scholarly journals A Latent Period Duration Model for Wheat Stem Rust

Plant Disease ◽  
2014 ◽  
Vol 98 (10) ◽  
pp. 1358-1363 ◽  
Author(s):  
John F. Hernandez Nopsa ◽  
William F. Pfender
Keyword(s):  
Mathematical Model ◽  
Latent Period ◽  
Stem Rust ◽  
Quantitative Model ◽  
Duration Model ◽  
Wheat Stem Rust ◽  
Small Grains ◽  
Epidemic Development ◽  
Period Duration ◽  
Outdoor Experiments

Wheat stem rust (WSR), caused by Puccinia graminis subsp. graminis Pers., is a highly destructive disease of wheat and several other small grains. The discovery of P. graminis subsp. graminis race Ug99, which overcomes previously effective resistance in wheat, raises concerns for global wheat production and food security. There is currently no mathematical model that describes the duration of the WSR latent period based on temperature or heat units. A study using P. graminis subsp. graminis race GFCDC in ‘Stephens’ wheat was conducted at a range of temperatures (from 4.7 to 33.4°C), to determine their effect on latent period duration. There were significant differences in latent period duration among temperatures, and temperatures above 30°C generally were not conducive for pustule development. A mathematical model to predict latent period duration based on temperature was formulated; the model can be applied to data consisting of varying temperature readings measured at any desired time increment. The model was validated in outdoor experiments under natural conditions on Stephens and ‘McNair’ wheat. In field and outdoor experiments, the latent period durations predicted with the model were within 16 h of the observed latent period, and most fell into the 99% confidence interval of the observations. For experiments conducted on field-grown plants, no significant differences were found between predicted and observed latent period duration. Factorial experiments conducted under growth chamber conditions, using four wheat cultivars (Stephens, McNair 701, ‘Scout 66’, and ‘Kingbird’) and four P. graminis subsp. graminis races (GCCNC, GCCSC, QFCSC, and GFCDC) at three temperatures (5, 15 and 30°C) showed significant differences among cultivars at each temperature. A quantitative model for latent period duration could help in estimating epidemic development, and also in improving our understanding of WSR epidemiology.

scholarly journals Field resistance to wheat stem rust in durum wheat ( Triticum turgidum ssp. durum ) accessions deposited at the USDA National Small Grains Collection

Crop Science ◽  
2021 ◽  
Author(s):  
Pablo D. Olivera ◽  
Worku D. Bulbula ◽  
Ayele Badebo ◽  
Harold E. Bockelman ◽  
Erena A. Edae ◽  
...  
Keyword(s):  
Durum Wheat ◽  
Stem Rust ◽  
Triticum Turgidum ◽  
Field Resistance ◽  
Wheat Stem Rust ◽  
Small Grains

scholarly journals A Temperature-Based Model for Latent-Period Duration in Stem Rust of Perennial Ryegrass and Tall Fescue

2001 ◽  
Vol 91 (1) ◽  
pp. 111-116 ◽  
Author(s):  
W. F. Pfender
Keyword(s):  
Latent Period ◽  
Constant Temperature ◽  
Perennial Ryegrass ◽  
Tall Fescue ◽  
Stem Rust ◽  
Field Experiments ◽  
Temperature Response ◽  
Linear Increase ◽  
Potted Plants ◽  
Period Duration

A temperature-response curve for latent-period duration in stem rust (caused by Puccinia graminis subsp. graminicola) on perennial ryegrass and tall fescue was developed from constant-temperature experiments with inoculated plants and evaluated in field experiments. Under constant-temperature conditions, time from infection to 50% of pustules erupted for perennial ryegrass ranged from 54 days at 3.5°C to 5.9 days at 26.5°C. The latent period (LP50) duration of tall fescue was 69 and 8.5 days at these respective temperatures. The dependence of latent-period completion rate on temperature was best described as a linear increase in rate with temperature up to approximately 26°C, then an exponential decline with temperature up to the maximum (lethal) temperature of approximately 35.5°C. LP20, the time required for 20% of open pustules to appear, was used as an estimator of latent-period duration for field observations. Percentage of one latent period completed per half hour (half-hourly rate), for perennial ryegrass was modeled as (0.0156T - 0.0206) {1 - exp[0.497(T - 35.5)]}, where T = average temperature (°C) during the half-hour period. For tall fescue the modeled rate was (0.0109T - 0.00214) {1 - exp[0.417(T - 35.5)]}. Latent periods modeled by these equations were compared with observed latent periods in field experiments with potted plants, where half-hourly temperatures were measured. Linear regressions of modeled versus observed latent periods had adjusted r2 values of 0.96 for perennial ryegrass and 0.93 for tall fescue. The latent-period equations could be used as components of a weather-based disease advisory model to optimize fungicide use in stem-rust management on these crops.

Retrospective analysis of virulence of the North Caucasian population of wheat stem rust pathogen

2019 ◽  
Vol 1 (81) ◽  
pp. 85-90
Author(s):  
Galina Volkova ◽  
◽  
Olesya Miroshnichenko ◽  
Olga Tarancheva ◽  
◽  
...  
Keyword(s):  
Retrospective Analysis ◽  
Stem Rust ◽  
Caucasian Population ◽  
Wheat Stem Rust ◽  
The North ◽  
Rust Pathogen

scholarly journals Large-Scale Atmospheric Dispersal Simulations Identify Likely Airborne Incursion Routes of Wheat Stem Rust Into Ethiopia

2017 ◽  
Vol 107 (10) ◽  
pp. 1175-1186 ◽  
Author(s):  
M. Meyer ◽  
L. Burgin ◽  
M. C. Hort ◽  
D. P. Hodson ◽  
C. A. Gilligan
Keyword(s):  
Stem Rust ◽  
Large Scale ◽  
Dispersion Model ◽  
Fungal Spores ◽  
Disease Outbreaks ◽  
Particle Dispersion ◽  
East African ◽  
Wheat Stem Rust ◽  
Sub Saharan ◽  
African Rift

In recent years, severe wheat stem rust epidemics hit Ethiopia, sub-Saharan Africa’s largest wheat-producing country. These were caused by race TKTTF (Digalu race) of the pathogen Puccinia graminis f. sp. tritici, which, in Ethiopia, was first detected at the beginning of August 2012. We use the incursion of this new pathogen race as a case study to determine likely airborne origins of fungal spores on regional and continental scales by means of a Lagrangian particle dispersion model (LPDM). Two different techniques, LPDM simulations forward and backward in time, are compared. The effects of release altitudes in time-backward simulations and P. graminis f. sp. tritici urediniospore viability functions in time-forward simulations are analyzed. Results suggest Yemen as the most likely origin but, also, point to other possible sources in the Middle East and the East African Rift Valley. This is plausible in light of available field surveys and phylogenetic data on TKTTF isolates from Ethiopia and other countries. Independent of the case involving TKTTF, we assess long-term dispersal trends (>10 years) to obtain quantitative estimates of the risk of exotic P. graminis f. sp. tritici spore transport (of any race) into Ethiopia for different ‘what-if’ scenarios of disease outbreaks in potential source countries in different months of the wheat season.

THE INHERITANCE OF PATHOGENICITY IN RACES 111 AND 29 OF WHEAT STEM RUST

1969 ◽  
Vol 11 (2) ◽  
pp. 266-274 ◽  
Author(s):  
K. N. Kao ◽  
D. R. Knott
Keyword(s):  
Stem Rust ◽  
Rust Resistance ◽  
Single Gene ◽  
Stem Rust Resistance ◽  
Wheat Stem Rust ◽  
Complementary Genes

The inheritance of pathogenicity in wheat stem rust was studied in selfed cultures of races 29 and 111, F1 and F2 cultures of a cross between the two races and cultures from a backcross to race 29. The various cultures were tested on Marquis and Prelude and on a series of lines of these varieties carrying single genes for stem rust resistance. Virulence on Sr 5, Sr 6, Sr 8, Sr 9a, Sr 14 and a gene in Marquis was recessive and in each case there was a single gene for virulence corresponding to each gene for resistance. Virulence on Sr 1 was possibly controlled by two dominant complementary genes. There appeared to be two alleles for virulence on Prelude, one dominant and one recessive.

Wheat stem rust leaf disease detection using image processing

2021 ◽  
Author(s):  
Basim Khalid. Mohammed Ali Al-windi ◽  
Amel H. Abbas ◽  
Mohammed Shakir Mahmood
Keyword(s):  
Image Processing ◽  
Stem Rust ◽  
Disease Detection ◽  
Wheat Stem Rust ◽  
Leaf Disease
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