CN113686983A - Crop disease and insect pest detection method - Google Patents
Crop disease and insect pest detection method Download PDFInfo
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- CN113686983A CN113686983A CN202110828822.9A CN202110828822A CN113686983A CN 113686983 A CN113686983 A CN 113686983A CN 202110828822 A CN202110828822 A CN 202110828822A CN 113686983 A CN113686983 A CN 113686983A
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- 241000607479 Yersinia pestis Species 0.000 title claims abstract description 102
- 201000010099 disease Diseases 0.000 title claims abstract description 66
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 title claims abstract description 66
- 241000238631 Hexapoda Species 0.000 title claims abstract description 55
- 238000001514 detection method Methods 0.000 title claims abstract description 19
- 238000003745 diagnosis Methods 0.000 claims abstract description 23
- 238000004451 qualitative analysis Methods 0.000 claims abstract description 8
- 238000004445 quantitative analysis Methods 0.000 claims abstract description 8
- 230000002265 prevention Effects 0.000 claims abstract description 5
- 238000004458 analytical method Methods 0.000 claims description 13
- 238000000034 method Methods 0.000 claims description 13
- 238000005070 sampling Methods 0.000 claims description 12
- 150000001875 compounds Chemical class 0.000 claims description 9
- 239000000126 substance Substances 0.000 claims description 9
- 238000002470 solid-phase micro-extraction Methods 0.000 claims description 6
- 230000003068 static effect Effects 0.000 claims description 6
- 238000001179 sorption measurement Methods 0.000 claims description 4
- 238000002290 gas chromatography-mass spectrometry Methods 0.000 claims description 3
- 238000010835 comparative analysis Methods 0.000 claims description 2
- -1 n Species 0.000 claims description 2
- 238000002360 preparation method Methods 0.000 claims description 2
- 238000012887 quadratic function Methods 0.000 claims description 2
- 238000007789 sealing Methods 0.000 claims description 2
- 238000012360 testing method Methods 0.000 claims description 2
- 238000005303 weighing Methods 0.000 claims description 2
- 239000003039 volatile agent Substances 0.000 claims 1
- 238000012271 agricultural production Methods 0.000 abstract description 4
- 238000011161 development Methods 0.000 abstract description 4
- 238000000605 extraction Methods 0.000 description 4
- 230000000694 effects Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 230000035945 sensitivity Effects 0.000 description 2
- 241000282414 Homo sapiens Species 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 238000013480 data collection Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000005265 energy consumption Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 238000001319 headspace solid-phase micro-extraction Methods 0.000 description 1
- 230000009545 invasion Effects 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000002414 normal-phase solid-phase extraction Methods 0.000 description 1
- 239000003960 organic solvent Substances 0.000 description 1
- 239000000575 pesticide Substances 0.000 description 1
- 239000012071 phase Substances 0.000 description 1
- 230000009897 systematic effect Effects 0.000 description 1
- 238000012929 ultra trace analysis Methods 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
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Abstract
A crop pest detection method includes the steps of collecting crop pest volatile matters, conducting qualitative and quantitative analysis on the collected volatile matters by using a gas chromatography-mass spectrometer, comparing the content change phenomenon of the volatile matters obtained by a gas sensor, building a pest volatile matter distinguishing model, and building a pest diagnosis platform. The invention solves the problem that the crop diseases and insect pests are difficult to detect efficiently and accurately in a complex environment at present, promotes the development of agricultural disease and insect pest detection, provides a more accurate and efficient crop disease and insect pest prevention and control means, and ensures the safety of agricultural production.
Description
Technical Field
The invention is used in the technical field of agricultural pest control, and particularly relates to a crop pest detection method.
Technical Field
Crops are important living materials of human beings, are food sources on which people live, are easily damaged by diseases and pests in the growth process, the potential yield of crops is reduced by 40% on average due to the current international diseases and pests, the problems of the diseases and the pests in China are prominent, more than 1400 common diseases and pests are caused, the major diseases and pests of the crops in China are estimated to be mainly caused, and the accumulated occurrence area is about 3 hundred million hectares in recent years.
The detection and identification of crop diseases and insect pests are the key of the development of precision agriculture and ecological agriculture, and the significance of scientifically and effectively reducing the occurrence frequency and the intensity of the diseases and insect pests is great. At present, the disease and insect pest control is mainly carried out by subjective judgment, the disease and insect pest control efficiency is low, the labor intensity is high, the misjudgment rate is high, the disease and insect pest cannot be timely and accurately controlled, the quality and the yield of crops are directly influenced, and the huge economic loss is caused.
Disclosure of Invention
The invention aims to provide a crop disease and insect pest detection method aiming at the problems of low information acquisition content of volatile matters of diseases and insect pests, poor stability, low disease and insect pest diagnosis accuracy, no systematic diagnosis, incapability of efficiently serving modern agricultural production and the like.
The technical scheme of the invention is as follows:
a crop pest detection method comprises the steps of collecting crop pest volatile matters, conducting qualitative and quantitative analysis on the collected volatile matters by using a gas chromatography-mass spectrometer, comparing the content change phenomenon of the volatile matters obtained by a gas sensor, establishing a pest volatile matter discrimination model, and building a pest diagnosis platform to realize efficient and accurate recognition of pests.
And collecting crop pest volatile matters by adopting a method combining solid-phase micro-extraction and static headspace.
The solid phase micro-extraction integrates sampling, extraction, concentration and sample introduction, is convenient to operate, short in time consumption and rapid and efficient in determination; no organic solvent is needed, solid phase extraction is truly realized, and secondary pollution to the environment is avoided; the instrument is simple, does not need auxiliary equipment, is suitable for field analysis and is easy to operate; the sensitivity is high, ultra trace analysis can be realized, and the detection of nanogram per gram level can be achieved. Static headspace refers to headspace sampling. The method is mainly used for measuring samples which can volatilize at a certain temperature and are relatively difficult to pre-treat.
The method of combining solid phase micro-extraction and static headspace can improve the stability and sensitivity of volatile matters of plant diseases and insect pests.
The gas chromatography-mass spectrometer can be used for completing sampling data acquisition and analysis, qualitatively and quantitatively analyzing volatile matter information of different diseases and insect pests, obtaining analysis results of components of the compounds of the diseases and insect pests, and providing index evaluation of extraction effect.
The pest volatile matter distinguishing model analyzes the internal relation among the sampling environment, the content of the pest volatile matter compound and the response information of the gas sensor, and establishes a curve equation model.
The method comprises the steps of analyzing the change phenomena of current change, response time and frequency characteristics by the resistance change of a gas sensor, obtaining the compound component content of a pest and disease performance substance by a gas chromatography-mass spectrometer, determining an internal relation, analyzing the response rule of crop pest and disease under different components, population density and colony count, extracting the area, steady state value and response value of a response curve, analyzing a quadratic term function, an exponential function, a Gaussian function and an adsorption kinetic equation, obtaining an optimal fitting curve, and establishing a sensor response model as a discrimination model.
The plant disease and insect pest diagnosis platform consists of a discrimination model, a gas sensor, a server, a controller, a sensing network and a display terminal.
The display terminal comprises a PC, a notebook and a mobile phone, the sensor obtains the volatile matter information of plant diseases and insect pests on the diagnosis site, the volatile matter information of plant diseases and insect pests is transmitted to the diagnosis host based on the volatile matter distinguishing model of plant diseases and insect pests, and the analysis and distinguishing result is displayed in front of workers through the display terminal, so that a basis is provided for preventing and controlling the plant diseases and insect pests of crops.
The implementation effect of the invention is as follows:
the invention effectively solves the problem that the current crop disease and insect pest prevention and control is difficult to meet the requirement of efficient and accurate identification in a complex environment, changes the past more or less qualitative judgment based on manual experience into quantitative judgment, can drive the current crop disease and insect pest information acquisition mode in China to change to the information direction, provides a more accurate and more efficient information acquisition technology for the crop disease and insect pest prevention and control, supports the development of modern agriculture, and ensures the agricultural safety.
According to the invention, the pest and disease invasion condition can be effectively monitored, the crop loss is reduced, the production energy consumption of pest and disease control equipment is reduced by 5-6%, the pesticide application is reduced by more than 30%, the production efficiency is improved by more than 25%, a more accurate and efficient diagnosis technology is provided for the pest and disease control of crops, the development of modern agriculture is promoted, and the safety of agricultural production is guaranteed.
Drawings
FIG. 1 is a flow chart of the present invention;
FIG. 2 is a flow chart of pest and disease volatile matter collection based on headspace solid phase microextraction;
FIG. 3 is a flow chart of response model building based on gas sensors and GC-MS;
fig. 4 is a block diagram of a pest diagnosis platform.
Detailed Description
The invention is described in further detail below with reference to the figures and the specific embodiments.
As shown in figure 1, the crop disease and insect pest detection method comprises the steps of collecting crop disease and insect pest volatile matters, carrying out qualitative and quantitative analysis on the collected volatile matters by using a gas chromatography-mass spectrometer, comparing the content change phenomenon of the volatile matters obtained by a gas sensor, establishing a disease and insect pest volatile matter distinguishing model, and building a disease and insect pest diagnosis platform to realize efficient and accurate recognition of disease and insect pest.
As shown in fig. 2, in order to obtain crop pest volatile matters required for qualitative and quantitative analysis and detection, a method combining solid phase microextraction and static headspace collection is adopted, sampling data collection and analysis are completed by designing sample preparation, weighing, sealing, extraction and adsorption operations and setting a detection limit of a gas chromatography-mass spectrometer, and pest compound component analysis results are obtained to provide entity samples and basic data for subsequent comparative analysis and analysis.
Wherein the sample collecting device comprises a magnetic stirrer, a water phase, a headspace bottle and an extraction head from bottom to top.
As shown in fig. 3, when the gas sensor obtains volatile insect pests from different crop samples, the response time, frequency and other characteristics of the volatile insect pests are obviously changed, the gas chromatography-mass spectrometry (GC-MS) method is used for performing qualitative and quantitative analysis on the information of the volatile insect pests collected from different crop samples, the response information of the gas sensor under different sampling environments and different volatile insect pests is obtained, the internal relation between the sampling environment and the content of the volatile insect pest compounds and the response information of the gas sensor is determined, different components are analyzed, and (3) extracting response curve characteristics according to crop pest information response rules under different population densities or colony counts, analyzing a quadratic function, an exponential function, a Gaussian function and an adsorption kinetic equation fitting response curve to obtain an optimal fitting curve, and establishing a pest volatile matter discrimination model as a discrimination model of a pest diagnosis platform.
As shown in fig. 4, the disease and pest diagnosis platform is composed of a discrimination model, a gas sensor, a server, a controller, a sensing network, a display terminal, and the like. The display terminal and electronic instruments such as the gas-sensitive sensor are connected to the controller through serial ports, PCI, USB and other connection modes, the diagnosis field terminal, the remote test server, the database server and the diagnosis host (PC) transmit information through the network by the intervention of the controller in a sensing network. The sensor obtains volatile substance information of plant diseases and insect pests on a diagnosis site, the volatile substance information of the plant diseases and insect pests is transmitted to a diagnosis host based on a volatile substance distinguishing model of the plant diseases and insect pests, and an analysis distinguishing result is displayed in front of workers through a display terminal, so that a basis is provided for prevention and control of the plant diseases and insect pests of crops.
The invention has clear conception and clear working principle, solves the problem that the crop diseases and pests are difficult to efficiently and accurately detect in a complex environment according to a crop disease and pest detection system, reduces the disease and pest control cost, reduces the labor intensity, improves the fine level of the crop disease and pest control, and provides high-quality, safe and convenient operation guarantee for agricultural production in China.
Claims (8)
1. A crop pest detection method is characterized by firstly collecting crop pest volatile matters, then carrying out qualitative and quantitative analysis on the collected volatile matters by using a gas chromatography-mass spectrometer, comparing the content change phenomenon of the volatile matters obtained by a gas sensor, establishing a pest volatile matter discrimination model, and building a pest diagnosis platform.
2. A method according to claim 1, wherein the crop pest volatiles are collected by a combination of solid phase micro-extraction and static headspace.
3. The method for detecting the crop diseases and insect pests according to claim 2, wherein a gas chromatography-mass spectrometer is used for completing sampling data acquisition and analysis, and volatile matter information of different diseases and insect pests is qualitatively and quantitatively analyzed to obtain analysis results of components of the compounds of the diseases and insect pests.
4. The method for detecting the crop diseases and insect pests according to claim 3, wherein in order to obtain the crop disease and insect pest volatile matters required for qualitative and quantitative analysis and detection, a method combining solid phase microextraction and static headspace acquisition is adopted, and sampling data acquisition and analysis are completed by designing sample preparation, weighing, sealing, extracting and adsorbing operations and setting the detection limit of a gas chromatography-mass spectrometer instrument, so that the analysis result of the components of the disease and insect pest compounds is obtained, and entity samples and basic data are provided for subsequent comparative analysis and analysis.
5. The crop pest detection method according to claim 4, wherein the pest volatile substance discrimination model is used for analyzing the internal relation between the sampling environment, the content of the pest volatile substance compound and the response information of the gas sensor and establishing a curve equation model.
6. The method for detecting the crop diseases and insect pests according to claim 5, wherein the gas sensor has the phenomenon of obvious response time and frequency characteristic change when acquiring the volatile matters of the diseases and insect pests in different crop samples, the gas chromatography-mass spectrometry combined method is used for carrying out qualitative and quantitative analysis on the information of the volatile matters of the diseases and insect pests acquired, the response information of the gas sensor under different sampling environments and different volatile matters of the crops is acquired, the internal relation between the sampling environment and the content of the volatile compounds of the diseases and insect pests and the response information of the gas sensor is determined, the response rule of the information of the crop diseases and insect pests under different components and different population densities or colony counts is analyzed, the response curve characteristics are extracted, the quadratic function, the exponential function, the Gaussian function and the adsorption kinetics equation are analyzed to fit the response curve, the optimal fit curve is obtained, and the volatile matter distinguishing model of the diseases and insect pests is established, and the model is used as a discrimination model of a plant disease and insect pest diagnosis platform.
7. The crop pest detection method according to claim 6, wherein the pest diagnosis platform comprises a discrimination model, a gas sensor, a server, a controller, a sensing network and a display terminal.
8. A crop pest detection method according to claim 7, wherein the display terminal and the gas-sensitive sensor are connected to a controller, the controller intervenes in a sensing network, and a diagnosis field terminal, a remote test server, a database server and a diagnosis host transmit information through the network; the sensor obtains volatile substance information of plant diseases and insect pests on a diagnosis site, the volatile substance information of the plant diseases and insect pests is transmitted to a diagnosis host based on a volatile substance distinguishing model of the plant diseases and insect pests, and an analysis distinguishing result is displayed in front of workers through a display terminal, so that a basis is provided for prevention and control of the plant diseases and insect pests of crops.
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| CN202110828822.9A CN113686983A (en) | 2021-07-22 | 2021-07-22 | Crop disease and insect pest detection method |
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| CN202110828822.9A CN113686983A (en) | 2021-07-22 | 2021-07-22 | Crop disease and insect pest detection method |
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102084794A (en) * | 2010-10-22 | 2011-06-08 | 华南农业大学 | Method and device for early detecting crop pests based on multisensor information fusion |
| CN102279213A (en) * | 2011-07-20 | 2011-12-14 | 浙江大学 | Method for rapid diagnosis of crop disease by volatile matter |
| CN102353701A (en) * | 2011-07-20 | 2012-02-15 | 浙江大学 | Diagnostic method for insect attacks on crops by utilizing volatile matter |
| JP2016065868A (en) * | 2014-09-16 | 2016-04-28 | 三井造船株式会社 | Method and device for diagnosing plant, and method and device for discriminating pest |
| CN110018203A (en) * | 2019-03-18 | 2019-07-16 | 江苏大学 | Aromatic vinegar flavor quantitatively characterizing method based on electronic nose electronic tongues intelligent sensory technology |
| EP3654272A1 (en) * | 2018-11-15 | 2020-05-20 | Korea Institute of Science and Technology | Crop injury diagnosis system and method |
| CN112415057A (en) * | 2020-12-30 | 2021-02-26 | 南京农业大学 | Method for quantitatively detecting eugenol in natural membrane based on electronic nose technology |
| CN112949984A (en) * | 2021-02-01 | 2021-06-11 | 中国水产科学研究院南海水产研究所 | Multi-dimensional fusion identification method for fermentation degree of Meixiang fish based on smell visualization |
-
2021
- 2021-07-22 CN CN202110828822.9A patent/CN113686983A/en active Pending
Patent Citations (8)
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|---|---|---|---|---|
| CN102084794A (en) * | 2010-10-22 | 2011-06-08 | 华南农业大学 | Method and device for early detecting crop pests based on multisensor information fusion |
| CN102279213A (en) * | 2011-07-20 | 2011-12-14 | 浙江大学 | Method for rapid diagnosis of crop disease by volatile matter |
| CN102353701A (en) * | 2011-07-20 | 2012-02-15 | 浙江大学 | Diagnostic method for insect attacks on crops by utilizing volatile matter |
| JP2016065868A (en) * | 2014-09-16 | 2016-04-28 | 三井造船株式会社 | Method and device for diagnosing plant, and method and device for discriminating pest |
| EP3654272A1 (en) * | 2018-11-15 | 2020-05-20 | Korea Institute of Science and Technology | Crop injury diagnosis system and method |
| CN110018203A (en) * | 2019-03-18 | 2019-07-16 | 江苏大学 | Aromatic vinegar flavor quantitatively characterizing method based on electronic nose electronic tongues intelligent sensory technology |
| CN112415057A (en) * | 2020-12-30 | 2021-02-26 | 南京农业大学 | Method for quantitatively detecting eugenol in natural membrane based on electronic nose technology |
| CN112949984A (en) * | 2021-02-01 | 2021-06-11 | 中国水产科学研究院南海水产研究所 | Multi-dimensional fusion identification method for fermentation degree of Meixiang fish based on smell visualization |
Non-Patent Citations (2)
| Title |
|---|
| YUBING SUN等: "Evaluation of E-nose data analyses for discrimination of tea plants with different damage types", 《JOURNAL OF PLANT DISEASES AND PROTECTION》 * |
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Application publication date: 20211123 |