CN108764542A - The remote sensing prediction method of phase and occurrence quantity occur for diversiform-leaved poplar spring looper - Google Patents
The remote sensing prediction method of phase and occurrence quantity occur for diversiform-leaved poplar spring looper Download PDFInfo
- Publication number
- CN108764542A CN108764542A CN201810469507.XA CN201810469507A CN108764542A CN 108764542 A CN108764542 A CN 108764542A CN 201810469507 A CN201810469507 A CN 201810469507A CN 108764542 A CN108764542 A CN 108764542A
- Authority
- CN
- China
- Prior art keywords
- phase
- diversiform
- temperature
- development
- leaved poplar
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 241000219000 Populus Species 0.000 title claims abstract description 190
- 238000000034 method Methods 0.000 title claims abstract description 63
- 241001585671 Paleacrita vernata Species 0.000 claims abstract description 58
- 241000238631 Hexapoda Species 0.000 claims abstract description 32
- 238000007689 inspection Methods 0.000 claims abstract description 9
- 230000018109 developmental process Effects 0.000 claims description 188
- 238000011161 development Methods 0.000 claims description 186
- 238000009395 breeding Methods 0.000 claims description 53
- 230000001488 breeding effect Effects 0.000 claims description 53
- 238000012417 linear regression Methods 0.000 claims description 53
- 230000012447 hatching Effects 0.000 claims description 52
- 238000012795 verification Methods 0.000 claims description 38
- 230000012010 growth Effects 0.000 claims description 26
- 230000008569 process Effects 0.000 claims description 17
- 241001634830 Geometridae Species 0.000 claims description 15
- 241000382353 Pupa Species 0.000 claims description 15
- 230000008859 change Effects 0.000 claims description 15
- 238000013178 mathematical model Methods 0.000 claims description 13
- 230000001419 dependent effect Effects 0.000 claims description 12
- 102000002322 Egg Proteins Human genes 0.000 claims description 11
- 108010000912 Egg Proteins Proteins 0.000 claims description 11
- 210000004681 ovum Anatomy 0.000 claims description 11
- 238000000605 extraction Methods 0.000 claims description 10
- 230000007423 decrease Effects 0.000 claims description 8
- 238000011534 incubation Methods 0.000 claims description 6
- 230000003455 independent Effects 0.000 claims description 6
- 238000010219 correlation analysis Methods 0.000 claims description 4
- 238000012360 testing method Methods 0.000 claims 4
- 235000013399 edible fruits Nutrition 0.000 claims 1
- 241000607479 Yersinia pestis Species 0.000 abstract description 28
- 230000002265 prevention Effects 0.000 abstract description 13
- 201000010099 disease Diseases 0.000 abstract description 7
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 abstract description 7
- 238000011160 research Methods 0.000 abstract description 7
- 230000035613 defoliation Effects 0.000 abstract description 4
- 238000005070 sampling Methods 0.000 abstract description 2
- 235000013601 eggs Nutrition 0.000 description 38
- ZPEIMTDSQAKGNT-UHFFFAOYSA-N chlorpromazine Chemical compound C1=C(Cl)C=C2N(CCCN(C)C)C3=CC=CC=C3SC2=C1 ZPEIMTDSQAKGNT-UHFFFAOYSA-N 0.000 description 17
- 230000017448 oviposition Effects 0.000 description 17
- 230000006378 damage Effects 0.000 description 13
- 238000010586 diagram Methods 0.000 description 8
- 230000034994 death Effects 0.000 description 7
- 230000005058 diapause Effects 0.000 description 7
- 230000001850 reproductive effect Effects 0.000 description 7
- 230000032669 eclosion Effects 0.000 description 6
- 241001269238 Data Species 0.000 description 5
- 241001278112 Populus euphratica Species 0.000 description 5
- 230000000694 effects Effects 0.000 description 5
- 238000005516 engineering process Methods 0.000 description 5
- 238000011835 investigation Methods 0.000 description 5
- 238000012544 monitoring process Methods 0.000 description 5
- 230000013011 mating Effects 0.000 description 4
- 230000004060 metabolic process Effects 0.000 description 4
- 239000000047 product Substances 0.000 description 4
- 239000002689 soil Substances 0.000 description 4
- 238000002474 experimental method Methods 0.000 description 3
- 210000000056 organ Anatomy 0.000 description 3
- 241001124144 Dermaptera Species 0.000 description 2
- 208000027418 Wounds and injury Diseases 0.000 description 2
- 238000006243 chemical reaction Methods 0.000 description 2
- 238000009826 distribution Methods 0.000 description 2
- 230000007613 environmental effect Effects 0.000 description 2
- 208000014674 injury Diseases 0.000 description 2
- 230000001418 larval effect Effects 0.000 description 2
- 230000029052 metamorphosis Effects 0.000 description 2
- 238000000611 regression analysis Methods 0.000 description 2
- 230000004083 survival effect Effects 0.000 description 2
- 230000002123 temporal effect Effects 0.000 description 2
- NAWXUBYGYWOOIX-SFHVURJKSA-N (2s)-2-[[4-[2-(2,4-diaminoquinazolin-6-yl)ethyl]benzoyl]amino]-4-methylidenepentanedioic acid Chemical compound C1=CC2=NC(N)=NC(N)=C2C=C1CCC1=CC=C(C(=O)N[C@@H](CC(=C)C(O)=O)C(O)=O)C=C1 NAWXUBYGYWOOIX-SFHVURJKSA-N 0.000 description 1
- 244000025254 Cannabis sativa Species 0.000 description 1
- 241000196324 Embryophyta Species 0.000 description 1
- 102000004190 Enzymes Human genes 0.000 description 1
- 108090000790 Enzymes Proteins 0.000 description 1
- 241000471162 Erysipelothrix larvae Species 0.000 description 1
- 206010035148 Plague Diseases 0.000 description 1
- FAPWRFPIFSIZLT-UHFFFAOYSA-M Sodium chloride Chemical compound [Na+].[Cl-] FAPWRFPIFSIZLT-UHFFFAOYSA-M 0.000 description 1
- 230000006978 adaptation Effects 0.000 description 1
- 230000002411 adverse Effects 0.000 description 1
- 230000003698 anagen phase Effects 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 210000004027 cell Anatomy 0.000 description 1
- 238000005336 cracking Methods 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000009795 derivation Methods 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 230000005059 dormancy Effects 0.000 description 1
- 239000000428 dust Substances 0.000 description 1
- 235000013305 food Nutrition 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 230000001771 impaired effect Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000002427 irreversible effect Effects 0.000 description 1
- 230000033001 locomotion Effects 0.000 description 1
- 238000012067 mathematical method Methods 0.000 description 1
- 230000007758 mating behavior Effects 0.000 description 1
- 230000035800 maturation Effects 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 230000002503 metabolic effect Effects 0.000 description 1
- 230000000877 morphologic effect Effects 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 230000001766 physiological effect Effects 0.000 description 1
- 230000035479 physiological effects, processes and functions Effects 0.000 description 1
- 230000008288 physiological mechanism Effects 0.000 description 1
- 239000002244 precipitate Substances 0.000 description 1
- 239000003223 protective agent Substances 0.000 description 1
- 230000019617 pupation Effects 0.000 description 1
- 238000011084 recovery Methods 0.000 description 1
- 230000008439 repair process Effects 0.000 description 1
- 230000010539 reproductive behavior Effects 0.000 description 1
- 239000004576 sand Substances 0.000 description 1
- 239000011780 sodium chloride Substances 0.000 description 1
- 230000007480 spreading Effects 0.000 description 1
- 238000003892 spreading Methods 0.000 description 1
- 230000002277 temperature effect Effects 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
- 230000007704 transition Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/02—Agriculture; Fishing; Forestry; Mining
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Data Mining & Analysis (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Mathematical Physics (AREA)
- Computational Mathematics (AREA)
- Marketing (AREA)
- Life Sciences & Earth Sciences (AREA)
- Pure & Applied Mathematics (AREA)
- Tourism & Hospitality (AREA)
- Operations Research (AREA)
- General Business, Economics & Management (AREA)
- Mathematical Optimization (AREA)
- Mathematical Analysis (AREA)
- Marine Sciences & Fisheries (AREA)
- Primary Health Care (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Agronomy & Crop Science (AREA)
- Evolutionary Biology (AREA)
- Animal Husbandry (AREA)
- General Health & Medical Sciences (AREA)
- Mining & Mineral Resources (AREA)
- Probability & Statistics with Applications (AREA)
- Health & Medical Sciences (AREA)
- Algebra (AREA)
- Bioinformatics & Computational Biology (AREA)
- Databases & Information Systems (AREA)
- Software Systems (AREA)
- General Engineering & Computer Science (AREA)
- Development Economics (AREA)
- Game Theory and Decision Science (AREA)
- Entrepreneurship & Innovation (AREA)
- Quality & Reliability (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Catching Or Destruction (AREA)
Abstract
The present invention relates to forestry pests & diseases data remote sensing analysis technical fields, are a kind of remote sensing prediction methods of diversiform-leaved poplar spring looper generation phase and occurrence quantity, include the following steps：The first step establishes the spring looper prediction of emergence period model based on the rule of effective temperature summation；Second step calculates each worm state Remote Sensing Model based on the rule of effective temperature summation, predicts the temperature of each worm state；Third walks, and predicts the occurrence degree of diversiform-leaved poplar spring looper；4th step, verifies prediction result.The present invention is using diversiform-leaved poplar looper as research object, according to the history of life rule of diversiform-leaved poplar leafeating insect, in conjunction with field sampling and on-site inspection, it calculates analysis and show that spring cankerworm's defoliation mount not yet increases substantially when two instars occur, and egg hatch enters the whole story phase, looper spring, defoliator four ages does not occur substantially, therefore when two instars that the best prevention time is larva occur, and carries out prevention at this stage and can effectively improve insect pest incidence.
Description
Technical field
It is that a kind of diversiform-leaved poplar spring looper occurs the phase and occurs the present invention relates to forestry pests & diseases data remote sensing analysis technical field
The remote sensing prediction method of amount.
Background technology
Diversiform-leaved poplar is as a kind of Desert Riparian Forest grown under the wet conditions such as riverbank, lake, unique physiological structure
It can survive in the adverse circumstances of saline and alkaline, dust storm and arid, be the nearly top natural arbor group in arid-desert area, be
The important component of desert ecosystem is safeguarding the Desert Regions ecological balance, is checking winds and fixing drifting sand, regulates the climate, improves ecological ring
Border etc. plays important ecological functions.But in recent years, due to artificial excessively diversion and climate change, diversiform-leaved poplar is caused to give birth to
Dis environment deteriorates, and growing way is gradually weak, and normal physiological activity weakens, and the ability for resisting pest and disease damage declines so that pest and disease damage
Sprawling is rapid, starts large area and wantonly plunders, wherein especially the most serious with looper insect pest, forest loses leaf as met with fire when serious,
And have the tendency that further spreading to oasis.Therefore, diversiform-leaved poplar looper insect pest feature and its regularity of distribution are studied to Populus Euphratica
Protection has a very important significance.
In terms of looper research, many scholars from the living environment of looper, physiological mechanism, life habit, history of life rule,
Distribution, Dynamic state of population, caused by hazard conditions, prediction prevention etc. done numerous studies.But diversiform-leaved poplar
Forest zone is located in desert, has inconvenient traffic, and is difficult to carry out it a wide range of, in-depth study with traditional on-site inspection method.It is distant
Sense technology, which has, to be limited less by surface condition, obtains the advantage that data speed is fast, the period is short, widely used, has become state at present
Forest transition is monitored on border and endangers one of state-of-the-art means, and being had proved to be in the application of forest disease and pest field of detecting can
Row and effective, but this technology is still in and explores developing stage at present, however it remains it is few remote sensing monitoring parameter, data source
And the underutilization of auxiliary information, the problems such as technology and method is lack of pertinence difference；Cause the effective monitoring time section of pest and disease damage compared with
Short, monitoring accuracy is relatively low, and is difficult to monitor Random early Detection.Therefore, it is still necessary to further strengthen fundamental research, makes full use of gloomy
The Physiology and biochemistry and morphological index of woods difference damaging phases construct suitable remote sensing monitoring index, more mathematical methods are incorporated
Pest and disease damage Remote sensing monitoring study.
Invention content
The present invention provides a kind of remote sensing prediction methods that phase and occurrence quantity occur for diversiform-leaved poplar spring looper, overcome above-mentioned existing
The deficiency of technology can be solved effectively pre- there are no being carried out to the occurrence quantity in diversiform-leaved poplar spring looper each generation phase in the prior art
The method of survey cannot accurately find effective prevention phase of diversiform-leaved poplar spring looper, to prevent the problem of looper plague of insects occurs.
One of technical scheme of the present invention is realized by following measures：Phase and occurrence quantity occur for diversiform-leaved poplar spring looper
Remote sensing prediction method, includes the following steps：
The first step establishes the spring looper prediction of emergence period model based on the rule of effective temperature summation, the model of the rule of effective temperature summation
For：
Wherein, N is each effective development duration of worm state；K is effective total accumulated temperature；T is each stage mean daily temperature；C is each worm
State threshold of development；Sk is effective accumulated temperature standard variance；Sc is the standard variance of each worm state threshold of development；Enter later
Second step；
Second step calculates each worm state Remote Sensing Model based on the rule of effective temperature summation, predicts the temperature of each worm state, it
Enter third afterwards to walk；
Third walks, and predicts the occurrence degree of diversiform-leaved poplar spring looper, enters the 4th step later；
4th step, verifies prediction result.
Here is the further optimization and/or improvements to foregoing invention technical solution：
It is above-mentioned that calculating extraction carried out to each worm state threshold of development and effective accumulated temperature respectively in the first step, including with
Lower calculating process：
(1) developmental rate of insect refers to the percentage that all growth courses are completed in the unit interval, that is, is completed a certain
The time required to worm state full development process, the inverse of development duration, as unit of day, i.e.,：
V=1/N (2)
Wherein：V is diversiform-leaved poplar spring looper phasic development rate, and N is the number of days completed needed for worm state development；
(2) correlation analysis of development time and temperature factor of effective remote sensing accumulated temperature rule for insect, refers to biology and exists
It during growth and development, needs to absorb some heats from external environment, and completes the total heat needed for its growth and development process
Amount is a stability constant, and expression formula is：
NT=K (3)
In formula：N is development duration, unit：It, T be development during mean temperature unit be DEG C, K be total accumulated temperature, unit：
Day degree；
(3) growth and development of diversiform-leaved poplar spring looper does not start in a fixed temperature, starts to send out when being higher than 0 DEG C at one
It educates, referred to as threshold of development, is indicated with C, expression formula is revised as：
N (T-C)=K (4)
Wherein, C is threshold of development, and (T-C) is average developmental temperature, and K is the total accumulated temperature of effective remote sensing；Linear regression side
Journey (formula 4) indicates that developmental rate shows significant linear relationship with temperature；
(4) effective accumulated temperature is solved, expression formula is：
T=C+KV (5)
In formula：Threshold of development C is equivalent to a in linear equation, i.e. intercept of the straight line in reference axis, and effectively distant
Feel the slope b that total accumulated temperature K is then equivalent in linear equation；
(5) C, K parameter are solved according to linear equation, is acquired with least square method, calculating formula is：
Wherein：V is developmental rate (V=1/N)；T is temperature, and n is the group number of temperature.
In above-mentioned second step, each worm state Remote Sensing Model based on the rule of effective temperature summation, including following procedure are calculated：
(1) to diversiform-leaved poplar spring looper worm pupa emergence period predict, derive the effective remote sensing accumulated temperature rule mathematical model of emergence period is：
Wherein, N1For the effective development duration of emergence period；K1For the effectively total accumulated temperature of emergence period；T1For emergence period mean daily temperature；
C1For emergence period threshold of development；Sk1For emergence period effective accumulated temperature standard variance；Sc1For the mark of emergence period threshold of development
Quasi- variance；
(2) geometer breeding period in diversiform-leaved poplar spring is predicted, derives to obtain adult breeding period effective remote sensing accumulated temperature rule mathematical model
For：
Wherein, N2For moth breeding period effective development duration；K2For moth breeding period effectively total accumulated temperature；T2It is flat for moth breeding period day
Equal temperature；C3For moth breeding period threshold of development；Sk4For moth breeding period effective accumulated temperature standard variance；Sc5It is developed for moth breeding period
The standard variance of origin temp；
(3) prediction of looper egg hatch phase in diversiform-leaved poplar spring, which calculates, derives to obtain incubation period effective remote sensing accumulated temperature rule mathematical model
For：
Wherein, N3For egg hatch phase effective development duration；K3For egg hatch phase effectively total accumulated temperature；T3For egg hatch
Phase mean daily temperature；C3For egg hatch phase threshold of development；Sk3For egg hatch phase effective accumulated temperature standard variance；Sc3For worm
The standard variance of egg hatching phase threshold of development；
(4) cankerworm's puberty diversiform-leaved poplar spring predict, derive larvae development phase effective remote sensing accumulated temperature rule mathematical modulo
Type is：
Wherein, N4For larvae development phase effective development duration；K4For larvae development phase effectively total accumulated temperature；T4For larvae development
Phase mean daily temperature；C4For larvae development phase threshold of development；Sk4For larvae development phase effective accumulated temperature standard variance；Sc4For children
The standard variance of worm puberty threshold of development.
It is above-mentioned in the third step, using temperature trend map method or using some eco-physiological indexes method to the occurrence degree of each worm state
Prediction obtains prediction result.
In above-mentioned 4th step, the prediction result of each worm state is verified, is included the following steps：
(1) verification sample data is obtained, phase verification is gone through according to based on Linear Regression Model in One Unknown, then enters (2), if
Using the phase based on multiple linear regression analysis away from verification, then enter (3), according to the phase analyzed based on time series models away from
Verification then enters (4)；
(2) phase verification is gone through based on Linear Regression Model in One Unknown；Respectively with diversiform-leaved poplar spring looper develop after emergence, breeding,
Hatching, the average remote sensing temperature in 4 stages of larvae development build unitary line as independent variable to go through issue according to as dependent variable
Property regression analysis, mathematic(al) representation are：
Nn=a+bTn (12)
Wherein：NnRepresentative sprouts wings, breeding, hatches, larvae development each stage goes through issue evidence, TnIt is averaged remote sensing temperature for the stage
Degree, n=1,2,3,4, wherein 1,2,3,4 respectively represents emergence, breeding, hatching, larvae development each stage；
(3) based on the phase of multiple linear regression analysis away from verification；
Multiple linear regression equations model refers to for disclosing linear relationship between a dependent variable and multiple independents variable
The empirical model of linear regression model (LRM), multiple linear regression equations is as follows：
Y=β0+β1X1+β2X2+···βnXn (13)
In above formula, it is assumed that multiple linear equation has n independent variable X1, Xn, β i are being biased back to for equation independent variable
Return coefficient；Occur to begin to see phase of phase away from inspection to diversiform-leaved poplar spring cankerworm, the generation period of diversiform-leaved poplar spring cankerworm with sprout wings, at
Worm, hatching go through phase correlation, i.e., it is related to occur the mean temperature in period to the worms state such as looper emergences of diversiform-leaved poplar spring, adult, hatching, with Hu
It is that establish multiple linear regression equations as follows for independent variable that the mean temperature in period, which occurs, for the emergence of Yang Chun loopers, adult, hatching worm state：
N=N1+N2+N3 (14)
I.e.：N=β0+β1T1+β2T2+β3T3 (15)
Multiple regression Linear correlative analysis is carried out using statistical analysis software and obtains regression coefficient, examines diversiform-leaved poplar spring looper
Larva occur begin see phase phase away from；
(4) phase based on time series models analysis is away from verification；
For probing into the total variation tendency of variable and rough amplitude of variation of each period, and the shadow of decrease data error
It rings.Using the method for arithmetic average, the random fluctuation in time series is removed, ordered series of numbers is made to become smoother, can be reflected
Its basic track, and predicted in conjunction with certain model；On the basis of a sliding average, then carry out second, the
Three times or multi-level sliding average, expression formula are:
Wherein：XtRaw statistical data, N are data number.
The present invention is using diversiform-leaved poplar looper as research object, according to the history of life rule of diversiform-leaved poplar leafeating insect, in conjunction with field sampling
And on-site inspection, it calculates analysis and show that spring cankerworm's defoliation mount not yet increases substantially when two instars occur, and egg hatch
Into the whole story phase, looper spring, defoliator four ages does not occur substantially, therefore when two instars that the best prevention time is larva occur,
Prevention is carried out at this stage can effectively improve insect pest incidence.
Description of the drawings
Attached drawing 1 is the flow chart of the present invention.
Attached drawing 2 is the relation schematic diagram of the elosion period and year samming of the present invention.
Attached drawing 3 is that the relation schematic diagram of phase and year samming are gone through in the adult breeding of the present invention.
Attached drawing 4 is that the relation schematic diagram of phase and year samming are gone through in the hatching of the present invention.
Attached drawing 5 is the relation schematic diagram that larva of the present invention goes through phase and year samming.
Attached drawing 6 is diversiform-leaved poplar spring cankerworm's changes of weight trend schematic diagram of the present invention.
Attached drawing 7 is the relation schematic diagram of insect density of the present invention and year active stage samming.
Attached drawing 8 is each Developmental duration mean temperature trend schematic diagram of the present invention.
Attached drawing 9 is extreme value temperature of the present invention and dead ratio of overwintering chrysalis schematic diagram.
Specific implementation mode
The present invention is not limited by following embodiments, can be determined according to the technique and scheme of the present invention with actual conditions specific
Embodiment.
With reference to embodiment and attached drawing, the invention will be further described：
As shown in attached drawing 1,2,3,4,5,6,7,8,9, the remote sensing prediction method of phase and occurrence quantity, packet occur for diversiform-leaved poplar spring looper
Include following steps：
The first step establishes the spring looper prediction of emergence period model based on the rule of effective temperature summation, the model of the rule of effective temperature summation
For：
Wherein, N is each effective development duration of worm state；K is effective total accumulated temperature；T is each stage mean daily temperature；C is each worm
State threshold of development；SkFor effective accumulated temperature standard variance；ScFor the standard variance of each worm state threshold of development；Enter later
Second step；
Second step calculates each worm state Remote Sensing Model based on the rule of effective temperature summation, predicts the temperature of each worm state, it
Enter third afterwards to walk；
Third walks, and predicts the occurrence degree of diversiform-leaved poplar spring looper, enters the 4th step later；
4th step, verifies prediction result.
The remote sensing prediction method work that phase and occurrence quantity according to actual needs, above-mentioned diversiform-leaved poplar spring looper can be occurred is further excellent
Change or/and improves：
As shown in attached drawing 1,2,3,4,5,6,7,8,9, in the first step, respectively to each worm state threshold of development and effectively
Accumulated temperature carries out calculating extraction, including following calculating process：
(1) developmental rate of insect refers to the percentage of all growth courses being completed in the unit interval, that is, complete
A certain worm state full development process required time, the i.e. inverse of development duration, as unit of day, i.e.,：
V=1/N (2)
Wherein：V is diversiform-leaved poplar spring looper phasic development rate, and N is the number of days completed needed for worm state development；
(2) correlation analysis of development time and temperature factor of effective remote sensing accumulated temperature rule for insect, biology is in life
It during long development, needs to absorb some heats from external environment, and completes the total amount of heat needed for its growth and development process
It is a stability constant, expression formula is：
NT=K (3)
In formula：N is development duration, unit：It, T be development during mean temperature unit be DEG C, K be total accumulated temperature, unit：
Day degree；
(3) growth and development of diversiform-leaved poplar spring looper does not start in a fixed temperature, when being usually higher than 0 DEG C at one
It germinates, referred to as threshold of development, is indicated with C, expression formula may be modified such that：
N (T-C)=K (4)
Wherein, C is threshold of development, and (T-C) is average developmental temperature, and K is the total accumulated temperature of effective remote sensing；Linear regression side
Journey (formula 4) indicates that developmental rate shows significant linear relationship with temperature；
(4) effective accumulated temperature is solved, expression formula is：
T=C+KV (5)
In formula：Threshold of development C is equivalent to a in linear equation, i.e. intercept of the straight line in reference axis, and effectively distant
Feel the slope b that total accumulated temperature K is then equivalent in linear equation；
(5) C, K parameter are solved according to linear equation, is acquired with least square method, calculating formula is：
Wherein：V is developmental rate (V=1/N)；T is temperature, and n is the group number of temperature.
As shown in attached drawing 1,2,3,4,5,6,7,8,9, in second step, it is distant to calculate each worm state based on the rule of effective temperature summation
Feel model, including following procedure：
(1) to diversiform-leaved poplar spring looper worm pupa emergence period predict, derive the effective remote sensing accumulated temperature rule mathematical model of emergence period is：
Wherein, N1For the effective development duration of emergence period；K1For the effectively total accumulated temperature of emergence period；T1For emergence period mean daily temperature；
C1For emergence period threshold of development；Sk1For emergence period effective accumulated temperature standard variance；Sc1For the mark of emergence period threshold of development
Quasi- variance；
(2) geometer breeding period in diversiform-leaved poplar spring is predicted, derives to obtain adult breeding period effective remote sensing accumulated temperature rule mathematical model
For：
Wherein, N2For moth breeding period effective development duration；K2For moth breeding period effectively total accumulated temperature；T2It is flat for moth breeding period day
Equal temperature；C3For moth breeding period threshold of development；Sk4For moth breeding period effective accumulated temperature standard variance；Sc5It is developed for moth breeding period
The standard variance of origin temp；
(3) prediction of looper egg hatch phase in diversiform-leaved poplar spring, which calculates, derives to obtain incubation period effective remote sensing accumulated temperature rule mathematical model
For：
Wherein, N3For egg hatch phase effective development duration；K3For egg hatch phase effectively total accumulated temperature；T3For egg hatch
Phase mean daily temperature；C3For egg hatch phase threshold of development；Sk3For egg hatch phase effective accumulated temperature standard variance；Sc3For worm
The standard variance of egg hatching phase threshold of development；
(4) cankerworm's puberty diversiform-leaved poplar spring predict, derive larvae development phase effective remote sensing accumulated temperature rule mathematical modulo
Type is：
Wherein, N4For larvae development phase effective development duration；K4For larvae development phase effectively total accumulated temperature；T4For larvae development
Phase mean daily temperature；C4For larvae development phase threshold of development；Sk4For larvae development phase effective accumulated temperature standard variance；Sc4For children
The standard variance of worm puberty threshold of development.
As shown in attached drawing 1,2,3,4,5,6,7,8,9, in the third step, using temperature trend map method or physiological ecological is used
Index method predicts the occurrence degree of each worm state, obtains prediction result.
As shown in attached drawing 1,2,3,4,5,6,7,8,9, in the 4th step, the prediction result of each worm state is verified, including
Following steps：
(1) verification sample data is obtained, phase verification is gone through according to based on Linear Regression Model in One Unknown, then enters (2), if
Using the phase based on multiple linear regression analysis away from verification, then enter (3), according to the phase analyzed based on time series models away from
Verification then enters (4)；
(2) phase verification is gone through based on Linear Regression Model in One Unknown；Respectively with diversiform-leaved poplar spring looper develop after emergence, breeding,
Hatching, the average remote sensing temperature in 4 stages of larvae development build unitary line as independent variable to go through issue according to as dependent variable
Property regression analysis, mathematic(al) representation are：
Nn=a+bTn (12)
Wherein：NnRepresentative sprouts wings, breeding, hatches, larvae development each stage goes through issue evidence, TnIt is averaged remote sensing temperature for the stage
Degree, n=1,2,3,4, wherein 1,2,3,4 respectively represents emergence, breeding, hatching, larvae development each stage；
(3) based on the phase of multiple linear regression analysis away from verification；
Multiple linear regression equations model refers to for disclosing linear relationship between a dependent variable and multiple independents variable
The empirical model of linear regression model (LRM), multiple linear regression equations is as follows：
Y=β0+β1X1+β2X2+···βnXn (13)
In above formula, it is assumed that multiple linear equation has n independent variable X1, Xn, β i are being biased back to for equation independent variable
Return coefficient；Occur to begin to see phase of phase away from inspection to diversiform-leaved poplar spring cankerworm, the generation period of diversiform-leaved poplar spring cankerworm with sprout wings, at
Worm, hatching go through phase correlation, i.e., it is related to occur the mean temperature in period to the worms state such as looper emergences of diversiform-leaved poplar spring, adult, hatching, with Hu
It is that establish multiple linear regression equations as follows for independent variable that the mean temperature in period, which occurs, for the emergence of Yang Chun loopers, adult, hatching worm state：
N=N1+N2+N3 (14)
I.e.：N=β0+β1T1+β2T2+β3T3 (15)
Multiple regression Linear correlative analysis is carried out using statistical analysis software and obtains regression coefficient, examines diversiform-leaved poplar spring looper
Larva occur begin see phase phase away from；
(4) phase based on time series models analysis is away from verification；
For probing into the total variation tendency of variable and rough amplitude of variation of each period, and the shadow of decrease data error
It rings.Using the method for arithmetic average, the random fluctuation in time series is removed, ordered series of numbers is made to become smoother, can be reflected
Its basic track, and predicted in conjunction with certain model；On the basis of a sliding average, then carry out second, the
Three times or multi-level sliding average, expression formula are:
Wherein：XtRaw statistical data, N are data number.
Above-mentioned sliding average is the important method of repair time sequence, is simple average value and describes naturally between the two
Improved method, be according to set time the period variable is divided into part all containing n period, then take being averaged for each section
Value；
Embodiment 2：As shown in attached drawing 2 to 9, to the remote sensing prediction side of each the generation phase and occurrence quantity of diversiform-leaved poplar spring looper
Method includes the following steps：
As shown in table 1, table 2, the development duration of each worm state and mean daily temperature in table 1 are arranged and calculated such as above-mentioned reality
The required data in the formula (6) in example 1 are applied, are the data mode in table 2 after arranging.Wherein N is each worm state development duration,
T is to go through mean daily temperature in the phase, and V is the worm state developmental rate.Then the formula (6) that is utilized respectively in above-described embodiment 1 and
(7) numerical value of the threshold of development C and effective accumulated temperature K in stages such as emergence, breeding, hatching, larva are calculated.
It brings the data of table 3 into formula (6) and formula (7) respectively, respectively obtains emergence period origin temp C1With effective product
Warm K1；Breeding period origin temp C2With effective accumulated temperature K2；Incubation period origin temp C3With effective accumulated temperature K3；Larvae development starting point temperature
Spend C4With effective accumulated temperature K4.It is calculated by the data of different groups of numbers, obtained data is counted, respectively obtain each rank
The standard variance (table 3) of the origin temp and effective accumulated temperature data of section.
(1) emergence period is predicted
In the eclosion process of diversiform-leaved poplar spring looper hibernal pupae, without feed, therefore the dominant factor for influencing development is temperature.Root
Know according to the diversiform-leaved poplar spring looper development research experiment data carried out based on accumulated temperature rule, the emergence starting point temperature of diversiform-leaved poplar spring looper hibernal pupae
Degree is 0 DEG C, uses C1To indicate.Development of sprouting wings, which is fully finished, needs total accumulated temperature for 55.62 day degrees, referred to as effectively total accumulated temperature K1Table
Show.
Derivation knows that the effective remote sensing accumulated temperature rule mathematical model of emergence period is：
In formula, N is effective development duration that diversiform-leaved poplar spring looper worm pupa is sprouted wings；T is the per day remote sensing temperature of emergent stage.
As shown in Fig. 2, being carried out with development experimental data to the remote sensing temperature data of extraction using effective remote sensing accumulated temperature model
It calculates, obtains 2001-2015 diversiform-leaved poplar spring looper elosion period information.In each year various kinds diversiform-leaved poplar spring looper hibernal pupae sprout wings
It is different in size to go through the phase, the reason is that differently surface temperature difference also different, the difference pair of temperature that obtains remote sensing temperature information
The development metabolic effect of diversiform-leaved poplar spring looper hibernal pupae is apparent, and the date for turning into adult is also just respectively different.Each time diversiform-leaved poplar spring
Looper worm pupa, which turns into Adult Development, to be gone through the overall trend of phase and compares.
As shown in Fig. 2, 2009,2011, the looper hibernal pupae elosion period of diversiform-leaved poplar spring in 2013 it is whole partially long, be more than
20 days development durations, this 3 years emergent stage ensemble average temperature are respectively 2.72 DEG C, 2.51 DEG C, 2.76 DEG C, average
Temperature is significantly lower than other times, and by low temperature effect diapause phenomenon is occurred for the emergence of diversiform-leaved poplar spring looper hibernal pupae.
It is calculated in conjunction with the extraction information of remote sensing temperature according to the threshold of development of diversiform-leaved poplar spring looper worm pupa emergent stage
The beginning that diversiform-leaved poplar spring looper worm pupa over the years is sprouted wings sees the phase that is, spring looper worm pupa emergence phenomenon starts to occur.In conjunction with diversiform-leaved poplar spring looper plumage
Change progress, analysis are understood：Eclosion rate is counted since 0%, and beginning peak period refers to that eclosion progress reaches 40% or so, what peak period referred to
It is that eclosion progress completes 80% or so.The specific time sprouted wings and started is known according to remote sensing temperature information, by effective remote sensing accumulated temperature mould
Type calculates emergence integrated stages and goes through issue evidence, it is known that the whole story phase temporal information that the emergence of 15 years diversiform-leaved poplar spring looper worm pupa occurs,
The specific time (table 5) for the different phase that i.e. eclosion progress is completed.
It is more early to reach within wherein 2007,2013,2014 the threshold of development time, therefore it is also early to develop the time started
In other times.The time started the latest is 2008 and 2010, just starts emergence developmental process within 22 days 2 months or so.And plumage
Change the developmental process end time the latest be 2011 times, reason be exactly this in 2 month of year mean temperature it is integrally relatively low, sprout wings
The development time started is later and with diapause, occurs sprouting wings and develops slower phenomenon.Therefore in low temperature time, diversiform-leaved poplar spring ruler
Earwig emergence development time can universal later generation.
In general, the prediction of spring looper is begun to see ranging from 1.8 to 6.2 DEG C of phase surface temperature, corresponding to begin to see that date phase is 2 months
To March 7, see that the date is 19 days 2 months to March 21 eventually within 10th, specifically always the date can according to there and then LST data and
Effective accumulated temperature is calculated according to formula (8).It compares and finds with nearly 4 years measured datas, predicted time is when actual measurement
Between.
(2) diversiform-leaved poplar Spring cankerworm breeding period is predicted
The adult of diversiform-leaved poplar spring looper is Spring cankerworm, and experience hibernal pupae is sprouted wings.Turning into adult later can not be immediately
It is unearthed, generally need to gradually break through the soil in the afternoon in native room reasonable time statvolt.Concealment on adult daytime is in residual branch, fallen leaves, miscellaneous
Grass, the rhizosphere set greatly, are just hidden under the bark of cracking, the breaking part of trunk through what is climbd up a tree.Activity time of adult is dusk,
At night 6,7 when or so, female adult climbs up trunk, and male worm flies around trunk finds female adult mating, and place trunk lower part is in the majority.Day and night
It can lay eggs, position is mostly bark crack, at branch crack of breaking.
For diversiform-leaved poplar spring looper adult Spring cankerworm experiment proves that will not feed, the activity time is limited with spatial dimension,
Influence factor only has temperature in life cycle.The development of reproductive organs and the generation of reproductive behavior.After oviposition, adult is
The mission for completing existence, in the near future will natural death.Male worm is just dead after mating for several times.After female adult oviposition
It generally all can be dead within 2 days.Therefore since predetermined period of adult terminated to oviposition turning into adult.Adult mates
The morning and evening of time just determines the morning and evening of its death time.And adult mating needs suitable temperature condition, the hair of reproductive organs
It educates further perfect, promotes the generation of mating behavior.Therefore, the life cycle of adult also has close relationship with temperature.It is sent out
The process educated is irreversible, is all continued at various temperatures, but the speed of rate is related with optimum temperature.Higher than
When certain temperature value, the speed of developmental rate and the increase of temperature show positive correlation, therefore are also sent out for adult at the temperature value
Educate origin temp.
It will not be fed in the vital movement time of diversiform-leaved poplar spring looper adult, therefore environment temperature is its life cycle length
Unique dominant factor.According to carried out based on accumulated temperature rule diversiform-leaved poplar spring looper development research experiment data know, diversiform-leaved poplar spring looper at
Worm Spring cankerworm threshold of development is 1.32 DEG C, uses C2To indicate.The oviposition that is developed to of Spring cankerworm terminates this stage needs always
Accumulated temperature is 56.06 day degrees, referred to as effectively total accumulated temperature K2It indicates.
Derive adult breeding period effective remote sensing accumulated temperature rule mathematical model is：
In formula, N is effective development duration of diversiform-leaved poplar spring looper adult Spring cankerworm；T is that Spring cankerworm reproductive stage is per day distant
Temperature-sensitive degree.
As shown in figure 3, being carried out with development experimental data to the remote sensing temperature data of extraction using effective remote sensing accumulated temperature model
It calculates, obtains 2001-2015 Spring cankerworm reproductive stages and go through phase information.Spring cankerworm reproductive stage is gone through phase length and is become with environment temperature
Change related, the difference of temperature improves development to Spring cankerworm organ of multiplication has certain influence, Adult worms producting eggs date also different.
The phase of going through that is averaged that the phase is gone through in the breeding of 2001-2015 diversiform-leaved poplar spring looper adults sees Fig. 3 with samming variation tendency.
Wherein, 2009,2014 and 2015 year-round average temperatures in 2012 are relatively low relative to other times, therefore spring ruler
It is also longer than other times that the phase is gone through in moth breeding, respectively 14.2,15.4,13.8,15.0 days.The phase is gone through in the existence for observing Spring cankerworm over the years
Know, changing rule is that having fluctuating change starting in 2007, shows first to drop and rises afterwards, lifts the orderly variation that fluctuates.This
Variation with early and middle ten days in March temperature in recent years have it is close contact, since 2007 the variation of annual early and middle ten days temperature in March have
Apparent fluctuating change.
According to the threshold of development of Spring cankerworm reproductive stage diversiform-leaved poplar over the years is calculated in conjunction with the extraction information of remote sensing temperature
The whole story phase of spring looper worm moth.The beginning of Spring cankerworm sees that phase i.e. spring looper worm pupa emergence completes Spring cankerworm and starts to occur, from eclosion rate
100% time starts to count.Beginning peak period refers to the process of that Spring cankerworm oviposition is completed to reach 40% or so, and oviposition will enter height
The peak phase.Peak period refers to that the process of oviposition is completed 80% or so.According to the specific time that elosion period is completed, by effectively distant
Sense accumulated temperature model calculates the Spring cankerworm oviposition stage and goes through issue according to (table 6), it is known that the time letter of the Spring cankerworm oviposition whole story in 2015
Breath, whole story phase are that Spring cankerworm oviposition process has been fully completed.
Being averaged in the wherein 2001-2007 stages, remote sensing temperature is higher, and Adult Development is very fast, thus lay eggs time of origin compared with
Early, 2007-2015 adult developmental stages be averaged, and remote sensing temperature is relatively low, and it is slower that Spring cankerworm is developed, lay eggs time of origin compared with
Evening.Time of origin is more early, and peak period time of occurrence also relatively early, is completed at the same time the time of all oviposition stages of development earlier than it
His in time.The time that Spring cankerworm oviposition phenomenon occurs over 15 years is gradually elapsed by late Febuary to mid-March, accompanying this oviposition
Being fully completed for phenomenon also gradually postpones backward.And gradually elapsing backward with the time, the time sprouted with diversiform-leaved poplar gradually connect
Closely, the generation of insect pest is more easy with propagation.
In general, spring looper prediction breeding occurs to begin to see that the phase corresponds to remote sensing average temperature range to be 3.7 to 8.7 DEG C, incubates
Phase ranging from 7-15 is gone through in change, and corresponding to begin to see that phase date range is 15 days 2 months to March 17, whole story phase estimation range is 28 days 2 months
To April 2, specifically the date can be calculated according to there and then data measured and effective accumulated temperature according to formula (9) always.
It compares and finds with nearly 4 years measured datas, predicted time is slightly before the elapsed time.
(3) the looper egg hatch phase in diversiform-leaved poplar spring is predicted
The looper worm's ovum phase in diversiform-leaved poplar spring is not required to feed, and temperature is to determine the unique factor of egg hatch phase length.According to collection
Experimental data knows that diversiform-leaved poplar spring looper egg hatch threshold of development is 1.74 DEG C, uses C3To indicate.Spring looper worm's ovum output
When, mean daily temperature data are higher than origin temp, therefore are directly entered incubation period, substantially reduce brooding time length,
Therefore difficulty is increased to worm's ovum investigation.Spring cankerworm be developed to oviposition terminate this stage need effective accumulated temperature be 197.28 days
Degree, the referred to as effectively total accumulated temperature K of remote sensing3It indicates.
It calculates to derive and knows that incubation period effective remote sensing accumulated temperature rule mathematical model is：
In formula, N is that the phase is gone through in the hatching of diversiform-leaved poplar spring looper worm's ovum；T is diversiform-leaved poplar spring looper egg hatch stage earth's surface remote sensing temperature
The mean temperature of degree.
As shown in figure 4, the remote sensing temperature data to extraction and diversiform-leaved poplar spring using the effective accumulated temperature model based on remote sensing temperature
Each phasic development required temperature information of looper is calculated, and going through for 2001-2015 looper egg hatch stages in diversiform-leaved poplar spring is obtained
Issue evidence.Go through that phase length is related with variation of ambient temperature the looper egg hatch stage in diversiform-leaved poplar spring, the difference of temperature is to diversiform-leaved poplar spring ruler
The development of earwig egg hatch has certain influence, but also the date that larva occurs is different.2001-2015 diversiform-leaved poplar spring looper worms
Egg hatching goes through the average value of phase and samming variation tendency is shown in Fig. 4.
Wherein, downward trend is presented in 2003-2006 earth's surfaces remote sensing temperature, reaches lowest trough by 2006；2006-2009
Temperature gradually rises, 2009 to summit；Then decline year by year, until minimizing within 2011 value, coming years undulation becomes
Change little.Therefore the hatching of diversiform-leaved poplar spring looper worm's ovum changes with the fluctuation of temperature, and temperature is higher, and hatching is faster, and it is shorter to go through the phase；
Conversely, hatching is slower, it is longer to go through the phase.Wherein 2006 year-round average temperatures are minimum, and hatch and go through the phase also most, mean temperature and go through time value
Respectively 11.03 DEG C and 21.4 days.
According to the threshold of development in looper egg hatch stage in diversiform-leaved poplar spring, in conjunction with remote sensing temperature information data, reckoning is gone through
The whole story phase of year egg hatch.The beginning of diversiform-leaved poplar spring looper worm's ovum sees that phase i.e. Spring cankerworm oviposition is completed to start, from spawning rate 100%
Time starts to count.Beginning peak period refers to that the completion of diversiform-leaved poplar spring looper egg hatch reaches 40% or so, and hatching will enter peak period.
Peak period refers to that hatching is completed 80% or so.According to the specific time that elosion period is completed, by effective remote sensing accumulated temperature model
It calculates diversiform-leaved poplar spring looper egg hatch and goes through issue according to (table 7), it is known that the time of 15 years diversiform-leaved poplar spring looper egg hatch whole story believes
Breath, the whole story phase is that diversiform-leaved poplar spring looper egg hatch process has been fully completed, i.e. the conversion stage of worm's ovum to larva is complete
At.
Being averaged in wherein 2001 to 2007 stages, remote sensing temperature is higher, and egg hatch development is very fast, therefore larva goes out
Relatively early between current, being averaged 2007 to 2015 hatching stages of development, remote sensing temperature is slightly lower, and hatching rate is slower, and larva occurs
Time is later.Time of origin is more early, and peak period time of occurrence also relatively early, is completed at the same time the time of all hatching stages of development
Earlier than other times.The time that Spring cankerworm egg hatch phenomenon occurs over 15 years is gradually elapsed by mid-March to late March and 3
The end of month, accompanying this being fully completed for phenomenon of hatching also gradually postpone backward.
In general, spring looper prediction hatching occurs to begin to see that the phase corresponds to remote sensing average temperature range to be 14.6-18.4 DEG C, incubates
Phase ranging from 15-21 is gone through in change, and corresponding to begin to see that phase date range is March 2 to March 31, whole story phase estimation range is March 25
Day, specifically the date can be surveyed according to there and then LST data and effective accumulated temperature according to formula (10) always to April 29
It calculates.It compares and finds with nearly 4 years measured datas, predicted time is slightly before the elapsed time.
In formula, N1 is the effective development duration of emergence period；K1 is the effectively total accumulated temperature of emergence period；T1 is the per day temperature of emergence period
Degree；
In formula, N2 is moth breeding period effective development duration；K2 is moth breeding period effectively total accumulated temperature；T2 is that moth breeding period day is flat
Equal temperature
In formula, N3For diversiform-leaved poplar spring looper egg hatch phase development duration；T3For egg hatch phase per day remote sensing temperature.
In formula, N4 is diversiform-leaved poplar spring cankerworm's development duration；T4 is the per day remote sensing temperature of larval stage.
As shown in table 8, according to the threshold of development of cankerworm's stage of development diversiform-leaved poplar spring, sprout wings in conjunction with diversiform-leaved poplar spring looper
Issue evidence is gone through in time started and each phasic development, calculates that the beginning that diversiform-leaved poplar spring cankerworm over the years pupates sees the phase, i.e. spring looper such as soil
Room phenomenon of pupating is done to start to occur.Beginning peak period refers to that larvae development completion reaches 40% or so, and the diversiform-leaved poplar spring looper amount of pupating will
Into peak period, i.e. larvae development completion pupates quantity up to 80% or so.Know the specific of beginning that sprout wings according to remote sensing temperature information
Time calculates the stage by effective remote sensing accumulated temperature model and goes through issue evidence, it is known that the whole story of 15 years diversiform-leaved poplar spring looper worm larvae pupation
Phase temporal information (table 8).
It is more early to reach within wherein 2007 the threshold of development time, therefore buries and pupate the time started also earlier than its another year
Part.The time started the latest is 2013 and 2014,22 days or so the 2 months processes that just germinate.It buries the deadline of pupating
The latest be also 2013 and 2014, this 2 years larva growth and development stage mean daily temperatures are less than other times, and emergence
Time started is also later than other times, therefore the development time period of spring cankerworm is longer, is also got over to the harm of Populus Euphratica
Greatly.
In general, spring looper prediction larva occurs to begin to see that the phase corresponds to remote sensing average temperature range to be 12.2-20.9 DEG C, incubates
Change goes through the phase ranging from 24-48 days, and corresponding to begin to see that phase date range is March 29 to May 09, whole story phase estimation range is 2 months
To June 31, specifically the date can carry out according to there and then LST data and effective accumulated temperature according to formula (11) always on 21
Measuring and calculating.It compares and finds with nearly 4 years measured datas, predicted time is slightly before the elapsed time.
Embodiment 3：Prediction of emergence size process in the looper generation phase in diversiform-leaved poplar spring is as follows：
As shown in table 9, according to survey data and statistics display of gathering information, the active stage of spring cankerworm is annual
2-5 months, the mark that wherein spring looper active stage starts are that the emergence of hibernal pupae starts, and are buried after 5 instar of spring looper is ripe
It does room and pupates and represent the end of looper active stage in spring into the dormancy phase.It can be obtained by the phase prediction result of going through of each worm state of spring looper
The prediction result (table 9) of looper active stage in spring.
Known by active stage Information Statistics, the prediction of looper active stage in spring start just to be reached in 2007 January 29 time earliest
Emergence standard, surface temperature are stablized through zero degree, and heat transfer is led to, and the hibernal pupae total to soil layer carries out accumulated temperature, make hibernal pupae
Emergence takes place.Start to sprout wings the latest known to simultaneously is 22 days 2 months, wherein respectively 2010,2013 and 2014
The spring temperature recovery in three times is later, the evening of temperature rise, and the effective accumulated temperature sprouted wings and occurred is not achieved in hibernal pupae, then will not
Start to sprout wings.For overall trend, the emergence time started from 2001 to 2015 year gradually elapses backward.
The active stage of spring looper is to live in seclusion to terminate with spring cankerworm's development and maturation phase, and looper active stage in spring is pre- between 15 years
It surveys in result and terminates earliest to be 2007, be put into the whole story phase at the beginning of 5 months.The latest be in mid-June, 2014.2001 extremely
The date that looper active stage in spring terminates between 2015 is also constantly elapsing backward, when prediction result shows the harm of spring looper
Between gradually extending, in the backward passage delay diversiform-leaved poplar branches and leaves development it is more long, it is also bigger to the harm of diversiform-leaved poplar.
In general, the active stage of diversiform-leaved poplar spring looper is to gradually increase, while with smoothly passing 0 DEG C of time increasingly
Evening, looper active stage in spring, also become strong to the influence that spring diversiform-leaved poplar growth and development is brought gradual, the Populus Euphratica of spring looper harm
Development time is throughout the year longer, then the death rate of diversiform-leaved poplar will gradually increase.Prediction result shows, over 15 years active stage start when
Between range January 29 to 22 days 2 months, active stage, goes through the phase ranging from 67 to 100 days, and the beginning for completion of sprouting wings sees phase range 2
Months 6 days to March 7, and the predicted time that active stage terminates ranging from May 1 to June 21.
As shown in Fig. 5, table 10, the Best Times of prevention diversiform-leaved poplar spring looper, the mark that the looper insect pest of diversiform-leaved poplar spring occurs are determined
It is the appearance for eating leaf larva, i.e., enters larval stage, tender shoots, tender leaf to Populus Euphratica green sprouting after the hatching of diversiform-leaved poplar spring looper
It is endangered.The diversiform-leaved poplar spring, cankerworm showed by survey data, was divided into 5 grades：1 instar, 2 instars, 3 instars, 4 instars,
5 instars.Each age of spring cankerworm, which is divided into, grows early period, mid-term, later stage, and the spring, cankerworm nibbled diversiform-leaved poplar since instar
Tender leaf, weight rapidly increase.Pass through each growth phase average weight variation tendency (Fig. 9) of the larva of across comparison each age
Know, first-instar young later stage average weight rises to 132.6% with preliminary phase ratio, and later stage and the preliminary phase of second instar larvae compare growth rate
It is 436.8%, third-instar larvae later stage and preliminary phase ratio growth rate are 243.4%, and the four-age larva same period is compared to growth rate
258.7%, the five-age larva same period is 254.2% compared to growth rate.There are data it is found that each age, the weight of spring looper are all
It is doubled and redoubled, this is related with spring looper development by metamorphosis, and the larva of each age grade can slough off old skin, break the limit of body length
System, grows into the larva of next age grade.Longitudinal comparison finds that 2 instar larvae later stage average weights are 1 instar larvae later stage average weights
18.52 times；3 instar larvae later stage average weights are 3.46 times of 2 instar larvae later stage average weights, are that 1 instar larvae later stage is average
64 times of weight；4 instar larvae later stage average weights are 3.24 times of 3 instar larvae later stage average weights, are that 2 instar larvae later stages are flat
11.21 times of equal weight, are 208 times of 1 instar larvae later stage average weight；5 instar larvae later stage average weights were 3 instar larvae later stages
10.28 times of average weight are 35.54 times of 2 instar larvae later stage average weights, are the 658 of 1 instar larvae later stage average weight
Times.While age grade increases, also geometric growth is being presented in average weight for spring cankerworm.The food source of diversiform-leaved poplar spring looper
It is exactly tender leaf, the tender shoots that diversiform-leaved poplar newly sprouts, and the variation of diversiform-leaved poplar spring looper weight intuitively embodies the extent of injury to diversiform-leaved poplar.
Most obvious one variation is exactly in third-instar larva to this stage of four instars, and the later stage average weight of third-instar larva is
Reach 64 times of an instar later stage average weight, it follows that the third-instar larva stage of spring cankerworm is a watershed, three ages
The defoliation mount of worm has begun drastically to increase, therefore needs to solve before aggravating the harm of diversiform-leaved poplar to the prevention of spring cankerworm
Certainly, so an instar and two instar stages can be prevented.
Wherein larvae development time span is about 40 days or so, according to each age development time length of diversiform-leaved poplar spring cankerworm
Know that an instar development duration is about 10 days, the development duration of two instars is about 8 days, then the generation of two instars and tailend are about 10
To 18 days, and the hatching of spring looper entered the time of whole story phase and the time of origin of two instars is sufficiently close to (table 10).
Know according to the time of origin comparison of two instar time of origin of spring looper and spring looper second instar larvae, 2005,
2006 spring in time loopers hatch the whole story phase a little later, and when the development of remaining one instar of spring in time looper is completed, spring looper worm's ovum majority is
It is completed through hatching, becomes larva.It chose for two instar stages to prevent spring looper, can effectively kill the children for having hatched completion
Worm, control effect are preferable.A small amount of unhatched remaining phase in protective agents can also hatch and then be killed successively, reach prevention
The rationalization of effect and high efficiency, and the harm of Populus Euphratica was also strangled in the slight generation phase.
In conclusion the foundation of most preferably prevention period selection be each Ling Chun cankerworms to the extent of injury of diversiform-leaved poplar and
It prevents efficiency highest period, the time that two instars occur is the best prevention time, and spring in stage cankerworm's defoliation mount is not yet
It increases substantially, and the hatching rate of spring looper worm's ovum also enters the whole story phase, two instars, which carry out prevention, can greatly improve prevention
Efficiency.
Occurrence degree of the diversiform-leaved poplar spring looper within the generation phase is predicted, the prediction of emergence size is the important interior of insect pest forecast
One of hold, the projected relationship of pest occurrence quantity to the dynamics for implementing to prevent.Pest occurrence quantity and hazard of plant degree and loss late
There is direct relation, therefore, grasping developmental rate, hatching rate, the survival rate of hibernal pupae and the environmental factor of pest influences quantity
Size, be the basis of the pest prediction of emergence size.The prediction of diversiform-leaved poplar spring looper occurrence quantity focuses mostly on the statistics of after to calamity data
In analysis, according to existing diversiform-leaved poplar spring looper Investigation of Pests data, occurred in conjunction with the temperature data that MODIS temperature products extract
The research of degree.
As shown in Figure 6,7, be using temperature trend map method prediction result diversiform-leaved poplar spring looper growth and development and temperature change
Change closely related, has different metamorphosis to the variation of temperature under different worm states.Because diversiform-leaved poplar spring looper belongs to poecilothermia
Insect, its growth and development speed is mostly derived from the rate of internal metabolism, and the variation of insect metabolism is related with temperature.
Temperature reaches certain standard, and metabolism will be accelerated, and accelerates to grow；When temperature is less than preference temperature, metabolism
Slow down, growth and development rate reduces；Simultaneously under high or extremely low extreme temperature, the growth and development of diversiform-leaved poplar spring looper can but subtract
It is slow.
(1) spring looper insect density and active stage samming
The mean temperature of the insect density for collecting survey data and active stage upper one year were compared (Fig. 7), found
Steady situation was presented with active stage samming variation tendency between coming year border in 2009.Spring looper insect density data show spring looper children
Worm occurrence quantity year is increased year by year from 2012 to 2015, this is related with upper spring fraction of the year looper insect population.Spring looper children
Borer population amount increases, and the adult quantity of second year can gradually increase, cause egg laying amount drastically to increase, then cause the quick-fried of larva quantity
Hair.
(2) looper diversiform-leaved poplar spring, temperature changing trend active stage
The emergent stage of diversiform-leaved poplar spring looper hibernal pupae just have with temperature it is higher contact, only when the environment temperature of hibernal pupae
When degree reaches 0 DEG C of threshold of development, it can just start to sprout wings.Diversiform-leaved poplar spring looper worm pupa is to encounter in experience summer, two season of winter simultaneously
Extreme temperature can lead to the death of diversiform-leaved poplar spring looper worm pupa.And diversiform-leaved poplar spring looper worm pupa turns into after adult Spring cankerworm, it is living
Dynamic time length is also influenced by temperature.The hatching of diversiform-leaved poplar spring looper worm's ovum is even more to be limited by temperature, in temperature change play
In the case of strong, impaired development.And requirement of the growth and development of diversiform-leaved poplar spring cankerworm to temperature is minimum, need to only be in centainly
Under appropriate temperature conditions, population quantity can expand rapidly, and wildness is caused disaster.Especially the diversiform-leaved poplar spring, cankerworm can be expired in foodstuff
In the case of foot, Population fluctuation is caused by being led based on temperature.Therefore it is inquired by drawing temperature trend map
The relationship of occurrence quantity and temperature components, to carry out the prediction of emergence size.
As shown in figure 8, the remote sensing temperature data according to the extraction of MODIS temperature products, in conjunction with each worm state hair of diversiform-leaved poplar spring looper
The phase is gone through in life, counts the mean temperature of each worm state growth and development stage of each time.Hatch with the looper of diversiform-leaved poplar spring in 2014 within wherein 2001
Stage mean temperature is relatively low, and whole fluctuations are larger, and insect pest occurrence quantity is lighter；The looper hibernal pupae emergence rank of diversiform-leaved poplar spring in 2012
Section and adult Spring cankerworm operational phase mean temperature variation it is smaller, Spring cankerworm mating, oviposition activity be affected, insect pest occur compared with
Gently；2004,2007 and 2011 cankerworm diversiform-leaved poplar spring, mean temperatures stage of development are more than 20 DEG C, then the development speed of larva
Degree is very fast, and the outburst of insect pest is very fast, and generation quantity is more, and insect pest occurs extremely heavy；Remaining time mean temperature is in gradually increase
Trend, on the growth and development of diversiform-leaved poplar spring looper rise it is positive influence, the generation quantity of diversiform-leaved poplar spring looper steadily increases, and insect pest occurs
Seriously.
As shown in figure 9, the suspend mode occurred using each worm state of prediction result diversiform-leaved poplar spring looper of some eco-physiological indexes method with it is stagnant
It educates, is the adaptation management to unsuitable environmental condition.When bad condition occurs, if suspend mode or diapause shape cannot be entered in time
State, population then may be caused mortality by precipitate strike, and insect pest occurs gently；Otherwise population can save
It is good, and occur greatly caused by more than survival worm amount.Therefore the ratio in the generation period and generation of the suspend mode of insect and diapause characteristic, can
Trend prediction is carried out for quantity to occur to future.The investigation for facultative diapause insect occurring the time and ratio of diapause, can be pre-
Survey the conversion ratio (i.e. occurrence quantity) in its last generation.As long as in investigation to residing for certain pest in the period of critical photoperiod occurs
Worm state (age) carries out the investigation of quantity, then can determine whether out that how many worm amount will not occur diapause and continue to develop to next worm state.
To obtain the occurrence quantity and coming year occurrence tendency of next worm state.
In the various regions worm state growth course of diversiform-leaved poplar spring looper, diversiform-leaved poplar spring cankerworm pupate into underground phases-time compared with
Long, experience summer, autumn, three seasons of winter then proceed to develop to next worm state.Wherein annual extreme temperature has summer respectively
The extremely low temperature of very high temperature and winter.Under very high temperature and pole low temperature condition, the biological enzyme in diversiform-leaved poplar spring looper worm pupal cell can be killed,
And then lead to the death of diversiform-leaved poplar spring looper hibernal pupae polypide.The death rate of hibernal pupae is higher, the generation number of diversiform-leaved poplar current year, looper spring
Amount is then lower, and damage level is lighter.
As shown in figure 9, according to diversiform-leaved poplar spring looper insect pest field survey data, in conjunction with the remote sensing of MODIS temperature products extraction
Data Data, statistics obtain extreme temperature and the relationship of dead ratio of overwintering chrysalis.
The death rate of annual diversiform-leaved poplar spring looper worm pupa is related with the extreme temperature of summer upper one year and winter, soft using Spss
Part carries out correlation analysis to statistical data and knows, very high temperature is 0.075 with diversiform-leaved poplar spring looper dead ratio of overwintering chrysalis relative coefficient,
Its notable coefficient is 0.904, and extremely low temperature is 0.102 with diversiform-leaved poplar spring looper dead ratio of overwintering chrysalis relative index, and notable coefficient is
0.870, known by analysis data, extreme temperature and diversiform-leaved poplar spring looper worm pupa are shown in existing 5 years diversiform-leaved poplar spring looper survey datas
Dead rate dependence unobvious.
The above technical characteristic constitutes the embodiment of the present invention, can basis with stronger adaptability and implementation result
Actual needs increases and decreases non-essential technical characteristic, to meet the needs of different situations.
The beginning of 1 diversiform-leaved poplar spring of table each worm state of looper sees that phase and correspondence go through phase mean temperature
Each worm state effective accumulated temperature (K) of 2 diversiform-leaved poplar spring of table looper and threshold of development (C)
| Group number | N1 | T1 | V1 | N2 | T2 | V2 | N3 | T3 | V3 | N4 | T4 | V4 |
| 1 | 22 | 2.5 | 0.0455 | 16 | 4.9 | 0.0639 | 16 | 14.1 | 0.0629 | 40 | 17.2 | 0.0253 |
| 2 | 16 | 3.5 | 0.0625 | 12 | 6.1 | 0.0853 | 15 | 15.0 | 0.0674 | 42 | 16.8 | 0.0241 |
| 3 | 19 | 2.9 | 0.0526 | 18 | 4.5 | 0.0566 | 18 | 12.8 | 0.0558 | 40 | 17.2 | 0.0252 |
| 4 | 15 | 3.7 | 0.0667 | 10 | 7.1 | 0.1030 | 15 | 15.1 | 0.0677 | 40 | 17.0 | 0.0248 |
| 5 | 15 | 3.7 | 0.0661 | 13 | 5.8 | 0.0792 | 17 | 13.3 | 0.0587 | 34 | 18.7 | 0.0294 |
| 6 | 13 | 4.4 | 0.0767 | 18 | 4.4 | 0.0550 | 17 | 13.6 | 0.0602 | 37 | 17.8 | 0.0269 |
| 7 | 17 | 3.1 | 0.0588 | 15 | 5.0 | 0.0654 | 20 | 11.7 | 0.0507 | 43 | 16.5 | 0.0233 |
| 8 | 15 | 3.1 | 0.0649 | 15 | 5.0 | 0.0648 | 20 | 11.6 | 0.0500 | 40 | 17.1 | 0.0249 |
3 diversiform-leaved poplar spring of table each worm state threshold of development of looper and effective accumulated temperature data
4 average annual temperature (DEG C) of table and the different depth soil moisture (DEG C)
Table 5, which is sprouted wings, develops schedule timetable
6 Spring cankerworm reproductive stage whole story timetable of table
7 diversiform-leaved poplar spring of table looper egg hatch stage whole story timetable
The 8 diversiform-leaved poplar spring of table, progress occurred for cankerworm
9 cankerworm diversiform-leaved poplar spring, prediction result active stage of table
| Time | Steady 0 DEG C of time of > | Active stage, goes through the phase | Sprout wings and begins to see the phase | The whole story of the pupating phase |
| 2002 | 2/10 | 74 | 2/22 | 5/22 |
| 2003 | 2/6 | 90 | 2/19 | 6/6 |
| 2004 | 2/10 | 67 | 2/20 | 5/3 |
| 2005 | 2/14 | 73 | 2/22 | 5/25 |
| 2006 | 2/6 | 83 | 2/19 | 5/22 |
| 2007 | 1/29 | 84 | 2/6 | 5/1 |
| 2008 | 2/22 | 80 | 3/4 | 6/2 |
| 2009 | 2/6 | 94 | 2/20 | 6/1 |
| 2010 | 2/22 | 74 | 3/2 | 5/20 |
| 2011 | 2/10 | 81 | 3/1 | 5/28 |
| 2012 | 2/14 | 86 | 2/22 | 6/19 |
| 2013 | 2/22 | 92 | 3/7 | 6/12 |
| 2014 | 2/22 | 97 | 3/5 | 6/21 |
| 2015 | 2/6 | 83 | 2/20 | 5/28 |
| Estimation range | 01/29-02/22 | 67-100 | 02/06-03/07 | 05/01-06/21 |
Table 10 hatches whole story phase and two instar time of origins
| Time | Hatch the whole story phase | One instar whole story phase | Two instar whole story phases |
| 2001 | 3/29-4/3 | 3/24-3/28 | 4/1-4/4 |
| 2002 | 4/2-4/6 | 4/3-4/7 | 4/11-4/15 |
| 2003 | 4/2-4/6 | 3/31—4/3 | 4/8-4/12 |
| 2004 | 4/3-4/7 | 3/31-4-3 | 4/8-4/12 |
| 2005 | 4/14-4/18 | 4/9-4/13 | 4/17-4/21 |
| 2006 | 4/10-4/13 | 4/5-4/9 | 4/13-4/17 |
| 2007 | 3/22-3/26 | 3/23-3/27 | 3/31-4/3 |
| 2008 | 4/14-4/18 | 4/15-4/19 | 4/23-4/27 |
| 2009 | 4/10-4/14 | 4/8-4/12 | 4/16-4/20 |
| 2010 | 4/3-4/7 | 4/7-4/11 | 4/15-4/19 |
| 2011 | 4/20-4/24 | 4/16-4/20 | 4/24-4/28 |
| 2012 | 4/20-4/25 | 4/14-4/18 | 4/22-4/26 |
| 2013 | 4/14-4/18 | 4/14-4/18 | 4/22-4/26 |
| 2014 | 4/20-4/23 | 4/18-4/22 | 4/26-4/29 |
| 2015 | 4/17-4/21 | 4/16-4/20 | 4/24-4/28 |
Claims (9)
1. the remote sensing prediction method of phase and occurrence quantity occur for a kind of diversiform-leaved poplar spring looper, it is characterised in that include the following steps：
The first step, establishes the spring looper prediction of emergence period model based on the rule of effective temperature summation, and the model of the rule of effective temperature summation is：
Wherein, N is each effective development duration of worm state；K is effective total accumulated temperature；T is each stage mean daily temperature；C sends out for each worm state
Educate origin temp；SkFor effective accumulated temperature standard variance；ScFor the standard variance of each worm state threshold of development；Enter second later
Step；
Second step, calculate each worm state Remote Sensing Model based on the rule of effective temperature summation, the temperature of each worm state is predicted, it is laggard
Enter third step；
Third walks, and predicts the occurrence degree of diversiform-leaved poplar spring looper, enters the 4th step later；
4th step, verifies prediction result.
2. the remote sensing prediction method of phase and occurrence quantity occur for diversiform-leaved poplar spring looper according to claim 1, it is characterised in that the
In one step, calculating extraction, including following calculating process are carried out to each worm state threshold of development and effective accumulated temperature respectively：
(1) developmental rate of insect refers to the percentage that all growth courses are completed in the unit interval, that is, completes a certain worm state
The time required to full development process, the inverse of development duration, i.e.,：
V=1/N (2)
Wherein：V is diversiform-leaved poplar spring looper phasic development rate, and N is the number of days completed needed for worm state development, as unit of day；
(2) effectively correlation analysis of the remote sensing accumulated temperature rule for the development time and temperature factor of insect, biology are sent out in growth
It during educating, needs to absorb some heats from external environment, the total amount of heat completed needed for its growth and development process is one
Stability constant, expression formula are：
NT=K (3)
In formula：N is development duration, unit：It, T be development during mean temperature unit be DEG C, K be total accumulated temperature, unit：Day degree；
(3) growth and development of diversiform-leaved poplar spring looper does not start in a fixed temperature, germinates when being higher than 0 DEG C at one,
Referred to as threshold of development indicates that expression formula is revised as with C：
N (T-C)=K (4)
Wherein, C is threshold of development, and (T-C) is average developmental temperature, and K is the total accumulated temperature of effective remote sensing；Linear regression equation
(formula 4) indicates that developmental rate shows significant linear relationship with temperature；
(4) effective accumulated temperature is solved, expression formula is：
T=C+KV (5)
In formula：Threshold of development C is equivalent to a in linear equation, i.e. intercept of the straight line in reference axis, and effectively remote sensing is total
Accumulated temperature K is then equivalent to the slope b in linear equation；
(5) C, K parameter are solved according to linear equation, is acquired with least square method, calculating formula is：
Wherein：V is developmental rate (V=1/N)；T is temperature, and n is the group number of temperature.
3. the remote sensing prediction method of phase and occurrence quantity occurs for diversiform-leaved poplar spring looper according to claim 1 or 2, in second step,
Calculate each worm state Remote Sensing Model based on the rule of effective temperature summation, including following procedure：
(1) to diversiform-leaved poplar spring looper worm pupa emergence period predict, derive the effective remote sensing accumulated temperature rule mathematical model of emergence period is：
Wherein, N1For the effective development duration of emergence period；K1For the effectively total accumulated temperature of emergence period；T1For emergence period mean daily temperature；C1For
Emergence period threshold of development；Sk1For emergence period effective accumulated temperature standard variance；Sc1For the standard side of emergence period threshold of development
Difference；
(2) to geometer breeding period in diversiform-leaved poplar spring predict, derive adult breeding period effective remote sensing accumulated temperature rule mathematical model is：
Wherein, N2For moth breeding period effective development duration；K2For moth breeding period effectively total accumulated temperature；T2For moth breeding period per day temperature
Degree；C3For moth breeding period threshold of development；Sk4For moth breeding period effective accumulated temperature standard variance；Sc5For moth breeding period development zero
The standard variance of temperature；
(3) the looper egg hatch phase in diversiform-leaved poplar spring prediction calculate derive incubation period effective remote sensing accumulated temperature rule mathematical model is：
Wherein, N3For egg hatch phase effective development duration；K3For egg hatch phase effectively total accumulated temperature；T3For the egg hatch phase day
Mean temperature；C3For egg hatch phase threshold of development；Sk3For egg hatch phase effective accumulated temperature standard variance；Sc3It is incubated for worm's ovum
The standard variance of change phase threshold of development；
(4) cankerworm's puberty diversiform-leaved poplar spring is predicted, derive the mathematical model of larvae development phase effective remote sensing accumulated temperature rule is：
Wherein, N4For larvae development phase effective development duration；K4For larvae development phase effectively total accumulated temperature；T4For the larvae development phase day
Mean temperature；C4For larvae development phase threshold of development；Sk4For larvae development phase effective accumulated temperature standard variance；Sc4It is sent out for larva
Educate the standard variance of phase threshold of development.
4. the remote sensing prediction method of phase and occurrence quantity occur for diversiform-leaved poplar spring looper according to claim 1 or 2, it is characterised in that
In third step, predicts, predicted using temperature trend map method or using some eco-physiological indexes method to the occurrence degree of each worm state
As a result.
5. the remote sensing prediction method of phase and occurrence quantity occur for diversiform-leaved poplar spring looper according to claim 3, it is characterised in that the
In three steps, is predicted using temperature trend map method or using some eco-physiological indexes method to the occurrence degree of each worm state, obtain prediction knot
Fruit.
6. the remote sensing prediction method of phase and occurrence quantity occur for diversiform-leaved poplar spring looper according to claim 1 or 2, it is characterised in that
In 4th step, the prediction result of each worm state is verified, is included the following steps：
(1) verification sample data is obtained, phase verification is gone through according to based on Linear Regression Model in One Unknown, then enters (2), according to
Based on the phase of multiple linear regression analysis away from verification, then enter (3), according to the phase analyzed based on time series models away from school
It tests, then enters (4)；
(2) phase verification is gone through based on Linear Regression Model in One Unknown；Respectively with diversiform-leaved poplar spring looper develop after emergence, breeding, hatching,
The average remote sensing temperature in 4 stages of larvae development builds one-variable linear regression as independent variable to go through issue according to as dependent variable
Analysis, mathematic(al) representation are：
Nn=a+bTn (12)
Wherein：NnRepresentative sprouts wings, breeding, hatches, larvae development each stage goes through issue evidence, TnIt is averaged remote sensing temperature for the stage, n
=1,2,3,4, wherein 1,2,3,4 respectively represents emergence, breeding, hatching, larvae development each stage；
(3) based on the phase of multiple linear regression analysis away from verification；
Multiple linear regression equations model refers to for disclosing the linear of linear relationship between a dependent variable and multiple independents variable
The empirical model of regression model, multiple linear regression equations is as follows：
Y=β0+β1X1+β2X2+···βnXn (13)
In above formula, it is assumed that multiple linear equation has n independent variable X1, Xn, β i are the partial regression systems of equation independent variable
Number；Occur to begin to see phase of phase away from inspection to diversiform-leaved poplar spring cankerworm, generation period of diversiform-leaved poplar spring cankerworm and emergence, adult,
Phase correlation is gone through in hatching, i.e., related to the worms state generation mean temperature in period such as looper emergences of diversiform-leaved poplar spring, adult, hatching, with diversiform-leaved poplar
It is that establish multiple linear regression equations as follows for independent variable that the mean temperature in period, which occurs, for spring looper emergence, adult, hatching worm state：
N=N1+N2+N3 (14)
I.e.：N=β0+β1T1+β2T2+β3T3 (15)
Multiple regression Linear correlative analysis is carried out using statistical analysis software and obtains regression coefficient, examines diversiform-leaved poplar spring cankerworm
Occur begin see phase phase away from；
(4) phase based on time series models analysis is away from verification；
For probing into the total variation tendency of variable and rough amplitude of variation of each period, and the influence of decrease data error.It adopts
With the method for arithmetic average, the random fluctuation in time series is removed, ordered series of numbers is made to become smoother, can reflect that it is basic
Track, and predicted in conjunction with certain model；On the basis of a sliding average, then carry out second, third time or
Multi-level sliding average, expression formula are:
Wherein：XtRaw statistical data, N are data number.
7. the remote sensing prediction method of phase and occurrence quantity occur for diversiform-leaved poplar spring looper according to claim 3, it is characterised in that the
In four steps, the prediction result of each worm state is verified, is included the following steps：
(1) verification sample data is obtained, phase verification is gone through according to based on Linear Regression Model in One Unknown, then enters (2), according to
Based on the phase of multiple linear regression analysis away from verification, then enter (3), according to the phase analyzed based on time series models away from school
It tests, then enters (4)；
(2) phase verification is gone through based on Linear Regression Model in One Unknown；Respectively with diversiform-leaved poplar spring looper develop after emergence, breeding, hatching,
The average remote sensing temperature in 4 stages of larvae development builds one-variable linear regression as independent variable to go through issue according to as dependent variable
Analysis, mathematic(al) representation are：
Nn=a+bTn (12)
Wherein：NnRepresentative sprouts wings, breeding, hatches, larvae development each stage goes through issue evidence, TnIt is averaged remote sensing temperature for the stage, n
=1,2,3,4, wherein 1,2,3,4 respectively represents emergence, breeding, hatching, larvae development each stage；
(3) based on the phase of multiple linear regression analysis away from verification；
Multiple linear regression equations model refers to for disclosing the linear of linear relationship between a dependent variable and multiple independents variable
The empirical model of regression model, multiple linear regression equations is as follows：
Y=β0+β1X1+β2X2+···βnXn (13)
In above formula, it is assumed that multiple linear equation has n independent variable X1, Xn, β i are the partial regression systems of equation independent variable
Number；Occur to begin to see phase of phase away from inspection to diversiform-leaved poplar spring cankerworm, generation period of diversiform-leaved poplar spring cankerworm and emergence, adult,
Phase correlation is gone through in hatching, i.e., related to the worms state generation mean temperature in period such as looper emergences of diversiform-leaved poplar spring, adult, hatching, with diversiform-leaved poplar
It is that establish multiple linear regression equations as follows for independent variable that the mean temperature in period, which occurs, for spring looper emergence, adult, hatching worm state：
N=N1+N2+N3 (14)
I.e.：N=β0+β1T1+β2T2+β3T3 (15)
Multiple regression Linear correlative analysis is carried out using statistical analysis software and obtains regression coefficient, examines diversiform-leaved poplar spring cankerworm
Occur begin see phase phase away from；
(4) phase based on time series models analysis is away from verification；
For probing into the total variation tendency of variable and rough amplitude of variation of each period, and the influence of decrease data error.It adopts
With the method for arithmetic average, the random fluctuation in time series is removed, ordered series of numbers is made to become smoother, can reflect that it is basic
Track, and predicted in conjunction with certain model；On the basis of a sliding average, then carry out second, third time or
Multi-level sliding average, expression formula are:
Wherein：XtRaw statistical data, N are data number.
8. the remote sensing prediction method of phase and occurrence quantity occur for diversiform-leaved poplar spring looper according to claim 4, it is characterised in that the
In four steps, the prediction result of each worm state is verified, is included the following steps：
(1) verification sample data is obtained, phase verification is gone through according to based on Linear Regression Model in One Unknown, then enters (2), according to
Based on the phase of multiple linear regression analysis away from verification, then enter (3), according to the phase analyzed based on time series models away from school
It tests, then enters (4)；
(2) phase verification is gone through based on Linear Regression Model in One Unknown；Respectively with diversiform-leaved poplar spring looper develop after emergence, breeding, hatching,
The average remote sensing temperature in 4 stages of larvae development builds one-variable linear regression as independent variable to go through issue according to as dependent variable
Analysis, mathematic(al) representation are：
Nn=a+bTn (12)
Wherein：NnRepresentative sprouts wings, breeding, hatches, larvae development each stage goes through issue evidence, TnIt is averaged remote sensing temperature for the stage, n
=1,2,3,4, wherein 1,2,3,4 respectively represents emergence, breeding, hatching, larvae development each stage；
(3) based on the phase of multiple linear regression analysis away from verification；
Multiple linear regression equations model refers to for disclosing the linear of linear relationship between a dependent variable and multiple independents variable
The empirical model of regression model, multiple linear regression equations is as follows：
Y=β0+β1X1+β2X2+···βnXn (13)
In above formula, it is assumed that multiple linear equation has n independent variable X1, Xn, β i are the partial regression systems of equation independent variable
Number；Occur to begin to see phase of phase away from inspection to diversiform-leaved poplar spring cankerworm, generation period of diversiform-leaved poplar spring cankerworm and emergence, adult,
Phase correlation is gone through in hatching, i.e., related to the worms state generation mean temperature in period such as looper emergences of diversiform-leaved poplar spring, adult, hatching, with diversiform-leaved poplar
It is that establish multiple linear regression equations as follows for independent variable that the mean temperature in period, which occurs, for spring looper emergence, adult, hatching worm state：
N=N1+N2+N3 (14)
I.e.：N=β0+β1T1+β2T2+β3T3 (15)
Multiple regression Linear correlative analysis is carried out using statistical analysis software and obtains regression coefficient, examines diversiform-leaved poplar spring cankerworm
Occur begin see phase phase away from；
(4) phase based on time series models analysis is away from verification；
For probing into the total variation tendency of variable and rough amplitude of variation of each period, and the influence of decrease data error.It adopts
With the method for arithmetic average, the random fluctuation in time series is removed, ordered series of numbers is made to become smoother, can reflect that it is basic
Track, and predicted in conjunction with certain model；On the basis of a sliding average, then carry out second, third time or
Multi-level sliding average, expression formula are:
Wherein：XtRaw statistical data, N are data number.
9. the remote sensing prediction method of phase and occurrence quantity occur for diversiform-leaved poplar spring looper according to claim 5, it is characterised in that the
In four steps, the prediction result of each worm state is verified, is included the following steps：
(1) verification sample data is obtained, phase verification is gone through according to based on Linear Regression Model in One Unknown, then enters (2), according to
Based on the phase of multiple linear regression analysis away from verification, then enter (3), according to the phase analyzed based on time series models away from school
It tests, then enters (4)；
(2) phase verification is gone through based on Linear Regression Model in One Unknown；Respectively with diversiform-leaved poplar spring looper develop after emergence, breeding, hatching,
The average remote sensing temperature in 4 stages of larvae development builds one-variable linear regression as independent variable to go through issue according to as dependent variable
Analysis, mathematic(al) representation are：
Nn=a+bTn (12)
Wherein：NnRepresentative sprouts wings, breeding, hatches, larvae development each stage goes through issue evidence, TnIt is averaged remote sensing temperature for the stage, n
=1,2,3,4, wherein 1,2,3,4 respectively represents emergence, breeding, hatching, larvae development each stage；
(3) based on the phase of multiple linear regression analysis away from verification；
Multiple linear regression equations model refers to for disclosing the linear of linear relationship between a dependent variable and multiple independents variable
The empirical model of regression model, multiple linear regression equations is as follows：
Y=β0+β1X1+β2X2+···βnXn (13)
In above formula, it is assumed that multiple linear equation has n independent variable X1, Xn, β i are the partial regression systems of equation independent variable
Number；Occur to begin to see phase of phase away from inspection to diversiform-leaved poplar spring cankerworm, generation period of diversiform-leaved poplar spring cankerworm and emergence, adult,
Phase correlation is gone through in hatching, i.e., related to the worms state generation mean temperature in period such as looper emergences of diversiform-leaved poplar spring, adult, hatching, with diversiform-leaved poplar
It is that establish multiple linear regression equations as follows for independent variable that the mean temperature in period, which occurs, for spring looper emergence, adult, hatching worm state：
N=N1+N2+N3 (14)
I.e.：N=β0+β1T1+β2T2+β3T3 (15)
Multiple regression Linear correlative analysis is carried out using statistical analysis software and obtains regression coefficient, examines diversiform-leaved poplar spring cankerworm
Occur begin see phase phase away from；
(4) phase based on time series models analysis is away from verification；
For probing into the total variation tendency of variable and rough amplitude of variation of each period, and the influence of decrease data error.It adopts
With the method for arithmetic average, the random fluctuation in time series is removed, ordered series of numbers is made to become smoother, can reflect that it is basic
Track, and predicted in conjunction with certain model；On the basis of a sliding average, then carry out second, third time or
Multi-level sliding average, expression formula are:
Wherein：XtRaw statistical data, N are data number.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810469507.XA CN108764542A (en) | 2018-05-16 | 2018-05-16 | The remote sensing prediction method of phase and occurrence quantity occur for diversiform-leaved poplar spring looper |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810469507.XA CN108764542A (en) | 2018-05-16 | 2018-05-16 | The remote sensing prediction method of phase and occurrence quantity occur for diversiform-leaved poplar spring looper |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN108764542A true CN108764542A (en) | 2018-11-06 |
Family
ID=64008078
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810469507.XA Pending CN108764542A (en) | 2018-05-16 | 2018-05-16 | The remote sensing prediction method of phase and occurrence quantity occur for diversiform-leaved poplar spring looper |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108764542A (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109635490A (en) * | 2018-12-26 | 2019-04-16 | 贾翔 | The Dynamic Simulation Method of sprawling process occurs for the diversiform-leaved poplar spring looper based on CLUE-S model |
| CN113575520A (en) * | 2021-08-11 | 2021-11-02 | 浙江省农业科学院 | Fly pupa preservation method based on effective accumulated temperature accumulation value |
| CN113689034A (en) * | 2021-08-19 | 2021-11-23 | 云南省气候中心(云南省生态气象和卫星遥感中心) | Method for comprehensively predicting growth suitability of spodoptera frugiperda |
| CN114723118A (en) * | 2022-03-30 | 2022-07-08 | 北京云洋物联技术有限公司 | Insect pest early warning system based on Internet of things |
| JP7555167B2 (en) | 2022-10-20 | 2024-09-24 | 国立研究開発法人農業・食品産業技術総合研究機構 | Growth prediction program and growth prediction method |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN203274794U (en) * | 2013-04-22 | 2013-11-06 | 塔里木大学 | Euphrates poplar forest spring cankerworm pest emergence period prediction data acquisition apparatus |
| CN103616482A (en) * | 2013-12-04 | 2014-03-05 | 吉林省农业科学院 | Automatic injurious insect emergence period early-warning device |
| CN104915535A (en) * | 2015-02-04 | 2015-09-16 | 湖南农业大学 | Biomass population dynamics predictive parsing worldwide general key factor presupposing array platform |
| JP2016184232A (en) * | 2015-03-25 | 2016-10-20 | 株式会社富士通エフサス | Prediction apparatus and prediction method |
| CN106708782A (en) * | 2016-12-22 | 2017-05-24 | 贾翔 | Regional pest detection diagnosis judging method based on wavelet analysis |
| CN107392503A (en) * | 2017-08-18 | 2017-11-24 | 中国农业大学 | A kind of appraisal procedure of corn Climatic regionalization risk |
-
2018
- 2018-05-16 CN CN201810469507.XA patent/CN108764542A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN203274794U (en) * | 2013-04-22 | 2013-11-06 | 塔里木大学 | Euphrates poplar forest spring cankerworm pest emergence period prediction data acquisition apparatus |
| CN103616482A (en) * | 2013-12-04 | 2014-03-05 | 吉林省农业科学院 | Automatic injurious insect emergence period early-warning device |
| CN104915535A (en) * | 2015-02-04 | 2015-09-16 | 湖南农业大学 | Biomass population dynamics predictive parsing worldwide general key factor presupposing array platform |
| JP2016184232A (en) * | 2015-03-25 | 2016-10-20 | 株式会社富士通エフサス | Prediction apparatus and prediction method |
| CN106708782A (en) * | 2016-12-22 | 2017-05-24 | 贾翔 | Regional pest detection diagnosis judging method based on wavelet analysis |
| CN107392503A (en) * | 2017-08-18 | 2017-11-24 | 中国农业大学 | A kind of appraisal procedure of corn Climatic regionalization risk |
Non-Patent Citations (6)
| Title |
|---|
| M. GONZALEZ等: "Wireless image-sensor network application for population monitoring of lepidopterous insects pest (moths) in fruit crops", 《2014 IEEE INTERNATIONAL INSTRUMENTATION AND MEASUREMENT TECHNOLOGY CONFERENCE (I2MTC) PROCEEDINGS》 * |
| 唐翠翠: "基于多源遥感数据的小麦病虫害大尺度监测预测研究", 《中国优秀博硕士学位论文全文数据库(硕士)信息科技辑》 * |
| 张福丽: "气象因素对黑龙江省三种病虫害的影响及预测预报", 《中国优秀博硕士学位论文全文数据库(博士)农业科技辑》 * |
| 杨振德等: "八角尺蠖发育起点温度与有效积温的研究", 《中国植保导刊》 * |
| 石春华等: "《茶叶无公害生产技术》", 31 January 2003 * |
| 黄铁成: "新疆塔里木河流域吐加依林春尺蠖危害遥感监测研究", 《中国优秀博硕士学位论文全文数据库(硕士) 农业科技辑》 * |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109635490A (en) * | 2018-12-26 | 2019-04-16 | 贾翔 | The Dynamic Simulation Method of sprawling process occurs for the diversiform-leaved poplar spring looper based on CLUE-S model |
| CN109635490B (en) * | 2018-12-26 | 2022-06-07 | 贾翔 | CLUE-S model-based dynamic simulation method for occurrence and propagation processes of populus diversifolia spring inchworm |
| CN113575520A (en) * | 2021-08-11 | 2021-11-02 | 浙江省农业科学院 | Fly pupa preservation method based on effective accumulated temperature accumulation value |
| CN113689034A (en) * | 2021-08-19 | 2021-11-23 | 云南省气候中心(云南省生态气象和卫星遥感中心) | Method for comprehensively predicting growth suitability of spodoptera frugiperda |
| CN113689034B (en) * | 2021-08-19 | 2024-06-28 | 云南省气候中心(云南省生态气象和卫星遥感中心) | Comprehensive prediction method for growth suitability of spodoptera frugiperda |
| CN114723118A (en) * | 2022-03-30 | 2022-07-08 | 北京云洋物联技术有限公司 | Insect pest early warning system based on Internet of things |
| JP7555167B2 (en) | 2022-10-20 | 2024-09-24 | 国立研究開発法人農業・食品産業技術総合研究機構 | Growth prediction program and growth prediction method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108764542A (en) | The remote sensing prediction method of phase and occurrence quantity occur for diversiform-leaved poplar spring looper | |
| Pianka | Ecology and natural history of desert lizards: analyses of the ecological niche and community structure | |
| Arendt | Adaptive intrinsic growth rates: an integration across taxa | |
| Hixon et al. | Territory area, flower density, and time budgeting in hummingbirds: an experimental and theoretical analysis | |
| Wang et al. | A POPULATION MODEL FOR PLANT GROWTH AND DEVELOPMENT: COUPLING COTTON–HERBIVORE INTERACTION1 | |
| Shelford | An experimental investigation of the relations of the codling moth to weather and climate | |
| Seifert et al. | Predation on artificial caterpillars is higher in countryside than near-natural forest habitat in lowland south-western Costa Rica | |
| Martínez-García et al. | Optimizing Nesidiocoris tenuis (Hemiptera: Miridae) as a biological control agent: mathematical models for predicting its development as a function of temperature | |
| Fenoglio et al. | Influence of weather conditions and density of Doru luteipes (Dermaptera: Forficulidae) on Diatraea saccharalis (Lepidoptera: Crambidae) egg mortality | |
| Jorde | Winter and spring staging ecology of mallards in south central Nebraska | |
| Lu | Reproductive ecology of three Tibetan waterbird species, with special reference to life-history alterations along elevational gradients | |
| Andrews et al. | Long-term population fluctuations of a tropical lizard: a test of causality | |
| Atkinson | Preliminary analysis of a field population of citrus red scale, Aonidiella aurantii (Maskell), and the measurement and expression of stage duration and reproduction for life tables | |
| Petty | Productivity and density of tawny owls Strix aluco in relation to the structure of a spruce forest in Britain | |
| Tauber et al. | Soil moisture and postdormancy emergence of Colorado potato beetles (Coleoptera: Chrysomelidae): descriptive model and field emergence patterns | |
| Conway et al. | Intraspecific variation in reproductive traits of Burrowing Owls | |
| Keena et al. | The potential climatic range of spotted lanternfly may be broader than previously predicted | |
| Frolov et al. | Role of meteorological factor in long-term population dynamics of the European corn borer, Ostrinia nubilalis Hbn., in Krasnodar Area: the analysis of life tables | |
| Sukhodolskaya et al. | Sexual size dimorphism in ground beetles and its variation in altitude gradient | |
| Anttonen et al. | Predation pressure by arthropods, birds, and rodents is interactively shaped by tree species richness, vegetation structure, and season | |
| Sheehan | The western spruce budworm model: structure and content | |
| Ali et al. | Nest trees, habitat and breeding biology of the spotted owlet Athene brama brama (Temminck, 1821) in human habitation and agricultural landscape of India | |
| LI et al. | A review of impacts of climate change on birds: implications of long-term studies | |
| Doyle | Timing of reproduction by Red-tailed Hawks, Northern Goshawks and Great Horned Owls in the Kluane boreal forest of southwestern Yukon | |
| Khanday et al. | Life cycle and biology of Pityogenes scitus blandford, 1893 (Coleoptera: Curculionidae: Scolytinae), a pest of Pinus wallichiana in Kashmir, India. |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20181106 |