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Research ArticleThreshold Dynamics of a Huanglongbing Model withLogistic Growth in Periodic Environments
Jianping Wang Shujing Gao Yueli Luo and Dehui Xie
Key Laboratory of Jiangxi Province for Numerical Simulation and Emulation Techniques Gannan Normal UniversityGanzhou 341000 China
Correspondence should be addressed to Shujing Gao gaosjmathtomcom
Received 10 January 2014 Accepted 10 February 2014 Published 20 March 2014
Academic Editor Kaifa Wang
Copyright copy 2014 Jianping Wang et al This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited
We analyze the impact of seasonal activity of psyllid on the dynamics of Huanglongbing (HLB) infection A newmodel about HLBtransmissionwith Logistic growth in psyllid insect vectors and periodic coefficients has been investigated It is shown that the globaldynamics are determined by the basic reproduction number 119877
0which is defined through the spectral radius of a linear integral
operator If 1198770lt 1 then the disease-free periodic solution is globally asymptotically stable and if 119877
0gt 1 then the disease persists
Numerical values of parameters of the model are evaluated taken from the literatures Furthermore numerical simulations supportour analytical conclusions and the sensitive analysis on the basic reproduction number to the changes of average and amplitudevalues of the recruitment function of citrus are shown Finally some useful comments on controlling the transmission of HLB aregiven
1 Introduction
Plant disease is an important constraint to crop productionDue to plant diseases more than 10 of global food pro-duction is lost and 800 million people do not have adequatefood in the world [1ndash3] Plant pathologists cannot ignorethe juxtaposition of these figures for food shortage and thereduction of crops caused by plant disease
Nowadays Huanglongbing (HLB) which is a century olddisease caused by the bacteria Candidatus Liberibacter sppis one of the most serious problems of citrus worldwide[4] HLB has been responsible for the near destruction ofcitrus industries in Asia and Africa [4] The main symptomson HLB-infected citrus trees are yellow shoots leaves withblotchy mottle and small lopsided fruits [4 5] The HLB isa phloem-restricted noncultured Gram-negative bacteriumcausing crippling diseases denoting ldquogreeningrdquo in SouthAfrica ldquomottle leaf rdquo in the Philippines ldquodiebackrdquo in Indiaand ldquovein phloem degenerationrdquo in Indonesia The infectedcitrus orchards are usually destroyed or becomeunproductivein 5 to 8 years [4]
Most of the known plant viruses are transmitted byinsect vectors and entirely dependent on the behaviour and
dispersal capacity of their vectors to spread from plant toplant HLB a destructive disease of citrus can be transmittedby grafting from citrus to citrus and by dodder to periwinkleThe citrus psyllid (Diaphorina Citri Kuwayama) is naturaland mainly vector [4] In this paper we mainly consider thatHLB transmitted from tree to tree by Asian citrus psyllidinsect vectors
Mathematical models play an important role in under-standing the epidemiology of vector-transmitted plant dis-eases Since the introduction of HLB a lot of researcheshave been conducted on the epidemiology of the disease andon the vector but the result of these two lines of inquiryintegrated is very fewAnalyticalmodels have also beendevel-oped for the spread of citrus canker [6] butmodels for vector-transmitted bacterial pathogens are still preliminary [7] In[8] the authors proposed a deterministic compartmentalmathematic model to analyze HLB spread between citrusplants They assumed that all coefficients of the model areconstant (autonomous systems) However in the real worldactual data and evidence show that dynamics of diseasetransmission are not as simple as shown in the model In[9] Hall and Hentz have studied seasonal activity of psyllidinsect vectors which is correlated with humidity Seasonal
Hindawi Publishing CorporationAbstract and Applied AnalysisVolume 2014 Article ID 841367 10 pageshttpdxdoiorg1011552014841367
2 Abstract and Applied Analysis
fluctuations in the transmission of infectious diseases implythat the corresponding mathematical models may admitperiodic solutions It is interesting and important to studythe globally dynamics which are determined by thresholdparameter 119877
0in periodic epidemiological models
Based on above introduction we propose a model withperiodic transmission rates to investigate the seasonal HLBepidemics [10 11] In this model we consider Logistic growthterm for dynamics of susceptible psyllid vector Furthermorewe assumed that the infective citrus population is generatedthrough susceptible citrus which was bit by infective psyllidand the susceptible psyllid bit the infective citrus which willbecome infective psyllid Then the periodic system is asfollows
119889119878ℎ (119905)
119889119905= Λ (119905) minus 1205731 (119905) 119878ℎ (119905) 119868V (119905) minus 1205831 (119905) 119878ℎ (119905)
119889119868ℎ (119905)
119889119905= 1205731 (119905) 119878ℎ (119905) 119868V (119905) minus 1205831 (119905) 119868ℎ (119905) minus 119889 (119905) 119868ℎ (119905)
119889119878V (119905)
119889119905= 119887 (119905) (119878V (119905) + 119868V (119905)) [1 minus
119878V (119905) + 119868V (119905)
119898 (119878ℎ (119905) + 119868ℎ (119905))
]
minus 1205732(119905) 119878V (119905) 119868ℎ (119905)
1205832(119905) are continuous positive 120596-periodic functionsThe paper is organized as follows In the next section
we give the basic reproduction number of (1) In Sections 3and 4 the results show that the dynamical properties of themodel are completely determined by 119877
0 That is if 119877
0lt 1
the disease-free periodic solution is globally asymptoticallystable and if 119877
0gt 1 the model is permanence In Section 5
we present numerical simulations which demonstrate thetheoretical analysis and a brief discussion of ourmain results
2 Basic Reproduction Number
In the following we introduce some notations and lemmaswhich will be used for our further argument
Let (119877119896 119877119896+) be the standard ordered 119896-dimensional
Euclidean space with a norm sdot For 119906 V isin 119877119896 we denote
119906 ge V if 119906 minus V isin 119877119896+ 119906 gt V if 119906 minus V isin 119877119896
+ 0 and 119906 ≫ V if
119906 minus V isin Int(119877119896+) respectively
Define 119892119871 = max119905isin[0120596)
119892(119905) and 119892119872 = min119905isin[0120596)
119892(119905)where 119892(119905) is a continuous positive 120596-periodic function
Consider the following linear ordinary differential sys-tem
119889119909 (119905)
119889119905= 119860 (119905) 119909 (119905) (3)
where 119860(119905) is a continuous cooperative irreducible and120596-periodic 119896 times 119896 matrix function Denote Φ
119860(119905) be the
fundamental solution matrix of (3) and 119903(Φ119860(120596)) be the
spectral radius ofΦ119860(120596) By the Perron-Frobenius Theorem
we know that 119903(Φ119860(120596)) is the principle eigenvalue of Φ
119860(120596)
that is it is simple and admits an eigenvector Vlowast ≫ 0
Lemma 1 (see [12]) Let 119901 = (1120596) ln 119903(Φ119860(sdot)(120596)) Then there
exists a positive 120596-periodic function V(119905) such that exp(119901119905)V(119905)is a solution of (3)
Consider the following nonautonomous linear equation119889119878ℎ (119905)
119889119905= Λ (119905) minus 1205831 (119905) 119878ℎ (119905) (4)
whereΛ(119905) and 1205831(119905) are the same as in System (1) FromZhang
and Teng ([13 Lemma 21]) and simple calculation we have thefollowing lemma
Lemma 2 System (4) has a unique positive 120596-periodic solu-tion 119878lowast
ℎ(119905) which is globally asymptotically stable
Consider the following nonautonomous Logistic equation119889119878V (119905)
119889119905= 119887 (119905) 119878V (119905) (1 minus
119878V (119905)
119898119878ℎ(119905)) (5)
where 119887(119905) and119898 are the same as in system (1) From Teng andLi ([14 Lemma 2]) and simple calculation we can obtain thefollowing lemma
Lemma3 System (5) has a unique positive120596-periodic solution119878lowast
V (119905) which is globally asymptotically stable where 119878lowastV (119905) =
119898119878lowast
ℎ(119905)
According to Lemmas 2 and 3 it is easy to see that (1) hasa unique disease-free periodic solution (119878lowast
ℎ(119905) 0 119878
lowast
V (119905) 0)Now we use the generation operator approach (see [15])
to derive the basic reproduction number Applying the sym-bol of the theory in Wang and Zhao [15] for system (1) wehave
where 119909 = (119868ℎ(119905) 119868V(119905) 119878ℎ(119905) 119878V(119905))
119879 Then System (1) can bewritten as the following form
119889119909 (119905)
119889119905= F (119905 119909 (119905)) minusV (119905 119909 (119905)) (7)
whereV(119905 119909(119905)) =Vminus(119905 119909(119905)) minusV+(119905 119909(119905))It is easy to obtain that the conditions (A1)ndash(A5) in [15]
hold In the following we will check the conditions (A6) and(A7) in [15]
We know that 119909lowast(119905) = (0 0 119878lowast
ℎ(119905) 119878lowast
V (119905)) is the disease-free periodic solution of system (7) Denote
Let 119882(119905 119904 120582) 119905 ⩾ 119904 119904 isin 119877 be the evolution operator ofthe System (15) on 1198772 Since 119865(119905) is nonnegative and minus119881(119905)is cooperative then 119903(119882(120596 0 120582)) is continuous and nonin-creasing for 120582 isin (0infin) and lim
V )) minus 119906 (1199051 1198750)10038171003817100381710038171003817le 120578
(36)
for all 119905 ge 0 which implies that 119878lowastℎ(119905) minus 120578 le 119878
ℎ(119905) le 119878
lowast
ℎ(119905) + 120578
119878lowast
V (119905) minus 120578 le 119878V(119905) le 119878lowast
V (119905) + 120578 Then from (1) we have
119889119868ℎ(119905)
119889119905ge 1205731(119905) (119878lowast
ℎ(119905) minus 120578) 119868V (119905) minus (1205831 (119905) + 119889 (119905)) 119868ℎ (119905)
119889119868V (119905)
119889119905ge 1205732(119905) (119878lowast
V (119905) minus 120578) 119868ℎ (119905) minus 1205832 (119905) 119868V (119905)
(37)
6 Abstract and Applied Analysis
Table 1 Parameter definitions and values used for numerical simulations of the Huanglongbing model
Parameter Definition Average value Unit ReferenceΛ The recruitment rate of citrus mdash monthminus1 Estimate1205731
Infected rate of citrus mdash monthminus1 Estimate1205831
Nature death rate of citrus 000275ndash0004167 monthminus1 [20]119889 Disease induced death rate of citrus 0016667ndash0027775 monthminus1 [21]119863 Birth rate of psyllid 378327ndash33526137 monthminus1 [20 22]1205732
Infected rate of psyllid mdash monthminus1 Estimate1205832
Nature death rate of psyllid 01169825ndash095052 monthminus1 [23]119898 Max abundance of psyllid per citrus 120ndash1000 mdash [24]
Table 2 Parameter functions for model (1) according to the values of Table 1
Parameter functions Value Reference
1205731(119905) 00042925 + 0003543 cos (212058711990512) Estimate
1205831(119905) 00034585 + 00007085 cos (212058711990512) [20]
119889 (119905) 0022221 + 0005554 cos (212058711990512) [21]
119863 (119905) 186547035 + 148714335 cos (212058711990512) [20 22]
1205732(119905) 0008779171 + 0004838437 cos (212058711990512) Estimate
1205832(119905) 053375125 + 041676875 cos (212058711990512) [23]
119887 (119905) = 119863 (119905) minus 1205832(119905) 18120952 + 1445466475 cos (212058711990512) [20 22 23]
119898 560 [24]
Consider the linear system
119889119868ℎ (119905)
119889119905= 1205731 (119905) (119878
lowast
ℎ(119905) minus 120578) 119868V (119905) minus (1205831 (119905) + 119889 (119905)) 119868ℎ (119905)
119889119868V (119905)
119889119905= 1205732 (119905) (119878
lowast
V (119905) minus 120578) 119868ℎ (119905) minus 1205832 (119905) 119868V (119905)
(38)
By Lemma 1 and the standard comparison principle we havethat there exists a positive120596-periodic function V
2(119905) such that
119869(119905) = exp(1199012119905)V2(119905) is a solution of System (38) where 119869(119905) =
(119868ℎ(119905) 119868V(119905))
119879 and
1199012=1
120596ln 119903 (Φ
119865minus119881minus119872120578
(120596)) (39)
It follows from 119903(Φ119865minus119881minus119872
120578
(120596)) gt 1 that 1199012gt 0 and 119869(119905) rarr
+infin as 119905 rarr +infin Applying the comparison principle [18] weknow that 119868
ℎ(119905) rarr +infin and 119868V(119905) rarr +infin as 119905 rarr +infin This
is a contradictionThus we have proved that (32) holds and119875is weakly uniformly persistent with respect to (119883
0 1205971198830)
According to the results of Lemma 7 we can easily obtainthat119875 has a global attractor119875
0 It is easy to obtain that119875
0is an
isolated invariant set in119883 and119882119904(1198750)cap1198830= 0We know that
1198750is acyclic in119872
120597and every solution in119872
120597converges to 119875
0
According to Zhao [19] we have that119875 is uniformly persistentwith respect to (119883
0 1205971198830) This implies that the solution of
(1) is uniformly persistent with respect to (1198830 1205971198830) Thus we
have that there exists a 120598 gt 0 such that lim inf119905rarr+infin
119868ℎ(119905) ge 120598
lim inf119905rarr+infin
119868V(119905) ge 120598
5 Numerical Simulationsand Sensitivity Analysis
In this section we will make numerical simulations bymeansof Matlab 71 to support our theoretical results to predictthe trend of the disease and to explore some control andprevention measures Numerical values of parameters ofsystem (1) are given in Table 1 (most of the data are taken fromthe literatures ([20ndash24]))
According to the periodicity of System (1) and Table 1 weset 1205831(119905) = 120572
0
1+ 1205720
2cos(212058711990512) where 1205720
2= (0004167 minus
000275)2 = 00007085 and 12057201= 000275 + 120572
0
2= 00034585
By the similar method we can obtain the other parameterfunctions of model (1) (see Table 2) For the simulations thatfollows we apply the parameters in Table 2 unless otherwisestated
ChooseΛ(119905) = 000265+000235 cos(212058711990512)Then fromLemma 5 we can compute 119877
0= 09844 lt 1 by means of
Matlab 71 FromTheorem 8 we obtain that the infected citruspopulation 119868
ℎ(119905) and the infected psyllid population 119868V(119905) of
system (1) are extinct (see Figures 1 and 2)Choose Λ(119905) = 0005 + 00035 cos(212058711990512) Then from
Lemma 5 we obtain that 1198770= 18342 gt 1 From Theorem 9
we have that the infected citrus population 119868ℎ(119905) and the
infected psyllid population 119868V(119905) of System (1) are permanence(see Figures 3 and 4)
From the formulae for 1198770 we can predict the general
tendency of the epidemic in a long term according to thecurrent situation which is presented in Figures 1 2 3 and 4From the first two figures we know that the epidemic of
Abstract and Applied Analysis 7
002
004
006
008
01
012
0 500 1000 1500 2000 25000
t (month)
R0 = 09844
Ih(t)
(a)
0 100 200 300 400 5000
002
004
006
008
01
012
t (month)
R0 = 09844
Ih(t)
(b)
Figure 1 Graphs of numerical simulations of (1) showings the tendency of the infected citrus population (a) 119905 isin [0 2500] (b) 119905 isin [0 500]
R0 = 09844
0
02
04
06
08
1
12
14
Iv(t)
0 500 1000 1500 2000 25000
t (month)
(a)
02
04
06
08
1
12
14
R0 = 09844
Iv(t)
0 100 200 300 400 5000
t (month)
(b)
Figure 2 It is similar to Figure 1
Huanglongbing can be rising in a short time but cannot beoutbreak with the current prevention and control measuresFrom Figures 3 and 4 we can see that the epidemic ofHuanglongbing dropped heavily after 100 months whilethere is still tendency to a stable periodic solution in a longtime
Next we perform some sensitivity analysis to determinethe influence 119877
0on the parameters Λ(119905) 120573
1(119905) and 120573
2(119905)
We choose function Λ(119905) = Λ01+ Λ0
2cos(212058711990512) where
Λ0
1 Λ02denote the average and amplitude values of Λ(119905)
respectively and Λ0
1= (112) int
12
0Λ(119905)119889119905 From Figure 5
we can observe that the blue line is linear relation between1198770and Λ
0
2 and 119877
0increases as Λ0
2increases The red
curve reflects the influence of the average value of Λ(119905) on1198770 Figure 5 shows that Λ0
1is more sensitive than Λ
0
2on
the basic reproduction number 1198770 Therefore in the real
world decreasing the average recruitment rate of citrus is thevaluable way to control Huanglongbing
Now we consider the combined influence of 1205731(119905) and
1205732(119905) on 119877
0 Set Λ(119905) = 00027 + 000235 cos(212058711990512)
1205731(119905) = 119886
1+ 1198871cos(212058711990512) and 120573
2(119905) = 119886
2+ 1198872cos(212058711990512)
Moreover we know that 1198861
= (112) int12
01205731(119905)119889119905 and
1198862= (112) int
12
01205732(119905)119889119905 Other parameters can be seen in
Table 2
Case (I) We fix 1198871= 0003543 and 119887
2= 0004838437
and let 1198861vary from 000001 to 0015 and 119886
2from 000001
to 002 For this case it is interesting to examine how theaverage values of adequate contact rate 120573
1(119905) and 120573
2(119905) affect
the basic reproduction number 1198770 Numerical results shown
8 Abstract and Applied Analysis
R0 = 18342
006
008
01
012
014
016
018
02Ih(t)
0 500 1000 1500 2000 2500t (month)
(a)
006
008
01
012
014
016
018
02
R0 = 18342
Ih(t)
0 100 200 300 400 500t (month)
(b)
Figure 3 The figures show that the infected citrus population is permanence (a) 119905 isin [0 2500] (b) 119905 isin [0 500]
02
04
06
08
1
12
14
16
18
2
R0 = 18342
0 500 1000 1500 2000 25000
t (month)
Iv(t)
(a)
R0 = 18342
02
04
06
08
1
12
14
16
18
2Iv(t)
0 100 200 300 400 5000
t (month)
(b)
Figure 4 It is similar to Figure 3
in Figure 6 imply that the basic reproduction number1198770may
be less than 1 when 1198861or 1198862is small enough And the results
also imply that 1198770increases as 119886
1and 1198862increase Further we
can observe that from Figure 6(i)the smaller the values of 1198861
or 1198862are the more sensitive 119877
0is (ii) increasing 119886
2may be
more sensitive for 1198770when 119886
1is fixed (iii) increasing 119886
1may
be more sensitive for 1198770when 119886
2is fixed
Case (II) We fix 1198861= 00042925 and 119886
2= 000877917 and
let 1198871vary from 0000001 to 0005 and 119887
2from 0000002 to
0006Then we obtain the result of numerical simulation andit is shown in Figure 7 Obviously Figure 7 shows that 119877
0is
linearly related to both 1198871and 119887
2with the pattern that 119877
0
decreases to a relatively small value (less than 1) only when1198871and 1198872are very small
By the above graphs of the basic reproduction number1198770on the average values of recruitment rate of citrus Λ(119905)
and adequate contact rate 1205731(119905) 1205732(119905) we know that the basic
reproduction number 1198770is a monotonic increasing function
by the average values From the sensitivity analysis diagramswe observe that 119877
0falls to less than 1 by decreasing the values
of those parameters
6 Conclusion
In this paper we have analyzed a HLB transmission modelwith Logistic growth in periodic environments It is provedthat 119877
0is the threshold for distinguishing the disease extinc-
tion or permanence The disease-free periodic solution is
Abstract and Applied Analysis 9
0 1 2 3 4 502
04
06
08
1
12
14
16
18
2
R0
times10minus3
Λ0
1= 00027
Λ0
2= [0000001 0005]
Λ0
1= [0000001 0005]Λ0
2= 000235
Λ0
1or Λ0
2
Figure 5 The graph shows the sensitivity of the basic reproductionnumber 119877
0to the changes of Λ(119905)
00005
0010015
000050010015
0020
05
1
15
2
25
3
R0
a1a2
Figure 6 The graph of 1198770in terms of 119886
1and 119886
2
globally asymptotically stable and the disease dies out when1198770lt 1 When 119877
0gt 1 the disease persists
The numerical simulations shown in Figure 5 show thatthere are some parameter ranges of Λ
1and Λ
2such that the
threshold parameter 1198770is smaller than 1 It indicates a useful
way to eradicate Huanglongbing by limiting the recruitmentof citrus including the average value and amplitude ofrecruitment function
The results shown in Figure 6 (Figure 7) show that if theamplitudes of infected functions 119887
1 1198872(the average infected
rate 1198861 1198862) are fixed we can control the infection of citrus
and psyllid by limiting the average infected rates 1198861 1198862(the
amplitudes of infected functions 1198871 1198872)
According to the above theoretical analysis andnumericalsimulations we can conclude that the recruitment of citrusand the infection of citrus and psyllid have significanteffects on Huanglongbing transmission In order to preventthe epidemic disease from generating endemic making anappropriate reduction of the recruitment rate of citrus and
01
23
45
02
46
09
1
11
12
13
b1b2
R0
times10minus3
times10minus3
Figure 7 The graph of 1198770in terms of 119887
1and 1198872
decreasing the contact rate between psyllid and the citrus areeffective measures to control Huanglongbing
Disclosure
The paper is approved by all authors for publication Theauthors would like to declare that the work described wasoriginal research that has not been published previously andnot under consideration for publication elsewhere
Conflict of Interests
No conflict of interests exists in the submission of this paper
Acknowledgments
The research has been supported by the Natural ScienceFoundation of China (11261004) the Natural Science Foun-dation of Jiangxi Province (20122BAB211010) the Scienceand Technology Plan Projects of Jiangxi Provincial EducationDepartment (GJJ13646) and the Postgraduate InnovationFund of Jiangxi Province (YC2012-S121)
References
[1] P Christou and R M Twyman ldquoThe potential of geneticallyenhanced plants to address food insecurityrdquo Nutrition ResearchReviews vol 17 no 1 pp 23ndash42 2004
[2] FAO The State of Food Insecurity in the World (SOFI) FAORome Italy 2000 httpwwwfaoorgFOCUSESOFI00sofi001-ehtm
[3] C James ldquoGlobal food securityrdquo in International Congress ofPlant Pathology Pittsburgh Pa USA August 1998
[4] J M Bove ldquoHuanglongbing a destructive newly-emergingcentury-old disease of citrusrdquo Journal of Plant Pathology vol88 no 1 pp 7ndash37 2006
[5] S E Halbert and K L Manjunath ldquoAsian citrus psyllids (Stern-orrhyncha Psyllidae) and greening disease of citrus a literaturereview and assessment of risk in Floridardquo Florida Entomologistvol 87 no 3 pp 330ndash353 2004
10 Abstract and Applied Analysis
[6] S Parnell T R Gottwald C A Gilligan N J Cunniffe and FVan Den Bosch ldquoThe effect of landscape pattern on the optimaleradication zone of an invading epidemicrdquo Phytopathology vol100 no 7 pp 638ndash644 2010
[7] R FMizell III C Tipping P C Andersen B V BrodbeckW BHunter and T Northfield ldquoBehavioral model for Homalodiscavitripennis (Hemiptera Cicadellidae) optimization of hostplant utilization andmanagement implicationsrdquo EnvironmentalEntomology vol 37 no 5 pp 1049ndash1062 2008
[8] G A Braga S Ternes et al ldquoModelagem Matematica daDinamica TemporaldoHLB emCitrosrdquo in Proceedings of the 8thCongresso Brasileiro de Agroinformatica Bento Goncalves 2011
[9] DGHall andMGHentz ldquoSeasonal flight activity by theAsiancitrus psyllid in east central Floridardquo Entomologia et Applicatavol 139 no 1 pp 75ndash85 2011
[10] X Song and A U Neumann ldquoGlobal stability and periodicsolution of the viral dynamicsrdquo Journal ofMathematical Analysisand Applications vol 329 no 1 pp 281ndash297 2007
[11] K Wang Z Teng and H Jiang ldquoOn the permanence forn-species non-autonomous Lotka-Volterra competitive systemwith infinite delays and feedback controlsrdquo International Journalof Biomathematics vol 1 no 1 pp 29ndash43 2008
[12] F Zhang and X-Q Zhao ldquoA periodic epidemic model in apatchy environmentrdquo Journal of Mathematical Analysis andApplications vol 325 no 1 pp 496ndash516 2007
[13] T Zhang and Z Teng ldquoOn a nonautonomous SEIRS model inepidemiologyrdquo Bulletin of Mathematical Biology vol 69 no 8pp 2537ndash2559 2007
[14] Z Teng and Z Li ldquoPermanence and asymptotic behavior of thetv-species nonautonomous lotka-volterra competitive systemsrdquoComputers and Mathematics with Applications vol 39 no 7-8pp 107ndash116 2000
[15] W Wang and X-Q Zhao ldquoThreshold dynamics for compart-mental epidemic models in periodic environmentsrdquo Journal ofDynamics and Differential Equations vol 20 no 3 pp 699ndash7172008
[16] Y Nakata and T Kuniya ldquoGlobal dynamics of a class ofSEIRS epidemic models in a periodic environmentrdquo Journal ofMathematical Analysis and Applications vol 363 no 1 pp 230ndash237 2010
[17] Y Nakata Permanence and Global Asymptotic Stability ForPopulation Models in Mathematical Biology Waseda UniversityTokyo Japan 2010
[18] H Smith and P Waltman The Theory of the Chemostat Cam-bridge University Press Cambridge Mass USA 1995
[19] X ZhaoDynamical Systems in Population Biology Spring NewYork NY USA 2003
[20] X M Deng ldquoFormming process and basis and technologicalpoints of the theory emphasis on control citrus psylla for inte-grated control Huanglongbingrdquo Chinese Agricultural ScienceBulletin vol 25 no 23 pp 358ndash363 2009 (Chinese)
[21] T Li C Z Cheng et al ldquoDetection of the bearing rate ofliberobacter asiaticum in citrus psylla and its host plantrdquo ActaAgriculturae Universitatis Jiangxiensis vol 29 no 5 pp 743ndash745 2007 (Chinese)
[22] G F Chen and X M Deng ldquoDynamic observation adult citruspsyllid quantity live through the winter in spring and winterrdquoSouth China Fruits vol 39 no 4 pp 36ndash38 2010 (Chinese)
[23] XMDeng G F Chen et al ldquoThe newly process of Huanglong-bing in citrusrdquo Guangxi Horticulture vol 17 no 3 pp 49ndash512006
[24] R G drsquoA Vilamiu S Ternes B A Guilherme et al ldquoA modelfor Huanglongbing spread between citrus plants includingdelay times and human interventionrdquo in Proceedings of theInternational Conference of Numerical Analysis and AppliedMathematics (ICNAAM rsquo12) vol 1479 pp 2315ndash2319 2012
fluctuations in the transmission of infectious diseases implythat the corresponding mathematical models may admitperiodic solutions It is interesting and important to studythe globally dynamics which are determined by thresholdparameter 119877
0in periodic epidemiological models
Based on above introduction we propose a model withperiodic transmission rates to investigate the seasonal HLBepidemics [10 11] In this model we consider Logistic growthterm for dynamics of susceptible psyllid vector Furthermorewe assumed that the infective citrus population is generatedthrough susceptible citrus which was bit by infective psyllidand the susceptible psyllid bit the infective citrus which willbecome infective psyllid Then the periodic system is asfollows
119889119878ℎ (119905)
119889119905= Λ (119905) minus 1205731 (119905) 119878ℎ (119905) 119868V (119905) minus 1205831 (119905) 119878ℎ (119905)
119889119868ℎ (119905)
119889119905= 1205731 (119905) 119878ℎ (119905) 119868V (119905) minus 1205831 (119905) 119868ℎ (119905) minus 119889 (119905) 119868ℎ (119905)
119889119878V (119905)
119889119905= 119887 (119905) (119878V (119905) + 119868V (119905)) [1 minus
119878V (119905) + 119868V (119905)
119898 (119878ℎ (119905) + 119868ℎ (119905))
]
minus 1205732(119905) 119878V (119905) 119868ℎ (119905)
1205832(119905) are continuous positive 120596-periodic functionsThe paper is organized as follows In the next section
we give the basic reproduction number of (1) In Sections 3and 4 the results show that the dynamical properties of themodel are completely determined by 119877
0 That is if 119877
0lt 1
the disease-free periodic solution is globally asymptoticallystable and if 119877
0gt 1 the model is permanence In Section 5
we present numerical simulations which demonstrate thetheoretical analysis and a brief discussion of ourmain results
2 Basic Reproduction Number
In the following we introduce some notations and lemmaswhich will be used for our further argument
Let (119877119896 119877119896+) be the standard ordered 119896-dimensional
Euclidean space with a norm sdot For 119906 V isin 119877119896 we denote
119906 ge V if 119906 minus V isin 119877119896+ 119906 gt V if 119906 minus V isin 119877119896
+ 0 and 119906 ≫ V if
119906 minus V isin Int(119877119896+) respectively
Define 119892119871 = max119905isin[0120596)
119892(119905) and 119892119872 = min119905isin[0120596)
119892(119905)where 119892(119905) is a continuous positive 120596-periodic function
Consider the following linear ordinary differential sys-tem
119889119909 (119905)
119889119905= 119860 (119905) 119909 (119905) (3)
where 119860(119905) is a continuous cooperative irreducible and120596-periodic 119896 times 119896 matrix function Denote Φ
119860(119905) be the
fundamental solution matrix of (3) and 119903(Φ119860(120596)) be the
spectral radius ofΦ119860(120596) By the Perron-Frobenius Theorem
we know that 119903(Φ119860(120596)) is the principle eigenvalue of Φ
119860(120596)
that is it is simple and admits an eigenvector Vlowast ≫ 0
Lemma 1 (see [12]) Let 119901 = (1120596) ln 119903(Φ119860(sdot)(120596)) Then there
exists a positive 120596-periodic function V(119905) such that exp(119901119905)V(119905)is a solution of (3)
Consider the following nonautonomous linear equation119889119878ℎ (119905)
119889119905= Λ (119905) minus 1205831 (119905) 119878ℎ (119905) (4)
whereΛ(119905) and 1205831(119905) are the same as in System (1) FromZhang
and Teng ([13 Lemma 21]) and simple calculation we have thefollowing lemma
Lemma 2 System (4) has a unique positive 120596-periodic solu-tion 119878lowast
ℎ(119905) which is globally asymptotically stable
Consider the following nonautonomous Logistic equation119889119878V (119905)
119889119905= 119887 (119905) 119878V (119905) (1 minus
119878V (119905)
119898119878ℎ(119905)) (5)
where 119887(119905) and119898 are the same as in system (1) From Teng andLi ([14 Lemma 2]) and simple calculation we can obtain thefollowing lemma
Lemma3 System (5) has a unique positive120596-periodic solution119878lowast
V (119905) which is globally asymptotically stable where 119878lowastV (119905) =
119898119878lowast
ℎ(119905)
According to Lemmas 2 and 3 it is easy to see that (1) hasa unique disease-free periodic solution (119878lowast
ℎ(119905) 0 119878
lowast
V (119905) 0)Now we use the generation operator approach (see [15])
to derive the basic reproduction number Applying the sym-bol of the theory in Wang and Zhao [15] for system (1) wehave
where 119909 = (119868ℎ(119905) 119868V(119905) 119878ℎ(119905) 119878V(119905))
119879 Then System (1) can bewritten as the following form
119889119909 (119905)
119889119905= F (119905 119909 (119905)) minusV (119905 119909 (119905)) (7)
whereV(119905 119909(119905)) =Vminus(119905 119909(119905)) minusV+(119905 119909(119905))It is easy to obtain that the conditions (A1)ndash(A5) in [15]
hold In the following we will check the conditions (A6) and(A7) in [15]
We know that 119909lowast(119905) = (0 0 119878lowast
ℎ(119905) 119878lowast
V (119905)) is the disease-free periodic solution of system (7) Denote
Let 119882(119905 119904 120582) 119905 ⩾ 119904 119904 isin 119877 be the evolution operator ofthe System (15) on 1198772 Since 119865(119905) is nonnegative and minus119881(119905)is cooperative then 119903(119882(120596 0 120582)) is continuous and nonin-creasing for 120582 isin (0infin) and lim
V )) minus 119906 (1199051 1198750)10038171003817100381710038171003817le 120578
(36)
for all 119905 ge 0 which implies that 119878lowastℎ(119905) minus 120578 le 119878
ℎ(119905) le 119878
lowast
ℎ(119905) + 120578
119878lowast
V (119905) minus 120578 le 119878V(119905) le 119878lowast
V (119905) + 120578 Then from (1) we have
119889119868ℎ(119905)
119889119905ge 1205731(119905) (119878lowast
ℎ(119905) minus 120578) 119868V (119905) minus (1205831 (119905) + 119889 (119905)) 119868ℎ (119905)
119889119868V (119905)
119889119905ge 1205732(119905) (119878lowast
V (119905) minus 120578) 119868ℎ (119905) minus 1205832 (119905) 119868V (119905)
(37)
6 Abstract and Applied Analysis
Table 1 Parameter definitions and values used for numerical simulations of the Huanglongbing model
Parameter Definition Average value Unit ReferenceΛ The recruitment rate of citrus mdash monthminus1 Estimate1205731
Infected rate of citrus mdash monthminus1 Estimate1205831
Nature death rate of citrus 000275ndash0004167 monthminus1 [20]119889 Disease induced death rate of citrus 0016667ndash0027775 monthminus1 [21]119863 Birth rate of psyllid 378327ndash33526137 monthminus1 [20 22]1205732
Infected rate of psyllid mdash monthminus1 Estimate1205832
Nature death rate of psyllid 01169825ndash095052 monthminus1 [23]119898 Max abundance of psyllid per citrus 120ndash1000 mdash [24]
Table 2 Parameter functions for model (1) according to the values of Table 1
Parameter functions Value Reference
1205731(119905) 00042925 + 0003543 cos (212058711990512) Estimate
1205831(119905) 00034585 + 00007085 cos (212058711990512) [20]
119889 (119905) 0022221 + 0005554 cos (212058711990512) [21]
119863 (119905) 186547035 + 148714335 cos (212058711990512) [20 22]
1205732(119905) 0008779171 + 0004838437 cos (212058711990512) Estimate
1205832(119905) 053375125 + 041676875 cos (212058711990512) [23]
119887 (119905) = 119863 (119905) minus 1205832(119905) 18120952 + 1445466475 cos (212058711990512) [20 22 23]
119898 560 [24]
Consider the linear system
119889119868ℎ (119905)
119889119905= 1205731 (119905) (119878
lowast
ℎ(119905) minus 120578) 119868V (119905) minus (1205831 (119905) + 119889 (119905)) 119868ℎ (119905)
119889119868V (119905)
119889119905= 1205732 (119905) (119878
lowast
V (119905) minus 120578) 119868ℎ (119905) minus 1205832 (119905) 119868V (119905)
(38)
By Lemma 1 and the standard comparison principle we havethat there exists a positive120596-periodic function V
2(119905) such that
119869(119905) = exp(1199012119905)V2(119905) is a solution of System (38) where 119869(119905) =
(119868ℎ(119905) 119868V(119905))
119879 and
1199012=1
120596ln 119903 (Φ
119865minus119881minus119872120578
(120596)) (39)
It follows from 119903(Φ119865minus119881minus119872
120578
(120596)) gt 1 that 1199012gt 0 and 119869(119905) rarr
+infin as 119905 rarr +infin Applying the comparison principle [18] weknow that 119868
ℎ(119905) rarr +infin and 119868V(119905) rarr +infin as 119905 rarr +infin This
is a contradictionThus we have proved that (32) holds and119875is weakly uniformly persistent with respect to (119883
0 1205971198830)
According to the results of Lemma 7 we can easily obtainthat119875 has a global attractor119875
0 It is easy to obtain that119875
0is an
isolated invariant set in119883 and119882119904(1198750)cap1198830= 0We know that
1198750is acyclic in119872
120597and every solution in119872
120597converges to 119875
0
According to Zhao [19] we have that119875 is uniformly persistentwith respect to (119883
0 1205971198830) This implies that the solution of
(1) is uniformly persistent with respect to (1198830 1205971198830) Thus we
have that there exists a 120598 gt 0 such that lim inf119905rarr+infin
119868ℎ(119905) ge 120598
lim inf119905rarr+infin
119868V(119905) ge 120598
5 Numerical Simulationsand Sensitivity Analysis
In this section we will make numerical simulations bymeansof Matlab 71 to support our theoretical results to predictthe trend of the disease and to explore some control andprevention measures Numerical values of parameters ofsystem (1) are given in Table 1 (most of the data are taken fromthe literatures ([20ndash24]))
According to the periodicity of System (1) and Table 1 weset 1205831(119905) = 120572
0
1+ 1205720
2cos(212058711990512) where 1205720
2= (0004167 minus
000275)2 = 00007085 and 12057201= 000275 + 120572
0
2= 00034585
By the similar method we can obtain the other parameterfunctions of model (1) (see Table 2) For the simulations thatfollows we apply the parameters in Table 2 unless otherwisestated
ChooseΛ(119905) = 000265+000235 cos(212058711990512)Then fromLemma 5 we can compute 119877
0= 09844 lt 1 by means of
Matlab 71 FromTheorem 8 we obtain that the infected citruspopulation 119868
ℎ(119905) and the infected psyllid population 119868V(119905) of
system (1) are extinct (see Figures 1 and 2)Choose Λ(119905) = 0005 + 00035 cos(212058711990512) Then from
Lemma 5 we obtain that 1198770= 18342 gt 1 From Theorem 9
we have that the infected citrus population 119868ℎ(119905) and the
infected psyllid population 119868V(119905) of System (1) are permanence(see Figures 3 and 4)
From the formulae for 1198770 we can predict the general
tendency of the epidemic in a long term according to thecurrent situation which is presented in Figures 1 2 3 and 4From the first two figures we know that the epidemic of
Abstract and Applied Analysis 7
002
004
006
008
01
012
0 500 1000 1500 2000 25000
t (month)
R0 = 09844
Ih(t)
(a)
0 100 200 300 400 5000
002
004
006
008
01
012
t (month)
R0 = 09844
Ih(t)
(b)
Figure 1 Graphs of numerical simulations of (1) showings the tendency of the infected citrus population (a) 119905 isin [0 2500] (b) 119905 isin [0 500]
R0 = 09844
0
02
04
06
08
1
12
14
Iv(t)
0 500 1000 1500 2000 25000
t (month)
(a)
02
04
06
08
1
12
14
R0 = 09844
Iv(t)
0 100 200 300 400 5000
t (month)
(b)
Figure 2 It is similar to Figure 1
Huanglongbing can be rising in a short time but cannot beoutbreak with the current prevention and control measuresFrom Figures 3 and 4 we can see that the epidemic ofHuanglongbing dropped heavily after 100 months whilethere is still tendency to a stable periodic solution in a longtime
Next we perform some sensitivity analysis to determinethe influence 119877
0on the parameters Λ(119905) 120573
1(119905) and 120573
2(119905)
We choose function Λ(119905) = Λ01+ Λ0
2cos(212058711990512) where
Λ0
1 Λ02denote the average and amplitude values of Λ(119905)
respectively and Λ0
1= (112) int
12
0Λ(119905)119889119905 From Figure 5
we can observe that the blue line is linear relation between1198770and Λ
0
2 and 119877
0increases as Λ0
2increases The red
curve reflects the influence of the average value of Λ(119905) on1198770 Figure 5 shows that Λ0
1is more sensitive than Λ
0
2on
the basic reproduction number 1198770 Therefore in the real
world decreasing the average recruitment rate of citrus is thevaluable way to control Huanglongbing
Now we consider the combined influence of 1205731(119905) and
1205732(119905) on 119877
0 Set Λ(119905) = 00027 + 000235 cos(212058711990512)
1205731(119905) = 119886
1+ 1198871cos(212058711990512) and 120573
2(119905) = 119886
2+ 1198872cos(212058711990512)
Moreover we know that 1198861
= (112) int12
01205731(119905)119889119905 and
1198862= (112) int
12
01205732(119905)119889119905 Other parameters can be seen in
Table 2
Case (I) We fix 1198871= 0003543 and 119887
2= 0004838437
and let 1198861vary from 000001 to 0015 and 119886
2from 000001
to 002 For this case it is interesting to examine how theaverage values of adequate contact rate 120573
1(119905) and 120573
2(119905) affect
the basic reproduction number 1198770 Numerical results shown
8 Abstract and Applied Analysis
R0 = 18342
006
008
01
012
014
016
018
02Ih(t)
0 500 1000 1500 2000 2500t (month)
(a)
006
008
01
012
014
016
018
02
R0 = 18342
Ih(t)
0 100 200 300 400 500t (month)
(b)
Figure 3 The figures show that the infected citrus population is permanence (a) 119905 isin [0 2500] (b) 119905 isin [0 500]
02
04
06
08
1
12
14
16
18
2
R0 = 18342
0 500 1000 1500 2000 25000
t (month)
Iv(t)
(a)
R0 = 18342
02
04
06
08
1
12
14
16
18
2Iv(t)
0 100 200 300 400 5000
t (month)
(b)
Figure 4 It is similar to Figure 3
in Figure 6 imply that the basic reproduction number1198770may
be less than 1 when 1198861or 1198862is small enough And the results
also imply that 1198770increases as 119886
1and 1198862increase Further we
can observe that from Figure 6(i)the smaller the values of 1198861
or 1198862are the more sensitive 119877
0is (ii) increasing 119886
2may be
more sensitive for 1198770when 119886
1is fixed (iii) increasing 119886
1may
be more sensitive for 1198770when 119886
2is fixed
Case (II) We fix 1198861= 00042925 and 119886
2= 000877917 and
let 1198871vary from 0000001 to 0005 and 119887
2from 0000002 to
0006Then we obtain the result of numerical simulation andit is shown in Figure 7 Obviously Figure 7 shows that 119877
0is
linearly related to both 1198871and 119887
2with the pattern that 119877
0
decreases to a relatively small value (less than 1) only when1198871and 1198872are very small
By the above graphs of the basic reproduction number1198770on the average values of recruitment rate of citrus Λ(119905)
and adequate contact rate 1205731(119905) 1205732(119905) we know that the basic
reproduction number 1198770is a monotonic increasing function
by the average values From the sensitivity analysis diagramswe observe that 119877
0falls to less than 1 by decreasing the values
of those parameters
6 Conclusion
In this paper we have analyzed a HLB transmission modelwith Logistic growth in periodic environments It is provedthat 119877
0is the threshold for distinguishing the disease extinc-
tion or permanence The disease-free periodic solution is
Abstract and Applied Analysis 9
0 1 2 3 4 502
04
06
08
1
12
14
16
18
2
R0
times10minus3
Λ0
1= 00027
Λ0
2= [0000001 0005]
Λ0
1= [0000001 0005]Λ0
2= 000235
Λ0
1or Λ0
2
Figure 5 The graph shows the sensitivity of the basic reproductionnumber 119877
0to the changes of Λ(119905)
00005
0010015
000050010015
0020
05
1
15
2
25
3
R0
a1a2
Figure 6 The graph of 1198770in terms of 119886
1and 119886
2
globally asymptotically stable and the disease dies out when1198770lt 1 When 119877
0gt 1 the disease persists
The numerical simulations shown in Figure 5 show thatthere are some parameter ranges of Λ
1and Λ
2such that the
threshold parameter 1198770is smaller than 1 It indicates a useful
way to eradicate Huanglongbing by limiting the recruitmentof citrus including the average value and amplitude ofrecruitment function
The results shown in Figure 6 (Figure 7) show that if theamplitudes of infected functions 119887
1 1198872(the average infected
rate 1198861 1198862) are fixed we can control the infection of citrus
and psyllid by limiting the average infected rates 1198861 1198862(the
amplitudes of infected functions 1198871 1198872)
According to the above theoretical analysis andnumericalsimulations we can conclude that the recruitment of citrusand the infection of citrus and psyllid have significanteffects on Huanglongbing transmission In order to preventthe epidemic disease from generating endemic making anappropriate reduction of the recruitment rate of citrus and
01
23
45
02
46
09
1
11
12
13
b1b2
R0
times10minus3
times10minus3
Figure 7 The graph of 1198770in terms of 119887
1and 1198872
decreasing the contact rate between psyllid and the citrus areeffective measures to control Huanglongbing
Disclosure
The paper is approved by all authors for publication Theauthors would like to declare that the work described wasoriginal research that has not been published previously andnot under consideration for publication elsewhere
Conflict of Interests
No conflict of interests exists in the submission of this paper
Acknowledgments
The research has been supported by the Natural ScienceFoundation of China (11261004) the Natural Science Foun-dation of Jiangxi Province (20122BAB211010) the Scienceand Technology Plan Projects of Jiangxi Provincial EducationDepartment (GJJ13646) and the Postgraduate InnovationFund of Jiangxi Province (YC2012-S121)
References
[1] P Christou and R M Twyman ldquoThe potential of geneticallyenhanced plants to address food insecurityrdquo Nutrition ResearchReviews vol 17 no 1 pp 23ndash42 2004
[2] FAO The State of Food Insecurity in the World (SOFI) FAORome Italy 2000 httpwwwfaoorgFOCUSESOFI00sofi001-ehtm
[3] C James ldquoGlobal food securityrdquo in International Congress ofPlant Pathology Pittsburgh Pa USA August 1998
[4] J M Bove ldquoHuanglongbing a destructive newly-emergingcentury-old disease of citrusrdquo Journal of Plant Pathology vol88 no 1 pp 7ndash37 2006
[5] S E Halbert and K L Manjunath ldquoAsian citrus psyllids (Stern-orrhyncha Psyllidae) and greening disease of citrus a literaturereview and assessment of risk in Floridardquo Florida Entomologistvol 87 no 3 pp 330ndash353 2004
10 Abstract and Applied Analysis
[6] S Parnell T R Gottwald C A Gilligan N J Cunniffe and FVan Den Bosch ldquoThe effect of landscape pattern on the optimaleradication zone of an invading epidemicrdquo Phytopathology vol100 no 7 pp 638ndash644 2010
[7] R FMizell III C Tipping P C Andersen B V BrodbeckW BHunter and T Northfield ldquoBehavioral model for Homalodiscavitripennis (Hemiptera Cicadellidae) optimization of hostplant utilization andmanagement implicationsrdquo EnvironmentalEntomology vol 37 no 5 pp 1049ndash1062 2008
[8] G A Braga S Ternes et al ldquoModelagem Matematica daDinamica TemporaldoHLB emCitrosrdquo in Proceedings of the 8thCongresso Brasileiro de Agroinformatica Bento Goncalves 2011
[9] DGHall andMGHentz ldquoSeasonal flight activity by theAsiancitrus psyllid in east central Floridardquo Entomologia et Applicatavol 139 no 1 pp 75ndash85 2011
[10] X Song and A U Neumann ldquoGlobal stability and periodicsolution of the viral dynamicsrdquo Journal ofMathematical Analysisand Applications vol 329 no 1 pp 281ndash297 2007
[11] K Wang Z Teng and H Jiang ldquoOn the permanence forn-species non-autonomous Lotka-Volterra competitive systemwith infinite delays and feedback controlsrdquo International Journalof Biomathematics vol 1 no 1 pp 29ndash43 2008
[12] F Zhang and X-Q Zhao ldquoA periodic epidemic model in apatchy environmentrdquo Journal of Mathematical Analysis andApplications vol 325 no 1 pp 496ndash516 2007
[13] T Zhang and Z Teng ldquoOn a nonautonomous SEIRS model inepidemiologyrdquo Bulletin of Mathematical Biology vol 69 no 8pp 2537ndash2559 2007
[14] Z Teng and Z Li ldquoPermanence and asymptotic behavior of thetv-species nonautonomous lotka-volterra competitive systemsrdquoComputers and Mathematics with Applications vol 39 no 7-8pp 107ndash116 2000
[15] W Wang and X-Q Zhao ldquoThreshold dynamics for compart-mental epidemic models in periodic environmentsrdquo Journal ofDynamics and Differential Equations vol 20 no 3 pp 699ndash7172008
[16] Y Nakata and T Kuniya ldquoGlobal dynamics of a class ofSEIRS epidemic models in a periodic environmentrdquo Journal ofMathematical Analysis and Applications vol 363 no 1 pp 230ndash237 2010
[17] Y Nakata Permanence and Global Asymptotic Stability ForPopulation Models in Mathematical Biology Waseda UniversityTokyo Japan 2010
[18] H Smith and P Waltman The Theory of the Chemostat Cam-bridge University Press Cambridge Mass USA 1995
[19] X ZhaoDynamical Systems in Population Biology Spring NewYork NY USA 2003
[20] X M Deng ldquoFormming process and basis and technologicalpoints of the theory emphasis on control citrus psylla for inte-grated control Huanglongbingrdquo Chinese Agricultural ScienceBulletin vol 25 no 23 pp 358ndash363 2009 (Chinese)
[21] T Li C Z Cheng et al ldquoDetection of the bearing rate ofliberobacter asiaticum in citrus psylla and its host plantrdquo ActaAgriculturae Universitatis Jiangxiensis vol 29 no 5 pp 743ndash745 2007 (Chinese)
[22] G F Chen and X M Deng ldquoDynamic observation adult citruspsyllid quantity live through the winter in spring and winterrdquoSouth China Fruits vol 39 no 4 pp 36ndash38 2010 (Chinese)
[23] XMDeng G F Chen et al ldquoThe newly process of Huanglong-bing in citrusrdquo Guangxi Horticulture vol 17 no 3 pp 49ndash512006
[24] R G drsquoA Vilamiu S Ternes B A Guilherme et al ldquoA modelfor Huanglongbing spread between citrus plants includingdelay times and human interventionrdquo in Proceedings of theInternational Conference of Numerical Analysis and AppliedMathematics (ICNAAM rsquo12) vol 1479 pp 2315ndash2319 2012
where 119909 = (119868ℎ(119905) 119868V(119905) 119878ℎ(119905) 119878V(119905))
119879 Then System (1) can bewritten as the following form
119889119909 (119905)
119889119905= F (119905 119909 (119905)) minusV (119905 119909 (119905)) (7)
whereV(119905 119909(119905)) =Vminus(119905 119909(119905)) minusV+(119905 119909(119905))It is easy to obtain that the conditions (A1)ndash(A5) in [15]
hold In the following we will check the conditions (A6) and(A7) in [15]
We know that 119909lowast(119905) = (0 0 119878lowast
ℎ(119905) 119878lowast
V (119905)) is the disease-free periodic solution of system (7) Denote
Let 119882(119905 119904 120582) 119905 ⩾ 119904 119904 isin 119877 be the evolution operator ofthe System (15) on 1198772 Since 119865(119905) is nonnegative and minus119881(119905)is cooperative then 119903(119882(120596 0 120582)) is continuous and nonin-creasing for 120582 isin (0infin) and lim
V )) minus 119906 (1199051 1198750)10038171003817100381710038171003817le 120578
(36)
for all 119905 ge 0 which implies that 119878lowastℎ(119905) minus 120578 le 119878
ℎ(119905) le 119878
lowast
ℎ(119905) + 120578
119878lowast
V (119905) minus 120578 le 119878V(119905) le 119878lowast
V (119905) + 120578 Then from (1) we have
119889119868ℎ(119905)
119889119905ge 1205731(119905) (119878lowast
ℎ(119905) minus 120578) 119868V (119905) minus (1205831 (119905) + 119889 (119905)) 119868ℎ (119905)
119889119868V (119905)
119889119905ge 1205732(119905) (119878lowast
V (119905) minus 120578) 119868ℎ (119905) minus 1205832 (119905) 119868V (119905)
(37)
6 Abstract and Applied Analysis
Table 1 Parameter definitions and values used for numerical simulations of the Huanglongbing model
Parameter Definition Average value Unit ReferenceΛ The recruitment rate of citrus mdash monthminus1 Estimate1205731
Infected rate of citrus mdash monthminus1 Estimate1205831
Nature death rate of citrus 000275ndash0004167 monthminus1 [20]119889 Disease induced death rate of citrus 0016667ndash0027775 monthminus1 [21]119863 Birth rate of psyllid 378327ndash33526137 monthminus1 [20 22]1205732
Infected rate of psyllid mdash monthminus1 Estimate1205832
Nature death rate of psyllid 01169825ndash095052 monthminus1 [23]119898 Max abundance of psyllid per citrus 120ndash1000 mdash [24]
Table 2 Parameter functions for model (1) according to the values of Table 1
Parameter functions Value Reference
1205731(119905) 00042925 + 0003543 cos (212058711990512) Estimate
1205831(119905) 00034585 + 00007085 cos (212058711990512) [20]
119889 (119905) 0022221 + 0005554 cos (212058711990512) [21]
119863 (119905) 186547035 + 148714335 cos (212058711990512) [20 22]
1205732(119905) 0008779171 + 0004838437 cos (212058711990512) Estimate
1205832(119905) 053375125 + 041676875 cos (212058711990512) [23]
119887 (119905) = 119863 (119905) minus 1205832(119905) 18120952 + 1445466475 cos (212058711990512) [20 22 23]
119898 560 [24]
Consider the linear system
119889119868ℎ (119905)
119889119905= 1205731 (119905) (119878
lowast
ℎ(119905) minus 120578) 119868V (119905) minus (1205831 (119905) + 119889 (119905)) 119868ℎ (119905)
119889119868V (119905)
119889119905= 1205732 (119905) (119878
lowast
V (119905) minus 120578) 119868ℎ (119905) minus 1205832 (119905) 119868V (119905)
(38)
By Lemma 1 and the standard comparison principle we havethat there exists a positive120596-periodic function V
2(119905) such that
119869(119905) = exp(1199012119905)V2(119905) is a solution of System (38) where 119869(119905) =
(119868ℎ(119905) 119868V(119905))
119879 and
1199012=1
120596ln 119903 (Φ
119865minus119881minus119872120578
(120596)) (39)
It follows from 119903(Φ119865minus119881minus119872
120578
(120596)) gt 1 that 1199012gt 0 and 119869(119905) rarr
+infin as 119905 rarr +infin Applying the comparison principle [18] weknow that 119868
ℎ(119905) rarr +infin and 119868V(119905) rarr +infin as 119905 rarr +infin This
is a contradictionThus we have proved that (32) holds and119875is weakly uniformly persistent with respect to (119883
0 1205971198830)
According to the results of Lemma 7 we can easily obtainthat119875 has a global attractor119875
0 It is easy to obtain that119875
0is an
isolated invariant set in119883 and119882119904(1198750)cap1198830= 0We know that
1198750is acyclic in119872
120597and every solution in119872
120597converges to 119875
0
According to Zhao [19] we have that119875 is uniformly persistentwith respect to (119883
0 1205971198830) This implies that the solution of
(1) is uniformly persistent with respect to (1198830 1205971198830) Thus we
have that there exists a 120598 gt 0 such that lim inf119905rarr+infin
119868ℎ(119905) ge 120598
lim inf119905rarr+infin
119868V(119905) ge 120598
5 Numerical Simulationsand Sensitivity Analysis
In this section we will make numerical simulations bymeansof Matlab 71 to support our theoretical results to predictthe trend of the disease and to explore some control andprevention measures Numerical values of parameters ofsystem (1) are given in Table 1 (most of the data are taken fromthe literatures ([20ndash24]))
According to the periodicity of System (1) and Table 1 weset 1205831(119905) = 120572
0
1+ 1205720
2cos(212058711990512) where 1205720
2= (0004167 minus
000275)2 = 00007085 and 12057201= 000275 + 120572
0
2= 00034585
By the similar method we can obtain the other parameterfunctions of model (1) (see Table 2) For the simulations thatfollows we apply the parameters in Table 2 unless otherwisestated
ChooseΛ(119905) = 000265+000235 cos(212058711990512)Then fromLemma 5 we can compute 119877
0= 09844 lt 1 by means of
Matlab 71 FromTheorem 8 we obtain that the infected citruspopulation 119868
ℎ(119905) and the infected psyllid population 119868V(119905) of
system (1) are extinct (see Figures 1 and 2)Choose Λ(119905) = 0005 + 00035 cos(212058711990512) Then from
Lemma 5 we obtain that 1198770= 18342 gt 1 From Theorem 9
we have that the infected citrus population 119868ℎ(119905) and the
infected psyllid population 119868V(119905) of System (1) are permanence(see Figures 3 and 4)
From the formulae for 1198770 we can predict the general
tendency of the epidemic in a long term according to thecurrent situation which is presented in Figures 1 2 3 and 4From the first two figures we know that the epidemic of
Abstract and Applied Analysis 7
002
004
006
008
01
012
0 500 1000 1500 2000 25000
t (month)
R0 = 09844
Ih(t)
(a)
0 100 200 300 400 5000
002
004
006
008
01
012
t (month)
R0 = 09844
Ih(t)
(b)
Figure 1 Graphs of numerical simulations of (1) showings the tendency of the infected citrus population (a) 119905 isin [0 2500] (b) 119905 isin [0 500]
R0 = 09844
0
02
04
06
08
1
12
14
Iv(t)
0 500 1000 1500 2000 25000
t (month)
(a)
02
04
06
08
1
12
14
R0 = 09844
Iv(t)
0 100 200 300 400 5000
t (month)
(b)
Figure 2 It is similar to Figure 1
Huanglongbing can be rising in a short time but cannot beoutbreak with the current prevention and control measuresFrom Figures 3 and 4 we can see that the epidemic ofHuanglongbing dropped heavily after 100 months whilethere is still tendency to a stable periodic solution in a longtime
Next we perform some sensitivity analysis to determinethe influence 119877
0on the parameters Λ(119905) 120573
1(119905) and 120573
2(119905)
We choose function Λ(119905) = Λ01+ Λ0
2cos(212058711990512) where
Λ0
1 Λ02denote the average and amplitude values of Λ(119905)
respectively and Λ0
1= (112) int
12
0Λ(119905)119889119905 From Figure 5
we can observe that the blue line is linear relation between1198770and Λ
0
2 and 119877
0increases as Λ0
2increases The red
curve reflects the influence of the average value of Λ(119905) on1198770 Figure 5 shows that Λ0
1is more sensitive than Λ
0
2on
the basic reproduction number 1198770 Therefore in the real
world decreasing the average recruitment rate of citrus is thevaluable way to control Huanglongbing
Now we consider the combined influence of 1205731(119905) and
1205732(119905) on 119877
0 Set Λ(119905) = 00027 + 000235 cos(212058711990512)
1205731(119905) = 119886
1+ 1198871cos(212058711990512) and 120573
2(119905) = 119886
2+ 1198872cos(212058711990512)
Moreover we know that 1198861
= (112) int12
01205731(119905)119889119905 and
1198862= (112) int
12
01205732(119905)119889119905 Other parameters can be seen in
Table 2
Case (I) We fix 1198871= 0003543 and 119887
2= 0004838437
and let 1198861vary from 000001 to 0015 and 119886
2from 000001
to 002 For this case it is interesting to examine how theaverage values of adequate contact rate 120573
1(119905) and 120573
2(119905) affect
the basic reproduction number 1198770 Numerical results shown
8 Abstract and Applied Analysis
R0 = 18342
006
008
01
012
014
016
018
02Ih(t)
0 500 1000 1500 2000 2500t (month)
(a)
006
008
01
012
014
016
018
02
R0 = 18342
Ih(t)
0 100 200 300 400 500t (month)
(b)
Figure 3 The figures show that the infected citrus population is permanence (a) 119905 isin [0 2500] (b) 119905 isin [0 500]
02
04
06
08
1
12
14
16
18
2
R0 = 18342
0 500 1000 1500 2000 25000
t (month)
Iv(t)
(a)
R0 = 18342
02
04
06
08
1
12
14
16
18
2Iv(t)
0 100 200 300 400 5000
t (month)
(b)
Figure 4 It is similar to Figure 3
in Figure 6 imply that the basic reproduction number1198770may
be less than 1 when 1198861or 1198862is small enough And the results
also imply that 1198770increases as 119886
1and 1198862increase Further we
can observe that from Figure 6(i)the smaller the values of 1198861
or 1198862are the more sensitive 119877
0is (ii) increasing 119886
2may be
more sensitive for 1198770when 119886
1is fixed (iii) increasing 119886
1may
be more sensitive for 1198770when 119886
2is fixed
Case (II) We fix 1198861= 00042925 and 119886
2= 000877917 and
let 1198871vary from 0000001 to 0005 and 119887
2from 0000002 to
0006Then we obtain the result of numerical simulation andit is shown in Figure 7 Obviously Figure 7 shows that 119877
0is
linearly related to both 1198871and 119887
2with the pattern that 119877
0
decreases to a relatively small value (less than 1) only when1198871and 1198872are very small
By the above graphs of the basic reproduction number1198770on the average values of recruitment rate of citrus Λ(119905)
and adequate contact rate 1205731(119905) 1205732(119905) we know that the basic
reproduction number 1198770is a monotonic increasing function
by the average values From the sensitivity analysis diagramswe observe that 119877
0falls to less than 1 by decreasing the values
of those parameters
6 Conclusion
In this paper we have analyzed a HLB transmission modelwith Logistic growth in periodic environments It is provedthat 119877
0is the threshold for distinguishing the disease extinc-
tion or permanence The disease-free periodic solution is
Abstract and Applied Analysis 9
0 1 2 3 4 502
04
06
08
1
12
14
16
18
2
R0
times10minus3
Λ0
1= 00027
Λ0
2= [0000001 0005]
Λ0
1= [0000001 0005]Λ0
2= 000235
Λ0
1or Λ0
2
Figure 5 The graph shows the sensitivity of the basic reproductionnumber 119877
0to the changes of Λ(119905)
00005
0010015
000050010015
0020
05
1
15
2
25
3
R0
a1a2
Figure 6 The graph of 1198770in terms of 119886
1and 119886
2
globally asymptotically stable and the disease dies out when1198770lt 1 When 119877
0gt 1 the disease persists
The numerical simulations shown in Figure 5 show thatthere are some parameter ranges of Λ
1and Λ
2such that the
threshold parameter 1198770is smaller than 1 It indicates a useful
way to eradicate Huanglongbing by limiting the recruitmentof citrus including the average value and amplitude ofrecruitment function
The results shown in Figure 6 (Figure 7) show that if theamplitudes of infected functions 119887
1 1198872(the average infected
rate 1198861 1198862) are fixed we can control the infection of citrus
and psyllid by limiting the average infected rates 1198861 1198862(the
amplitudes of infected functions 1198871 1198872)
According to the above theoretical analysis andnumericalsimulations we can conclude that the recruitment of citrusand the infection of citrus and psyllid have significanteffects on Huanglongbing transmission In order to preventthe epidemic disease from generating endemic making anappropriate reduction of the recruitment rate of citrus and
01
23
45
02
46
09
1
11
12
13
b1b2
R0
times10minus3
times10minus3
Figure 7 The graph of 1198770in terms of 119887
1and 1198872
decreasing the contact rate between psyllid and the citrus areeffective measures to control Huanglongbing
Disclosure
The paper is approved by all authors for publication Theauthors would like to declare that the work described wasoriginal research that has not been published previously andnot under consideration for publication elsewhere
Conflict of Interests
No conflict of interests exists in the submission of this paper
Acknowledgments
The research has been supported by the Natural ScienceFoundation of China (11261004) the Natural Science Foun-dation of Jiangxi Province (20122BAB211010) the Scienceand Technology Plan Projects of Jiangxi Provincial EducationDepartment (GJJ13646) and the Postgraduate InnovationFund of Jiangxi Province (YC2012-S121)
References
[1] P Christou and R M Twyman ldquoThe potential of geneticallyenhanced plants to address food insecurityrdquo Nutrition ResearchReviews vol 17 no 1 pp 23ndash42 2004
[2] FAO The State of Food Insecurity in the World (SOFI) FAORome Italy 2000 httpwwwfaoorgFOCUSESOFI00sofi001-ehtm
[3] C James ldquoGlobal food securityrdquo in International Congress ofPlant Pathology Pittsburgh Pa USA August 1998
[4] J M Bove ldquoHuanglongbing a destructive newly-emergingcentury-old disease of citrusrdquo Journal of Plant Pathology vol88 no 1 pp 7ndash37 2006
[5] S E Halbert and K L Manjunath ldquoAsian citrus psyllids (Stern-orrhyncha Psyllidae) and greening disease of citrus a literaturereview and assessment of risk in Floridardquo Florida Entomologistvol 87 no 3 pp 330ndash353 2004
10 Abstract and Applied Analysis
[6] S Parnell T R Gottwald C A Gilligan N J Cunniffe and FVan Den Bosch ldquoThe effect of landscape pattern on the optimaleradication zone of an invading epidemicrdquo Phytopathology vol100 no 7 pp 638ndash644 2010
[7] R FMizell III C Tipping P C Andersen B V BrodbeckW BHunter and T Northfield ldquoBehavioral model for Homalodiscavitripennis (Hemiptera Cicadellidae) optimization of hostplant utilization andmanagement implicationsrdquo EnvironmentalEntomology vol 37 no 5 pp 1049ndash1062 2008
[8] G A Braga S Ternes et al ldquoModelagem Matematica daDinamica TemporaldoHLB emCitrosrdquo in Proceedings of the 8thCongresso Brasileiro de Agroinformatica Bento Goncalves 2011
[9] DGHall andMGHentz ldquoSeasonal flight activity by theAsiancitrus psyllid in east central Floridardquo Entomologia et Applicatavol 139 no 1 pp 75ndash85 2011
[10] X Song and A U Neumann ldquoGlobal stability and periodicsolution of the viral dynamicsrdquo Journal ofMathematical Analysisand Applications vol 329 no 1 pp 281ndash297 2007
[11] K Wang Z Teng and H Jiang ldquoOn the permanence forn-species non-autonomous Lotka-Volterra competitive systemwith infinite delays and feedback controlsrdquo International Journalof Biomathematics vol 1 no 1 pp 29ndash43 2008
[12] F Zhang and X-Q Zhao ldquoA periodic epidemic model in apatchy environmentrdquo Journal of Mathematical Analysis andApplications vol 325 no 1 pp 496ndash516 2007
[13] T Zhang and Z Teng ldquoOn a nonautonomous SEIRS model inepidemiologyrdquo Bulletin of Mathematical Biology vol 69 no 8pp 2537ndash2559 2007
[14] Z Teng and Z Li ldquoPermanence and asymptotic behavior of thetv-species nonautonomous lotka-volterra competitive systemsrdquoComputers and Mathematics with Applications vol 39 no 7-8pp 107ndash116 2000
[15] W Wang and X-Q Zhao ldquoThreshold dynamics for compart-mental epidemic models in periodic environmentsrdquo Journal ofDynamics and Differential Equations vol 20 no 3 pp 699ndash7172008
[16] Y Nakata and T Kuniya ldquoGlobal dynamics of a class ofSEIRS epidemic models in a periodic environmentrdquo Journal ofMathematical Analysis and Applications vol 363 no 1 pp 230ndash237 2010
[17] Y Nakata Permanence and Global Asymptotic Stability ForPopulation Models in Mathematical Biology Waseda UniversityTokyo Japan 2010
[18] H Smith and P Waltman The Theory of the Chemostat Cam-bridge University Press Cambridge Mass USA 1995
[19] X ZhaoDynamical Systems in Population Biology Spring NewYork NY USA 2003
[20] X M Deng ldquoFormming process and basis and technologicalpoints of the theory emphasis on control citrus psylla for inte-grated control Huanglongbingrdquo Chinese Agricultural ScienceBulletin vol 25 no 23 pp 358ndash363 2009 (Chinese)
[21] T Li C Z Cheng et al ldquoDetection of the bearing rate ofliberobacter asiaticum in citrus psylla and its host plantrdquo ActaAgriculturae Universitatis Jiangxiensis vol 29 no 5 pp 743ndash745 2007 (Chinese)
[22] G F Chen and X M Deng ldquoDynamic observation adult citruspsyllid quantity live through the winter in spring and winterrdquoSouth China Fruits vol 39 no 4 pp 36ndash38 2010 (Chinese)
[23] XMDeng G F Chen et al ldquoThe newly process of Huanglong-bing in citrusrdquo Guangxi Horticulture vol 17 no 3 pp 49ndash512006
[24] R G drsquoA Vilamiu S Ternes B A Guilherme et al ldquoA modelfor Huanglongbing spread between citrus plants includingdelay times and human interventionrdquo in Proceedings of theInternational Conference of Numerical Analysis and AppliedMathematics (ICNAAM rsquo12) vol 1479 pp 2315ndash2319 2012
V )) minus 119906 (1199051 1198750)10038171003817100381710038171003817le 120578
(36)
for all 119905 ge 0 which implies that 119878lowastℎ(119905) minus 120578 le 119878
ℎ(119905) le 119878
lowast
ℎ(119905) + 120578
119878lowast
V (119905) minus 120578 le 119878V(119905) le 119878lowast
V (119905) + 120578 Then from (1) we have
119889119868ℎ(119905)
119889119905ge 1205731(119905) (119878lowast
ℎ(119905) minus 120578) 119868V (119905) minus (1205831 (119905) + 119889 (119905)) 119868ℎ (119905)
119889119868V (119905)
119889119905ge 1205732(119905) (119878lowast
V (119905) minus 120578) 119868ℎ (119905) minus 1205832 (119905) 119868V (119905)
(37)
6 Abstract and Applied Analysis
Table 1 Parameter definitions and values used for numerical simulations of the Huanglongbing model
Parameter Definition Average value Unit ReferenceΛ The recruitment rate of citrus mdash monthminus1 Estimate1205731
Infected rate of citrus mdash monthminus1 Estimate1205831
Nature death rate of citrus 000275ndash0004167 monthminus1 [20]119889 Disease induced death rate of citrus 0016667ndash0027775 monthminus1 [21]119863 Birth rate of psyllid 378327ndash33526137 monthminus1 [20 22]1205732
Infected rate of psyllid mdash monthminus1 Estimate1205832
Nature death rate of psyllid 01169825ndash095052 monthminus1 [23]119898 Max abundance of psyllid per citrus 120ndash1000 mdash [24]
Table 2 Parameter functions for model (1) according to the values of Table 1
Parameter functions Value Reference
1205731(119905) 00042925 + 0003543 cos (212058711990512) Estimate
1205831(119905) 00034585 + 00007085 cos (212058711990512) [20]
119889 (119905) 0022221 + 0005554 cos (212058711990512) [21]
119863 (119905) 186547035 + 148714335 cos (212058711990512) [20 22]
1205732(119905) 0008779171 + 0004838437 cos (212058711990512) Estimate
1205832(119905) 053375125 + 041676875 cos (212058711990512) [23]
119887 (119905) = 119863 (119905) minus 1205832(119905) 18120952 + 1445466475 cos (212058711990512) [20 22 23]
119898 560 [24]
Consider the linear system
119889119868ℎ (119905)
119889119905= 1205731 (119905) (119878
lowast
ℎ(119905) minus 120578) 119868V (119905) minus (1205831 (119905) + 119889 (119905)) 119868ℎ (119905)
119889119868V (119905)
119889119905= 1205732 (119905) (119878
lowast
V (119905) minus 120578) 119868ℎ (119905) minus 1205832 (119905) 119868V (119905)
(38)
By Lemma 1 and the standard comparison principle we havethat there exists a positive120596-periodic function V
2(119905) such that
119869(119905) = exp(1199012119905)V2(119905) is a solution of System (38) where 119869(119905) =
(119868ℎ(119905) 119868V(119905))
119879 and
1199012=1
120596ln 119903 (Φ
119865minus119881minus119872120578
(120596)) (39)
It follows from 119903(Φ119865minus119881minus119872
120578
(120596)) gt 1 that 1199012gt 0 and 119869(119905) rarr
+infin as 119905 rarr +infin Applying the comparison principle [18] weknow that 119868
ℎ(119905) rarr +infin and 119868V(119905) rarr +infin as 119905 rarr +infin This
is a contradictionThus we have proved that (32) holds and119875is weakly uniformly persistent with respect to (119883
0 1205971198830)
According to the results of Lemma 7 we can easily obtainthat119875 has a global attractor119875
0 It is easy to obtain that119875
0is an
isolated invariant set in119883 and119882119904(1198750)cap1198830= 0We know that
1198750is acyclic in119872
120597and every solution in119872
120597converges to 119875
0
According to Zhao [19] we have that119875 is uniformly persistentwith respect to (119883
0 1205971198830) This implies that the solution of
(1) is uniformly persistent with respect to (1198830 1205971198830) Thus we
have that there exists a 120598 gt 0 such that lim inf119905rarr+infin
119868ℎ(119905) ge 120598
lim inf119905rarr+infin
119868V(119905) ge 120598
5 Numerical Simulationsand Sensitivity Analysis
In this section we will make numerical simulations bymeansof Matlab 71 to support our theoretical results to predictthe trend of the disease and to explore some control andprevention measures Numerical values of parameters ofsystem (1) are given in Table 1 (most of the data are taken fromthe literatures ([20ndash24]))
According to the periodicity of System (1) and Table 1 weset 1205831(119905) = 120572
0
1+ 1205720
2cos(212058711990512) where 1205720
2= (0004167 minus
000275)2 = 00007085 and 12057201= 000275 + 120572
0
2= 00034585
By the similar method we can obtain the other parameterfunctions of model (1) (see Table 2) For the simulations thatfollows we apply the parameters in Table 2 unless otherwisestated
ChooseΛ(119905) = 000265+000235 cos(212058711990512)Then fromLemma 5 we can compute 119877
0= 09844 lt 1 by means of
Matlab 71 FromTheorem 8 we obtain that the infected citruspopulation 119868
ℎ(119905) and the infected psyllid population 119868V(119905) of
system (1) are extinct (see Figures 1 and 2)Choose Λ(119905) = 0005 + 00035 cos(212058711990512) Then from
Lemma 5 we obtain that 1198770= 18342 gt 1 From Theorem 9
we have that the infected citrus population 119868ℎ(119905) and the
infected psyllid population 119868V(119905) of System (1) are permanence(see Figures 3 and 4)
From the formulae for 1198770 we can predict the general
tendency of the epidemic in a long term according to thecurrent situation which is presented in Figures 1 2 3 and 4From the first two figures we know that the epidemic of
Abstract and Applied Analysis 7
002
004
006
008
01
012
0 500 1000 1500 2000 25000
t (month)
R0 = 09844
Ih(t)
(a)
0 100 200 300 400 5000
002
004
006
008
01
012
t (month)
R0 = 09844
Ih(t)
(b)
Figure 1 Graphs of numerical simulations of (1) showings the tendency of the infected citrus population (a) 119905 isin [0 2500] (b) 119905 isin [0 500]
R0 = 09844
0
02
04
06
08
1
12
14
Iv(t)
0 500 1000 1500 2000 25000
t (month)
(a)
02
04
06
08
1
12
14
R0 = 09844
Iv(t)
0 100 200 300 400 5000
t (month)
(b)
Figure 2 It is similar to Figure 1
Huanglongbing can be rising in a short time but cannot beoutbreak with the current prevention and control measuresFrom Figures 3 and 4 we can see that the epidemic ofHuanglongbing dropped heavily after 100 months whilethere is still tendency to a stable periodic solution in a longtime
Next we perform some sensitivity analysis to determinethe influence 119877
0on the parameters Λ(119905) 120573
1(119905) and 120573
2(119905)
We choose function Λ(119905) = Λ01+ Λ0
2cos(212058711990512) where
Λ0
1 Λ02denote the average and amplitude values of Λ(119905)
respectively and Λ0
1= (112) int
12
0Λ(119905)119889119905 From Figure 5
we can observe that the blue line is linear relation between1198770and Λ
0
2 and 119877
0increases as Λ0
2increases The red
curve reflects the influence of the average value of Λ(119905) on1198770 Figure 5 shows that Λ0
1is more sensitive than Λ
0
2on
the basic reproduction number 1198770 Therefore in the real
world decreasing the average recruitment rate of citrus is thevaluable way to control Huanglongbing
Now we consider the combined influence of 1205731(119905) and
1205732(119905) on 119877
0 Set Λ(119905) = 00027 + 000235 cos(212058711990512)
1205731(119905) = 119886
1+ 1198871cos(212058711990512) and 120573
2(119905) = 119886
2+ 1198872cos(212058711990512)
Moreover we know that 1198861
= (112) int12
01205731(119905)119889119905 and
1198862= (112) int
12
01205732(119905)119889119905 Other parameters can be seen in
Table 2
Case (I) We fix 1198871= 0003543 and 119887
2= 0004838437
and let 1198861vary from 000001 to 0015 and 119886
2from 000001
to 002 For this case it is interesting to examine how theaverage values of adequate contact rate 120573
1(119905) and 120573
2(119905) affect
the basic reproduction number 1198770 Numerical results shown
8 Abstract and Applied Analysis
R0 = 18342
006
008
01
012
014
016
018
02Ih(t)
0 500 1000 1500 2000 2500t (month)
(a)
006
008
01
012
014
016
018
02
R0 = 18342
Ih(t)
0 100 200 300 400 500t (month)
(b)
Figure 3 The figures show that the infected citrus population is permanence (a) 119905 isin [0 2500] (b) 119905 isin [0 500]
02
04
06
08
1
12
14
16
18
2
R0 = 18342
0 500 1000 1500 2000 25000
t (month)
Iv(t)
(a)
R0 = 18342
02
04
06
08
1
12
14
16
18
2Iv(t)
0 100 200 300 400 5000
t (month)
(b)
Figure 4 It is similar to Figure 3
in Figure 6 imply that the basic reproduction number1198770may
be less than 1 when 1198861or 1198862is small enough And the results
also imply that 1198770increases as 119886
1and 1198862increase Further we
can observe that from Figure 6(i)the smaller the values of 1198861
or 1198862are the more sensitive 119877
0is (ii) increasing 119886
2may be
more sensitive for 1198770when 119886
1is fixed (iii) increasing 119886
1may
be more sensitive for 1198770when 119886
2is fixed
Case (II) We fix 1198861= 00042925 and 119886
2= 000877917 and
let 1198871vary from 0000001 to 0005 and 119887
2from 0000002 to
0006Then we obtain the result of numerical simulation andit is shown in Figure 7 Obviously Figure 7 shows that 119877
0is
linearly related to both 1198871and 119887
2with the pattern that 119877
0
decreases to a relatively small value (less than 1) only when1198871and 1198872are very small
By the above graphs of the basic reproduction number1198770on the average values of recruitment rate of citrus Λ(119905)
and adequate contact rate 1205731(119905) 1205732(119905) we know that the basic
reproduction number 1198770is a monotonic increasing function
by the average values From the sensitivity analysis diagramswe observe that 119877
0falls to less than 1 by decreasing the values
of those parameters
6 Conclusion
In this paper we have analyzed a HLB transmission modelwith Logistic growth in periodic environments It is provedthat 119877
0is the threshold for distinguishing the disease extinc-
tion or permanence The disease-free periodic solution is
Abstract and Applied Analysis 9
0 1 2 3 4 502
04
06
08
1
12
14
16
18
2
R0
times10minus3
Λ0
1= 00027
Λ0
2= [0000001 0005]
Λ0
1= [0000001 0005]Λ0
2= 000235
Λ0
1or Λ0
2
Figure 5 The graph shows the sensitivity of the basic reproductionnumber 119877
0to the changes of Λ(119905)
00005
0010015
000050010015
0020
05
1
15
2
25
3
R0
a1a2
Figure 6 The graph of 1198770in terms of 119886
1and 119886
2
globally asymptotically stable and the disease dies out when1198770lt 1 When 119877
0gt 1 the disease persists
The numerical simulations shown in Figure 5 show thatthere are some parameter ranges of Λ
1and Λ
2such that the
threshold parameter 1198770is smaller than 1 It indicates a useful
way to eradicate Huanglongbing by limiting the recruitmentof citrus including the average value and amplitude ofrecruitment function
The results shown in Figure 6 (Figure 7) show that if theamplitudes of infected functions 119887
1 1198872(the average infected
rate 1198861 1198862) are fixed we can control the infection of citrus
and psyllid by limiting the average infected rates 1198861 1198862(the
amplitudes of infected functions 1198871 1198872)
According to the above theoretical analysis andnumericalsimulations we can conclude that the recruitment of citrusand the infection of citrus and psyllid have significanteffects on Huanglongbing transmission In order to preventthe epidemic disease from generating endemic making anappropriate reduction of the recruitment rate of citrus and
01
23
45
02
46
09
1
11
12
13
b1b2
R0
times10minus3
times10minus3
Figure 7 The graph of 1198770in terms of 119887
1and 1198872
decreasing the contact rate between psyllid and the citrus areeffective measures to control Huanglongbing
Disclosure
The paper is approved by all authors for publication Theauthors would like to declare that the work described wasoriginal research that has not been published previously andnot under consideration for publication elsewhere
Conflict of Interests
No conflict of interests exists in the submission of this paper
Acknowledgments
The research has been supported by the Natural ScienceFoundation of China (11261004) the Natural Science Foun-dation of Jiangxi Province (20122BAB211010) the Scienceand Technology Plan Projects of Jiangxi Provincial EducationDepartment (GJJ13646) and the Postgraduate InnovationFund of Jiangxi Province (YC2012-S121)
References
[1] P Christou and R M Twyman ldquoThe potential of geneticallyenhanced plants to address food insecurityrdquo Nutrition ResearchReviews vol 17 no 1 pp 23ndash42 2004
[2] FAO The State of Food Insecurity in the World (SOFI) FAORome Italy 2000 httpwwwfaoorgFOCUSESOFI00sofi001-ehtm
[3] C James ldquoGlobal food securityrdquo in International Congress ofPlant Pathology Pittsburgh Pa USA August 1998
[4] J M Bove ldquoHuanglongbing a destructive newly-emergingcentury-old disease of citrusrdquo Journal of Plant Pathology vol88 no 1 pp 7ndash37 2006
[5] S E Halbert and K L Manjunath ldquoAsian citrus psyllids (Stern-orrhyncha Psyllidae) and greening disease of citrus a literaturereview and assessment of risk in Floridardquo Florida Entomologistvol 87 no 3 pp 330ndash353 2004
10 Abstract and Applied Analysis
[6] S Parnell T R Gottwald C A Gilligan N J Cunniffe and FVan Den Bosch ldquoThe effect of landscape pattern on the optimaleradication zone of an invading epidemicrdquo Phytopathology vol100 no 7 pp 638ndash644 2010
[7] R FMizell III C Tipping P C Andersen B V BrodbeckW BHunter and T Northfield ldquoBehavioral model for Homalodiscavitripennis (Hemiptera Cicadellidae) optimization of hostplant utilization andmanagement implicationsrdquo EnvironmentalEntomology vol 37 no 5 pp 1049ndash1062 2008
[8] G A Braga S Ternes et al ldquoModelagem Matematica daDinamica TemporaldoHLB emCitrosrdquo in Proceedings of the 8thCongresso Brasileiro de Agroinformatica Bento Goncalves 2011
[9] DGHall andMGHentz ldquoSeasonal flight activity by theAsiancitrus psyllid in east central Floridardquo Entomologia et Applicatavol 139 no 1 pp 75ndash85 2011
[10] X Song and A U Neumann ldquoGlobal stability and periodicsolution of the viral dynamicsrdquo Journal ofMathematical Analysisand Applications vol 329 no 1 pp 281ndash297 2007
[11] K Wang Z Teng and H Jiang ldquoOn the permanence forn-species non-autonomous Lotka-Volterra competitive systemwith infinite delays and feedback controlsrdquo International Journalof Biomathematics vol 1 no 1 pp 29ndash43 2008
[12] F Zhang and X-Q Zhao ldquoA periodic epidemic model in apatchy environmentrdquo Journal of Mathematical Analysis andApplications vol 325 no 1 pp 496ndash516 2007
[13] T Zhang and Z Teng ldquoOn a nonautonomous SEIRS model inepidemiologyrdquo Bulletin of Mathematical Biology vol 69 no 8pp 2537ndash2559 2007
[14] Z Teng and Z Li ldquoPermanence and asymptotic behavior of thetv-species nonautonomous lotka-volterra competitive systemsrdquoComputers and Mathematics with Applications vol 39 no 7-8pp 107ndash116 2000
[15] W Wang and X-Q Zhao ldquoThreshold dynamics for compart-mental epidemic models in periodic environmentsrdquo Journal ofDynamics and Differential Equations vol 20 no 3 pp 699ndash7172008
[16] Y Nakata and T Kuniya ldquoGlobal dynamics of a class ofSEIRS epidemic models in a periodic environmentrdquo Journal ofMathematical Analysis and Applications vol 363 no 1 pp 230ndash237 2010
[17] Y Nakata Permanence and Global Asymptotic Stability ForPopulation Models in Mathematical Biology Waseda UniversityTokyo Japan 2010
[18] H Smith and P Waltman The Theory of the Chemostat Cam-bridge University Press Cambridge Mass USA 1995
[19] X ZhaoDynamical Systems in Population Biology Spring NewYork NY USA 2003
[20] X M Deng ldquoFormming process and basis and technologicalpoints of the theory emphasis on control citrus psylla for inte-grated control Huanglongbingrdquo Chinese Agricultural ScienceBulletin vol 25 no 23 pp 358ndash363 2009 (Chinese)
[21] T Li C Z Cheng et al ldquoDetection of the bearing rate ofliberobacter asiaticum in citrus psylla and its host plantrdquo ActaAgriculturae Universitatis Jiangxiensis vol 29 no 5 pp 743ndash745 2007 (Chinese)
[22] G F Chen and X M Deng ldquoDynamic observation adult citruspsyllid quantity live through the winter in spring and winterrdquoSouth China Fruits vol 39 no 4 pp 36ndash38 2010 (Chinese)
[23] XMDeng G F Chen et al ldquoThe newly process of Huanglong-bing in citrusrdquo Guangxi Horticulture vol 17 no 3 pp 49ndash512006
[24] R G drsquoA Vilamiu S Ternes B A Guilherme et al ldquoA modelfor Huanglongbing spread between citrus plants includingdelay times and human interventionrdquo in Proceedings of theInternational Conference of Numerical Analysis and AppliedMathematics (ICNAAM rsquo12) vol 1479 pp 2315ndash2319 2012
V )) minus 119906 (1199051 1198750)10038171003817100381710038171003817le 120578
(36)
for all 119905 ge 0 which implies that 119878lowastℎ(119905) minus 120578 le 119878
ℎ(119905) le 119878
lowast
ℎ(119905) + 120578
119878lowast
V (119905) minus 120578 le 119878V(119905) le 119878lowast
V (119905) + 120578 Then from (1) we have
119889119868ℎ(119905)
119889119905ge 1205731(119905) (119878lowast
ℎ(119905) minus 120578) 119868V (119905) minus (1205831 (119905) + 119889 (119905)) 119868ℎ (119905)
119889119868V (119905)
119889119905ge 1205732(119905) (119878lowast
V (119905) minus 120578) 119868ℎ (119905) minus 1205832 (119905) 119868V (119905)
(37)
6 Abstract and Applied Analysis
Table 1 Parameter definitions and values used for numerical simulations of the Huanglongbing model
Parameter Definition Average value Unit ReferenceΛ The recruitment rate of citrus mdash monthminus1 Estimate1205731
Infected rate of citrus mdash monthminus1 Estimate1205831
Nature death rate of citrus 000275ndash0004167 monthminus1 [20]119889 Disease induced death rate of citrus 0016667ndash0027775 monthminus1 [21]119863 Birth rate of psyllid 378327ndash33526137 monthminus1 [20 22]1205732
Infected rate of psyllid mdash monthminus1 Estimate1205832
Nature death rate of psyllid 01169825ndash095052 monthminus1 [23]119898 Max abundance of psyllid per citrus 120ndash1000 mdash [24]
Table 2 Parameter functions for model (1) according to the values of Table 1
Parameter functions Value Reference
1205731(119905) 00042925 + 0003543 cos (212058711990512) Estimate
1205831(119905) 00034585 + 00007085 cos (212058711990512) [20]
119889 (119905) 0022221 + 0005554 cos (212058711990512) [21]
119863 (119905) 186547035 + 148714335 cos (212058711990512) [20 22]
1205732(119905) 0008779171 + 0004838437 cos (212058711990512) Estimate
1205832(119905) 053375125 + 041676875 cos (212058711990512) [23]
119887 (119905) = 119863 (119905) minus 1205832(119905) 18120952 + 1445466475 cos (212058711990512) [20 22 23]
119898 560 [24]
Consider the linear system
119889119868ℎ (119905)
119889119905= 1205731 (119905) (119878
lowast
ℎ(119905) minus 120578) 119868V (119905) minus (1205831 (119905) + 119889 (119905)) 119868ℎ (119905)
119889119868V (119905)
119889119905= 1205732 (119905) (119878
lowast
V (119905) minus 120578) 119868ℎ (119905) minus 1205832 (119905) 119868V (119905)
(38)
By Lemma 1 and the standard comparison principle we havethat there exists a positive120596-periodic function V
2(119905) such that
119869(119905) = exp(1199012119905)V2(119905) is a solution of System (38) where 119869(119905) =
(119868ℎ(119905) 119868V(119905))
119879 and
1199012=1
120596ln 119903 (Φ
119865minus119881minus119872120578
(120596)) (39)
It follows from 119903(Φ119865minus119881minus119872
120578
(120596)) gt 1 that 1199012gt 0 and 119869(119905) rarr
+infin as 119905 rarr +infin Applying the comparison principle [18] weknow that 119868
ℎ(119905) rarr +infin and 119868V(119905) rarr +infin as 119905 rarr +infin This
is a contradictionThus we have proved that (32) holds and119875is weakly uniformly persistent with respect to (119883
0 1205971198830)
According to the results of Lemma 7 we can easily obtainthat119875 has a global attractor119875
0 It is easy to obtain that119875
0is an
isolated invariant set in119883 and119882119904(1198750)cap1198830= 0We know that
1198750is acyclic in119872
120597and every solution in119872
120597converges to 119875
0
According to Zhao [19] we have that119875 is uniformly persistentwith respect to (119883
0 1205971198830) This implies that the solution of
(1) is uniformly persistent with respect to (1198830 1205971198830) Thus we
have that there exists a 120598 gt 0 such that lim inf119905rarr+infin
119868ℎ(119905) ge 120598
lim inf119905rarr+infin
119868V(119905) ge 120598
5 Numerical Simulationsand Sensitivity Analysis
In this section we will make numerical simulations bymeansof Matlab 71 to support our theoretical results to predictthe trend of the disease and to explore some control andprevention measures Numerical values of parameters ofsystem (1) are given in Table 1 (most of the data are taken fromthe literatures ([20ndash24]))
According to the periodicity of System (1) and Table 1 weset 1205831(119905) = 120572
0
1+ 1205720
2cos(212058711990512) where 1205720
2= (0004167 minus
000275)2 = 00007085 and 12057201= 000275 + 120572
0
2= 00034585
By the similar method we can obtain the other parameterfunctions of model (1) (see Table 2) For the simulations thatfollows we apply the parameters in Table 2 unless otherwisestated
ChooseΛ(119905) = 000265+000235 cos(212058711990512)Then fromLemma 5 we can compute 119877
0= 09844 lt 1 by means of
Matlab 71 FromTheorem 8 we obtain that the infected citruspopulation 119868
ℎ(119905) and the infected psyllid population 119868V(119905) of
system (1) are extinct (see Figures 1 and 2)Choose Λ(119905) = 0005 + 00035 cos(212058711990512) Then from
Lemma 5 we obtain that 1198770= 18342 gt 1 From Theorem 9
we have that the infected citrus population 119868ℎ(119905) and the
infected psyllid population 119868V(119905) of System (1) are permanence(see Figures 3 and 4)
From the formulae for 1198770 we can predict the general
tendency of the epidemic in a long term according to thecurrent situation which is presented in Figures 1 2 3 and 4From the first two figures we know that the epidemic of
Abstract and Applied Analysis 7
002
004
006
008
01
012
0 500 1000 1500 2000 25000
t (month)
R0 = 09844
Ih(t)
(a)
0 100 200 300 400 5000
002
004
006
008
01
012
t (month)
R0 = 09844
Ih(t)
(b)
Figure 1 Graphs of numerical simulations of (1) showings the tendency of the infected citrus population (a) 119905 isin [0 2500] (b) 119905 isin [0 500]
R0 = 09844
0
02
04
06
08
1
12
14
Iv(t)
0 500 1000 1500 2000 25000
t (month)
(a)
02
04
06
08
1
12
14
R0 = 09844
Iv(t)
0 100 200 300 400 5000
t (month)
(b)
Figure 2 It is similar to Figure 1
Huanglongbing can be rising in a short time but cannot beoutbreak with the current prevention and control measuresFrom Figures 3 and 4 we can see that the epidemic ofHuanglongbing dropped heavily after 100 months whilethere is still tendency to a stable periodic solution in a longtime
Next we perform some sensitivity analysis to determinethe influence 119877
0on the parameters Λ(119905) 120573
1(119905) and 120573
2(119905)
We choose function Λ(119905) = Λ01+ Λ0
2cos(212058711990512) where
Λ0
1 Λ02denote the average and amplitude values of Λ(119905)
respectively and Λ0
1= (112) int
12
0Λ(119905)119889119905 From Figure 5
we can observe that the blue line is linear relation between1198770and Λ
0
2 and 119877
0increases as Λ0
2increases The red
curve reflects the influence of the average value of Λ(119905) on1198770 Figure 5 shows that Λ0
1is more sensitive than Λ
0
2on
the basic reproduction number 1198770 Therefore in the real
world decreasing the average recruitment rate of citrus is thevaluable way to control Huanglongbing
Now we consider the combined influence of 1205731(119905) and
1205732(119905) on 119877
0 Set Λ(119905) = 00027 + 000235 cos(212058711990512)
1205731(119905) = 119886
1+ 1198871cos(212058711990512) and 120573
2(119905) = 119886
2+ 1198872cos(212058711990512)
Moreover we know that 1198861
= (112) int12
01205731(119905)119889119905 and
1198862= (112) int
12
01205732(119905)119889119905 Other parameters can be seen in
Table 2
Case (I) We fix 1198871= 0003543 and 119887
2= 0004838437
and let 1198861vary from 000001 to 0015 and 119886
2from 000001
to 002 For this case it is interesting to examine how theaverage values of adequate contact rate 120573
1(119905) and 120573
2(119905) affect
the basic reproduction number 1198770 Numerical results shown
8 Abstract and Applied Analysis
R0 = 18342
006
008
01
012
014
016
018
02Ih(t)
0 500 1000 1500 2000 2500t (month)
(a)
006
008
01
012
014
016
018
02
R0 = 18342
Ih(t)
0 100 200 300 400 500t (month)
(b)
Figure 3 The figures show that the infected citrus population is permanence (a) 119905 isin [0 2500] (b) 119905 isin [0 500]
02
04
06
08
1
12
14
16
18
2
R0 = 18342
0 500 1000 1500 2000 25000
t (month)
Iv(t)
(a)
R0 = 18342
02
04
06
08
1
12
14
16
18
2Iv(t)
0 100 200 300 400 5000
t (month)
(b)
Figure 4 It is similar to Figure 3
in Figure 6 imply that the basic reproduction number1198770may
be less than 1 when 1198861or 1198862is small enough And the results
also imply that 1198770increases as 119886
1and 1198862increase Further we
can observe that from Figure 6(i)the smaller the values of 1198861
or 1198862are the more sensitive 119877
0is (ii) increasing 119886
2may be
more sensitive for 1198770when 119886
1is fixed (iii) increasing 119886
1may
be more sensitive for 1198770when 119886
2is fixed
Case (II) We fix 1198861= 00042925 and 119886
2= 000877917 and
let 1198871vary from 0000001 to 0005 and 119887
2from 0000002 to
0006Then we obtain the result of numerical simulation andit is shown in Figure 7 Obviously Figure 7 shows that 119877
0is
linearly related to both 1198871and 119887
2with the pattern that 119877
0
decreases to a relatively small value (less than 1) only when1198871and 1198872are very small
By the above graphs of the basic reproduction number1198770on the average values of recruitment rate of citrus Λ(119905)
and adequate contact rate 1205731(119905) 1205732(119905) we know that the basic
reproduction number 1198770is a monotonic increasing function
by the average values From the sensitivity analysis diagramswe observe that 119877
0falls to less than 1 by decreasing the values
of those parameters
6 Conclusion
In this paper we have analyzed a HLB transmission modelwith Logistic growth in periodic environments It is provedthat 119877
0is the threshold for distinguishing the disease extinc-
tion or permanence The disease-free periodic solution is
Abstract and Applied Analysis 9
0 1 2 3 4 502
04
06
08
1
12
14
16
18
2
R0
times10minus3
Λ0
1= 00027
Λ0
2= [0000001 0005]
Λ0
1= [0000001 0005]Λ0
2= 000235
Λ0
1or Λ0
2
Figure 5 The graph shows the sensitivity of the basic reproductionnumber 119877
0to the changes of Λ(119905)
00005
0010015
000050010015
0020
05
1
15
2
25
3
R0
a1a2
Figure 6 The graph of 1198770in terms of 119886
1and 119886
2
globally asymptotically stable and the disease dies out when1198770lt 1 When 119877
0gt 1 the disease persists
The numerical simulations shown in Figure 5 show thatthere are some parameter ranges of Λ
1and Λ
2such that the
threshold parameter 1198770is smaller than 1 It indicates a useful
way to eradicate Huanglongbing by limiting the recruitmentof citrus including the average value and amplitude ofrecruitment function
The results shown in Figure 6 (Figure 7) show that if theamplitudes of infected functions 119887
1 1198872(the average infected
rate 1198861 1198862) are fixed we can control the infection of citrus
and psyllid by limiting the average infected rates 1198861 1198862(the
amplitudes of infected functions 1198871 1198872)
According to the above theoretical analysis andnumericalsimulations we can conclude that the recruitment of citrusand the infection of citrus and psyllid have significanteffects on Huanglongbing transmission In order to preventthe epidemic disease from generating endemic making anappropriate reduction of the recruitment rate of citrus and
01
23
45
02
46
09
1
11
12
13
b1b2
R0
times10minus3
times10minus3
Figure 7 The graph of 1198770in terms of 119887
1and 1198872
decreasing the contact rate between psyllid and the citrus areeffective measures to control Huanglongbing
Disclosure
The paper is approved by all authors for publication Theauthors would like to declare that the work described wasoriginal research that has not been published previously andnot under consideration for publication elsewhere
Conflict of Interests
No conflict of interests exists in the submission of this paper
Acknowledgments
The research has been supported by the Natural ScienceFoundation of China (11261004) the Natural Science Foun-dation of Jiangxi Province (20122BAB211010) the Scienceand Technology Plan Projects of Jiangxi Provincial EducationDepartment (GJJ13646) and the Postgraduate InnovationFund of Jiangxi Province (YC2012-S121)
References
[1] P Christou and R M Twyman ldquoThe potential of geneticallyenhanced plants to address food insecurityrdquo Nutrition ResearchReviews vol 17 no 1 pp 23ndash42 2004
[2] FAO The State of Food Insecurity in the World (SOFI) FAORome Italy 2000 httpwwwfaoorgFOCUSESOFI00sofi001-ehtm
[3] C James ldquoGlobal food securityrdquo in International Congress ofPlant Pathology Pittsburgh Pa USA August 1998
[4] J M Bove ldquoHuanglongbing a destructive newly-emergingcentury-old disease of citrusrdquo Journal of Plant Pathology vol88 no 1 pp 7ndash37 2006
[5] S E Halbert and K L Manjunath ldquoAsian citrus psyllids (Stern-orrhyncha Psyllidae) and greening disease of citrus a literaturereview and assessment of risk in Floridardquo Florida Entomologistvol 87 no 3 pp 330ndash353 2004
10 Abstract and Applied Analysis
[6] S Parnell T R Gottwald C A Gilligan N J Cunniffe and FVan Den Bosch ldquoThe effect of landscape pattern on the optimaleradication zone of an invading epidemicrdquo Phytopathology vol100 no 7 pp 638ndash644 2010
[7] R FMizell III C Tipping P C Andersen B V BrodbeckW BHunter and T Northfield ldquoBehavioral model for Homalodiscavitripennis (Hemiptera Cicadellidae) optimization of hostplant utilization andmanagement implicationsrdquo EnvironmentalEntomology vol 37 no 5 pp 1049ndash1062 2008
[8] G A Braga S Ternes et al ldquoModelagem Matematica daDinamica TemporaldoHLB emCitrosrdquo in Proceedings of the 8thCongresso Brasileiro de Agroinformatica Bento Goncalves 2011
[9] DGHall andMGHentz ldquoSeasonal flight activity by theAsiancitrus psyllid in east central Floridardquo Entomologia et Applicatavol 139 no 1 pp 75ndash85 2011
[10] X Song and A U Neumann ldquoGlobal stability and periodicsolution of the viral dynamicsrdquo Journal ofMathematical Analysisand Applications vol 329 no 1 pp 281ndash297 2007
[11] K Wang Z Teng and H Jiang ldquoOn the permanence forn-species non-autonomous Lotka-Volterra competitive systemwith infinite delays and feedback controlsrdquo International Journalof Biomathematics vol 1 no 1 pp 29ndash43 2008
[12] F Zhang and X-Q Zhao ldquoA periodic epidemic model in apatchy environmentrdquo Journal of Mathematical Analysis andApplications vol 325 no 1 pp 496ndash516 2007
[13] T Zhang and Z Teng ldquoOn a nonautonomous SEIRS model inepidemiologyrdquo Bulletin of Mathematical Biology vol 69 no 8pp 2537ndash2559 2007
[14] Z Teng and Z Li ldquoPermanence and asymptotic behavior of thetv-species nonautonomous lotka-volterra competitive systemsrdquoComputers and Mathematics with Applications vol 39 no 7-8pp 107ndash116 2000
[15] W Wang and X-Q Zhao ldquoThreshold dynamics for compart-mental epidemic models in periodic environmentsrdquo Journal ofDynamics and Differential Equations vol 20 no 3 pp 699ndash7172008
[16] Y Nakata and T Kuniya ldquoGlobal dynamics of a class ofSEIRS epidemic models in a periodic environmentrdquo Journal ofMathematical Analysis and Applications vol 363 no 1 pp 230ndash237 2010
[17] Y Nakata Permanence and Global Asymptotic Stability ForPopulation Models in Mathematical Biology Waseda UniversityTokyo Japan 2010
[18] H Smith and P Waltman The Theory of the Chemostat Cam-bridge University Press Cambridge Mass USA 1995
[19] X ZhaoDynamical Systems in Population Biology Spring NewYork NY USA 2003
[20] X M Deng ldquoFormming process and basis and technologicalpoints of the theory emphasis on control citrus psylla for inte-grated control Huanglongbingrdquo Chinese Agricultural ScienceBulletin vol 25 no 23 pp 358ndash363 2009 (Chinese)
[21] T Li C Z Cheng et al ldquoDetection of the bearing rate ofliberobacter asiaticum in citrus psylla and its host plantrdquo ActaAgriculturae Universitatis Jiangxiensis vol 29 no 5 pp 743ndash745 2007 (Chinese)
[22] G F Chen and X M Deng ldquoDynamic observation adult citruspsyllid quantity live through the winter in spring and winterrdquoSouth China Fruits vol 39 no 4 pp 36ndash38 2010 (Chinese)
[23] XMDeng G F Chen et al ldquoThe newly process of Huanglong-bing in citrusrdquo Guangxi Horticulture vol 17 no 3 pp 49ndash512006
[24] R G drsquoA Vilamiu S Ternes B A Guilherme et al ldquoA modelfor Huanglongbing spread between citrus plants includingdelay times and human interventionrdquo in Proceedings of theInternational Conference of Numerical Analysis and AppliedMathematics (ICNAAM rsquo12) vol 1479 pp 2315ndash2319 2012
Table 1 Parameter definitions and values used for numerical simulations of the Huanglongbing model
Parameter Definition Average value Unit ReferenceΛ The recruitment rate of citrus mdash monthminus1 Estimate1205731
Infected rate of citrus mdash monthminus1 Estimate1205831
Nature death rate of citrus 000275ndash0004167 monthminus1 [20]119889 Disease induced death rate of citrus 0016667ndash0027775 monthminus1 [21]119863 Birth rate of psyllid 378327ndash33526137 monthminus1 [20 22]1205732
Infected rate of psyllid mdash monthminus1 Estimate1205832
Nature death rate of psyllid 01169825ndash095052 monthminus1 [23]119898 Max abundance of psyllid per citrus 120ndash1000 mdash [24]
Table 2 Parameter functions for model (1) according to the values of Table 1
Parameter functions Value Reference
1205731(119905) 00042925 + 0003543 cos (212058711990512) Estimate
1205831(119905) 00034585 + 00007085 cos (212058711990512) [20]
119889 (119905) 0022221 + 0005554 cos (212058711990512) [21]
119863 (119905) 186547035 + 148714335 cos (212058711990512) [20 22]
1205732(119905) 0008779171 + 0004838437 cos (212058711990512) Estimate
1205832(119905) 053375125 + 041676875 cos (212058711990512) [23]
119887 (119905) = 119863 (119905) minus 1205832(119905) 18120952 + 1445466475 cos (212058711990512) [20 22 23]
119898 560 [24]
Consider the linear system
119889119868ℎ (119905)
119889119905= 1205731 (119905) (119878
lowast
ℎ(119905) minus 120578) 119868V (119905) minus (1205831 (119905) + 119889 (119905)) 119868ℎ (119905)
119889119868V (119905)
119889119905= 1205732 (119905) (119878
lowast
V (119905) minus 120578) 119868ℎ (119905) minus 1205832 (119905) 119868V (119905)
(38)
By Lemma 1 and the standard comparison principle we havethat there exists a positive120596-periodic function V
2(119905) such that
119869(119905) = exp(1199012119905)V2(119905) is a solution of System (38) where 119869(119905) =
(119868ℎ(119905) 119868V(119905))
119879 and
1199012=1
120596ln 119903 (Φ
119865minus119881minus119872120578
(120596)) (39)
It follows from 119903(Φ119865minus119881minus119872
120578
(120596)) gt 1 that 1199012gt 0 and 119869(119905) rarr
+infin as 119905 rarr +infin Applying the comparison principle [18] weknow that 119868
ℎ(119905) rarr +infin and 119868V(119905) rarr +infin as 119905 rarr +infin This
is a contradictionThus we have proved that (32) holds and119875is weakly uniformly persistent with respect to (119883
0 1205971198830)
According to the results of Lemma 7 we can easily obtainthat119875 has a global attractor119875
0 It is easy to obtain that119875
0is an
isolated invariant set in119883 and119882119904(1198750)cap1198830= 0We know that
1198750is acyclic in119872
120597and every solution in119872
120597converges to 119875
0
According to Zhao [19] we have that119875 is uniformly persistentwith respect to (119883
0 1205971198830) This implies that the solution of
(1) is uniformly persistent with respect to (1198830 1205971198830) Thus we
have that there exists a 120598 gt 0 such that lim inf119905rarr+infin
119868ℎ(119905) ge 120598
lim inf119905rarr+infin
119868V(119905) ge 120598
5 Numerical Simulationsand Sensitivity Analysis
In this section we will make numerical simulations bymeansof Matlab 71 to support our theoretical results to predictthe trend of the disease and to explore some control andprevention measures Numerical values of parameters ofsystem (1) are given in Table 1 (most of the data are taken fromthe literatures ([20ndash24]))
According to the periodicity of System (1) and Table 1 weset 1205831(119905) = 120572
0
1+ 1205720
2cos(212058711990512) where 1205720
2= (0004167 minus
000275)2 = 00007085 and 12057201= 000275 + 120572
0
2= 00034585
By the similar method we can obtain the other parameterfunctions of model (1) (see Table 2) For the simulations thatfollows we apply the parameters in Table 2 unless otherwisestated
ChooseΛ(119905) = 000265+000235 cos(212058711990512)Then fromLemma 5 we can compute 119877
0= 09844 lt 1 by means of
Matlab 71 FromTheorem 8 we obtain that the infected citruspopulation 119868
ℎ(119905) and the infected psyllid population 119868V(119905) of
system (1) are extinct (see Figures 1 and 2)Choose Λ(119905) = 0005 + 00035 cos(212058711990512) Then from
Lemma 5 we obtain that 1198770= 18342 gt 1 From Theorem 9
we have that the infected citrus population 119868ℎ(119905) and the
infected psyllid population 119868V(119905) of System (1) are permanence(see Figures 3 and 4)
From the formulae for 1198770 we can predict the general
tendency of the epidemic in a long term according to thecurrent situation which is presented in Figures 1 2 3 and 4From the first two figures we know that the epidemic of
Abstract and Applied Analysis 7
002
004
006
008
01
012
0 500 1000 1500 2000 25000
t (month)
R0 = 09844
Ih(t)
(a)
0 100 200 300 400 5000
002
004
006
008
01
012
t (month)
R0 = 09844
Ih(t)
(b)
Figure 1 Graphs of numerical simulations of (1) showings the tendency of the infected citrus population (a) 119905 isin [0 2500] (b) 119905 isin [0 500]
R0 = 09844
0
02
04
06
08
1
12
14
Iv(t)
0 500 1000 1500 2000 25000
t (month)
(a)
02
04
06
08
1
12
14
R0 = 09844
Iv(t)
0 100 200 300 400 5000
t (month)
(b)
Figure 2 It is similar to Figure 1
Huanglongbing can be rising in a short time but cannot beoutbreak with the current prevention and control measuresFrom Figures 3 and 4 we can see that the epidemic ofHuanglongbing dropped heavily after 100 months whilethere is still tendency to a stable periodic solution in a longtime
Next we perform some sensitivity analysis to determinethe influence 119877
0on the parameters Λ(119905) 120573
1(119905) and 120573
2(119905)
We choose function Λ(119905) = Λ01+ Λ0
2cos(212058711990512) where
Λ0
1 Λ02denote the average and amplitude values of Λ(119905)
respectively and Λ0
1= (112) int
12
0Λ(119905)119889119905 From Figure 5
we can observe that the blue line is linear relation between1198770and Λ
0
2 and 119877
0increases as Λ0
2increases The red
curve reflects the influence of the average value of Λ(119905) on1198770 Figure 5 shows that Λ0
1is more sensitive than Λ
0
2on
the basic reproduction number 1198770 Therefore in the real
world decreasing the average recruitment rate of citrus is thevaluable way to control Huanglongbing
Now we consider the combined influence of 1205731(119905) and
1205732(119905) on 119877
0 Set Λ(119905) = 00027 + 000235 cos(212058711990512)
1205731(119905) = 119886
1+ 1198871cos(212058711990512) and 120573
2(119905) = 119886
2+ 1198872cos(212058711990512)
Moreover we know that 1198861
= (112) int12
01205731(119905)119889119905 and
1198862= (112) int
12
01205732(119905)119889119905 Other parameters can be seen in
Table 2
Case (I) We fix 1198871= 0003543 and 119887
2= 0004838437
and let 1198861vary from 000001 to 0015 and 119886
2from 000001
to 002 For this case it is interesting to examine how theaverage values of adequate contact rate 120573
1(119905) and 120573
2(119905) affect
the basic reproduction number 1198770 Numerical results shown
8 Abstract and Applied Analysis
R0 = 18342
006
008
01
012
014
016
018
02Ih(t)
0 500 1000 1500 2000 2500t (month)
(a)
006
008
01
012
014
016
018
02
R0 = 18342
Ih(t)
0 100 200 300 400 500t (month)
(b)
Figure 3 The figures show that the infected citrus population is permanence (a) 119905 isin [0 2500] (b) 119905 isin [0 500]
02
04
06
08
1
12
14
16
18
2
R0 = 18342
0 500 1000 1500 2000 25000
t (month)
Iv(t)
(a)
R0 = 18342
02
04
06
08
1
12
14
16
18
2Iv(t)
0 100 200 300 400 5000
t (month)
(b)
Figure 4 It is similar to Figure 3
in Figure 6 imply that the basic reproduction number1198770may
be less than 1 when 1198861or 1198862is small enough And the results
also imply that 1198770increases as 119886
1and 1198862increase Further we
can observe that from Figure 6(i)the smaller the values of 1198861
or 1198862are the more sensitive 119877
0is (ii) increasing 119886
2may be
more sensitive for 1198770when 119886
1is fixed (iii) increasing 119886
1may
be more sensitive for 1198770when 119886
2is fixed
Case (II) We fix 1198861= 00042925 and 119886
2= 000877917 and
let 1198871vary from 0000001 to 0005 and 119887
2from 0000002 to
0006Then we obtain the result of numerical simulation andit is shown in Figure 7 Obviously Figure 7 shows that 119877
0is
linearly related to both 1198871and 119887
2with the pattern that 119877
0
decreases to a relatively small value (less than 1) only when1198871and 1198872are very small
By the above graphs of the basic reproduction number1198770on the average values of recruitment rate of citrus Λ(119905)
and adequate contact rate 1205731(119905) 1205732(119905) we know that the basic
reproduction number 1198770is a monotonic increasing function
by the average values From the sensitivity analysis diagramswe observe that 119877
0falls to less than 1 by decreasing the values
of those parameters
6 Conclusion
In this paper we have analyzed a HLB transmission modelwith Logistic growth in periodic environments It is provedthat 119877
0is the threshold for distinguishing the disease extinc-
tion or permanence The disease-free periodic solution is
Abstract and Applied Analysis 9
0 1 2 3 4 502
04
06
08
1
12
14
16
18
2
R0
times10minus3
Λ0
1= 00027
Λ0
2= [0000001 0005]
Λ0
1= [0000001 0005]Λ0
2= 000235
Λ0
1or Λ0
2
Figure 5 The graph shows the sensitivity of the basic reproductionnumber 119877
0to the changes of Λ(119905)
00005
0010015
000050010015
0020
05
1
15
2
25
3
R0
a1a2
Figure 6 The graph of 1198770in terms of 119886
1and 119886
2
globally asymptotically stable and the disease dies out when1198770lt 1 When 119877
0gt 1 the disease persists
The numerical simulations shown in Figure 5 show thatthere are some parameter ranges of Λ
1and Λ
2such that the
threshold parameter 1198770is smaller than 1 It indicates a useful
way to eradicate Huanglongbing by limiting the recruitmentof citrus including the average value and amplitude ofrecruitment function
The results shown in Figure 6 (Figure 7) show that if theamplitudes of infected functions 119887
1 1198872(the average infected
rate 1198861 1198862) are fixed we can control the infection of citrus
and psyllid by limiting the average infected rates 1198861 1198862(the
amplitudes of infected functions 1198871 1198872)
According to the above theoretical analysis andnumericalsimulations we can conclude that the recruitment of citrusand the infection of citrus and psyllid have significanteffects on Huanglongbing transmission In order to preventthe epidemic disease from generating endemic making anappropriate reduction of the recruitment rate of citrus and
01
23
45
02
46
09
1
11
12
13
b1b2
R0
times10minus3
times10minus3
Figure 7 The graph of 1198770in terms of 119887
1and 1198872
decreasing the contact rate between psyllid and the citrus areeffective measures to control Huanglongbing
Disclosure
The paper is approved by all authors for publication Theauthors would like to declare that the work described wasoriginal research that has not been published previously andnot under consideration for publication elsewhere
Conflict of Interests
No conflict of interests exists in the submission of this paper
Acknowledgments
The research has been supported by the Natural ScienceFoundation of China (11261004) the Natural Science Foun-dation of Jiangxi Province (20122BAB211010) the Scienceand Technology Plan Projects of Jiangxi Provincial EducationDepartment (GJJ13646) and the Postgraduate InnovationFund of Jiangxi Province (YC2012-S121)
References
[1] P Christou and R M Twyman ldquoThe potential of geneticallyenhanced plants to address food insecurityrdquo Nutrition ResearchReviews vol 17 no 1 pp 23ndash42 2004
[2] FAO The State of Food Insecurity in the World (SOFI) FAORome Italy 2000 httpwwwfaoorgFOCUSESOFI00sofi001-ehtm
[3] C James ldquoGlobal food securityrdquo in International Congress ofPlant Pathology Pittsburgh Pa USA August 1998
[4] J M Bove ldquoHuanglongbing a destructive newly-emergingcentury-old disease of citrusrdquo Journal of Plant Pathology vol88 no 1 pp 7ndash37 2006
[5] S E Halbert and K L Manjunath ldquoAsian citrus psyllids (Stern-orrhyncha Psyllidae) and greening disease of citrus a literaturereview and assessment of risk in Floridardquo Florida Entomologistvol 87 no 3 pp 330ndash353 2004
10 Abstract and Applied Analysis
[6] S Parnell T R Gottwald C A Gilligan N J Cunniffe and FVan Den Bosch ldquoThe effect of landscape pattern on the optimaleradication zone of an invading epidemicrdquo Phytopathology vol100 no 7 pp 638ndash644 2010
[7] R FMizell III C Tipping P C Andersen B V BrodbeckW BHunter and T Northfield ldquoBehavioral model for Homalodiscavitripennis (Hemiptera Cicadellidae) optimization of hostplant utilization andmanagement implicationsrdquo EnvironmentalEntomology vol 37 no 5 pp 1049ndash1062 2008
[8] G A Braga S Ternes et al ldquoModelagem Matematica daDinamica TemporaldoHLB emCitrosrdquo in Proceedings of the 8thCongresso Brasileiro de Agroinformatica Bento Goncalves 2011
[9] DGHall andMGHentz ldquoSeasonal flight activity by theAsiancitrus psyllid in east central Floridardquo Entomologia et Applicatavol 139 no 1 pp 75ndash85 2011
[10] X Song and A U Neumann ldquoGlobal stability and periodicsolution of the viral dynamicsrdquo Journal ofMathematical Analysisand Applications vol 329 no 1 pp 281ndash297 2007
[11] K Wang Z Teng and H Jiang ldquoOn the permanence forn-species non-autonomous Lotka-Volterra competitive systemwith infinite delays and feedback controlsrdquo International Journalof Biomathematics vol 1 no 1 pp 29ndash43 2008
[12] F Zhang and X-Q Zhao ldquoA periodic epidemic model in apatchy environmentrdquo Journal of Mathematical Analysis andApplications vol 325 no 1 pp 496ndash516 2007
[13] T Zhang and Z Teng ldquoOn a nonautonomous SEIRS model inepidemiologyrdquo Bulletin of Mathematical Biology vol 69 no 8pp 2537ndash2559 2007
[14] Z Teng and Z Li ldquoPermanence and asymptotic behavior of thetv-species nonautonomous lotka-volterra competitive systemsrdquoComputers and Mathematics with Applications vol 39 no 7-8pp 107ndash116 2000
[15] W Wang and X-Q Zhao ldquoThreshold dynamics for compart-mental epidemic models in periodic environmentsrdquo Journal ofDynamics and Differential Equations vol 20 no 3 pp 699ndash7172008
[16] Y Nakata and T Kuniya ldquoGlobal dynamics of a class ofSEIRS epidemic models in a periodic environmentrdquo Journal ofMathematical Analysis and Applications vol 363 no 1 pp 230ndash237 2010
[17] Y Nakata Permanence and Global Asymptotic Stability ForPopulation Models in Mathematical Biology Waseda UniversityTokyo Japan 2010
[18] H Smith and P Waltman The Theory of the Chemostat Cam-bridge University Press Cambridge Mass USA 1995
[19] X ZhaoDynamical Systems in Population Biology Spring NewYork NY USA 2003
[20] X M Deng ldquoFormming process and basis and technologicalpoints of the theory emphasis on control citrus psylla for inte-grated control Huanglongbingrdquo Chinese Agricultural ScienceBulletin vol 25 no 23 pp 358ndash363 2009 (Chinese)
[21] T Li C Z Cheng et al ldquoDetection of the bearing rate ofliberobacter asiaticum in citrus psylla and its host plantrdquo ActaAgriculturae Universitatis Jiangxiensis vol 29 no 5 pp 743ndash745 2007 (Chinese)
[22] G F Chen and X M Deng ldquoDynamic observation adult citruspsyllid quantity live through the winter in spring and winterrdquoSouth China Fruits vol 39 no 4 pp 36ndash38 2010 (Chinese)
[23] XMDeng G F Chen et al ldquoThe newly process of Huanglong-bing in citrusrdquo Guangxi Horticulture vol 17 no 3 pp 49ndash512006
[24] R G drsquoA Vilamiu S Ternes B A Guilherme et al ldquoA modelfor Huanglongbing spread between citrus plants includingdelay times and human interventionrdquo in Proceedings of theInternational Conference of Numerical Analysis and AppliedMathematics (ICNAAM rsquo12) vol 1479 pp 2315ndash2319 2012
Figure 1 Graphs of numerical simulations of (1) showings the tendency of the infected citrus population (a) 119905 isin [0 2500] (b) 119905 isin [0 500]
R0 = 09844
0
02
04
06
08
1
12
14
Iv(t)
0 500 1000 1500 2000 25000
t (month)
(a)
02
04
06
08
1
12
14
R0 = 09844
Iv(t)
0 100 200 300 400 5000
t (month)
(b)
Figure 2 It is similar to Figure 1
Huanglongbing can be rising in a short time but cannot beoutbreak with the current prevention and control measuresFrom Figures 3 and 4 we can see that the epidemic ofHuanglongbing dropped heavily after 100 months whilethere is still tendency to a stable periodic solution in a longtime
Next we perform some sensitivity analysis to determinethe influence 119877
0on the parameters Λ(119905) 120573
1(119905) and 120573
2(119905)
We choose function Λ(119905) = Λ01+ Λ0
2cos(212058711990512) where
Λ0
1 Λ02denote the average and amplitude values of Λ(119905)
respectively and Λ0
1= (112) int
12
0Λ(119905)119889119905 From Figure 5
we can observe that the blue line is linear relation between1198770and Λ
0
2 and 119877
0increases as Λ0
2increases The red
curve reflects the influence of the average value of Λ(119905) on1198770 Figure 5 shows that Λ0
1is more sensitive than Λ
0
2on
the basic reproduction number 1198770 Therefore in the real
world decreasing the average recruitment rate of citrus is thevaluable way to control Huanglongbing
Now we consider the combined influence of 1205731(119905) and
1205732(119905) on 119877
0 Set Λ(119905) = 00027 + 000235 cos(212058711990512)
1205731(119905) = 119886
1+ 1198871cos(212058711990512) and 120573
2(119905) = 119886
2+ 1198872cos(212058711990512)
Moreover we know that 1198861
= (112) int12
01205731(119905)119889119905 and
1198862= (112) int
12
01205732(119905)119889119905 Other parameters can be seen in
Table 2
Case (I) We fix 1198871= 0003543 and 119887
2= 0004838437
and let 1198861vary from 000001 to 0015 and 119886
2from 000001
to 002 For this case it is interesting to examine how theaverage values of adequate contact rate 120573
1(119905) and 120573
2(119905) affect
the basic reproduction number 1198770 Numerical results shown
8 Abstract and Applied Analysis
R0 = 18342
006
008
01
012
014
016
018
02Ih(t)
0 500 1000 1500 2000 2500t (month)
(a)
006
008
01
012
014
016
018
02
R0 = 18342
Ih(t)
0 100 200 300 400 500t (month)
(b)
Figure 3 The figures show that the infected citrus population is permanence (a) 119905 isin [0 2500] (b) 119905 isin [0 500]
02
04
06
08
1
12
14
16
18
2
R0 = 18342
0 500 1000 1500 2000 25000
t (month)
Iv(t)
(a)
R0 = 18342
02
04
06
08
1
12
14
16
18
2Iv(t)
0 100 200 300 400 5000
t (month)
(b)
Figure 4 It is similar to Figure 3
in Figure 6 imply that the basic reproduction number1198770may
be less than 1 when 1198861or 1198862is small enough And the results
also imply that 1198770increases as 119886
1and 1198862increase Further we
can observe that from Figure 6(i)the smaller the values of 1198861
or 1198862are the more sensitive 119877
0is (ii) increasing 119886
2may be
more sensitive for 1198770when 119886
1is fixed (iii) increasing 119886
1may
be more sensitive for 1198770when 119886
2is fixed
Case (II) We fix 1198861= 00042925 and 119886
2= 000877917 and
let 1198871vary from 0000001 to 0005 and 119887
2from 0000002 to
0006Then we obtain the result of numerical simulation andit is shown in Figure 7 Obviously Figure 7 shows that 119877
0is
linearly related to both 1198871and 119887
2with the pattern that 119877
0
decreases to a relatively small value (less than 1) only when1198871and 1198872are very small
By the above graphs of the basic reproduction number1198770on the average values of recruitment rate of citrus Λ(119905)
and adequate contact rate 1205731(119905) 1205732(119905) we know that the basic
reproduction number 1198770is a monotonic increasing function
by the average values From the sensitivity analysis diagramswe observe that 119877
0falls to less than 1 by decreasing the values
of those parameters
6 Conclusion
In this paper we have analyzed a HLB transmission modelwith Logistic growth in periodic environments It is provedthat 119877
0is the threshold for distinguishing the disease extinc-
tion or permanence The disease-free periodic solution is
Abstract and Applied Analysis 9
0 1 2 3 4 502
04
06
08
1
12
14
16
18
2
R0
times10minus3
Λ0
1= 00027
Λ0
2= [0000001 0005]
Λ0
1= [0000001 0005]Λ0
2= 000235
Λ0
1or Λ0
2
Figure 5 The graph shows the sensitivity of the basic reproductionnumber 119877
0to the changes of Λ(119905)
00005
0010015
000050010015
0020
05
1
15
2
25
3
R0
a1a2
Figure 6 The graph of 1198770in terms of 119886
1and 119886
2
globally asymptotically stable and the disease dies out when1198770lt 1 When 119877
0gt 1 the disease persists
The numerical simulations shown in Figure 5 show thatthere are some parameter ranges of Λ
1and Λ
2such that the
threshold parameter 1198770is smaller than 1 It indicates a useful
way to eradicate Huanglongbing by limiting the recruitmentof citrus including the average value and amplitude ofrecruitment function
The results shown in Figure 6 (Figure 7) show that if theamplitudes of infected functions 119887
1 1198872(the average infected
rate 1198861 1198862) are fixed we can control the infection of citrus
and psyllid by limiting the average infected rates 1198861 1198862(the
amplitudes of infected functions 1198871 1198872)
According to the above theoretical analysis andnumericalsimulations we can conclude that the recruitment of citrusand the infection of citrus and psyllid have significanteffects on Huanglongbing transmission In order to preventthe epidemic disease from generating endemic making anappropriate reduction of the recruitment rate of citrus and
01
23
45
02
46
09
1
11
12
13
b1b2
R0
times10minus3
times10minus3
Figure 7 The graph of 1198770in terms of 119887
1and 1198872
decreasing the contact rate between psyllid and the citrus areeffective measures to control Huanglongbing
Disclosure
The paper is approved by all authors for publication Theauthors would like to declare that the work described wasoriginal research that has not been published previously andnot under consideration for publication elsewhere
Conflict of Interests
No conflict of interests exists in the submission of this paper
Acknowledgments
The research has been supported by the Natural ScienceFoundation of China (11261004) the Natural Science Foun-dation of Jiangxi Province (20122BAB211010) the Scienceand Technology Plan Projects of Jiangxi Provincial EducationDepartment (GJJ13646) and the Postgraduate InnovationFund of Jiangxi Province (YC2012-S121)
References
[1] P Christou and R M Twyman ldquoThe potential of geneticallyenhanced plants to address food insecurityrdquo Nutrition ResearchReviews vol 17 no 1 pp 23ndash42 2004
[2] FAO The State of Food Insecurity in the World (SOFI) FAORome Italy 2000 httpwwwfaoorgFOCUSESOFI00sofi001-ehtm
[3] C James ldquoGlobal food securityrdquo in International Congress ofPlant Pathology Pittsburgh Pa USA August 1998
[4] J M Bove ldquoHuanglongbing a destructive newly-emergingcentury-old disease of citrusrdquo Journal of Plant Pathology vol88 no 1 pp 7ndash37 2006
[5] S E Halbert and K L Manjunath ldquoAsian citrus psyllids (Stern-orrhyncha Psyllidae) and greening disease of citrus a literaturereview and assessment of risk in Floridardquo Florida Entomologistvol 87 no 3 pp 330ndash353 2004
10 Abstract and Applied Analysis
[6] S Parnell T R Gottwald C A Gilligan N J Cunniffe and FVan Den Bosch ldquoThe effect of landscape pattern on the optimaleradication zone of an invading epidemicrdquo Phytopathology vol100 no 7 pp 638ndash644 2010
[7] R FMizell III C Tipping P C Andersen B V BrodbeckW BHunter and T Northfield ldquoBehavioral model for Homalodiscavitripennis (Hemiptera Cicadellidae) optimization of hostplant utilization andmanagement implicationsrdquo EnvironmentalEntomology vol 37 no 5 pp 1049ndash1062 2008
[8] G A Braga S Ternes et al ldquoModelagem Matematica daDinamica TemporaldoHLB emCitrosrdquo in Proceedings of the 8thCongresso Brasileiro de Agroinformatica Bento Goncalves 2011
[9] DGHall andMGHentz ldquoSeasonal flight activity by theAsiancitrus psyllid in east central Floridardquo Entomologia et Applicatavol 139 no 1 pp 75ndash85 2011
[10] X Song and A U Neumann ldquoGlobal stability and periodicsolution of the viral dynamicsrdquo Journal ofMathematical Analysisand Applications vol 329 no 1 pp 281ndash297 2007
[11] K Wang Z Teng and H Jiang ldquoOn the permanence forn-species non-autonomous Lotka-Volterra competitive systemwith infinite delays and feedback controlsrdquo International Journalof Biomathematics vol 1 no 1 pp 29ndash43 2008
[12] F Zhang and X-Q Zhao ldquoA periodic epidemic model in apatchy environmentrdquo Journal of Mathematical Analysis andApplications vol 325 no 1 pp 496ndash516 2007
[13] T Zhang and Z Teng ldquoOn a nonautonomous SEIRS model inepidemiologyrdquo Bulletin of Mathematical Biology vol 69 no 8pp 2537ndash2559 2007
[14] Z Teng and Z Li ldquoPermanence and asymptotic behavior of thetv-species nonautonomous lotka-volterra competitive systemsrdquoComputers and Mathematics with Applications vol 39 no 7-8pp 107ndash116 2000
[15] W Wang and X-Q Zhao ldquoThreshold dynamics for compart-mental epidemic models in periodic environmentsrdquo Journal ofDynamics and Differential Equations vol 20 no 3 pp 699ndash7172008
[16] Y Nakata and T Kuniya ldquoGlobal dynamics of a class ofSEIRS epidemic models in a periodic environmentrdquo Journal ofMathematical Analysis and Applications vol 363 no 1 pp 230ndash237 2010
[17] Y Nakata Permanence and Global Asymptotic Stability ForPopulation Models in Mathematical Biology Waseda UniversityTokyo Japan 2010
[18] H Smith and P Waltman The Theory of the Chemostat Cam-bridge University Press Cambridge Mass USA 1995
[19] X ZhaoDynamical Systems in Population Biology Spring NewYork NY USA 2003
[20] X M Deng ldquoFormming process and basis and technologicalpoints of the theory emphasis on control citrus psylla for inte-grated control Huanglongbingrdquo Chinese Agricultural ScienceBulletin vol 25 no 23 pp 358ndash363 2009 (Chinese)
[21] T Li C Z Cheng et al ldquoDetection of the bearing rate ofliberobacter asiaticum in citrus psylla and its host plantrdquo ActaAgriculturae Universitatis Jiangxiensis vol 29 no 5 pp 743ndash745 2007 (Chinese)
[22] G F Chen and X M Deng ldquoDynamic observation adult citruspsyllid quantity live through the winter in spring and winterrdquoSouth China Fruits vol 39 no 4 pp 36ndash38 2010 (Chinese)
[23] XMDeng G F Chen et al ldquoThe newly process of Huanglong-bing in citrusrdquo Guangxi Horticulture vol 17 no 3 pp 49ndash512006
[24] R G drsquoA Vilamiu S Ternes B A Guilherme et al ldquoA modelfor Huanglongbing spread between citrus plants includingdelay times and human interventionrdquo in Proceedings of theInternational Conference of Numerical Analysis and AppliedMathematics (ICNAAM rsquo12) vol 1479 pp 2315ndash2319 2012
Figure 3 The figures show that the infected citrus population is permanence (a) 119905 isin [0 2500] (b) 119905 isin [0 500]
02
04
06
08
1
12
14
16
18
2
R0 = 18342
0 500 1000 1500 2000 25000
t (month)
Iv(t)
(a)
R0 = 18342
02
04
06
08
1
12
14
16
18
2Iv(t)
0 100 200 300 400 5000
t (month)
(b)
Figure 4 It is similar to Figure 3
in Figure 6 imply that the basic reproduction number1198770may
be less than 1 when 1198861or 1198862is small enough And the results
also imply that 1198770increases as 119886
1and 1198862increase Further we
can observe that from Figure 6(i)the smaller the values of 1198861
or 1198862are the more sensitive 119877
0is (ii) increasing 119886
2may be
more sensitive for 1198770when 119886
1is fixed (iii) increasing 119886
1may
be more sensitive for 1198770when 119886
2is fixed
Case (II) We fix 1198861= 00042925 and 119886
2= 000877917 and
let 1198871vary from 0000001 to 0005 and 119887
2from 0000002 to
0006Then we obtain the result of numerical simulation andit is shown in Figure 7 Obviously Figure 7 shows that 119877
0is
linearly related to both 1198871and 119887
2with the pattern that 119877
0
decreases to a relatively small value (less than 1) only when1198871and 1198872are very small
By the above graphs of the basic reproduction number1198770on the average values of recruitment rate of citrus Λ(119905)
and adequate contact rate 1205731(119905) 1205732(119905) we know that the basic
reproduction number 1198770is a monotonic increasing function
by the average values From the sensitivity analysis diagramswe observe that 119877
0falls to less than 1 by decreasing the values
of those parameters
6 Conclusion
In this paper we have analyzed a HLB transmission modelwith Logistic growth in periodic environments It is provedthat 119877
0is the threshold for distinguishing the disease extinc-
tion or permanence The disease-free periodic solution is
Abstract and Applied Analysis 9
0 1 2 3 4 502
04
06
08
1
12
14
16
18
2
R0
times10minus3
Λ0
1= 00027
Λ0
2= [0000001 0005]
Λ0
1= [0000001 0005]Λ0
2= 000235
Λ0
1or Λ0
2
Figure 5 The graph shows the sensitivity of the basic reproductionnumber 119877
0to the changes of Λ(119905)
00005
0010015
000050010015
0020
05
1
15
2
25
3
R0
a1a2
Figure 6 The graph of 1198770in terms of 119886
1and 119886
2
globally asymptotically stable and the disease dies out when1198770lt 1 When 119877
0gt 1 the disease persists
The numerical simulations shown in Figure 5 show thatthere are some parameter ranges of Λ
1and Λ
2such that the
threshold parameter 1198770is smaller than 1 It indicates a useful
way to eradicate Huanglongbing by limiting the recruitmentof citrus including the average value and amplitude ofrecruitment function
The results shown in Figure 6 (Figure 7) show that if theamplitudes of infected functions 119887
1 1198872(the average infected
rate 1198861 1198862) are fixed we can control the infection of citrus
and psyllid by limiting the average infected rates 1198861 1198862(the
amplitudes of infected functions 1198871 1198872)
According to the above theoretical analysis andnumericalsimulations we can conclude that the recruitment of citrusand the infection of citrus and psyllid have significanteffects on Huanglongbing transmission In order to preventthe epidemic disease from generating endemic making anappropriate reduction of the recruitment rate of citrus and
01
23
45
02
46
09
1
11
12
13
b1b2
R0
times10minus3
times10minus3
Figure 7 The graph of 1198770in terms of 119887
1and 1198872
decreasing the contact rate between psyllid and the citrus areeffective measures to control Huanglongbing
Disclosure
The paper is approved by all authors for publication Theauthors would like to declare that the work described wasoriginal research that has not been published previously andnot under consideration for publication elsewhere
Conflict of Interests
No conflict of interests exists in the submission of this paper
Acknowledgments
The research has been supported by the Natural ScienceFoundation of China (11261004) the Natural Science Foun-dation of Jiangxi Province (20122BAB211010) the Scienceand Technology Plan Projects of Jiangxi Provincial EducationDepartment (GJJ13646) and the Postgraduate InnovationFund of Jiangxi Province (YC2012-S121)
References
[1] P Christou and R M Twyman ldquoThe potential of geneticallyenhanced plants to address food insecurityrdquo Nutrition ResearchReviews vol 17 no 1 pp 23ndash42 2004
[2] FAO The State of Food Insecurity in the World (SOFI) FAORome Italy 2000 httpwwwfaoorgFOCUSESOFI00sofi001-ehtm
[3] C James ldquoGlobal food securityrdquo in International Congress ofPlant Pathology Pittsburgh Pa USA August 1998
[4] J M Bove ldquoHuanglongbing a destructive newly-emergingcentury-old disease of citrusrdquo Journal of Plant Pathology vol88 no 1 pp 7ndash37 2006
[5] S E Halbert and K L Manjunath ldquoAsian citrus psyllids (Stern-orrhyncha Psyllidae) and greening disease of citrus a literaturereview and assessment of risk in Floridardquo Florida Entomologistvol 87 no 3 pp 330ndash353 2004
10 Abstract and Applied Analysis
[6] S Parnell T R Gottwald C A Gilligan N J Cunniffe and FVan Den Bosch ldquoThe effect of landscape pattern on the optimaleradication zone of an invading epidemicrdquo Phytopathology vol100 no 7 pp 638ndash644 2010
[7] R FMizell III C Tipping P C Andersen B V BrodbeckW BHunter and T Northfield ldquoBehavioral model for Homalodiscavitripennis (Hemiptera Cicadellidae) optimization of hostplant utilization andmanagement implicationsrdquo EnvironmentalEntomology vol 37 no 5 pp 1049ndash1062 2008
[8] G A Braga S Ternes et al ldquoModelagem Matematica daDinamica TemporaldoHLB emCitrosrdquo in Proceedings of the 8thCongresso Brasileiro de Agroinformatica Bento Goncalves 2011
[9] DGHall andMGHentz ldquoSeasonal flight activity by theAsiancitrus psyllid in east central Floridardquo Entomologia et Applicatavol 139 no 1 pp 75ndash85 2011
[10] X Song and A U Neumann ldquoGlobal stability and periodicsolution of the viral dynamicsrdquo Journal ofMathematical Analysisand Applications vol 329 no 1 pp 281ndash297 2007
[11] K Wang Z Teng and H Jiang ldquoOn the permanence forn-species non-autonomous Lotka-Volterra competitive systemwith infinite delays and feedback controlsrdquo International Journalof Biomathematics vol 1 no 1 pp 29ndash43 2008
[12] F Zhang and X-Q Zhao ldquoA periodic epidemic model in apatchy environmentrdquo Journal of Mathematical Analysis andApplications vol 325 no 1 pp 496ndash516 2007
[13] T Zhang and Z Teng ldquoOn a nonautonomous SEIRS model inepidemiologyrdquo Bulletin of Mathematical Biology vol 69 no 8pp 2537ndash2559 2007
[14] Z Teng and Z Li ldquoPermanence and asymptotic behavior of thetv-species nonautonomous lotka-volterra competitive systemsrdquoComputers and Mathematics with Applications vol 39 no 7-8pp 107ndash116 2000
[15] W Wang and X-Q Zhao ldquoThreshold dynamics for compart-mental epidemic models in periodic environmentsrdquo Journal ofDynamics and Differential Equations vol 20 no 3 pp 699ndash7172008
[16] Y Nakata and T Kuniya ldquoGlobal dynamics of a class ofSEIRS epidemic models in a periodic environmentrdquo Journal ofMathematical Analysis and Applications vol 363 no 1 pp 230ndash237 2010
[17] Y Nakata Permanence and Global Asymptotic Stability ForPopulation Models in Mathematical Biology Waseda UniversityTokyo Japan 2010
[18] H Smith and P Waltman The Theory of the Chemostat Cam-bridge University Press Cambridge Mass USA 1995
[19] X ZhaoDynamical Systems in Population Biology Spring NewYork NY USA 2003
[20] X M Deng ldquoFormming process and basis and technologicalpoints of the theory emphasis on control citrus psylla for inte-grated control Huanglongbingrdquo Chinese Agricultural ScienceBulletin vol 25 no 23 pp 358ndash363 2009 (Chinese)
[21] T Li C Z Cheng et al ldquoDetection of the bearing rate ofliberobacter asiaticum in citrus psylla and its host plantrdquo ActaAgriculturae Universitatis Jiangxiensis vol 29 no 5 pp 743ndash745 2007 (Chinese)
[22] G F Chen and X M Deng ldquoDynamic observation adult citruspsyllid quantity live through the winter in spring and winterrdquoSouth China Fruits vol 39 no 4 pp 36ndash38 2010 (Chinese)
[23] XMDeng G F Chen et al ldquoThe newly process of Huanglong-bing in citrusrdquo Guangxi Horticulture vol 17 no 3 pp 49ndash512006
[24] R G drsquoA Vilamiu S Ternes B A Guilherme et al ldquoA modelfor Huanglongbing spread between citrus plants includingdelay times and human interventionrdquo in Proceedings of theInternational Conference of Numerical Analysis and AppliedMathematics (ICNAAM rsquo12) vol 1479 pp 2315ndash2319 2012
Figure 5 The graph shows the sensitivity of the basic reproductionnumber 119877
0to the changes of Λ(119905)
00005
0010015
000050010015
0020
05
1
15
2
25
3
R0
a1a2
Figure 6 The graph of 1198770in terms of 119886
1and 119886
2
globally asymptotically stable and the disease dies out when1198770lt 1 When 119877
0gt 1 the disease persists
The numerical simulations shown in Figure 5 show thatthere are some parameter ranges of Λ
1and Λ
2such that the
threshold parameter 1198770is smaller than 1 It indicates a useful
way to eradicate Huanglongbing by limiting the recruitmentof citrus including the average value and amplitude ofrecruitment function
The results shown in Figure 6 (Figure 7) show that if theamplitudes of infected functions 119887
1 1198872(the average infected
rate 1198861 1198862) are fixed we can control the infection of citrus
and psyllid by limiting the average infected rates 1198861 1198862(the
amplitudes of infected functions 1198871 1198872)
According to the above theoretical analysis andnumericalsimulations we can conclude that the recruitment of citrusand the infection of citrus and psyllid have significanteffects on Huanglongbing transmission In order to preventthe epidemic disease from generating endemic making anappropriate reduction of the recruitment rate of citrus and
01
23
45
02
46
09
1
11
12
13
b1b2
R0
times10minus3
times10minus3
Figure 7 The graph of 1198770in terms of 119887
1and 1198872
decreasing the contact rate between psyllid and the citrus areeffective measures to control Huanglongbing
Disclosure
The paper is approved by all authors for publication Theauthors would like to declare that the work described wasoriginal research that has not been published previously andnot under consideration for publication elsewhere
Conflict of Interests
No conflict of interests exists in the submission of this paper
Acknowledgments
The research has been supported by the Natural ScienceFoundation of China (11261004) the Natural Science Foun-dation of Jiangxi Province (20122BAB211010) the Scienceand Technology Plan Projects of Jiangxi Provincial EducationDepartment (GJJ13646) and the Postgraduate InnovationFund of Jiangxi Province (YC2012-S121)
References
[1] P Christou and R M Twyman ldquoThe potential of geneticallyenhanced plants to address food insecurityrdquo Nutrition ResearchReviews vol 17 no 1 pp 23ndash42 2004
[2] FAO The State of Food Insecurity in the World (SOFI) FAORome Italy 2000 httpwwwfaoorgFOCUSESOFI00sofi001-ehtm
[3] C James ldquoGlobal food securityrdquo in International Congress ofPlant Pathology Pittsburgh Pa USA August 1998
[4] J M Bove ldquoHuanglongbing a destructive newly-emergingcentury-old disease of citrusrdquo Journal of Plant Pathology vol88 no 1 pp 7ndash37 2006
[5] S E Halbert and K L Manjunath ldquoAsian citrus psyllids (Stern-orrhyncha Psyllidae) and greening disease of citrus a literaturereview and assessment of risk in Floridardquo Florida Entomologistvol 87 no 3 pp 330ndash353 2004
10 Abstract and Applied Analysis
[6] S Parnell T R Gottwald C A Gilligan N J Cunniffe and FVan Den Bosch ldquoThe effect of landscape pattern on the optimaleradication zone of an invading epidemicrdquo Phytopathology vol100 no 7 pp 638ndash644 2010
[7] R FMizell III C Tipping P C Andersen B V BrodbeckW BHunter and T Northfield ldquoBehavioral model for Homalodiscavitripennis (Hemiptera Cicadellidae) optimization of hostplant utilization andmanagement implicationsrdquo EnvironmentalEntomology vol 37 no 5 pp 1049ndash1062 2008
[8] G A Braga S Ternes et al ldquoModelagem Matematica daDinamica TemporaldoHLB emCitrosrdquo in Proceedings of the 8thCongresso Brasileiro de Agroinformatica Bento Goncalves 2011
[9] DGHall andMGHentz ldquoSeasonal flight activity by theAsiancitrus psyllid in east central Floridardquo Entomologia et Applicatavol 139 no 1 pp 75ndash85 2011
[10] X Song and A U Neumann ldquoGlobal stability and periodicsolution of the viral dynamicsrdquo Journal ofMathematical Analysisand Applications vol 329 no 1 pp 281ndash297 2007
[11] K Wang Z Teng and H Jiang ldquoOn the permanence forn-species non-autonomous Lotka-Volterra competitive systemwith infinite delays and feedback controlsrdquo International Journalof Biomathematics vol 1 no 1 pp 29ndash43 2008
[12] F Zhang and X-Q Zhao ldquoA periodic epidemic model in apatchy environmentrdquo Journal of Mathematical Analysis andApplications vol 325 no 1 pp 496ndash516 2007
[13] T Zhang and Z Teng ldquoOn a nonautonomous SEIRS model inepidemiologyrdquo Bulletin of Mathematical Biology vol 69 no 8pp 2537ndash2559 2007
[14] Z Teng and Z Li ldquoPermanence and asymptotic behavior of thetv-species nonautonomous lotka-volterra competitive systemsrdquoComputers and Mathematics with Applications vol 39 no 7-8pp 107ndash116 2000
[15] W Wang and X-Q Zhao ldquoThreshold dynamics for compart-mental epidemic models in periodic environmentsrdquo Journal ofDynamics and Differential Equations vol 20 no 3 pp 699ndash7172008
[16] Y Nakata and T Kuniya ldquoGlobal dynamics of a class ofSEIRS epidemic models in a periodic environmentrdquo Journal ofMathematical Analysis and Applications vol 363 no 1 pp 230ndash237 2010
[17] Y Nakata Permanence and Global Asymptotic Stability ForPopulation Models in Mathematical Biology Waseda UniversityTokyo Japan 2010
[18] H Smith and P Waltman The Theory of the Chemostat Cam-bridge University Press Cambridge Mass USA 1995
[19] X ZhaoDynamical Systems in Population Biology Spring NewYork NY USA 2003
[20] X M Deng ldquoFormming process and basis and technologicalpoints of the theory emphasis on control citrus psylla for inte-grated control Huanglongbingrdquo Chinese Agricultural ScienceBulletin vol 25 no 23 pp 358ndash363 2009 (Chinese)
[21] T Li C Z Cheng et al ldquoDetection of the bearing rate ofliberobacter asiaticum in citrus psylla and its host plantrdquo ActaAgriculturae Universitatis Jiangxiensis vol 29 no 5 pp 743ndash745 2007 (Chinese)
[22] G F Chen and X M Deng ldquoDynamic observation adult citruspsyllid quantity live through the winter in spring and winterrdquoSouth China Fruits vol 39 no 4 pp 36ndash38 2010 (Chinese)
[23] XMDeng G F Chen et al ldquoThe newly process of Huanglong-bing in citrusrdquo Guangxi Horticulture vol 17 no 3 pp 49ndash512006
[24] R G drsquoA Vilamiu S Ternes B A Guilherme et al ldquoA modelfor Huanglongbing spread between citrus plants includingdelay times and human interventionrdquo in Proceedings of theInternational Conference of Numerical Analysis and AppliedMathematics (ICNAAM rsquo12) vol 1479 pp 2315ndash2319 2012
[6] S Parnell T R Gottwald C A Gilligan N J Cunniffe and FVan Den Bosch ldquoThe effect of landscape pattern on the optimaleradication zone of an invading epidemicrdquo Phytopathology vol100 no 7 pp 638ndash644 2010
[7] R FMizell III C Tipping P C Andersen B V BrodbeckW BHunter and T Northfield ldquoBehavioral model for Homalodiscavitripennis (Hemiptera Cicadellidae) optimization of hostplant utilization andmanagement implicationsrdquo EnvironmentalEntomology vol 37 no 5 pp 1049ndash1062 2008
[8] G A Braga S Ternes et al ldquoModelagem Matematica daDinamica TemporaldoHLB emCitrosrdquo in Proceedings of the 8thCongresso Brasileiro de Agroinformatica Bento Goncalves 2011
[9] DGHall andMGHentz ldquoSeasonal flight activity by theAsiancitrus psyllid in east central Floridardquo Entomologia et Applicatavol 139 no 1 pp 75ndash85 2011
[10] X Song and A U Neumann ldquoGlobal stability and periodicsolution of the viral dynamicsrdquo Journal ofMathematical Analysisand Applications vol 329 no 1 pp 281ndash297 2007
[11] K Wang Z Teng and H Jiang ldquoOn the permanence forn-species non-autonomous Lotka-Volterra competitive systemwith infinite delays and feedback controlsrdquo International Journalof Biomathematics vol 1 no 1 pp 29ndash43 2008
[12] F Zhang and X-Q Zhao ldquoA periodic epidemic model in apatchy environmentrdquo Journal of Mathematical Analysis andApplications vol 325 no 1 pp 496ndash516 2007
[13] T Zhang and Z Teng ldquoOn a nonautonomous SEIRS model inepidemiologyrdquo Bulletin of Mathematical Biology vol 69 no 8pp 2537ndash2559 2007
[14] Z Teng and Z Li ldquoPermanence and asymptotic behavior of thetv-species nonautonomous lotka-volterra competitive systemsrdquoComputers and Mathematics with Applications vol 39 no 7-8pp 107ndash116 2000
[15] W Wang and X-Q Zhao ldquoThreshold dynamics for compart-mental epidemic models in periodic environmentsrdquo Journal ofDynamics and Differential Equations vol 20 no 3 pp 699ndash7172008
[16] Y Nakata and T Kuniya ldquoGlobal dynamics of a class ofSEIRS epidemic models in a periodic environmentrdquo Journal ofMathematical Analysis and Applications vol 363 no 1 pp 230ndash237 2010
[17] Y Nakata Permanence and Global Asymptotic Stability ForPopulation Models in Mathematical Biology Waseda UniversityTokyo Japan 2010
[18] H Smith and P Waltman The Theory of the Chemostat Cam-bridge University Press Cambridge Mass USA 1995
[19] X ZhaoDynamical Systems in Population Biology Spring NewYork NY USA 2003
[20] X M Deng ldquoFormming process and basis and technologicalpoints of the theory emphasis on control citrus psylla for inte-grated control Huanglongbingrdquo Chinese Agricultural ScienceBulletin vol 25 no 23 pp 358ndash363 2009 (Chinese)
[21] T Li C Z Cheng et al ldquoDetection of the bearing rate ofliberobacter asiaticum in citrus psylla and its host plantrdquo ActaAgriculturae Universitatis Jiangxiensis vol 29 no 5 pp 743ndash745 2007 (Chinese)
[22] G F Chen and X M Deng ldquoDynamic observation adult citruspsyllid quantity live through the winter in spring and winterrdquoSouth China Fruits vol 39 no 4 pp 36ndash38 2010 (Chinese)
[23] XMDeng G F Chen et al ldquoThe newly process of Huanglong-bing in citrusrdquo Guangxi Horticulture vol 17 no 3 pp 49ndash512006
[24] R G drsquoA Vilamiu S Ternes B A Guilherme et al ldquoA modelfor Huanglongbing spread between citrus plants includingdelay times and human interventionrdquo in Proceedings of theInternational Conference of Numerical Analysis and AppliedMathematics (ICNAAM rsquo12) vol 1479 pp 2315ndash2319 2012