Analysis of the temporal and spatial disease progress of
Bemisia tabaci
-transmitted
Cucurbit yellow stunting disorder virus
and
Cucumber vein yellowing virus
in cucumber
L. Ruiz
a
, D. Janssen
b
*, G. Martín
b
, L. Velasco
c
, E. Segundo
b
and I. M. Cuadrado
b
a
Departamento de Protección Vegetal INIA, Carretera de la Coruña Km 8, 28040 Madrid;
b
Departamento de Protección Vegetal, CIFA Almeria (IFAPA), Autovía del Mediterraneo km420, La Mojonera 04745; and
c
Departamento de Biotecnología IMIDA, c/Mayor s/n, La Alberca 30150, Spain
Cucurbit yellow stunting disorder virus
(CYSDV) has been present in greenhouse-grown cucumber in Spain since 1992.However, in the autumn of 2000
Cucumber vein yellowing virus
(CVYV) was introduced, leading to mixed infectionsof both
Bemisia tabaci
-transmitted viruses. The temporal and spatial spread of disease symptoms were monitored inexperimental plastic-covered greenhouses during six consecutive cucumber plantings from 2000 to 2002. Using linearregression analysis of 46 disease-progress curves, the Gompertz model best described the CYSDV epidemics in 2000,whereas the logistic model best described the development of CYSDV and CVYV epidemics in 2001 and 2002. The fittedmodels were used to calculate the amount of degree Celsius-days at half-maximum infection in the greenhouses (
°
D
0·5
).After multiple regression analysis, 56% of the variation in
°
D
0·5
of CYSDV was related to the numbers of whiteflies infest-ing the cucumber crops, and was independent of the mean temperatures in the greenhouses. In contrast, 76% of the var-iation in
°
D
0·5
of CVYV was related to both the numbers of vectors present and maximum temperature. Symptomexpression in cucumbers mechanically inoculated with CVYV was most prevalent when plants were grown at regimesof at least 28
°
C day temperature. According to analysis of spread using Taylor’s power law, beta-binomial distributionfitting, and the ordinary runs test, the prevalence of CVYV showed significant overdispersion, whereas that of CYSDVdid not. The
χ
2
test of independence and Spearman’s rank correlation coefficient were used to measure co-occurrenceand covariation, respectively, during the first half of the cultivation period. These results showed that the two diseaseswere not associated.
Since the 1960s, plastic-covered greenhouses haveincreasingly been used to produce horticultural crops inthe Mediterranean area, in order to isolate and protectplants against pests and diseases while optimizing envi-ronmental temperature, humidity and light (Castilla &Jarrett, 1995). However, this production system has alsoresulted in a favourable ecological niche for whiteflies ingeneral, and the sweetpotato whitefly
Bemisia tabaci
inparticular. Production is centred in Almeria (southern
Spain), where greenhouses cover about 28 000 ha, almost40% of which are dedicated to cucurbitaceous crops.Cucumber (
Cucumis sativus
) is produced predominantlyfor export throughout the year.
Bemisia tabaci
was first identified in Spain in 1943, andbecame a pest in greenhouses in 1988, finally displacingthe whitefly
Trialeurodes vaporariorum
during theautumn of 1997 (Gómez-Menor, 1943; Ruiz
et al
., 1999).The population of
B. tabaci
proved to be highly resistantto the majority of phytosanitary treatments (Cahill &Denholm, 1998; Elbert & Nauen, 2000), which jeopard-ized its control. The main problem with
B. tabaci
in inten-sive greenhouse production stems from its transmissionof many virus diseases, including
., 1996). The latter virus has beenpresent in cucurbitaceous crops since 1992 (Sese
et al
.,1994; Célix
et al
., 1996), but the recent introduction of
Cucumber vein yellowing virus
(CVYV) (Cuadrado
et al
.,2001) has led to newly observed mixed infections ingreenhouses in southern Spain.
CYSDV has a bipartite single-stranded RNA genome,and is a member of the genus
Crinivirus
of the family
Closteroviridae
(Wisler
et al
., 1988). First reported in theUnited Arab Emirates (Hassan & Duffus, 1991), it hasspread throughout the Middle East (Rubio
et al
., 1999);the western part of the Mediterranean (Sese
et al
., 1994;Desbiez
et al
., 2000; Louro
et al
., 2000); and the USA(Kao
et al
., 2000). It is transmitted semipersistently by
B. tabaci
and causes phloem-limited infections (Célix
et al
.,1996). Symptoms of CYSDV infection are interveinalchlorosis and necrosis, and stiffness or brittleness of thelower leaves, resembling early senescence and nutritionaldeficiencies in cucurbits. In cucumber, chlorotic flecks arefirst produced in intermediate and older leaves. Theseenlarge and coalesce to produce large areas of chlorosis.Necrosis forms in these chlorotic areas, and leaves dieprematurely.
CVYV is a member of the genus
Ipomovirus
, family
Potyviridae
(Lecoq
et al
., 2000). This virus has a narrowhost range restricted to a number of cucurbitaceous plantspecies (Cohen & Nitzany, 1960), and its geographic dis-tribution is confined to the oriental Mediterranean Basin.CVYV was first described in cucumbers in Israel andthought to be synonymous with a similar virus, ‘bottlegourd mosaic virus’ (Cohen & Nitzany, 1960). Subse-quently it was recognized as the most prevalent diseaseaffecting cucumber in plastic-covered greenhouses in Jor-dan (Al Musa
et al
., 1985). CVYV has also been reportedfrom Turkey (Yimaz
et al
., 1989) and Sudan (Desbiez
et al
., 2001). Symptoms induced by CVYV are severe veinyellowing on the youngest leaves, and stunted growth ofplants with reduced fruit production (Cohen & Nitzany,1960). The virus is transmitted mechanically, and by
B. tabaci
in a semipersistent manner (Harpaz & Cohen,1965; Mansour & Al-Musa, 1993). Although CVYV wasreported only in the Middle East for many years, it wasfound for the first time in cucumber crops in Spain duringthe autumn of 2000 (Cuadrado
et al
., 2001), and readilyspread into cucurbitaceous crops throughout the areaduring the spring of 2001 (Janssen & Cuadrado, 2001).
The presence of both CYSDV and CVYV in the regionhas put cucumber production and trade at risk, increasingthe difficulty of breeding resistant cultivars. Developmentof adequate control strategies requires knowledge of theepidemiology of the diseases, and of the degree of associ-ation between the two viruses and the whitefly popula-tion. The objectives of this study were to monitorwhitefly-transmitted disease incidence rates and patternsof spread in experimental greenhouses during six consec-utive cucumber plantings from 2000 to 2002. Models werefitted to progress curves of the incidence of CYSDV andCVYV disease to summarize and compare the epidemics.Regression models were fitted to half-maximum infection
values against thermal time, the numbers of infestingwhiteflies and maximum temperatures.
Materials and methods
Data collection
The incidence of whiteflies and whitefly-transmitteddiseases was monitored in commercial cucumber crops(
Cucumis sativus
cv. Marianna RZ) grown in separategreenhouses, each spanning 600 m
2
, located within anexperimental farm at the Agriculture Research and Train-ing Centre (CIFA), Almeria, Spain. The crops were grownduring six consecutive crop seasons from spring 2000 toautumn 2002, at a mean density of one plant per m
2
.Three crops were monitored in spring and autumn 2000,while two additional crops were included in spring 2001–autumn 2002. The greenhouses had similar structuralfeatures, and were covered with conventional polyethylenefilm over the roof and nets over the lateral windows, rep-resentative of those used in Almeria. In each greenhouse,weekly routine monitoring started at the first-leaf stageand continued for 10 consecutive weeks. The dates of thefirst data collection (crop season) were 27 March 2000(spring 2000); 2 October 2000 (autumn 2000); 2 April2001 (spring 2001); 25 September 2001 (autumn 2001);8 April 2002 (spring 2002); and 28 October 2002(autumn 2002). For analysis of temporal disease progress,in each greenhouse the numbers of adult whiteflies werecounted on the undersides of the 10 uppermost leavesfrom 24 plants (
c.
5% of plants in each greenhouse),selected by simple random sampling (Campbell &Madden, 1990). Disease symptoms on leaves were alsorecorded. CVYV symptoms presented as vein yellowing inyoung shoots (Cohen & Nitzany, 1960); CYSDV symptomswere mottled patches and interveinal chlorosis on leaves(Célix
et al
., 1996). Attribution of symptoms to CVYVor CYSDV was confirmed by reverse transcriptase-polymerase chain reaction (RT–PCR) assays as describedbelow. During this study plants displaying symptomswere not removed. To assess spatial patterns of virus-infected plants, all plants from four greenhouses (477–483 sampling units per greenhouse) were monitored weeklyfor disease symptoms during four consecutive weeks from2–23 October 2001. The data from 2 October, togetherwith data obtained during samplings performed on 11November 2002, were also used to study the associationbetween these two viruses.
During each crop season and within each greenhouse,temperature was recorded continuously using Escort dataloggers (Escort Data Logging Systems Ltd, New Zealand)at 5-min intervals. Temperatures in greenhouses werecompared, and means calculated to normalize diseaseprogress rates in different crop seasons and under differ-ent temperature conditions. Degree days were calculatedby multiplying the daily mean temperature above 10
°
Cwith time (24 h or 1 day) (Zalom
et al
., 1983). The basetemperature of 10
°
C was chosen arbitrarily as the mini-mum developmental temperature of
., 1985) and because of its proximity to the lowerthreshold temperature of cucumber plant development,which is approximately 11
°
C (Manrique, 1993). By serialaccumulation, and beginning from the start of each cropseason, any given point in time was thus expressed inaccumulated degree-days (
°
D
). Mean daily maximumtemperatures (
T
max
) during the first 4 weeks of productionwere also calculated.
Temporal disease progress analysis
Disease incidence data were transformed as numbers ofplants displaying symptoms of CYSDV and/or CVYV,divided by the total number of plants observed (diseaseincidence). Disease-progress curves were fitted to fourgrowth models using linear regression analysis (Campbell& Madden, 1990): monomolecular {ln[1/(1
−
y
)] = ln[1/(1
−
y
0
)] +
r
M
x
}; logistic {ln[
y
/(1
−
y
)] = ln[
y
/(1
−
y
0
)] +
r
L
x
};Gompertz {–ln[–ln(
y
)] = –ln[–ln(
y
0
)] +
r
G
x
}; and the ex-ponential model {ln(
y
) = ln(
y
0
) +
r
E
x
}. These models wereused as predicted equations to compare, statistically, thelinearly transformed empirical data. In these models therange of possible values for disease incidence
y
(from 0 to1) is described for positive values of
x
(
°
Day);
y
0
= initialdisease incidence; and
r
* = rate of disease increase foreach model. Only
y
values >0 and <1 were used for logisticand Gompertz models. For the monomolecular model,only values <1 were used. Coefficients of determination(
R
2
) and mean square error (MSE) values were obtainedusing regression and
anova
procedures of the
table-curve
2D version 2·02 software (Systat Software Inc.)program. For comparisons, recalculated
R
2
and MSE val-ues (designated
R
*2 and MSE*) were used, as described byCampbell & Madden (1990). For this, transformed pre-dicted disease values were back-transformed to the origi-nal scale and regressed on the observed disease values. R*2
and MSE* values, as well as plots of standardized residu-als vs. the predicted values, were used to select the bestmodel to describe disease-progress curves for each disease,greenhouse and season. For each selected linear regressionmodel, the values of the slope and intercept parametersand their standard error estimates were obtained, andused to calculate the number of degree Celsius-days cor-responding to the temperature-time when half the plantsin the greenhouse displayed disease symptoms (°D0·5).
Using the simple and multiple regression modules instatistical software package statgraphics plus version4·0 (Statistical Graphics Corp., Rockville, MD, USA),relationships between dependent variable °D0·5 and explan-atory variables [numbers of whiteflies per plant (w), meanmaximum temperatures (Tmax) recorded in the green-house] were explored. The principles of these statisticaltests are adequately described in standard texts (e.g. Sokal& Rohlf, 1981).
Spatial pattern analysis
Spatial patterns were quantified using two approaches:spatial point-pattern and geostatistical analyses. In the
former, disease patterns were analysed at the level of thesampling unit and below, or the pattern of diseased indi-viduals within the sampling unit (Turechek & Madden,1999). The greenhouses were divided into 40 blocksgrouping 12 plants. The beta-binomial (Hughes & Mad-den, 1993) and the binomial distributions were fitted tothe disease incidence data using the program bbd (Mad-den & Hughes, 1994) for each virus separately, and thenfor total disease (a plant was considered diseased if it hadeither CYSDV or CVYV symptoms). The binomial distri-bution has a single parameter representing the probabilityof the disease (π). The beta-binomial has two parameters:p, the expected probability of a diseased plant in the field;and θ, a measure of the variation or heterogeneity in dis-ease incidence per sampling unit for a given field. A goodfit to the binomial distribution is suggestive of a randomspatial pattern of disease incidence, while a good fit to thebeta-binomial distribution is suggestive of an aggregatedpattern of disease incidence (Madden & Hughes, 1995).A log-likelihood ratio test statistic (LRS) was calculatedfor each data set to determine if the beta-binomial fittedthe data better than the binomial (Williams, 1975). Inaddition, Taylor’s power law was used to calculate thedispersion index b from the regression between the linear-ized estimates of the mean disease incidence (m) and thesample variance (s) for CYSDV, CVYV and total disease(CVYV or CYSDV), where ln(s2) = ln(a) + b ln(m). Thespatial distribution of disease is considered regularwhen b < 1; random when b = 1; and clustered when b > 1(Taylor, 1961; Campbell & Madden, 1990).
Ordinary runs analysis can be used as a geostatisticalapproach to quantify pattern at the level of the samplingunit and above, or among sampling units (Madden et al.,1982; Gibbons, 1985). A run is a sequence of samplingunits with the same disease status. For example, if 1 indi-cates disease and 0 indicates no disease, the sequence 1–1−0–1−0–0 contains four runs (1–1; 0; 1; 0–0). If diseasedplants in a row resulted from a pathogen spreading fromplant to plant, one would expect an aggregation (cluster-ing) of infected plants and an aggregation of healthyplants. Thus there would be fewer runs. If there were nomovement of the pathogen from plant to plant, one wouldexpect a random mixing of healthy and infected plantsand a correspondingly large number of runs. The nullhypothesis evaluated in this test is that the orderedsequence of symbols (infected plants) is random. Thealternative hypothesis is that the ordered sequence is clus-tered. Let m represent the number of infected plants in arow with a total number of plants equal to N. The totalnumber of runs is represented by U. Under the nullhypothesis of randomness, the expected value (E) of Uis given by: E(U) = 1 + 2m(N − m)/N. The observednumber of runs will be less than E(U) if there is a cluster-ing of infected plants (Gibbons, 1985). The standarddeviation of U is given by: su = {2m(N − m)[2m(N − m)− N]/[N2(N − 1)]}1/2. The standardized U is givenby: Zu = [U + 0·5 − E(U)]/su. The constant 0·5 is the‘correction for continuity’ (Gibbons, 1985). The asympto-tic sampling distribution of Zu is the standard normal
distribution. The value of Zu will be a large negativenumber if there is clustering. Therefore the test for non-randomness (clustering) is one-sided, and left-tail probabi-lity is used (Gibbons, 1985). A row of plants was consideredto have a nonrandom sequence of infected and healthyplants if –Zu was >1·65 (P = 0·05).
Analysis of spatial association
Co-occurrence of CVYV and CYSDV, or the tendency forthe two viruses to infect the same plant, was evaluatedusing the χ2 test of independence (Ludwig & Reynolds,1988). In addition, covariation between the two diseases,as the tendency to increase or decrease together, wasdetermined calculating Spearman’s rank correlation co-efficient (r) (Ludwig & Reynolds, 1988), and significantcorrelation was accepted at P < 0·05 according to theSpearman’s rank correlation analysis. statgraphics plusversion 4·0 was used for statistical analysis.
Effect of environmental temperature on CVYV incidence
Eight groups of 20 cucumber cv. Marianna RZ plantswere inoculated mechanically at the first true-leaf phase.The inoculum was made by grinding infected leaves(7 days after symptom appearance) of cucumber in0·01 m phosphate buffer (1 g mL−1) pH 8 containing0·001 m sodium diethyldithiocarbamate (NaDIECA) and0·1% mercaptoethanol. Plants were grown in 10-cm plas-tic pots in a growth chamber with a photoperiod of 16 h.Each group was grown at one of the following series oftemperature regimes (N and D are temperatures of nightand day periods, respectively): N 16°C, D 16 h/20°C; N16°C, D 6·5 h/20°C, 3 h/37°C, 6·5 h/20°C; N 20°C, D16 h/24°C; N 20°C, D 6·5 h/24°C, 3 h/37°C, 6·5 h/24°C;N 24°C, D 16 h/28°C; N 24°C, D 6·5 h/28°C, 3 h/37°C,6·5 h/28°C; N 28°C, D 16 h/32°C; N 28°C, D 6·5 h/32°C, 3 h/37°C, 6·5 h/32°C. The heat-shock parameter(3 h at 37°C) was used to simulate peak temperaturesthat occur during cultivation of cucumber crops in thegreenhouse. Test plants were observed for symptomdevelopment 2 weeks after inoculation. Tip leaves of allplants were also tested for CVYV by RT–PCR analysis, asdescribed below. The study was performed in triplicate.
CYSDV and CVYV detection by RT–PCR
Total plant RNA was extracted from 2 mg tip leavesusing Qiagen RNA easy plant mini-kit (IZASA, Spain),resuspended in 20 µL DEPC-treated H2O, and heated for3 min at 80°C prior to reverse transcription. First-strandcDNA was synthesized in independent, standard reverse-transcription reactions using 100 units of Superscript IIRNAse H– Reverse Transcriptase (Life Technologies,USA) following the manufacturers instructions. Reverseprimers used were 410L (5′-TTGGGCATGTGACAT-3′)for CYSDV (Célix et al., 1996); and CV(–) (5′-GCGC-CGCAAGTGCAAATAAAT-3′) for CVYV (Cuadrado
et al., 2001). Aliquots of 2 µL of the reaction mixtureswere used for PCR amplification by adding 100 ngupstream primer, 410U (5′-AGAGACGGTAAGTAT-3′) for CYSDV (Célix et al., 1996); and CV(+)(5′-AGCTAGCGCGTATGGGGTGAC-3′) for CVYV(Cuadrado et al., 2001). Template cDNA was denaturedat 96°C for 5 min, and amplification was performedusing Taq polymerase (Roche, Spain) in a total volumeof 50 µL. Thermocycling conditions were: 2 min at 94°C,35 cycles of 30 s at 95°C, 30 s at 55°C and 1 min at72°C, and a final extension step at 72°C for 5 min. ThePCR products were fractionated on a 2% agarosegel alongside known molecular weight markers, andbands were visualized by SyberGreen (Molecular Probes,USA) staining and viewed with ultraviolet light.
Results
Disease-progress curves and explanatory regression models
Figure 1 illustrates the 46 disease-progress curvesobtained. Disease progress was rapid, so that by the endof each season around 100% of the plants appeareddiseased with CYSDV and/or CVYV, except for the year2000 when only CYSDV was present. Linear regressionanalyses in the evaluation of four growth-curve modelsfor describing disease progress showed that the Gompertzmodel best described disease progress of CYSDV during2000. In 2001 and 2002, the logistic model best describeddisease progress for CYSDV and CVYV (Table 1). Graphsof residual vs. predicted values were randomly distributedfor the models described previously for each greenhouse,virus and season. These models, producing the best fits,were chosen to calculate the °D0·5 values (Table 2).
During the study all greenhouses were naturallyinfested with B. tabaci whiteflies. A plot of the °D0·5 valuesfrom CYSDV against the mean numbers of adult white-flies per plant at the first-leaf stage suggests that a similarrelationship existed in spring and autumn cultures(Table 2). However, differences between crop seasonswere obvious for CVYV, so that use of degree-days wasnot sufficient to normalize the disease-progress curves(Fig. 2). Similar plots and results were also achieved withaccumulated numbers of whiteflies per plant duringfour consecutive weeks (data and results not shown), butonly considering the first-leaf stage could make datacollection simpler for technicians in commercial cropproductions.
Simple and multiple regression analysis further exploredthe elements that could play a role in disease-progressmodels. Although the integration of the accumulatedtemperatures into the temporal dimension (degree-days)reduced differences in temperatures along crop seasons,such procedure may exclude the weight of brief periodsof high temperatures that occur daily (generallyaround noon) within a greenhouse. Therefore mean dailymaximum temperatures registered during the first4 weeks were also introduced as explanatory data. The
equations of calculated regression models between °D0·5
(y), whitefly numbers (w) and maximum greenhouse tem-peratures (Tmax) that yielded the best-adjusted coefficientsof determinations were y = 447·23 − 5·54w for CYSDV;and y = 2864·39 − 9·77w − 72·27 Tmax for CVYV(Table 3). In the case of CYSDV, the adjusted coefficientsof determination were high when the independent vari-ables w and Tmax were considered (equations 1 and 3,Table 3). However, the large P values of Tmax in equations2 and 3 (Table 3), the former taking Tmax as the only in-dependent variable, were ≥0·10, so this term was notstatistically significant at the 90% or higher confidencelevel, and should be removed from the model. This indi-cated that numbers of whiteflies infesting cucumber cropsin the greenhouse explained 56% of the total variation of°D0·5. In the case of CVYV, considering either w or Tmax asindependent variables, this procedure resulted in models(equations 4 and 5, Table 3) with w and Tmax values thatwere significant at the 99% confidence level. However,the adjusted coefficients of determination for thesemodels were rather small. Only when both variableswere considered together (equation 6, Table 3) was aregression model obtained that explained 76% of thetotal variation of °D0·5, with both variables beingappropriate as their P values were significant at the99% confidence level.
Spatial disease progress
During the spring and autumn of 2001 and 2002, CYSDVand CVYV diseases differed from one another in terms ofspatial distribution. Figure 3 shows the spread of the dis-eases during autumn 2001. After transformation of thedisease data, maximum-likelihood estimates of p and θfor 16 data sets for CYSDV, CVYV and mixed infections,respectively, were calculated successfully using the beta-binomial-fitting software program bbd (Madden &Hughes, 1994). Distribution of diseased plants could bedescribed better by the beta-binomial rather than thebinomial distribution in 14 of the 16 data sets for CVYV,and only in four of 16 data sets for CYSDV, suggestiveof aggregation. The ranges of incidence of CYSDV andCVYV (p) were not significantly different, having equiva-lent medians and quartiles, suggesting similar skewing(Table 4). For these statistics, total disease-incidencevalues (p) must by definition be greater than or equal tothe maximum p of the two diseases separately.
The range of disease heterogeneity values (θ) forCYSDV was almost half compared with the range foreither CVYV or total disease (Table 4). The median hetero-geneity value for CYSDV was about five and three timesless than for CVYV and for mixed infections, respectively.Considering the differences in median and first quartile
Figure 1 Disease-progress curves of CYSDV and CVYV in 26 cucumber cultivations in 2000–02.
C Exponential 91·9 0·056 0·0100 84·5 random 97·5 0·027 0·0002 92·7 randomMonomolecular 51·0 0·161 0·1110 48·0 nonrandom 69·5 0·104 0·0101 60·8 nonrandomLogistic 92·5 0·114 0·0383 92·4 random 99·0 0·027 0·0000 99·0 randomGompertz 88·1 0·086 0·0614 87·9 random 96·5 0·034 0·0005 97·3 random
D Exponential 97·5 0·009 0·0016 95·2 random 85·7 0·317 0·0028 69·1 nonrandomMonomolecular 71·4 0·098 0·0083 61·4 random? 72·8 0·233 0·0308 55·0 nonrandomLogistic 98·1 0·024 0·0011 98·4 random 94·6 0·363 0·0054 97·0 randomGompertz 97·1 0·019 0·0021 97·1 random 94·0 0·148 0·0064 96·7 random
E Exponential 91·1 0·162 0·0031 86·6 random 97·5 0·021 0·0002 96·4 randomMonomolecular 57·7 0·953 0·0288 39·7 nonrandom 64·0 0·246 0·0172 58·2 nonrandomLogistic 96·2 0·302 0·0006 96·4 random 96·7 0·097 0·0004 98·3 randomGompertz 89·3 0·458 0·0045 91·9 random 91·3 0·127 0·0029 95·5 random
aGH = greenhouse; R 2 = coefficient of determination, MSE = mean square error; R *2 = recalculated coefficient of determination.bCVYV was not observed during 2000.
Virus
CYSDV CVYV
Year Season GH Model R 2 (%) MSE P > F R *2 (%) Residuals R 2 (%) MSE P > F R *2 (%) Residuals
values, the results suggested substantial overdispersion (ornonrandom distribution) of disease in the case of CVYV,in contrast to CYSDV. Similarly, the binary power lawprovided an excellent description of the relationship
between the observed means and sample variances of thedata sets on a log scale for CYSDV, CVYV and total dis-ease across the data sets (Table 5). Estimated intercepts[ln(a)] were not, or only slightly, different from 0, and
Table 2 Degree-days at half-maximum infection in the greenhouse (°D0·5), best fitting linear equations describing disease progress of CYSDV and CVYV, and numbers of Bemisia tabaci adults (w) per cucumber plant at the first-leaf stage, during six consecutive seasons in 2000–02a
Virus
CYSDV CVYV
Year Season Model GH b ± SE a ± SE °D0·5 b ± SE a ± SE °D0·5 w b
aGH = greenhouse; a and b are estimated intercept and slope, respectively, of the best fitting linear equation, SE = standard error.bMeans (n = 24).cCVYV was not observed during 2000.
Figure 2 Relationships between the mean number of adult whiteflies (Bemisia tabaci ) per cucumber plant sampled (w) and the number of degree-days at half-maximum infection of CVYV and of CYSDV in the greenhouse (°D0·5).
Table 3 Regression coefficients, adjusted coefficients of determination (R *2) of simple and multiple regression between ° D0·5a (dependent variable),
and mean numbers of whiteflies (w) and maximum temperatures (Tmax) (independent variables), and associated equations for CYSDV and CVYV
Virus Equation w P of w Tmax P of Tmax Constant P of constant R*2 (%)
slopes were significantly <1 for CYSDV and >1 for CVYVand total disease (P < 0·01). This indicated significantaggregation of disease incidence across all data sets in thecase of CVYV and total disease, but not in that of CYSDV.
Geostatistical pattern analysis of plants with symptomsin the greenhouse yielded similar results. Ordinary runsanalysis showed a nonrandom distribution in 14 of the 16data sets for CVYV and in five of 16 data sets for CYSDV.Median and first quartile values for the standardizednumber of runs suggested nonrandomness of disease inthe case of CVYV, but not CYSDV (Table 4).
Spatial association of CYSDV and CVYV
Submitting the spatial disease data from four greenhousesto the χ2 test of independence suggested that the occur-rence of both viruses in a plant was independent fromone another in seven out of eight data sets (P < 0·05)(Table 6). Co-variation of CYSDV and CVYV was
Figure 3 Symptoms of CYSDV and CVYV recorded in 480 cucumber plants during autumn 2001 in a representative greenhouse (600 m2). The two central vertical lines and the arrow represent a pathway and the entrance door, respectively.
Table 4 Minimum, maximum and three quartiles (Q1, median and Q3) of estimated beta-binomial parameters p (expected probability of a diseased plant) and θ (heterogeneity of disease), and of the standardized number of runs (Zu) for individual diseases and total disease (CYSDV or CVYV) in 16 data sets collected in autumn 2001
aValues smaller than −1·64 are considered nonrandom (P = 0·05).
Table 5 Results of fitting the binary power lawa to CYSDV, CVYV and total disease (CYSDV or CVYV) incidence means and variances for 16 data sets collected in 2001
aln(a) and b are estimated intercept and slope, respectively, of the best fitting line based on least squares regression; and SE is standard error. R 2 is the coefficient of determination.
Table 6 χ2 test of independence statistic and Spearman’s rank correlation coefficient (r) of CYSDV and CVYV in four greenhousesa
observed in only one (0·01 < P < 0·05) out of eight datasets after Spearman’s rank correlation analysis (Table 6).Both types of analysis suggested that CYSDV and CVYVare not spatially associated.
Effect of environmental temperature on CVYV incidence
The number of diseased cucumber plants after mechanicalinoculation with CVYV was dependent on growth condi-tions. Fewer than 10% of plants showed symptoms, orwere positive after RT–PCR analysis, when grown at a16°C night/20°C day regime, whereas higher infectionrates (80–100%) were obtained at regimes of 24°C night/28°C day and above. Simulation of greenhouse peaktemperatures (heat-shock treatment) caused c. 45–75% ofplants to express symptoms and give positive RT–PCRresults at the two lower temperature regimes. Such effectsof heat-shock treatments were not observed at highertemperature regimes (Table 7).
Discussion
Mixed infection of whitefly-transmitted viruses is a recentevent in greenhouse-grown cucurbits in Spain, and maythreaten other regions of the Mediterranean. Here thespread of CYSDV and CVYV was studied in naturallyinfected cucumber greenhouses. In the case of CYSDV, thefirst cucumber leaves, produced 1–2 weeks after planting,were readily colonized by whiteflies and visible symptomsappear after a further 3–5 weeks (latency period) (Ruiz,2002). Although spread of CYSDV varied among theyears and seasons, half the cucumber plants showedsymptoms at 270–440 degree-days (4–5 weeks afterplanting in spring and 3–4 weeks in autumn). CVYVspread was characterized by major seasonal differences.Disease progress was similar to CYSDV in autumn (from260 to 480 degree-days), but in spring, disease progresswas delayed (450–670 degree-days, or 5–6 weeks).
Whitefly numbers and indoor temperatures were alsofound to have a significant impact on viral epidemics.During this 3-year study, the number of infesting vectorswas the driving force behind both epidemics (Table 3).Epidemic progress based on vector number is a typicalfeature of vector-borne viruses. This has been shown withleafhopper-borne viruses (Power, 1992); aphid-borne
viruses (Thresh, 1986); as well as for CYSDV (Célix et al.,1996), CVYV (Mansour & Al-Musa, 1993; Caciagli, 2001)and other whitefly-transmitted viruses (Caciagli, 2001).Temperature has also been shown to affect epidemic ratesignificantly by affecting vector dynamics (Thresh, 1986).In countries of the Middle East, disease caused by CVYVhas been observed mostly during the hottest crop seasons,when the highest numbers of whiteflies are produced(Cohen & Nitzany, 1960; Ucko et al., 1998). In southernSpain, mild winter months and high densities of green-houses lead to abundant whiteflies throughout the entireyear, with uninterrupted access to cucurbitaceous crops.Therefore the seasonal variability of whitefly-transmitteddisease in the greenhouse could result from the effect theindoor climate has on the virus–vector or virus–plantrelationship (Harrison, 1981). In the present study, CVYVcould be explained by whitefly numbers and meanmaximum temperatures in the greenhouse during the firstcrop month. The incidence of CYSDV was also stronglyrelated to thermal time in spring and autumn, althoughthis was not the case for CVYV. Observations in thegreenhouse suggested that the incidence of CVYVincreased significantly after hot days. Therefore theexpression of disease evolution against degree-days, whichconsiders the overall mean daily temperatures, wouldreduce the weight of peaks of high temperatures registered.Only when numbers of whiteflies and mean maximumtemperatures were considered as explanatory variableswas a regression model obtained that explained 76% of°D0·5 of CVYV spread. The effect of temperature on CVYVdisease was reproduced in a growth chamber. Theefficiency of CVYV infection after mechanical inoculationin cucumber plants was 100% when plants were grownat constant day temperatures of 32°C, and c. 50% whengrown at 24°C (Table 7). The optimum temperature forrapid expansion of individual cucumber leaves is also25°C (Milthorpe, 1959), whereas maximum rate of drymatter production occurs at 30–35°C under experimentallight conditions (Friend & Helson, 1976), or at 28–29°Cin greenhouse conditions with natural light (Grimstad &Frimanslund, 1993).
Other factors driving the introduction and spread ofCYSDV and CVYV would be the source of inoculum,and immigration and emigration of vector populations.Although dispersal parameters of whiteflies are difficult toquantify, the introduction of disease into a greenhouse
aMean numbers (± standard error) of plants from a total of 20 inoculated plants per group (n = 3).bGrowth temperature at 37°C during 3 h of day period.cNight (N ) and day (D) temperatures in °C during 8 and 16 h, respectively.
Table 7 Numbersa of cucumber plants showing symptoms and reacting positively after RT–PCR analysis, 14 days after mechanical inoculation with CVYV
relies on long-range fly activities that benefit from verticalconvection currents and horizontal air movements (Joyce,1983), and therefore greenhouses downwind in closeproximity to infested crops are more likely to be infestedthan those at more distant locations (Watson et al., 1992).Several weed species can act as reservoirs of CVYV(Janssen et al., 2002). Still, the natural source of inoculumin south-eastern Spain is most likely to be neighbouringgreenhouse crops because of the high density of green-houses in the production area. The spread within thegreenhouse will also depend on short-range fliers. Labo-ratory studies show take-off activity during daytime andthe capability of sustaining flight for over 2 h (Blackmer& Byrne, 1993). Spatial pattern analysis demonstratedsignificant differences between CYSDV and CVYV. Theincidence of CVYV, and not of CYSDV, was overdis-persed relative to the binomial distribution, and describedwell by the beta-binomial distribution in the same fields.This also supports the better correlation between the inci-dence of CYSDV with the mean numbers of whiteflies perplant sampled at random. The results reported here havealso shown that CYSDV and CVYV were distributedindependently at the early stage of the cultivation period,in terms of their co-occurrence and covariation (χ2 test ofindependence and Spearman’s rank correlation coefficient).This suggests that some biological aspects of these pathogensmay differ. CYSDV and CVYV are both semipersistentlytransmitted by B. tabaci with comparable acquisition andinoculation thresholds. Yet the duration of persistence inthe vector is 7–9 days in the case of CYSDV (Célix et al.,1996; Wisler & Duffus, 2001), and 5 h in CVYV (Mansour& Al-Musa, 1993). Although the longevity of the vectorhas been estimated to range from 4 to 62 days, depending onthe biotype, sex and environmental temperature (Yimazet al., 1989), one could argue that B. tabaci behaves virtu-ally as a nonpersistent transmitter of CVYV and a persistenttransmitter of CYSDV in epidemiological terms.
The key to management of these viruses in cucumberproduction in southern Spain lies in restricting theentrance and indoor mobility of the vectors into green-house crops. In the present study, greenhouse-grownplants displaying disease symptoms were not removedsystematically, and it is not known whether such a prac-tice would have influenced the spatial–temporal dynam-ics. In view of the different epidemiological features ofCYSDV and CVYV, roguing of diseased plants and tem-perature control of greenhouse crops may reduce the dis-ease progress of CVYV, but not of CYSDV. Managementstrategies might also include the introduction of crop-freeperiods (Ucko et al., 1998), the development of virus-tolerant cultivars (Lopez-Sese & Gomez-Guillamon,2000) and improving the physical barriers (Janssen et al.,2003), or other measures such as UV-absorbing films(Antignus et al., 2001) that reduce whitefly numbers.
Acknowledgements
We thank Professor L.V. Madden for kindly supplyingus with the bbd program. We would like also to thank
Professors Piero Caciagli (CNR, Torino) and Hsing-YehLiu (USDA-ARS, Salinas) for critical review of themanuscript. The first and fourth authors had fellowshipsfrom the Dirección General de Investigación (Consejeríade Agricultura y Pesca) of the Junta de Andalucía. Thesecond and third author had fellowships from INIA.This work was supported by project SC99-050 (INIA).We also thank Antonia Belmonte and Montserrat Canofor technical assistance.
References
Al Musa AM, Qusus SJ, Mansour AN, 1985. Cucumber vein yellowing virus on cucumber in Jordan. Plant Disease 69, 361.
Antignus Y, Lapidot M, Cohen SI, 2001. Interference with ultraviolet vision of insects to impede insect pests and insect-borne plant viruses. In: Harris KF, Smith OP, Duffus JE, eds. Virus–Insect–Plant Interactions. San Diego, CA, USA: Academic Press, 331–50.
Blackmer JL, Byrne DN, 1993. Flight behaviour of Bemisia tabaci in a vertical flight chamber: effect of time of day, sex, age and host quality. Physiological Entomology 18, 223–32.
Caciagli C, 2001. Whitefly-borne viruses in continental Europe. In: Harris KF, Smith OP, Duffus JE, eds. Virus–Insect–Plant Interactions. San Diego, CA, USA: Academic Press, 279–92.
Cahill M, Denholm I, 1998. Pesticide resistance in protected agriculture – emphasis on Bemisia. In: Cuadrado IM, Viñuela E, eds. Pesticide Resistance in Horticultural Crops. Almeria, Spain: FIAPA, 45–53.
Campbell CL, Madden LV, 1990. Introduction to Plant Disease Epidemiology. New York, USA: Wiley-Interscience.
Castilla N, Jarrett P, 1995. Protected cultivation in the Mediterranean area. Plasticulture 107, 13–20.
Célix A, López-Sesé A, Almarza N, Gómez-Guillamón ML, Rodríguez-Cerezo E, 1996. Characterization of Cucurbit yellow stunting disorder virus, a Bemisia tabaci-transmitted closterovirus. Phytopathology 86, 1370–6.
Cohen S, Nitzany FE, 1960. A whitefly-transmitted virus of cucurbits in Israel. Phytopathologica Mediterranea 1, 44–6.
Cuadrado IM, Janssen D, Velasco L, Ruiz L, Segundo E, 2001. First report of Cucumber vein yellowing virus in Spain. Plant Disease 85, 336.
Desbiez C, Lecoq H, Aboulama S, Peterschmitt P, 2000. First report of Cucurbit yellow stunting disorder virus in Morocco. Plant Disease 84, 596.
Desbiez C, Delecolle B, Wipf-Scheibel C, Lecoq H, 2001. Le Cucumber vein yellowing virus, virus transmis par l’aleurode Bemisia tabaci, est un member des Ipomovirus, Potyviridae. In: 8èmes Rencontres de Virologie Végétale, Aussois, 2001. Strasbourg, France: IBMP du CNRS, 31.
Elbert A, Nauen R, 2000. Resistance of Bemisia tabaci (Homoptera: Aleyrodidae) to insecticides in southern Spain with special reference to neonicotinoids. Pest Management Science 56, 60–4.
Friend DHC, Helson VA, 1976. Thermoperiodic effects on the growth and photosynthesis of wheat and other crop plants. Botanical Gazette 137, 75–84.
Gibbons JD, 1985. Nonparametric Methods for Quantitative Analysis, 2nd edn. Columbus, OH, USA: American Sciences Press.
Gómez-Menor J, 1943. Contribución al conocimiento de los
Aleyródidos de España (Hem. Homóptera) 1° nota. Eos 19, 173–209.
Grimstad SO, Frimanslund E, 1993. Effect of different day and night temperature regimes on greenhouse cucumber young plant production, flower bud formation and early yield. Scientia Horticulturae 53, 191–204.
Harpaz I, Cohen S, 1965. Semipersistent relationship between Cucumber vein yellowing virus (CVYV) and its vector, to tobacco whitefly (Bemisia tabaci Gennadius). Phytopathologische Zeitung 54, 240–8.
Harrison BD, 1981. Plant virus ecology: ingredients, interactions and environmental influences. Annals of Applied Biology 99, 195–209.
Hassan AA, Duffus JE, 1991. A review of a yellowing and stunting disorder of cucurbits in the United Arab Emirates. Emirates Journal of Agricultural Research 2, 1–16.
Hughes G, Madden LV, 1993. Using the beta-binomial distribution to describe aggregated patterns of disease incidence. Phytopathology 83, 759–63.
Janssen D, Ruiz L, Velasco L, Segundo E, Cuadrado IM, 2002. Non-cucurbitaceous weed species shown to be natural hosts of Cucumber vein yellowing virus in south-eastern Spain. Plant Pathology 51, 797.
Janssen D, Ruiz L, Cano M, Belmonte A, Martin G, Segundo E, Cuadrado IM, 2003. Physical and genetic control of Bemisia tabaci-transmitted Cucurbit yellow stunting disorder virus and Cucumber vein yellowing virus in cucumber. IOBC wprs Bulletin 26, 101–6.
Joyce RJV, 1983. Aerial transport of pests and pest outbreaks. European and Mediterranean Plant Protection Organization Bulletin 13, 111–9.
Kao J, Jia L, Tian E, Rubio L, Falk BW, 2000. First report of Cucurbit yellow stunting disorder virus (genus Crinivirus) in North America. Plant Disease 101, 84.
Lecoq H, Desbiez C, Delécolle B, Cohen S, Mansour A, 2000. Cytological and molecular evidence that the whitefly-transmitted Cucumber vein yellowing virus is a tentative member of the family Potyviridae. Journal of General Virology 81, 2289–93.
Lopez-Sese AI, Gomez-Guillamon ML, 2000. Resistance to Cucurbit yellowing stunting disorder virus (CYSDV) in Cucumis melo L. Hortscience 35, 110–3.
Louro D, Vicente M, Vaira AM, Accotto GP, Nolasco G, 2000. Cucurbit yellow stunting disorder virus (genus Crinivirus) associated with yellowing disease of cucurbit crops in Portugal. Plant Disease 84, 1156.
Ludwig JA, Reynolds JF, 1988. Statistical Ecology. New York, USA: John Wiley & Sons.
Madden LV, Hughes G, 1994. bbd – computer software for fitting the beta-binomial distribution to disease incidence data. Plant Disease 78, 536–40.
Madden LV, Hughes G, 1995. Plant disease incidence: distributions, heterogeneity, and temporal analysis. Annual Review of Phytopathology 33, 529–64.
Madden LV, Louie R, Abt JJ, Knoke JK, 1982. Evaluation of tests for randomness in infected plants. Phytopathology 72, 195–8.
Manrique LA, 1993. Greenhouse crops: a review. Journal of Plant Nutrition 16, 2411–77.
Mansour A, Al-Musa A, 1993. Cucumber vein yellowing virus: host range and virus vector relationships. Journal of Phytopathology 137, 73–8.
Milthorpe FL, 1959. Studies on the expansion on the leaf surface. I. The influence of temperature. Journal of Experimental Botany 10, 233–49.
Moriones E, Arnó J, Accotto GP, Noris E, Cavallarin L, 1993. First report of tomato yellow leaf curl virus in Spain. Plant Disease 77, 953.
Power AG, 1992. Host plant dispersion, leafhopper movement and disease transmission. Ecological Entomology 17, 63–8.
Rubio L, Soong J, Kao J, Falk BW, 1999. Geographic distribution and molecular variation of isolates of three whitefly-borne closteroviruses of cucurbits: Lettuce infectious yellows virus, Cucurbit yellow stunting disorder virus, and Beet pseudo-yellows virus. Phytopathology 89, 707–11.
Ruiz L, 2002. Epidemiología cuantitativa de las virosis del pepino transmitidas por mosca blanca. Almeria, Spain: University of Almeria, PhD Thesis.
Ruiz L, Janssen D, Cuadrado IM, 1999. Moscas blancas (Homoptera: Aleyrodidae) sobre cultivos protegidos de cucurbitáceas en Almería: dinámica de las poblaciones de Trialeurodes vaporariorum (West.) y Bemisia tabaci (Genn.) y caracterización del biotipo de B. tabaci. Agricola Vergel 18, 660–6.
Sese AIL, Gomez-Guillamon ML, Diaz-Ruiz JR, 1994. Appearance of a possibly new yellowing disease in Spain. Cucurbit Genetics Cooperative 17, 72–3.
Sokal RR, Rohlf FJ, 1981. Biometry. New York, USA: W.F. Freeman.Taylor LR, 1961. Aggregation, variance, and mean. Nature
GD, Garret RG, Ruesink WG, eds. Plant Virus Epidemics, Monitoring, Modelling and Predicting Outbreaks. New York, USA: Academic Press, 359–86.
Turechek WW, Madden LV, 1999. Spatial pattern analysis and sequential sampling for the incidence of leaf spot on strawberry in Ohio. Plant Disease 83, 992–1000.
Ucko O, Cohen S, Ben-Joseph R, 1998. Prevention of virus epidemics by a crop-free period in the Arava region of Israel. Phytoparasitica 26, 313–21.
Watson TF, Silvertooth JC, Tellez A, LL, 1992. Seasonal dynamics of sweetpotato whitefly in Arizona. Southwestern Entomology 17, 149–67.
Williams DA, 1975. The analysis of binary responses from toxicological experiments involving reproduction and teratogenicity. Biometrics 31, 949–52.
Wisler GC, Duffus JE, 2001. Transmission properties of whitefly-borne criniviruses and their impact on virus epidemiology. In: Harris KF, Smith OP, Duffus JE, eds. Virus–Insect–Plant Interactions. San Diego, CA, USA: Academic Press, 293–308.
Wisler GC, Duffus JE, Liu H-Y, Li RH, 1988. Ecology and epidemiology of whitefly-transmitted closteroviruses. Plant Disease 82, 270–80.
Yimaz MA, Ozaslan M, Ozaslan D, 1989. Cucumber vein yellowing virus in Cucurbitaceae in Turkey. Plant Disease 73, 610.
Zalom FG, Goodell PB, Wilson LT, Barnett WW, Bentley WJ, 1983. Degree-Days: The Calculation and Use of Heat Units in Pest Management. Leaflet 21373. Oakland, CA, USA: University of California, Division of Agriculture and Natural Resources.
Zalom FG, Natwick ET, Toscano NC, 1985. Temperature regulation of Bemisia tabaci (Homoptera: Aleyrodidae) populations in Imperial Valley cotton. Journal of Economic Entomology 78, 61–4.
