A method and system for evaluating bamboo shoot growth based on ecological data analysis

Abstract

This invention belongs to the field of bamboo shoot technology and discloses a method and system for assessing bamboo shoot growth based on ecological data analysis. The method identifies deviation points in the ecological growth data of bamboo shoots. A deviation point is a time point where the deviation value of the ecological growth data relative to the standard growth stage data of bamboo shoots exceeds a preset deviation threshold. In response to the identified deviation points, the method constructs data samples based on these deviation points. This construction method includes determining the earliest deviation point in time as a leading deviation point and setting it as a sample point. Based on qualitative and quantitative analysis of the data samples, a final assessment result is generated, and an alarm level is generated according to the final assessment result. This invention, by identifying deviation points and constructing data samples based on leading deviation points, combined with qualitative and quantitative analysis, achieves early warning of growth risks, improving the accuracy and timeliness of the assessment.

Description

Technical Field

[0001] This invention belongs to the field of bamboo shoot technology, specifically relating to a method and system for evaluating bamboo shoot growth based on ecological data analysis. Background Technology

[0002] In the field of cash crop cultivation, real-time and refined data monitoring and analysis of crop growth environment plays a crucial role in optimizing resource allocation, improving crop quality and yield, and ensuring food safety. In particular, for green and ecological agricultural products such as bamboo shoots, building an intelligent growth assessment and supervision system is a key technological guarantee for achieving their industrialization, standardization, and sustainable development.

[0003] However, most existing technologies simplify the complex growth process into isolated judgments of a single environmental indicator (such as temperature and humidity), ignoring the comprehensive impact of the complex nonlinear coupling relationship between multidimensional environmental factors on crop growth. They cannot truly reflect the dynamic changes in growth status. In addition, existing methods lack the ability to deeply mine time series data. The growth of bamboo shoots is a continuous dynamic process, and its growth deviations or the occurrence of potential diseases often manifest as gradual trends or periodic fluctuations in the data. Traditional methods usually treat data as discrete time points, which cannot effectively identify such time-related patterns, affecting the timeliness and accuracy of fault warnings. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for evaluating bamboo shoot growth based on ecological data analysis, which can provide a dynamic basis for evaluating the bamboo shoot growth process.

[0005] To achieve the above-mentioned objectives, the technical solution adopted by the present invention is as follows:

[0006] This application provides a method for evaluating bamboo shoot growth based on ecological data analysis, including the following steps:

[0007] When deviations are identified in the ecological growth data of bamboo shoots, data samples are constructed based on the deviations.

[0008] Based on the analysis of the data samples, a final evaluation result is generated;

[0009] The deviation point is the time point at which the deviation value of the ecological growth data relative to the preset standard growth stage data of bamboo shoots exceeds a preset deviation threshold at one or more time points.

[0010] The process of constructing data samples based on the deviation points includes:

[0011] Divide one or more analysis periods containing the aforementioned deviation points into multiple benchmark evaluation periods;

[0012] The earliest deviation point in time is determined as the leading deviation point and set as the sample point;

[0013] Based on the ecological growth data corresponding to the sample points in multiple subsequent benchmark assessment periods, a sampling curve is constructed;

[0014] Based on the slope of the sampling curve, the endpoints of the sampling curve are marked as forward sampling nodes and reverse sampling nodes, respectively, and their corresponding measurement values ​​are recorded as forward sample data and reverse sample data, respectively, to jointly constitute the data sample.

[0015] In a preferred embodiment, identifying deviation points in the ecological growth data of bamboo shoots includes:

[0016] For any time point to be measured within the analysis period, the time point to be measured is defined as the base point;

[0017] The base point is paired with adjacent time periods of a preset time length before and after the base point to set the deviation calculation time period;

[0018] The ecological growth data within the deviation measurement period is submitted to a preset difference calculation function to generate a deviation value;

[0019] Furthermore, if the deviation value is greater than or equal to a preset deviation threshold, the base point is marked as a deviation point.

[0020] In a preferred technical solution, based on the analysis of the data sample, a final evaluation result is generated, including:

[0021] Qualitative analysis is performed on the positive sample data to generate qualitative evaluation results;

[0022] Quantitative analysis is performed on the reverse sample data to generate quantitative evaluation results;

[0023] The final evaluation result is generated by combining the qualitative evaluation results with the quantitative evaluation results.

[0024] In a preferred technical solution, qualitative analysis of the positive sample data includes:

[0025] Determine whether the value of the positive sample data is lower than a preset growth lower limit threshold, or determine whether the trend of the positive sample data deviates from the trend of the standard growth stage data. If either determination is yes, then generate a qualitative evaluation result indicating the failure state.

[0026] Quantitative analysis of the reverse sample data includes:

[0027] The trend value of the reverse sample data is calculated, and the trend value is matched with the preset scoring criteria to generate a quantitative numerical score as a quantitative evaluation result.

[0028] In a preferred embodiment, the method further includes the following steps:

[0029] Set a threshold for the evaluation result classification, divide it into multiple classification ranges, and map the final evaluation result to the corresponding classification range to generate an alarm level.

[0030] In a preferred embodiment, the ecological growth data includes: air temperature, air humidity, soil temperature, soil humidity, soil pH value, or light intensity.

[0031] This application also provides a bamboo shoot growth assessment system based on ecological data analysis, including:

[0032] The deviation identification module is used to identify deviation points in the ecological growth data of bamboo shoots. The deviation point is the time point at which the deviation value of the ecological growth data relative to the preset standard growth stage data of bamboo shoots exceeds a preset deviation threshold at one or more time points.

[0033] The growth assessment module is used to construct data samples based on the deviation points and generate final assessment results based on the analysis of the data samples.

[0034] The alarm generation module is used to generate alarm levels based on the final evaluation results;

[0035] The process of constructing data samples based on the deviation points includes:

[0036] Divide one or more analysis periods containing the aforementioned deviation points into multiple benchmark evaluation periods;

[0037] The earliest deviation point in time is determined as the leading deviation point and set as the sample point;

[0038] Based on the ecological growth data corresponding to the sample points in multiple subsequent benchmark assessment periods, a sampling curve is constructed;

[0039] Based on the slope of the sampling curve, the endpoints of the sampling curve are marked as forward sampling nodes and reverse sampling nodes, respectively, and their corresponding measurement values ​​are recorded as forward sample data and reverse sample data, respectively, to jointly constitute the data sample.

[0040] In a preferred embodiment, the growth evaluation module is further used for:

[0041] Qualitative analysis is performed on the positive sample data to generate qualitative evaluation results, and quantitative analysis is performed on the negative sample data to generate quantitative evaluation results;

[0042] Furthermore, the final evaluation result is generated by combining the qualitative evaluation results with the quantitative evaluation results. Beneficial effects

[0043] This invention first divides ecological growth data into analysis periods based on standard bamboo shoot growth stage data, and then dynamically divides these analysis periods into benchmark assessment periods according to deviation values. This allows the assessment benchmark to closely align with the physiological rhythms and real-time conditions of bamboo shoots, overcoming the shortcomings of traditional methods that cannot adapt to the nonlinear changes in biological growth. This improves the accuracy and reliability of growth assessment. Furthermore, by identifying the earliest deviation point in time as the leading deviation point and using it as an anchor point to construct data samples for analysis in subsequent periods, the analysis can focus on the initial evolution of abnormalities. This enables early warning of potential growth risks, allowing for timely intervention and improving the timeliness and predictive ability of the assessment.

[0044] This invention separates data samples into positive and negative sample data, and performs qualitative and quantitative analyses on them respectively. Finally, it combines the qualitative and quantitative evaluation results to generate the final evaluation result. It can comprehensively evaluate from two dimensions: the compliance of growth status and the degree of abnormal deviation, overcoming the one-sidedness of single-indicator evaluation and making the final evaluation result more comprehensive and objective. Attached Figure Description

[0045] Figure 1 This is an overall flowchart of the present invention;

[0046] Figure 2 This is a flowchart of the present invention. Detailed Implementation

[0047] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments. It should be understood that the specific embodiments described herein are merely for explaining the invention and are not intended to limit the scope of protection of the invention.

[0048] Example 1

[0049] Please see Figure 1 As shown in this embodiment, a bamboo shoot growth assessment method based on ecological data analysis is disclosed. During implementation, based on the collection of bamboo shoot ecological growth data, deviation identification, and comprehensive assessment based on trend analysis, a final assessment result is generated to evaluate the growth status of bamboo shoots at different growth stages. This method is particularly suitable for environmentally sensitive areas or planting areas promoting high-value bamboo shoot products. The method includes the following steps:

[0050] When deviation points are identified in the ecological growth data of bamboo shoots, data samples are constructed based on the deviation points. The deviation points are the time points at which the deviation value of the ecological growth data relative to the preset standard growth stage data of bamboo shoots exceeds a preset deviation threshold at one or more time points.

[0051] Based on the analysis of the data sample, the final evaluation result is generated.

[0052] Specifically, data collection can be achieved by using sensor terminals or centralized collection devices deployed at bamboo shoot planting sites to periodically acquire multidimensional ecological growth data of the bamboo shoot growth environment. This data is used to comprehensively depict the instantaneous state of the bamboo shoot growth environment. The collected information includes, but is not limited to, air temperature, air humidity, soil temperature, soil humidity, soil pH value, or light intensity. The above data is collected in minutes or hours and automatically archived to the central database, providing the raw data foundation for subsequent analysis.

[0053] Furthermore, the continuous ecological growth data is divided into multiple analysis periods, such as the germination period and the vigorous growth period according to the physiological cycle of bamboo shoots. In order to establish a reliable comparison benchmark, historical growth data of bamboo shoot planting sites is obtained and used as the preset standard growth stage data of bamboo shoots. The standard growth stage data of bamboo shoots is a historical or theoretical ecological growth data sequence representing the ideal or normal growth state of bamboo shoots in a specific growth stage (such as the germination period and the vigorous growth period). It serves as a benchmark to measure the degree of deviation of the current growth state. The historical growth data is divided into the first historical period and the second historical period, and the first historical period is defined as the initial reference period, which is used to preliminarily assess whether it can represent the candidate period of the standard growth pattern. In order to screen out stable and representative segments from the historical data, the initial reference period is input into the preset comparison function. The comparison function generates the comparison output value by calculating the dispersion of key growth parameters within the period or the fit with the ideal model.

[0054] If the comparison output value is greater than the preset reference offset value, the initial reference period is determined as the baseline reference period. If the comparison output value is not greater than the reference offset value, the second historical period is set as the new initial reference period, and the steps of inputting the initial reference period into the preset comparison function and generating the comparison output value are repeated until the comparison output value is greater than the reference offset value. The initial reference period that meets the conditions is determined as the baseline reference period, which is a historical period that can be used as a reference for the standard growth pattern. The reference offset value is a preset numerical threshold used to determine whether the comparison output value has reached an acceptable level of stability. Only when the comparison output value is greater than the threshold value is the corresponding period considered to be sufficiently stable.

[0055] The comparison function is a computational model used to evaluate the stability of ecological growth data over a specified period. Its specific formula is as follows:

[0056] In the formula, This represents the comparison output value, which is a scalar value that measures the stability of the data. The smaller the variance of each parameter within a time period, the more stable the data, and the closer this value is to 1; conversely, the greater the data fluctuation, the closer this value is to 0. Represents the parameter weight, which means the weight of the parameter with respect to the first parameter. Preset weighting coefficients for the importance of each ecological growth parameter (such as soil moisture). ; Represents the parameter variance, which means the variance of the first parameter. Ecological growth parameters during time period The variance of the time series data within the specified time period is used to quantify its dispersion; the formula is input to the initial reference period. Time series data of N key ecological growth parameters within .

[0057] Furthermore, based on a defined benchmark reference period, and using it as the center, a preset first unit of time is extended forward and a preset second unit of time is extended backward to form a time interval. This interval is used to capture the dynamic change characteristics before and after the benchmark state. Based on the start and end points of this time interval, a deviation calculation template is constructed. This template essentially contains the feature vector or time series form of the dynamic change law of parameters under the standard growth model. It should be noted that the deviation calculation template is an ideal time series model representing the dynamic change law of multidimensional ecological growth data under the standard growth model, extracted from the benchmark reference period and its extended interval. For any given period within the current analysis time... For each test point, the corresponding comparison deviation value is obtained. This value is the difference or feature value between the current ecological growth data and the standard growth stage data of bamboo shoots at the test point. The deviation calculation template is used for processing, such as calculating the similarity through convolution operation or dynamic time warping algorithm, to generate template comparison results. This is used to quantify the degree of matching between the current state and the standard pattern. If the result is greater than or equal to the preset deviation judgment threshold, it indicates that the growth state at the current point of time has significantly deviated from the standard pattern, and it is marked as a deviation point. This is a specific point of time on the time axis where the ecological growth data has significantly deviated from the standard growth pattern.

[0058] The deviation point identification method can be as follows: For example, any test point within the analysis period can be defined as a base point, and it can be paired with adjacent time periods of preset time lengths before and after to form a deviation calculation period. The deviation calculation period is a local time period centered on a test point (base point) and including a small time window before and after it. It is used to calculate the instantaneous change characteristics of the point. The ecological growth data in this period is submitted to a preset difference calculation function. The function calculates the rate of change of the data in the period or the difference from the local mean to generate a deviation value. If the deviation value is greater than or equal to the preset deviation evaluation threshold, the base point is also marked as a deviation point. This method does not rely on a global historical template and is especially suitable for real-time anomaly detection.

[0059] The difference calculation function is a computational model used to quantify the degree of local variation in ecological growth data within a given period. Its specific formula is as follows:

[0060] In the formula, This indicates the difference output result, which means that during the deviation measurement period, the parameter... The maximum absolute value of the instantaneous rate of change (first derivative) indicates that the data fluctuates more drastically within that local time period. This represents the time series of parameters, meaning the period during which the deviation is measured. A function of how a key ecological growth parameter (such as air temperature) changes over time.

[0061] After identifying the deviation points, the sample construction and analysis phase begins. Based on the chronological order of the deviation points on the timeline, the earliest deviation point is identified as the leading deviation point and set as the sample point, serving as the trigger point for subsequent analyses. To further refine the division of the analysis period, the target reference time of this leading deviation point, i.e., the timestamp of the leading deviation node, is obtained, and its time difference with a preset baseline time is calculated and calibrated as the base time value. The base time value is the time interval between the target reference time and a preset baseline time, which serves as the origin of a unified time coordinate. Based on this base time value and the total duration of the analysis period, the number of time slices that can be accommodated is calculated, and the analysis period is divided into multiple consecutive time slices using this as the unit. These are basic time units of equal or unequal length, divided according to specific rules (such as the base time value). The end point of each time slice is defined as the end point of an independent baseline evaluation period. The baseline evaluation period consists of one or more consecutive time slices and is used for a single growth state assessment.

[0062] To construct data samples for in-depth analysis, the endpoints of two adjacent baseline assessment periods are obtained and marked as decision points. These are key nodes for determining state changes, and their corresponding measurements are read to form assessment nodes. Based on these assessment nodes, a preset sampling time interval is extended forward and backward to form candidate sampling areas. Each assessment node is a data structure containing the decision points and their corresponding ecological growth parameter measurements. To ensure sample validity, the duration of the candidate sampling area is determined to be greater than or equal to a preset sampling area duration threshold. A candidate sampling area must be greater than or equal to this threshold to be considered valid. If this threshold is not met, the sampling time interval is adjusted until the condition is satisfied, and the final sampling area is determined as the valid time region used to extract sample data. By connecting the endpoints of adjacent sampling areas, a sampling curve is constructed to reflect the macroscopic trend of ecological parameters over a period of time. The slope is calculated. If the slope is positive (upward trend), it indicates that the ecological parameters are changing in a direction that is conducive to growth. The endpoint is then marked as a positive sampling node, and its corresponding measurement value sequence is recorded as positive sample data. If the slope is negative (downward trend), it indicates that the stress is increasing. The endpoint is marked as a reverse sampling node, and the data is recorded as reverse sample data.

[0063] In the result judgment stage, a comprehensive evaluation combining qualitative and quantitative analysis is conducted on the constructed data samples. Qualitative analysis is performed on the positive sample data to determine whether the growth-promoting conditions are truly effective. For example, it is determined whether the value of the positive sample data is lower than the preset lower growth threshold, or whether its trend deviates from the trend of the bamboo shoot standard growth stage data. If either judgment is correct, a qualitative evaluation result indicating the failure state is generated. At the same time, quantitative analysis is performed on the reverse sample data to calculate its trend value, and this trend value is matched with the preset scoring criteria to generate a quantitative numerical score as the quantitative evaluation result. The trend value is a value calculated from the reverse sample data that can quantify the degree of stress or the rate of deterioration, such as the absolute value of the slope or the total magnitude of the change.

[0064] It should be noted that qualitative evaluation results are non-numerical classifications of growth status, such as judging it as normal, ineffective, or improved. Quantitative evaluation results are numerical assessments of growth status, usually expressed as a specific score or indicator. The scoring standard is a pre-defined mapping rule or lookup table that converts the calculated trend value into a standardized numerical score. The numerical score is a standardized score representing the severity of growth stress, generated by quantitative analysis based on the scoring standard.

[0065] Furthermore, the qualitative and quantitative evaluation results are input together into the comprehensive judgment model. The model weighs the results according to the preset judgment rules and combines the two to generate the final evaluation result. As another analysis path, qualitative analysis can generate qualitative evaluation results indicating the normal state for positive sample data, while quantitative analysis extracts the measurement difference corresponding to the reverse sample data as a reference quantity. After inputting it into the preset difference function, a verification score is generated as the quantitative evaluation result.

[0066] The comprehensive judgment model is a computational model used to integrate qualitative and quantitative analysis results to generate a final evaluation conclusion. Its specific formula is as follows:

[0067] In the formula, This indicates the final evaluation result, which is a comprehensive assessment score that combines the effectiveness of growth improvement with the severity of stress. If the qualitative evaluation is failure ( If ), then the final result is 0; This represents the qualitative evaluation result (Boolean value, 1 represents normal / valid, 0 represents invalid), and its meaning is a flag bit indicating whether the positive sample data is valid; It represents the quantitative evaluation result (numerical score), which means a quantitative score of the reverse sample data (stress); This represents the weighting coefficient, which is a preset weight used to balance the proportion of the base score and the coercion score in the final result. Its value range is [0, 1]. This represents the base score, which is the initial score given when the qualitative evaluation is valid.

[0068] The difference function is a computational model used to convert raw measurement differences into standardized scores. Its specific formula is as follows:

[0069] In the formula, This represents the verification score, which is a standardized quantitative evaluation score. The larger the measurement difference, the lower the score. This represents the highest score, which is the preset upper limit of the score. This represents the measurement difference, which indicates the original stress level index input. This represents the critical difference, which is a preset critical difference. When the measurement difference reaches this value, the verification score drops to 0.

[0070] In the results output stage, the generated final evaluation results are compared with preset evaluation result grading thresholds. These thresholds define multiple grading ranges. Based on the grading range to which the final evaluation result belongs, the corresponding alarm level is matched and determined, such as excellent, normal, attention, and warning. Control suggestions can also be pushed to management personnel simultaneously. This embodiment reflects the closed-loop logic from raw data collection to comprehensive judgment. Its combination of qualitative and quantitative analysis can take into account the dynamic balance between growth incentives and stress inhibition in the ecosystem, realize accurate and dynamic evaluation of bamboo shoot growth status, and generate final evaluation results.

[0071] Example 2

[0072] This embodiment discloses a bamboo shoot growth assessment system based on ecological data analysis, used to implement the bamboo shoot growth assessment method based on ecological data analysis in Embodiment 1 above. Based on real-time collected ecological growth data, when abnormal growth is identified, the system automatically constructs data samples and generates accurate final assessment results and alarm levels, thereby providing decision support for the refined and intelligent management of bamboo shoots. The system includes the following modules:

[0073] The deviation identification module is used to continuously receive and process bamboo shoot ecological growth data from the sensor network, and identify deviation points in the ecological growth data. The ecological growth data may include, but is not limited to, at least one of air temperature, air humidity, soil temperature, soil humidity, soil pH value, or light intensity.

[0074] In a specific execution process, real-time collected ecological growth data is aligned with preset standard bamboo shoot growth stage data. The standard bamboo shoot growth stage data are ideal variation curves or ranges of various ecological indicators at different growth stages, derived from historical experience or agricultural research. For any point in time within the analysis period, it is defined as a baseline, and this baseline is paired with adjacent time periods of preset duration before and after it to set a deviation calculation period. The ecological growth data within this deviation calculation period and the corresponding standard bamboo shoot growth stage data are submitted to a preset time series comparison function. This function calculates the degree of difference between the two and generates a deviation value. This deviation value is compared with a preset deviation threshold. If the deviation value is greater than or equal to the threshold, it indicates a significant deviation in the growth state of the bamboo shoot at that time point, and the baseline is marked as a deviation point.

[0075] The growth assessment module is used to construct data samples based on deviation points and generate final assessment results based on the analysis of the data samples.

[0076] The data sample construction process involves dividing one or more analysis periods containing deviation points into multiple benchmark assessment periods according to a preset time granularity (e.g., hourly or half-day). Among all identified deviation points, the earliest one is identified as the leading deviation point and set as the sample point for analysis. Starting from this sample point, the corresponding ecological growth data in multiple subsequent benchmark assessment periods are tracked. These continuous data points together form a sampling curve, which intuitively reflects the trajectory of growth data changes since the anomaly occurred. Further analysis of the slope or trend of the sampling curve is performed. According to preset rules, for example, if the slope is positive and exceeds a certain trend threshold, the growth status is considered to be developing in a positive direction, and the end point of the sampling curve is marked as a positive sampling node. Conversely, if the slope is negative or growth stagnates, it is marked as a negative sampling node. The measurement values ​​corresponding to the positive and negative sampling nodes are recorded as positive sample data and negative sample data, respectively, which together constitute the data sample for subsequent analysis.

[0077] The final evaluation result is generated based on the constructed data sample. This process is divided into two dimensions: qualitative and quantitative. For positive sample data, qualitative analysis is performed. Specifically, it is determined whether the value of the positive sample data is lower than a preset lower growth threshold (representing insufficient growth vitality), or whether its trend of change significantly deviates from the expected trend of bamboo shoot standard growth stage data. If either judgment is correct, a qualitative evaluation result indicating "failure state" is generated, indicating that the growth recovery is not ideal. For negative sample data, quantitative analysis is performed. The trend value of the negative sample data (e.g., the rate of decline) is calculated and matched with a preset scoring standard. This scoring standard maps different ranges of trend values ​​to different numerical scores, thereby generating a quantitative numerical score as a quantitative evaluation result. This score reflects the degree of growth deterioration. Combining the qualitative and quantitative evaluation results, the final evaluation result is generated. For example, if the qualitative evaluation result is "failure state", the final evaluation result is directly determined to be the worst level. Otherwise, a comprehensive evaluation conclusion is generated based on the score of the quantitative evaluation result.

[0078] The alarm generation module receives the final evaluation results from the growth evaluation module and generates an alarm level that is perceptible to the user based on the results.

[0079] In a specific execution process, multiple evaluation result grading thresholds are preset. These thresholds divide the possible range of the final evaluation result into multiple grading ranges, such as excellent, normal, attention, and warning. When the final evaluation result is received, it is compared with the evaluation result grading thresholds to determine its grading range. The preset label corresponding to this range is output as the alarm level. This alarm level can be highlighted on the user interface of the monitoring platform or triggered by SMS, email, or other notification mechanisms so that managers can understand the growth status of bamboo shoots in a timely manner and take corresponding measures.

[0080] The above are merely preferred embodiments of this application and are not intended to limit this application. For those skilled in the art, this application can have various modifications and variations. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for evaluating bamboo shoot growth based on ecological data analysis, characterized in that, Includes the following steps: When deviations are identified in the ecological growth data of bamboo shoots, data samples are constructed based on the deviations. Based on the analysis of the data samples, a final evaluation result is generated; The deviation point is the time point at which the deviation value of the ecological growth data relative to the preset standard growth stage data of bamboo shoots exceeds a preset deviation threshold at one or more time points. The process of constructing data samples based on the deviation points includes: Divide one or more analysis periods containing the aforementioned deviation points into multiple benchmark evaluation periods; The earliest deviation point in time is determined as the leading deviation point and set as the sample point; Based on the ecological growth data corresponding to the sample points in multiple subsequent benchmark assessment periods, a sampling curve is constructed; Based on the slope of the sampling curve, the endpoints of the sampling curve are marked as forward sampling nodes and reverse sampling nodes, respectively, and their corresponding measurement values ​​are recorded as forward sample data and reverse sample data, respectively, to jointly constitute the data sample; The identification of deviations in the ecological growth data of bamboo shoots includes: For any time point to be measured within the analysis period, the time point to be measured is defined as the base point; The base point is paired with adjacent time periods of a preset time length before and after the base point to set the deviation calculation time period; The ecological growth data within the deviation measurement period is submitted to a preset difference calculation function to generate a deviation value; Furthermore, if the deviation value is greater than or equal to a preset deviation threshold, the base point is marked as a deviation point; Based on the analysis of the data sample, a final evaluation result is generated, including: Qualitative analysis is performed on the positive sample data to generate qualitative evaluation results; Quantitative analysis is performed on the reverse sample data to generate quantitative evaluation results; The final evaluation result is generated by combining the qualitative evaluation results with the quantitative evaluation results; Qualitative analysis of the positive sample data includes: Determine whether the value of the positive sample data is lower than a preset growth lower limit threshold, or determine whether the trend of the positive sample data deviates from the trend of the standard growth stage data. If either determination is yes, then generate a qualitative evaluation result indicating the failure state. Quantitative analysis of the reverse sample data includes: The trend value of the reverse sample data is calculated, and the trend value is matched with the preset scoring criteria to generate a quantitative numerical score as a quantitative evaluation result.

2. The bamboo shoot growth assessment method based on ecological data analysis according to claim 1, characterized in that, The method also includes the following steps: Set a threshold for the evaluation result classification, divide it into multiple classification ranges, and map the final evaluation result to the corresponding classification range to generate an alarm level.

3. The bamboo shoot growth assessment method based on ecological data analysis according to claim 1, characterized in that, The ecological growth data includes: air temperature, air humidity, soil temperature, soil humidity, soil pH value, or light intensity.

4. A bamboo shoot growth assessment system based on ecological data analysis, used to implement the bamboo shoot growth assessment method based on ecological data analysis as described in any one of claims 1-3, characterized in that, include: The deviation identification module is used to identify deviation points in the ecological growth data of bamboo shoots. The deviation point is the time point at which the deviation value of the ecological growth data relative to the preset standard growth stage data of bamboo shoots exceeds a preset deviation threshold at one or more time points. The growth assessment module is used to construct data samples based on the deviation points and generate final assessment results based on the analysis of the data samples. And an alarm generation module, used to generate alarm levels based on the final evaluation results; The process of constructing data samples based on the deviation points includes: Divide one or more analysis periods containing the aforementioned deviation points into multiple benchmark evaluation periods; The earliest deviation point in time is determined as the leading deviation point and set as the sample point; Based on the ecological growth data corresponding to the sample points in multiple subsequent benchmark assessment periods, a sampling curve is constructed; Based on the slope of the sampling curve, the endpoints of the sampling curve are marked as forward sampling nodes and reverse sampling nodes, respectively, and their corresponding measurement values ​​are recorded as forward sample data and reverse sample data, respectively, to jointly constitute the data sample.

5. The bamboo shoot growth assessment system based on ecological data analysis according to claim 4, characterized in that, The growth assessment module is also used for: Qualitative analysis is performed on the positive sample data to generate qualitative evaluation results, and quantitative analysis is performed on the negative sample data to generate quantitative evaluation results; Furthermore, the final evaluation result is generated by combining the qualitative evaluation results with the quantitative evaluation results.

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