American Journal of Plant Sciences, 2013, 4, 2049-2059
Published Online November 2013 (
Open Access AJPS
Epidemiologic Study of Ramularia areola under Different
Soil Covers and Spacings, for Cotton Crops
Jaqueline Aguilla Pizzato1, Dejânia Vieira Araújo1, Milson Evaldo Serafim2, Kelly Lana Araújo3,
Rivanildo Dallacort1, Thiago Alexandre Santana Gílio4, Jair Romano Jr.5,
Vanderlei Antunes Maciel5
1Programa de Pós-graduação em Ambiente e Sistemas de Produção Agrícola, Universidade do Estado de Mato Grosso, Tangará da
Serra, Brasil; 2Instituto Federal de Educação, Ciência e Tecnologia de Mato Grosso—IFMT, Cáceres, Brasil; 3Laboratório de
Melhoramento Genético Vegetal. Universidade do Estado de Mato Grosso, Cáceres, Brasil. 4Programa de Pós-graduação em
Genética e Melhoramento de Plantas, Universidade do Estado de Mato Grosso, Tangará da Serra, Brasil; 5Laboratório de
Fitopatologia, Universidade do Estado de Mato Grosso, Tangará da Serra, Brasil.
Received July 9th, 2013; revised August 9th, 2013; accepted September 15th, 2013
Copyright © 2013 Jaqueline Aguilla Pizzato et al. This is an open access article distributed under the Creative Commons Attribution
License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
The objective of this work was to evaluate the progress of the areolate mildew of cotton under different soil cover and
spacing conditions. The experiment was carried out using randomized blocks and a 2 × 3 factorial design, with two
spacings (0.45 m and 0.90 m) and three soil covers (no cover, Pennisetum glaucum and Crotalaria spectabilis) with
four replications. The plants were inoculated with R. areola, sixty DAS. A total of 14 evaluations of disease severity
were performed. At the lower, middle and upper thirds of plants, a diagram scale with nine levels of severity was used
and the resulting data were converted into the AUDPC. Gompertz, logistic, and monomolecular mathematical models
were tested in the disease severity curves for each third. Agronomics characteristics were evaluated as well. Significant
differences of AUDPC were found for the cotton plants thirds, and the middle third was the highest AUDPC. Signifi-
cant difference for the lower and upper thirds, whose AUDPC were highest on 0.90 m spacing, was observed too. The
disease progress curves of the thirds did not fit the tested models. Significant results to the both covers situations, where
the treatments grown on crotalária cover and without cover had highest AUDPC, were evidenced. The treatments with
C. spectabilis cover were taller than other treatments. Significant data were observed for the cover crops used and in the
treatments grown at 0.90 m spacing, to residual cover and crop yield, respectively.
Keywords: Pennisetum glaucum; Crotalaria spectabilis; Areolate Mildew; High-Density Crops and No-Till
1. Introduction
Areolate mildew, caused by fungus Ramularia areola
G.F. Atk., [syn. = Ramularia gossypii (Speg.) Cif., Cer-
cosporella gossypii Speg.], is among the main diseases
affecting cotton crops, standing out for its early onset,
leading to early defoliation and leaf lesions, decreasing
photosynthetic leaf area and resulting in losses in pro-
duction and fiber quality, in addition to high management
costs [1,2].
The management of this disease has been based on in-
tegrated measures, such as the use of partially resistant
cultivars, sowing season, and especially fungicide appli-
cation [3]. Thus, chemical control has been the measure
most used by growers in Brazil’s Center-West region to
reduce the R. areola inoculum when the disease reaches
25% of the leaf area in the lower third of plants [4-7],
given that productivity losses can reach 30% when ways
of control not are adopted, under the edaphoclimatic
conditions prevailing on region [8].
In that context, the use of cover crops to improve the
cultivation conditions has yielded positive effects on the
chemical, physical and biological properties of soil,
promoting nutrient cycling and providing adequate nutri-
tional balance for plants. With that, plants can better re-
act to diseases, improving growth conditions for crop
sequencing, in addition to providing greater soil conser-
vation, recovery and maintenance and improving its
productive potential in the middle and long term [9].
Another alternative for optimizing yield is to adopt
Epidemiologic Study of Ramularia areola under Different Soil Covers and Spacings, for Cotton Crops
shorter row spacing, a cost-effective method to reduce
pesticide applications [10,11], possibly even favoring
crop yield as reported in studies by [11].
Thus, changes to the management system and the
adoption of conservationist practices have been evi-
denced in works that confirm the advantages of using
these methods, encouraging the possibility of interaction
between them. With regard to the high-density crop sys-
tem, authors observed increases in plant height, yield,
chemical, physical and biological quality of the soil, by
using cover crops [9,12].
Therefore, the objective of this work was to evaluate
the progress of areolate mildew in cotton plants using
different soil covers and spacing rows.
2. Material and Methods
2.1. Performing the Experiment
The experiment was carried out at the experimental area
of the State University of Mato Grosso, Tangará da Serra
campus—MT, located at 14˚38'52.19" - 14˚38'57.80"S,
57˚25'52.38" - 57˚25'51.85"W, elevation 320 m. The soil
at the experimental area was classified as a clayish dys-
troferric Red Latosol [13].
The experimental area was prepared by tilling and
loosening the soil, by harrowing. The fertilization con-
sisted of applying P on the sowing row and topdressing
with K and N, 30 and 45 DAS, respectively, it done ac-
cordance with the nutritional requirements of the crop,
and through the chemical analysis of the soil results,
which showed adequate levels for most of the elements
(Table 1).
The experiment was performed in randomized blocks,
in a 2 × 3 factorial design, with two spacing (0.45 m and
0.90 m) and three soil cover conditions (no cover, Peni-
setum glaucum L. and Crotalaria spectabilis L.) with
four replications. The variety used was FMT 701, which
features a late cycle and is moderately susceptible to
areolate mildew [14]. Each plot consisted of eight and 16
rows, using six and 14 rows of useful area, according to
their respective spacings. Thus, plot size was 7 m × 7.20
m and the useful area evaluated was 50 m long, consid-
ering a 1.0 m long border and a one-row wide border on
each side. The space used between blocks and between
plots was 2.0 m and 0.50 m, respectively.
The soil covers were broadcast on the first week of
October 2011, using 40 to 50 kg of seeds ha1 for P.
glaucum L. and 6 to 8 kg of seeds ha1 for C. spectabilis
L., which correspond to potential biomass average pro-
duction of 5.2 tons·ha1 and 9.3 tons to hectare, respec-
tively [9]. Cover crops were dried prior to the flowering
period, 60 days after emergence [9].
To evaluate the persistence of dry biomass of the plant
species, 0.25 m² samples were obtained at random, using
an iron square, at three points within the useful area of
each plot, 176 days after sowing (DAS) (harvest period)
In order to reduce the influence of external factors on
the dissemination of the pathogen during the experiment,
three rows of maize (Zea mays ssp. mays L.) were
planted around the experiment and between blocks,
spaced 0.45 m apart, prior to soil cover management.
Cotton was sown in the first week of January 2012, 30
days after the plant covers were dried, in order to provide
more decomposition benefits, and consequently nutrient
release from some cover crops, due to their longer expo-
sure period to soil.
Pesticides were applied during the course of the ex-
periment, according to pest incidence. Two applications
of growth regulator were made—one during stage F1
(opening of the first flowers), and the other between the
FC stages (period between the last flowers and opening
of the first boll), when the cotton plants resumed growth
2.2. Inoculation with Ramularia areola and
Analysis of Disease Progress
Inoculation with R. areola was done in plants confined
with a 1 m2 area at the center of each plot, representing a
point source of inoculum [17], 60 days after sowing, at
the start of the reproductive stage (B1) of plants. The
inoculum was obtained by wetting the leaves of the cot-
ton plant using a brush, in an Erlermeyer flask containing
Table1. Interpretation of the chemical analysis of macro and micronutrients of a Dystroferric Red Latosol.
Elements/Results/Fertility Levels
pH (CaCl2) MO (%) P (meh) (mg/dm3) K (mg/dm3) Ca (cmolc/dm3) Mg (cmolc/dm3) CTC (cmolc/dm3)
5.30 2.50 2.00 0.15 2.05 1.69 7.00
V (%) S (mg/dm3) B (mg/dm3) Cu (mg/dm3) Fe (mg/dm3) Mn (mg/dm3) Zn (mg/dm3)
55.70 4.00 0.42 3.50 95.00 32.30 1.90
Baixo (B)”, “Muito Baixo (MB)”, “Médio (M)”, “Adequado (A)”, “Alto (A)”, “Muito Alto (MA)”.
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Epidemiologic Study of Ramularia areola under Different Soil Covers and Spacings, for Cotton Crops 2051
distilled water. The spore suspension was adjusted to the
concentration of 104 conidia mL1 of distilled water [18],
with the aid of a Neubauer chamber.
The analysis of the temporal progress of areolate mil-
dew consisted of the severity of 10 plants marked in each
plot, starting at the first symptoms of the disease, at an
interval of five to seven days.
The evaluations of temporal progress of R. areola in
the treatments took place by evaluating the severity of
the disease, in which severity was measured by a grade
scale adapted from the diagram scale devised by [1] fea-
turing nine levels of severity (Table 2).
The lower, middle and upper thirds of ten marked
plants were evaluated, considering as the lower third the
leaves arranged up to the 7th node of the main stem,
middle third from the 8th to 14th node, and upper third
above the 15th node [1].
The scores were weighted using the Mckinney index
[19] to calculate the disease index (DI) as a percentage,
which represents the severity of the disease, expressed by
the following equation:
 
%.. 100DIfvn x
Severity progress curves were created from the DI
values, and the area under the disease progress curve
(AUDPC) was calculated according to [17]:
ii ii
 
The treatments were compared using the area under
the disease progress curve for the severity of areolate
2.3. Fit of Mathematical Models
In order to study the progress curves of areolate mildew
and make comparisons of the epidemic of the disease
between treatments, classical mathematical models such
as logistic, Gompertz and monomolecular were tested, in
an attempt to fit them to the disease severity progress
11 11expyyrt
 
exp lnexpyyrt
 
11exp M
, in which:
yx = estimation of the disease; 00
yx = initial in-
oculum amount; r = specific rate of progress of the disease
Table 2. Coefficient of determination (R*2), standard deviation of the initial inoculum (X0) and standard deviation of the
infection rate (r) after fitting the Monomolecular, Logistic and Gompertz models to the data on the severity of areolate mil-
dew in cotton crops.
Lower Third Middle Third Upper Third
Treatments Models
R*2 (Y0) (r) R*2 (Y0) (r) R*2 (Y0) (r)
Logístico 29.00 0.005360.002244.80 0.009720.0060047.85 0.00023 0.00595
Gompertz 29.20 0.008050.001605.79 0.010070.0018654.98 0.00000 0.00191
Molecular 28.99 0.009460.0001710.29 0.014430.0002767.18 3822.77 0.00007
Logístico 26.22 0.021640.0006711.74 0.006790.0065042.88 0.00151 0.00921
Gompertz 26.24 0.005230.0012112.97 0.006940.0017946.29 0.00114 0.00235
Molecular 26.21 0.005740.0001112.90 0.011540.0001954.58 3480.61 0.00006
Logístico 11.24 0.005940.004642.41 0.013530.0073945.80 0.00118 0.00672
Gompertz 11.24 0.005520.001233.28 0.013880.0022949.32 0.00053 0.00193
Molecular 11.22 0.010480.000216.23 0.017620.0003260.20 3515.39 0.00006
Logístico 25.20 0.040660.003411.74 0.014430.0068940.04 0.00587 0.01038
Gompertz 0.29 256.905137002 1.79 0.014770.0021350.24 0.01731 0.00371
Molecular 25.19 0.022470.000411.42 0.016690.0003149.85 7428.54 0.00013
Logístico 21.39 0.011120.004250.87 0.012320.0077634.03 0.00772 0.01261
Gompertz 21.40 0.012850.001430.78 0.012620.0022436.50 0.00632 0.00382
Molecular 21.38 0.016790.000310.20 0.014870.0002744.24 9473.26 0.00017
Logístico 32.55 0.013140.003740.05 0.009850.0061750.26 0.00401 0.00939
Gompertz 32.56 0.020240.002570.31 0.010150.0018553.10 0.00294 0.00279
Molecular 32.54 0.017820.000300.22 0.013050.0002459.15 6070.18 0.00011
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Epidemiologic Study of Ramularia areola under Different Soil Covers and Spacings, for Cotton Crops
for each model; and t = time.
To select the regression model that best fit the data of
the disease progress curves, the following criteria were
collective considered: 1) highest adjusted coefficient of
determination (R*2), obtained from the linear regression
between the values predicted by the models (dependent
variable) and those observed (independent variable), 2)
lowest standard deviation for the initial inoculum and the
disease progress rate, and 3) lowest variance and most
random error distribution (observed severity minus se-
verity estimated by the model) [17].
2.4. Analysis of Soil Chemical Conditions under
the Influence of Cover Crops
In order to evaluate whether the chemical attributes of
the soil underwent any change due to the cover crops and
spacing, three soil samplings took place—the first before
the start of the experiment, the second at the star of
evaluations of disease incidence and severity (72 DAS),
and the third after the cotton harvest (176 DAS).
For the first collection, 20 grab samples were taken to
form a composite sample of the 0 - 20 cm layer, and then
submitted to routine chemical and physical analyses [12].
For the second and third samplings, four grab samples
were taken to form a composite sample of the 0 - 20 cm
and 20 - 40 cm layer, corresponding to each cover and
spacing condition, totaling 12 composite samples.
2.5. Seedling Emergence and Final Stand of
Cotton Plants
Emergence and final stand evaluations were carried out,
at 10 and 30 days after sowing, respectively, using 4.5 m²
of the useful area of the plot. The data were converted
into the percentage of seedlings with cotyledons above
ground or live plants [20]. After the evaluation of final
stand, the plants were lopped in order to maintain eight
plants per meter in all plots.
2.6. Cotton Plant Height
During the ripening period (FC), cotton plant height was
evaluated by sampling 10 plants per plot, measuring the
length, from the collar to the last apical bud, using a
measuring tape graduated in centimeters [12,21]. The
result was given in centimeters with the average for the
10 evaluated plants.
2.7. Evaluation of Climate Data
Climate data were obtained for the period of disease in-
oculation and evaluation (March-July 2012) from the
Meteorology Institute (INMET), in order to relate cli-
mate data to the epidemiology of areolate mildew.
2.8. Seed Cotton Yield
The harvest was done manually, over 4.5 m2 of the useful
area of each plot, in accordance with the methodology of
[12], adapted to the experimental conditions of this work.
The yield per plot was obtained by weighing the seed
cotton in a 0.005 kg precision scale, and later converted
into kg·ha1.
2.9. Data Analysis
The data were subjected to statistical analysis using
SISVAR 5.3 software [22], the means between treat-
ments were compared by Tukey’s test at 5% probability.
SAEG software (Federal University of Viçosa) was used
to the fit the mathematical models. Descriptive analysis
was carried out to interpret soil results.
3. Results
The progress curves of areolate mildew in the lower,
middle and upper thirds are depicted in Figure 1. The
first symptoms of the disease were detected twelve days
after inoculation, which corresponds to 72 days after
sowing (DAS) in all treatments and in the lower, middle
and up- per thirds of all evaluated plants.
By observing the peaks in the disease in the lower,
middle and upper thirds, a gradient was detected in that
order: in the lower third, the disease reached the peak of
its severity at 82 and 104 DAS, later decreasing the se-
verity curve starting at 111 DAS; at that time, the first
severity peak was seen in the middle third, with a second
peak at 125 DAS; the decline of the that curve coincided
with the peak of disease severity in the upper third, at
132 DAS, in which the disease surpassed 20% severity
only after 104 DAS (Figure 1).
The declines in the disease severity curves were attrib-
uted to the defoliation start caused by intense infection
by disease, influencing particularly the lower third, con-
sidering that the closure of the canopy of plants favors
infection with the disease in the lower section of the can-
Throughout the disease progress, favorable climate
conditions (temperature, moisture and rainfall) for
pathogen development were observed (Figure 2). Opti-
mal temperatures between 25˚C - 30˚C were recorded,
but with temperatures prevalence between 20˚C - 25˚C,
considered favorable for pathogen development.
Significant hours at 12˚C - 20˚C range were also re-
corded, between 116 and 128 DAS, coinciding with the
peak of the disease severity curve in the middle third a
preceding the peak of the disease severity curve in the
upper third.
Moisture values stood at over 13 hours of relative
humidity above 80%, with highs of 98% and lows of
38%, while rainfall data behaved alternately with the
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Epidemiologic Study of Ramularia areola under Different Soil Covers and Spacings, for Cotton Crops 2053
Figure 1. Progress curve of the Severity Index of areolate mildew in cotton plants, in the lower (a), middle (b) and upper (c)
thirds, as a function of days after sowing (DAS).
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Epidemiologic Study of Ramularia areola under Different Soil Covers and Spacings, for Cotton Crops
Figure 2. Climate data collected from the Meteorological Station (INMET), on the daily hours under temperatures of 12˚C -
20˚C, 20˚C - 25˚C, 25˚C - 30˚C and >30˚C (a), daily hours of relative humidity (UR) >80% and daily averages for high and
low UR (b) and rainfall (mm) (c).
occurrence of dry periods, and showing significant oc-
currence between 30 and 40 DAS, as well between 116
and 128 DAS, similar to the temperature pattern. Also
important is the occurrence of rainfall during the inocula-
tion period of the disease, 60 DAS, until near the start of
the onset of the disease on the plants.
With regard to the fit of the Logistic, Gompertz and
Monomolecular models (Table 2), used to evaluate dis-
ease progress more closely to reality [23], it was detected
that the disease severity progress curves did not fit any of
the three tested models, as the values of the coefficient of
determination (R*2)—one of the advisable criteria for
choosing the best model [17] were lower than 80%,
leading to unsatisfactory adjustments in the disease pro-
gress curves.
As the models did not fit the data, the treatments were
compared using the AUDPC of the disease in the lower,
middle and upper thirds, and significant effects of intera-
tion were observed just to spacing factor in relation the
plant thirds, it found the independence of the cover situa-
tions with another factors studied.
Significant results were obtained to the AUSPC in the
cover factor (Table 3), where the treatments grown under
cover C. spectabilis and without cover present highest
AUDPC, in comparison with the treatments grown under
cover of P. glaucum wich shown less AUDPC of disease.
The spacing factor related to the plant thirds (Table 4),
it found significative difference to AUDPC in all cotton
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Epidemiologic Study of Ramularia areola under Different Soil Covers and Spacings, for Cotton Crops 2055
Table 3. Area under Severity Progress Curve (AUDPC) of
disease as a function of two spacings, on the lower, middle
and upper thirds.
Spacings (m) Lower Third Middle Third Upper Third
Spacing. 0.45 2791.94 Bc 4139.35 Aa 3330.83 Bb
Spacing. 0.90 3486.85 Ab 4229.25 Aa 3692.22 Ab
CV (%) MSD 11.76 348.23/418.85
Means with uppercase letter in the column and minuscule letter in the line
do not differ from one another, according to Tukey’s test at 5%. “Coefficient
of Variation (CV)”, “Minimum Significant Difference (MSD)”.
plant thirds in spacing 0.45, wich the middle third shown
highest AUDPC of disease, in sequence the upper and
lower third. Similarly, the results observed to the cotton
grown in spacing 0.90, shown also highest AUDPC to
the medium third of the plant, however without statistical
difference for the other thirds.
Although statistically the disease severity hasn’t been
significant in the lower third of the plant, and it is note-
worthy the defoliation occurred in the lower third of the
plant (loss botton) interfered with the evaluation disease
progress on the leaves, in this plant portion, in order the
evaluation method of the disease progress used on this
work, and it not include the quantification of damages
occurred to the cotton crop, for the disease.
When we compare the plant thirds in relation to each
spacing (Table 4), we observe there was significative
difference to the lower and upper thirds, whose AUDPC
was highest in the spacing 0.90, hadn’t been observed
significative difference to the middle plants third.
No significant difference was observed in the variables
initial and final stand of the crop. However, the variable
height showed a significant result for the factor cover, in
that treatments with C. spectabilis cover showed higher
averages (Table 5). With regard to the residual cover of
cover crops at 176 DAS, a significant difference was
observed among cover averages, in which treatments
with P. glaucum showed higher averages than treatments
with C. spectabilis.
When evaluating seed cotton yield, significance was
found in the data for treatments under 0.90 m spacing,
which showed the highest yield averages.
This means there were controversies in the results for
disease severity and yield, as both variables were sig-
nificant for the treatments with 0.90 m spacing. However,
these results can be hypothetically explained by the more
intense underside loss in the 0.45 m spacing. That may
have interfered in the quantification of the disease on
those leaves, given that the method used to evaluate the
progress of the disease in this work does not quantify
losses and damage caused by the disease on the cotton
Consequently, treatments with 0.90 m spacing showed
greater disease severity because they did not have sig-
nificant underside loss, which made it possible to con-
tinue quantifying the disease, not interfering in yield re-
sults (Table 5).
Were realized the interpretation of the soil analyses to
evaluate the chemical attributes in the different soil cover
situations, in the 0 - 20 cm and 20 - 40 cm depths.
The data for 0 - 20 cm in the initial soil condition
(prior to the experiment) and all three cover situations
(72 DAS) are arranged in Figure 3. The graphs of the 20
- 40 cm analysis are represented in the Figure 4, of all
three cover situations, making a comparison between
non-covered soil and that covered with C. spectabilis and
P. glaucum, according to the soil analyses carried out at
72 DAS and 176 DAS.
Based on these data, for the 0 - 20 cm and 20 - 40 cm
layers alike, it can be observed that soil fertility provided
the same conditions for all treatments, making it a
non-relevant factor for the different levels of incidence
and severity obtained from each treatment, even though
certain differences were noticed in the levels of interpre-
tation approached with the factors in question.
It can also be observed that some elements like sulfur
(S), calcium (Ca) and magnesium (Mg) showed varia-
Another factor to observe is the level of P, explained
by the adsorption process by the soil matrix, which limit
P availability in the soil.
Thus, it was detected that the plant covers used in this
study did not alter the chemical composition of the soil,
so relevant, during the study period, showing there was
no interference in chemical soil attributes. In addition to
the recent use of cover crops in the area, this fact can be
explained in part by the clayish texture of the soil
(49.3%), which gives a tampon effect at soil, particularly
due to the occluded organic matter that remains protected
by soil aggregates.
4. Discussion
The infection on the thirds can be justified by the in-
crease in the inoculum in the lower third, as well as fa-
vorable climate conditions for pathogen development
observed in this work, resulting in greater infection in the
middle and upper thirds of the plant [1]. This is relevant
for the time of chemical control application against the
disease; it should take place when up to 20% of the leaf
area in the lower third is diseased [24], in order to avoid
infection on the remaining thirds of the plant.
The declines of the disease severity on the thirds pro-
vides an appropriate microclimate, which with favorable
moisture and temperature conditions results in early de-
foliation in the underside [8,25-27].
The infection of cotton plants by fungus R. areola
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Epidemiologic Study of Ramularia areola under Different Soil Covers and Spacings, for Cotton Crops
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Table 4. Plant height (cm), residual cover (Kg·ha1) and seed cotton yield, as a function of three cover situations and two
Cover situations Height (cm) Residual Cover (Kg·ha1) Seed Cotton Yield (Kg·ha1)
Without cover 102.0 b 0.0 c 2.468.1 a
P. glaucum 98.0 b 4.249.5 a 2.175.1 a
C. spectabilis 112.0 a 1.021.7 b 2.362.5 a
CV (%) 6.39 27.91 28.59
DMS 0.05 11.24 77.45
Spacings (m) Height (cm) Residual Cover (Kg·ha1) Seed Cotton Yield (Kg·ha1)
Spacing. 0.45 106.0 a 1.385.6 a 1.731.5 b
Spacing. 0.90 102.0 a 2.128.5 a 2.939.0 a
CV (%) 6.39 27.91 28.59
MSD 0.03 7.55 51.87
Means with the same letter in the column do not differ from one another, according to Tukey’s test at 5%. Data converted to the square root of X. “Coefficient
of Variation (CV)”, “Minimum Significant Difference (MSD)”.
Table 5. Area under Severity Progress Curve (AUDPC) of
disease as a function of tree cover situations.
Cover Situations AUDPC
Without cover 3771.85 a
P. glaucum 3366.20 b
C. spectabilis 3697.17 a
CV (%) 11.76
MSD 296.17
Means with the same letter in the column do not differ from one another,
according to Tukey’s test at 5%. “Coefficient of Variation (CV)”, “Mini-
mum Significant Difference (MSD)”.
requires a leaf wetting period following by drying [28],
as well as the presence of free water on plants favors the
germination of spores and infection by the pathogen [27].
According to the literature, the infection process of R.
areola begins under favorable temperature conditions
around 12˚C to 32˚C, the best being the range between
25˚C and 30˚C and relative air humidity above 80%,
which influences both conidia germination and germ tube
emission [27,28], in which humid nights followed by dry
days, without extended lead wetting periods, favor the
development of the disease [29].
In relation of the disease severity progress curves, did
not fit any of the three tested models. Although [30]
found similar results to the present study, in which the
severity progress curves for the red rot of sisal (Agave
sisalana Perrine) caused by fungus Aspergillus Niger did
not fit any of the tested mathematical models, [31] found
a better fit of monomolecular model for the progress
curves of areolate mildew in five cotton cultivars. Figure 3. Analysis of soil elements in the 0 - 20 cm layer, by
comparing all three cover situations at 72 DAS with the
nitial soil condition.
The results of AUSPC agree with studies realized by i
Epidemiologic Study of Ramularia areola under Different Soil Covers and Spacings, for Cotton Crops 2057
Figure 4. Analysis of soil elements in the 20 - 40 cm, by comparing all three cover situations at 72 DAS (a) and 176 DAS (b),
and the initial soil situation.
[32] evaluating the areolate mildew severity in different
handling systems, reported less severity of disease in
sowing direct system (SDS), whose principles are based
in the cover soil and in the crop turn, followed of con-
ventional system with crop turn biannual.
These same authors confirm yet that is possible to re-
duce significantly the incidence of diseases in cotton
crop just with the changes on the production system ac-
tually used, for example, by providing an adequate sup-
ply of straw in the SDS, this essential feature to the sys-
tem, making it possible to obtain a satisfactory level of
control of certain diseases.
In relation the disease severity on the thirds, [29] re-
lated the diseases occurrence on this portion of the plant,
is favored as a function of the accumulation of the mois-
ture in the lower canopy of plants.
The results of the thirds plant in relation of each spac-
ing, contrast the [29] information that relate the diseases
occurrance is favored as a function of dense crops, due to
shading that begins early in culture.
The plant height results corroborate those found by
[12], who while studying cotton plant cultivars under
organic system with no-tillage in different soil covers,
observed greater plant height on C. juncea straw for cul-
tivar BRS Itaúba.
However, in works with vegetal, grass and legume
species as soil cover for cotton crops (cultivar BRS
Cedro), no significant difference was observed for that
variable [15,33].
To the residual cover results, can be explained by
studies of [15]using vegetal species for soil cover in cot-
ton crops under no-till, values of 906 Kg·ha1 and 2.422
Kg·ha1 of straw were obtained for C. spectabilis and P.
glaucum, respectively, during the same period (175
This fact is explained by the low C/N ratio of legumes
such as C. spectabilis, leading some authors to suggest a
mixture of legumes and grasses in order to achieve an
intermediate C/N ratio. That makes it possible to de-
crease the rate of decomposition of vegetal wastes and
increase N supply compared to grass-only use [15].
The seed cotton yield results differ from those found
by [11], detected a significant difference in yield while
studying cotton varieties at different spacings (0.90 m
and 0.45 m), with superior yields in the high-density crop
In relation of the soil data, was observed variability in
some elements, that can be explained, as in the case of S,
or even by their export to the crop, as in the case of Ca,
which is a component that gives firmness plant structure,
and Mg, 75% of which is absorbed by the crop after be-
ing removed from the soil by the plant [34].
According to [35], the behavior of sulfate (form avail-
able to plants), is similar to that of nitrate, resulting from
the mineralization of organic matter, which is continuous
during the crop cycle and varies according to environ-
mental conditions.
5. Conclusion
Overall, significant effects are related to the covers situa-
tions, noting up lower AUDPC in cotton plants grown
Open Access AJPS
Epidemiologic Study of Ramularia areola under Different Soil Covers and Spacings, for Cotton Crops
under P. glaucum cover, and significant interaction re-
sults between spacing and plant thirds, where the middle
third present highest AUDPC in both spacing used, are
obtained. It was not possible to fit the disease severity
data of the thirds of the plant to any of the tested models.
Plant height was influenced by C. spectabilis as cover,
which showed the lowest average biomass residue. Even
showing greater disease severity, crop yield was higher
in the treatments with 0.90 m spacing. Soil fertility con-
ditions were similar for all treatments, not interfering
with the epidemiology of the disease.
6. Acknowledgements
We wish to thank the Coordination for the Improvement
of Higher Education Personnel (CAPES), for the grant
given to the first author; to the Graduate Environment
and Agricultural Production Systems Program (PPGAT)
and all faculty members for the support and assistance
given during the study period.
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