Prediction method for infection success probability of pepper colletotrichum gloeosporioides and disease prevention method

Abstract

The invention discloses a method for predicting the infection success probability of pepper colletotrichum gloeosporioides and a method for preventing diseases, which are characterized in that a prediction model of the integral value of the contribution degree of the temperature and the infection success probability of the colletotrichum gloeosporioides under saturated humidity is established to predict a time node with the success probability of 50%, so that targeted pesticide spraying prevention and control are carried out. By adopting the prediction model provided by the invention, the pathogen infection success probability condition can be pre-judged, so that precise pesticide application is performed, the control effect can be improved, the pesticide spraying frequency can be reduced, the pesticide application cost can be reduced, and pesticide residues can be reduced.

Description

A method for predicting the success rate of anthracnose infection in peppers and a method for preventing disease development. Technical Field

[0001] This invention relates to the field of plant protection, specifically to a method for predicting the success probability of infection by *Anthracnose causal agent* in peppers and a method for preventing disease development. Background Technology

[0002] Anthracnose, the pathogen of peppers, belongs to the genus *Colletotrichum*, a significant group of plant pathogenic fungi worldwide. As one of the three major diseases affecting pepper production, anthracnose infection is more likely to occur in warm climates and moist soil conditions. The pathogen spreads to the pepper surface via wind and rain splashes, insects, or watering. It primarily damages ripening peppers, but also infects fruit stalks and leaves, impacting yield and quality, causing leaf drop, fruit rot, and seedling death. In severe cases, the disease incidence rate can reach over 50%, even leading to total crop failure. Control methods for pepper anthracnose include agricultural, biological, and chemical control. Chemical control has long been considered the most effective and simplest method for controlling pepper anthracnose. However, problems such as untimely application and overuse of pesticides are common in disease control, leading to pesticide residues, environmental pollution, and the potential for secondary diseases. Therefore, disease prediction and early warning technology has emerged. It enhances the predictability and planning of diseases, improves the economic, ecological and social benefits of prevention and control work, and makes it more economical, safe and effective. It is of strategic significance for improving the overall benefits of long-term integrated disease control. However, there are currently no reported prediction models for pepper anthracnose. Summary of the Invention

[0003] One objective of this invention is to provide a method for predicting the success rate of infection with anthracnose fungus in peppers. This method can predict the time point at which the success rate of infection with anthracnose fungus in peppers is 50%, thereby contributing to scientific prevention and control.

[0004] To achieve the above objectives, the present invention adopts the following technical solution:

[0005] A method for predicting the probability of successful infection by *Anthracnose causal agent* in chili peppers includes the following steps:

[0006] Step S1: Obtain field temperature and humidity information;

[0007] Step S2: Starting from the point of reaching saturation humidity, using hours as the time unit, according to the formula... Calculate the integral value V of temperature x on the probability of successful pathogen infection within different time units. In the formula, the value of temperature x is greater than or equal to 15 degrees Celsius and less than or equal to 35 degrees Celsius. When the temperature is less than 15 degrees Celsius or greater than 35 degrees Celsius, the integral value V is 0.

[0008] Step S3: During the saturated humidity duration described in step S2, the integral values ​​V corresponding to each time unit are added together to obtain the total integral value S=ΣV. When the total integral value S reaches 100, the probability of successful infection of pepper anthracnose fungus reaches 50% after a disease incubation period of 4 to 7 days.

[0009] Another objective of this invention is to provide a method for preventing the occurrence of anthracnose in peppers, which allows for precise application of pesticides by predicting the time point at which the pathogen is likely to successfully infect, thereby reducing the number of applications, saving costs, and lowering pesticide residues.

[0010] To achieve this objective, the present invention adopts the following technical solution:

[0011] A method for preventing the occurrence of anthracnose in chili peppers includes the following steps:

[0012] Step S1: Obtain field temperature and humidity information, including future temperature and humidity information;

[0013] Step S2: Starting from the point of reaching saturation humidity, using hours as the time unit, according to the formula... Calculate the integral value V of temperature x on the probability of successful pathogen infection within different time units. In the formula, the value of temperature x is greater than or equal to 15 degrees Celsius and less than or equal to 35 degrees Celsius. When the temperature is less than 15 degrees Celsius or greater than 35 degrees Celsius, the integral value V is 0.

[0014] Step S3: During the saturated humidity duration described in step S2, the integral values ​​V corresponding to each time unit are added together to obtain the total integral value S=ΣV. After the integral value S reaches 100, the probability of successful infection of pepper anthracnose fungus reaches 50% after a 4-7 day incubation period. Therefore, measures are taken to prevent pepper anthracnose before this time point.

[0015] Preferably, the temperature and humidity information in step S1 includes current temperature and humidity information as well as future temperature and humidity information; in step S3, the duration of saturated humidity includes a future time, and the total integral value S reaches 100 at a future time node, and the time difference between the time point when the preventive measures are taken and the future time node can meet the operation time of the preventive measures.

[0016] Preferably, the preventive measure is spraying pesticides to kill the anthracnose pathogen of peppers.

[0017] Preferably, in step S1, temperature and humidity sensors are set up in the field to obtain current temperature and humidity information, and future temperature and humidity information is obtained through weather forecasts.

[0018] Preferably, the pathogen used to prevent anthracnose in peppers is *Anthracnose spp.*

[0019] This invention establishes a predictive model based on the relationship between the infection status of pepper anthracnose under saturated humidity and temperature-time. It obtains integral values ​​over different temperature time intervals under saturated humidity, then sums these integral values. When the total integral value reaches 100, it represents a 50% probability of successful infection. Targeted control measures can be implemented before this time point. Compared to traditional periodic spraying prevention methods, this invention predicts the probability of successful infection and grasps the timing, enabling precise application of pesticides rather than indiscriminate application. This reduces the number of sprays, lowers application costs, and reduces pesticide residues. Attached Figure Description

[0020] Figure 1 shows a photograph of the anthracnose disease incidence in peppers at 10-25℃ after 48 hours of moisturization under saturated humidity.

[0021] Figure 2 shows a photograph of anthracnose disease in peppers at 30-40℃ after being kept moist at saturated humidity for 48 hours.

[0022] Figure 3 shows a photograph of the anthracnose disease in peppers during 0-12 hours of moisturization at 30℃ under saturated humidity.

[0023] Figure 4 shows a photograph of the anthracnose disease in peppers after being kept moist at 30℃ for 24-48 hours under saturated humidity.

[0024] Figure 5 shows the regression equation curves of the time and the probability of successful bacterial infection when moisturizing at 15℃ for 6-24 hours under saturated humidity.

[0025] Figure 6 shows the curve of the regression equation of the prediction model. Detailed Implementation

[0026] Example 1: Establishment of the Prediction Model

[0027] The prediction model is built using the following steps:

[0028] Step 1: Prepare the long pepper fruits

[0029] Select a sufficient quantity of healthy, fresh chili peppers, disinfect the surface of the chili peppers with 75% ethanol, rinse them three times with sterile water, and then air dry them naturally.

[0030] Step 2: Configure a moisturizing environment

[0031] Place the long pepper fruits in an enamel dish, then place 3-4 layers of sterile filter paper underneath, along with a water-resistant pad and 50mL of sterile water. Seal the enamel dish with plastic film to achieve saturated humidity.

[0032] Step 3: Inoculation and Moisturizing

[0033] Step 31: Make 5 shallow punctures on the surface of each chili pepper for inoculation.

[0034] Step 32: Add 50 μL of 1×10 to each inoculation site in the treatment group. 6 A CFU / mL suspension of conidia of *Anthracis chinensis* was prepared and weighed down with small pieces of absorbent cotton to prevent the suspension from slipping. For the control group, water was added to each inoculation point and weighed down with small pieces of absorbent cotton.

[0035] Step 33: For each treatment, use 3 long pepper fruits, repeat 3 times, and place them in the same enamel dish; for each control, use 3 long pepper fruits, repeat 3 times, and place them in the same enamel dish.

[0036] Step 34: Seal the enamel trays with plastic film and place them in incubators. Each incubator contains 6 enamel trays for the treatment groups and 1 enamel tray for the control group. The 6 enamel trays for the treatment groups correspond to experiments with 6h, 12h, 18h, 24h, 36h, and 48h of humidification, respectively. There are a total of 8 incubators, corresponding to experiments with incubation temperatures of 5℃, 10℃, 15℃, 20℃, 25℃, 30℃, 35℃, and 40℃, respectively. When the humidification time in each incubator reaches 6h, 12h, 18h, 24h, 36h, and 48h, take out all the pepper fruits from the enamel trays of one treatment group and dry them. Then put them back into the incubator for further incubation (the above temperature selection is based on a preliminary experiment on the germination dynamics of anthracnose conidia of pepper at different temperatures).

[0037] Step 4: Investigate the probability of successful pathogen infection.

[0038] Continuously observe and record the pathogen infection status. After an incubation period of 4-7 days, calculate the probability of successful pathogen infection. Assuming 15 inoculation sites (three peppers per treatment group), calculate the percentage of inoculation sites that developed disease after inoculation among the 15 sites. Then, calculate the average of the three treatment groups to obtain the probability of successful pathogen infection. The pathogen infection status after 48 hours of moisturization at different temperatures is shown in Figures 1 and 2, where nine peppers represent the three treatment groups and one pepper represents the water control. As an example, the pathogen infection status after moisturization at 30℃ for 0, 6, 12, 24, and 48 hours is shown in Figure 3, where 0 hours of moisturization means immediately drying after inoculation and placing the peppers in an incubator.

[0039] To determine the time when the success rate of pathogen infection reaches 50% under saturated humidity and various temperatures, the time intervals containing the 50% success rate were further subdivided based on the above experimental results. Hydration was maintained hourly, and the success rate of pathogen infection was observed and calculated. For example, at 15℃, hydration for 18-24 hours resulted in a success rate of 24-51%. The experiment was repeated, and the success rates of pathogen infection in each treatment group were investigated after hydration for 18h, 19h, 20h, 21h, 22h, 23h, and 24h. The results are as follows:

[0040]

[0041] To determine the precise moisturizing time when the probability of successful bacterial infection is 50%, a regression equation was fitted based on the data in Table 1, yielding y = 0.7396x. 2 - 26.143x + 253.83, R² = 0.9683, the equation curve is shown in Figure 5. In the equation, x is the humidification time at 15℃, and y is the corresponding probability of successful pathogen infection. Substituting y=50 into the equation, we get x=23.73h, meaning that when the humidification time is 23.37 hours, the probability of successful pathogen infection is 50%. Then, with the integral value of 50% at 23.37h being 100, we calculate the integral value for 1h as 100 / 23.73=4.21. Similarly, experiments were conducted using a similar method, and the regression equations and corresponding integral values ​​V for 1 hour at 20℃, 25℃, 30℃, and 35℃ were obtained (spores do not germinate at 10℃ and 40℃, therefore no infection occurs), as shown in Table 2.

[0042] Table 2. Regression equations and integral values ​​of pathogen infection success probability-moisture retention time at different temperatures.

[0043]

[0044] Then, based on the five relationship points between temperature (15-35℃) and V in Table 2, the regression equation was fitted again to obtain:

[0045]

[0046] R=0.99976

[0047] In the above formula, x represents the temperature, ranging from 15-35℃, and V represents the integral value of humidification for 1 hour at a certain temperature. The equation curve is shown in Figure 6. In practical applications, during the duration of saturated humidity, the integral value is calculated hourly based on the temperature (the average temperature within that hour) and then summed to obtain the total integral value. When the total integral value reaches 100, it indicates that the probability of successful pathogen infection has reached 50%, and spraying should be completed before this time point.

[0048] Example 2: Field Application Trial of Anthracnose Prediction Model for Pepper

[0049] From May to October 2025, a field control trial for anthracnose in chili peppers was conducted in Taocheng District, Hengshui City, Hebei Province. The main pathogen in this area is *Anthracnose spp.*, and the tested chili pepper variety was "Neihuang New Generation". Ridge planting was adopted with a ridge spacing of 1m, double rows per ridge, a row spacing of 30cm, and a plant spacing of 25cm. Watering and fertilization were carried out by drip irrigation under mulch. Water and fertilizer management, weeding, and pest control in the experimental field followed local conventional measures. An automatic weather station (equipped with temperature and humidity sensors) was installed in the field to collect air temperature and humidity data. The temperature and humidity data for weather forecasts came from a third-party weather forecast data service company.

[0050] The experiment included three treatments: regular spraying (spraying every 10 days for a total of 4 times, using 75% azoxystrobin·tebuconazole water-dispersible granules at a dosage of 12.5 g / mu), model-guided spraying (using the same pesticide as the regular spraying treatment, with spraying dates based on a pepper anthracnose prediction model), and a water control (Table 3). The experiment employed a randomized block design, with 4 replicates per treatment and a plot area of ​​20 m². The first spraying began in early August when sporadic anthracnose-infected fruit first appeared in the field. During the experiment, the "regular spraying treatment" was sprayed 4 times on August 1st, 11th, 21st, and 31st; the "model-guided spraying treatment" was guided by model predictions, using weather forecasts of temperature and humidity to calculate the integral values ​​for the current and future times, and then spraying was carried out in advance based on the time point when the total future integral value reached 100, with 3 sprays on August 5th, 17th, and 25th.

[0051] Disease surveys were conducted 14 days after the last application of the "regular spraying treatment" (September 14th). Five plants were surveyed per plot (five-point sampling method), and all fruits (including fallen fruits) were surveyed on each plant. The total number of fruits and the number of anthracnose-infected fruits were recorded. The disease rate of each plot was calculated by grade, and the relative control efficacy was calculated based on the disease rate of each treatment and the water control. Data were statistically analyzed using Duncan's multiple range test (DMRT). The survey data showed that the water control had the most severe disease, while the "regular spraying treatment" and "model-guided spraying treatment" had milder disease, showing significant differences from the water control. However, there was no significant difference between the "regular spraying treatment" and the "model-guided spraying treatment" (Table 3). However, the "regular spraying treatment" involved a total of 4 sprays, while the "model-guided spraying treatment" only involved 3 sprays. The results of this experiment show that using the pepper anthracnose prediction model to guide pesticide application for field pepper anthracnose control can reduce the number of pesticide applications compared to the traditional regular spraying method, while ensuring that the control efficacy is not reduced. This has a good effect on reducing production costs, reducing the risk of pesticide residues in peppers, and mitigating the risk of pesticide pollution to the ecological environment.

[0052] In the above experiment, the model predicts the spraying by incorporating the forecast values ​​of relative humidity and temperature from the weather forecast into the prediction model. This allows the model to determine the time point at which the probability of successful pathogen infection reaches 50% in the future, thus ensuring that spraying can be carried out before this time point, thereby playing a role in predicting and preventing the disease.

[0053] Table 3. Record of Field Control Trial for Anthracnose in Pepper

[0054]

Claims

1. A method for predicting the probability of successful infection by *Anthracnose* fungus in chili peppers, characterized in that... The process includes the following steps: Step S1: Obtain field temperature and humidity information; Step S2: Starting from the point of reaching saturation humidity, calculate the temperature and humidity using the formula, in hourly increments. Calculate the integral value V of temperature x on the success probability of pathogen infection within different time units. In the formula, the value of temperature x is greater than or equal to 15 degrees Celsius and less than or equal to 35 degrees Celsius. When the temperature is less than 15 degrees Celsius or greater than 35 degrees Celsius, the integral value V is 0. Step S3: During the saturated humidity duration mentioned in step S2, add the obtained integral values ​​V corresponding to each time unit to obtain the total integral value S=ΣV. When the total integral value S reaches 100, the success probability of pepper anthracnose infection reaches 50% after a disease incubation period of 4 to 7 days.

2. A method for preventing the occurrence of anthracnose in chili peppers, characterized in that... The process includes the following steps: Step S1: Obtain field temperature and humidity information, including future temperature and humidity information; Step S2: Starting from the point of reaching saturation humidity, calculate the temperature and humidity using the formula, in hourly increments. Calculate the integral value V of temperature x on the success probability of pathogen infection within different time units. In the formula, the value of temperature x is greater than or equal to 15 degrees Celsius and less than or equal to 35 degrees Celsius. When the temperature is less than 15 degrees Celsius or greater than 35 degrees Celsius, the integral value V is 0. Step S3: During the saturated humidity duration mentioned in step S2, add the obtained integral values ​​V corresponding to each time unit to obtain the total integral value S=ΣV. After the time node when the total integral value S reaches 100, the success probability of pepper anthracnose pathogen infection reaches 50% after a disease incubation period of 4 to 7 days. Then, take measures to prevent pepper anthracnose before this time node.

3. The method for preventing the occurrence of anthracnose in chili peppers as described in claim 2, characterized in that, The temperature and humidity information in step S1 includes current temperature and humidity information as well as future temperature and humidity information; in step S3, the duration of saturated humidity includes a future time, and the total integral value S reaches 100 at a future time node, and the time difference between the time point when the preventive measures are taken and the future time node can meet the operation time of the preventive measures.

4. The method for preventing the occurrence of anthracnose in chili peppers as described in claim 2, characterized in that, The preventive measure is to spray pesticides to kill the anthracnose pathogen affecting peppers.

5. The method for preventing the occurrence of anthracnose in chili peppers as described in claim 3, characterized in that, In step S1, temperature and humidity sensors are set up in the field to obtain current temperature and humidity information, and future temperature and humidity information is obtained through weather forecasts.

6. The method for preventing the occurrence of anthracnose in chili peppers as described in any one of claims 1-5, characterized in that, The pathogen causing anthracnose in chili peppers is *Anthracnose spp.*

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