A New Model to Measure Yield Losses Caused by Stem Rust in Spring Wheat.

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Molecular characterization of slow leaf-rusting resistance in wheat

Slow leaf-rusting resistance in wheat (Triticum aestivum L) is gaining acceptance as a breeding objective because of its durability in comparison with race-specific resistance. CI 13227 was previously reported to provide the highest level of slow leaf-rusting resistance. The objective of this study was to characterize the slow leaf-rusting resistance conferred by CI 13227 using molecular markers. A population of recombinant inbred lines (RILs) derived from CI 13227/Suwon 92 was evaluated for final severity (FS), area under disease progress curve (AUDPC), infection rate (IR), and infection duration (ID) of leaf rust. Four hundred fifty-nine amplified fragment length polymorphism (AFLP) markers and 28 simple sequence repeat (SSR) markers were analyzed in the population. Two quantitative trait loci (QTL), designated as QLr.osu-2B and QLr.osu-7BL, were consistently associated with AUDPC, FS, and IR of leaf rust, caused by Puccinia triticina (previously P. recondita Rob. Ex Desm. f. sp. tritici). The percentages of phenotypic variance explained by each QTL varied with experiments and traits, ranging from 13.4 to 18.8% for AUDPC, 12.5 to 20.8% for FS, and 12.9 to 16.1% for IR. The third QTL for leaf rust ID, designated as QLrid.osu-2DS, was located on chromo- some 2DS and explained 26.4 and 21.47% of the phenotypic variance in 1994 and 1995, respectively. Both the QTL and correlation analysis indicate reasonable progress in leaf-rusting resistance by selecting for final severity. SSR markers closely associated with QLr.osu-2B or QLr.osu-7BL have potential to be used in marker-assisted selection (MAS) for durable leaf rust resistant cultivars.Peer reviewedPlant and Soil SciencesEntomology and Plant Patholog

A polyetic modelling framework for plant disease emergence

Plant disease emergences have dramatically increased recently as a result of global changes, especially with respect to trade, host genetic uniformity, and climate change. A better understanding of the conditions and processes determining epidemic outbreaks caused by the emergence of a new pathogen, or pathogen strain, is needed to develop strategies and inform decisions to manage emerging diseases. A polyetic process-based model is developed to analyse conditions of disease emergence. This model simulates polycyclic epidemics during successive growing seasons, the yield losses they cause, and the pathogen survival between growing seasons. This framework considers an immigrant strain coming into a system where a resident strain is already established. Outcomes are formulated in terms of probability of emergence, time to emergence, and yield loss, resulting from deterministic and stochastic simulations. An analytical solution to determine a threshold for emergence is also derived. Analyses focus on the effects of two fitness parameters on emergence: the relative rate of reproduction (speed of epidemics), and the relative rate of mortality (decay of population between seasons). Analyses revealed that stochasticity is a critical feature of disease emergence. The simulations suggests that: (1) emergence may require a series of independent immigration events before a successful invasion takes place; (2) an explosion in the population size of the new pathogen (or strain) may be preceded by many successive growing seasons of cryptic presence following an immigration event, and; (3) survival between growing seasons is as important as reproduction during the growing season in determining disease emergence