CN106331635A - Xiaozhou tuber mustard disease and pest occurrence situation monitoring and analyzing system - Google Patents
Xiaozhou tuber mustard disease and pest occurrence situation monitoring and analyzing system Download PDFInfo
- Publication number
- CN106331635A CN106331635A CN201610779942.3A CN201610779942A CN106331635A CN 106331635 A CN106331635 A CN 106331635A CN 201610779942 A CN201610779942 A CN 201610779942A CN 106331635 A CN106331635 A CN 106331635A
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- disease
- pest
- xiaozhou
- little
- monitoring
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
- H04N7/181—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a plurality of remote sources
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/10—Terrestrial scenes
- G06V20/188—Vegetation
Abstract
The invention relates to a Xiaozhou tuber mustard disease and pest occurrence situation monitoring and analyzing system. Three representative Xiaozhou tuber mustard fields of high, middle and low levels are selected from large-scale fields for planting Xiaozhou tuber mustards; monitoring probes are installed at five points on diagonals of each field according to a close visual angle; each monitoring point investigates 20 Xiaozhou tuber mustards from emergence to harvest; and the monitoring probes are connected with an image identification module. The image identification module analyzes returned images once every other ten days and inputs disease and pest species and quantity into a database; samples of the diseases and pests incapable of being identified by the image identification module are taken to a laboratory for identification, and then the disease and pest species and quantity are manually input into the database through a manual input module; and statistics, analysis and response are carried out on the data of the database according to demands through utilization of a processing module. The disease and pest data can be collected in real time, a whole growing process is sampled and analyzed really, statistics analysis is convenient, and the accuracy is greatly improved.
Description
Technical field
The present invention relates to planting technology, particularly relate to a kind of little continent head dish pest and disease damage a situation arises monitoring analysis system.
Background technology
Little continent head dish is that Zhen little Zhou village, Chang'an, Rongan County, Guangxi, continent village one band peasant continue plantation for a long time the earliest
Vegetable, peasant reserves seed for planting the most voluntarily, defines the Stem lettuce improved seeds being adapted to local plantation, because its pickling process is only
Spy, excellent quality, and main product Yu little Zhou village, so little continent head dish of gaining the name, for many years, little continent head dish is always Chang'an town peasant and increases
The main source received, but easily there is insect pest in it.
Summary of the invention
It is an object of the invention to provide a kind of little continent head dish pest and disease damage a situation arises monitoring analysis system, it is intended to solve little
The problem of the statistics and analysis of continent head dish main diseases and insect pests.
The technical solution used in the present invention is: a kind of little continent head dish pest and disease damage a situation arises monitoring analysis system, exists respectively
The field of contiguous plant little continent head dish, chooses three pieces of representational little continent head field of vegetables blocks respectively by high, medium and low three classifications,
Every field is pressed 5 near-sighted angles of diagonal and is installed monitoring probe, every some monitoring investigation omnidistance 20 strain little continent heads from emerging to gathering in the crops
Dish, monitoring probe is connected with picture recognition module, and picture recognition module analyzes the image once returned for every ten days and by disease pest kind
Class and quantity input database, the disease pest that picture recognition module can not be identified, manually record after laboratory qualification of sampling back
Enter module input database, finally utilize processing module that database data carries out statistical analysis reaction on demand.
The invention has the beneficial effects as follows: owing to using technique scheme, collection pest and disease damage data that can be real-time, really
Achieve growth overall process sampling analysis so that the while that statistical analysis being convenient, greatly improve accuracy.
Detailed description of the invention
A kind of little continent head dish pest and disease damage a situation arises monitoring analysis system, respectively in the field of contiguous plant little continent head dish,
Choosing three pieces of representational little continent head field of vegetables blocks respectively by high, medium and low three classifications, every field presses 5 near-sighted angles of diagonal
Monitoring probe, every some monitoring investigation omnidistance 20 strain little continent head dishes, monitoring probe and picture recognition module from emerging to gathering in the crops are installed
Connecting, picture recognition module analyzes the image once returned for every ten days and by disease pest kind and quantity input database, to image
The disease pest that identification module can not identify, after laboratory qualification of sampling back, manually typing module input database, finally utilizes
Database data is carried out statistical analysis reaction by processing module on demand.Collection pest and disease damage data that can be real-time, really realize
Growth overall process sampling analysis so that the while that statistical analysis being convenient, greatly improve accuracy.
Through 3 years, continual analysis found, little continent head dish easily occurs insect pest, main insect pest to have clubroot, downy mildew
Disease, virosis, soft rot, anthrax, melasma, black rot, sclerotiniose, nematicide, phyllotreta striolata, aphid, Pieris rapae, pickles
Moth, Prodenia litura, beet armyworm, Americal rice leaf miner, cutworm, Limax, wireworm, Gryllotalpa, root demodicid mite.
One of feature that pest and disease damage occurs: year after year plant, pest and disease damage occurs the most serious；Plant the most continuously, Yi Jinong
The minimizing of family's fertilizer, chemical fertilizer, a large amount of uses of chemical pesticide, make soil environment generation large change, gaseous phase of soil and soil
Earth ecology receives relatively havoc, and disease showed increased increases the weight of.
The two of the feature that pest and disease damage occurs: insect pest kind is many, but loss is few, and disease species is few, but loss is big；Insect pest is general
All being present in surface, peasant is it is readily seen that so being easier to use chemical pesticide control, and majority is harm blade, to little
The yield effect of continent head dish is little；And disease species survey to lack relatively on the head dish of little continent, only 7 kinds；Occur serious only
Having clubroot and soft rot, the moderate generation of soft rot, black rot, virosis are medium the gentliest to be occurred, and other disease is light sending out
Raw.But, these diseases are the biggest, such as to the yield effect of little continent head dish: seedling stage clubroot seriously occur even to make peasant without
Seedling can be planted；Virosis has a strong impact on increment；Within 2014, black rot occurs serious vegetable plot loss rate unexpectedly to reach 42%.
The three of the feature that pest and disease damage occurs: the subterranean pest-insect impacts such as root demodicid mite are serious；In recent years, cutworm, Gryllotalpa, Holotrichia diomphalia Bates etc.
Subterranean pest-insect has reduced, but wireworm, nematicide, the harm of root demodicid mite are increase, particularly wireworm and root demodicid mite；Subterranean pest-insect except
Directly contributing and be short of seedling and affect outside Root Absorption, its wound is also apparent from causing the serious generation of soil-borne disease；In recent years
Observe the vegetable plot finding that root demodicid mite occurs, soft rot, clubroot and black rot showed increased, there is bigger dependency.
The foregoing is only presently preferred embodiments of the present invention, not in order to limit the present invention, all essences in the present invention
Any amendment, equivalent and the improvement etc. made within god and principle, should be included within the scope of the present invention.
Claims (1)
1. one kind little continent head dish pest and disease damage a situation arises monitoring analysis system, it is characterised in that: respectively at contiguous plant little continent head
The field of dish, chooses three pieces of representational little continent head field of vegetables blocks respectively by high, medium and low three classifications, and every field presses diagonal
5 near-sighted angles install monitoring probe, monitoring investigation omnidistance 20 strain little continent head dishes, monitoring probe and figure from emerging to gathering in the crops at every
As identification module connects, picture recognition module is analyzed the image once returned for every ten days and disease pest kind and quantity is inputted data
Storehouse, the disease pest that picture recognition module can not be identified, manually typing module input database after laboratory qualification of sampling back,
Finally utilize processing module that database data carries out statistical analysis reaction on demand.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610779942.3A CN106331635A (en) | 2016-08-31 | 2016-08-31 | Xiaozhou tuber mustard disease and pest occurrence situation monitoring and analyzing system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610779942.3A CN106331635A (en) | 2016-08-31 | 2016-08-31 | Xiaozhou tuber mustard disease and pest occurrence situation monitoring and analyzing system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN106331635A true CN106331635A (en) | 2017-01-11 |
Family
ID=57790063
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610779942.3A Pending CN106331635A (en) | 2016-08-31 | 2016-08-31 | Xiaozhou tuber mustard disease and pest occurrence situation monitoring and analyzing system |
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101938512A (en) * | 2010-08-13 | 2011-01-05 | 仲恺农业工程学院 | Internet of thing based automatic monitoring system of crop disease and pest image information |
| CN102915446A (en) * | 2012-09-20 | 2013-02-06 | 复旦大学 | Plant disease and pest detection method based on SVM (support vector machine) learning |
| CN103425088A (en) * | 2012-05-17 | 2013-12-04 | 乔广行 | Crop disease and pest monitoring system |
| CN104199425A (en) * | 2014-09-15 | 2014-12-10 | 中国农业科学院农业信息研究所 | Intelligent agricultural monitoring pre-warning system and method |
-
2016
- 2016-08-31 CN CN201610779942.3A patent/CN106331635A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101938512A (en) * | 2010-08-13 | 2011-01-05 | 仲恺农业工程学院 | Internet of thing based automatic monitoring system of crop disease and pest image information |
| CN103425088A (en) * | 2012-05-17 | 2013-12-04 | 乔广行 | Crop disease and pest monitoring system |
| CN102915446A (en) * | 2012-09-20 | 2013-02-06 | 复旦大学 | Plant disease and pest detection method based on SVM (support vector machine) learning |
| CN104199425A (en) * | 2014-09-15 | 2014-12-10 | 中国农业科学院农业信息研究所 | Intelligent agricultural monitoring pre-warning system and method |
Non-Patent Citations (1)
| Title |
|---|
| 韦健谋，廖善忠，等.: "广西融安县小洲头菜病虫害发生情况及防治建议", 《北京农业》 * |
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Application publication date: 20170111 |
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| RJ01 | Rejection of invention patent application after publication |