Early warning system and early warning method for extreme climate in orange orchard soil cultivation process

Abstract

The invention provides an early warning system and early warning method for extreme climate in the orange orchard soil cultivation process, and relates to the technical field of agricultural meteorological monitoring, and the early warning method specifically comprises the steps: collecting a plurality of climate-related key parameters of an orange orchard soil cultivation region, and calculating a temperature stability index, a precipitation fluctuation index and a temperature and humidity adaptability index; generating an environmental influence index and an ecological adaptability index according to the soil humidity, the illumination intensity, the soil pH value, the soil organic matter content, the temperature stability index and the precipitation fluctuation index after the dimensionless treatment; and combining the environmental influence index, the ecological adaptability index and the temperature and humidity adaptability index to generate a comprehensive evaluation value of the soil cultivation area of the orange garden, comparing the comprehensive evaluation value with a preset climate evaluation threshold value, and formulating corresponding management measures according to a comparison result. The scientific assessment enables farmers to timely identify climate risk levels, and provides a basis for formulating targeted management measures.

Description

Technical Field

[0001] The present invention relates to the technical field of agricultural meteorological monitoring, and specifically to an early warning system and method for extreme climates during the cultivation process of orange orchard soil. Background Technique

[0002] In modern agricultural production, the frequent occurrence of extreme climate events poses a severe challenge to the growth and yield of crops, especially the cultivation of fruit trees such as orange orchards. With the intensification of global climate change, the increase in temperature and the change of precipitation patterns have made orange orchards face greater survival pressure. Traditional meteorological monitoring means mainly rely on meteorological stations to collect data. The distribution of these stations is often not dense enough to cover all farmlands, resulting in many areas being unable to obtain accurate meteorological information. In addition, the update cycle of meteorological data is relatively long and often cannot reflect the rapidly changing climate conditions in real time, thus making farmers lack effective basis and guidance when dealing with extreme weather. More importantly, existing monitoring systems mostly focus on macroscopic meteorological characteristics and ignore the microscopic factors of soil health and crop growth. This makes farmers unable to comprehensively master various factors affecting crop growth during agricultural management, resulting in limitations in the effectiveness of management measures.

[0003] In addition, for soil management, traditional methods often rely on experience and conventional soil tests, lacking systematic comprehensive analysis. The monitoring of key indicators such as soil moisture, pH value, and organic matter content and their interaction with environmental factors are often not effectively integrated. Farmers lack a scientific and reasonable decision-making support system when choosing fertilization, irrigation, and disaster prevention measures. Coupled with the fact that existing climate adaptation strategies are mostly limited to the adjustment of single factors and it is difficult to form a systematic and scientific response plan, this makes agricultural production appear vulnerable when facing extreme climates. Therefore, there is an urgent need for a new type of integrated early warning system that can integrate meteorology, soil, and crop growth dynamics to help farmers more scientifically evaluate climate risks, optimize agricultural management measures, and thus improve the growth stability and yield of crops.

[0004] The above information disclosed in the background art section is only used to enhance the understanding of the background of the present disclosure, and therefore it may include information that does not constitute the prior art known to those of ordinary skill in the art. Summary of the Invention

[0005] The purpose of the present invention is to provide an early warning system and method for extreme climates during the cultivation process of orange orchard soil to solve the problems raised in the above background art.

[0006] To achieve the above purpose, the present invention provides the following technical solutions:

[0007] An early warning system for extreme climates during the cultivation process of orange orchard soil specifically includes:

[0008] A data acquisition module, which is used to collect the environmental temperature and precipitation data of the orange orchard soil cultivation area, and evenly divide the orange orchard soil cultivation area into several grids. The center of each grid is used as a monitoring point to collect soil humidity, light intensity, soil pH value and soil organic matter content. At the same time, the environmental temperature and soil humidity are stratified, and the temperature stability index, precipitation fluctuation index and temperature-humidity adaptability index are calculated;

[0009] An index generation module, which is used to generate an environmental impact index according to the dimensionless processed soil humidity, light intensity, soil pH value and soil organic matter content, and generate an ecological adaptability index according to the dimensionless processed temperature stability index and precipitation fluctuation index;

[0010] A comprehensive evaluation value calculation module, which is used to combine the environmental impact index, ecological adaptability index and temperature-humidity adaptability index to generate a comprehensive evaluation value of the orange orchard soil cultivation area, and the weights of the environmental impact index, ecological adaptability index and temperature-humidity adaptability index in the comprehensive evaluation value calculation are determined based on the analytic hierarchy process;

[0011] A risk level assessment module, which is used to compare the comprehensive evaluation value with a preset climate assessment threshold, and generate a climate risk level of the orange orchard soil cultivation area according to the comparison result. The climate risk level is divided into three levels: low risk level, medium risk level and high risk level, and corresponding management measures are formulated according to different levels.

[0012] Furthermore, the environmental temperature refers to the air temperature at 1.5 meters above the ground, and the precipitation data refers to the total precipitation within 24 hours traced back from the current moment. Denote the environmental temperature as T and the precipitation as R;

[0013] Calculate the mean values of the soil humidity, light intensity, soil pH value and soil organic matter content collected from each grid as the representative data of the entire orange orchard, and denote the soil humidity as S w , denote the light intensity as L, the soil pH value as pH, and the soil organic matter content as SC;

[0014] Among them, the specific logic for collecting soil humidity is: use a soil humidity sensor to measure the shallow, middle and deep soil humidity, and take the mean value as the soil humidity:

[0015]

[0016] In the formula, S w is the soil humidity, S w,shallow is the shallow soil humidity, S w,middle is the middle soil humidity, S w,deep is the deep soil humidity;

[0017] The above-mentioned collected environmental temperature, precipitation, soil humidity, light intensity, soil pH value, and soil organic matter content are all daily average data.

[0018] Furthermore, the environmental temperature and soil humidity are stratified, and the temperature-humidity adaptability index is calculated. The specific logic is as follows:

[0019] Collect the environmental temperature in the orange orchard soil cultivation area in the past 30 days, and calculate the monthly average temperature and standard deviation of the orange orchard soil cultivation area:

[0020]

[0021]

[0022] In the formula, T avg is the monthly average temperature, T std is the standard deviation of temperature, T i is the environmental temperature on the i-th day, n is the number of statistical days, specifically 30 days, and i is the index of the number of days;

[0023] According to the following formula, calculate sub-index 1: temperature stability index,

[0024]

[0025] In the formula, is the temperature stability index, T std is the standard deviation of temperature;

[0026] Collect the precipitation in the orange orchard soil cultivation area in the past 30 days, and calculate the monthly average precipitation and standard deviation of the orange orchard soil cultivation area:

[0027]

[0028] In the formula, R avg is the monthly average precipitation, R std is the standard deviation of precipitation, R i is the precipitation on the i-th day;

[0029] According to the following formula, calculate sub-index 2: precipitation fluctuation index,

[0030]

[0031] In the formula, is the precipitation fluctuation index, R std is the standard deviation of precipitation;

[0032] Calculate the temperature-humidity adaptability index according to the following formula:

[0033]

[0034] In the formula, is the temperature - humidity adaptability index, T avg is the monthly average temperature, R avg is the monthly average precipitation, T ref and R ref are the reference thresholds of environmental temperature and precipitation respectively.

[0035] Furthermore, according to the current soil humidity, light intensity, soil pH value, and soil organic matter content after dimensionless processing, an environmental impact index is generated, and the formula is as follows:

[0036]

[0037] In the formula, ENV is the environmental impact index, S w is the soil humidity, pH is the soil pH value, L is the light intensity, SC is the soil organic matter content; S w,ref , pH ref , L ref and SC ref are the reference thresholds of soil humidity, soil pH value, light intensity, and soil organic matter content respectively;

[0038] An ecological adaptability index is generated, and the formula is as follows:

[0039]

[0040] In the formula, ECO is the ecological adaptability index, is the precipitation fluctuation index, is the temperature stability index.

[0041] Furthermore, by combining the environmental impact index, ecological adaptability index, and temperature - humidity adaptability index, a comprehensive evaluation value of the orange orchard soil cultivation area is generated, and the expression is as follows:

[0042]

[0043] In the formula, ZS is the comprehensive evaluation value, e is the natural constant, is the temperature - humidity adaptability index, ENV is the environmental impact index, ECO is the ecological adaptability index, ω 1 , ω 2 and ω 3 are the weights of the temperature - humidity adaptability index, environmental impact index, and ecological adaptability index respectively, which are determined by the analytic hierarchy process.

[0044] Furthermore, the specific logic for determining the weights by the analytic hierarchy process is:

[0045] Mark the three indicators of the temperature and humidity adaptability index, the environmental impact index, and the ecological adaptability index, determine the relative importance values between each pair through the nine-scale method, and construct a judgment matrix. Among them, mark the temperature and humidity adaptability index as 1, the environmental impact index as 2, and the ecological adaptability index as 3. The constructed judgment matrix is:

[0046]

[0047] Among them, both f and v represent the indices of the indices, and f ∈ [1, 3], v ∈ [1, 3], b fv represents the importance degree of the index with index f relative to the index with index v. The importance degree adopts the 1-9 scale method, and b fv The larger the value, the greater the importance degree of the index with index f compared to the index with index v, and b ff = 1,

[0048] Divide each element value in the judgment matrix by the sum of its column to obtain the normalized judgment matrix. Calculate the mean value of each row element value in the normalized judgment matrix, take the mean value of the first row element value as the weight of the temperature and humidity adaptability index, take the mean value of the second row element value as the weight of the environmental impact index, and take the mean value of the third row element value as the weight of the ecological adaptability index. With the constraint that the sum of the scaled values is equal to 1, scale the three weights proportionally, and use the scaled weights as the proportionality coefficients of the corresponding indices.

[0049] Furthermore, compare the comprehensive evaluation value with the preset climate evaluation threshold. The specific logic is as follows:

[0050] When ZS ≤ 0.5ZY, the climate risk level is rated as a high-risk level, indicating that the current climate conditions pose a greater threat to the orange orchard, and immediate countermeasures need to be taken, such as adjusting water and fertilizer management and strengthening disaster prevention measures;

[0051] When 0.5ZY < ZS ≤ ZY, the climate risk level is rated as a medium-risk level, and the monitoring frequency is increased to collect climate data in a timely manner;

[0052] When ZS > 0.5ZY, the climate risk level is rated as a low-risk level, indicating that the current climate conditions are suitable, and the existing water and fertilizer management plan is maintained;

[0053] In the formula, ZS is the comprehensive evaluation value, and ZY is the preset climate evaluation threshold.

[0054] The present invention also provides an early warning method for extreme climate during the orange orchard soil cultivation process. The early warning method for extreme climate during the orange orchard soil cultivation process is obtained by executing the above-mentioned early warning system for extreme climate during the orange orchard soil cultivation process. The specific steps include:

[0055] Step 1: Collect the environmental temperature and precipitation data of the orange orchard soil cultivation area, and evenly divide the orange orchard soil cultivation area into several grids. The center of each grid is used as a monitoring point to collect soil humidity, light intensity, soil pH value, and soil organic matter content; at the same time, perform stratification processing on the environmental temperature and soil humidity, and calculate the temperature stability index, precipitation fluctuation index, and temperature-humidity adaptability index;

[0056] Step 2: Generate an environmental impact index based on the dimensionless processed soil humidity, light intensity, soil pH value, and soil organic matter content, and generate an ecological adaptability index based on the dimensionless processed temperature stability index and precipitation fluctuation index;

[0057] Step 3: Combine the environmental impact index, ecological adaptability index, and temperature-humidity adaptability index to generate a comprehensive evaluation value for the orange orchard soil cultivation area, and the weights of the environmental impact index, ecological adaptability index, and temperature-humidity adaptability index in the comprehensive evaluation value calculation are determined based on the analytic hierarchy process;

[0058] Step 4: Compare the comprehensive evaluation value with a preset climate evaluation threshold, and generate a climate risk level for the orange orchard soil cultivation area according to the comparison result. The climate risk level is divided into three levels: low risk level, medium risk level, and high risk level, and corresponding management measures are formulated according to different levels.

[0059] Compared with the prior art, the beneficial effects of the present invention are:

[0060] The present invention uses a data acquisition module to real-time monitor multiple parameters such as the environmental temperature, precipitation, soil humidity, light intensity, soil pH value, and organic matter content of the orange orchard. After these data are subjected to stratification processing and dimensionless processing, a temperature-humidity adaptability index and an environmental impact index can be generated, providing a quantitative basis for evaluating the climate adaptability of the orange orchard. Secondly, the comprehensive evaluation value calculation module combines each index, determines the weight according to the analytic hierarchy process, and through the generated comprehensive evaluation value, farmers can clearly identify the climate risk level. The risk level evaluation module of the system further refines the classification of the climate risk level, clarifies the criteria for low, medium, and high risks, enabling farmers to take corresponding management measures in a timely manner. For example, when the system prompts a high risk, farmers can quickly adjust water and fertilizer management and take disaster prevention measures; in the case of medium risk, the monitoring frequency can be increased, thereby reducing losses caused by climate change to a certain extent. Through such systematic management and decision support, the stress resistance of the orange orchard is enhanced, and the production efficiency and economic benefits are significantly improved. Brief Description of the Drawings

[0061] Figure 1 It is a schematic diagram of the system module of the present invention;

[0062] Figure 2 This is a schematic diagram of the overall method flow of the present invention. Detailed implementation manners

[0063] To make the objectives, technical solutions and advantages of the present invention more clear and understandable, the present invention will be further described in detail below in conjunction with specific embodiments.

[0064] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should have the ordinary meanings understood by those with ordinary skills in the field to which the present invention belongs. The "first", "second" and similar terms used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. The terms such as "comprising" or "including" mean that the elements or objects appearing before this term cover the elements or objects listed after this term and their equivalents, without excluding other elements or objects. The terms such as "connected" or "coupled" are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The terms such as "upper", "lower", "left" and "right" are only used to represent relative positional relationships, and when the absolute position of the object being described changes, the relative positional relationship may also change accordingly.

[0065] Embodiment:

[0066] Please refer to Figure 1 , the present invention provides an early warning system for extreme climates during the cultivation of citrus orchard soil, specifically including:

[0067] A data acquisition module, which is used to collect environmental temperature and precipitation data in the citrus orchard soil cultivation area, and evenly divide the citrus orchard soil cultivation area into several grids, with the center of each grid as a monitoring point to collect soil humidity, light intensity, soil pH value and soil organic matter content; at the same time, perform stratified processing on the environmental temperature and soil humidity, and calculate the temperature stability index, precipitation fluctuation index and temperature-humidity adaptability index;

[0068] In this embodiment, the environmental temperature refers to the air temperature at a height of 1.5 meters from the ground, and the precipitation data refers to the total precipitation within 24 hours back from the current moment. Denote the environmental temperature as T and the precipitation as R;

[0069] Calculate the average value of the soil humidity, light intensity, soil pH value and soil organic matter content collected from each grid as the representative data of the entire citrus orchard, and denote the soil humidity as S w , denote the light intensity as L, denote the soil pH value as pH, and denote the soil organic matter content as SC;

[0070] Among them, the specific logic for collecting soil humidity is as follows: Use a soil humidity sensor to measure the shallow, middle, and deep soil humidity, and take the average value as the soil humidity:

[0071]

[0072] In the formula, S w is the soil humidity, S w,shallow is the shallow soil humidity, S w,middle is the middle soil humidity, S w,deep is the deep soil humidity;

[0073] The above-collected environmental temperature, precipitation, soil humidity, light intensity, soil pH value, and soil organic matter content are all daily average data.

[0074] Perform stratified processing on the environmental temperature and soil humidity, and calculate the temperature-humidity adaptability index. The specific logic is as follows:

[0075] Collect the environmental temperature in the orange orchard soil cultivation area in the past 30 days, and calculate the monthly average temperature and standard deviation of the orange orchard soil cultivation area:

[0076]

[0077] In the formula, T avg is the monthly average temperature, T std is the standard deviation of the temperature, T i is the environmental temperature on the i-th day, n is the number of statistical days, specifically 30 days, and i is the index of the number of days;

[0078] According to the following formula, calculate sub-index 1: Temperature stability index,

[0079]

[0080] In the formula, is the temperature stability index, T std is the standard deviation of the temperature; A higher temperature stability index means relatively stable temperature conditions, which is beneficial to agricultural production. Crops grow under relatively consistent temperature conditions, which can increase yield and quality and reduce growth risks caused by temperature fluctuations.

[0081] Collect the precipitation in the orange orchard soil cultivation area in the past 30 days, and calculate the monthly average precipitation and standard deviation of the orange orchard soil cultivation area:

[0082]

[0083] In the formula, R avg is the monthly average precipitation, R std is the standard deviation of the precipitation, R i is the precipitation on the i-th day;

[0084] Calculate sub - index 2: precipitation fluctuation index according to the following formula

[0085]

[0086] In the formula, is the precipitation fluctuation index, and R std is the standard deviation of precipitation; the higher the value of the precipitation fluctuation index, the more stable the change in precipitation, which is usually more beneficial to agricultural production.

[0087] Calculate the temperature - humidity adaptability index according to the following formula

[0088]

[0089] In the formula, is the temperature - humidity adaptability index. The higher its value, the closer the monthly average temperature and precipitation are to the reference values, indicating that the climate conditions are more comfortable and more suitable for crop growth. Conversely, if its value is lower, it means that the climate conditions are harsher and may have a negative impact on crop growth; T avg is the monthly average temperature, R avg is the monthly average precipitation, T ref and R ref are the reference thresholds of environmental temperature and precipitation respectively. The use of the cube root is to smooth the final adaptability index so that the final index will not be overly amplified or reduced due to extreme changes in a single factor.

[0090] When |T avg - T ref | increases, it means that the deviation of the monthly average temperature from the temperature reference threshold increases. When the temperature deviation is large, it may affect crop growth, especially in the case of extreme high or low temperatures. Crops may face risks such as slow growth, reduced yield, and even death. Therefore will decrease; when |R avg - R ref | increases, it means that the deviation of the monthly average precipitation from the precipitation reference threshold increases. The drastic change in precipitation may lead to the uncertainty of agricultural production. Therefore will decrease accordingly; that is to say, |T avg - T ref |, |R avg - R ref | and show a negative correlation.

[0091] The main advantage of the data acquisition module lies in its efficient and meticulous environmental monitoring capabilities. By evenly dividing the orange orchard soil cultivation area into several grids and setting up monitoring points at the center of each grid, this module can collect environmental temperature and precipitation data in real time, while obtaining soil humidity, light intensity, soil pH value, and soil organic matter content. This refined monitoring method is more comprehensive and real-time compared to traditional weather station monitoring, capable of capturing minor climate changes within the region, providing more accurate and timely data support, and laying a solid foundation for subsequent climate risk assessment and formulation of management measures.

[0092] Compared with the existing technology, this data acquisition module solves the problems of long data update cycle and insufficient coverage in traditional meteorological monitoring through multi-dimensional monitoring means, ensuring an immediate response to changes in the orange orchard environment. The detailed data it provides not only enables farmers to understand the environmental changes in real time but also provides a basis for calculating key indicators such as temperature stability index and precipitation fluctuation index, further enhancing the scientificity and accuracy of the entire early warning system. After adopting this module, the effectiveness of the overall solution has been greatly improved, enabling farmers to take corresponding management measures in a timely manner before extreme weather occurs, reducing the potential threat of climate risk to orange orchard production, and thus improving the yield and quality of crops.

[0093] An index generation module, which is used to generate an environmental impact index based on the dimensionless processed soil humidity, light intensity, soil pH value, and soil organic matter content, and generate an ecological adaptability index based on the dimensionless processed temperature stability index and precipitation fluctuation index;

[0094] In this embodiment, the formula for generating the environmental impact index based on the dimensionless processed current soil humidity, light intensity, soil pH value, and soil organic matter content is as follows:

[0095]

[0096] In the formula, ENV is the environmental impact index, which can comprehensively reflect the suitability and health of a specific environmental condition for plant growth. A higher ENV value indicates that the current environmental condition is similar to the reference condition, suitable for plant growth, and the environment has a stronger support capacity for organisms; S w is the soil humidity, pH is the soil pH value, L is the light intensity, and SC is the soil organic matter content; S w,ref 、pH ref 、L ref and SC refThey are the reference thresholds for soil moisture, soil pH value, light intensity, and soil organic matter content respectively. The design of taking the cube of the entire formula result can enhance the sensitivity to environmental impacts, and small deviation changes will more significantly affect the final environmental impact index. This non-linear transformation makes the index more sensitive to changes in environmental conditions and can better reflect the importance of environmental suitability.

[0097] When |S w -S w,ref | increases, it means that the deviation between soil moisture and the soil moisture reference threshold increases, which may cause plants to face the risk of drought or over-wetness. Too low soil moisture will cause plants to lack water, affecting growth and yield, while too high soil moisture may lead to root hypoxia, increased diseases, and even plant death. Therefore, ENV will decrease. Similarly, when |pH - pH ref |, |L - L ref |, or |SC - SC ref | increases, ENV will decrease accordingly. That is to say, |S w -S w,ref |, |pH - pH ref |, |L - L ref |, |SC - SC ref | and ENV are negatively correlated.

[0098] The formula for generating the ecological adaptability index is as follows:

[0099]

[0100] In the formula, ECO is the ecological adaptability index, which reflects the adaptability and stability of an ecosystem in the face of temperature and precipitation fluctuations. is the precipitation fluctuation index. is the temperature stability index. Using and The construction of the sum of squares can effectively combine the stability indicators of temperature and precipitation. The square operation ensures that regardless of whether these two stability indices are positive or negative, the final result is positive. At the same time, the square operation also emphasizes the influence of extreme values to a certain extent, that is, when a certain index is significantly low, its impact on the overall ecological adaptability index will be more significant.

[0101] A higher temperature stability index means that the temperature conditions are relatively stable, which is beneficial to agricultural production. Crops grow under relatively consistent temperature conditions, which can increase yield and quality and reduce the growth risks brought by temperature fluctuations. Therefore, when increases, ECO also increases. The higher the precipitation fluctuation index value, it means that the change in precipitation is relatively stable, which is usually more beneficial to agricultural production. Therefore, when When it increases, ECO also increases; that is to say, It has a positive correlation with ECO.

[0102] The main advantage of the index generation module is that it can convert multi-dimensional and dimensionless environmental data into quantifiable environmental impact indices and ecological adaptability indices. This module comprehensively processes key indicators such as soil humidity, light intensity, soil pH value, and soil organic matter, enabling different environmental variables to be compared and analyzed with a unified standard. This not only improves the availability of data but also provides a scientific basis for subsequent comprehensive evaluations, ensuring more accurate and effective decision-making.

[0103] Compared with the prior art, the design of this index generation module enables the evaluation of the environment and ecological adaptability not to rely on a single factor, but to form a more comprehensive evaluation system by integrating multiple indicators. This diversified evaluation method can more accurately reflect the actual adaptability of the orange orchard under extreme climates, avoiding the limitations and one-sidedness that may exist in traditional methods. After adopting this module, the overall solution becomes more scientific and systematic, which can not only enhance the risk response ability of farmers but also provide more reliable decision-making support for agricultural management, thereby improving the overall production efficiency and sustainable development level of the orange orchard.

[0104] The comprehensive evaluation value calculation module is used to combine the environmental impact index, the ecological adaptability index, and the temperature and humidity adaptability index to generate the comprehensive evaluation value of the orange orchard soil cultivation area, and the weights of the environmental impact index, the ecological adaptability index, and the temperature and humidity adaptability index in the comprehensive evaluation value calculation are determined based on the analytic hierarchy process;

[0105] In this embodiment, the environmental impact index, the ecological adaptability index, and the temperature and humidity adaptability index are combined to generate the comprehensive evaluation value of the orange orchard soil cultivation area, and the expression is as follows:

[0106]

[0107] In the formula, ZS is the comprehensive evaluation value, which comprehensively considers climate adaptability, environmental suitability, and ecological stability to comprehensively evaluate the orange orchard soil cultivation area. e is the natural constant, is the temperature and humidity adaptability index, ENV is the environmental impact index, ECO is the ecological adaptability index, ω 1 、ω 2 and ω 3They are the weights of the temperature-humidity adaptability index, the environmental impact index, and the ecological adaptability index, respectively, determined by the analytic hierarchy process. The introduction of the cube root helps to smooth the influence between different indicators, making the comprehensive evaluation value more stable under different conditions. Through the cube root processing, it can prevent a certain indicator from being too prominent numerically and having a disproportionate impact on the result. This design ensures the rationality and consistency of the comprehensive evaluation value. Using the natural constant e for exponential operation not only enhances the mathematical properties of the formula but also keeps the final result within a certain range. The exponential function can effectively amplify small changes, strengthening the sensitivity of the system to environmental and ecological factors, so that the final evaluation can better reflect the suitability of the orange orchard.

[0108] When increases, it indicates that the temperature and humidity conditions are more suitable for the growth of orange trees. This means that the soil environment is more friendly to the growth and development of orange trees, which may promote the healthy growth and good fruit setting of the plants, and ZS will increase accordingly; a higher ENV value indicates that the current environmental conditions are similar to the reference conditions and are suitable for the growth of plants, and the environment has a strong supporting ability for organisms. Therefore, when ENV increases, ZS will also increase; a higher ECI value usually indicates that the ecosystem in this area is more resilient and adaptable. This means that orange trees can better cope with environmental changes, climate fluctuations, and other external pressures, such as pests and diseases and extreme weather, thus promoting the healthy growth of plants. Therefore, when ECI increases, ZS will also increase; that is to say, ENV, ECO and ZS are positively correlated.

[0109] The specific logic for determining the weights by the analytic hierarchy process is as follows:

[0110] Mark the three indicators of the temperature-humidity adaptability index, the environmental impact index, and the ecological adaptability index, and determine the numerical values of the relative importance between each pair through the nine-scale method to construct a judgment matrix. Among them, mark the temperature-humidity adaptability index as 1, the environmental impact index as 2, and the ecological adaptability index as 3. The constructed judgment matrix is:

[0111]

[0112] where f and v both represent the indices of the exponents, and f ∈ [1, 3], v ∈ [1, 3], and b fv represents the importance degree of the exponent with index f relative to the exponent with index v. The importance degree adopts the 1-9 scale method, and b fv The larger the value, the greater the importance degree of the exponent with index f compared to the exponent with index v, and b ff = 1,

[0113] Divide each element value in the judgment matrix by the sum of its column to obtain a normalized judgment matrix. Calculate the mean value of each row element value in the normalized judgment matrix, and take the mean value of the first row element value as the weight of the temperature and humidity adaptability index, the mean value of the second row element value as the weight of the environmental impact index, and the mean value of the third row element value as the weight of the ecological adaptability index. With the constraint that the sum of the scaled values equals 1, scale the three weights proportionally, and use the scaled weights as the proportional coefficients of the corresponding indices.

[0114] The main advantage of the comprehensive evaluation value calculation module is that it can integrate multiple environmental and ecological indicators into a unified comprehensive evaluation value, which not only simplifies the data processing process but also improves the accuracy and effectiveness of decision-making support. By using the analytic hierarchy process to assign weights to different indices, this module can dynamically adjust the influence degree of each index according to the changes in actual environmental conditions, making the evaluation results more targeted and practical. This comprehensive evaluation method can help farmers quickly understand the overall health status and climate adaptability of the orange orchard, so as to make more informed management decisions in the face of extreme climates.

[0115] Compared with the prior art, this comprehensive evaluation value calculation module avoids the one-sidedness and limitations that may exist in traditional evaluation methods by integrating multi-dimensional data and indices. Traditional technologies often rely on single or a small number of evaluation indices and are prone to ignoring the influence of other important factors on the climate adaptability of the orange orchard. This module combines the environmental impact index, the ecological adaptability index, and the temperature and humidity adaptability index to form a more comprehensive evaluation system. This innovation makes the overall solution more powerful in coping with extreme climates, not only improving the management efficiency of the orange orchard but also significantly reducing the risks and losses that may be caused by climate change, and promoting the development of sustainable agriculture.

[0116] The risk level evaluation module is used to compare the comprehensive evaluation value with a preset climate evaluation threshold. According to the comparison result, generate the climate risk level of the orange orchard soil cultivation area. Divide the climate risk level into three levels: low risk level, medium risk level, and high risk level, and formulate corresponding management measures according to different levels;

[0117] In this embodiment, the specific logic for comparing the comprehensive evaluation value with the preset climate evaluation threshold is as follows:

[0118] When ZS ≤ 0.5ZY, the climate risk level is rated as the high risk level, indicating that the current climate conditions pose a greater threat to the orange orchard, and immediate countermeasures need to be taken, such as adjusting water and fertilizer management and strengthening disaster prevention measures;

[0119] When 0.5ZY < ZS ≤ ZY, the climate risk level is rated as the medium risk level, and the monitoring frequency is increased to collect climate data in a timely manner;

[0120] When ZS > 0.5ZY, the climate risk level is rated as a low risk level, indicating that the current climate conditions are suitable and the existing water and fertilizer management plan should be maintained;

[0121] In the formula, ZS is the comprehensive evaluation value, and ZY is the preset climate evaluation threshold.

[0122] The main advantage of the risk level assessment module is that it can systematically compare the comprehensive evaluation value with the preset climate evaluation threshold, so as to quickly evaluate the climate risk level of the orange orchard. This module not only provides clear risk classification, but also helps farmers and managers make timely and effective responses in the face of extreme climate through specific management measure suggestions. Such an evaluation mechanism can significantly improve the flexibility and response ability of orange orchard management, and ensure the effective protection of the growth environment of crops.

[0123] Compared with the existing technology, the risk level assessment module avoids the ambiguity and uncertainty in traditional risk assessment by quantitatively comparing the comprehensive evaluation value with specific preset thresholds. Traditional methods often lack clear judgment criteria and are difficult to provide specific management guidance for farmers. However, this module enhances the scientificity and operability of decision-making through clear risk level classification and corresponding management measures. This refined management can effectively reduce the potential risks caused by climate change, improve the risk resistance ability of the orange orchard, promote the development of sustainable agriculture, provide a comprehensive climate adaptation plan for farmers, and enhance the overall economic benefits.

[0124] Please refer to Figure 2 , the early warning method for extreme climate in the process of orange orchard soil cultivation, the specific steps include:

[0125] Step 1: Collect the environmental temperature and precipitation data of the orange orchard soil cultivation area, and evenly divide the orange orchard soil cultivation area into several grids. The center of each grid is used as a monitoring point to collect soil humidity, light intensity, soil pH value and soil organic matter content; at the same time, conduct hierarchical processing on the environmental temperature and soil humidity, and calculate the temperature stability index, precipitation fluctuation index and temperature-humidity adaptability index;

[0126] Step 2: Generate an environmental impact index based on the dimensionless processed soil humidity, light intensity, soil pH value and soil organic matter content, and generate an ecological adaptability index based on the dimensionless processed temperature stability index and precipitation fluctuation index;

[0127] Step 3: Combine the environmental impact index, ecological adaptability index and temperature-humidity adaptability index to generate a comprehensive evaluation value of the orange orchard soil cultivation area, and the weights of the environmental impact index, ecological adaptability index and temperature-humidity adaptability index in the calculation of the comprehensive evaluation value are determined based on the analytic hierarchy process;

[0128] Step 4: Compare the comprehensive evaluation value with the preset climate evaluation threshold. According to the comparison result, generate the climate risk level of the citrus orchard soil cultivation area. The climate risk level is divided into three levels: low risk level, medium risk level, and high risk level. And corresponding management measures shall be formulated according to different levels.

[0129] The above formulas are all dimensionless and take their numerical values for calculation. The formulas are obtained by collecting a large amount of data for software simulation to get a formula closest to the actual situation. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0130] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. Those skilled in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or by the combination of computer software and electronic hardware. Whether these functions are executed by hardware or software methods depends on the specific application and design constraints of the technical solution.

[0131] The units described as separate components may or may not be physically separated. The components shown as units may or may not be physical units. They can be located in one place, or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0132] The above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed in this application, and all of them should be covered by the protection scope of this application.

Claims

1. An early warning system for extreme weather conditions during soil cultivation in orange orchards, characterized in that: Specifically include: The data acquisition module is used to collect the ambient temperature and precipitation data of the orange orchard soil cultivation area, and evenly divide the orange orchard soil cultivation area into several grids. The center of each grid is used as a monitoring point to collect soil moisture, light intensity, soil pH value and soil organic matter content; at the same time, the ambient temperature and soil moisture are layered and processed to calculate the temperature stability index, precipitation fluctuation index and temperature and humidity adaptability index; An index generation module is used to generate an environmental impact index based on dimensionless soil moisture, light intensity, soil pH value and soil organic matter content, and to generate an ecological adaptability index based on dimensionless temperature stability index and precipitation fluctuation index; A comprehensive evaluation value calculation module is used to combine the environmental impact index, the ecological adaptability index and the temperature and humidity adaptability index to generate a comprehensive evaluation value of the orange orchard soil cultivation area, and the weights of the environmental impact index, the ecological adaptability index and the temperature and humidity adaptability index in the calculation of the comprehensive evaluation value are determined based on the hierarchical analysis method; The risk level assessment module is used to compare the comprehensive assessment value with the preset climate assessment threshold. According to the comparison result, the climate risk level of the orange orchard soil cultivation area is generated, and the climate risk level is divided into three levels: low risk level, medium risk level and high risk level. According to different levels, corresponding management measures are formulated.

2. The early warning system for extreme climate during soil cultivation in orange orchards according to claim 1, characterized in that: The ambient temperature refers to the air temperature at 1.5 meters above the ground, and the precipitation data refers to the total precipitation within 24 hours from the current time. The ambient temperature is recorded as T and the precipitation is recorded as R; The soil moisture, light intensity, soil pH value and soil organic matter content collected at each grid monitoring point were averaged to serve as representative data for the entire orange orchard, and the soil moisture was recorded as S w , light intensity is recorded as L, soil pH is recorded as pH, and soil organic matter content is recorded as SC; The specific logic for collecting soil moisture is as follows: use a soil moisture sensor to measure the shallow, middle and deep soil moisture at the monitoring point, and take the average as the soil moisture at the monitoring point: In the formula, S w is soil moisture, S w,shallow is the shallow soil moisture, S w,middle is the middle soil moisture, S w,deep is deep soil moisture; The above-collected ambient temperature, precipitation, soil moisture, light intensity, soil pH value and soil organic matter content are all daily average data.

3. The early warning system for extreme climate during soil cultivation in orange orchards according to claim 1, characterized in that: The ambient temperature and soil moisture are processed in layers to calculate the temperature and humidity adaptability index. The specific logic is as follows: Collect the ambient temperature of the orange orchard soil cultivation area in the past 30 days, and calculate the monthly average temperature and standard deviation of the orange orchard soil cultivation area: Where, T avg is the monthly mean temperature, T std is the standard deviation of temperature, T i is the ambient temperature of the past i-th day, n is the number of statistical days, specifically 30 days, and i is the index of the day; Sub-index 1: Temperature stability index is calculated according to the following formula: In the formula, is the temperature stability index, T std is the standard deviation of temperature; Collect the precipitation in the orange orchard soil cultivation area in the past 30 days, and calculate the average monthly precipitation and standard deviation in the orange orchard soil cultivation area: In the formula, R avg is the average monthly precipitation, R std is the standard deviation of precipitation, R i is the precipitation on the i-th day; Sub-indicator 2: Precipitation Fluctuation Index is calculated according to the following formula: In the formula, is the precipitation fluctuation index, r std is the standard deviation of precipitation; The temperature and humidity adaptability index is calculated based on the following formula: In the formula, is the temperature and humidity adaptability index, T avg is the monthly mean temperature, R avg is the average monthly precipitation, T ref and R ref are the reference thresholds for ambient temperature and precipitation, respectively.

4. The early warning system for extreme climate during soil cultivation in orange orchards according to claim 1, characterized in that: The environmental impact index is generated based on the current soil moisture, light intensity, soil pH value and soil organic matter content after dimensionless processing. The formula is as follows: In the formula, ENV is the environmental impact index, S w is soil moisture, pH is soil pH, L is light intensity, SC is soil organic matter content; S w,ref , pH ref , L ref and SC ref They are the reference thresholds for soil moisture, soil pH, light intensity, and soil organic matter content; The ecological adaptability index is generated based on the following formula: In the formula, ECO is the ecological adaptability index, is the precipitation fluctuation index, is the temperature stability index.

5. The early warning system for extreme climate during soil cultivation in orange orchards according to claim 4, characterized in that: The environmental impact index, ecological adaptability index and temperature and humidity adaptability index are combined to generate a comprehensive evaluation value of the orange orchard soil cultivation area. The expression is as follows: In the formula, ZS is the comprehensive evaluation value, e is the natural constant, is the temperature and humidity adaptability index, ENV is the environmental impact index, ECO is the ecological adaptability index, ω1, ω2 and ω3 are the weights of the temperature and humidity adaptability index, the environmental impact index and the ecological adaptability index, respectively, which are determined according to the hierarchical analysis method.

6. The early warning system for extreme climate during soil cultivation in orange orchards according to claim 1, characterized in that: The specific logic of determining weights through the hierarchical analysis method is: Mark the three indicators of the temperature and humidity adaptability index, the environmental impact index, and the ecological adaptability index, determine the relative importance values between each pair through the nine-scale method, and construct a judgment matrix. Among them, mark the temperature and humidity adaptability index as 1, the environmental impact index as 2, and the ecological adaptability index as 3. The constructed judgment matrix is as follows: Where f and v both represent indexes of the exponent, and f∈[1,3], v∈[1,3], b fv Indicates the importance of the index with index f relative to the index with index v. The importance is scaled from 1 to 9, and b fv The larger the value, the more important the index f is compared to the index v, and b ff =1, Divide each element value in the judgment matrix by the sum of its column to obtain the normalized judgment matrix. Calculate the mean value of each row element value in the normalized judgment matrix, and take the mean value of the first row element value as the weight of the temperature and humidity adaptability index, the mean value of the second row element value as the weight of the environmental impact index, and the mean value of the third row element value as the weight of the ecological adaptability index. With the constraint that the sum of the scaled values is equal to 1, scale the three weights proportionally, and take the scaled weights as the proportional coefficients of the corresponding indices.

7. The early warning system for extreme climate during soil cultivation in orange orchards according to claim 1, characterized in that: Compare the comprehensive evaluation value with the preset climate evaluation threshold. The specific logic is as follows: When ZS ≤ 0.5ZY, the climate risk level is rated as the high-risk level, indicating that the current climate conditions pose a greater threat to the orange orchard, and immediate countermeasures need to be taken, such as adjusting water and fertilizer management and strengthening disaster prevention measures; When 0.5ZY < ZS ≤ ZY, the climate risk level is rated as the medium-risk level, and the monitoring frequency is strengthened to collect climate data in a timely manner; When ZS > 0.5ZY, the climate risk level is rated as the low-risk level, indicating that the current climate conditions are suitable, and the existing water and fertilizer management plan is maintained; In the formula, ZS is the comprehensive evaluation value, and ZY is the preset climate evaluation threshold.

8. A method for early warning of extreme weather during soil cultivation in an orange orchard, characterized by: The early warning method for extreme climate during the orange orchard soil cultivation process is obtained by executing the early warning system for extreme climate during the orange orchard soil cultivation process described in any one of claims 1-7. The specific steps include: Step 1: Collect the environmental temperature and precipitation data in the orange orchard soil cultivation area, and evenly divide the orange orchard soil cultivation area into several grids. The center of each grid is used as a monitoring point to collect soil humidity, light intensity, soil pH value, and soil organic matter content; at the same time, perform hierarchical processing on the environmental temperature and soil humidity, and calculate the temperature stability index, precipitation fluctuation index, and temperature and humidity adaptability index; Step 2: Generate the environmental impact index based on the dimensionless processed soil humidity, light intensity, soil pH value, and soil organic matter content, and generate the ecological adaptability index based on the dimensionless processed temperature stability index and precipitation fluctuation index; Step 3: Combine the environmental impact index, the ecological adaptability index, and the temperature and humidity adaptability index to generate the comprehensive evaluation value of the orange orchard soil cultivation area, and the weights of the environmental impact index, the ecological adaptability index, and the temperature and humidity adaptability index in the calculation of the comprehensive evaluation value are determined based on the analytic hierarchy process; Step 4: Compare the comprehensive evaluation value with the preset climate evaluation threshold. According to the comparison result, generate the climate risk level of the orange orchard soil cultivation area. The climate risk level is divided into three levels: low-risk level, medium-risk level, and high-risk level, and corresponding management measures are formulated according to different levels.

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