	Instituto Nacional de Tecnología Agropecuaria	Estación Experimental Agropecuaria Balcarce

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Detection of meteorological factors affecting the development of leaf blotch (Mycosphaerella graminicola (anamorph Septoria tritici)) on two susceptible wheat cultivars

MELEGARI¹ A.L., MOSCHINI² R.C. ¹UIB Balcarce EEA INTA-FCA

amelegari@balcarce.inta gov.ar

²Instituto de Clima y Agua CIRN INTA Castelar

rmoschini@cnia.inta.gov.ar

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Introduction

Leaf blotch of wheat is an important disease in most of the production areas of Argentina. Understanding the relationship between environment and disease development could improve control strategies.

The aim of this study was to identify the meteorological factors most strongly associated with disease severity, recorded on the top three leaves of susceptible wheat cultivars.

Materials and Methods

Disease severity. Picnidial coverage on flag leaf (F), F-1, and F-2 was recorded 3 times per crop season, on susceptible wheat cultivars San Agustin (1990 to 1992) and ProINTA Federal (1994), at UIB-FCA-INTA Balcarce, Argentina. Disease severity was calculated as the of the product of number of leaves within each level of foliar picnidial coverage, recorded according to Ziv-Eyal, 1978.

Meteorological data. Meteorological cumulative variables were calculated according to Moschini et al, 2004.

DPr: days with precipitation > 7 mí

DRH: days with RH > ó = 82 %.

MTx and MTn: mean of the daily records of Tx (maximum temperature) and Tn (minimum temperature).

DDTn: if daily Tn < 7 °ºC, the residuals 7 - Tn are accumulated.
DDTd (Td=(Tx+Tn)/2): if Td > ó = 14 °ºC (if Td > 24°ºC then Td = 24°ºC), residuals Td - 14 are accumulated.

NPTn: number of two day periods with Tn < 7 °ºC in both days.

The variables were accumulated from October 12 (stem elongation) until the end of crop cycle.

Statistical analyses. Linear multiple regression techniques were used to identify the strongest associations between mean severity data (n=12) and meteorological cumulative variables, considering determination coefficients values (R² ).

Environmental effect was quantified through the development of linear (selected by R² and Stepwise) and nonlinear (exponential) models.

General lineal models for estimating disease severity per leaf layer (n=36), were fit.

Results and Discussion

Models for predicting mean disease severity (DS%) are in Table1.

Table 1

Equation	R²
A- DS %= -14.71+3.15 DRH	0.791
B- DS %= -154.9+19.54 MTn	0.749
C- DS %= -101.6+1.99 DRH+11.09 MTn	0.925
D- DS %= -6.69+1.97 DRH+0.21 DDTd 0.44 DDTn	0.953
F- DS %= -34.1938 8.1855 Exp (0.0387 DRH +0.1575 MTn)	0.980

Figure 1. Click to enlarge

Graphical comparisons between the four epidemic progress curves estimated by exponential model (Equation F) vs. the three observed disease data per crop season, are showed in Figure 1.

General linear models, with leaf layer as significant classificatory variable, included DPr, DRH, DDTn and DDTd as meteorological variables (Table 2).

Table 2

Leaf	Equation
Flag	DS%= -8.895-3.01 DPr+2.192 DRH-0.414 DDTn+ 0.226 DDTd
F-1	DS%= -10.941+0.371 DPr+2.192 DRH-0.414 DDTn +0.226 DDTd
F-2	DS%= -2.175+0.354 DPr+2.192 DRH-0.414 DDTn+ 0.226 DDTd
A significant interactive effect between leaf layer and DPr was detected (R2=0.871, n=36)

Coakley et al (1985) found that the frequency of consecutive days with temperatures below 7°ºC at the end of tillering and start of stem elongation was negatively associated with S. tritici severity. In agreement, in this study the highest associations between disease severity and thermal effects were obtained with the cumulative variables DDTn (negative slope), MTn (positive slope) and DDTd (positive slope).
Previous work has shown that after starting stem elongation, disease development is driven by splashy precipitations. In accordance, in this work the frequency of days with precipitation greater than 7 mm (DPr) was found to be highly correlated with S. tritici severity.

Lovell et al. (2004) demonstrated that infection of the top three leaves could occur in the absence of splashy rainfall, being better simulated by dew. Concordantly, in the present study the frequency of days with relative humidity greater than 82 % (related to dewfall and light rain) was found to be the most strongly associated with the epidemic progression.

References

Coakley S.M,L.R.McDaniel,G.Shaner.1985 Model for predicting severity of Septoria tritici blotch on winterPhytopathology75:1245-1251.

Lovell D.J., Parker S.R., Hunter T., Welham S.J., Nichols A.R. 2004. Position of inoculim in the canopy affects the risk of septoria blotch epidemics in winter wheat. Plant Pathology (2004)53, 11-21.

Moschini R.C., Kraan G., Bariffi J.H. Análisis del efecto ambiental sobre el coeficiente de infección de Septoria tritici en trigo, en el sur de la región pampeana. VI Congreso Nacional del Trigo. Bahía Blanca, 20-22 octubre 2004

Ziv,O and Eyal, Z. 1978. Assessment of yield component losses caused in plants of spring wheat cultivars by selected isolates of Septoria tritici. Phytopathology 68:791-794.