CN-121995037-A - Intelligent monitoring system for planting fritillaria thunbergii soil environment

CN121995037ACN 121995037 ACN121995037 ACN 121995037ACN-121995037-A

Abstract

The application relates to the technical field of soil environment monitoring, in particular to an intelligent monitoring system for a Thunberg fritillary bulb planting soil environment, which can collect the content of autotoxic substances of a plurality of sampling points at a plurality of sampling moments, then determine historical continuous cropping lines and continuous cropping points based on the content of the autotoxic substances of each sampling point at the plurality of sampling moments and the position distribution of the plurality of sampling points, determine continuous cropping accumulation reference values based on the content of the autotoxic substances of each continuous cropping point at the current sampling moment and the content of the autotoxic substances generated by each sampling point in the current sampling period, input the content prediction model of the content of the autotoxic substances generated by each sampling point in the current sampling period and the continuous cropping accumulation reference values, obtain the predicted value of the content of the autotoxic substances of each sampling point at the next sampling moment, and monitor the soil environment based on the predicted value of the content of the autotoxic substances of each sampling point at the next sampling moment.

Inventors

HUI NING
LIU JIA
GE WEIHONG
LI HONGFA
YANG YANG
TANG RUI
LI MENGMENG
WANG HUI
WANG LERAN
ZHU HONGHAI
Zheng Qiaomei

Assignees

浙江中医药大学(淳安千岛湖)研究院有限公司
浙江千岛湖美誉药业有限公司

Dates

Publication Date: 20260508
Application Date: 20260409

Claims (10)

1. The intelligent monitoring system for the soil environment for planting the fritillary bulb is characterized by comprising a data acquisition unit, a data processing unit, a data prediction unit and a data monitoring unit; The data acquisition unit is used for acquiring the content of the autotoxic substances of a plurality of sampling points by presetting the sampling period length to obtain the content of the autotoxic substances of each sampling point at a plurality of sampling moments; the data processing unit is used for determining a historical continuous cropping line based on the content change of the autotoxic substance of each sampling point at a plurality of sampling moments and the position distribution of the sampling points, and determining the sampling points included in the historical continuous cropping line as continuous cropping points; The data processing unit is also used for determining a continuous cropping accumulation reference value and the content of the autotoxic substance generated by each sampling point in the current sampling period based on the content of the autotoxic substance of each continuous cropping point at the current sampling moment; The data prediction unit is used for inputting the content of the autotoxic substance generated by each sampling point in the current sampling period and the continuous cropping accumulation reference value into a content prediction model to obtain an autotoxic substance content prediction value of each sampling point at the next sampling moment, wherein the content prediction model is used for predicting the content of the autotoxic substance; And the data monitoring unit is used for monitoring the soil environment based on the predicted value of the content of the autotoxic substance at the next sampling time of each sampling point.
2. The intelligent monitoring system for the soil environment for fritillary planting according to claim 1, wherein the data processing unit is specifically configured to: determining the change rate of the content of the autotoxic substance at each sampling point based on the content of the autotoxic substance at a plurality of sampling moments at each sampling point; Determining the affected degree of each sampling point based on the change rate of the content of the autotoxic substance of each sampling point, wherein the affected degree is used for representing the degree of the influence of current planting on one sampling point; Determining an autotoxic substance distribution regularity of each candidate line based on the affected extent of sampling points included in each candidate line of the N candidate lines and the autotoxic substance content of each sampling point, N being an integer greater than or equal to 1; and determining the candidate row with the greatest distribution regularity of the autotoxicity substance as the historical continuous cropping row.
3. The intelligent monitoring system for the soil environment for fritillary planting according to claim 2, wherein the data processing unit is specifically configured to: Determining the maximum value and the minimum value of the content change rate of the autotoxic substance of the sampling points in a first local area, wherein the first local area is the local area where the first sampling points are located, and the first sampling points are one of the sampling points; And determining the ratio between a first difference value and a second difference value as the affected degree of the first sampling point, wherein the first difference value is the difference value between the automatic toxic substance content change rate of the first sampling point and the minimum value of the automatic toxic substance content change rate, and the second difference value is the difference value between the maximum value of the automatic toxic substance content change rate and the automatic toxic substance content change rate of the first sampling point.
4. The intelligent monitoring system for the soil environment for fritillary planting according to claim 2, wherein the data processing unit is specifically configured to: determining M current planting rows based on the positions of the sampling points, wherein M is an integer greater than or equal to 1; and rotating at least one angle and/or translating at least one preset distance on the M current planting rows to obtain N candidate rows, wherein N is more than or equal to M.
5. The intelligent monitoring system for the soil environment for fritillary planting according to claim 2, wherein the data processing unit is specifically configured to: Determining a historical continuous referential of each sample point based on the affected extent of the sample points included in the first candidate row and the autotoxic material content of each sample point, the first candidate row being any one of the N candidate rows; Determining historical continuous reference differences of every two adjacent sampling points in the first candidate row; And determining the distribution regularity of the autotoxic substances in the first candidate line based on the historical continuous reference difference of every two adjacent sampling points in the first candidate line.
6. The intelligent monitoring system for the soil environment for fritillary planting according to claim 5, wherein the data processing unit is specifically configured to: Determining the distance between a first sampling point and a root sampling point in a first local area, wherein the root sampling point in the first local area is a sampling point corresponding to the maximum value of the content change rate of the autotoxic substance in the first local area; determining continuous cropping representativeness of the first sampling point based on the distance and the affected degree of the first sampling point; The historical continuous cropping reference of the first sampling point is determined based on the continuous cropping representative of the first sampling point and the autotoxic substance content of the first sampling point.
7. The intelligent monitoring system for the soil environment for fritillary planting according to claim 6, wherein the data processing unit is specifically configured to: Determining the continuous cropping accumulation reference value based on the distribution regularity of the autotoxic substances of the historical continuous cropping row, the autotoxic substance content of all continuous cropping points in the historical continuous cropping row at the current sampling moment and the continuous cropping representativeness of each continuous cropping point; and determining the difference value between the content of the autotoxic substance of each sampling point at the current sampling moment and the continuous cropping accumulation reference value as the content of the autotoxic substance generated by each sampling point in the current sampling period.
8. The intelligent monitoring system for the soil environment for fritillary planting according to claim 1, wherein the system further comprises a model construction unit for: generating a plurality of autotoxic substance content sequences based on the autotoxic substance content of each sampling point at a plurality of acquisition moments, wherein one sampling point corresponds to one autotoxic substance content sequence; performing least square fitting on the plurality of autotoxicity substance content sequences to obtain initial parameters, wherein the initial parameters are used for representing the overall change trend of the autotoxicity substance content; and constructing a content prediction model based on the initial parameters.
9. The intelligent monitoring system for the soil environment for fritillary planting according to claim 8, wherein the data acquisition unit is further configured to: acquiring the actual value of the content of the autotoxic substance of each sampling point at the next sampling moment; the model construction unit is further used for adjusting initial parameters in the automatic toxic substance content prediction model based on the actual value of the automatic toxic substance content at the next sampling time and the predicted value of the automatic toxic substance content at the next sampling time of each sampling point.
10. The intelligent monitoring system for the soil environment for fritillary planting according to claim 1, wherein the data monitoring unit is specifically configured to: And sending out alarm information under the condition that the content predicted value of the autotoxic substance at the first sampling point exceeds a preset risk threshold.

Description

Intelligent monitoring system for planting fritillaria thunbergii soil environment Technical Field The application relates to the technical field of soil environment monitoring, in particular to an intelligent monitoring system for the soil environment for planting fritillaria thunbergii. Background The fritillary bulb is used as an important Chinese medicinal material, and the growth and development of the fritillary bulb are highly dependent on the soil environment condition. In the continuous planting process, the root system of the thunberg fritillary bulb can secrete phenolic acid and other autotoxic substances, and the accumulation of the substances in soil can inhibit the growth of successive cropping plants, so that the problem of continuous cropping obstacle is caused, and the yield and quality of medicinal materials are seriously influenced. In the related art, a sampling point is set, the sampling point is sampled and analyzed periodically, and the soil environment is monitored based on the content of the autotoxic substances in the sample. However, the tillage operations such as soil turning and leveling in the continuous cropping process can destroy the spatial distribution of original self-toxic substances in soil, and the analysis results obtained by sampling at sampling points are difficult to truly reflect the accumulation of the self-toxic substances caused by continuous cropping in the soil, so that the monitoring and evaluation accuracy of the soil environment is lower. Disclosure of Invention In order to solve the technical problem that the analysis result obtained by sampling at a sampling point is difficult to truly reflect the accumulation of autotoxic substances caused by continuous cropping in soil, and the monitoring and evaluation accuracy of the soil environment is low, the application aims to provide an intelligent soil environment monitoring system for fritillary planting, which adopts the following technical scheme: The application provides an intelligent monitoring system for a soil environment for fritillary planting, which comprises a data acquisition unit, a data processing unit, a data prediction unit and a data monitoring unit, wherein the data acquisition unit is used for acquiring the autotoxic substance content of a plurality of sampling points in a preset sampling period length to obtain the autotoxic substance content of each sampling point in a plurality of sampling moments, the data processing unit is used for determining a historical continuous cropping line based on the autotoxic substance content change of each sampling point in a plurality of sampling moments and the position distribution of the sampling points, the sampling points included in the historical continuous cropping line are determined as continuous cropping points, the data processing unit is also used for determining a continuous cropping accumulation reference value and the autotoxic substance content generated by each sampling point in the current sampling period based on the autotoxic substance content of each continuous cropping point in the current sampling period, the data prediction unit is used for obtaining an autotoxic substance content prediction value of each sampling point in the next sampling moment based on the autotoxic substance content of each sampling point in the current sampling period and a continuous cropping input content prediction model, and the data prediction unit is used for monitoring the autotoxic substance content of each sampling point in the current sampling period. The data processing unit is specifically used for determining the change rate of the autotoxic substance content of each sampling point based on the autotoxic substance content of each sampling point at a plurality of sampling moments, determining the affected degree of each sampling point based on the change rate of the autotoxic substance content of each sampling point, wherein the affected degree is used for representing the degree of influence of current planting on one sampling point, determining the distribution regularity of the autotoxic substance of each candidate line based on the affected degree of the sampling point and the autotoxic substance content of each sampling point in each candidate line, wherein N is an integer greater than or equal to 1, and determining the candidate line with the largest distribution regularity of the autotoxic substance as the historical continuous operation line. Optionally, the data processing unit is specifically configured to determine a maximum value and a minimum value of an auto-toxic substance content change rate of sampling points in a first local area, where the first local area is the local area where the first sampling point is located, and the first sampling point is one of the plurality of sampling points, and determine a ratio between a first difference value and a second difference value as an affected degree of the first sampling point, where