 P7 34.95 31.78 1.18 1.33 0.79 0.73 H3 25.63 28.49 0.91 1.33 0.79 0.23 Yuanxiao 29.02 26.85 1.06 1.33 0.79 0.51 DN 20.86 25.28 0.79 1.33 0.79 0.00

[0071] SOD activity determination: each treatment was sampled 3 times, and the sampling site was the first fully expanded leaf of the new shoot. The SOD activity was determined using a superoxide dismutase kit (product code JC0101-M, Nanjing Jceme Biotechnology Co., Ltd.). About 0.1 g of fresh leaf sample was weighed, 1 mL of extraction solution was added, and homogenization was performed; 8000g, 4℃ centrifugation for 10 min, take the supernatant, and place it on ice for determination. The enzyme marker was preheated for more than 30 min, and the wavelength was adjusted to 560 nm. Reagent two was diluted twice with distilled water, and the amount of reagent two was equal to the amount of distilled water (1:1 dilution). One bottle of reagent four was dissolved in 5 mL of distilled water (used within one week after dissolution), and then diluted 4 times with distilled water, and the amount of reagent four was equal to the amount of distilled water (1:3 dilution). Before determination, reagents one, three and four were placed in a 25℃ water bath for more than 5 min. The following reagents were added in order in a 96-well plate for sample determination:

[0072] Table 7 Reagent sample determination

[0073]

[0074]

[0075] Mix well, and after standing at room temperature for 30 min, measure the absorbance value A of each tube at 560 nm.

[0076] Results calculation: ① Calculation of inhibition percentage: inhibition percentage = (A 对照管 -A 测定管 ) ÷ A 对照管 × 100%. ② SOD enzyme activity unit: when the inhibition percentage in the above xanthine oxidase coupled reaction system is 50%, the SOD enzyme activity in the reaction system is defined as one enzyme activity unit (U / mL). ③ SOD enzyme activity calculation: SOD activity (U / g fresh weight) = [inhibition percentage ÷ (1-inhibition percentage) × V 反总 ] ÷ (W × V 样 ÷ V 样总 ) = 11.11 × inhibition percentage ÷ (1-inhibition percentage) ÷ W. V 反总 : total volume of the reaction system, 0.2 mL; V 样 : sample volume added to the reaction system, 0.018 mL; V 样总 : extraction solution volume, 1 mL; W: sample mass, g. The results are as follows:

[0077] Table 8 Superoxide dismutase activity (U / g fresh weight) and membership function value F(Xi)

[0078] Variety (germplasm) H CK Xi Xmax Xmin F(Xi) MT 353.23 403.38 0.93 1.27 0.83 0.22 Huangyou No. 2 423.46 476.36 1.03 1.27 0.83 0.46 H36 466.61 373.45 1.27 1.27 0.83 1.00 Dongli honey 277.69 183.09 1.14 1.27 0.83 0.71 Taigeng No. 1 319.84 413.69 0.83 1.27 0.83 0.00 Xiaji 412.55 444.59 1.04 1.27 0.83 0.47 P1 383.16 416.55 0.99 1.27 0.83 0.36 P5 333.91 355.51 0.93 1.27 0.83 0.23 P7 296.77 297.84 0.91 1.27 0.83 0.18 H3 388.52 440.60 0.98 1.27 0.83 0.34 Yuanxiao 309.22 322.42 0.91 1.27 0.83 0.18 DN 366.37 307.08 1.10 1.27 0.83 0.62

[0079] Peroxidase activity determination: each treatment was sampled for determination of 3 replicates, and the sampling site was the first fully expanded leaf of the new branch. The peroxidase kit (item number JC0102-S, Nanjing Jimesi Biological Technology Co., Ltd.) was used for determination. 0.1 g of fresh leaf sample was weighed, 1 mL of extraction solution was added, and homogenization was performed; 8000g, 4°C centrifugation for 10 min, take the supernatant, and place it on ice for determination. The spectrophotometer was preheated for more than 30 min, the wavelength was adjusted to 470 nm, and distilled water was used for zero adjustment. Preparation of working solution: before use, mix reagent 1, reagent 2 and reagent 3 according to the ratio of 2.6 mL:1.5 μL:1 μL; preheat at 25°C for more than 10 min; prepare and use immediately. In a 1 mL glass cuvette, add 50 μL of sample and 950 μL of working solution, mix well, and record the absorbance A1 at 470 nm for 1 min and the absorbance A2 after 2 min. Calculate ΔA=A2-A1.

[0080] Result calculation: POD activity unit definition: A 470 0.01 is an enzyme activity unit. POD (U / g fresh weight) = ΔA x V 反总 ÷ (W x V 样 ÷ V 样总 ) ÷ 0.01 ÷ T = 2000 x ΔA ÷ W. V 反总 : total volume of reaction system, 1 mL; V 样 : sample volume, 0.05 mL; V 样总 : extraction solution volume, 1 mL; T: reaction time, 1 min; W: fresh weight of sample. The results are as follows:

[0081] Table 9 Peroxidase activity (U / g fresh weight) and membership function value F(Xi)

[0082] Variety (germplasm) H CK Xi Xmax Xmin F(Xi) MT 2233.74 2044.82 1.44 1.66 0.25 0.84 Huangyou No. 2 2194.44 3138.03 1.23 1.66 0.25 0.69 H36 2652.47 2219.13 1.66 1.66 0.25 1.00 Dongli honey 393.63 1534.88 0.29 1.66 0.25 0.03 Taigeng No. 1 225.99 386.90 0.38 1.66 0.25 0.10 Xiaji 669.86 365.61 1.18 1.66 0.25 0.66 P1 1182.69 1894.93 0.79 1.66 0.25 0.38 P5 1728.97 1432.69 1.30 1.66 0.25 0.74 P7 1006.46 1067.42 0.88 1.66 0.25 0.44 H3 1222.22 2584.70 0.73 1.66 0.25 0.34 Yuanxiao 1143.64 1735.85 0.79 1.66 0.25 0.38 DN 304.52 1215.72 0.25 1.66 0.25 0.00

[0083] Catalase activity determination: Each treatment was sampled for determination of triplicate, and the sampling site was the first fully expanded leaf of the new shoot. The catalase kit (item number JC0103-S, Nanjing Jiemai Biological Technology Co., Ltd.) was used for determination. About 0.1 g of fresh leaf sample was weighed, 1 mL of extraction solution was added, and homogenization was performed; 8000 g, 4°C centrifugation for 10 min, take the supernatant, and place it on ice for determination. The enzyme marker was preheated for more than 30 min, the wavelength was adjusted to 240 nm, and distilled water was used for zero adjustment. CAT detection working solution was measured at 25°C for more than 10 min before determination. Prepare one 96-well UV plate. Add 10 μL of sample and 190 μL of working solution to the enzyme marker plate (UV plate), mix well, and immediately measure the initial absorbance A1 and the absorbance A2 after 1 min at 240 nm, and calculate ΔA = A1-A2.

[0084] CAT activity calculation: The definition of CAT activity unit is that 1 μmol of H2O2 is catalyzed per minute per milliliter of sample extract, which is defined as one enzyme activity unit. CAT (U / mL) = [ΔA x V 反总 ÷ (ε x d) x 10 6 ] ÷ V 样 ÷ T. V 反总 : total volume of the reaction system, 1.035 x 10 -3 L; ε: molar extinction coefficient of H2O2, 43.6 L / mol / cm; d: cuvette optical path, 1 cm; V 样 : sample volume, 0.035 mL; T: reaction time, 1 min; 10 6 : unit conversion factor, 1 mol = 10 6 μmol. The results are as follows:

[0085] Table 10 Catalase activity (U / g fresh weight) and membership function value F(Xi)

[0086]

[0087]

[0088] Pollen germination rate determination: After 40 days of heat stress treatment, collect the flower buds of the heat stress treatment and control plants that bloom on the same day (the flower buds have been white, and the petals have not yet unfolded). Collect 8 flowers per plot for each treatment, and 24 flowers for 3 plots. Take the anthers off the flower buds in the laboratory at 25°C, place them on a weighing paper, and place them in a well-ventilated dry place for 2 hours. When the anthers are fully cracked, use a brush to sweep the pollen and mix it well for use. Take a 5 cm diameter culture dish, add 4.0 mL of liquid medium to the culture dish, evenly spread the pollen sample into the culture dish, mix well, and incubate in the liquid medium at 25°C in the dark for 3 hours. Count the number of pollen germination under a light microscope, and the total number of pollen in each field is ≥60. Each sample is repeated 3 times, and the pollen germination rate (%) is calculated. The formula of the liquid medium is: 400 mg / mL Ca(NO3)2·4H2O, 100 g / L sucrose, 20 mg / L boric acid (H3BO3), 150 g / L PEG-4000. The results are as follows:

[0089] Table 11 Pollen germination rate (%) and membership function value F(Xi)

[0090]

[0091]

[0092] Single plant fruit number determination: The number of fruits per plant of the heat stress treatment and control plants during the heat stress period is determined, and all plants in each plot are counted, repeated 3 times. The results are as follows:

[0093] Table 12 Number of fruits per plant (number / plant) and membership function value F(Xi)

[0094] Variety (germplasm) H CK Xi Xmax Xmin F(Xi) MT 12.00 25.70 1.95 1.95 0.00 1.00 Huangyou No. 2 0.00 0.89 0.00 1.95 0.00 0.00 H36 7.57 13.86 1.35 1.95 0.00 0.70 Dongli honey 0.00 0.00 0.00 1.95 0.00 0.00 Taigeng No. 1 2.29 4.43 0.58 1.95 0.00 0.30 Xiaji 5.14 14.14 0.92 1.95 0.00 0.47 P1 2.43 2.86 0.77 1.95 0.00 0.40 P5 2.86 3.14 0.86 1.95 0.00 0.44 P7 4.14 3.00 1.28 1.95 0.00 0.66 H3 4.43 5.29 1.05 1.95 0.00 0.54 Yuanxiao 0.00 1.43 0.00 1.95 0.00 0.00 DN 1.14 2.00 0.45 1.95 0.00 0.23

[0095] Fruit setting rate determination: The fruit setting rate of the heat stress treatment and control plants is investigated at the peak flowering period. The flowers that bloom on the same day are marked with a date, and the marking can be done continuously for 3-5 days. The number of marked flowers in each plot is ≥50, repeated 3 times, and the number of marked flowers in each treatment is ≥150. After 20 days of marking, the fruit setting is investigated, the number of fruit setting is counted, and the fruit setting rate (%) is calculated as fruit setting number / number of marked flowers. The results are as follows:

[0096] Table 13 Fruit setting rate (%) and membership function value F(Xi)

[0097]

[0098]

[0099] Relative heat tolerance index calculation of the tested guava varieties (germplasm): The relative heat tolerance index of each determination index is calculated according to the following formula:

[0100]

[0101] F(Xi) = 1 - (Xi - Xmin) / (Xmax - Xmin);

[0102] F(Xi) = (Xi - Xmin) / (Xmax - Xmin);

[0103] S = ∑F(Xi) / 9 (i = 1, 2, 3, 4, 5, 6, 7, 8, 9);

[0104] In the formula, H is the average value of the i th index of the variety under high temperature heat stress treatment; is the average value of the i th index of all varieties to be identified under high temperature heat stress treatment; CK is the average value of the i th index of the variety under normal temperature control treatment; Xi is the heat tolerance coefficient of the i th index of the variety; Xmin is the minimum value of the heat tolerance coefficient of the i th index among all varieties; Xmax is the maximum value of the heat tolerance coefficient of the i th index among all varieties. The results are as follows:

[0105] Table 14 Relative heat tolerance index S

[0106]

[0107] According to the relative heat tolerance index S value of the variety, the stronger the heat tolerance, the greater the S value, and the stronger the heat tolerance of the variety. The heat tolerance of the 12 test guava varieties is ranked in Table 14.

[0108] Based on the size of the above heat tolerance index S value, the guava heat tolerance evaluation system is divided into four levels, as follows:

[0109]

[0110] Referring to the above guava heat tolerance evaluation classification, it can be seen from the relative heat tolerance index S value that among the 12 guava variety (germplasm) resources tested in 2023, there are 2 high heat tolerance variety (germplasm) resources: H36, MT, 5 moderate heat tolerance germplasm resources: H3, Tainong No. 1, P5, P7, Xiaji, 3 intermediate varieties (germplasm) resources: P1, Donghuisu and Yuanxiao, 2 heat sensitive varieties (germplasm) resources: Huangyou No. 2 and DN.

[0111] The above classification of heat tolerance is mainly based on the size of the relative heat tolerance index S value. The reasons are as follows: (1) The greater the S value, the stronger the heat tolerance, and the S value can be used to sort the heat tolerance of the test variety. (2) From the results of the relative heat tolerance index S value, it can be seen that the heat tolerance of the varieties can be divided into four levels, and the classification is reasonable. Figure 3It can be seen that the heat tolerance classification of the varieties is consistent with the classification result of cluster analysis, proving the reliability of the grade parameters and classification.(3) In the examples, a total of 12 varieties participated in the test, and the S values and grade parameters obtained under the test conditions are also based on the actual application results, and can be applied to the heat tolerance grade evaluation reference of varieties under the same test conditions.

[0112] According to the known H36 and Taikang No. 1, they are high heat tolerance type varieties and moderate heat tolerance type varieties respectively, and the relative heat tolerance indexes S values of H36 and Taikang No. 1 calculated by the identification method of the present application are 0.69 and 0.53 respectively, and the two relative heat tolerance indexes S values are matched with the heat tolerance grade of the guava, so it can be seen that H36 and Taikang No. 1 are just high heat tolerance type and moderate heat tolerance type varieties, which corresponds to the known heat tolerance of H36 and Taikang No. 1, and illustrates the reliability and accuracy of the identification method of the present application.

[0113] The above only describes the preferred embodiments of the present application and is not intended to limit the present application, and any modification, equivalent replacement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for identifying the heat resistance of passion fruit, characterized in that, Includes the following steps: (1) Heat treatment: High temperature treatment and normal temperature control treatment were set for the passion fruit varieties to be identified. The high temperature treatment was high temperature heat stress treatment in a plastic greenhouse, and the normal temperature control treatment was normal treatment under natural climate conditions. (2) Index detection: After the heat treatment, the relative conductivity, soluble protein content, soluble sugar content, superoxide dismutase activity, peroxidase activity and catalase activity of the plant leaves were measured. In addition, the pollen germination rate, number of fruits per plant, and fruit set rate of the plants were measured. (3) Calculation of relative heat resistance index: Substitute the index measured in step (2) into the following formula to calculate the relative heat resistance index S value of the variety to be identified: (4) Heat resistance ranking: The relative heat resistance index S values ​​of the varieties to be identified calculated in step (3) are ranked, that is, the heat resistance of the corresponding varieties is strong or weak. (5) Classification of heat resistance: Based on the relative heat resistance index S value of known heat-resistant passion fruit varieties, the heat resistance evaluation system of passion fruit is divided into four levels, as follows: Heat resistance rating reference S value Highly heat-resistant type, S≥0.60 Medium heat resistance type: 0.45 ≤ S < 0.60 Intermediate type: 0.30 ≤ S ≤ 4.50 For heat-sensitive types, S < 0.30; (6) Evaluation of heat resistance level: The relative heat resistance index S value of the passion fruit variety to be identified calculated in step (3) is matched with the heat resistance level in step (5) to evaluate the heat resistance level of the variety to be identified.

2. The method for identifying the heat resistance of passion fruit according to claim 1, characterized in that, In step (1), the high temperature treatment is as follows: the highest daily temperature is 38-45℃, the average daily temperature is 30-31℃, the daily temperature is ≥35℃ for 4-6 hours, and the humidity inside the greenhouse is >30%.

3. The method for identifying the heat resistance of passion fruit according to claim 1, characterized in that, In step (1), the normal temperature control treatment is as follows: the highest daily temperature is <37℃, the average daily temperature is <28.5℃, and the duration of the daily temperature ≥35℃ is <2h.

4. The method for identifying the heat resistance of passion fruit according to claim 1, characterized in that, In step (2), the relative conductivity of the leaves was determined by immersion method; the soluble protein content of the leaves was determined by Coomassie Brilliant Blue G-250 method; the soluble sugar content of the leaves was determined by anthrone colorimetric method or kit method; the superoxide dismutase activity of the leaves was determined by nitrotetrazole chloride blue photochemical reduction method or kit method; the peroxidase activity of the leaves was determined by guaiacol method or kit method; and the catalase activity of the leaves was determined by ultraviolet spectrophotometry or kit method.

5. The method for identifying the heat resistance of passion fruit according to claim 4, characterized in that, The leaf in question is the first fully expanded leaf of a new shoot.

6. The method for identifying the heat resistance of passion fruit according to claim 1, characterized in that, In step (2), the pollen germination rate is determined by collecting flower buds that bloomed on the same day from plants treated with high temperature and those treated with normal temperature. The anthers of the flower buds are removed at 24-26℃ and placed in a ventilated and dry place for 1.5-2 hours until the anthers fully dehisce. The pollen is then swept off with a brush. Mix thoroughly, then evenly sprinkle into the liquid culture medium and mix thoroughly. Incubate in the dark at 24–26°C for 2.5–3 hours.

7. The method for identifying the heat resistance of passion fruit according to claim 6, characterized in that, The liquid culture medium is formulated with the following components: 350–400 mg / mL Ca(NO3)2·4H2O, 80–100 g / L sucrose, 15–20 mg / L boric acid, and 130–150 g / L PEG-4000.

8. The method for identifying the heat resistance of passion fruit according to claim 1, characterized in that, In step (6), H36 and MT were identified as highly heat-resistant varieties, H3, P5, P7 and Xiaji as moderately heat-resistant varieties, P1, Donghuimi and Yuanxiao as intermediate varieties, and Huangyou No. 2 and DN as heat-sensitive varieties.

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