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Modelling the frequency and severity of root and foot diseases in winter wheat monocultures
Eur. J. Agron., 1995, 4(2), 217-227
Modelling the frequency and severity of root and foot diseases in winter wheat monocultures N. Colbach and P. Huet* INRA-Agronomie, Centre de Grignon, F-78850 Thiverval-Grignon, France.
Accepted 2 February 1995
* Abstract
To whom correspondence should be addressed.
From 1986 to 1993, wheat crops from plots which had been cultivated with cereals for various lengths of time were assessed for the major foot and root diseases : eyespot (Pseudocercosporella herpotrichoides), take-all (Gaeumannomyces graminis) and sharp eyespot (Rhizoctonia cerealis). For each disease, mean frequency and severity were modelled as a function of the number of years of continuous cereal cropping. Both take-all and eyespot increased during the first 3 to 5 years of monoculture before disease decline was observed. Decline was more important for take-all severity than frequency, whereas it was considerably stronger for eyespot frequency than severity. Take-all decline started sooner than eyespot decline. Model quality was highest for eyespot frequency and lowest for take-all frequency and severity. The incidence of sharp eyespot was too low to observe any influence of crop succession. We observed however an important year effect and a negative correlation with eyespot. Key-words : Pseudocercosporella herpotrichoides, Gaeumannomyces graminis, Rhizoctonia cerealis, cereal monoculture, disease decline, modelling.
INTRODUCTION The most important foot and root diseases of winter wheat in Northern Europe are eyespot (Pseudocercosporella herpotrichoides (Fron) Deighton), sharp eyespot (Rhizoctonia cerealis Van der Hoeven) and takeall (Gaeumannomyces graminis (Sacc.) von Arx and Olivier var. tritici (Walker)). The former two infect first the sheaths and later the tiller bases of the host plants and the latter is responsible for black lesions on both seminal and nodal roots. If no suitable host plants are available, these pathogens survive as saprophytes on host residues for a limited period (Steinbrenner and Hoflich, 1984). A high proportion of host crops, mostly cereals, in the succession should therefore increase disease. This has been confirmed in the short term (Glynne and Slope, 1959; Steinbrenner and Htiflich, 1984). However, a decrease of take-all after a period of 3 to 4 years of severely infected cereal crops, has been observed by numerous authors in Great-Britain (Glynne, 1935 ; Shipton, 1972, 1975), France (Lemaire and Coppenet, 1968), Ireland (Cunningham, 1975), the Netherlands ISSN Jl6l-030l/95/02/$ 4.00/ © Gauthier- Villars - ESAg
(Gerlagh, 1968), Denmark (Jensen, 1975), Switzerland (Zogg, 1967; Vez, 1975), Germany (Gliemeroth and KUbler, 1972). There have been fewer studies on eyespot decline (Glynne, 1935 ; Glynne and Slope, 1959; Vez, 1975) and the pathogen population has evolved considerably during the last years as shown by the development of fungicide resistances (King and Griffin, 1985 ; Maraite and Weyns, 1986 ; Leroux and Gredt, 1988 ; Cavelier et al., 1992). Disease decline seems not to have been observed for sharp eyespot. The analysis of this disease is furthermore complicated by the possible · interactions with P. herpotrichoides which seems to dominate the sharp eyespot fungus (Obst et al., 1977; Reinecke and Fehrmann, 1979 ; Van der Hoeven and Bollen, 1980; Cavelier et al., 1985). Moreover, not only the pathogen populations, but also the cultivation techniques have changed greatly since the above mentioned results were published. In most of these trials, the wheat crop assessed for diseases was furthermore not cultivated uniformly, since techniques such as sowing date or soil tillage depend on crop succession. There is therefore an
218
N. Colbach and P. Huet
important risk of confusing crop succession effects and, for example, those due to changes in sowing date in recent years.
Table 2. Trial design : plots with continuous wheat cultivation assessed for diseases from 1986 to 1993
The aim of our work was to follow disease evolution as well as pathogen interactions on cereal monocultures for several years and to describe disease level, if possible, as a function of the number of years of continuous cereal cultivation. Our field trial compared each year the disease levels of plots on which wheat had been cultivated for a variable number of years. To assure that disease assessment would only express crop succession effects, all wheat crops of a given year were cultivated uniformly, whatever the preceding crops.
Year(s) of continuous wheat cultivation
2
3
4
X
X
5
6
7
8
10
9
Year
1986 1987 1988 1989 1990 1991 1992 1993
X X X X X X X X
X
X
X
X
X X
X
X X
X
X
X
X
X
X
X
X
X
X denotes presence in that year of wheat grown for I ,2 .. 10 years continuously.
MATERIALS AND METHODS Field trial
As for a given year not every duration of continuous wheat cultivation was represented, there was the possibility of confusing the year effect and the year x monoculture duration interaction (Huet and Recamier, 1986). This risk was however limited as every year 3 to 5 different degrees of monoculture were present and each degree existed at least for one year. The year x monoculture duration interaction cannot be analyzed in this work.
Table 1 shows the various crop successions of our field trial at Grignon from 1980 to 1993. From 1986 to 1993, nearly all wheat crops were assessed for foot and root diseases. We had therefore wheat crops available, corresponding to different lengths of cereal monoculture (Table 2), assuming that the spring barley of succession 2 in 1984 did not interrupt monoculture (Shipton, 1972, 1975).
Table 1. Crop succession of the Grignon field trial
Succession
2
5
7
9
11
13
15
pot.
w.w.
luc. + coc.
luc. + coc. pot.
w.w.
s.b.
s.b.
luc. + coc. luc. + coc.
pot.
w.w.
w.w.
s.b.
luc. + coc. luc. + coc.
Year
1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993
s.b.
pot.
luc. + coc. luc. + coc.
pot.
w.w.
s.b.
luc. + coc.
pot.
w.w.
pot.
w.w.
s.b.
luc.
luc.
luc.
w.w.
s.b.
w.w.
s.b.
luc.
luc.
luc.
pot.
w.w.
w.w.
w.b.
luc.
luc.
luc.
luc.
w.w.
w.w.
w.w.
luc.
luc.
luc.
luc.
w.w.
w.b.
w.w.
w.w.
luc.
luc.
luc.
w.w.
w.b.
luc.
w.w.
w.w.
luc.
luc.
w.w.
w.b.
luc.
luc.
w.w.*
w.w.
luc.
w.w.
w.b.
luc.
luc.
luc.
w.w.*
w.w.
w.w.
w.w.
luc.
luc.
luc.
luc.
w.w.*
w.w.
w.w.
w.w.
luc.
luc.
luc.
w.w.
w.w.
luc.
w.w.
w.w.
luc.
luc.
w.w.
w.w.
w.w.
luc.
w.w.
luc.
luc.
w.w.
w.w.
w.w.
w. w. = winter wheat, w.b. = winter barley, s.b. = spring barley pot. = potato, luc. = lucerne, coc. = cocksfoot All wheat crops between 1986 and 1993 were assessed for foot and root diseases except those marked*.
Eur. J. Agron.
Root and foot diseases in wheat monocultures
Each succession was tested in a randomized block design with four replications ; plot size was 17 m x 5.25 m. Each year, all wheat plots were sown on the same day (about mid-October) and at the same density (about 300 grains per m 2 ) in rows 0.16 m apart. The wheat cultivar was Fidel which is not resistant to the assessed diseases. Soil tillage (plough and shallow tillage), herbicide and insecticide treatments were the same whatever the plot. No fungicide or growth regulator was used. Nitrogen was applied at the rate of about 180 kg ha- 1 after wheat and 160 kg ha- 1 after lucerne. Together with soil nitrogen residues and mineralization, all wheat crops therefore had approximately an equal quantity of total nitrogen available.
219
potato-dextrose-agarose contammg antibacterial antibiotics. Incubation period was about 10 days at 20 ac. Statistical analysis
To analyse disease level, we used the General Linear Model (GLM procedure) of the SAS software program (Statistical Analysis System, SAS Institute Inc, 1989) for our analysis of covariance. For the foot diseases, the percentage of diseased tillers as well as the severity score ; for take-all, the percentage of diseased plants and the sum of necrosed root length per plant, were the output variables. The tested (initial) model was as follows :
On every plant (for all diseases) and on every tiller (only for foot diseases) absence or presence were noted visually. All diseased tillers were sectioned at the height of the necrosis and classified according to the necrosed section part :
disease = constant + year effect + f(x) + block effect + error) (E) where f(x) is a function representing disease level as a function of monoculture degree x. The covariable tiller number per plant was introduced into foot disease models to take into account wheat population influences such as separating diseased sheaths from older tillers during tiller emergence and thus limiting disease transmission (Glynne, 1951 ; Huet, 1986). The sharp eyespot models contained the covariable % of tillers with eyespot because of the interaction between sharp eyespot and eyespot, the latter dominating the former.
class 1 : necrosed section part less than 10 per cent of total section area.
If we suppose that disease increases, passes through a
Measurements
At flowering, the plants in four randomly placed quadrats of 0.5 m x 2 rows in each plot were sampled with a spade. In each quadrat, 12 randomly chosen plants were assessed for foot and six for root diseases.
There are different possibilities for the function f(x).
class 2 : necrosed section part more than 10 per cent and less than 30 per cent of total section area.
maximum and decreases until stabilizing at an asymptote value, then the following equation is appropriate :
class 3 : necrosed section part more than 30 per cent and less than 60 per cent of total section area.
j{x)=ax2+bx
class 4 : necrosed section part more than 60 per cent of total section area.
2
X
+C
A severity score equivalent to the mean necrosed section part was then calculated for each plot and every disease, with the following formula where the percentages of diseased tillers of each class are weighted by their median necrosed sections :
We did not have enough values for high monoculture degrees to be able to evaluate correctly the asymptote value a. Furthermore, this is a non-linear model for which the statistics may only be correctly calculated for a large number of points.
%mean necrosed section = (0.05% tillers of class 1 + 0.2 X% tillers of class 2 + 0.45 X% tillers of class 3 + 0.8 X% tillers of class 4)/total % of necrosed tillers.
We therefore preferred a more simple model with a limited application domain, but more robust in this domain. A second-degree equation fix) = a . x + b • i (1) might be suitable in those cases where pre-maximum increase and post-maximum decrease are symmetric. If increase is faster than decrease, a modified second-degree equation flx) = 2 a. ln(x) + b. (ln(x)) (2) where ln(x) is the logarithm of x, might be suitable. If however pre-maximum increase is slower, then the equation flx) = a. exp(x) + b · (exp(x)) 2 (3) should be chosen.
On nodal roots, the length of each take-all necrosis was measured and summed to give the necrosed root length per plant, representing the severity of take-all infection. As plants were sampled with a spade, the sampled root length was approximately 10 em. In 1993, eyespot forms P. herpotrichoides var. herpotrichoides and P. herpotrichoides var. acuformis were identified in vitro at flowering + 350 degree-days (basis 0 °C). For each plot and disease, 30 diseased tillers were superficially disinfected and incubated on Vol. 4,
0°
2- 1995
For each disease, three different versions of the initial model (E), where f( x) was respectively replaced by the equations (1), (2) or (3), were tested. Only the
220
N. Colbach and P. Huet
dered the contribution due to the factor or covariable as not significant. The sum of squares used to calculate the probability values for each factor or covariable was adjusted to all terms present in the model and did thus not depend on their order of appearance in the model (type III sum of squares of the GLM procedure).
models explaining most of the variability (giving the greatest ? and F value) were retained and discussed. As noted earlier, the interaction year x monoculture duration could not be analysed on this trial as the experimental design did not permit a correct evaluation of this interaction. Where the condition of variance homogeneity necessary for a linear model was not fulfilled, the Box and Cox transformation (Box et al., 1978) was used: if the relation between mean and variance (of a given variable for each experimental treatment) ln(variance) = a + b.ln(mean) was significant, then the necessary transformation was as follows : transformed variable
RESULTS
Take-all
= variable (1 - b/2!
The model retained to explain the percentage of diseased plants (Table 3) was the following: % plants with take-all = constant + year effect + 2 a. ln(x) + b. (ln(x)) + block effect where a > 0 and b < 0.
The final model contained only those factors and/or covariables for which the probability values of the statistical zero hypothesis test were less than 5 per cent. If these values were greater than 5 per cent, we consi-
Table 3. Linear model retained to explain the percentage of plants with take-all (Analysis of variance table and estimations for significant effects)
SOURCE MODEL ERROR CORRECTED TOTAL EFFECTS year In( monoculture) (ln(monoculture)) 2 block
degrees of freedom
sum of squares
mean square
F value
Pr > F
?
12 89 101
14756 26375 41131
1129 296
4.15
0.0001
0.36
7
6495 4370 2595 2711
927 4370 2595 903
3.13 14.76 18.77 3.05
0.0053 0.0002 0.0040 0.0327
1 3
Sum of squares for the various effects are adjusted to all the terms of the model (type III sum of squares of GLM procedure of SAS).
ESTIMATORS OF THE FACTOR AND COVARIABLE EFFECTS constant
64.6
ESTIMATIONS FOR THE FACTORS YEAR AND BLOCK* Year estimation Year 1986 -13.3 1990 1991 1987 12.4 1988 1992 4 -3.7 1993 1989
estimation 11.3 -0.34 -5 -5.5
ESTIMATIONS FOR THE COVARIABLE PARAMETERS Covariable parameter ln(monoculture) : a (In( monoculture) )2 b
estimation 28.3 -10.4
Block I 2 3 4
estimation 4.3 5 -8.4 0.86
The final linear model was : % plants with take-all~ constant+ year effect+ a. ln(monoculture) + b. (ln(monoculture)f + block effect+ error. * The sum of the estimations for each factor is nil.
Eur. J. Agron.
221
Root and foot diseases in wheat monocultures
Infection level at the first year of monoculture was already high (mean = 64 per cent of infected plants). The mean maximum was at x = 3.9 (standard-error= 0.6) with 84 per cent of diseased plants and at the tenth year of monoculture, mean infection level was at 74 per cent, which is halfway between initial and maximum level. The post-maximum disease evaluation was however less precise as it was only based on 1 to 2 years disease data whereas the pre-maximum evaluation was based on 4 years data. Figure 1 confirms that infection level increased during the first years of monoculture when the influence of parameter a was predominant. When parameter b began to dominate, disease increase slowed down, passed through a maximum and then decreased. The model retained for the sum of necrosed root length (Table 4) was similar except that it did not contain a block effect. This model, similar to that shown in Figure 1, show a similar but more pronounced trend. The mean necrosis sum was 2.3 em for
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60
2
1
3
2
4
5
6
8
7
9
10
years with continuous wheat
Figure 1. Take-all evolution in wheat monoculture. Disease fre= 0.35) as a func0.36) and severity(---. quency(~ tion of the number of years with continuous wheat culture.
r
r=
Table 4. Linear model retained to explain the sum of root length necrosed by take-all (Analysis of variance table and estimations for significant effects)
SOURCE MODEL ERROR CORRECTED TOTAL EFFECTS year ln(monoculture) (ln(monoculture) )'
degrees of freedom
sum of squares
mean square
F value
Pr > F
9 92 101
36075 67206 103281
4008 731
5.49
0.0001
7
25101 9880 6929
3585 9880 6929
4.91 13.53 9.49
0.0001 0.0004 0.0027
0.35
Sum of squares for the various effects are adjusted to all the terms of the model (type III sum of squares of GLM procedure of SAS).
ESTIMATORS OF THE FACTOR AND COVARIABLE EFFECTS 2.34
constant ESTIMATIONS FOR THE FACTOR YEAR* Year 1986 1987 1988 1989
estimation - 1.57 0.17
-1.3 -0.25
ESTIMATIONS FOR THE COVARIABLE PARAMETERS Covariable ln(monoculture) : (ln(monoculture)) 2
Year 1990 1991 1992 1993
estimation 0.97 -0.894 -1.09 3.96
parameter a b
estimation 4.25 -1.7
2 The final linear model was: sum of necrosed root length per plant (em)+ constant+ year effect+ a. ln(monoculture) + b. (ln(monoculture)) +error. * The sum of the estimations for each factor is nil.
Vol. 4, n° 2- 1995
N. Colbach and P. Huet
222
the first year of monoculture, 4.9 em for maximum at x = 3.5 (standard-error = 0.5) and 3.1 em at the tenth year. The post-maximum decrease was faster for disease severity than for frequency. The variability explained by these two models was low : 35 per cent for the frequency model ( / = 0.35) and 36 per cent for the severity model. For neither model was the distribution of residuals normal at a = 0.05, but it was not more asymmetric than the normal residual distributions observed for the other diseases (Table 5).
Table 5. Residual distribution for the various disease indicators
VARIABLE
normality (I)
symmetry (2)
0.0362 0.0124 0.4129 0.1619 0.0072 0.0793
-0.7152 0.7922 -0.1502 -0.5220 -0.0204 0.4454
take-all frequency take-all severity eyespot frequency eyespot severity sharp eyespot frequency sharp eyespot severity
(I) probability associated to the null hypothesis 'the distribution is normal'.
(2) measure of skewness : the closer to zero, the more symmetric the distribution.
Eyespot The model retained to explain the percentage of tillers with eyespot (Table 6) was similar to the abovedescribed ones :
% tillers with eyespot 2
= constant
+ year effect +
a. ln(x) + b. (ln(x)) + c.tillers per plant where a > 0; band c < 0.
Table 6. Linear model retained to explain the percentage of tillers with eyespot (Analysis of variance table and estimations for significant effects)
SOURCE MODEL ERROR CORRECTED TOTAL EFFECTS year In (monoculture) (In (monoculture)}' tillers per plant
degrees of freedom
sum of squares
mean square
F value
Pr > F
(2
10 91 101
70154 32397 102551
7015 356
19.71
0.0001
0.68
7
15224 23254 12102 1928
2174 23254 12102 1928
6.11 65.32 33.99 5.42
0.0001 0.0001 0.0001 0.0221
Sum of squares for the various effects are adjusted to all the terms of the model (type III sum of squares of GLM procedure of SAS).
ESTIMATORS OF THE FACTOR AND COVARIABLE EFFECTS constant ESTIMATIONS FOR THE FACTOR YEAR* Year 1986 1987 1988 1989
48.8
estimation -4.4 15.4 -6.4 -6.0
ESTIMATIONS FOR THE COVARIABLE PARAMETERS Covariable ln(monoculture) : (ln(monoculture) )2 tillers per plant :
Year 1990 1991 1992 1993
estimation 2.8 16.1 -2.2 -27.2
parameter a
estimation 67.2 -22.5 -13.8
b c
* The sum of the estimation for each factor is nil. The final linear model was: % tillers with eyespot + constant+ year effect+ a. ln(monoculture) + b. (ln(monoculture)) 2 + C. tiller number per plant+ error. Eur. ]. Agron.
223
Root and foot diseases in wheat monocultures
Mean frequency (with a mean tiller number per plant of 1.9) was 23 per cent for the first year of monoculture, 73 per cent at the maximum x = 4.5 (standard-error = 0.5) and 58 per cent at the tenth year. The decrease in onset was later than for take-all (x = 4.5 is significantly different from x = 3.5 at a = 0.10) and was not sufficient to reach the halfway level between initial and maximum values. As for take-all, evaluation was less precise for post-maximum than for pre-maximum disease evolution because of our unbalanced data set.
80-r------------------,.-go
The severity model (Table 7) was different in so far as it directly contained the monoculture degree x and not the logarithm form ln(x). Furthermore, a Box and Cox transformation was required to homogenize variance. The covariable tillers per plant was not significant. Mean severity was 67 per cent for the first year of, monoculture, 76 per cent at the maximum x = 5.3 (standard-error = 0.4) and 65 per cent at the
m
-------
-- -----
' '
m 2
4
3
6
5
7
8
w
9
years with continuous wheat
Figure 2. Eyespot evolution in wheat monoculture. Disease frequency(~?= 0.68) and severity(---,?= 0.47) as a func-
tion of the number of years with continuous wheat culture.
Table 7. Linear model retained eyespot severity (Analysis of variance table and estimations for significant effects)
SOURCE MODEL ERROR CORRECTED TOTAL EFFECTS year monoculture monoculture 2
degrees of freedom
sum of squares
mean square
9 92 101
1.24. 10 19 1.42. 10 19 2.66. 10 19
1.37 . 10 18 1.54. 10 17
7
9.15. 10 18 4.33 . 10 18 3.67. 10 18
1.31 . 10 18 4.33. 10 18 3.67. 10 18
F value
Pr > F
?
8·9
0·0001
0-47
8-49 28·12 23·83
0·0001 0·0001 0·0001
Sum of squares for the various effects are adjusted to all the terms of the model (type III sum of squares of GLM procedure of SAS).
ESTIMATORS OF THE FACTOR AND COVARIABLE EFFECTS 4.08. 108
Constant ESTIMATIONS FOR THE FACTOR YEAR* Year 1986 1987 1988 1989
estimation -6.4- 106 7.6. 107 -4.7. 106 8 - 3.9. 108
ESTIMATIONS FOR THE COVARIABLE PARAMETERS Covariab1e monoculture : (monoculture) 2
Year 1990 1991 1992 1993
parameter
a b
estimation
-1.3. 108 5. 108 -2.2. 108 -1.3. 108
estimation 3.25. 10 8 -3.05. 107
* The sum of the estimation for each factor is nil. 2 A Box and Cox The final linear model was: % of necrosed section (I + 7.696/2) = constant+ year effect+ a · monoculture + b · (monoculture) + block effect+ error. -7.696. = b with significant is ln(mean) b. =a+ ln(variance) transformation (Box et al.. 1978) is necessary as the relation Vol. 4. n° 2- 1995
N. Colbach and P. Huet
224
transfonned % tillers with sharp eyespot = constant + year effect + block effect + a . tillers with eyespot + b • tillers per plant.
tenth year which is similar to the initial disease level. Overall, variations were therefore not very marked. These models, as well as Figure 2, show a similar evolution as for take-all : an increasing period, passage through a maximum, which was followed by a disease decrease. The model quality depended on the output variable : 68 per cent of variability were explained by the frequency model, but only 47 per cent by the severity model. Residual distribution was normal for both models (Table 5).
with a and b < 0. A Box and Cox transformation was necessary to homogenize variance. Crop succession had no influence on sharp eyespot. The covariables %tillers with eyespot and tillers per plant were negatively correlated with sharp eyespot, otherwise we only observed year and block effects. Mean frequency was low (3 per cent), and 34 per cent of variability was explained by the model. The model retained for sharp eyespot severity (mean value = 10 per cent), was similar to the above one (results not shown) but with lower r (0.28). Residual distribution was not normal, but symmetric for sharp eyespot frequency ; it was normal for severity (Table 5).
Only P. herpotrichoides var. herpotrichoides was isolated from the eyespot affected tissue in 1993. Sharp eyespot
The retained model for frequency (Table 8) was the following:
Table 8. Linear model retained to explain the percentage of tillers with sharp eyespot (Analysis of variance table and estimations for significant effects)
SOURCE MODEL ERROR CORRECTED TOTAL EFFECTS year block eyespot tillers/plant
degrees of freedom
sum of squares
mean square
F value
Pr > F
12 89 101
12.68 24.67 37.36
1.06 0.277
3.82
0.0001
7 3
7.08 3.23 2.05 1.61
1.01 1.08 2.05 1.61
3.65 3.90 7.40 5.81
0.0017 0.0117 0.0078 0.0179
0.34
Sum of squares for the various effects are adjusted to all the terms of the model (type 11I sum of squares of GLM procedure of SAS).
ESTIMATORS OF THE FACTOR AND COVARIABLE EFFECTS constant
1.49
ESTIMATIONS FOR THE FACTORS YEAR AND BLOCK* Year estimation Year 1986 -0.21 1990 1987 -0.33 1991 1988 0.23 1992 1989 -0.48 1993
estimation 0.27 0.29 0.19 0.03
ESTIMATIONS FOR THE COVARIABLE PARAMETERS Covariable parameter % tillers with eyespot : a tillers per plant : b
estimation -0.00565 -0.398
Block I 2 3 4
estimation -0.23 -0.072 0.28 0.016
* The sum of the estimation for each factor is nil. The final linear model was : % tillers with sharp eyespot (I - 1.665/2) = constant + year effect+ a · % tillers with eyes pot + b · tillers per plant + error. A Box and Cox transformation (Box et al., 1978) is necessary as the relation ln(variance) = a+ b .ln(mean) is significant with b = 1.665. Eur. J. Agron.
Root and foot diseases in wheat monocultures
DISCUSSION Diseases decline in monoculture : take-all and eyespot
Disease decline after a period of increasing disease for three to four years of cereal monoculture has already been observed for take-all by numerous authors. For eyespot however, there are few reports on a decline. Take-all decline is believed to result from a stimulation of antagonistic microflora, for instance Pseudomonas fiuorescens (Cook and Rovira, 1976). Mechanisms responsible for eyespot decline have not yet been identified, but microbiological antagonism might also be the reason for this effect (Diercks et al., 1970). However, our results on take-all differ from previous reports in that we observed a considerable takeall level in the first wheat and a slower disease decrease after maximum. The first difference may easily be explained : the first wheat was preceded by a lucerne crop which was usually heavily infested by spontaneous Gramineae such as Latium perenne. The above-named Gramineae may be infected by take-all and thus carry over Gaeumannomyces graminis inoculum (Garrett, 1941; Wehrle and Ogilvie, 1955; Coventry et al., 1989), while the introduction of one non-cereal crop in a monoculture cycle is sufficient to stop take-all decline and allow the disease to increase again (Zogg, 1976; Lucas et al., 1989). G. graminis inoculum is therefore already important before the first wheat is sown, whereas the associated antagonistic microflora is not able to grow under noncereal crops. This unbalance might also be the reason why post-maximum decrease was slow. On the other hand, microflora species and frequency in our trial were probably not the same as in other authors' fields. The unbalanced data set could also be the reason for the slow take-all decline : evaluation was less precise for post-maximum than for pre-maximum disease evolution. Take-all decrease might therefore be stronger than shown by our curves.
225
saprophytical survival of P. herpotrichoides and sporulation and therefore disease frequency. Infection and disease spread on the plant may only be affected if spore quality is impaired. Both take-all dissemination and infection are however within reach of soil microflora as the fungus spreads by mycelial growth towards the roots of new host plants (Prew, 1977). As P. fiuorescens needs a prior G. graminis infection on a plant before expanding and impairing further take-all development on this host (Samiguet et al., 1992a, 1992b), disease frequency is only slightly reduced by antagonistic activity whereas disease severity is considerably limited. Thus for take-all, not only is the observed disease extent limited, but the amount of infected plant residues and therefore next year primary inoculum are also lower than for eyespot. A longer period is therefore necessary for antagonistic microflora to limit eyespot. This might be the reason for the first difference between the two diseases. The longer saprophytical survival of P. herpotrichoides (2- 3 years ; Macer, 196la, 196lb; Steinbrenner and Hoflich, 1984) might also contribute to delayed eyespot decline. The short-distance dissemination mode of G. graminis might also explain the poorer fit of the models for this disease as well as the presence of block effects. Disease spreads irregularly and variability both within and between plots is therefore high. Furthermore, disease variability due to host population irregularities was partially taken into account for eyespot with the tiller number per plant covariable, reflecting phenomena such as separation of diseased sheaths from older tillers during tiller emergence (Glynne, 1951 ; Huet, 1986). Sharp eyespot : a disease with no observable decline
We also observed differences between take-all and eyespot: (a) the latter reached its maximum later; (b) disease decrease was only visible for frequency and severity may be considered constant (with regards to the observation precision) whereas take-all decline was more marked for disease severity than for frequency.
We were not able to demonstrate disease decline for sharp eyespot. Disease level was too low to detect any influence of crop succession, such as those reported by Colbach et al. (1994), even if it was corrected for P. herpotrichoides. This relation is reflected by the negative correlation between the two diseases which has been reported frequently (Obst et al., 1977 ; Reinecke and Fehrmann, 1979 ; Van der Hoeven and Bollen, 1980; Cavelier et al., 1985 ; Colbach et al., 1994). Both pathogens infect and therefore compete for the same tissues (Reinecke et al., 1979). Antagonism was reported in vitro, even if both fungi may be present on a same necrosis (Briick and Schlosser, 1982).
This last difference is an argument in favour of the existence of an antagonistic soil microflora as a cause for eyespot decrease : as Pseudocercosporella herpotrichoides is disseminated by spores carried by wind and rain drops (Fitt and Bainbridge, 1983 ; Fitt and Lysandrou, 1984), soil microorganisms may only limit
We have not been able to find any previous work explaining the negative correlation between sharp eyespot and the covariable tillers per plant. However as Rhizoctonia cerealis infects the same wheat organ as P. herpotrichoides, the same explanation as for eyespot might hold.
Vol. 4,
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CONCLUSION
For both fungi with high disease level and pathogenicity, i.e. take-all and eyespot, we were able to observe disease decline after a period of 3 to 5 years of disease increase in cereal monoculture. The length of this period and therefore the onset of the decline, as well as the importance of this decrease, might depend on (a) the length of saprophytical survival, and on (b) soil contact during dissemination as well as infection. It is possible that maximum disease level and both the onset of decline and its magnitude depend on the nature of those crops preceding the first cereal of the monoculture. These preceding crops are not only responsible for the amount of inoculum ready to infect the cereal crops, but they may also influence the frequency and the quality of antagonistic microflora which are responsible at least for take-all decline. It was not possible to conclude whether there was a decline in sharp eyespot. The disease level was too low to allow any significant influence. We observed however a strong interaction with P. herpotrtchoides. Whatever the influence of crop succession on disease level, all pathogens were strongly influenced by the year effect. Year effect, i.e. climatic conditions, not only influences disease on the assessed wheat, but also determine disease on the previous wheat crops and therefore the amount of primary inoculum at the beginning of the next wheat crop. This year effect should be further analysed by future work, using epidemiological models which, however, do not exist for these diseases. ACKNOWLEDGEMENTS
We thank Philippe Lucas (INRA-Rennes) for his help in improving this paper, Jacques Troizier (Domaine experimental de Grignon) for conducting our field trials and Beatrice Le Fouillen for technical assistance. REFERENCES Box G. E. P., Hunter W. G. and Hunter J. S. (1978). Statistics for Experimenters : an introduction to design, data analysis and model building. New York : Wiley. Briick K. P. and Schlosser E. (1982). GetreidefuBkrankheitserreger, V. Antagonismus zwischen den Erregem. Z. Pfianzenkr. Pfianzenschutz,89, 337-343. Cavelier N., Lucas P. and Boulch G. 1985. Evolution du complexe parasitaire constitue par Rhizoctonia cerealis et Pseudocercosporella herpotrichoides, champignons parasites de Ia base des tiges des cereales. Agronomie,S, 693-700. Cavelier N., Loree F. and Prunier M. (1992). Resistance of the eyespot fungus, Pseudocercosporella herpotrichoides, to DMI Fungicides. Proc. br. Crop. Prot. Conf, Pests Dis., 1, 189194.
N. Colbach and P. Huet
Colbach N., Lucas P. and Cavelier N. (1994). Influence des successions culturales sur les maladies du pied et des racines du ble d'hiver. Agronomie 14, 525-540. Cook R. J. and Rovira A. D. (1976). The role of bacteria in the biological control of Gaeumannomyces graminis by suppressive soils. Soil Biol. Biochem.,S, 269-273. Coventry D. R., Brooke H. D., Kollmorgen J. F. and Ballinger D. J. (1989). Increases in wheat yield on limed soil after reduction of take-all by fungicide application and crop rotation. Aust. J. exp. Agric.,29, 85-89. Cunningham P. C. (1975). Some consequences of cereal monoculture on Gaeumannomyces graminis (Sacc.) Arx et Olivier and the take-all disease. EPPO Bull., 5, 297-317. Diercks R., ObstA. and Bachthaler G. (1970). Ist fortgesetzter Getreidebau im Hinblick auf FuBkrankheiten moglich ? Nachrichtenbl. dtsch. Pfianzenschutzdienstes, Braunschweig,22, 51-58. Fitt B. D. L. and Bainbridge A. (1983). Recovery of Pseudocercosporella herpotrichoides spores from rain splash samples. Phytopathol. Z., 106, 177-182. Fitt B. D. L. and Lysandrou M. (1984). Studies on mechanism of splash dispersal of spores, using Pseudocercosporella herpotrichoides spores. Phytopathol. Z.,111, 323-331. Garrett S.D. (1941). Soil conditions and the take-all disease of wheat, VII. Survival of Ophiobolus graminis on the roots of grassess. Ann. appl. Biol.,28, 325-332. Gerlagh M. (1968). Introduction of Ophiobolus graminis into new polders and its decline. Neth. J. Plant Pathol., 74, S2, 1-97. Gliemeroth G. and Kubler E. (1972). Untersuchungen an unterschiedlich getreidestarken Fruchtfolgen auf fiinf Standorten. Teil 1 : Ertragsverlauf von drei Getreidearten. Z Acker. Pfianzenbau,136, 34-54. Glynne M. D. (1935). Incidence of take-all on wheat and barley on experimental plots at Woburn. Ann. appl. Biol.,22, 225235. Glynne M.D. (1951). Effect of cultural treatments on wheat and on the incidence of eyespot lodging, take-all and weeds, Ann. appl. Biol.,38, 665-688. Glynne M.D. and Slope D. B. (1959). Effects of previous wheat crops, seed rate and nitrogen on eyespot, take- all, weeds and yields of two varieties of winter wheat. Ann. appl. Biol.,47, 187-199. Huet P. (1986). Influence du systeme de culture sur le pietinverse du ble. In : Les rotations cen!alieres intensives. Dix annees d'etudes concertees INRA-ONIC-ITCF 1973-1983. Paris : INRA, pp. 95-111. Huet P. and Recamier A. (1986). La monoculture du ble. Etude experimentale de !'evolution du rendement. In: Les rotations cerealieres intensives. Dix annees d'itudes concertees 1NRAONIC-ITCF 1973-1983. Paris: INRA, pp. 391-400. Jensen A. (1975). Danish experiences with cereals in monoculture. EPPO Bull.,S, 181-191. King J. E. and Griffin M. J. (1985). Survey of benomyl resistance in Pseudocercosporella herpotrichoides on winter wheat and barley in England and Wales in 1983. Plant Pathol.,34, 272-283. Lemaire J. M. and Coppenet M. (1968). Influence de Ia succession cerealiere sur les fluctuations de Ia gravite du pietinechaudage (Ophiobolus graminis Sacc.). Ann. Epiphyt.,19, 589-599. Leroux P. and Gredt M. (1988). Caracterisation des souches de Pseudocercosporella herpotrichoides, agent du pietin-verse des cereales, resistantes a des substances antimitotiques et a des inhibiteurs de Ia biosynthese des sterols. Agronomie,S, 719-729. Lucas P., Samiguet A., Collet J. M. and Lucas M. (I 989). Receptivite du sol au pietin-echaudage (Gaeumannomyces Eur. J. Agron.
Root and foot diseases in wheat monocultures
graminis var. tritici)). Influence de certaines techniques culturales. Soil Bioi. Biochem.,21,l073-l078. Macer R. C. F. (196la). Saprophytic colonization of wheat straw by Cercosporella herpotrichoides Fron and other fungi. Ann. appl. Biol.,49, 152-164. Macer R. C. F. (196lb). Survival of Cercosporella herpotrichoides Fron in wheat straw. Ann. appl. Bio/.,49, 165-172. Maraite H. and Weyns J. (1986). Evolution of MBC-resistance in Pseudocercosporella herpotrichoides on winter wheat and winter barley. Meded. Fac. Landbouwwet., Rijksuniv. Gent.,51, 691-697. Obst A., Graf R. and Riippold H. (1977). Beobachtungen in einem Monokultur-Weizensortiment zur Vikarianz der Pjlanzendtsch. Nachrichtenbl. FuBkrankheitserreger. schutzdienstes, Braunschweig,29, 113- 114. Prew R. D. (1977). Studies of the spread, survival and control of take-all and other foot and root diseases of wheat and barley. Ph. D. Thesis, University of London. Reinecke H. and Fehrmann H. (1979). Rhizoctonia cerealis Van der Hoeven an Getreide in der BRD, Z. Pjlanzenkr. Pjlanzenschutz,86, 190-204. Reinecke P., Duben J. and Fehrmann J. (1979). Antagonism between fungi of the foot rot complex of cereals. In : B. Schippes and W. Gams (Eds.) Soilborne plant pathogens. New York and London : Academic Press, pp. 327- 336. Samiguet A., Lucas P. and Lucas M. (1992a). Relationships between take-all, soil conduciveness to the disease, populations of fluorescent pseudomonads and nitrogen fertilizer. Plant Soil,145, 17-27. Samiguet A., Lucas P. and Lucas M. (1992b). Soil conduciveness to take-all of wheat : Influence of the nitrogen fertilizers on the structure of populations of fluorescent pseudomonads. Plant Soil,145, 29-36.
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SAS Institute Inc. (1989). SAS/STAT User's Guide, Version 6. Cary NC USA : SAS Institute Inc., Fourth Edition. Shipton P. J. (1972). Take-all in spring sown cereals under continous cultivation, disease progress and decline in relation to crop succession and nitrogen. Ann. appl. Bioi., 71, 33-46. Shipton P. J. (1975). Yield trends during take-all decline in spring barley and wheat grown continously. EPPO Bull.,5, 363-374. Steinbrenner K. and Hoflich G. (1980). Bedeutung bodenbiirtiger GetreidefuBkrankheitserreger in spezialisierten Getreidefruchtfolgen und Moglickeiten zu ihrer Bekampfung, Tag. Ber., Akad. Landwirtsch. wiss. dtsch. demokr. Repub., 181, 29-36. Steinbrenner K. and HOflich G. (1984). EinfluP acker- und pflanzenbaulicher Mapnahmen auf den Befall des Getreides durch Pseudocercosporella herpotrichoides (Fron) Deighton und Gaeumannomyces graminis (Sacc.) Arx et Olivier. Arch. Phytopathol. Pjlsch., 20, 469-486. Van der Hoeven E. P. and Bollen G. J. (1980). Effect of benomyl on soil fungi associated with rye. Effect on the incidence of sharp eyes spot caused by Rhizoctonia cerealis, Neth. J. Plant Pathol., 86, 163-180. Vez A. (1975). Observations dans les essais de rotation de cultures a Changins au cours des dix demieres annees. Rev. suisse Agric., 7, 113-118. Wehrle V. M. and Ogilvie L. (1955). Effect of ley grasses on the carry-over of take-all. Plant Pathol.,4, 111-113. Zogg H. (1967). Probleme der biologischen Bodenentseuchung. Meded. Fac. Landbouwwet, Rijksuniv. Gent,32, 401-408. Zogg H. (1976). Problems of biological soil disinfection. Soil Bioi. Biochem.,8, 299-303.
Modelling the frequency and severity of root and foot diseases in winter wheat monocultures N. Colbach and P. Huet* INRA-Agronomie, Centre de Grignon, F-78850 Thiverval-Grignon, France.
Accepted 2 February 1995
* Abstract
To whom correspondence should be addressed.
From 1986 to 1993, wheat crops from plots which had been cultivated with cereals for various lengths of time were assessed for the major foot and root diseases : eyespot (Pseudocercosporella herpotrichoides), take-all (Gaeumannomyces graminis) and sharp eyespot (Rhizoctonia cerealis). For each disease, mean frequency and severity were modelled as a function of the number of years of continuous cereal cropping. Both take-all and eyespot increased during the first 3 to 5 years of monoculture before disease decline was observed. Decline was more important for take-all severity than frequency, whereas it was considerably stronger for eyespot frequency than severity. Take-all decline started sooner than eyespot decline. Model quality was highest for eyespot frequency and lowest for take-all frequency and severity. The incidence of sharp eyespot was too low to observe any influence of crop succession. We observed however an important year effect and a negative correlation with eyespot. Key-words : Pseudocercosporella herpotrichoides, Gaeumannomyces graminis, Rhizoctonia cerealis, cereal monoculture, disease decline, modelling.
INTRODUCTION The most important foot and root diseases of winter wheat in Northern Europe are eyespot (Pseudocercosporella herpotrichoides (Fron) Deighton), sharp eyespot (Rhizoctonia cerealis Van der Hoeven) and takeall (Gaeumannomyces graminis (Sacc.) von Arx and Olivier var. tritici (Walker)). The former two infect first the sheaths and later the tiller bases of the host plants and the latter is responsible for black lesions on both seminal and nodal roots. If no suitable host plants are available, these pathogens survive as saprophytes on host residues for a limited period (Steinbrenner and Hoflich, 1984). A high proportion of host crops, mostly cereals, in the succession should therefore increase disease. This has been confirmed in the short term (Glynne and Slope, 1959; Steinbrenner and Htiflich, 1984). However, a decrease of take-all after a period of 3 to 4 years of severely infected cereal crops, has been observed by numerous authors in Great-Britain (Glynne, 1935 ; Shipton, 1972, 1975), France (Lemaire and Coppenet, 1968), Ireland (Cunningham, 1975), the Netherlands ISSN Jl6l-030l/95/02/$ 4.00/ © Gauthier- Villars - ESAg
(Gerlagh, 1968), Denmark (Jensen, 1975), Switzerland (Zogg, 1967; Vez, 1975), Germany (Gliemeroth and KUbler, 1972). There have been fewer studies on eyespot decline (Glynne, 1935 ; Glynne and Slope, 1959; Vez, 1975) and the pathogen population has evolved considerably during the last years as shown by the development of fungicide resistances (King and Griffin, 1985 ; Maraite and Weyns, 1986 ; Leroux and Gredt, 1988 ; Cavelier et al., 1992). Disease decline seems not to have been observed for sharp eyespot. The analysis of this disease is furthermore complicated by the possible · interactions with P. herpotrichoides which seems to dominate the sharp eyespot fungus (Obst et al., 1977; Reinecke and Fehrmann, 1979 ; Van der Hoeven and Bollen, 1980; Cavelier et al., 1985). Moreover, not only the pathogen populations, but also the cultivation techniques have changed greatly since the above mentioned results were published. In most of these trials, the wheat crop assessed for diseases was furthermore not cultivated uniformly, since techniques such as sowing date or soil tillage depend on crop succession. There is therefore an
218
N. Colbach and P. Huet
important risk of confusing crop succession effects and, for example, those due to changes in sowing date in recent years.
Table 2. Trial design : plots with continuous wheat cultivation assessed for diseases from 1986 to 1993
The aim of our work was to follow disease evolution as well as pathogen interactions on cereal monocultures for several years and to describe disease level, if possible, as a function of the number of years of continuous cereal cultivation. Our field trial compared each year the disease levels of plots on which wheat had been cultivated for a variable number of years. To assure that disease assessment would only express crop succession effects, all wheat crops of a given year were cultivated uniformly, whatever the preceding crops.
Year(s) of continuous wheat cultivation
2
3
4
X
X
5
6
7
8
10
9
Year
1986 1987 1988 1989 1990 1991 1992 1993
X X X X X X X X
X
X
X
X
X X
X
X X
X
X
X
X
X
X
X
X
X
X denotes presence in that year of wheat grown for I ,2 .. 10 years continuously.
MATERIALS AND METHODS Field trial
As for a given year not every duration of continuous wheat cultivation was represented, there was the possibility of confusing the year effect and the year x monoculture duration interaction (Huet and Recamier, 1986). This risk was however limited as every year 3 to 5 different degrees of monoculture were present and each degree existed at least for one year. The year x monoculture duration interaction cannot be analyzed in this work.
Table 1 shows the various crop successions of our field trial at Grignon from 1980 to 1993. From 1986 to 1993, nearly all wheat crops were assessed for foot and root diseases. We had therefore wheat crops available, corresponding to different lengths of cereal monoculture (Table 2), assuming that the spring barley of succession 2 in 1984 did not interrupt monoculture (Shipton, 1972, 1975).
Table 1. Crop succession of the Grignon field trial
Succession
2
5
7
9
11
13
15
pot.
w.w.
luc. + coc.
luc. + coc. pot.
w.w.
s.b.
s.b.
luc. + coc. luc. + coc.
pot.
w.w.
w.w.
s.b.
luc. + coc. luc. + coc.
Year
1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993
s.b.
pot.
luc. + coc. luc. + coc.
pot.
w.w.
s.b.
luc. + coc.
pot.
w.w.
pot.
w.w.
s.b.
luc.
luc.
luc.
w.w.
s.b.
w.w.
s.b.
luc.
luc.
luc.
pot.
w.w.
w.w.
w.b.
luc.
luc.
luc.
luc.
w.w.
w.w.
w.w.
luc.
luc.
luc.
luc.
w.w.
w.b.
w.w.
w.w.
luc.
luc.
luc.
w.w.
w.b.
luc.
w.w.
w.w.
luc.
luc.
w.w.
w.b.
luc.
luc.
w.w.*
w.w.
luc.
w.w.
w.b.
luc.
luc.
luc.
w.w.*
w.w.
w.w.
w.w.
luc.
luc.
luc.
luc.
w.w.*
w.w.
w.w.
w.w.
luc.
luc.
luc.
w.w.
w.w.
luc.
w.w.
w.w.
luc.
luc.
w.w.
w.w.
w.w.
luc.
w.w.
luc.
luc.
w.w.
w.w.
w.w.
w. w. = winter wheat, w.b. = winter barley, s.b. = spring barley pot. = potato, luc. = lucerne, coc. = cocksfoot All wheat crops between 1986 and 1993 were assessed for foot and root diseases except those marked*.
Eur. J. Agron.
Root and foot diseases in wheat monocultures
Each succession was tested in a randomized block design with four replications ; plot size was 17 m x 5.25 m. Each year, all wheat plots were sown on the same day (about mid-October) and at the same density (about 300 grains per m 2 ) in rows 0.16 m apart. The wheat cultivar was Fidel which is not resistant to the assessed diseases. Soil tillage (plough and shallow tillage), herbicide and insecticide treatments were the same whatever the plot. No fungicide or growth regulator was used. Nitrogen was applied at the rate of about 180 kg ha- 1 after wheat and 160 kg ha- 1 after lucerne. Together with soil nitrogen residues and mineralization, all wheat crops therefore had approximately an equal quantity of total nitrogen available.
219
potato-dextrose-agarose contammg antibacterial antibiotics. Incubation period was about 10 days at 20 ac. Statistical analysis
To analyse disease level, we used the General Linear Model (GLM procedure) of the SAS software program (Statistical Analysis System, SAS Institute Inc, 1989) for our analysis of covariance. For the foot diseases, the percentage of diseased tillers as well as the severity score ; for take-all, the percentage of diseased plants and the sum of necrosed root length per plant, were the output variables. The tested (initial) model was as follows :
On every plant (for all diseases) and on every tiller (only for foot diseases) absence or presence were noted visually. All diseased tillers were sectioned at the height of the necrosis and classified according to the necrosed section part :
disease = constant + year effect + f(x) + block effect + error) (E) where f(x) is a function representing disease level as a function of monoculture degree x. The covariable tiller number per plant was introduced into foot disease models to take into account wheat population influences such as separating diseased sheaths from older tillers during tiller emergence and thus limiting disease transmission (Glynne, 1951 ; Huet, 1986). The sharp eyespot models contained the covariable % of tillers with eyespot because of the interaction between sharp eyespot and eyespot, the latter dominating the former.
class 1 : necrosed section part less than 10 per cent of total section area.
If we suppose that disease increases, passes through a
Measurements
At flowering, the plants in four randomly placed quadrats of 0.5 m x 2 rows in each plot were sampled with a spade. In each quadrat, 12 randomly chosen plants were assessed for foot and six for root diseases.
There are different possibilities for the function f(x).
class 2 : necrosed section part more than 10 per cent and less than 30 per cent of total section area.
maximum and decreases until stabilizing at an asymptote value, then the following equation is appropriate :
class 3 : necrosed section part more than 30 per cent and less than 60 per cent of total section area.
j{x)=ax2+bx
class 4 : necrosed section part more than 60 per cent of total section area.
2
X
+C
A severity score equivalent to the mean necrosed section part was then calculated for each plot and every disease, with the following formula where the percentages of diseased tillers of each class are weighted by their median necrosed sections :
We did not have enough values for high monoculture degrees to be able to evaluate correctly the asymptote value a. Furthermore, this is a non-linear model for which the statistics may only be correctly calculated for a large number of points.
%mean necrosed section = (0.05% tillers of class 1 + 0.2 X% tillers of class 2 + 0.45 X% tillers of class 3 + 0.8 X% tillers of class 4)/total % of necrosed tillers.
We therefore preferred a more simple model with a limited application domain, but more robust in this domain. A second-degree equation fix) = a . x + b • i (1) might be suitable in those cases where pre-maximum increase and post-maximum decrease are symmetric. If increase is faster than decrease, a modified second-degree equation flx) = 2 a. ln(x) + b. (ln(x)) (2) where ln(x) is the logarithm of x, might be suitable. If however pre-maximum increase is slower, then the equation flx) = a. exp(x) + b · (exp(x)) 2 (3) should be chosen.
On nodal roots, the length of each take-all necrosis was measured and summed to give the necrosed root length per plant, representing the severity of take-all infection. As plants were sampled with a spade, the sampled root length was approximately 10 em. In 1993, eyespot forms P. herpotrichoides var. herpotrichoides and P. herpotrichoides var. acuformis were identified in vitro at flowering + 350 degree-days (basis 0 °C). For each plot and disease, 30 diseased tillers were superficially disinfected and incubated on Vol. 4,
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2- 1995
For each disease, three different versions of the initial model (E), where f( x) was respectively replaced by the equations (1), (2) or (3), were tested. Only the
220
N. Colbach and P. Huet
dered the contribution due to the factor or covariable as not significant. The sum of squares used to calculate the probability values for each factor or covariable was adjusted to all terms present in the model and did thus not depend on their order of appearance in the model (type III sum of squares of the GLM procedure).
models explaining most of the variability (giving the greatest ? and F value) were retained and discussed. As noted earlier, the interaction year x monoculture duration could not be analysed on this trial as the experimental design did not permit a correct evaluation of this interaction. Where the condition of variance homogeneity necessary for a linear model was not fulfilled, the Box and Cox transformation (Box et al., 1978) was used: if the relation between mean and variance (of a given variable for each experimental treatment) ln(variance) = a + b.ln(mean) was significant, then the necessary transformation was as follows : transformed variable
RESULTS
Take-all
= variable (1 - b/2!
The model retained to explain the percentage of diseased plants (Table 3) was the following: % plants with take-all = constant + year effect + 2 a. ln(x) + b. (ln(x)) + block effect where a > 0 and b < 0.
The final model contained only those factors and/or covariables for which the probability values of the statistical zero hypothesis test were less than 5 per cent. If these values were greater than 5 per cent, we consi-
Table 3. Linear model retained to explain the percentage of plants with take-all (Analysis of variance table and estimations for significant effects)
SOURCE MODEL ERROR CORRECTED TOTAL EFFECTS year In( monoculture) (ln(monoculture)) 2 block
degrees of freedom
sum of squares
mean square
F value
Pr > F
?
12 89 101
14756 26375 41131
1129 296
4.15
0.0001
0.36
7
6495 4370 2595 2711
927 4370 2595 903
3.13 14.76 18.77 3.05
0.0053 0.0002 0.0040 0.0327
1 3
Sum of squares for the various effects are adjusted to all the terms of the model (type III sum of squares of GLM procedure of SAS).
ESTIMATORS OF THE FACTOR AND COVARIABLE EFFECTS constant
64.6
ESTIMATIONS FOR THE FACTORS YEAR AND BLOCK* Year estimation Year 1986 -13.3 1990 1991 1987 12.4 1988 1992 4 -3.7 1993 1989
estimation 11.3 -0.34 -5 -5.5
ESTIMATIONS FOR THE COVARIABLE PARAMETERS Covariable parameter ln(monoculture) : a (In( monoculture) )2 b
estimation 28.3 -10.4
Block I 2 3 4
estimation 4.3 5 -8.4 0.86
The final linear model was : % plants with take-all~ constant+ year effect+ a. ln(monoculture) + b. (ln(monoculture)f + block effect+ error. * The sum of the estimations for each factor is nil.
Eur. J. Agron.
221
Root and foot diseases in wheat monocultures
Infection level at the first year of monoculture was already high (mean = 64 per cent of infected plants). The mean maximum was at x = 3.9 (standard-error= 0.6) with 84 per cent of diseased plants and at the tenth year of monoculture, mean infection level was at 74 per cent, which is halfway between initial and maximum level. The post-maximum disease evaluation was however less precise as it was only based on 1 to 2 years disease data whereas the pre-maximum evaluation was based on 4 years data. Figure 1 confirms that infection level increased during the first years of monoculture when the influence of parameter a was predominant. When parameter b began to dominate, disease increase slowed down, passed through a maximum and then decreased. The model retained for the sum of necrosed root length (Table 4) was similar except that it did not contain a block effect. This model, similar to that shown in Figure 1, show a similar but more pronounced trend. The mean necrosis sum was 2.3 em for
6
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60
2
1
3
2
4
5
6
8
7
9
10
years with continuous wheat
Figure 1. Take-all evolution in wheat monoculture. Disease fre= 0.35) as a func0.36) and severity(---. quency(~ tion of the number of years with continuous wheat culture.
r
r=
Table 4. Linear model retained to explain the sum of root length necrosed by take-all (Analysis of variance table and estimations for significant effects)
SOURCE MODEL ERROR CORRECTED TOTAL EFFECTS year ln(monoculture) (ln(monoculture) )'
degrees of freedom
sum of squares
mean square
F value
Pr > F
9 92 101
36075 67206 103281
4008 731
5.49
0.0001
7
25101 9880 6929
3585 9880 6929
4.91 13.53 9.49
0.0001 0.0004 0.0027
0.35
Sum of squares for the various effects are adjusted to all the terms of the model (type III sum of squares of GLM procedure of SAS).
ESTIMATORS OF THE FACTOR AND COVARIABLE EFFECTS 2.34
constant ESTIMATIONS FOR THE FACTOR YEAR* Year 1986 1987 1988 1989
estimation - 1.57 0.17
-1.3 -0.25
ESTIMATIONS FOR THE COVARIABLE PARAMETERS Covariable ln(monoculture) : (ln(monoculture)) 2
Year 1990 1991 1992 1993
estimation 0.97 -0.894 -1.09 3.96
parameter a b
estimation 4.25 -1.7
2 The final linear model was: sum of necrosed root length per plant (em)+ constant+ year effect+ a. ln(monoculture) + b. (ln(monoculture)) +error. * The sum of the estimations for each factor is nil.
Vol. 4, n° 2- 1995
N. Colbach and P. Huet
222
the first year of monoculture, 4.9 em for maximum at x = 3.5 (standard-error = 0.5) and 3.1 em at the tenth year. The post-maximum decrease was faster for disease severity than for frequency. The variability explained by these two models was low : 35 per cent for the frequency model ( / = 0.35) and 36 per cent for the severity model. For neither model was the distribution of residuals normal at a = 0.05, but it was not more asymmetric than the normal residual distributions observed for the other diseases (Table 5).
Table 5. Residual distribution for the various disease indicators
VARIABLE
normality (I)
symmetry (2)
0.0362 0.0124 0.4129 0.1619 0.0072 0.0793
-0.7152 0.7922 -0.1502 -0.5220 -0.0204 0.4454
take-all frequency take-all severity eyespot frequency eyespot severity sharp eyespot frequency sharp eyespot severity
(I) probability associated to the null hypothesis 'the distribution is normal'.
(2) measure of skewness : the closer to zero, the more symmetric the distribution.
Eyespot The model retained to explain the percentage of tillers with eyespot (Table 6) was similar to the abovedescribed ones :
% tillers with eyespot 2
= constant
+ year effect +
a. ln(x) + b. (ln(x)) + c.tillers per plant where a > 0; band c < 0.
Table 6. Linear model retained to explain the percentage of tillers with eyespot (Analysis of variance table and estimations for significant effects)
SOURCE MODEL ERROR CORRECTED TOTAL EFFECTS year In (monoculture) (In (monoculture)}' tillers per plant
degrees of freedom
sum of squares
mean square
F value
Pr > F
(2
10 91 101
70154 32397 102551
7015 356
19.71
0.0001
0.68
7
15224 23254 12102 1928
2174 23254 12102 1928
6.11 65.32 33.99 5.42
0.0001 0.0001 0.0001 0.0221
Sum of squares for the various effects are adjusted to all the terms of the model (type III sum of squares of GLM procedure of SAS).
ESTIMATORS OF THE FACTOR AND COVARIABLE EFFECTS constant ESTIMATIONS FOR THE FACTOR YEAR* Year 1986 1987 1988 1989
48.8
estimation -4.4 15.4 -6.4 -6.0
ESTIMATIONS FOR THE COVARIABLE PARAMETERS Covariable ln(monoculture) : (ln(monoculture) )2 tillers per plant :
Year 1990 1991 1992 1993
estimation 2.8 16.1 -2.2 -27.2
parameter a
estimation 67.2 -22.5 -13.8
b c
* The sum of the estimation for each factor is nil. The final linear model was: % tillers with eyespot + constant+ year effect+ a. ln(monoculture) + b. (ln(monoculture)) 2 + C. tiller number per plant+ error. Eur. ]. Agron.
223
Root and foot diseases in wheat monocultures
Mean frequency (with a mean tiller number per plant of 1.9) was 23 per cent for the first year of monoculture, 73 per cent at the maximum x = 4.5 (standard-error = 0.5) and 58 per cent at the tenth year. The decrease in onset was later than for take-all (x = 4.5 is significantly different from x = 3.5 at a = 0.10) and was not sufficient to reach the halfway level between initial and maximum values. As for take-all, evaluation was less precise for post-maximum than for pre-maximum disease evolution because of our unbalanced data set.
80-r------------------,.-go
The severity model (Table 7) was different in so far as it directly contained the monoculture degree x and not the logarithm form ln(x). Furthermore, a Box and Cox transformation was required to homogenize variance. The covariable tillers per plant was not significant. Mean severity was 67 per cent for the first year of, monoculture, 76 per cent at the maximum x = 5.3 (standard-error = 0.4) and 65 per cent at the
m
-------
-- -----
' '
m 2
4
3
6
5
7
8
w
9
years with continuous wheat
Figure 2. Eyespot evolution in wheat monoculture. Disease frequency(~?= 0.68) and severity(---,?= 0.47) as a func-
tion of the number of years with continuous wheat culture.
Table 7. Linear model retained eyespot severity (Analysis of variance table and estimations for significant effects)
SOURCE MODEL ERROR CORRECTED TOTAL EFFECTS year monoculture monoculture 2
degrees of freedom
sum of squares
mean square
9 92 101
1.24. 10 19 1.42. 10 19 2.66. 10 19
1.37 . 10 18 1.54. 10 17
7
9.15. 10 18 4.33 . 10 18 3.67. 10 18
1.31 . 10 18 4.33. 10 18 3.67. 10 18
F value
Pr > F
?
8·9
0·0001
0-47
8-49 28·12 23·83
0·0001 0·0001 0·0001
Sum of squares for the various effects are adjusted to all the terms of the model (type III sum of squares of GLM procedure of SAS).
ESTIMATORS OF THE FACTOR AND COVARIABLE EFFECTS 4.08. 108
Constant ESTIMATIONS FOR THE FACTOR YEAR* Year 1986 1987 1988 1989
estimation -6.4- 106 7.6. 107 -4.7. 106 8 - 3.9. 108
ESTIMATIONS FOR THE COVARIABLE PARAMETERS Covariab1e monoculture : (monoculture) 2
Year 1990 1991 1992 1993
parameter
a b
estimation
-1.3. 108 5. 108 -2.2. 108 -1.3. 108
estimation 3.25. 10 8 -3.05. 107
* The sum of the estimation for each factor is nil. 2 A Box and Cox The final linear model was: % of necrosed section (I + 7.696/2) = constant+ year effect+ a · monoculture + b · (monoculture) + block effect+ error. -7.696. = b with significant is ln(mean) b. =a+ ln(variance) transformation (Box et al.. 1978) is necessary as the relation Vol. 4. n° 2- 1995
N. Colbach and P. Huet
224
transfonned % tillers with sharp eyespot = constant + year effect + block effect + a . tillers with eyespot + b • tillers per plant.
tenth year which is similar to the initial disease level. Overall, variations were therefore not very marked. These models, as well as Figure 2, show a similar evolution as for take-all : an increasing period, passage through a maximum, which was followed by a disease decrease. The model quality depended on the output variable : 68 per cent of variability were explained by the frequency model, but only 47 per cent by the severity model. Residual distribution was normal for both models (Table 5).
with a and b < 0. A Box and Cox transformation was necessary to homogenize variance. Crop succession had no influence on sharp eyespot. The covariables %tillers with eyespot and tillers per plant were negatively correlated with sharp eyespot, otherwise we only observed year and block effects. Mean frequency was low (3 per cent), and 34 per cent of variability was explained by the model. The model retained for sharp eyespot severity (mean value = 10 per cent), was similar to the above one (results not shown) but with lower r (0.28). Residual distribution was not normal, but symmetric for sharp eyespot frequency ; it was normal for severity (Table 5).
Only P. herpotrichoides var. herpotrichoides was isolated from the eyespot affected tissue in 1993. Sharp eyespot
The retained model for frequency (Table 8) was the following:
Table 8. Linear model retained to explain the percentage of tillers with sharp eyespot (Analysis of variance table and estimations for significant effects)
SOURCE MODEL ERROR CORRECTED TOTAL EFFECTS year block eyespot tillers/plant
degrees of freedom
sum of squares
mean square
F value
Pr > F
12 89 101
12.68 24.67 37.36
1.06 0.277
3.82
0.0001
7 3
7.08 3.23 2.05 1.61
1.01 1.08 2.05 1.61
3.65 3.90 7.40 5.81
0.0017 0.0117 0.0078 0.0179
0.34
Sum of squares for the various effects are adjusted to all the terms of the model (type 11I sum of squares of GLM procedure of SAS).
ESTIMATORS OF THE FACTOR AND COVARIABLE EFFECTS constant
1.49
ESTIMATIONS FOR THE FACTORS YEAR AND BLOCK* Year estimation Year 1986 -0.21 1990 1987 -0.33 1991 1988 0.23 1992 1989 -0.48 1993
estimation 0.27 0.29 0.19 0.03
ESTIMATIONS FOR THE COVARIABLE PARAMETERS Covariable parameter % tillers with eyespot : a tillers per plant : b
estimation -0.00565 -0.398
Block I 2 3 4
estimation -0.23 -0.072 0.28 0.016
* The sum of the estimation for each factor is nil. The final linear model was : % tillers with sharp eyespot (I - 1.665/2) = constant + year effect+ a · % tillers with eyes pot + b · tillers per plant + error. A Box and Cox transformation (Box et al., 1978) is necessary as the relation ln(variance) = a+ b .ln(mean) is significant with b = 1.665. Eur. J. Agron.
Root and foot diseases in wheat monocultures
DISCUSSION Diseases decline in monoculture : take-all and eyespot
Disease decline after a period of increasing disease for three to four years of cereal monoculture has already been observed for take-all by numerous authors. For eyespot however, there are few reports on a decline. Take-all decline is believed to result from a stimulation of antagonistic microflora, for instance Pseudomonas fiuorescens (Cook and Rovira, 1976). Mechanisms responsible for eyespot decline have not yet been identified, but microbiological antagonism might also be the reason for this effect (Diercks et al., 1970). However, our results on take-all differ from previous reports in that we observed a considerable takeall level in the first wheat and a slower disease decrease after maximum. The first difference may easily be explained : the first wheat was preceded by a lucerne crop which was usually heavily infested by spontaneous Gramineae such as Latium perenne. The above-named Gramineae may be infected by take-all and thus carry over Gaeumannomyces graminis inoculum (Garrett, 1941; Wehrle and Ogilvie, 1955; Coventry et al., 1989), while the introduction of one non-cereal crop in a monoculture cycle is sufficient to stop take-all decline and allow the disease to increase again (Zogg, 1976; Lucas et al., 1989). G. graminis inoculum is therefore already important before the first wheat is sown, whereas the associated antagonistic microflora is not able to grow under noncereal crops. This unbalance might also be the reason why post-maximum decrease was slow. On the other hand, microflora species and frequency in our trial were probably not the same as in other authors' fields. The unbalanced data set could also be the reason for the slow take-all decline : evaluation was less precise for post-maximum than for pre-maximum disease evolution. Take-all decrease might therefore be stronger than shown by our curves.
225
saprophytical survival of P. herpotrichoides and sporulation and therefore disease frequency. Infection and disease spread on the plant may only be affected if spore quality is impaired. Both take-all dissemination and infection are however within reach of soil microflora as the fungus spreads by mycelial growth towards the roots of new host plants (Prew, 1977). As P. fiuorescens needs a prior G. graminis infection on a plant before expanding and impairing further take-all development on this host (Samiguet et al., 1992a, 1992b), disease frequency is only slightly reduced by antagonistic activity whereas disease severity is considerably limited. Thus for take-all, not only is the observed disease extent limited, but the amount of infected plant residues and therefore next year primary inoculum are also lower than for eyespot. A longer period is therefore necessary for antagonistic microflora to limit eyespot. This might be the reason for the first difference between the two diseases. The longer saprophytical survival of P. herpotrichoides (2- 3 years ; Macer, 196la, 196lb; Steinbrenner and Hoflich, 1984) might also contribute to delayed eyespot decline. The short-distance dissemination mode of G. graminis might also explain the poorer fit of the models for this disease as well as the presence of block effects. Disease spreads irregularly and variability both within and between plots is therefore high. Furthermore, disease variability due to host population irregularities was partially taken into account for eyespot with the tiller number per plant covariable, reflecting phenomena such as separation of diseased sheaths from older tillers during tiller emergence (Glynne, 1951 ; Huet, 1986). Sharp eyespot : a disease with no observable decline
We also observed differences between take-all and eyespot: (a) the latter reached its maximum later; (b) disease decrease was only visible for frequency and severity may be considered constant (with regards to the observation precision) whereas take-all decline was more marked for disease severity than for frequency.
We were not able to demonstrate disease decline for sharp eyespot. Disease level was too low to detect any influence of crop succession, such as those reported by Colbach et al. (1994), even if it was corrected for P. herpotrichoides. This relation is reflected by the negative correlation between the two diseases which has been reported frequently (Obst et al., 1977 ; Reinecke and Fehrmann, 1979 ; Van der Hoeven and Bollen, 1980; Cavelier et al., 1985 ; Colbach et al., 1994). Both pathogens infect and therefore compete for the same tissues (Reinecke et al., 1979). Antagonism was reported in vitro, even if both fungi may be present on a same necrosis (Briick and Schlosser, 1982).
This last difference is an argument in favour of the existence of an antagonistic soil microflora as a cause for eyespot decrease : as Pseudocercosporella herpotrichoides is disseminated by spores carried by wind and rain drops (Fitt and Bainbridge, 1983 ; Fitt and Lysandrou, 1984), soil microorganisms may only limit
We have not been able to find any previous work explaining the negative correlation between sharp eyespot and the covariable tillers per plant. However as Rhizoctonia cerealis infects the same wheat organ as P. herpotrichoides, the same explanation as for eyespot might hold.
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CONCLUSION
For both fungi with high disease level and pathogenicity, i.e. take-all and eyespot, we were able to observe disease decline after a period of 3 to 5 years of disease increase in cereal monoculture. The length of this period and therefore the onset of the decline, as well as the importance of this decrease, might depend on (a) the length of saprophytical survival, and on (b) soil contact during dissemination as well as infection. It is possible that maximum disease level and both the onset of decline and its magnitude depend on the nature of those crops preceding the first cereal of the monoculture. These preceding crops are not only responsible for the amount of inoculum ready to infect the cereal crops, but they may also influence the frequency and the quality of antagonistic microflora which are responsible at least for take-all decline. It was not possible to conclude whether there was a decline in sharp eyespot. The disease level was too low to allow any significant influence. We observed however a strong interaction with P. herpotrtchoides. Whatever the influence of crop succession on disease level, all pathogens were strongly influenced by the year effect. Year effect, i.e. climatic conditions, not only influences disease on the assessed wheat, but also determine disease on the previous wheat crops and therefore the amount of primary inoculum at the beginning of the next wheat crop. This year effect should be further analysed by future work, using epidemiological models which, however, do not exist for these diseases. ACKNOWLEDGEMENTS
We thank Philippe Lucas (INRA-Rennes) for his help in improving this paper, Jacques Troizier (Domaine experimental de Grignon) for conducting our field trials and Beatrice Le Fouillen for technical assistance. REFERENCES Box G. E. P., Hunter W. G. and Hunter J. S. (1978). Statistics for Experimenters : an introduction to design, data analysis and model building. New York : Wiley. Briick K. P. and Schlosser E. (1982). GetreidefuBkrankheitserreger, V. Antagonismus zwischen den Erregem. Z. Pfianzenkr. Pfianzenschutz,89, 337-343. Cavelier N., Lucas P. and Boulch G. 1985. Evolution du complexe parasitaire constitue par Rhizoctonia cerealis et Pseudocercosporella herpotrichoides, champignons parasites de Ia base des tiges des cereales. Agronomie,S, 693-700. Cavelier N., Loree F. and Prunier M. (1992). Resistance of the eyespot fungus, Pseudocercosporella herpotrichoides, to DMI Fungicides. Proc. br. Crop. Prot. Conf, Pests Dis., 1, 189194.
N. Colbach and P. Huet
Colbach N., Lucas P. and Cavelier N. (1994). Influence des successions culturales sur les maladies du pied et des racines du ble d'hiver. Agronomie 14, 525-540. Cook R. J. and Rovira A. D. (1976). The role of bacteria in the biological control of Gaeumannomyces graminis by suppressive soils. Soil Biol. Biochem.,S, 269-273. Coventry D. R., Brooke H. D., Kollmorgen J. F. and Ballinger D. J. (1989). Increases in wheat yield on limed soil after reduction of take-all by fungicide application and crop rotation. Aust. J. exp. Agric.,29, 85-89. Cunningham P. C. (1975). Some consequences of cereal monoculture on Gaeumannomyces graminis (Sacc.) Arx et Olivier and the take-all disease. EPPO Bull., 5, 297-317. Diercks R., ObstA. and Bachthaler G. (1970). Ist fortgesetzter Getreidebau im Hinblick auf FuBkrankheiten moglich ? Nachrichtenbl. dtsch. Pfianzenschutzdienstes, Braunschweig,22, 51-58. Fitt B. D. L. and Bainbridge A. (1983). Recovery of Pseudocercosporella herpotrichoides spores from rain splash samples. Phytopathol. Z., 106, 177-182. Fitt B. D. L. and Lysandrou M. (1984). Studies on mechanism of splash dispersal of spores, using Pseudocercosporella herpotrichoides spores. Phytopathol. Z.,111, 323-331. Garrett S.D. (1941). Soil conditions and the take-all disease of wheat, VII. Survival of Ophiobolus graminis on the roots of grassess. Ann. appl. Biol.,28, 325-332. Gerlagh M. (1968). Introduction of Ophiobolus graminis into new polders and its decline. Neth. J. Plant Pathol., 74, S2, 1-97. Gliemeroth G. and Kubler E. (1972). Untersuchungen an unterschiedlich getreidestarken Fruchtfolgen auf fiinf Standorten. Teil 1 : Ertragsverlauf von drei Getreidearten. Z Acker. Pfianzenbau,136, 34-54. Glynne M. D. (1935). Incidence of take-all on wheat and barley on experimental plots at Woburn. Ann. appl. Biol.,22, 225235. Glynne M.D. (1951). Effect of cultural treatments on wheat and on the incidence of eyespot lodging, take-all and weeds, Ann. appl. Biol.,38, 665-688. Glynne M.D. and Slope D. B. (1959). Effects of previous wheat crops, seed rate and nitrogen on eyespot, take- all, weeds and yields of two varieties of winter wheat. Ann. appl. Biol.,47, 187-199. Huet P. (1986). Influence du systeme de culture sur le pietinverse du ble. In : Les rotations cen!alieres intensives. Dix annees d'etudes concertees INRA-ONIC-ITCF 1973-1983. Paris : INRA, pp. 95-111. Huet P. and Recamier A. (1986). La monoculture du ble. Etude experimentale de !'evolution du rendement. In: Les rotations cerealieres intensives. Dix annees d'itudes concertees 1NRAONIC-ITCF 1973-1983. Paris: INRA, pp. 391-400. Jensen A. (1975). Danish experiences with cereals in monoculture. EPPO Bull.,S, 181-191. King J. E. and Griffin M. J. (1985). Survey of benomyl resistance in Pseudocercosporella herpotrichoides on winter wheat and barley in England and Wales in 1983. Plant Pathol.,34, 272-283. Lemaire J. M. and Coppenet M. (1968). Influence de Ia succession cerealiere sur les fluctuations de Ia gravite du pietinechaudage (Ophiobolus graminis Sacc.). Ann. Epiphyt.,19, 589-599. Leroux P. and Gredt M. (1988). Caracterisation des souches de Pseudocercosporella herpotrichoides, agent du pietin-verse des cereales, resistantes a des substances antimitotiques et a des inhibiteurs de Ia biosynthese des sterols. Agronomie,S, 719-729. Lucas P., Samiguet A., Collet J. M. and Lucas M. (I 989). Receptivite du sol au pietin-echaudage (Gaeumannomyces Eur. J. Agron.
Root and foot diseases in wheat monocultures
graminis var. tritici)). Influence de certaines techniques culturales. Soil Bioi. Biochem.,21,l073-l078. Macer R. C. F. (196la). Saprophytic colonization of wheat straw by Cercosporella herpotrichoides Fron and other fungi. Ann. appl. Biol.,49, 152-164. Macer R. C. F. (196lb). Survival of Cercosporella herpotrichoides Fron in wheat straw. Ann. appl. Bio/.,49, 165-172. Maraite H. and Weyns J. (1986). Evolution of MBC-resistance in Pseudocercosporella herpotrichoides on winter wheat and winter barley. Meded. Fac. Landbouwwet., Rijksuniv. Gent.,51, 691-697. Obst A., Graf R. and Riippold H. (1977). Beobachtungen in einem Monokultur-Weizensortiment zur Vikarianz der Pjlanzendtsch. Nachrichtenbl. FuBkrankheitserreger. schutzdienstes, Braunschweig,29, 113- 114. Prew R. D. (1977). Studies of the spread, survival and control of take-all and other foot and root diseases of wheat and barley. Ph. D. Thesis, University of London. Reinecke H. and Fehrmann H. (1979). Rhizoctonia cerealis Van der Hoeven an Getreide in der BRD, Z. Pjlanzenkr. Pjlanzenschutz,86, 190-204. Reinecke P., Duben J. and Fehrmann J. (1979). Antagonism between fungi of the foot rot complex of cereals. In : B. Schippes and W. Gams (Eds.) Soilborne plant pathogens. New York and London : Academic Press, pp. 327- 336. Samiguet A., Lucas P. and Lucas M. (1992a). Relationships between take-all, soil conduciveness to the disease, populations of fluorescent pseudomonads and nitrogen fertilizer. Plant Soil,145, 17-27. Samiguet A., Lucas P. and Lucas M. (1992b). Soil conduciveness to take-all of wheat : Influence of the nitrogen fertilizers on the structure of populations of fluorescent pseudomonads. Plant Soil,145, 29-36.
Vol. 4,
0°
2- 1995
227
SAS Institute Inc. (1989). SAS/STAT User's Guide, Version 6. Cary NC USA : SAS Institute Inc., Fourth Edition. Shipton P. J. (1972). Take-all in spring sown cereals under continous cultivation, disease progress and decline in relation to crop succession and nitrogen. Ann. appl. Bioi., 71, 33-46. Shipton P. J. (1975). Yield trends during take-all decline in spring barley and wheat grown continously. EPPO Bull.,5, 363-374. Steinbrenner K. and Hoflich G. (1980). Bedeutung bodenbiirtiger GetreidefuBkrankheitserreger in spezialisierten Getreidefruchtfolgen und Moglickeiten zu ihrer Bekampfung, Tag. Ber., Akad. Landwirtsch. wiss. dtsch. demokr. Repub., 181, 29-36. Steinbrenner K. and HOflich G. (1984). EinfluP acker- und pflanzenbaulicher Mapnahmen auf den Befall des Getreides durch Pseudocercosporella herpotrichoides (Fron) Deighton und Gaeumannomyces graminis (Sacc.) Arx et Olivier. Arch. Phytopathol. Pjlsch., 20, 469-486. Van der Hoeven E. P. and Bollen G. J. (1980). Effect of benomyl on soil fungi associated with rye. Effect on the incidence of sharp eyes spot caused by Rhizoctonia cerealis, Neth. J. Plant Pathol., 86, 163-180. Vez A. (1975). Observations dans les essais de rotation de cultures a Changins au cours des dix demieres annees. Rev. suisse Agric., 7, 113-118. Wehrle V. M. and Ogilvie L. (1955). Effect of ley grasses on the carry-over of take-all. Plant Pathol.,4, 111-113. Zogg H. (1967). Probleme der biologischen Bodenentseuchung. Meded. Fac. Landbouwwet, Rijksuniv. Gent,32, 401-408. Zogg H. (1976). Problems of biological soil disinfection. Soil Bioi. Biochem.,8, 299-303.