CN113076523A - Early warning method, system and equipment for occurrence time of central diseased strain of potato late blight - Google Patents

Early warning method, system and equipment for occurrence time of central diseased strain of potato late blight Download PDF

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CN113076523A
CN113076523A CN202010004434.4A CN202010004434A CN113076523A CN 113076523 A CN113076523 A CN 113076523A CN 202010004434 A CN202010004434 A CN 202010004434A CN 113076523 A CN113076523 A CN 113076523A
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张斌
谈孝凤
张君
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Abstract

The application relates to a potato late blight central disease plant occurrence time early warning method, a system and equipment, and the method comprises the following steps: acquiring currently input variety information of the potatoes and first emergence time of the potatoes, and determining a reference curve for predicting the emergence time of central diseased plants according to the variety information; acquiring meteorological factor data of a planting area where potatoes are located every day from the first time of emergence, and generating a potato infection curve by adopting an early warning model based on the acquired meteorological factor data; the potato infection curve comprises a plurality of curves; when a reference curve appears in the generated potato infestation curve, acquiring meteorological information of a planting area within preset days from the appearance date of the reference curve, and calculating to obtain a corresponding infestation score according to the meteorological information within the preset days; and (5) according to the infection score, comparing with a reference curve, and acquiring and outputting the occurrence time of the central diseased plant. It can accurately master the occurrence time of central diseased plants of different potato varieties.

Description

Early warning method, system and equipment for occurrence time of central diseased strain of potato late blight
Technical Field
The disclosure relates to the field of monitoring of central diseased potato plants, in particular to a method, a system and equipment for early warning of occurrence time of central diseased potato plants with late blight.
Background
At present, a potato early warning model is mainly an artificial early warning technology based on certain meteorological condition rules. The model is based on the existence of susceptible varieties and pathogenic bacteria, the hourly relative humidity and the hourly relative temperature of the field are taken as the basis, and when any situation according with the model setting appears in the growing season, the spores of the late blight bacteria enter the leaves, namely the late blight bacteria enter the infection process. Once the average temperature of each day is obtained, a score can be obtained according to the data provided by the parameters of the Conce, and then the scores obtained each day are accumulated to 7 points, which indicates that an infection process is finished.
The occurrence time of the central disease strain of the potato late blight is influenced by variety and microclimate factors, the early warning value difference is relatively large, and the model has high accuracy on high-sensitivity varieties. However, potato planting varieties in China are many and complex, the potato planting varieties are generally divided into early, middle and late varieties, early maturing varieties are high-sensitive varieties, resistance of the middle and late maturing varieties has different differences, the differences are extremely large, and prediction of central disease plants of the early, middle and late varieties cannot be completely carried out by using the model.
Disclosure of Invention
In view of the above, the present disclosure provides a method for early warning of occurrence time of central diseased plants of potato late blight, which can accurately grasp occurrence time of central diseased plants of different potato varieties.
According to one aspect of the disclosure, a method for early warning the occurrence time of a central potato late blight disease strain is provided, which comprises the following steps:
acquiring currently input variety information of the potato and first emergence time of the potato, and determining a reference curve for predicting the occurrence time of central diseased plants according to the variety information;
acquiring meteorological factor data of a planting area where the potatoes are located every day from the first plant emergence time, and generating a potato infection curve by adopting an early warning model based on the acquired meteorological factor data; monitoring and acquiring the weather factor data every day at preset time intervals; the potato infestation curve comprises a plurality of lines;
when the reference curve appears in the generated potato infestation curve, acquiring meteorological information of the planting area within preset days from the appearance date of the reference curve, and calculating to obtain a corresponding infestation score according to the meteorological information within the preset days;
and contrasting the reference curve according to the infection score, and acquiring and outputting the occurrence time of the central diseased plant.
In a possible implementation manner, based on the obtained data of each meteorological factor, a potato infection curve is generated by adopting an early warning model, and the method comprises the following steps:
based on the meteorological factor data, calculating the times and degree of infection wetting period formation according to a preset first relation table; wherein the degree comprises at least one of light, medium, heavy, and extremely heavy;
the first relation table is used for characterizing the relation between the severity degree of the phytophthora infestans infection and the duration time of the wetting period and the average temperature of the wetting period;
determining the forming time of the infection wetting period corresponding to the variety information according to the forming times and degree of the infection wetting period;
after the forming time of the infection wetting period is determined, obtaining corresponding scores according to the average temperature of each day after the forming time of the infection wetting period and a second relation table, accumulating the scores and generating a corresponding potato infection curve according to the accumulated scores;
wherein the second relation table is used for representing the mapping relation between the scores and the average temperature.
In one possible implementation manner, determining a reference curve for predicting the occurrence time of the central disease plant according to the variety information includes: acquiring a corresponding reference curve from a prestored variety information and reference curve comparison table according to the variety information;
the variety information and reference curve comparison table comprises varieties of a plurality of potatoes and algebraic sum frequency information of reference curves corresponding to the varieties.
In one possible implementation, the meteorological factor data includes at least one of temperature, humidity, and rainfall;
the value of the preset interval time is 1 hour.
In a possible implementation manner, calculating a corresponding infection score according to the weather information in the preset number of days includes:
acquiring the meteorological information of the current time within the preset days, and obtaining the initial score of the meteorological information of the current time by referring to the second relation table; wherein the current time is any one day in the preset days;
and acquiring initial values corresponding to weather information of each day before the current time, and accumulating the acquired initial values to obtain the infection values.
In one possible implementation, the variety information includes at least one of a high susceptible variety potato, a susceptible variety potato, and a resistant variety potato;
the value of the preset days is between 3 days and 10 days.
In one possible implementation, the preset number of days takes a value of 5 days.
According to another aspect of the disclosure, the early warning system for the occurrence time of the central diseased plant of the potato late blight is further provided, and comprises a data input module, a reference curve determining module, a meteorological factor collecting module, an infection curve generating module, an infection score calculating module and a score comparison predicting module;
the data input module is configured to acquire variety information of a current potato and first emergence time of the potato;
the reference curve determining module is configured to determine a reference curve for predicting the occurrence time of the central diseased plant according to the variety information;
the meteorological factor acquisition module is configured to acquire meteorological factor data of a planting area where the potatoes are located every day from the first plant emergence time; wherein, the meteorological factor data of each day is monitored and acquired at preset time intervals;
the infestation curve generation module is configured to generate a potato infestation curve by adopting an early warning model based on the acquired meteorological factor data; wherein the potato infestation curve generated comprises a plurality of lines;
the infestation score calculation module is configured to obtain meteorological information of the planting area within a preset number of days from the appearance date of the reference curve when the reference curve appears in the generated potato infestation curve, and calculate corresponding infestation scores according to the meteorological information within the preset number of days;
and the score comparison prediction module is configured to compare the reference curve according to the infection score and acquire and output the occurrence time of the central diseased plant.
According to another aspect of this application, still provide a potato late blight central disease trunk emergence time early warning equipment, include:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to execute the executable instructions to implement any of the methods described above.
According to an aspect of the application, there is also provided a non-transitory computer readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement the method of any of the preceding.
According to the early warning method for the occurrence time of the central diseased plant of the potato late blight, the early warning model is adopted to generate a potato infection curve in real time according to different varieties of potatoes, meanwhile, a reference curve used for predicting the occurrence time of the central diseased plant is determined according to variety information of the potatoes, so that after the reference curve is formed in the process of generating the potato infection curve, weather information of preset days from the formation date of the reference curve is obtained, the corresponding infection score is calculated, and finally, the occurrence time of the central diseased plant of the variety of potatoes is obtained by comparing the infection score obtained through calculation with the reference curve. When the method is used for predicting the occurrence time of the central diseased plant, different infection curves generated in real time are adopted for different varieties, so that the prediction basis conditions are more in line with the actual conditions, and the accuracy of the prediction result is ensured. According to the early warning method for the occurrence time of the central diseased plant of the potato late blight, the occurrence time of the central diseased plant of different potato varieties can be accurately mastered, and an accurate basis is provided for the 1 st prevention work. According to multiple experimental observations, the actual field occurrence conditions of the experimental sites are re-emergence and are consistent with the prediction, and the accuracy rate reaches 100%. And the early warning of the recurrence trend provides a powerful prediction basis for technical departments in actual production, can timely carry out related prevention and control work according to early warning information, and lays a foundation for the prevention and control of the potato late blight.
Other features and aspects of the present disclosure will become apparent from the following detailed description of exemplary embodiments, which proceeds with reference to the accompanying drawings.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate exemplary embodiments, features, and aspects of the disclosure and, together with the description, serve to explain the principles of the disclosure.
FIG. 1 is a flowchart illustrating a method for warning the occurrence time of a central diseased potato plant with late blight according to the embodiment of the present application;
FIG. 2 is a data diagram showing a potato infection curve of a certain variety generated in real time in the early warning method for the occurrence time of central diseased potato late blight in the embodiment of the application;
FIG. 3 is a block diagram showing the structure of a potato late blight central disease occurrence time early warning system according to an embodiment of the present application;
fig. 4 shows a block diagram of the early warning device for the occurrence time of the central diseased potato late blight disease strain according to the embodiment of the present application.
Detailed Description
Various exemplary embodiments, features and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. In the drawings, like reference numbers can indicate functionally identical or similar elements. While the various aspects of the embodiments are presented in drawings, the drawings are not necessarily drawn to scale unless specifically indicated.
The word "exemplary" is used exclusively herein to mean "serving as an example, embodiment, or illustration. Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.
Furthermore, in the following detailed description, numerous specific details are set forth in order to provide a better understanding of the present disclosure. It will be understood by those skilled in the art that the present disclosure may be practiced without some of these specific details. In some instances, methods, means, elements and circuits that are well known to those skilled in the art have not been described in detail so as not to obscure the present disclosure.
Fig. 1 shows an early warning method for the occurrence time of a central diseased potato late blight strain according to an embodiment of the application. Referring to fig. 1, the method includes the steps of:
and S100, acquiring currently input variety information of the potatoes and emergence time of a first strain of the potatoes, and determining a reference curve for predicting the emergence time of the central diseased plant according to the variety information. Here, it should be noted that the variety information refers to the variety of potato. Generally, potato varieties can be broadly classified into high-sensory variety potatoes, sensory variety potatoes and resistant variety potatoes. The high-sensitive variety of potato corresponds to the potato with the Favorita variety, the medium-sensitive variety of potato corresponds to the potato with the Xuanshu No. 2 variety, and the resistant variety of potato corresponds to the potato with the green potato No. 9 variety. Here, it should be noted that the variety information of the potato is not limited to the above-mentioned varieties, but may include other varieties, and is not illustrated here.
The reference curve refers to the potato infestation curve used to predict the time of emergence of the central diseased plant. Different varieties of potatoes have different reference curves. That is, the number of generations and the number of infection curves used by different varieties of potatoes for predicting the occurrence time of central diseased plants are different. For example: the reference curve adopted by the potatoes of the Fiblet variety is a 3 rd generation 1 st infection curve, the reference curve adopted by the potatoes of the Xuan potato variety No. 2 is a 5 th generation 1 st infection curve, and the reference curve adopted by the potatoes of the green potato variety No. 9 is a 6 th generation 1 st infection curve.
Also, as will be understood by those skilled in the art, the time of emergence of the first potato strain in this application refers to the date the first potato strain emerged from the variety of potatoes planted.
And S200, acquiring weather factor data of the potato planting area from the first plant emergence time every day, and generating a potato infection curve by adopting an early warning model based on the acquired weather factor data. Here, it should be noted that the meteorological factor data includes at least one of temperature, humidity, and rainfall of the planting area. Meanwhile, the meteorological factor data of the planting area where the potatoes are located can be realized by arranging a field meteorological monitoring station in the planting area. The early warning model may be a carah model commonly used in the art. In a possible implementation mode, when the weather factor data of the potato planting area every day is obtained through monitoring of the field weather monitoring station, the monitoring can be carried out in real time, and the monitoring can also be carried out according to a preset time interval. When the monitoring is obtained according to the preset time interval, the value of the preset time interval can be 30min, and can also be set to 1 hour. The method comprises the steps of acquiring meteorological factor data of a planting area every day by taking hours as a unit, and generating a potato infestation curve through a carah model according to the acquired meteorological factor data. Referring to FIG. 2, a plurality of potato infestation curves are generated, each of which corresponds to a different number of infested wet period formations. Wherein, the infection curves in the same infection wetting period can be named in a mode of different times in the same generation. The infection curves at different infection wetting periods can be named in different generations. That is, the infections occurring during the same generation may be named in the manner of "1 st, 2 nd, 3 rd of generation 1, … …". The infections occurring during the different generations may then be named in the manner "generations 1, 2, 3, … …".
And S300, when a reference curve appears in the generated potato infestation curve, acquiring meteorological information of a planting area within preset days from the appearance date of the reference curve, and calculating to obtain a corresponding infestation score according to the meteorological information within the preset days. In other words, in the process of generating the potato infection curve in real time based on the acquired meteorological factor data, the reference curve is formed at the moment when the generation number and the times of the generated potato infection curve are the generation number and the times of the determined reference curve by monitoring the generation number and the times of the generated potato infection curve in real time. The meteorological information of the planting area within the preset days from the formation date of the reference curve can be obtained, and the corresponding infection score is calculated according to the obtained meteorological information. Then, in step S400, the occurrence time of the central disease is obtained and outputted according to the calculated regressive score compared with the formed reference curve.
Here, it should also be noted that in the method for early warning of the occurrence time of a central diseased plant of potato late blight according to the embodiment of the present disclosure, the acquired weather information is mainly temperature information at a planting area, and weather information (temperature) of a current area within a preset number of days can be acquired through weather forecast.
Therefore, according to the early warning method for the occurrence time of the central diseased plant of the potato late blight, the early warning model is adopted to generate a potato infection curve in real time according to different varieties of potatoes, meanwhile, a reference curve used for predicting the occurrence time of the central diseased plant is determined according to variety information of the potatoes, so that after the reference curve is formed in the process of generating the potato infection curve, the meteorological information of preset days from the formation date of the reference curve is obtained, the corresponding infection score is calculated, and finally the occurrence time of the central diseased plant of the variety of potatoes is obtained by contrasting the infection score obtained through calculation with the reference curve. When the method is used for predicting the occurrence time of the central diseased plant, different infection curves generated in real time are adopted for different varieties, so that the prediction basis conditions are more in line with the actual conditions, and the accuracy of the prediction result is ensured. According to the early warning method for the occurrence time of the central diseased plant of the potato late blight, the occurrence time of the central diseased plant of different potato varieties can be accurately mastered, and an accurate basis is provided for the 1 st prevention work. According to multiple experimental observations, the actual field occurrence conditions of the experimental sites are re-emergence and are consistent with the prediction, and the accuracy rate reaches 100%. And the early warning of the recurrence trend provides a powerful prediction basis for technical departments in actual production, can timely carry out related prevention and control work according to early warning information, and lays a foundation for the prevention and control of the potato late blight.
In a possible implementation manner, when the potato infection curve is generated by adopting the early warning model based on the acquired meteorological factor data, the adopted early warning model is a carah model. In generating a potato infestation curve using the carah model, this can be achieved in the following manner.
Namely, the number and degree of infection wetting period formation (wherein, the degree comprises at least one of light, medium, heavy and extremely heavy) are calculated according to a preset first relation table based on the acquired meteorological factor data of each day from the first emergence time of the potato strain, and the first relation table is used for representing the relation between the severity degree of infection of the phytophthora infestans and the duration time of the wetting period and the average temperature of the wetting period. See table 1 for an example of a first relationship table in an embodiment of the present application.
TABLE 1 first relation table
Figure BDA0002354724210000081
Here, it is also noted that the wet period is continuously calculated if the wet period is interrupted for not more than 3 hours. If the interruption time exceeds 4 hours, two different wetting periods should be counted. Meanwhile, it is also noted that if the infection wetting period lasts more than 48 hours, 1 infection wetting period is formed every 24 hours, and the infection degree is extremely heavy.
TABLE 2 second relation table
Temperature range Score of
<8℃ 0
8.1-12℃ 0.75
12.1-16.5℃ 1
16.6-20℃ 1.5
>20.1 1
And then, determining the forming time of the infection wetting period corresponding to the variety information according to the forming times and degree of the infection wetting period. And after the forming time of the infection wetting period is determined, obtaining corresponding scores according to the average temperature of each day after the forming time of the infection wetting period and a second relation table, accumulating the scores and generating a corresponding infection curve according to the accumulated scores (wherein the second relation table is used for representing the mapping relation between the scores and the average temperature). See table 2 for an example of a second relationship table in an embodiment of the present application.
Wherein, weather factor data of each day from the first emergence time of the potato can be acquired by an automatic field weather station. A field automatic weather station is arranged in a potato planting area, and weather factor data such as temperature, humidity, rainfall and the like in the area are collected. Wherein the frequency of acquisition (i.e., the preset time interval) is once per hour of acquisition.
Because the phytophthora infestans of the potatoes infects the potatoes in different degrees under different weather conditions, the frequency and the degree of the infection wet period are determined by acquiring the daily meteorological factor data of the potatoes from the first seedling emergence time, and the infection curve of the next step is generated according to the frequency and the degree of the infection wet period.
After a plurality of infection curves of the potatoes with different variety information are generated in any one mode, whether the generation number and the times of the generated potato curves reach the generation number and the times of the determined reference curves or not can be monitored in real time. I.e. monitoring the resulting potato curve for the presence of a reference curve. And after an infestation curve with the same algebra and times as those of the reference curve appears in the generated potato infestation curve, the reference curve is formed at the moment, so that the occurrence time of the central diseased plant can be predicted by acquiring the meteorological information of the planting area within a preset number of days from the formation date of the reference curve and combining the acquired meteorological information with the reference curve.
Here, it should be noted that, when determining the reference curve according to the variety information, the reference curve may be obtained from a comparison table of the pre-stored variety information and the reference curve according to the variety information. That is, by storing a look-up table including the number of generations and the number of times of reference curves corresponding to a variety and a variety of a potato in advance, the reference curve used by a potato of the variety information can be determined by adding the currently input variety information to the number of times of generations and the number of times of reference curves corresponding to the variety information recorded in the look-up table. The determination mode is simple and easy to realize, and is beneficial to real-time updating and maintenance of data.
In addition, when the reference curve used by the currently input variety information is realized in the above manner, it is necessary to determine the most suitable infection curve (i.e., the reference curve) corresponding to each variety through actual examination in advance.
In one possible implementation, the most suitable infection curve corresponding to the infection curve is determined by actual examination in advance, and the determination can be realized by a parameter confidence interval calculation method.
Specifically, a lower confidence limit and an upper confidence limit are obtained according to the occurrence frequency of the central diseased potato plant in the grading interval of each infection curve, which is obtained within the preset observation frequency. Then, according to an interval formed by the lower confidence limit and the upper confidence limit, a reference infection curve is determined from the plurality of infection curves.
It should be noted that the preset number of observation times may be 23. Furthermore, reference infection curves for different varieties of potatoes can be determined in the manner described above.
For example, by observing feurokitt (i.e., one of the potato varieties) 23 times, the occurrence of the central diseased plant corresponded to scores ranging from 2 to 7 scores for the 1 st infection of the 3 rd generation and 3 scores ranging from 1 to 2 scores for the 1 st infection of the 4 th generation. Using a parameter confidence interval calculation method to obtain a confidence lower limit (L)1) At 3.3, upper confidence limit (L)2) Was 3.7. Namely, when alpha is 0.05, in the 3.3-3.7 interval, 95% of intervals can cover the parameter mu, so that the main early warning parameter of the occurrence time of the central disease plant is determined to be 3-generation 1 st infection within 3-7 minutes; xuan potato No. 2 lower limit of confidence (L)1) Is 5.0 with an upper confidence limit of (L)2)5.7, in the interval of 5.0-5.7, 95% of the interval can cover the parameter mu, so that the main early warning parameter of the occurrence time of the central diseased plant is established between 0 and 7 minutes of the 1 st infection of the 5 generations; sweet potato No. 9 lower limit(L1) Is 6.0 with an upper confidence limit of (L)2)6.7, in the interval of 6.0-6.7, 95% of the interval can cover the parameter mu, so that the main early warning parameter of the occurrence time of the central diseased plant is established between 0 and 7 minutes of the 1 st infection of the 6 generations.
Therefore, the occurrence times of the central diseased potato plants in the same infection generation are divided together by detecting and counting the occurrence times of the central diseased potato plants in each infection curve, the occurrence times are recorded, the minimum infection score corresponding to the occurrence of the central diseased plants in the same infection generation is taken as the lower limit, the maximum infection score corresponding to the occurrence of the central diseased plants in the same infection generation is taken as the upper limit, and the confidence upper limit and the confidence lower limit are calculated. And obtaining the number of infection generations of the central diseased potato plant and the infection score interval of the central diseased potato plant according to the upper confidence limit and the lower confidence limit.
After the reference curve is determined in any one of the above manners and is formed in the process of generating the potato infection curve in real time, the corresponding infection score can be calculated according to the meteorological information within the preset number of days from the formation date of the reference curve, and then the occurrence time of the central diseased plant corresponding to the variety information is obtained and output according to the infection score by contrasting the determined reference infection curve.
In a possible implementation manner, when the corresponding infection score is calculated according to the weather information within the preset number of days, the weather information of the current time within the preset number of days is firstly obtained, and the initial score of the weather information of the current time is obtained by referring to the second relation table. Here, it should be noted that the current time is any one of preset days. The value of the preset number of days can be set to any value between 3 days and 10 days. Such as: the value of the preset number of days may be set to 5 days.
And then, acquiring initial scores corresponding to the weather information of each day before the current time, and accumulating the acquired initial scores to obtain the infection scores. Here, it should be noted that the day scores are zero scores after the secondary infective wetting period is established. Here, it should be noted that the current day here refers to the day before the first day of the preset number of days. And obtaining a score by comparing the average temperature of each day in the preset days with the second relation table, and then accumulating the score obtained on the current day and the score obtained on the previous days.
For example, taking Xuan potato No. 2 as an example, the reference infection curve of the variety is the 5 th generation 1 st infection curve. The preset days are five days, 10 ℃ for the first day, 13 ℃ for the second day, 14 ℃ for the third day, 15 ℃ for the fourth day and 16 ℃ for the fifth day. Then, referring to the second relation table, the score was 0.75 on the first day, 1 on the second day, 1 on the third day, 1 on the fourth day, and 1 on the fifth day. Correspondingly, the daily score is zero since the infection score is zero after the wetting period of the infection is formed, the infection score on the first day is 0.75, the infection score on the second day is 1+ 0.75-1.75, the infection score on the third day is 1+1+ 0.75-2.75, the infection score on the fourth day is 1+1+1+ 0.75-3.75, and the infection score on the fifth day is 1+1+1+1+ 0.75-4.75. After the five days of predicted scores are obtained, the obtained predicted scores (i.e., 4.75 points) are compared with the determined reference infection curve, and the date corresponding to the score in the determined reference infection curve is used as the predicted occurrence time of the central diseased plant of the potato variety.
Furthermore, in a possible implementation manner, when the current potato is judged to meet the early warning condition, the method further comprises the step of pushing warning information to the mobile terminal. Here, it will be understood by those skilled in the art that the mobile terminal may be any electronic device, such as: various devices such as mobile phones, tablet computers, desktop computers, alarms and the like. And is not particularly limited herein.
In order to more clearly illustrate the process of the method for warning the occurrence time of the central diseased plant of potato late blight according to the embodiment of the present disclosure, an embodiment is taken as example 1 to be more clearly described below.
Example 1:
representative 43 points (times) are selected in Guizhou province, main cultivars of the Guizhou province are observed for 62 times in an accumulated mode, and main cultivars of the Guizhou province, such as Fei Urita, Zhongshu No. 3, Weiyu No. 5, Xuanyao No. 2, Heimeren, Heijingang and the like, are observed and researched mainly by establishing a field cultivar observation garden. And (3) beginning from the generation of the infection wetting period of the 2 nd generation 1 st stage displayed by the system, surveying every two days in a central diseased plant observation nursery, adopting a step-down mode to survey, finding suspected diseased plants, bringing back to a laboratory for microscopic examination, and determining whether the potato late blight exists. And after the central diseased plant appears, recording the appearance time, and determining the corresponding infection generation and the score thereof by comparing the appearance time of the central diseased plant of each variety with a system.
The representative 43 points (times) are selected in Guizhou province, 62 times of observation are accumulated on main cultivars of the Guizhou province, the difference of the resistance of different potato varieties to the late blight is an important factor causing system errors, in order to solve the error problem, an 'indication cultivar' method is provided in the research, namely, among the main cultivars of the Guizhou province, representative cultivars with different resistance levels are selected as indication cultivars, the system parameters corresponding to the resistance are determined, cultivars without significant difference with the cultivars resistance are classified into one class, and the indication cultivar parameters are used for carrying out guidance, prevention and control work. Through observation, the Figurita is observed for 23 times, the corresponding system score of the central diseased plant is 20 times between 2 and 7 scores of 1 st infection of the 3 rd generation, and 3 times between 1 and 2 scores of 1 st infection of the 4 th generation, and a parameter confidence interval calculation method is used to obtain the lower confidence limit (L)1) Is 3.3 with an upper confidence limit of (L)2)3.7, namely alpha is 0.05, and in the interval of 3.3-3.7, 95% of intervals can cover the parameter mu, so that the main early warning parameter of the occurrence time of the central diseased plant is determined to be 3-generation 1 st infection within 3-7 minutes; xuan potato No. 2 lower limit of confidence (L)1) Is 5.0 with an upper confidence limit of (L)2)5.7, in the interval of 5.0-5.7, 95% of the interval can cover the parameter mu, so that the main early warning parameter of the occurrence time of the central diseased plant is established between 0 and 7 minutes of the 1 st infection of the 5 generations; sweet potato No. 9 lower limit of confidence (L)1) Is 6.0 with an upper confidence limit of (L)2)6.7, in the interval of 6.0-6.7, 95% of the interval can cover the parameter mu, so that the main early warning parameter of the occurrence time of the central diseased plant is established between 0 and 7 minutes of the 1 st infection of the 6 generations. That is to say that the first and second electrodes,
indication variety: figurita, after the 1 st infection curve of the 3 rd generation is generated, according to the temperature data provided by the weather forecast within 5d in the future, the infection score is calculated, and the occurrence time of the central disease plant is estimated to be within the 3-7 minutes of the 1 st infection score of the 3 rd generation.
Indication variety: and (3) after the Xuan potato No. 2 and the 1 st infection curve of the 5 th generation are generated, calculating according to temperature data provided by weather forecast within 5d in the future and contrasting infection scores, and predicting the occurrence time of central diseased plants in the 1 st infection parameter score of the 5 th generation by 0-7 minutes.
Indication variety: after the sweet potato No. 9 and the No. 6 infection curve of the 1 st generation are generated, according to temperature data provided by weather forecast within 5d in the future, the infection score is calculated, and the occurrence time of the central diseased plant is estimated to be within the period of 0-7 minutes of the No. 1 infection parameter score of the No. 5 generation.
The method for early warning the occurrence time of the central diseased potato strain for the late blight is based on any one of the methods, and the early warning device for the occurrence time of the central diseased potato strain for the late blight is further provided by the disclosure. Because the working principle of the early warning device for the occurrence time of the central diseased potato strain of the late blight provided by the application is the same as or similar to the principle of the early warning method for the occurrence time of the central diseased potato strain of the late blight provided by the application, repeated parts are not repeated.
Referring to fig. 3, the early warning system 100 for the occurrence time of a central diseased plant of potato late blight provided by the present application includes a data input module 110, a reference curve determination module 120, a meteorological factor acquisition module 130, an infection curve generation module 140, an infection score calculation module 150, and a score comparison prediction module 160. The data input module 110 is configured to obtain the variety information of the current potato and the first time of emergence of the potato. And a reference curve determining module 120 configured to determine a reference curve for predicting the occurrence time of the central disease according to the breed information. The meteorological factor acquisition module 130 is configured to acquire meteorological factor data of each day from the first plant emergence time in a planting area where potatoes are located; wherein, the meteorological factor data of each day is monitored and obtained at preset time intervals. The infestation curve generating module 140 is configured to generate a potato infestation curve by adopting an early warning model based on the acquired meteorological factor data; wherein the resulting potato infestation curve comprises a plurality of strips. And the infestation score calculation module 150 is configured to obtain meteorological information of a planting area within preset days from the appearance date of the reference curve when the reference curve appears in the generated potato infestation curve, and calculate corresponding infestation scores according to the meteorological information within the preset days. And the score comparison prediction module 160 is configured to compare the reference curve according to the infection score and acquire and output the occurrence time of the central diseased plant.
Still further, according to another aspect of the present disclosure, there is also provided a device 200 for early warning of occurrence time of a central diseased potato strain for late blight. Referring to fig. 4, the early warning apparatus 200 for the occurrence time of a central diseased plant of potato late blight according to the embodiment of the present disclosure includes a processor 210 and a memory 220 for storing executable instructions of the processor 210. Wherein the processor 210 is configured to execute the executable instructions to implement any one of the methods for early warning the occurrence time of the central disease strain of potato late blight.
Here, it should be noted that the number of the processors 210 may be one or more. Meanwhile, the early warning apparatus 200 for the occurrence time of the central diseased potato plant of late blight according to the embodiment of the present disclosure may further include an input device 230 and an output device 240. The processor 210, the memory 220, the input device 230, and the output device 240 may be connected via a bus, or may be connected via other methods, which is not limited in detail herein.
The memory 220, which is a computer-readable storage medium, may be used to store software programs, computer-executable programs, and various modules, such as: the program or the module corresponding to the early warning method for the occurrence time of the central diseased plant of the potato late blight in the embodiment of the disclosure. The processor 210 executes various functional applications and data processing of the early warning device 200 for the occurrence time of the potato late blight central disease by operating software programs or modules stored in the memory 220.
The input device 230 may be used to receive an input number or signal. Wherein the signal may be a key signal generated in connection with user settings and function control of the device/terminal/server. The output device 240 may include a display device such as a display screen.
According to another aspect of the present disclosure, there is also provided a non-transitory computer readable storage medium, on which computer program instructions are stored, wherein the computer program instructions, when executed by the processor 210, implement any of the aforementioned methods for early warning of occurrence time of potato late blight central disease strains.
Having described embodiments of the present disclosure, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terms used herein were chosen in order to best explain the principles of the embodiments, the practical application, or technical improvements to the techniques in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.

Claims (10)

1. A potato late blight central disease plant occurrence time early warning method is characterized by comprising the following steps: the method comprises the following steps:
acquiring currently input variety information of the potato and first emergence time of the potato, and determining a reference curve for predicting the occurrence time of central diseased plants according to the variety information;
acquiring meteorological factor data of a planting area where the potatoes are located every day from the first plant emergence time, and generating a potato infection curve by adopting an early warning model based on the acquired meteorological factor data; monitoring and acquiring the weather factor data every day at preset time intervals; the potato infestation curve comprises a plurality of lines;
when the reference curve appears in the generated potato infestation curve, acquiring meteorological information of the planting area within preset days from the appearance date of the reference curve, and calculating to obtain a corresponding infestation score according to the meteorological information within the preset days;
and contrasting the reference curve according to the infection score, and acquiring and outputting the occurrence time of the central diseased plant.
2. The early warning method for the occurrence time of the central diseased potato late blight strain according to claim 1, wherein the early warning model is used for generating a potato infection curve based on the acquired meteorological factor data, and the method comprises the following steps:
based on the meteorological factor data, calculating the times and degree of infection wetting period formation according to a preset first relation table; wherein the degree comprises at least one of light, medium, heavy, and extremely heavy;
the first relation table is used for characterizing the relation between the severity degree of the phytophthora infestans infection and the duration time of the wetting period and the average temperature of the wetting period;
determining the forming time of the infection wetting period corresponding to the variety information according to the forming times and degree of the infection wetting period;
after the forming time of the infection wetting period is determined, obtaining corresponding scores according to the average temperature of each day after the forming time of the infection wetting period and a second relation table, accumulating the scores and generating a corresponding potato infection curve according to the accumulated scores;
wherein the second relation table is used for representing the mapping relation between the scores and the average temperature.
3. The early warning method for the occurrence time of the central diseased potato late blight strain according to claim 1, wherein the step of determining a reference curve for predicting the occurrence time of the central diseased potato strain according to the variety information comprises the following steps: acquiring a corresponding reference curve from a prestored variety information and reference curve comparison table according to the variety information;
the variety information and reference curve comparison table comprises varieties of a plurality of potatoes and algebraic sum frequency information of reference curves corresponding to the varieties.
4. The early warning method for the occurrence time of the central diseased plant of potato late blight according to claim 1, wherein the meteorological factor data comprises at least one of temperature, humidity and rainfall;
the value of the preset interval time is 1 hour.
5. The early warning method for the occurrence time of central diseased potato late blight strains according to claim 2, wherein the corresponding infection score is calculated according to the meteorological information within the preset number of days, and comprises the following steps:
acquiring the meteorological information of the current time within the preset days, and obtaining the initial score of the meteorological information of the current time by referring to the second relation table; wherein the current time is any one day in the preset days;
and acquiring initial values corresponding to weather information of each day before the current time, and accumulating the acquired initial values to obtain the infection values.
6. The method for warning the occurrence time of central diseased potato strains with late blight according to any one of claims 1 to 5, wherein the variety information comprises at least one of a high-susceptible variety of potatoes, a sensitive variety of potatoes and a resistant variety of potatoes;
the value of the preset days is between 3 days and 10 days.
7. The early warning method for the occurrence time of central diseased potato late blight according to claim 6, wherein the preset number of days is 5 days.
8. The utility model provides a potato late blight central disease trunk emergence time early warning system which characterized in that: the system comprises a data input module, a reference curve determining module, a meteorological factor collecting module, an infection curve generating module, an infection score calculating module and a score comparison and prediction module;
the data input module is configured to acquire variety information of a current potato and first emergence time of the potato;
the reference curve determining module is configured to determine a reference curve for predicting the occurrence time of the central diseased plant according to the variety information;
the meteorological factor acquisition module is configured to acquire meteorological factor data of a planting area where the potatoes are located every day from the first plant emergence time; wherein, the meteorological factor data of each day is monitored and acquired at preset time intervals;
the infestation curve generation module is configured to generate a potato infestation curve by adopting an early warning model based on the acquired meteorological factor data; wherein the potato infestation curve generated comprises a plurality of lines;
the infestation score calculation module is configured to obtain meteorological information of the planting area within a preset number of days from the appearance date of the reference curve when the reference curve appears in the generated potato infestation curve, and calculate corresponding infestation scores according to the meteorological information within the preset number of days;
and the score comparison prediction module is configured to compare the reference curve according to the infection score and acquire and output the occurrence time of the central diseased plant.
9. The utility model provides a potato late blight central disease trunk emergence time early warning equipment which characterized in that includes:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to carry out the executable instructions when implementing the method of any one of claims 1 to 7.
10. A non-transitory computer readable storage medium having computer program instructions stored thereon, wherein the computer program instructions, when executed by a processor, implement the method of any of claims 1 to 7.
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