DYNAMICS OF AIRBORNE FUSARIUM MACROCONIDIA IN WHEAT … · Experimental fields and FHB...

SUMMARY

Dispersal of Fusarium macroconidia was studied us-ing a volumetric spore sampler that sampled air in win-ter wheat crops, with a natural Fusarium inoculum. Thespore sampler was operated over a 3-week periodaround wheat flowering, between 1994 and 1997; inthese years head blight ranged from traces to about100% of spikes affected. The numbers of spores per m3

air were counted and related to the meteorological con-ditions. An association was found between rainfall andpeaks of the macroconidia sampled from the air. In par-ticular, no or a very few conidia were sampled from theair before rainfall, but their number progressively in-creased during rainfall; in the presence of high humidi-ty, conidia continued to be sampled at high densitiesfor some hours after rain had ceased and they usuallyreached their peak under these conditions. Finally, den-sity of the airborne conidia rapidly decreased when rel-ative humidity dropped. Two regression equations werefound, which accounted for the effect of meteorologicalconditions on the number of airborne macroconidia, inrainy (at least 0.2 mm rain) and non rainy days. Theseequations produced an accurate estimate of the dynam-ics of airborne conidia over the sampling season; theyincluded average air temperature, amount and intensityof rainfall on the preceding day, and number of hourswith high relative humidity (> 80%). In the first equa-tion, an empirical weight accounting for the pattern ofairborne conidia over a sequence of rainy days was alsoincluded.

Key words: airborne conidia, seasonal pattern, envi-ronmental conditions, correlation analysis, regressionmodels.

Corresponding author: V. RossiFax: +39.0523.599256E-mail: [email protected]

INTRODUCTION

Fusarium head blight (FHB) is a potentially destruc-tive disease of small grain cereals, caused by severalspecies of Fusarium that infect the head tissues and theripening kernels (Wiese, 1977). The disease occursworldwide, but its severity varies markedly in differentyears and locations, being strictly dependent on the epi-demiological conditions (Parry et al., 1995). It is wellknown that severe epidemics of FHB occur when mete-orological conditions after heading are moist and warm,or in the presence of sprinkler irrigation (Parry et al.,1995). Statistical analyses based on field-collected datahave confirmed the crucial effect of weather on the dis-ease, the incidence increasing with increases in rainfall,air temperature, and the length of periods with high rel-ative humidity (Nakagawa et al., 1966; Castonguay andCouture, 1983; Snijders, 1990; Moschini and Fortugno,1996). However, none of these previously cited findingsexplained the effect of weather on inoculum dispersal,because they considered the entire infection process, in-cluding spore production from the inoculum sources tothe onset of disease symptoms or to kernel infection,through spore dispersal and landing on the head sur-face, infection and invasion of the host tissue.

Many studies have been carried out on the factors af-fecting the dispersal patterns of Gibberella zeae (teleo-morph of F. graminearum) ascospores under field con-ditions (Atanasoff, 1920; Ayers et al., 1975; Tschanz etal., 1976; Ye, 1980; Paulitz, 1996; Suty and Mauler-Machnik, 1996) and of Monographella (=Calonectria)nivalis [teleomorph of Fusarium (=Microdochium) ni-vale] ascospores (Millar and Colhoun, 1969; Sanderson,1970), while the dispersal of conidia has not been inves-tigated sufficiently. Nevertheless, there is no reason toconsider conidia less important than ascospores in caus-ing FHB. In fact, it is known that ascospores andmacroconidia of F. graminearum show the same abilityto infect wheat heads (Stack, 1989) and that both areabundantly produced on the infected residues when thewheat spikes are susceptible to infection (Khonga andSutton, 1988; Fernando et al., 1997). In addition, someFusarium species spread as conidia either exclusively or

Journal of Plant Pathology (2002), 84 (1), 53-64 Edizioni ETS Pisa, 2002 53

DYNAMICS OF AIRBORNE FUSARIUM MACROCONIDIA IN WHEAT FIELDSNATURALLY AFFECTED BY HEAD BLIGHT

V. Rossi, L. Languasco, E. Pattori and S. Giosuè

Istituto di Entomologia e Patologia Vegetale, Università Cattolica del Sacro Cuore, Via Emilia Parmense 84, I-29100 Piacenza, Italy

Dedicated to Prof. Antonio Granition the occasion of his 75th birthday

predominantly, since their perfect stage is not known orseldom occurs on diseased host tissues (Zillinsky, 1983).This is the case of F. culmorum, F. avenaceum or F.poae, which are often prevalent in the complex ofspecies causing the disease (Parry et al., 1995). Innorthern Italy, for instance, F. graminearum is not theprevalent species causing either foot rots (Rossi et al.,1995) or FHB (Pancaldi and Torricelli, 1998).

Sutton (1982) stated that ‘splashing or wind-drivenrain is widely regarded as the principal dispersal mecha-nism for macroconidia of F. graminearum … but …(this) does not appear to have the support of critical ex-perimentation’. The studies carried out by Stepanov(1935), and by Jenkinson and Parry (1994), showed thatthe conidia of F. graminearum, F. culmorum and F. ave-naceum can be carried by splash drops originating froma water drop falling onto either sporulating cultures orinfected sporulating wheat stems. However, the ballistictrajectories of these splashed droplets make directsplash-dispersal to heads impossible, especially undercrop conditions, where the dense crop canopy at thetime of anthesis would intercept both falling rain dropsand the splashed droplets originating from them. Thus,different hypotheses have been expressed to explain in-oculation of wheat spikes by conidia, including a seriesof upwards leaps involving infection and sporulation onthe upper leaves or the intervention of external windforces assisting the aerial upward movement of spores(Jenkinson and Parry, 1994). The latter hypothesiscould be strengthened by the results of some workers(Martin, 1988; Suty and Mauler-Machnik, 1996; Fer-nando et al., 1997), who found Fusarium spores, includ-ing conidia, to be present in the air above a wheat cropusing samplers that would not sample splash-dispersedspores. Unfortunately, these workers did not show de-tails on their conidial counts over the season and didnot relate them to the meteorological conditions.

The objectives of the present work were (i) to obtainquantitative estimates of airborne Fusarium macroconi-dia, (ii) to determine their seasonal patterns, and (iii) torelate them with the concomitant meteorological condi-tions. For this reason, a spore sampler was operated, af-ter heading, above the canopies of winter wheat crops,with a natural Fusarium inoculum.

MATERIALS AND METHODS

Experimental fields and FHB assessments. Air-borne spores were sampled during a 4-year (1994-1997)period at Piacenza (North Italy), in experimental fieldsdesigned to compare performances of several winter-sown cultivars of bread (Triticum aestivum L.) and du-

rum (T. durum Desf.) wheat; the list of cultivarschanged yearly, but some of them remained unchangedover the 4-year period, so that data collected in differ-ent years were comparable. Cultivars were randomlyarranged in big plots, grown following common use andnot sprayed with fungicides against FHB or other dis-eases. Rows were planted 15 cm apart, with a plantingdensity of approximately 450 plants m-2. After anthesis,at weekly intervals as long as healthy spikelets were stillgreen, the incidence and severity of FHB were assessedon each cultivar, on five 1-m2 samples randomly select-ed along the diagonal of each plot, as % of affectedheads and % of affected spikelets per head, respective-ly. Each year, the most affected cultivar was chosen asan indicator of the environmental conduciveness to thedisease. The growth stage of wheat plants was also not-ed using the decimal code (DC) of Zadoks et al. (1974).

Hourly meteorological values of air temperature (T,in °C), relative humidity (RH, in %) and rainfall (R, inmm) were measured by an automatic weather stationplaced at maximun 1.5 km from the experimental site. In1994, the leaf wetness (in min/day) was also measured byan electronic sensor placed within the wheat canopy.

Spore sampling. A 7-day recording wind-orientedvolumetric spore sampler (Lanzoni VPPS-2000,Bologna, Italy) was installed in the experimental crop inthe first half of May and operated continuously for 3weeks, around the flowering period. It was operated us-ing a 220 V 50 Hz power source, and was adjusted tosample air at 10 l min-1 at 150 cm above the ground.Thus, air was sampled above the wheat plants, whichranged from 80 to 90 cm in height. Spores entering thesampler impinged on a rotation drum (rotating at aspeed of 2 mm h-1) covered with a 14-mm-wide tapecoated with a thin layer of silicon and glycerol (Lan-zoni, Bologna, Italy). The tape was replaced every 7days and dissected for microscopic examination. Thetape was examined microscopically by scanning 4equidistant transects across the long axis of the tape at2-mm (1-hour) intervals. Since macroconidia of Fusari-um species do not lend themselves to ready identifica-tion macroconidia of any Fusarium species were identi-fied (Nelson et al., 1983; Burgess et al., 1988), the num-ber of macroconidia observed in each 1-hour transectwas corrected for the proportion of the tape examinedand the volume of air sampled, and expressed as macro-conidia m-3 air per hour

To have an estimate of the profile of Fusariumspecies present in the air, 20 Petri plates containing aPCNB medium selective for Fusarium species (Martin,1988) were exposed close to the spore sampler for oneday, 2 to 4 times per year. Plates were then incubated at

54 Airborn Fusarium macroconidia Journal of Plant Pathology (2002), 84 (1), 53-64

room temperature for 5-7 days; Fusarium colonies werepreliminarily transferred to a fresh PCNB medium andthen to PDA, to be identified according to Nelson et al.(1983).

Data analysis. Records from the spore sampler wereused as hourly values (cumulative 1-h average numberof macroconidia) or daily values (sum of the 24 hourlyvalues per day), both expressed as number of sporesper m3 air. Similarly, data of T, RH and R were used ashourly or daily (mean of 24 hourly values) values.

The SPSS statistical package (SPSS inc., Chicago,Michigan) was used to explore data, calculate summarystatistics, and calculate the Pearson’s coefficient of cor-relation between pairs of variables. To study the effectof meteorological conditions on the dynamics of air-borne Fusarium conidia, the meteorological variableslisted in Table 1 were used as independent variables ina multiple regression analysis, where the daily numberof conidia sampled was the dependent variable. A for-ward stepwise procedure (with F-ratio equal to 4 for ei-ther entering or removing variables from the regressionmodel) was applied to select the smallest set of inde-pendent variables related to the dependent one (Draperand Smith, 1968); the set of independent variables to beinserted in the selection procedure included the abovementioned meteorological variables, an empiricalweight based on the position of each day in a sequenceof rainy days (see below), and four dummy variables(with the alternative value 0 or 1) accounting for thedifferences between years in density of the airbornespores. Results of the regression analysis were evaluatedon the basis of the standard error of model parameters,the residual distribution, the coefficient of determina-tion (R2, which represents the proportion of variance ofthe response variable that is predictable from the re-gressors), and the adjusted R2 (that adjusts for the num-ber of independent variables in the model).

RESULTS

Seasonal patterns of airborne conidia and FHB onwheat. In 1994, the density of airborne conidia washigh over the whole 3-week sampling period, with a to-tal of more than 23,000 conidia sampled per m3 of air.During flowering of the wheat plants, about 6500 coni-dia were sampled; in this period there was a 3-day longrain event (3.4 mm rain), RH was higher than 80%, andT was around 15°C (Fig. 1A). The resulting incidenceof FHB was low, with a maximum of 2% of affectedheads on the bread wheat ‘Grazia’, each of them withfew affected spikelets.

In 1995, the total number of conida sampled fromthe air was lower than in 1994 (about 6800 conidia perm3 of air), and centred on the last part of the sporesampling period. During flowering, a total of 1250 coni-dia were sampled. The weather was characterised by re-peated rainfall, high RH and T ranging between 12 and15°C (Fig. 1B); it resulted in severe FHB epidemics: onthe durum wheat ‘Simeto’, 8% of the heads were al-ready affected at DC69, while at DC80 96% of theheads were scabbed for about 50% of their surface.Thus, it was inferred that the peak of the airbornespores found 12 days after flowering began was causedby the presence of sporodochia on the head tissue thathad been infected (Fig. 1B); actually, superficial myceli-um and spore masses were observed, especially on thebase of diseased spikelets.

In 1996, the situation was much like that of 1995. Atotal of about 8000 conidia were sampled per m3 of air.Three peaks of spore sampling occurred: at the begin-ning of flowering, 10 and 16 days later. During the firstpeak, the weather was wet, with RH higher than 80%and T lower than 15°C (Fig. 1C). Maximum FHB inci-dence occurred on the bread wheat ‘Santerno’, with5% of scabbed heads. In this case again, the latest twopeaks of airborne conidia were associated with the pro-duction of spores on the infected spike tissue.

In 1997, 9400 conidia were sampled in total, withthree peaks; the first peak was found before flowering,the second one occurred when flowering had finished,and the third peak one week later. Flowering occurredduring a dry period, with T higher than in the otheryears, RH around 60% and only two rainy days, on thefirst and on the last day of flowering (Fig. 1D). FHBwas present in traces only, on all cultivars.

About 90% of the Fusarium species collected fromthe air by exposing the Petri plates near to the sporesampler were, in decreasing order of frequency, M. ni-vale (especially in 1994 and 1995), F. graminearum (es-pecially in 1996), F. culmorum, F. poae, and F. ave-naceum. F. tricinctum, F. moniliforme and F.crokwellense were also detected.

Dynamics of the airborne conidia in relation to rain-fall. About 63% of total conidia were sampled from airduring rainy days. Spore samplings showed an associa-tion between airborne conidia and rain events (Fig. 1).Peaks of airborne spores were always triggered by rainevents, defined as periods of one or more successivedays with at least 0.2 mm of rainfall: the highest num-bers of conidia were sampled during such rain events orin the first days following rainfall. For instance, 1886conidia per m3 air were sampled during the rain eventon May 8-9, 1994 (18.7 mm rain), 1912, 817 and 453

Journal of Plant Pathology (2002), 84 (1), 53-64 Rossi et al. 55

conidia were sampled on the three no rainy days be-tween May 10 and 12; finally, 3627 were caught on therain event between May 13 and 15 (3.4 mm rain) (Fig.1A). On the rain event between May 11 and 14, 1995(53 mm rain) 702 conidia were sampled, 174 conidiawere sampled on the following non rainy day, while 341conidia were caught on the rain event between May 16and 19 (8.4 mm rain); the numbers of conidia remainedvery low during the following 6-day period with norain, and increased to 1183 on May 26 (4.6 mm rain)(Fig. 1B). Similarly, 3377 conidia were sampled on therain event between May 9 and 13, 1996 (35 mm rain),442 to 54 conidia were sampled during the dry periodbetween May 14 and 20, and 1084 conidia on May 21(0.6 mm rain) (Fig. 1C). Dynamics similar to these ex-amples were repeatedly observed during the sampling

seasons 1994 to 1997 (Fig. 1). Very high densities of air-borne conidia on dry days that immediately followed arain event were frequent at the end of the sampling sea-son; this occurred, for instance, on 26 May, 1994, be-tween 27 and 29 May, 1995, and on 28 May, 1996 (Fig.1A, 1B and 1C, respectively). In all these cases,sporodochia were already present on the scabbed headtissues that had been infected during flowering.

As a consequence of these dynamics, the most part(80%) of conidia sampled on the days with no rain wasfound on the first two days following a rain event (60%and 20% on the first and second day, respectively),while a few conidia were sampled far from a rain event.

As previously mentioned, 63% of total conidia weresampled during rain events. Dynamics of the sporenumbers over time during each rain event showed some


0

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Fig. 1. Fusarium macroconidia sampled daily from the air above wheat canopies in 1994 (A), 1995 (B), 1996 (C) and 1997 (D), inrelation to mean air temperature (T), total rainfall (R), and mean relative humidity (RH). Arrows show the period of flowering ofthe wheat plants.

differences (Fig. 1). On the second day, the spore num-ber increased compared to those sampled on the firstday, by 2 (May 6, 1994) to 11 (May 25, 1994, and May10, 1996) times; in only one case (May 15, 1994) it de-creased and in another one (May 17, 1995) it did notchange. On the third day, the spore numbers increasedagain by at maximum 2 times (May 15, 1994, and May13, 1995) or remained nearly unchanged (May 18, 1995,May 12, 1996); in only one case it decreased, by aboutone half (May 13, 1996). On the fourth day the sporenumbers decreased by one half (May 14, 1995) or twothird (May 12, 1996), or remained nearly unchanged(May 189, 1995). On May 13, 1996, the number ofspores sampled on the fifth day of one prolonged rainevent increased again. Notwithstanding the above men-tioned differences, an average pattern of spore numbersover the time of any rain event was singled out (Fig. 2):the average number of conidia sampled during an iso-lated rainy day or on the first day of any prolonged rainevent (582 per m3 air) was lower than that caught onthe second rainy day (1376); then, the spore numberdecreased on the third and on further rainy days (690and 437, respectively).

Patterns of the airborne conidia during rain events.Hourly records of spore samplings showed that rainfalland peaks of airborne conidia did not clash (Figs 3 and4). No or a very few conidia were sampled in the ab-sence of rain (Figs 3A, 4A and 4B), then the number ofconidia progressively increased with the beginning of


Fig. 2. Average number of Fusarium macroconidia sampledfrom the air above wheat canopies on each rainy day of asequence of days with rainfall. Whiskers show the standarderror of the means.

Fig. 3. Number of Fusarium macroconidia sampled from theair above wheat canopies in each hour of the day during some3-day periods in 1994, in relation to rainfall (R), relative hu-midity (RH) and leaf wetness (LW).

Successive rainy days

Con

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rainfall. Usually, this increase was marked after 3-4hours of rainfall and continued after the rainfall hadceased; the highest numbers of conidia were constantlysampled from the air in the hours following the end ofrainfall. The number of hours after rain had ceased inwhich conidia continued to be sampled was irregular,ranging from a few (Fig. 3B) to many (Fig. 3A) hours;in some cases, two peaks of conidia were found, as on10 May, 1994 (Fig. 3A) or on 27 May, 1995 (Fig. 4A).In any case, the dynamics of spore sampling after rainhad ceased was related to wetness and relative humidi-ty: spores continued to be sampled in the presence ofwetness, with high RH, and their density strongly de-creased at the end of a wet period or when RH dropped(Figs 3 and 4).

Effect of meteorological variables on the density ofthe airborne conidia. Pearson’s coefficients of correla-tion between the cumulative number of conidia sam-pled daily and the correspondent meteorological vari-ables were calculated for all days, and for rainy and nonrainy days, separately (Table 1). Dummy variables forthe year were included in the calculation of the coeffi-cients of correlation, when they had a significant effect;these variables reduced the effect of different sporedensities in different years.

Air temperature (T and Tmax) was significantly cor-related to the density of the conidia sampled, but onlyon the rainy days. Relative humidity was also signifi-cantly correlated to the conidia sampled from the air,particularly for the variables accounting for high RHduring days with no rainfall (RHmax, RH80, RH90): onthese days, the number of spores increased as the hu-midity increased. No linear relationship was found be-tween characteristics of rainfall (total rainfall, rain dura-tion or intensity) and density of the spores sampled onthe same rainy day; on the contrary, total rainfall(Rtot_P) and maximum intensity (RintMax_P) of therain that fell on the day preceding spore sampling weresignificantly correlated with density of airborne conidia;this occurred on either rainy or dry days, though for thelatter the coefficients of correlation were higher.

Modelling the effect of environment on the dailydensity of airborne conidia. A stepwise regressionanalysis was applied to select the minimum set of inde-pendent variables (meteorological variables listed inTable 1, empirical weight, dummy variables) to be usedin estimating the daily number of airborne conidia (de-pendent variable). After some preliminary analyses, theregression procedure was applied for rainy and nonrainy days, separately. The following models were thenselected:

Y’ = -839.7 + 410.3·W + 4.08·T2 ++ 115.45·RintMax_P – 455.9·Y95 [1]

Y’’ = -682.3 + 45.68·T + 21.5·RH80 + 107.0·Rtot_P[2]

where:– Y’ and Y’’ are the estimated numbers of conidia per

m3 air per day, in the days with and without rainfall,respectively;

– W is an empirical weight assigned to each day in re-lation to its position in a sequence of n successiverainy days, as follows: first rainy day = 1.1, secondrainy day = 2.5, third rainy day = 1.2, fourth or laterrainy day = 0.8 (Fig. 2);

– T is the average air temperature (°C);


Rain Conidia RH

25 to 27 May, 1995

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Fig. 4. Number of Fusarium macroconidia sampled from theair above wheat canopies in each hour of the day during some3-day periods in 1995 and 1996, in relation to rainfall (R) andrelative humidity (RH).

– RintMax_P is the maximum intensity of rain (mmhour-1) in the preceding day;

– Y95 is the dummy variable for the year 1995, equalto zero (for the years 1994, 1996 and 1997) or 1 (for1995);

– RH80 is the number of hours with RH > 80%;– Rtot_P is total rainfall (mm) on the preceding day.

The two equations accounted for 59% and 57% ofthe experimental variance, respectively (Table 2). Forboth equations, standard errors of model parameterswere small, and no systematic deviations occurred inresidual distribution over the range of variation of ei-ther the dependent variable or each independent vari-able (not shown). The mean standard error of estimateswas equal to 394 and 291 conidia, respectively; theywere sufficiently small compared to the range of varia-tion of the conidia sampled, which was 2997 and 1891on rainy and non rainy days, respectively.

In the equation [1], the empirical weight assigned onthe basis of the position of the day in a rain event of twoor more days was the most relevant variable influencingthe number of airborne spores (Table 2): this accountedfor 50% of the total variance accounted for by the mod-el. T was more influential (26% of total variance) thanRintMax_P (13%). An increase in either T or Rint-Max_P resulted in an increase in the number of airborneconidia, but an increase of 5.3°C was necessary to pro-duce the same effect on the spore density as a rain inten-sity of 1 mm h-1 on the preceding day. The negative in-

fluence of the year 1995 on the number of conidia sam-pled accounted for the low spore density found duringthe sampling season of this year, so that when the otherindependent variables did not change, the number ofconidia was lower by 456 in 1995 than in the other years.

In equation [2], 78% of the total variance accountedfor by the model was ascribed to the total amount ofrain that fell on the preceding day (Table 2); number ofhours with RH > 80% accounted for a greater part ofthe remaining variance compared to T. The number ofairborne conidia increased as Rtot_P or RH80 in-creased; two more hours of high RH were necessary toincrease the number of spores sampled as much as anincrease of 1°C in the mean temperature.

To evaluate the accuracy of the two equations in esti-mating the daily number of airborne conidia, the rightequation (Y’ or Y’’ according to rainfall) was workedout to calculate the estimated spore number on eachday of the sampling season, and compared with the ac-tual numbers. The coefficient of correlation betweenactual and estimated values was equal to 0.79 (P <0.001), and the regression line fitting these pairs of datahad intercept and slope not significantly (at P < 0.001)different from zero and one, respectively (not shown).Thus, these models accurately estimated the actual pat-tern of the airborne conidia over the sampling season inthe four years considered (Fig. 5). The most relevant er-rors were observed at the beginning of the sampling pe-riod in 1995 (Fig. 5B), in concomitance with repeatedheavy rainfall.


Table 1. Coefficient of linear correlation between the number of Fusarium macroconidia sampled daily from the air above thewheat canopy and correspondent values of the meteorological variables.

Minimum air temperature (°C), total rainfall (mm), duration of rainfall (hours), average and maximum rain intensity (mm h-1) were always notsignificant. *, ** and *** indicate significance at P < 0.05, 0.01 and 0.001, respectively.a The coefficient of correlation was calculated including dummy variables for the year.

Variable Rainy days

n=35

Non rainy days

n=49

All days

n=84

T average air temperature (°C) 0.37* 0.04 0.01

Tmax maximum air temperature (°C) 0.36* 0.10 0.04

RH average relative humidity (%) 0.15 0.23 0.33**

RHmin minimum relative humidity (%) 0.09 0.11 0.25*

RHmax maximum relative humidity (%) 0.52a** 0.32* 0.35**

RH80 hours with relative humidity > 80% 0.07 0.31* 0.54a***

RH90 hours with relative humidity > 90% 0.07 0.38** 0.31**

Rtot_P total rainfall of preceding day (mm) 0.51a** 0.68*** 0.64a***

Rdur_P rainfall duration of preceding day (hours) 0.20 0.64*** 0.64a***

RintMax_P maximum rain intensity of preceding day (mm h-1) 0.59a*** 0.62*** 0.67a***

DISCUSSION

The present work shows the seasonal dynamics ofthe airborne population of Fusarium macroconidia inwheat fields with natural inoculum, and relates thesedynamics to the concomitant environmental conditions.In previous works, artificial sources of inoculum pro-vided for spores of one Fusarium species, so that suchspecies was predominant in the spore samplings (Jugnetet al., 1993; Fernando et al., 2000). To determine thedensity of airborne conidia in the air, a spore samplerwas used that sucked air with a constant flow and col-lected the particles in the air on an adhesive tape, whichwas observed by a microscope to enumerate Fusariummacroconidia. Thus, the numbers that appeared incomputations referred to the conidia suspended in theair or in water droplets small enough to be wind-car-ried. On the contrary, the conidia carried by the largesplash-drops originating from rain drops should nothave been caught. This spore sampler did not allow adistinction to be made between the Fusarium speciessampled because of similarities between the macroconi-dia of a number of species (Nelson et al., 1983). Thus,spore counts referred to a population which could in-clude both the main Fusarium species causing FHB andother less important species. To have an estimate of theprevalence of the main species in this airborne popula-tion, fungal species grown on Petri plates exposed nearto the spore sampler were identified: the frequency ofthe minor Fusarium species was unimportant compared

to that of M. nivale, F. graminearum, F. avenaceum, F.culmorum, and F. poae. So, it is reasonable to believethat these species were prevalent in the air during thisstudy.

An association between rainfall and peaks of themacroconidia sampled from the air was found. In par-ticular, no or a very few conidia were sampled from theair before rainfall, but their number progressively in-creased with the beginning of a rain event; in the pres-ence of high humidity, conidia continued to be sampledat high densities for some hours after rain had ceasedand they usually reached their peak under these condi-tions. Finally, density of the airborne conidia rapidlydecreased when relative humidity dropped. This pat-tern was consistent over the sampling season in the fouryears considered, so that the meteorological variablesmentioned (rainfall and relative humidity) had a signifi-cant effect on spore counts: total amount, duration andintensity of a rain event positively influenced the num-ber of conidia sampled after such event had ceased;high RH and length of periods with high RH were posi-tively correlated with the number of spores sampledduring such periods. The observed effect of rainfallagreed with the data shown by Fernando et al. (2000)and Jugnet et al. (1993). In the first work, there weretwo peaks of airborne spores of F. crookwellense, bothoccurring on first and second day after a rain event, onepeak of F. equiseti that occurred on the first day afterrainfall, and three peaks of F. graminearum, two ofthem following a rain event. In the second work, peaks


Table 2. Parameters and statistics of the two regression models fitting the relationships between the daily number of Fusariummacroconidia sampled from the air and some influencing variables.

a Standard error.b Adjusted for the number of independent variables.

Variables Parameter SEa ofparameters

% of totalvariance

Plevel

R2 R2

adjustedbSE ofestimates

Rainy days (≥ 0.2 mm rain)W weight based on position

in a sequence of rainfalls 410.300 142.0600 50 0.007 0.585 0.530 494

T2 average air temperature(°C)

4.083 1.3535 26 0.005

RintMax_P maximum rain intensity of thepreceding day (mm h-1)

115.450 41.0840 13 0.009

Y95 dummy variable for theyear 1995

-455.900 108.8300 11 0.037

Non rainy daysT average air temperature

(°C) 45.680 19.7530 1 0.025 0.568 0.539 291

RH80 hours with relativehumidity > 80%

21.500 6.9900 21 0.004

Rtot_P total rainfall of thepreceding day (mm)

107.000 15.6300 78 0.000

of F. culmorum macroconidia at the head height oc-curred on May 16, 18-19, and 25, with rain events onMay 15, 17 and 19 to 24.

Two phenomena could explain the effect of rainfall

on the increased number of airborne conidia. One pos-sibility is that rainfall incited this increase throughfavouring sporulation on the infected plant tissues;however, the short delay between the beginning of arain event wetting the inoculum sources and the in-crease in the airborne conidia observed did not supportthis hypothesis. In addition, production of macroconi-dia does not depend on wetting, being more abundanton a substrate with –10 to –40 bar than with 0 bar(Sung and Cook, 1981). Another possibility is that rain-fall dispersed conidia previously produced on the in-oculum sources. Fusarium macroconidia are formed inmucilaginous masses in sporodochia; therefore, rain isneeded to liberate them, as demonstrated by Stepanov(1935) and by Jenkinson and Parry (1994); these Au-thors removed macroconidia in the splash-dropletsoriginating from water drops falling onto either sporu-lating cultures or infected sporulating wheat stems. It isknown that a rain drop falling on a sporulating surface,like a sporodochium, produces both large and smallsplash-droplets (Madden, 1992): larger slash-drops fol-low short vertical and horizontal ballistic trajectories,while smaller droplets become airborne by means of aircurrents (Fitt et al., 1989). Since the spore sampler usedin this work was not designed to measure splash-dis-persed spores, it can be assumed that the spores caughtbecame airborne mainly by means of small droplets car-ried by air turbulence: since peaks in spore counts con-stantly occurred after rainfall, spore-carrying dropletsoriginating from raindrops probably remained in aircurrents for some hours after rain had ceased; high en-vironmental humidity probably prevented the evapora-tion of such droplets and favoured their persistence inthe air within the crop canopy. This behaviour agreedwith that of the splash-dispersed pathogens Pseudocer-cosporella herpotrichoides (Fitt and Nijman, 1983; Fittand Brainbridge, 1983; Fitt and Lysandrau, 1984), Sep-toria nodorum (Faulkner and Colhoun, 1976; Wale andColhoun, 1979; Brennan et al., 1985) and Rynchospori-um secalis (Ayesu-Offei and Carter, 1971; Stedman,1980; Fitt et al., 1988): spore-carrying droplets werecaptured by air currents and dispersed into the air far-ther than their ballistic trajectory measured in still air;these droplets remained into the air also after the rainhad ceased, and a few spores became airborne afterdroplet water had evaporated.

In some cases, a second rain event which followed apreceding rainfall triggered the dispersal of high num-bers of Fusarium macroconidia (Fig. 3B, 3C). The up-ward movement of spores within the wheat canopy by asequence of rain splashes could explain this finding.Ooka and Kommendahl (1977) showed that many coni-dia of F. moniliforme are present in the rain water col-


Fig. 5. Numbers of Fusarium macroconidia sampled dailyfrom the air above wheat canopies over 3-week periods in1994 (A), 1995 (B), 1996 (C) and 1997 (D). Spore numberswere plotted as actual values (filled lines) and estimated val-ues (dotted lines), the latter calculated by two regressionequations (equations [1] and [2] of Table 2).

Sampling days

Con

idia

per

m3

air

(x10

0)

–––– Actual - - - - Estimated

lected from the surface of corn leaves after rainfall hassplashed such conidia. It is therefore possible that afirst rainfall splashed the conidia from the basal wheatplants to the upper leaves, so that the next rainfall re-splashed conidia from these leaves, so conidia becameairborne in greater numbers. For instance, the rainevent that occurred between 06.00 and 15.00 h, 18 May1994 (Fig. 3C), produced a few airborne macroconidiacompared to the rain that fell between 24.00 and 01.00h: a film of water covering leaves between these tworain events, as measured by the leaf wetness sensor,probably contained conidia which became airborne af-ter the second rainfall.

At the end of the sampling season, the number of air-borne conidia sampled during isolated rainfall was high-er than before, and high numbers remained airborne forsome time after rainfall had ceased. This was possibly re-lated to the presence of sporodochia on infected headtissue that had been infected at flowering. Ooka andKommendal (1977) showed that a gentle air currentpassing over corn kernels infected by Fusarium speciescan dislodge and carry conidia; thus, it is possible that,in cases like that observed on May 26 1995 (Fig. 1B),wet conditions caused by rainfall favoured abundantspore production on the scabbed head parts (Andersen,1948; Wiese, 1977), and that these conidia became air-borne because of air currents. This finding agreed withFernando et al. (1997), who demonstrated a downwindmovement of conidia from sporodochia formed on theheads that had been inoculated with F. graminearum atflowering, even though these macroconidia did not ap-pear to have caused secondary infections, due to the re-duced susceptibility of ripening heads.

The two regression equations produced estimates ofthe number of conidia sampled during rainy and nonrainy days, respectively; they accounted for the influenceof the previously described factors on the pattern of air-borne macroconidia. In equation [1], an empiricalweight (W) accounted for the fact that, during sequencesof rainy days, the number of spores sampled was con-stantly higher than that of an isolated rain event. Rint-Max_P (in equation [1]) and Rtot_P (in equation [2])accounted for the effect of rainfall on the number ofspores sampled after rain had ceased. In equation [2],RH80 accounted for the influence of prolonged humidperiods on spore counts. Mean air temperature (T) wasincluded in both equations; however it was not clear ifthere was a direct effect on spore counts of the high Tregimes which occurred at the end of the sampling sea-son, or an indirect effect due to the presence ofsporodochia that appeared late in the season on head tis-sue that had been infected at flowering. A dummy vari-able for the year 1995 was also included in equation [1],

which accounted for the low density of the airborneconidia found in this year. Understanding the reasonsfor this effect is not easy. Probably, factors like abun-dance of inoculum sources or rate of spore productionon such sources should be investigated. In any case, thesignificant effect of this dummy variable indicated thatthe pattern of airborne conidia as a function of W, T andRintMax_P was not influenced by the density of conidia.

The two regression models accounted for about onehalf of the experimental variance; this was due to the factthat differences between actual and estimated numbersof conidia were sometimes high (Fig. 5). So the modelswere not very accurate in estimating the exact numbersof conidia sampled from air, but they accurately deter-mined the dynamics of Fusarium airborne macroconidiabased on the meteorological conditions, as periods withlow spore densities and peaks (Fig. 5). Future workshould be aimed at verifying the accuracy of such equa-tions under different environmental conditions.

The present work produced new information on theenvironmental conditions favouring the presence of aform of inoculum for FHB in the air of a wheat crop,the Fusarium macroconidia. Thus, it completes previ-ous knowledge on another form of inoculum, as-cospores of G. zeae. Both sets of information are usefulfor defining the risk of FHB infection, especially in thewheat-growing areas where the Fusarium species pro-ducing exclusively or prevalently macroconidia are notless important than G. zeae in causing the disease. Fur-thermore, an estimate of the risk for FHB must com-bine information on the abundance of both forms of in-oculum with information on the relationships betweenenvironmental conditions and the rate of infection(Rossi et al., 2001). Actually, the density of inoculumalone is not sufficient for estimating the risk of infec-tion, because, as shown in the present work, the num-ber of spores sampled in each season was not directlycorrelated with FHB incidence. For instance, the small-er numbers of conidia sampled in 1995 caused more in-fection than the large numbers found in 1994, becausethe former spores developed under more repeated wetconditions which were more conducive to infection(Rossi et al., 2001).

ACKNOWLEDGEMENTS

This research was supported, in part, by funding fromthe CNR (Consiglio Nazionale delle Ricerche, coordi-nate project EPIFUS) and the Fondazione Invernizzi.We thank A. Libè for operating the spore sampler, S.Pasquini for his contribution in counting spores, and R.Bottazzi for her assistance in assessing the disease.


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Received 3 February 2001Accepted 21 December 2001

DYNAMICS OF AIRBORNE FUSARIUM MACROCONIDIA IN WHEAT … · Experimental fields and FHB...

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Transcript of DYNAMICS OF AIRBORNE FUSARIUM MACROCONIDIA IN WHEAT … · Experimental fields and FHB...