A method, system, equipment and medium for monitoring the bolting status of radishes

Abstract

This invention discloses a method, system, device, and medium for monitoring the bolting status of radishes, relating to the field of agricultural information monitoring technology. The method includes the following steps: acquiring environmental parameters of the target radish plant; acquiring the effective accumulated temperature and photoperiod effect accumulation of the target radish plant at the current time; acquiring monitoring images of the target radish plant; acquiring the relative growth rate and plant height growth acceleration of the target radish plant; inputting the effective accumulated temperature, photoperiod effect accumulation, and relative growth rate into a preset multi-source feature fusion model to obtain bolting feature values; acquiring the dynamic threshold of the target radish plant at the current time; determining whether the bolting judgment condition has been met at the current time; if so, outputting bolting alarm information. The bolting judgment condition is: the bolting feature value is greater than the dynamic threshold, and the plant height growth acceleration is greater than a preset critical value. This invention has the advantage of improving the accuracy of radish bolting monitoring.

Description

Technical Field

[0001] This invention relates to the field of agricultural information monitoring technology, and in particular to a method, system, equipment and medium for monitoring the bolting status of radishes. Background Technology

[0002] Radishes thrive in sunlight, particularly long-day sunlight. Under strong sunlight, they develop and bolt more quickly. Therefore, long days are essential for radishes to flower and bolt. Generally, radishes planted in spring bolt more easily than those planted in winter. However, due to the low temperatures in winter, although flower buds have already differentiated, the short daylight hours make it difficult to bolt. Therefore, during the sowing period, the temperature should be kept above 11℃ to promote flower bud differentiation. During the growing season, a lower temperature should be maintained to prevent bolting.

[0003] Currently, the main method for monitoring the growth status of radish bolting relies on manual methods. However, manual judgment is highly subjective, lacks quantitative standards, and cannot be monitored continuously in real time, thus lacking immediacy. Existing monitoring methods can use machine vision recognition technology to continuously monitor the characteristics of radish bolting, but they can only detect obvious bolting characteristics and trigger an alarm. Furthermore, the monitoring data mainly relies on changes in the height of the radish plant, resulting in limited data, making it difficult to accurately monitor the characteristics of radish bolting, and prone to misjudgment. Summary of the Invention

[0004] The main objective of this invention is to provide a method, system, device, and medium for monitoring the bolting state of radishes, aiming to solve the technical problem of low accuracy in monitoring radish bolting using existing methods.

[0005] To achieve the above objectives, the present invention provides a method for monitoring the bolting status of radishes, comprising the following steps:

[0006] Obtain the environmental parameters of the target radish plant; these parameters include ambient temperature and light intensity.

[0007] Based on environmental parameters, obtain the effective accumulated temperature and photoperiod effect accumulation of the target radish plant at the current time;

[0008] Acquire monitoring images of the target radish plants;

[0009] Based on the monitoring images, the relative growth rate and plant height growth acceleration of the target radish plant were obtained;

[0010] The effective accumulated temperature, the cumulative photoperiod effect, and the relative growth rate are input into a preset multi-source feature fusion model to obtain bolting feature values.

[0011] Obtain the dynamic threshold of the target radish plant at the current time;

[0012] Determine whether the bolting condition has been met at the current time. If yes, output a bolting alarm message. If no, return to obtain the environmental parameters of the target radish plant. The bolting condition is: the bolting characteristic value is greater than the dynamic threshold and the plant height growth acceleration is greater than the preset critical value.

[0013] Alternatively, the expression for the multi-source feature fusion model is:

[0014] S(t)=α·ΔT+β·ΔL+γ·ΔV;

[0015] In the formula, S(t) is the bolting characteristic value at the current time t, ΔT is the effective accumulated temperature accumulation, ΔL is the photoperiod effect accumulation, ΔV is the relative growth rate, α is the first weight value, β is the second weight value, and γ is the third weight value.

[0016] Where ΔV = ln(H / H0), H is the current height of the target radish plant, and H0 is the reference height.

[0017] Optionally, the method for determining the first weight value α, the second weight value β, and the third weight value γ is as follows:

[0018] Obtain the first weight value α of the temperature influence at the current time. The expression for α is:

[0019] α = α0·(1+K·G)

[0020] In the formula, α0 is the initial weight value of temperature influence, K is the adjustment coefficient, K is set according to the accumulated temperature requirement characteristics of the target radish plant variety, and G is the minimum effective accumulated temperature required for the target radish plant of the corresponding variety to complete the vernalization stage.

[0021] The values ​​of the second weight value β and the third weight value γ are adaptively adjusted based on the first weight value α.

[0022] Optionally, the dynamic threshold of the target radish plant at the current time is obtained, including:

[0023] Obtain the photoperiod parameter η and growth rate coefficient λ of the target radish plant at the current time t;

[0024] The photoperiod parameter η and the growth rate coefficient λ are input into a preset dynamic adjustment model to obtain a dynamic threshold; the expression of the dynamic adjustment model is:

[0025] δ=δ0[1+η·sin(2πt / 24)]·e λt ;

[0026] In the formula, δ is the dynamic threshold, δ0 is the initial threshold, and e is the natural constant.

[0027] Optionally, the expression for the optical period parameter η is:

[0028] η = η0 · (L / L0) ε ;

[0029] In the formula, η0 is the photoperiod reference correction coefficient, L is the real-time light intensity, L0 is the standard photoperiod of the target radish plant of the corresponding variety, and ε is the light response index.

[0030] Alternatively, the expression for the growth rate coefficient λ is:

[0031] ;

[0032] In the formula, λ max t1 is the vernalization completion time of the target radish plant, t2 is the bolting time of the target radish plant, and V is the growth response rate of the target radish plant.

[0033] Optionally, λ max The expression is:

[0034] λ max =λ0+∑β k SNP k ;

[0035] In the formula, λ0 is the initial value determined based on the historical growth data of the target radish plant of the corresponding variety, and β k SNP is the genetic effect coefficient. k This is the genotype encoding.

[0036] To achieve the above objectives, the present invention also provides a radish bolting status monitoring system, comprising:

[0037] The parameter acquisition module is used to acquire the environmental parameters of the target radish plant; among which, the environmental parameters include ambient temperature and light intensity.

[0038] The first data processing module is used to obtain the effective accumulated temperature and photoperiod effect accumulation of the target radish plant at the current time based on environmental parameters.

[0039] The image acquisition module is used to acquire monitoring images of the target radish plant;

[0040] The second data processing module is used to obtain the relative growth rate and plant height growth acceleration of the target radish plant based on the monitoring images.

[0041] The calculation module is used to input the effective accumulated temperature, photoperiod effect accumulation and relative growth rate into a preset multi-source feature fusion model to obtain bolting feature values;

[0042] The threshold acquisition module is used to acquire the dynamic threshold of the target radish plant at the current time.

[0043] The third data processing module is used to determine whether the bolting determination condition has been met at the current time. If so, it outputs a bolting alarm message; otherwise, it returns to obtain the environmental parameters of the target radish plant. The bolting determination condition is: the bolting characteristic value is greater than the dynamic threshold, and the plant height growth acceleration is greater than the preset critical value.

[0044] To achieve the above objectives, the present invention also provides a computer device, which includes a memory and a processor, wherein the memory stores a computer program and the processor executes the computer program to implement the above-described method.

[0045] To achieve the above objectives, the present invention also provides a computer-readable storage medium storing a computer program, wherein a processor executes the computer program to implement the above-described method.

[0046] The beneficial effects that this invention can achieve are as follows:

[0047] This invention calculates the effective accumulated temperature based on the ambient temperature of the target radish plant and the cumulative photoperiod effect based on light intensity. It also combines monitoring images of the target radish plant's growth to calculate the relative growth rate and plant height acceleration to characterize its growth. Therefore, this invention integrates representative influencing factors such as ambient temperature, light intensity, and growth status to comprehensively judge the bolting status of the radish. After quantifying these influencing factors, the quantified values ​​of the effective accumulated temperature, cumulative photoperiod effect, and relative growth rate are input into a preset multi-source feature fusion model to quantify and calculate the bolting characteristic value. Considering that the probability of bolting varies at different growth stages, a dynamic threshold is selected based on the target radish plant's current time to improve accuracy. A dual-condition joint judgment mechanism is adopted: the bolting judgment condition of this invention is that bolting alarm information is only output when the bolting characteristic value is greater than the dynamic threshold and the plant height acceleration is greater than a preset critical value, avoiding the random errors that may occur with a single judgment mechanism. In summary, this invention can combine multi-source data for comprehensive evaluation, effectively correlate environmental factors with growth status, reduce the risk of data distortion caused by single data, and adopt a dual-condition joint judgment mechanism, thereby improving the overall accuracy of monitoring radish bolting. Attached Figure Description

[0048] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the accompanying drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to scale.

[0049] Figure 1 This is a flowchart illustrating a method for monitoring the bolting status of radishes according to an embodiment of the present invention;

[0050] Figure 2 This is a schematic diagram of the framework structure of a radish bolting status monitoring system according to an embodiment of the present invention.

[0051] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0052] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0053] It should be noted that if the embodiments of the present invention involve descriptions such as "first" and "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined with "first" and "second" may explicitly or implicitly include at least one of those features. Furthermore, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by the present invention.

[0054] Example 1

[0055] Reference Figure 1 This embodiment provides a method for monitoring the bolting status of radishes, including the following steps:

[0056] Obtain the environmental parameters of the target radish plant; these parameters include ambient temperature and light intensity.

[0057] Based on environmental parameters, obtain the effective accumulated temperature and photoperiod effect accumulation of the target radish plant at the current time;

[0058] Acquire monitoring images of the target radish plants;

[0059] Based on the monitoring images, the relative growth rate and plant height growth acceleration of the target radish plant were obtained;

[0060] The effective accumulated temperature, the cumulative photoperiod effect, and the relative growth rate are input into a preset multi-source feature fusion model to obtain bolting feature values.

[0061] Obtain the dynamic threshold of the target radish plant at the current time;

[0062] Determine whether the bolting condition has been met at the current time. If yes, output a bolting alarm message. If no, return to obtain the environmental parameters of the target radish plant. The bolting condition is: the bolting characteristic value is greater than the dynamic threshold and the plant height growth acceleration is greater than the preset critical value.

[0063] In this embodiment, the effective accumulated temperature can be calculated based on the ambient temperature of the target radish plant, and the cumulative photoperiod effect can be calculated based on the light intensity. Simultaneously, the relative growth rate and plant height acceleration of the target radish plant can be calculated by combining monitoring images of the plant's growth to characterize its growth status. Therefore, this invention integrates representative influencing factors such as ambient temperature, light intensity, and growth status to comprehensively judge the bolting status of the radish. After quantifying and evaluating these influencing factors, the quantified values ​​of the effective accumulated temperature, cumulative photoperiod effect, and relative growth rate are input into a preset multi-source feature fusion model to quantify and calculate the bolting characteristic value. Considering that the probability of bolting varies at different growth stages, a corresponding dynamic threshold is selected based on the current time of the target radish plant to improve the accuracy of the judgment. A dual-condition joint judgment mechanism is adopted, namely, the bolting judgment condition of this invention: bolting alarm information is only output when the bolting characteristic value is greater than the dynamic threshold and the plant height acceleration is greater than a preset critical value, avoiding the random errors that may occur with a single judgment mechanism. In summary, this invention can combine multi-source data for comprehensive evaluation, effectively correlate environmental factors with growth status, reduce the risk of data distortion caused by single data, and adopt a dual-condition joint judgment mechanism, thereby improving the overall accuracy of monitoring radish bolting.

[0064] It should be noted that effective accumulated temperature is the sum of effective temperatures during a certain growth stage or the entire growth stage of a crop, that is, the sum of the daily average temperature difference between the crop and the biological zero point over a certain period of time. Effective accumulated temperature is an indicator reflecting the heat demand of biological growth and development or measuring regional heat resources, and is often used in agricultural meteorological forecasting. Since effective accumulated temperature excludes temperatures below the biological lower limit and above the upper limit, it basically reflects the linear relationship between crop growth rate and temperature. Therefore, the cumulative amount of effective accumulated temperature can reflect the continuous influence of environmental temperature on bolting. The effect of suitable photoperiod induction can be retained in the plant without disappearing; this phenomenon is called the photoperiod effect. Therefore, the cumulative degree of photoperiod effect can quantify the cumulative contribution of the photoperiod effect. The above monitoring images can be acquired at preset intervals t0, and by comparing two monitoring images, the relative growth rate and plant height growth acceleration can be quantitatively calculated, where the plant height growth acceleration can be expressed as d. 2 H / dt0 2 H represents the current height of the target radish plant, and d represents the differential symbol.

[0065] As an optional implementation method, the expression for the multi-source feature fusion model is:

[0066] S(t)=α·ΔT+β·ΔL+γ·ΔV;

[0067] In the formula, S(t) is the bolting characteristic value at the current time t, ΔT is the effective accumulated temperature accumulation, ΔL is the photoperiod effect accumulation, ΔV is the relative growth rate, α is the first weight value, β is the second weight value, and γ is the third weight value.

[0068] Where ΔV = ln(H / H0), H is the current height of the target radish plant, and H0 is the reference height.

[0069] In this embodiment, the quantitative values ​​of effective accumulated temperature ΔT, photoperiod effect accumulation ΔL, and relative growth rate ΔV are superimposed in the above formula. Based on the contribution ratio of ambient temperature, light intensity, and plant height to bolting, corresponding weight values ​​α, β, and γ are assigned respectively, so that bolting characteristic values ​​with reference and guidance can be accurately calculated. ΔV is obtained by taking the natural logarithm of the ratio of the current height value H of the target radish plant to the reference height value H0, which can effectively characterize the relative growth rate of the radish plant.

[0070] It should be noted that the effective accumulated temperature accumulation ΔT can be expressed as the sum of the effective accumulated temperature accumulation from the initial time to the current time t, and the cumulative degree of photoperiod effect can be expressed as the weighted sum of the light intensity in time segments (such as per hour) to quantify the cumulative contribution of the photoperiod effect.

[0071] As an optional implementation, the method for determining the first weight value α, the second weight value β, and the third weight value γ is as follows:

[0072] Obtain the first weight value α of the temperature influence at the current time. The expression for α is:

[0073] α = α0·(1+K·G)

[0074] In the formula, α0 is the initial weight value of temperature influence, K is the adjustment coefficient, K is set according to the accumulated temperature requirement characteristics of the target radish plant variety, and G is the minimum effective accumulated temperature required for the target radish plant of the corresponding variety to complete the vernalization stage.

[0075] The values ​​of the second weight value β and the third weight value γ are adaptively adjusted based on the first weight value α.

[0076] In this embodiment, considering that different radish varieties are affected by temperature to varying degrees, an initial weight value α0, such as 0.35, can be set based on the calculation formula of the first weight value α. Then, the initial weight value α0 is corrected by introducing the product of the adjustment coefficient K and the minimum effective accumulated temperature G (unit: ℃·d) required to complete the vernalization stage. K can be set according to the accumulated temperature requirements of the target radish plant variety, for example, K=0.2 for cold-resistant varieties and K=0.5 for warm-loving varieties. After determining the first weight value α, the corresponding adjustments are made. The values ​​of the second weight value β and the third weight value γ, for example, before adjustment β=0.35, γ=0.3, after adjustment the first weight value α=0.45, the adjustment amount compared to the initial weight value 0.35 is 0.1. The adjustment amount is evenly distributed to the second weight value β and the third weight value γ for adaptive adjustment, that is, after adjustment β=0.3, γ=0.25. Based on the above method for determining the first weight value α, the second weight value β and the third weight value γ, the multi-source feature fusion model can be modified according to different varieties of radish to improve the calculation accuracy of bolting feature value.

[0077] As an optional implementation method, obtaining the dynamic threshold of the target radish plant at the current time includes:

[0078] Obtain the photoperiod parameter η and growth rate coefficient λ of the target radish plant at the current time t;

[0079] The photoperiod parameter η and the growth rate coefficient λ are input into a preset dynamic adjustment model to obtain a dynamic threshold; the expression of the dynamic adjustment model is:

[0080] δ=δ0[1+η·sin(2πt / 24)]·e λt ;

[0081] In the formula, δ is the dynamic threshold, δ0 is the initial threshold, and e is the natural constant.

[0082] In this embodiment, since the effects of diurnal light variation on bolting differ at different growth stages, resulting in varying growth rates, a photoperiod parameter η and a growth rate coefficient λ at the current time t are introduced to accurately correct the dynamic adjustment model. This allows for the accurate calculation of a dynamic threshold based on the correlation between light conditions and growth rate at different growth stages of the radish. In the above formula, the initial threshold δ0 is set according to the characteristics of the radish variety (e.g., a lower value is set for early-maturing varieties), and sin(2πt / 24) serves as the periodic correction term. The threshold is adjusted with a 24-hour period to simulate the effect of diurnal light variation on bolting. λt Then, as an exponential growth term, it represents an exponential increase over time, reflecting the gradual increase in the threshold requirements as the growth stage progresses. η and λ can be used as adjustment parameters, where η can control the diurnal fluctuation range (such as reducing the value of η under cloudy weather), and λ is dynamically adjusted through the genetic parameters of the variety.

[0083] As an optional implementation, the expression for the optical period parameter η is:

[0084] η = η0 · (L / L0) ε ;

[0085] In the formula, η0 is the photoperiod reference correction coefficient, L is the real-time light intensity, L0 is the standard photoperiod of the target radish plant of the corresponding variety, and ε is the light response index.

[0086] In this embodiment, based on the above formula, when the real-time light intensity L is greater than L0, η is amplified exponentially to enhance the weight of the photoperiod effect. Conversely, when L is less than L0, η is correspondingly attenuated to reduce the impact of insufficient light on the threshold. At the same time, the parameter is constrained by the light response index ε, which is calibrated through variety light sensitivity experiments (e.g., ε=1.2 for light-loving varieties and ε=0.8 for shade-tolerant varieties), thereby achieving accurate adjustment of the photoperiod parameter η according to the actual light conditions.

[0087] As an optional implementation method, the expression for the growth rate coefficient λ is:

[0088] ;

[0089] In the formula, λ max t1 is the vernalization completion time of the target radish plant, t2 is the bolting time of the target radish plant, and V is the growth response rate of the target radish plant.

[0090] In this embodiment, based on the above formula, the growth rate coefficient λ can be dynamically adjusted according to the growth stage division of radishes. Specifically, during the vegetative growth stage (i.e., t < t1), the growth rate coefficient λ = 0. At this time, the dynamic threshold is only dominated by the reference value δ0 and the photoperiod effect. During the reproductive transition stage (t1 ≤ t ≤ t2), λ increases according to a saturation curve. In the formula, V controls the growth rate (for example, when V = 0.1, it takes about 10 days to reach 90% of the maximum value), thus reflecting that the plant accelerates the transition to reproductive growth after vernalization. During the bolting stage (i.e., t > t2), λ stabilizes at the maximum value λ max , and the dynamic threshold continuously increases with the growth process to forcibly match the physiological needs of the plant's rapid growth, thereby realizing the dynamic adjustment of λ according to the growth stage division of radishes to further improve the calculation accuracy of the dynamic threshold.

[0091] It should be noted that the vernalization completion time t1 and the bolting time t2 in the above formula are two key time points, where the vernalization completion time t1 is determined by the vernalization experiment (for example, starting to calculate after 15 days of low-temperature treatment), and the bolting time t2 is automatically calibrated by detecting the mutation point of the plant height acceleration.

[0092] As an optional embodiment, the expression of λ max is:

[0093] λ max = λ0 + ∑β k ·SNP k ;

[0094] In the formula, λ0 is the initial value calibrated according to the historical growth data of the target radish plants of the corresponding variety, β k is the genetic effect coefficient, and SNP​​​​​​​​​​​​​​​​​​​​​​Based on the same inventive concept as the foregoing embodiments, this embodiment also provides a radish bolting status monitoring system, including:

[0098] The parameter acquisition module is used to acquire the environmental parameters of the target radish plant; among which, the environmental parameters include ambient temperature and light intensity.

[0099] The first data processing module is used to obtain the effective accumulated temperature and photoperiod effect accumulation of the target radish plant at the current time based on environmental parameters.

[0100] The image acquisition module is used to acquire monitoring images of the target radish plant;

[0101] The second data processing module is used to obtain the relative growth rate and plant height growth acceleration of the target radish plant based on the monitoring images.

[0102] The calculation module is used to input the effective accumulated temperature, photoperiod effect accumulation and relative growth rate into a preset multi-source feature fusion model to obtain bolting feature values;

[0103] The threshold acquisition module is used to acquire the dynamic threshold of the target radish plant at the current time.

[0104] The third data processing module is used to determine whether the bolting determination condition has been met at the current time. If so, it outputs a bolting alarm message; otherwise, it returns to obtain the environmental parameters of the target radish plant. The bolting determination condition is: the bolting characteristic value is greater than the dynamic threshold, and the plant height growth acceleration is greater than the preset critical value.

[0105] The explanations and examples of the modules in this embodiment can be found in the methods of the foregoing embodiments, and will not be repeated here.

[0106] Example 3

[0107] Based on the same inventive concept as the foregoing embodiments, this embodiment provides a computer device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method.

[0108] Example 4

[0109] Based on the same inventive concept as the foregoing embodiments, this embodiment provides a computer-readable storage medium storing a computer program, and a processor executes the computer program to implement the above-described method.

[0110] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A method for monitoring the bolting state of radishes, characterized in that, Includes the following steps: Obtain the environmental parameters of the target radish plant; these parameters include ambient temperature and light intensity. Based on environmental parameters, obtain the effective accumulated temperature and photoperiod effect accumulation of the target radish plant at the current time; Acquire monitoring images of the target radish plants; Based on the monitoring images, the relative growth rate and plant height growth acceleration of the target radish plant were obtained; The effective accumulated temperature, photoperiod effect accumulation, and relative growth rate are input into a pre-defined multi-source feature fusion model to obtain bolting feature values; the expression of the multi-source feature fusion model is: S(t)=α·ΔT+β·ΔL+γ·ΔV; In the formula, S(t) is the bolting characteristic value at the current time t, ΔT is the effective accumulated temperature accumulation, ΔL is the photoperiod effect accumulation, ΔV is the relative growth rate, α is the first weight value, β is the second weight value, and γ is the third weight value; where ΔV = ln(H / H0), H is the current height of the target radish plant, and H0 is the reference height value; the method for determining the first weight value α, the second weight value β, and the third weight value γ is as follows: obtain the first weight value α of the temperature influence at the current time, and the expression for α is: α = α0·(1+K·G) In the formula, α0 is the initial weight value of temperature influence, K is the adjustment coefficient, K is set according to the accumulated temperature requirement characteristics of the target radish plant variety, G is the minimum effective accumulated temperature required for the target radish plant of the corresponding variety to complete the vernalization stage; the values ​​of the second weight value β and the third weight value γ are adaptively adjusted according to the first weight value α. Obtain the dynamic threshold of the target radish plant at the current time; Determine whether the bolting condition has been met at the current time. If yes, output a bolting alarm message. If no, return to obtain the environmental parameters of the target radish plant. The bolting condition is: the bolting characteristic value is greater than the dynamic threshold and the plant height growth acceleration is greater than the preset critical value.

2. The method for monitoring the bolting state of radishes as described in claim 1, characterized in that, Obtain the dynamic threshold of the target radish plant at the current time, including: Obtain the photoperiod parameter η and growth rate coefficient λ of the target radish plant at the current time t; The photoperiod parameter η and the growth rate coefficient λ are input into a preset dynamic adjustment model to obtain a dynamic threshold; the expression of the dynamic adjustment model is: δ=δ0[1+η·sin(2πt / 24)]·e λt ; In the formula, δ is the dynamic threshold, δ0 is the initial threshold, and e is the natural constant.

3. The method for monitoring the bolting state of radishes as described in claim 2, characterized in that, The expression for the optical period parameter η is: ； In the formula, η0 is the photoperiod reference correction coefficient, L is the real-time light intensity, L0 is the standard photoperiod of the target radish plant of the corresponding variety, and ε is the light response index.

4. The method for monitoring the bolting state of radishes as described in claim 2, characterized in that, The expression for the growth rate coefficient λ is: ; In the formula, λ max t1 is the vernalization completion time of the target radish plant, t2 is the bolting time of the target radish plant, and V is the growth response rate of the target radish plant.

5. The method for monitoring the bolting state of radishes as described in claim 4, characterized in that, λ max The expression is: l max =λ0+∑β k ·SNP k ; In the formula, λ0 is the initial value determined based on the historical growth data of the target radish plant of the corresponding variety, and β k SNP is the genetic effect coefficient. k This is the genotype encoding.

6. A radish bolting status monitoring system, characterized in that, include: The parameter acquisition module is used to acquire the environmental parameters of the target radish plant; among which, the environmental parameters include ambient temperature and light intensity. The first data processing module is used to obtain the effective accumulated temperature and photoperiod effect accumulation of the target radish plant at the current time based on environmental parameters. The image acquisition module is used to acquire monitoring images of the target radish plant; The second data processing module is used to obtain the relative growth rate and plant height growth acceleration of the target radish plant based on the monitoring images. The calculation module is used to input the effective accumulated temperature, photoperiod effect accumulation, and relative growth rate into a preset multi-source feature fusion model to obtain bolting feature values; the expression of the multi-source feature fusion model is: S(t)=α·ΔT+β·ΔL+γ·ΔV; In the formula, S(t) is the bolting characteristic value at the current time t, ΔT is the effective accumulated temperature accumulation, ΔL is the photoperiod effect accumulation, ΔV is the relative growth rate, α is the first weight value, β is the second weight value, and γ is the third weight value; where ΔV = ln(H / H0), H is the current height of the target radish plant, and H0 is the reference height value; the method for determining the first weight value α, the second weight value β, and the third weight value γ is as follows: obtain the first weight value α of the temperature influence at the current time, and the expression for α is: α = α0·(1+K·G) In the formula, α0 is the initial weight value of temperature influence, K is the adjustment coefficient, K is set according to the accumulated temperature requirement characteristics of the target radish plant variety, G is the minimum effective accumulated temperature required for the target radish plant of the corresponding variety to complete the vernalization stage; the values ​​of the second weight value β and the third weight value γ are adaptively adjusted according to the first weight value α. The threshold acquisition module is used to acquire the dynamic threshold of the target radish plant at the current time. The third data processing module is used to determine whether the bolting determination condition has been met at the current time. If so, it outputs a bolting alarm message; otherwise, it returns to obtain the environmental parameters of the target radish plant. The bolting determination condition is: the bolting characteristic value is greater than the dynamic threshold, and the plant height growth acceleration is greater than the preset critical value.

7. A computer device, characterized in that, The computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement a method for monitoring the bolting status of radishes as described in any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, and the processor executes the computer program to implement a method for monitoring the bolting status of radishes as described in any one of claims 1-5.

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