Factors affecting development of Septoria tritici in winter wheat and its effect on yield

Severe infection with Septoria tritici occurred in four of five experiments designed to create a series of different disease epidemics. These experiments successfully identified periods suitable for infection. They also indicated the effect of sprays, timed before and after these periods, on disease development and yield.
Analysis of disease progress and weather records suggested that critical conditions for initial development of S. tritici occurred during early May at four sites. Heavy rain giving at least 10 mm on 1 day or a total of 10 mm or more on 2 or 3 successive days occurred at all four sites prior to the appearance of symptoms on a particular leaf layer, though less heavy rain may suffice to splash inoculum onto upper leaves in shorter, immature canopies where stem elongation is incomplete. At the fifth site, infection occurred later in May and disease failed to develop to a significant degree. At all sites, the length of the incubation period on any of the top three leaves was found to be between 396 and 496 degree days.
Control of winter epidemics of S. tritici had little effect on yield, whereas spray sequences commencing later than growth stage (GS) 31 but immediately prior to the critical periods provided the best disease control and yield benefit. Regression models incorporating, as independent variables, area under the S. tritici disease progress curve for any of the top three leaves from their emergence (GS 32-37) satisfactorily explained yield loss at the four sites where disease was severe. Consideration of leaf 2 or leaf 3 alone accounted for more than 82% of the variance at each site and a yield loss from infection of leaf 2 related to thermal time is suggested as 0.00265% per C per day from the appearance of symptoms.     

Patterns of development of Septoria nodorum and S. tritici in some winter wheat crops in Western Europe, 1981-83

In data collected at 19 sites in Western Europe during 1981-83. two patterns of development of Septoria nodorum and S. tritici on foliage of winter wheal were distinguished. In sudden outbreaks, lesions appeared simultaneously on the upper leaf layers of crops, usually after the end of stem extension; these outbreaks were ascribed to short, heavy rain storms in which pycnidiospore inoculum in basal leaves was elevated up to 60 cm through the crop canopy. Gradual epidemics were characterized by disease arising on successive leaf layers as they appeared during sustained periods of weather suitable for inoculum transport and infection.
The data indicate incubation periods of 2-4 weeks for S. nodorum and 3-5 weeks for S. tritici. it is suggested that a leaf layer cannot normally sustain more than one pathogen generation and that its infection arises from inoculum borne on leaves older than in the layer situated immediately below it. The potential level of disease in a crop may relate to the amount of inoculum present in spring. The proportions of disease caused by the two Septoria species varied greatly between sites and years, but the data provided no explanation.
It is concluded that a septoria forecast scheme needs to recognise the importance of sudden disease outbreaks and to include not only weather but also host growth and inoculum factors.     

Weather-based prediction of anthracnose severity using artificial neural network models

Data were collected and analysed from seven field sites in Australia, Brazil and Colombia on weather conditions and the severity of anthracnose disease of the tropical pasture legume Stylosanthes scabra caused by Colletotrichum gloeosporioides . Disease severity and weather data were analysed using artificial neural network (ANN) models developed using data from some or all field sites in Australia and/or South America to predict severity at other sites. Three series of models were developed using different weather summaries. Of these, ANN models with weather for the day of disease assessment and the previous 24 h period had the highest prediction success, and models trained on data from all sites within one continent correctly predicted disease severity in the other continent on more than 75% of days; the overall prediction error was 21·9% for the Australian and 22·1% for the South American model. Of the six cross-continent ANN models trained on pooled data for five sites from two continents to predict severity for the remaining sixth site, the model developed without data from Planaltina in Brazil was the most accurate, with >85% prediction success, and the model without Carimagua in Colombia was the least accurate, with only 54% success. In common with multiple regression models, moisture-related variables such as rain, leaf surface wetness and variables that influence moisture availability such as radiation and wind on the day of disease severity assessment or the day before assessment were the most important weather variables in all ANN models. A set of weights from the ANN models was used to calculate the overall risk of anthracnose for the various sites. Sites with high and low anthracnose risk are present in both continents, and weather conditions at centres of diversity in Brazil and Colombia do not appear to be more conducive than conditions in Australia to serious anthracnose development.     

Models for predicting potential yield loss of wheat caused by stripe rust in the U.S. Pacific Northwest

Climatic variation in the U.S. Pacific Northwest (PNW) affects epidemics of wheat stripe rust caused by Puccinia striiformis f. sp. tritici. Previous models only estimated disease severity at the flowering stage, which may not predict the actual yield loss. To identify weather factors correlated to stripe rust epidemics and develop models for predicting potential yield loss, correlation and regression analyses were conducted using weather parameters and historical yield loss data from 1993 to 2007 for winter wheat and 1995 to 2007 for spring wheat. Among 1,376 weather variables, 54 were correlated to yield loss of winter wheat and 18 to yield loss of spring wheat. Among the seasons, winter temperature variables were more highly correlated to wheat yield loss than the other seasons. The sum of daily temperatures and accumulated negative degree days of February were more highly correlated to winter wheat yield loss than the other monthly winter variables. In addition, the number of winter rainfall days was found correlated with yield loss. Six yield loss models were selected for each of winter and spring wheats based on their better correlation coefficients, time of weather data availability during the crop season, and better performance in validation tests. Compared with previous models, the new system of using a series of the selected models has advantages that should make it more suitable for forecasting and managing stripe rust in the major wheat growing areas in the U.S. PNW, where the weather conditions have become more favorable to stripe rust.     

The reliability of visual estimates of disease severity on cereal leaves

Visual estimates of wheat disease severity were compared with actual severities determined using image analysis of tracings of diseased leaves. Septoria tritici , leaf senescence and Erysiphe graminis were studied. Observer estimates were widely scattered about the actual severities (i.e. they were imprecise), differed substantially from the actual severities even after averaging (i.e. they were inacctirate), and varied considerably over short time-scales. Relative bias decreased with increasing disease severity. In a comparison of three seed treatments to control powdery mildew on winter barley, visual assessment errors altered the conclusions of the experiment. Two treatments were statistically indistinguishable on the basis of visual severity estimates, while estimates obtained by image analysis showed that one seed treatment was twice as effective as the other.     

Measurements of spatial patterns of disease in winter wheat crops and the implications for sampling

Over a period of three crop seasons the spatial patterns of some common diseases of winter wheat were investigated at growth stages (GS) 31/33 and 59/61. A large-scale sampling procedure, using randomly positioned transects and based on the theory of autocorrelation analysis, is described. This novel technique enables valid tests of significance to be made on the autocorrelation coefficients calculated. The most complete data obtained were for Septoria tritici blotch which was found to have a near random pattern on scales between 31 cm and 31 m at the growth stages investigated. However, the severity of S. tritici blotch was found to be autocorrelated at scales below 1 m in some fields. With the exceptions of powdery mildew at GS 31/33 and yellow rust at GS 59/61, the other diseases also exhibited a near random pattern. Therefore, almost any convenient sampling pattern, with reasonable overall coverage, will be adequate to obtain samples for monitoring winter wheat at growth stages 31 and 59.     

Thresholds for control of Septoria spp. in winter wheat based on precipitation and growth stage

A simple forecasting model for Septoria spp. in winter wheat was developed based on historical data (1980–89) including precipitation, growth stage, disease severity and yield response to fungicide treatments. The number of days with precipitation ≥ 1 mm, calculated during a 30-day period starting at the beginning of stem elongation (GS 32), correlated well with attacks of Septoria spp. later in the season and with the yield response in trials with fungicide treatments. Seven or 8 days with rainfall ≥ 1 mm was suggested as a threshold for Septoria treatment. Model development and possible further improvements are discussed.     

The combined effects of multiple diseases and climatic conditions on thousand kernel weight losses in winter wheat

Thousand kernel weight (TKW) is a yield component associated with grain quality. It is reported in the literature that TKW is significantly influenced by varieties, agro-ecological conditions and disease indices, but the influence of their interactions on TKW loss has rarely been taken into consideration. The main objective of this study was to examine the combined effects of multiple diseases and climatic conditions on TKW losses in winter wheat. Leaf rust, powdery mildew, and Septoria tritici blotch were considered biotic predictor variables in regression models explaining TKW losses. Monthly averages of temperature, relative humidity and total rainfall in May and June in the 2006–2013 growing seasons were used as abiotic predictor variables. The results of this study indicated a significant low positive correlation between yield loss and TKW loss in the two varieties. TKW losses were less influenced by leaf rust, powdery mildew, and Septoria tritici blotch than yield losses. The significant influence of the interaction between variety and the environmental conditions on TKW loss was confirmed from the general linear model function. The results of this study indicated that factors influencing yield and yield component losses are part of the complex environment, and the relationship between them should be investigated with respect to their interactions.     

Development of empirical forecasting models for rice blast based on weather factors

Regression equations used as empirical models to predict rice blast caused by Pyricularia grisea on cv. Jinheung at Icheon, South Korea, and on cvs. IR50 and C22 at Cavinti, Philippines, were generated, using weather factors identified by the WINDOW PANE program to be highly correlated with disease. Consecutive days with RH≥80% (CDRH80), number of days with RH≥80% (NDRH80), consecutive days with precipitation, and number of days with precipitation ≥ 84 mm day⁻¹ were important variables predicting blast at Icheon. Total precipitation, precipitation frequency, mean maximum and minimum temperatures, number of days with wind speed above 3.5 m s⁻¹, CDRH80, and NDRH80 were important predictors of blast at Cavinti. The Allen's predicted error sum of squares (PRESS) criterion and a cross-validation procedure were used to evaluate the models using data that were not included in model development. Validation test showed that all models developed for the two sites, except the models predicting maximum lesion number and panicle blast incidence at Icheon, and panicle blast severity on IR50 at Cavinti, predicted blast reasonably well based on low PRESS values and close to zero average prediction errors. These models can be applied in actual rice production systems, but future validation is needed to further improve their predictive ability.     

Effects of treatments to perennial ryegrass on the development of Septoria spp. in a subsequent crop of winter wheat

An experiment started in spring 1979 tested the effects of different treatments to perennial ryegrass, established as pure stands or undersown in spring wheat, on the severity of septoria diseases on the grass and in a following crop of winter wheat, sown in autumn 1980. Other plots were fallowed in 1979 and 1980 before sowing to winter wheat, also in autumn 1980.
Septoria tritici was most severe in winter wheat after fallow and least severe in wheat that had been direct-drilled after ryegrass. These effects were attributed to differences in amounts of available nitrogen, and consequent differences in crop growth, rather than to any differences in primary inoculum.
Symptoms attributed to S. nodorum on the ryegrass were more common where the grass had been established under spring wheat than where it had been sown as a pure stand. They also tended to be more common where ryegrass had been inoculated with spores of S. nodorum than where it had been sprayed with captafol. Similar effects on symptoms attributed to Septoria spp. (mostly S. tritici ) on the wheat were apparent in July. The results support the conclusion that the greater severity of septoria diseases that often occurs on wheat after grass than after non-graminaceous breaks, is probably due in part to survival of the pathogens on grass and, in some circumstances, on debris remaining from a previous wheat crop. However, other factors are also likely to be involved.     

Decreasing azole sensitivity of Z. tritici in Europe contributes to reduced and varying field efficacy

Journal of Plant Diseases and Protection - Septoria tritici blotch (STB; Zymoseptoria tritici) is the most important leaf disease of wheat in Northern and Western Europe. The problem of fungicide...     

Spatial distributions of Septoria nodorum and S. tritici within crops of winter wheat

In some crops of winter wheat selected from a range monitored in Western Europe during 1981-83, Septoria nodovum and S . tritici were spatially very uniformly distributed from the beginning of the growing season onwards. A cube root transformation produced a constant variance in lesion numbers per leaf, similar for both pathogens at about 0.5. This permits the sample size needed for a given accuracy to be estimated. Counts of conidia washed from leaves by a standard procedure had a constant coefficient of variation, independent of disease level. Large samples would be necessary for accurate counts, particularly if leaves from different layers were examined separately. The pattern of lesion numbers on leaves was best described by a negative binomial distribution: this predicts an incidence-severity curve to which the data conformed closely. Hence incidence estimates can be used to estimate severity, which may be more economical of sampling effort. Correlations between lesion counts on different leaves of the same tiller were negative and highly significant for S. nodorum in 1982, but positive and significant for S. tritici in 1983. The causes of this difference are unknown.     

Interactions between Erysiphe graminis and Septoria nodorum on wheat

Interactions between Erysiphe graminis f.sp. tritici and Septoria nodorum on wheat were studied in the greenhouse and in a 2-year field experiment using artificial inoculation. The integrated form of the logistic growth model dy/dt = ry (1 -y/K ), with infection rate r and final accumulated disease K , was fitted to the disease progress data. Septoria nodorum substantially reduced the disease severities of E. graminis , and caused significant reductions of at least 60% in final accumulated disease K of E. graminis. In the field trials, E. graminis increased the final accumulated disease K of S. nodorum. Owing to the extremely low severity of E. graminis , the increase of S. nodorum severity was small, and significance was given in one of the two years only, with an increase in K of roughly 30%. In the pot experiment, final accumulated disease K of S. nodorum remained unchanged, but there was a significant 30% increase in the infection rate r of S. nodorum. The difference between field and pot trials was explained by the climatic conditions in the greenhouse which excluded secondary infections of 5. nodorum , and which are important factors for disease progress in the field.     

Airborne inoculum as a major source of Septoria tritici (Mycosphaerella graminicola) infections in winter wheat crops in the UK

The pattern and extent of primary infection by Septoria tritici were compared over a period of 3 years in winter wheat grown at sites with differing histories and from seed stocks obtained in different countries, in the open, under airtight cover and in sterilized soil. Only the airtight cover altered the number of lesions found, substantially reducing it. Lesions were evenly distributed. Lesions were found throughout the autumn and occasionally in the winter and spring on wheat seedlings exposed in trays to the open air for periods of 1 week, then given good conditions for infection to occur. This was true even at a site 0.4 km distant from wheat residues. The results show that the main source of primary infection of winter wheat in these experiments was evenly dispersed and airborne. It probably consisted mainly of ascospores of Mycosphaerella graminicola.     

Epidemics of ray blight on pyrethrum are linked to seed contamination and overwintering inoculum of Phoma ligulicola var. inoxydabilis

Ray blight, caused by Phoma ligulicola var. inoxydabilis, is the most damaging disease of pyrethrum (Tanacetum cinerariifolium) in Australia. Data collected from 72 plots in commercial pyrethrum fields since 2001 to 2009 revealed substantial annual variations in isolation frequency of the pathogen during semidormancy of the crop in autumn and winter. Isolation frequency of the pathogen during this time and subsequent outbreaks of ray blight in spring were similar across the eight production regions where sampling was conducted, and isolation frequency of the pathogen was linearly correlated (r = 0.88; P < 0.0001) with subsequent defoliation severity when plants commenced growth in spring. Isolation frequency and defoliation severity also were correlated with the incidence of seed infested with P. ligulicola var. inoxydabilis (r = 0.71 and 0.44, respectively; P < 0.0001 in both correlations). Highly accurate risk algorithms for the occurrence of severe epidemics of ray blight were constructed using logistic regression. A model based solely on isolation frequency of the pathogen over autumn and winter correctly predicted epidemic development in 92% of fields. Another model utilizing the incidence of infested seed and rain-temperature interactions in early autumn (austral March and April) and late winter (austral June and July) had similar predictive ability (92% accuracy). Path analysis modeling was used to disentangle interrelationships among the explanatory variables used in the second logistic regression model. The analysis indicated that seedborne inoculum of P. ligulicola var. inoxydabilis contributes indirectly to ray blight defoliation severity through directly increasing overwintering frequency of the pathogen. Autumn and fall weather variables were modeled to have indirect effects on defoliation severity through increasing overwintering success of the pathogen but also direct effects on defoliation severity. Collectively, the analyses point to several critical stages in the disease cycle that can be targeted to minimize the probability of regional epidemics of ray blight in this perennial pathosystem.     

Identification and Molecular Mapping of a Gene in Wheat Conferring Resistance to Mycosphaerella graminicola

ABSTRACT Septoria tritici leaf blotch (STB), caused by the ascomycete Mycosphaerella graminicola (anamorph Septoria tritici), is an economically important disease of wheat. Breeding for resistance to STB is the most effective means to control this disease and can be facilitated through the use of molecular markers. However, molecular markers linked to most genes for resistance to STB are not yet available. This study was conducted to test for resistance in the parents of a standard wheat mapping population and to map any resistance genes identified. The population consisted of 130 F(10) recombinant-inbred lines (RILs) from a cross between the synthetic hexaploid wheat W7984 and cv. Opata 85. Genetic analysis indicated that a single major gene controls resistance to M. graminicola in this population. This putative resistance gene is now designated Stb8 and was mapped with respect to amplified fragment length polymorphism (AFLP) and microsatellite markers. An AFLP marker, EcoRI-ACG/MseI-CAG5, was linked in repulsion with the resistance gene at a distance of approximately 5.3 centimorgans (cM). Two flanking microsatellite markers, Xgwm146 and Xgwm577, were linked to the Stb8 gene on the long arm of wheat chromosome 7B at distances of 3.5 and 5.3 cM, respectively. The microsatellite markers identified in this study have potential for use in marker-assisted selection in breeding programs and for pyramiding of Stb8 with other genes for resistance to M. graminicola in wheat.     

Disease-weather relationships for powdery mildew and yellow rust on winter wheat

Key weather factors determining the occurrence and severity of powdery mildew and yellow rust epidemics on winter wheat were identified. Empirical models were formulated to qualitatively predict a damaging epidemic (>5% severity) and quantitatively predict the disease severity given a damaging epidemic occurred. The disease data used was from field experiments at 12 locations in the UK covering the period from 1994 to 2002 with matching data from weather stations within a 5 km range. Wind in December to February was the most influential factor for a damaging epidemic of powdery mildew. Disease severity was best identified by a model with temperature, humidity, and rain in April to June. For yellow rust, the temperature in February to June was the most influential factor for a damaging epidemic as well as for disease severity. The qualitative models identified favorable circumstances for damaging epidemics, but damaging epidemics did not always occur in such circumstances, probably due to other factors such as the availability of initial inoculum and cultivar resistance.     

Influence of crop growth and structure on the risk of epidemics by Mycosphaerella graminicola (Septoria tritici) in winter wheat

Generally, it is recognized that inocula of Septoria tritici present on the basal leaves of winter wheat crops are spread towards the top of the canopy by splashy rainfall. This mechanism of inoculum dispersal is commonly accepted to be a key limit on disease progression. Therefore, attempts to forecast epidemics of S. tritici often quantify rainfall by some means, but largely ignore measurement of pathogen and host variables. In the present study, we show that new wheat leaves emerge initially at a height below established leaves that can contain sporulating lesions of S. tritici . This presents the possibility of horizontal inoculum transfer, even without splashy rainfall. The extent and duration of overlap between emergent and established leaves was found to differ considerably with cultivar and sowing date. Nitrogen application had little effect on overlap, because differences in crop phenology, e.g. leaf area and nodal length, were relative. However, estimates of raindrop penetration to the base of crop canopies suggested that vertical movement of inoculum is affected by nitrogen application. Crops receiving more nitrogen are denser, and therefore less rainfall reaches the base of the canopy. The interactions between crop and pathogen development are discussed with reference to the implications for predicting disease risk. In particular, cultivar traits that promote disease escape are quantified.     

A predictive model for early-warning of Septoria leaf blotch on winter wheat

Disease–weather relationships influencing Septoria leaf blotch (SLB) preceding growth stage (GS) 31 were identified using data from 12 sites in the UK covering 8 years. Based on these relationships, an early-warning predictive model for SLB on winter wheat was formulated to predict the occurrence of a damaging epidemic (defined as disease severity of 5% or > 5% on the top three leaf layers). The final model was based on accumulated rain > 3 mm in the 80-day period preceding GS 31 (roughly from early-February to the end of April) and accumulated minimum temperature with a 0°C base in the 50-day period starting from 120 days preceding GS 31 (approximately January and February). The model was validated on an independent data set on which the prediction accuracy was influenced by cultivar resistance. Over all observations, the model had a true positive proportion of 0.61, a true negative proportion of 0.73, a sensitivity of 0.83, and a specificity of 0.18. True negative proportion increased to 0.85 for resistant cultivars and decreased to 0.50 for susceptible cultivars. Potential fungicide savings are most likely to be made with resistant cultivars, but such benefits would need to be identified with an in-depth evaluation.     

Changes in agronomic practices and incidence and severity of diseases in winter wheat in England and Wales between 1999 and 2019

In continuation of the annual national surveys of winter wheat, which began in 1970, samples from between 250 and 350 randomly selected wheat crops in England and Wales between 1999 to 2019 were visually assessed for disease symptoms during the milky ripe development stages (GS 73–75). Septoria tritici blotch was the most prevalent and severe foliar disease each year, although annual levels fluctuated considerably and there was no overall significant change over the two decades. Incidence of brown rust, yellow rust, take-all, and barley yellow dwarf virus also showed no significant overall change during the survey period, whereas glume blotch, powdery mildew, eyespot, and sharp eyespot all showed significant decline. Fusarium ear blight has significantly increased in both incidence and severity, causing a serious epidemic in 2012, when 96% of crops were affected. Tan spot has been the third most prevalent foliar disease since 2009 although severity is still very low. Regional disease levels were consistent over the two decades, providing reliable baselines to measure changes in seasonal disease severity. There were significant changes in agronomic practice with a rise to predominance of minimum tillage over the use of ploughing, decreases in overall disease susceptibility of cultivars grown, a major increase in the use of oilseed rape in the rotation and a long-term trend towards earlier sowing. Fungicide use increased considerably, with over 98% crops sprayed and an average of 3.5 applications made per crop each year since 2014. Implications of changes over the last 21 years are discussed.