A data-driven method for constructing a rice low temperature injury model

Abstract

The present application relates to the technical field of rice low temperature chilling injury model construction, and specifically to a data-driven rice low temperature chilling injury model construction method, the method comprising: obtaining rice growth and development period data and daily average temperature data in preset historical years; determining the daily heat index in combination with the daily average temperature data and rice growth and development period data; analyzing the degree and number of consecutive days that the daily heat index is lower than the average heat index level in adjacent preset years, and combining the maximum value of the degree in preset standard sample data in different regions to construct the low temperature comprehensive intensity index of each agricultural meteorological station in different regions; using the low temperature comprehensive intensity index distribution characteristics of all agricultural meteorological stations obtained under different chilling injury levels in different regions to construct a rice low temperature chilling injury model. The present application aims to improve the accuracy and stability of the evaluation results of the rice low temperature chilling injury model.

Description

Technical Field

[0001] The present application relates to the technical field of rice low temperature chilling injury model construction, and in particular to a method for constructing a rice low temperature chilling injury model based on data-driven. Background Art

[0002] As climate change intensifies, the frequency and intensity of extreme weather events may increase. As crop planting boundaries move northward and eastward, regional cold damage increases, and drought intensifies, the cooling effect caused by irrigation will increase the occurrence of low temperature cold damage. Low temperature is one of the important environmental factors affecting rice growth and yield. In the existing technology, historical temperature data and rice growth and development data are usually used to identify whether rice has been affected by cold damage.

[0003] However, this method does not fully take into account the impact of the severity of extreme weather and the long-term persistence of extreme weather on the growth and development of rice, and does not combine the impact of different cold damage levels on the construction of the rice low temperature cold damage model, as well as the differences in the overall regional distribution characteristics of each region, resulting in low accuracy and stability in the evaluation results of the rice low temperature cold damage model. Summary of the invention

[0004] In order to solve the above technical problems, the present application provides a data-driven method for constructing a rice low temperature chilling injury model to solve the existing problems.

[0005] The data-driven rice low temperature chilling injury model construction method of the present application adopts the following technical solutions:

[0006] An embodiment of the present application provides a method for constructing a rice low temperature chilling injury model based on data-driven, the method comprising the following steps:

[0007] Obtain rice growth and development period data of multiple agricultural meteorological stations in preset historical years, and daily average temperature data of meteorological stations in the corresponding historical years in the corresponding areas where the agricultural meteorological stations are located;

[0008] Combine the daily average temperature data and rice growth and development period data to determine the daily heat index;

[0009] For each agricultural meteorological station during the rice growth and development period in the preset historical years, the degree to which the daily heat index is lower than the average heat index level in the adjacent preset years is analyzed and recorded as a negative cumulative value. Based on the negative cumulative value and the number of consecutive days when the daily heat index is lower than the average heat index level in the adjacent preset years, combined with the maximum negative cumulative value in the preset standard sample data of different regions, the low temperature comprehensive intensity index of each agricultural meteorological station in different regions is constructed;

[0010] A rice low temperature chilling damage model was constructed using the distribution characteristics of the low temperature comprehensive intensity index of all agricultural meteorological stations obtained under the division of different chilling damage levels in the preset standard sample data in different regions.

[0011] Preferably, the rice growth and development stage data are the upper limit temperature, lower limit temperature and suitable temperature of rice at different growth and development stages.

[0012] Preferably, the method for determining the daily calorie index includes:

[0013] Obtain the lower limit temperature, upper limit temperature and suitable temperature required for rice growth and development in the rice growth and development period data;

[0014] The calculation formula for the daily calorie index is: Where: S(i) is the heat index of the i-th day, T is the average daily temperature of the i-th day, T1, T2, and T0 are the lower limit temperature, upper limit temperature, and suitable temperature required for rice growth and development, respectively;

[0015] When T≤T1 or T≥T2, let S(i)=0, and when T=T0, let S(i)=1.

[0016] Preferably, the method for constructing the low temperature comprehensive intensity index of each agricultural meteorological station in different regions includes:

[0017] The negative cumulative value is determined based on the extent to which all heat indices during the rice growth and development period in the preset historical years at each agricultural meteorological station are lower than the average heat index level in the adjacent preset years;

[0018] Based on the number of consecutive days during the rice growth and development period in the preset historical years at each agricultural meteorological station, when all heat indices were lower than the average heat index in the adjacent preset years, the negative cumulative consecutive days were determined;

[0019] Among the preset standard sample data in different regions, the maximum negative cumulative value is combined to determine the comprehensive intensity index of low temperature for each agricultural meteorological station in different regions.

[0020] Preferably, the negative cumulative value is calculated as follows:

[0021] Calculate the average heat index for each day within the preset year;

[0022] Calculate the difference between the daily heat index and the average heat index;

[0023] The cumulative sum of all difference results less than 0 during the rice growth and development period in the preset historical years at each agricultural meteorological station is counted as the negative cumulative value.

[0024] Preferably, the negative cumulative consecutive number of days is the maximum consecutive number of days that all heat indices are lower than the average heat index level in adjacent preset years.

[0025] Preferably, the preset standard sample data in different regions include three low temperature damage levels: mild, moderate and severe.

[0026] Preferably, the preset standard sample data in different regions are combined with the maximum value of the negative cumulative value to determine the low temperature comprehensive intensity index of each agricultural meteorological station in different regions, including:

[0027] The expression of the low temperature comprehensive intensity index for the dth region at the i-th agricultural meteorological station is:

[0028]

[0029] In the formula, is the low temperature comprehensive intensity index of the ith agricultural meteorological station in the dth region, A is the preset amplification factor, are the first preset weight and the second preset weight of the dth region respectively, is the normalized value of the negative cumulative value of the i-th agricultural meteorological station in the d-th region, is the normalized value of the negative cumulative consecutive days of the i-th agricultural meteorological station in the d-th region, M d It is the maximum value of all negative cumulative values ​​of the dth region in the preset standard sample data.

[0030] Preferably, the process of constructing the rice low temperature chilling injury model includes:

[0031] On the basis of the preset standard sample data, the low temperature comprehensive intensity index of each agricultural meteorological station is calculated based on the division of different regions and different chilling damage levels to obtain several groups of sample sequences, wherein each group of sample sequences is composed of the low temperature comprehensive intensity index of all agricultural meteorological stations under the chilling damage level of the same preset standard sample data in the same region;

[0032] For each set of sample series, calculate the accuracy between the agricultural meteorological stations within the range divided by the minimum and maximum values ​​of all low temperature comprehensive intensity indices corresponding to the chilling damage level and the agricultural meteorological stations under the corresponding chilling damage level of the preset standard sample data;

[0033] The accuracy of all sample series calculated in different regions is divided in descending order to obtain the value range of low temperature comprehensive intensity index for different chilling damage levels;

[0034] Among them, the value range of the low temperature comprehensive intensity index for the re-determined chilling damage level with low accuracy will delete the overlapping part with the value range of the low temperature comprehensive intensity index for the re-determined chilling damage level with high accuracy, and add the range not included in the value range of the low temperature comprehensive intensity index for the re-determined adjacent chilling damage level with high accuracy; the value range of the low temperature comprehensive intensity index composed of the lower bound of the value range of the low temperature comprehensive intensity index greater than or equal to 0 and less than the mild chilling damage level is taken as the no chilling damage level;

[0035] The range of values ​​of the low temperature comprehensive intensity index under all the re-determined levels of no chilling damage, mild chilling damage, moderate chilling damage and severe chilling damage in each region was used to construct a rice chilling damage model for each region.

[0036] Preferably, after constructing the rice low temperature chilling damage model, the method further includes verifying the rice low temperature chilling damage model point by point based on historical disaster data and based on the spatial distribution of typical chilling damage years, and the historical disaster data are used for verification.

[0037] This application has at least the following beneficial effects:

[0038] The present application constructs a daily heat index in combination with historical temperature data and rice growth and development period data, which is used to analyze the heat conditions required for daily rice growth and development, thereby reflecting the growth and development status of rice; by combining the severity and duration of low temperature and chilling weather, different weights are set for it, and the low temperature comprehensive intensity index in different regions is analyzed, so as to more accurately evaluate the severity of chilling damage in the area where each agricultural meteorological station is located; by utilizing the distribution characteristics of the low temperature comprehensive intensity index of all agricultural meteorological stations obtained under the division of different regions, a rice low temperature and chilling damage model is constructed from the overall regional distribution level of each region, thereby improving the accuracy and stability of the evaluation results of the rice low temperature and chilling damage model. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0040] Figure 1 A flow chart of a method for constructing a rice low temperature chilling injury model based on data drive provided in one embodiment of the present application;

[0041] Figure 2 A flow chart of a method for calculating a negative cumulative value provided in one embodiment of the present application;

[0042] Figure 3 A flow chart of a method for constructing a low temperature comprehensive intensity index for each agricultural meteorological station in different regions provided in one embodiment of the present application;

[0043] Figure 4 A schematic diagram of a confusion matrix for fitting the chilling damage level and sample level of the low temperature comprehensive intensity index provided in one embodiment of the present application. DETAILED DESCRIPTION

[0044] In order to further explain the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the data-driven rice low temperature chilling injury model construction method proposed in the present application, its specific implementation method, structure, features and effects are described in detail as follows in conjunction with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0045] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0046] The specific scheme of the method for constructing a rice low temperature chilling injury model based on data drive provided by the present application is described in detail below with reference to the accompanying drawings.

[0047] An embodiment of the present application provides a data-driven method for constructing a rice low temperature chilling injury model.

[0048] Specifically, the following data-driven rice low temperature damage model construction method is provided, please refer to Figure 1 , the method comprises the following steps:

[0049] The first step is to obtain the rice growth and development period data of multiple agricultural meteorological stations in the preset historical years, as well as the daily average temperature data of the meteorological stations in the area where the agricultural meteorological stations are located in the preset historical years.

[0050] The data collected for the data-driven rice cold damage model in this application include meteorological data, agricultural meteorological data, and historical disaster data. The meteorological data and agricultural meteorological data come from the meteorological big data cloud platform, and the historical disaster data comes from the "China Meteorological Disaster Encyclopedia" and "China Meteorological Disaster Yearbook".

[0051] Among them, for agricultural meteorological data, rice growth and development period data from 25 agricultural meteorological stations from 1980 to 2020 were selected. Among them, the rice growth and development period data are the upper limit temperature T1, lower limit temperature T2 and suitable temperature T0 of rice in different growth and development periods. The units are all degrees Celsius, as shown in Table 1. Table 1 shows the T1, T2, and T0 values ​​of rice in each development period under high-yield conditions.

[0052] Table 1

[0053]

[0054] Among them, for meteorological data, the daily average temperature data of the meteorological stations in the corresponding historical years in the areas where the corresponding agricultural meteorological stations are located were selected.

[0055] According to the chilling injury classification method in the national standard "Chilling Injury Grades for Rice in Northern China" (GB / 34967-2017), the chilling injury grades are divided into three levels: light, moderate and severe, with corresponding numbers expressing the quantification of levels 2, 3 and 4, and the number 1 is used instead for no chilling injury.

[0056] According to the national standard "Northern Rice Low Temperature Chilling Damage Grade" (GB / 34967-2017), the "Delayed Chilling Damage Annual Index for Rice in Northeast China" low temperature chilling damage grade data is used as the preset standard sample data, and the standard sample data is shown in Table 2. At the same time, according to the chilling damage grade classification method in "Northern Rice Low Temperature Chilling Damage Grade", the chilling damage grade is divided into light, medium and severe grades, corresponding to the digital expression of 2, 3, and 4 grades, and no chilling damage is replaced by the number 1.

[0057] In Table 2, there are 704 chilling injury samples in Heilongjiang, 434 in Jilin, and 308 in Liaoning. This embodiment aims to construct light, medium, and severe chilling injury indicators for these sample data, thereby constructing a rice chilling injury model; at the same time, historical disaster data with clear records are used as authenticity test samples to verify the accuracy of the indicators.

[0058] Table 2

[0059]

[0060]

[0061] The second step is to determine the daily heat index by combining the daily average temperature data and the rice growth and development period data.

[0062] Since rice growth and development requires suitable temperatures, different temperature conditions will have certain effects on rice growth and development. Among them, high temperature will inhibit rice photosynthesis, thus affecting nutrient synthesis and growth rate; during flowering and fruiting, high temperature may lead to pollen sterility or bud development stagnation, thus reducing yield. Low temperature may lead to prolonged seedling period, poor growth and uneven growth, thus affecting the development process of the entire growth cycle; during maturity, low temperature may lead to insufficient grain, reducing yield and quality.

[0063] By analyzing the difference between the daily average temperature data and the temperature range required for rice growth and development, we can analyze the heat conditions required for daily rice growth and development, thereby reflecting the growth and development status of rice.

[0064] Based on this, this embodiment determines the daily heat index by combining the daily average temperature data and the rice growth and development period data, specifically:

[0065] The lower limit temperature T1, upper limit temperature T2 and suitable temperature T0 required for rice growth and development are obtained from the rice growth and development period data; the calculation formula of the daily heat index is: Where: S(i) is the heat index of the i-th day, T is the average daily temperature of the i-th day, T1, T2, and T0 are the lower limit temperature, upper limit temperature, and suitable temperature required for rice growth and development, respectively; When T≤T1 or T≥T2, let S(i)=0, and when T=T0, let S(i)=1.

[0066] It should be understood that this formula fully reflects the requirements of rice for temperature conditions in different growth and development periods. When the daily average temperature T on the i-th day exceeds the upper and lower temperature limits required for rice growth and development, the heat index is 0, indicating that the temperature on that day is high, the heat conditions required by rice are poor, and it is not suitable for rice growth and development; when the daily average temperature T on the i-th day is equal to the suitable temperature T0 required for rice growth and development, the heat index is 1, indicating that the temperature on that day is suitable, the heat conditions required by rice are good, and it is suitable for rice growth and development; otherwise, the daily heat index is calculated according to the calculation method of the above formula. The larger the daily heat index, the better the heat conditions required by rice and the more suitable it is for rice growth and development.

[0067] Among them, the different growth and development stages of rice are detailed in Table 3.

[0068] Each data in Table 3 is the daily heat index calculated based on the upper and lower limits of the temperature required for different development stages and the suitable temperature in the province where it is located.

[0069] Table 3

[0070]

[0071] The third step is to analyze the extent to which the daily heat index of each agricultural meteorological station is lower than the average level of the heat index in the adjacent preset years during the rice growth and development period in the preset historical years, and record it as a negative cumulative value. Based on the negative cumulative value and the number of consecutive days when the daily heat index is lower than the average level of the heat index in the adjacent preset years, and combined with the maximum negative cumulative value in the preset standard sample data of different regions, the low temperature comprehensive intensity index of each agricultural meteorological station in different regions is constructed.

[0072] Extreme weather during the growth and development period of rice will have a serious impact on the growth and development of rice. Extreme weather conditions will not only directly affect the growth and development of rice, but also cause pests and diseases, reduce disease resistance, and even affect the quality of the soil and microbial activities, thereby having a long-term impact on the farmland ecosystem. Long-term extreme weather has a more serious impact on the growth and development of rice. Among them, the impact of long-term low temperature environment is particularly serious. Long-term low temperature may cause physiological chilling damage to rice plants, affect the balance of photosynthesis and respiration, and thus affect the growth rate and yield of rice.

[0073] Accordingly, the present application first determines the negative cumulative value based on the extent to which all heat indices at each agricultural meteorological station during the rice growth and development period in a preset historical year are lower than the average heat index level in the adjacent preset year; specifically:

[0074] Calculate the average heat index value in the preset years adjacent to each day; calculate the difference between the daily heat index and the average heat index value; and count the cumulative sum of all difference results less than 0 during the rice growth and development period of each agricultural meteorological station in the preset historical years as the negative cumulative value.

[0075] In this embodiment, the adjacent preset years are set to the 30 years closest to the current day, and the specific setting can be made by the implementer according to the actual situation.

[0076] It should be understood that when the difference result is greater than or equal to 0, it means that the heat conditions required for rice growth and development are suitable or good; when the difference result is less than 0, it means that the heat conditions of rice are poor due to the influence of low temperature. By counting the cumulative sum of all difference results less than 0 during the growth and development period of rice in preset historical years at each agricultural meteorological station, it is used to describe the cumulative situation of the heat index being lower than the average value during the growing season. The larger the negative cumulative value, the worse the heat conditions required for rice during the growing season and the more serious the cold damage; the more the number of difference results less than 0, the longer the number of days the heat index is lower than the average value during the growing season and the more serious the cold damage. Negative cumulative values ​​can help evaluate the degree of low temperature during this period relative to the long-term average.

[0077] In one embodiment of the present application, the flow chart of the method for calculating the negative cumulative value is as shown in the attached figure. Figure 2 shown.

[0078] The present application then determines the negative cumulative consecutive days based on the consecutive days during the rice growth and development period in the preset historical years for each agricultural meteorological station, when all heat indices were lower than the average heat index level in the adjacent preset years.

[0079] The negative cumulative consecutive days are the maximum consecutive days when all heat indices are lower than the average heat index level in adjacent preset years.

[0080] It should be understood that if there is a long-term continuous temperature that is not suitable for the thermal conditions of rice growth and development, it will disrupt the growth cycle and physiological process of rice, making it difficult for it to develop normally and form high yields, and at the same time affecting its ability to adapt to environmental changes. Therefore, the greater the number of consecutive negative cumulative days, the more serious the chilling injury.

[0081] Considering that negative cumulative values ​​and consecutive negative cumulative days can measure the intensity and duration of low temperature damage, this application determines the low temperature comprehensive intensity index of each agricultural meteorological station in different regions in combination with the maximum value of negative cumulative values ​​in the preset standard sample data of different regions, specifically:

[0082] In this embodiment, the maximum value of the negative cumulative value in different regions in the preset standard sample data is obtained, which is -1076.5, -990.5 and -634.5 for Heilongjiang, Jilin and Liaoning respectively. The values ​​greater than the maximum value are directly classified as no chilling damage and represented by the value 1. This classification can avoid the interference of a large amount of no chilling damage data on the comprehensive chilling damage index. For negative cumulative values ​​less than the maximum value, the entropy weight method is used to set different weight proportions for negative cumulative values ​​and negative cumulative consecutive days in different regions by combining the negative cumulative consecutive days in the region where they are located.

[0083] In order to maintain the consistency of indicator changes, the negative cumulative value and the number of consecutive negative cumulative days are normalized to the maximum and minimum values. The maximum and minimum value normalization process is a well-known technology and will not be described in detail.

[0084] Among them, the expression of the low temperature comprehensive intensity index of the dth region at the i-th agricultural meteorological station is:

[0085]

[0086] In the formula, is the low temperature comprehensive intensity index of the i-th agricultural meteorological station in the d-th region, A is the preset amplification factor, which is 100 in this embodiment. It aims to highlight the discrimination of the low temperature comprehensive intensity index on the intensity of chilling damage by amplifying the negative cumulative value and the number of consecutive negative cumulative days. The value range is controlled between 0 and 100. are the first preset weight and the second preset weight of the dth region respectively, is the normalized value of the negative cumulative value of the i-th agricultural meteorological station in the d-th region, is the normalized value of the negative cumulative number of days at the i-th agricultural meteorological station in the d-th region, M d It is the maximum value of all negative cumulative values ​​of the dth region in the preset standard sample data.

[0087] It should be understood that the greater the low temperature comprehensive intensity index, the more severe the cold damage in the area where the corresponding agricultural meteorological station is located. Studies have shown that the negative cumulative value has a higher importance and contribution to the construction of the low temperature comprehensive intensity index. Therefore, when weighting the negative cumulative value and the number of consecutive negative cumulative days, the weight of the negative cumulative value is higher than the number of consecutive negative cumulative days.

[0088] In one embodiment of the present application, a flowchart of a method for constructing a low temperature comprehensive intensity index for each agricultural meteorological station in different regions is shown in the attached figure. Figure 3 shown.

[0089] The fourth step is to construct a rice low temperature damage model using the distribution characteristics of the low temperature comprehensive intensity index of all agricultural meteorological stations obtained under different cold damage levels in different regions.

[0090] On the basis of standard sample data, nine groups of sample sequences were obtained by calculating the low temperature comprehensive intensity index of each agricultural meteorological station under the division of different regions and different cold damage levels. Each group of sample sequences consisted of the low temperature comprehensive intensity index of all agricultural meteorological stations under the cold damage level of the same preset standard sample data in the same region.

[0091] For each set of sample series, the accuracy between the agricultural meteorological stations within the range divided according to the minimum and maximum values ​​of all low temperature comprehensive intensity indices corresponding to the chilling damage level and the agricultural meteorological stations under the corresponding chilling damage level of the standard sample data is calculated.

[0092] It should be noted that the accuracy is calculated by comparing the similarities between agricultural meteorological stations in two different division ranges, that is, the overlap of agricultural meteorological stations. The more overlaps there are between agricultural meteorological stations, the greater the accuracy between the agricultural meteorological stations in the division range according to the minimum and maximum values ​​of all low temperature comprehensive intensity indices of their corresponding chilling damage levels and the agricultural meteorological stations in the corresponding chilling damage levels of the standard sample data.

[0093] The accuracy of calculation of all group sample sequences in different regions is divided in order from large to small to obtain the value range of the low temperature comprehensive intensity index for different chilling damage levels that are re-determined.

[0094] Among them, the value range of the low temperature comprehensive intensity index for the re-determined cold damage level classification with low accuracy will delete the overlapping part with the value range of the low temperature comprehensive intensity index for the re-determined cold damage level classification with high accuracy, and add the range not included in the value range of the low temperature comprehensive intensity index for the re-determined adjacent cold damage level classification with high accuracy.

[0095] In addition, with a view to determining the range of no chilling damage levels, the range of values ​​of the low temperature comprehensive intensity index, which is greater than or equal to 0 and less than the mild chilling damage level, is taken as the no chilling damage level. That is, when the low temperature comprehensive intensity index of any agricultural meteorological station in any region is less than the lower limit of the range of values ​​of the low temperature comprehensive intensity index of the mild chilling damage level, it is determined that the agricultural meteorological station is not affected by chilling damage.

[0096] The range of values ​​of the low temperature comprehensive intensity index under all the re-determined levels of no chilling damage, mild chilling damage, moderate chilling damage and severe chilling damage in each region was used to construct a rice chilling damage model for each region.

[0097] It should be noted that the chilling damage level re-determined in each region based on the rice low temperature chilling damage model is basically consistent with the chilling damage level of the standard sample data.

[0098] The accuracy of the three regions was 63%, 64%, and 66%, respectively. The accuracy of the difference of one chilling damage level was 90%, 91%, and 93%, respectively. Figure 4 shown. Figure 4 Schematic diagram of the confusion matrix between the chilling damage level re-determined by the low temperature comprehensive intensity index and the chilling damage level of the standard sample data. Figure 4 (a), (b), and (c) are the confusion matrices of the chilling damage levels re-determined by the low temperature comprehensive intensity index and the chilling damage levels of the standard sample data in Heilongjiang, Jilin, and Liaoning, respectively. The rows and columns represent the categories predicted by the model and the actual categories, respectively, that is, the chilling damage levels re-determined by the low temperature comprehensive intensity index and the chilling damage levels of the standard sample data, and the value in each cell is the number of samples predicted correctly by the model.

[0099] The fifth step, after constructing the rice low temperature cold damage model, also includes point-by-point verification of the rice low temperature cold damage model based on historical disaster data and verification based on the spatial distribution of typical cold damage years.

[0100] 1.1 Point-by-point verification based on historical disaster data

[0101] The rice low temperature chilling injury model constructed based on the low temperature comprehensive intensity index was verified using historical disaster data as shown in Table 4: 21 of them fully met the verification results, with an accuracy rate of 80.7%, and the accuracy rate of basically meeting (one level difference) was 100%. It can be seen that the rice low temperature chilling injury model constructed by the low temperature comprehensive intensity index basically meets the actual occurrence of delayed chilling injury to rice, and the indicator has good applicability.

[0102] Table 4

[0103]

[0104]

[0105] 1.2 Verification based on the spatial distribution of typical years of chilling damage

[0106] Based on the records and research of China's Meteorological Disaster Encyclopedia and literature, 1969, 1986 and 1992 were taken as typical chilling damage years for rice in Northeast China, and 2007 was taken as a typical year without chilling damage. The rice chilling damage model based on CCI I (Comprehensive Low Temperature Intensity Index) was verified, aiming to evaluate the accuracy of the model in classifying disaster levels under different years and climatic conditions.

[0107] 1969 was a year of severe delayed low temperature damage, with CCI I of 47-75 in most areas of Heilongjiang, moderate and severe low temperature damage in most areas of Jilin, and CCI I of 31-47 in most areas of Liaoning. In 1986, CCI I in Yanji, Longjing and other eastern areas of Jilin was 48-50. When I is 66-75, severe chilling damage occurs. Mild chilling damage occurs in Ji'an, Meihekou and other places, which is consistent with historical records: "Rice heading and flowering are slow, filling speed is slow, growth is delayed, and mild chilling damage occurs; the lowest temperature during the flowering period of rice in Ji'an is 15℃, rice development is affected, tillering is less, and mild chilling damage occurs"; historical records in 1992: "The lowest daily temperature in Heilongjiang Province in early August was only 8-15℃, which is lower than the biological lower limit temperature of various crops during heading and flowering; in mid-August, the average temperature in most agricultural areas was lower than 15℃, which was below the biological lower limit temperature of various crops during the filling period, causing certain damage to the grain filling of crops, thereby reducing production and quality, and moderate chilling damage occurred to rice in most areas", and there were 33 moderate chilling damage stations in Heilongjiang (accounting for 52%), and CCI in Qianguo, Jilin I is 49, which is consistent with the historical record that "Qianguo's frost-free period is 130 days, and moderate delayed low temperature and chilling damage occurs"; in 2007, rice planting areas were widely distributed in areas without chilling damage, and there were 155 chilling damage-free stations in Northeast China (accounting for 97.5%). The IDW spatial distribution verification based on the typical year of chilling damage shows that the CCI I index's classification of chilling damage levels is consistent with historical records and literature research descriptions. Therefore, it shows that the rice chilling damage model constructed based on this index has a certain degree of accuracy and reliability.

[0108] 2 Spatial and temporal changes in the frequency of cold damage in the three northeastern provinces over the past 60 years

[0109] Based on the rice low temperature chilling injury model, the spatiotemporal changes in the frequency of mild, moderate and severe chilling injury in the three northeastern provinces in the past 60 years from 1961 to 1970 (1960S), 1971 to 1980 (1970S), 1981 to 1990 (1980S), 1991 to 2000 (1990S), 2001 to 2010 (2000S) and 2011 to 2020 (2010S) were analyzed to further illustrate the effectiveness of the indicator. It should be noted that S represents a ten-year period, for example: 1960S represents a ten-year period from 1960 to 1969.

[0110] 2.1 Frequency and spatial distribution characteristics of mild chilling injury

[0111] In 1970s, the number of stations with mild chilling injury was the largest and the frequency was the highest, mainly distributed in most parts of Heilongjiang, most parts of Jilin, and central and eastern Liaoning. There were 85 stations (53.5%) with a chilling injury frequency greater than 0.4 (4 times every 10 years). Mild chilling injury also occurred frequently in 1980s, with 44 stations with a chilling injury frequency greater than 0.4. After that, the chilling injury occurrence decreased with the years, that is, it decreased in 1990s, even less in 2000s, and least in 2010s, which is consistent with the research conclusions of the literature. The change in the frequency of mild chilling injury in the three northeastern provinces in the past 60 years showed a single peak change characteristic (most frequent in 1970s), and the frequency decreased significantly after 2000s, especially in the rice planting distribution areas in central Liaoning and western Jilin.

[0112] 2.2 Frequency and distribution of moderate chilling injury

[0113] In the 1970s, moderate chilling injury occurred in the widest range and at the highest frequency, with 107 stations experiencing a frequency greater than 0.2, and more than 90% of the stations experiencing moderate chilling injury (chilling injury frequency ≧0.1). According to incomplete statistics, among the historical records of moderate chilling injury that clearly identified the crop type as rice or crops, 16 records were from the 1970s, accounting for 27%; in the 1990s, moderate chilling injury was concentrated in the central and eastern parts of Heilongjiang, most of Jilin, and the northeastern region of Liaoning. From the 2000s to the 2010s, the range of moderate chilling injury decreased significantly, and the frequency of moderate chilling injury has also shown a significant decreasing trend in the past 30 years.

[0114] 2.3 Frequency and distribution of severe chilling injury

[0115] The severe chilling damage in 1960S, 1970S and 1980S occurred over a larger area, with 57, 64 and 51 stations with an occurrence frequency greater than 0.2, respectively. The severe chilling damage in 1970S was the most serious, followed by 1960S. The severe chilling damage in 1980S was mainly concentrated in most parts of Heilongjiang and eastern Jilin, and in 1990S was mainly concentrated in Heilongjiang and eastern Jilin. The frequency of severe chilling damage in 2000S and 2010S decreased significantly, and occasionally occurred in scattered areas.

[0116] The various embodiments in the present application are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0117] It should be noted that, unless otherwise specified and limited, terms such as "include", "comprises" or any other variants thereof are intended to cover non-exclusive inclusion, so that a circuit structure, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such article or device. In the absence of further restrictions, an element defined by the sentence "including one..." does not exclude the existence of other identical elements in the article or device including the element. In addition, the term "and\or" used herein includes any and all combinations of one or more related listed items.

[0118] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention herein. The present application is intended to cover any variations, uses or adaptations of the present application, which follow the general principles of the present application and include common knowledge or customary technical means in the art that are not invented by the present application.

[0119] It should be understood that the present application is not limited to the exact construction that has been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof.

Claims

1. A data-driven method for constructing a rice low temperature chilling injury model, characterized in that: The method comprises the following steps: Obtain rice growth and development period data of multiple agricultural meteorological stations in preset historical years, and daily average temperature data of meteorological stations in the corresponding historical years in the corresponding areas where the agricultural meteorological stations are located; Combine the daily average temperature data and rice growth and development period data to determine the daily heat index; For each agricultural meteorological station during the rice growth and development period in the preset historical years, the degree to which the daily heat index is lower than the average heat index level in the adjacent preset years is analyzed and recorded as a negative cumulative value. Based on the negative cumulative value and the number of consecutive days when the daily heat index is lower than the average heat index level in the adjacent preset years, combined with the maximum negative cumulative value in the preset standard sample data of different regions, the low temperature comprehensive intensity index of each agricultural meteorological station in different regions is constructed; The rice low temperature damage model was constructed by using the distribution characteristics of the low temperature comprehensive intensity index of all agricultural meteorological stations obtained under the division of different cold damage levels in the preset standard sample data in different regions; The method for constructing the low temperature comprehensive intensity index of each agricultural meteorological station in different regions includes: The negative cumulative value is determined based on the extent to which all heat indices during the rice growth and development period in the preset historical years at each agricultural meteorological station are lower than the average heat index level in the adjacent preset years; Based on the number of consecutive days during the rice growth and development period in the preset historical years at each agricultural meteorological station, when all heat indices were lower than the average heat index in the adjacent preset years, the negative cumulative consecutive days were determined; In the preset standard sample data of different regions, the maximum value of negative cumulative value is combined to determine the comprehensive intensity index of low temperature for each agricultural meteorological station in different regions; The preset standard sample data in different regions include three levels of low temperature damage: mild, moderate, and severe; In the preset standard sample data of different regions, the maximum value of the negative cumulative value is combined to determine the low temperature comprehensive intensity index of each agricultural meteorological station in different regions, including: The expression of the low temperature comprehensive intensity index for the dth region at the i-th agricultural meteorological station is: In the formula, is the low temperature comprehensive intensity index of the ith agricultural meteorological station in the dth region, A is the preset amplification factor, are the first preset weight and the second preset weight of the dth region respectively, is the normalized value of the negative cumulative value of the i-th agricultural meteorological station in the d-th region, is the normalized value of the negative cumulative consecutive days of the i-th agricultural meteorological station in the d-th region, M d It is the maximum value of all negative cumulative values ​​of the dth region in the preset standard sample data.

2. The method for constructing a rice low temperature chilling injury model based on data drive according to claim 1, characterized in that: The rice growth and development period data are the upper limit temperature, lower limit temperature and suitable temperature of rice at different growth and development periods.

3. The method for constructing a rice low temperature chilling injury model based on data drive according to claim 1, characterized in that: The method for determining the daily calorie index includes: Obtain the lower limit temperature, upper limit temperature and suitable temperature required for rice growth and development in the rice growth and development period data; The calculation formula for the daily calorie index is: Where: S(i) is the heat index of the i-th day, T is the average daily temperature of the i-th day, T1, T2, and T0 are the lower limit temperature, upper limit temperature, and suitable temperature required for rice growth and development, respectively; When T≤T1 or T≥T2, let S(i)=0, and when T=T0, let S(i)=1.

4. The method for constructing a rice low temperature chilling injury model based on data drive according to claim 1, characterized in that: The calculation method of the negative cumulative value is: Calculate the average heat index for each day within the preset year; Calculate the difference between the daily heat index and the average heat index; The cumulative sum of all difference results less than 0 during the rice growth and development period in the preset historical years at each agricultural meteorological station is counted as the negative cumulative value.

5. The method for constructing a rice low temperature chilling injury model based on data drive according to claim 1, characterized in that: The negative cumulative consecutive days are the maximum consecutive days that all heat indices are lower than the average heat index level in adjacent preset years.

6. The method for constructing a rice low temperature chilling injury model based on data drive according to claim 1, characterized in that: The construction process of the rice low temperature chilling injury model includes: On the basis of the preset standard sample data, the low temperature comprehensive intensity index of each agricultural meteorological station is calculated based on the division of different regions and different chilling damage levels to obtain several groups of sample sequences, wherein each group of sample sequences is composed of the low temperature comprehensive intensity index of all agricultural meteorological stations under the chilling damage level of the same preset standard sample data in the same region; For each set of sample series, calculate the accuracy between the agricultural meteorological stations within the range divided by the minimum and maximum values ​​of all low temperature comprehensive intensity indices corresponding to the chilling damage level and the agricultural meteorological stations under the corresponding chilling damage level of the preset standard sample data; The accuracy of all sample series calculated in different regions is divided in descending order to obtain the value range of low temperature comprehensive intensity index for different chilling damage levels; Among them, the value range of the low temperature comprehensive intensity index for the re-determined chilling damage level with low accuracy will delete the overlapping part with the value range of the low temperature comprehensive intensity index for the re-determined chilling damage level with high accuracy, and add the range not included in the value range of the low temperature comprehensive intensity index for the re-determined adjacent chilling damage level with high accuracy; the value range of the low temperature comprehensive intensity index composed of the lower bound of the value range of the low temperature comprehensive intensity index greater than or equal to 0 and less than the mild chilling damage level is taken as the no chilling damage level; The range of values ​​of the low temperature comprehensive intensity index under all the re-determined levels of no chilling damage, mild chilling damage, moderate chilling damage and severe chilling damage in each region was used to construct a rice chilling damage model for each region.

7. The method for constructing a rice low temperature chilling injury model based on data drive according to claim 1, characterized in that: After constructing the rice low temperature cold damage model, the rice low temperature cold damage model is also verified point by point based on historical disaster data and based on the spatial distribution of typical cold damage years. The verification data uses historical disaster data.

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