Physiological Traits Determining Yield Tolerance of Wheat to Foliar Diseases.

Tolerance is defined as the ability of one cultivar to yield more than another cultivar under similar disease severity. If both cultivars suffer an equal loss in healthy (green) leaf area duration (HAD) over the grain filling period due to disease presence, then the yield loss per unit HAD loss is smaller for a more tolerant cultivar. Little is understood of what physiological and developmental traits of cultivars determine disease tolerance. In this study, we use a mathematical model of wheat to investigate the effect of a wide range of wheat phenotypes on tolerance. During the phase from stem extension to anthesis, the model calculates the assimilate source and sink potential, allowing for dynamic changes to the source-sink balance by partitioning assimilates between ear development and storage of water-soluble carbon (WSC) reserves, according to assimilate availability. To quantify tolerance, rates of epidemic progress were varied on each phenotype, leading to different levels of HAD loss during the postanthesis, grain-filling period. Model outputs show that the main determinant of tolerance is the total amount of assimilate produced per grain during the rapid grain-fill period, leading to a strong positive correlation between HAD per grain and tolerance. Reductions in traits that affect carbon assimilation rate and increases in traits that determine the amount of structural biomass in the plant increase disease tolerance through their associated reduction in number of grains per ear. Some of the most influential traits are the canopy green area index, carbon use efficiency, and leaf specific weight. Increased WSC accumulation can either increase or decrease tolerance. Furthermore, a cultivar is shown to be maximally tolerant when a crop is able to just fill its total sink size in the presence of disease. The model has identified influential functional traits and established that their associations with tolerance have a mechanistic basis.

Identifying circumstances under which high insecticide dose increases or decreases resistance selection.

Insect management strategies for agricultural crop pests must reduce selection for insecticide resistant mutants while providing effective control of the insect pest. One management strategy that has long been advocated is the application of insecticides at the maximum permitted dose. This has been found, under some circumstances, to be able to prevent the resistance allele frequency from increasing. However this approach may, under different circumstances, lead to rapid selection for resistance to the insecticide. To test when a high dose would be an effective resistance management strategy, we present a flexible deterministic model of a population of an insect pest of agricultural crops. The model includes several possible life-history traits including sexual or asexual reproduction, diploid or haplodiploid genetics, univoltine or multivoltine life cycle, so that the high dose strategy can be tested for many different insect pests. Using this model we aim to identify the key characteristics of pests that make either a high dose or a low dose of insecticide optimal for resistance management. Two outputs are explored: firstly whether the frequency of the resistance allele increases over time or remains low indefinitely; and secondly whether lowering the dose of insecticide applied reduces or increases the rate of selection for the resistance allele. It is demonstrated that with high immigration resistance can be suppressed. This suppression however, is rarely lost if the insecticide dose is reduced, and is absent altogether when individuals move from the treated population back into an untreated population. Reducing the dose of insecticide often resulted in slower development of resistance, except where the population combined a high influx of less resistant individuals into the treated population, a recessive resistance gene and a high efficacy, in which case reducing the dose of insecticide could result in faster selection for resistance.

Targeting Fungicide Inputs According to Need.

Fungicides should be used to the extent required to minimize economic costs of disease in a given field in a given season. The maximum number of treatments and maximum dose per treatment are set by fungicide manufacturers and regulators at a level that provides effective control under high disease pressure. Lower doses are economically optimal under low or moderate disease pressure, or where other control measures such as resistant cultivars constrain epidemics. Farmers in many countries often apply reduced doses, although they may still apply higher doses than the optimum to insure against losses in high disease seasons. Evidence supports reducing the number of treatments and reducing the applied dose to slow the evolution of fungicide resistance. The continuing research challenge is to improve prediction of future disease damage and account for the combined effect of integrated control measures to estimate the optimum number of treatments and the optimum dose needed to minimize economic costs. The theory for optimizing dose is well developed but requires translation into decision tools because the current basis for farmers' dose decisions is unclear.

Dose and number of applications that maximize fungicide effective life exemplified by Zymoseptoria tritici on wheat - a model analysis.

Two key decisions that need to be taken about a fungicide treatment programme are (i) the number of applications that should be used per crop growing season, and (ii) the dosage that should be used in each application. There are two opposing considerations, with control efficacy improved by a higher number of applications and higher dose, and resistance management improved by a lower number of applications and lower dose. Resistance management aims to prolong the effective life of the fungicide, defined as the time between its introduction onto the market for use on the target pathogen, and the moment when effective control is lost due to a build-up of fungicide resistance. Thus, the question is whether there are optimal combinations of dose rate and number of applications that both provide effective control and lead to a longer effective life. In this paper, it is shown how a range of spray programmes can be compared and optimal programmes selected. This is explored with Zymoseptoria tritici on wheat and a quinone outside inhibitor (QoI) fungicide. For this pathogen-fungicide combination, a single treatment provided effective control under the simulated disease pressure, but only if the application timing was optimal and the dose was close to the maximum permitted. Programmes with three applications were generally not optimal as they exerted too much selection for resistance. Two-application fungicide programmes balanced effective control with reasonable flexibility of dose and application timing, and low resistance selection, leading to long effective lives of the fungicide.

Optimal fungicide application timings for disease control are also an effective anti-resistance strategy: a case study for Zymoseptoria tritici (Mycosphaerella graminicola) on wheat.

Strategies to slow fungicide resistance evolution often advocate early "prophylactic" fungicide application and avoidance of "curative" treatments where possible. There is little evidence to support such guidance. Fungicide applications are usually timed to maximize the efficiency of disease control during the yield-forming period. This article reports mathematical modeling to explore whether earlier timings might be more beneficial for fungicide resistance management compared with the timings that are optimal for efficacy. There are two key timings for fungicide treatment of winter wheat in the United Kingdom: full emergence of leaf three (counting down the canopy) and full emergence of the flag leaf (leaf 1). These timings (referred to as T1 and T2, respectively) maximize disease control on the upper leaves of the crop canopy that are crucial to yield. A differential equation model was developed to track the dynamics of leaf emergence and senescence, epidemic growth, fungicide efficacy, and selection for a resistant strain. The model represented Zymoseptoria tritici on wheat treated twice at varying spray timings. At all fungicide doses tested, moving one or both of the two sprays earlier than the normal T1 and T2 timings reduced selection but also reduced efficacy. Despite these opposing effects, at a fungicide dose just sufficient to obtain effective control, the T1 and T2 timings optimized fungicide effective life (the number of years that effective control can be maintained). At a higher dose, earlier spray timings maximized effective life but caused some reduction in efficacy, whereas the T1 and T2 timings maximized efficacy but resulted in an effective life 1 year shorter than the maximum achievable.

The usefulness of fungicide mixtures and alternation for delaying the selection for resistance in populations of Mycosphaerella graminicola on winter wheat: a modeling analysis.

A fungicide resistance model (reported and tested previously) was amended to describe the development of resistance in Mycosphaerella graminicola populations in winter wheat (Triticum aestivum) crops in two sets of fields, connected by spore dispersal. The model was used to evaluate the usefulness of concurrent, alternating, or mixture use of two high-resistance-risk fungicides as resistance management strategies. We determined the effect on the usefulness of each strategy of (i) fitness costs of resistance, (ii) partial resistance to fungicides, (iii) differences in the dose-response curves and decay rates between fungicides, and (iv) different frequencies of the double-resistant strain at the start of a treatment strategy. Parameter values for the quinine outside inhibitor pyraclostrobin were used to represent two fungicides with differing modes of action. The effectiveness of each strategy was quantified as the maximum number of growing seasons that disease was effectively controlled in both sets of fields. For all scenarios, the maximum effective lives achieved by the use of the strategies were in the order mixtures ≥ alternation ≥ concurrent use. Mixtures were of particular benefit where the pathogen strain resistant to both modes of action incurred a fitness penalty or was present at a low initial frequency.

Accounting for the economic risk caused by variation in disease severity in fungicide dose decisions, exemplified for Mycosphaerella graminicola on winter wheat.

A method is presented to calculate economic optimum fungicide doses accounting for the risk aversion of growers responding to variability in disease severity between crops. Simple dose-response and disease-yield loss functions are used to estimate net disease-related costs (fungicide cost plus disease-induced yield loss) as a function of dose and untreated severity. With fairly general assumptions about the shapes of the probability distribution of disease severity and the other functions involved, we show that a choice of fungicide dose which minimizes net costs, on average, across seasons results in occasional large net costs caused by inadequate control in high disease seasons. This may be unacceptable to a grower with limited capital. A risk-averse grower can choose to reduce the size and frequency of such losses by applying a higher dose as insurance. For example, a grower may decide to accept "high-loss" years 1 year in 10 or 1 year in 20 (i.e., specifying a proportion of years in which disease severity and net costs will be above a specified level). Our analysis shows that taking into account disease severity variation and risk aversion will usually increase the dose applied by an economically rational grower. The analysis is illustrated with data on Septoria tritici leaf blotch of wheat caused by Mycosphaerella graminicola. Observations from untreated field plots at sites across England over 3 years were used to estimate the probability distribution of disease severities at mid-grain filling. In the absence of a fully reliable disease forecasting scheme, reducing the frequency of high-loss years requires substantially higher doses to be applied to all crops. Disease-resistant cultivars reduce both the optimal dose at all levels of risk and the disease-related costs at all doses.

Delaying selection for fungicide insensitivity by mixing fungicides at a low and high risk of resistance development: a modeling analysis.

This study used mathematical modeling to predict whether mixtures of a high-resistance-risk and a low-risk fungicide delay selection for resistance against the high-risk fungicide. We used the winter wheat and Mycosphaerella graminicola host-pathogen system as an example, with a quinone outside inhibitor fungicide as the high-risk and chlorothalonil as the low-risk fungicide. The usefulness of the mixing strategy was measured as the "effective life": the number of seasons that the disease-induced reduction of the integral of canopy green area index during the yield forming period could be kept <5%. We determined effective lives for strategies in which the dose rate (i) was constant for both the low-risk and high-risk fungicides, (ii) was constant for the low-risk fungicide but could increase for the high-risk fungicide, and (iii) was adjusted for both fungicides but their ratio in the mixture was fixed. The effective life was highest when applying the full label-recommended dose of the low-risk fungicide and adjusting the dose of the high-risk fungicide each season to the level required to maintain effective control. This strategy resulted in a predicted effective life of ≤ 12 years compared with 3 to 4 years when using the high risk fungicide alone.

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.

Major genetic changes in wheat with potential to affect disease tolerance.

ABSTRACT Selection through plant breeding has resulted in most elite winter wheat germplasm in the United Kingdom containing the Rht-D1b semi-dwarfing allele, the 1BL.1RS chromosome arm translocation with rye, and an allele conferring suppression of awns. Near-isogenic lines (NILs) were used to test whether these major genetic changes have had any effect on disease tolerance. The ability of the NILs to tolerate epidemics of Septoria leaf blotch or stripe rust was measured in four field experiments over two seasons. Tolerance was quantified as yield loss per unit of green canopy area lost to disease. There was a trend for the presence of the 1BL.1RS translocation to decrease tolerance; however, this was not consistent across experiments and there was no effect of semi-dwarfing. The awned NIL exhibited decreased tolerance compared with the unawned NIL. There were significant differences in tolerance between the cultivar backgrounds in which the NILs were developed. Tolerance was lower in the modern genetic background of Weston, released in 1996, than in the genetic background of Maris Hunstman, released in 1972. The data suggest that certain physiological traits were associated with the tolerance differences among the backgrounds in these experiments. Potential yield, accumulation of stem soluble carbohydrate reserves, and grain sink capacity were negatively correlated with tolerance, whereas flag leaf area was positively correlated.

Steps in predicting the relationship of yield on fungicide dose.

ABSTRACT A set of hypothetical steps has been defined, which links fungicide dose to marketable yield, whereby (i) increasing dose decreases symptom area, according to a dose-response curve, (ii) decreased symptom area increases crop green area index (GAI), (iii) increasing GAI increases fractional interception of photosynthetically active radiation, (iv) increased fractional interception increases crop dry matter accumulation, and (v) yield increases, depending on the partitioning of dry matter to the marketable fraction. One equation represented all five steps. By integrating this equation for light interception during the yield forming period and differentiating with respect to the ratio of fungicide cost over yield value, an analytical solution was obtained for the economic optimum dose. Taking published ranges of parameter values for the Septoria tritici wheat pathosystem as an example, yield-response curves and optimum doses were biologically plausible when compared with data from four field experiments. The analytical and empirical results imply that the dose required to optimize economic return will vary substantially between sites, seasons, and cultivars. Sensitivity analyses identified parameters describing specific facets of disease severity, fungicide efficacy, and assimilate partitioning as most influential in determining the dose optimum.