Evaluation and Modeling of Rate-Reducing Resistance of Soybean Seedlings to<i>Phytophthora sojae</i>

Wagner, R. E.; Carmer, S. G.; Wilkinson, H. T.

doi:10.1094/phyto-83-187

Cited by 9 publications

(5 citation statements)

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“…Since the early 1980s, researchers have evaluated numerous methods to screen for PR to P. sojae (McBlain et al, 1991a, b; Schmitthenner and Bhat, 1994; Thomison et al, 1991; Tooley and Grau, 1982; Wagner et al, 1992). Some methods include direct inoculation of wounded cotyledons or roots while others involve inoculation of nonwounded plants (McBlain et al, 1991b; Tooley and Grau, 1982; Wagner et al, 1992). The layer test has been the most widely accepted assay and has become the standardized method to screen soybeans for PR to P. sojae in greenhouse conditions (Dorrance et al, 2003b; Ferro et al, 2006; Jackson et al, 2004; Schmitthenner et al, 1994; Thomison et al, 1991).…”

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A Modified Method to Screen for Partial Resistance to Phytophthora sojae in Soybean

Stewart¹,

Robertson

2012

Crop Science

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Phytophthora root and stem rot, caused by Phytophthora sojae Kauf and Gerd, is one of the most damaging diseases of soybean [Glycine max (L.) Merr.] in the United States. Partial resistance (PR), which is defined as the relative ability of a soybean plant to survive root infection without showing severe symptoms, is an effective way to manage this disease. A modification of the layer test method used to screen for PR to P. sojae in soybean was evaluated. Instead of the P. sojae‐colonized agar layer, which is used in the current greenhouse cup assay, P. sojae‐infested rice (Oryza sativa L.) grains were used. In addition, a dry root weight (Drw) measurement was compared to a disease severity root rot score, which uses a 1 to 10 visual scale. The rice method was not statistically different from the layer test for the variables evaluated. Advantages of the rice method include reduced cost and the ability to screen soybean germplasm with more than one pathotype of the pathogen in a single assay. A mixture of several pathotypes of P. sojae ensures compatible interactions between isolates used and all known Rps genes, thus avoiding Rps genes that could go undetected and mask PR during screening. Although collecting and handling of roots for Drw data may require more time, it is a more objective variable, which assures precise scoring, it is not rater dependent, and less training of personnel is required.

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A Modified Method to Screen for Partial Resistance to Phytophthora sojae in Soybean

Stewart¹,

Robertson

2012

Crop Science

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“…The appearance and subsequent domination of race 4 in central and southern New South Wales after the widespread deployment of the Rps1a gene provides an example of the short life of cultivars with single-gene resistance. The use of cultivars with partial resistance, also referred to as field resistance (21), tolerance (34), rate-reducing resistance (30,32), and root resistance (27,28) has been advocated by many authors. Rps2 is the only resistance gene that has been identified as conferring this type of resistance (13), but some workers have suggested that other as yet unidentified genes may also be responsible (27).…”

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Changes in the Racial Composition ofPhytophthora sojaein Australia Between 1979 and 1996

et al. 1998

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Surveys of commercial soybean fields, disease nurseries, and trial plots of soybean were conducted throughout eastern Australia between 1979 and 1996, and 694 isolates of Phytophthora sojae were collected and classified into races. Fourteen races, 1, 2, 4, 10, 15, and 25, and eight new races, 46 to 53, were identified, but only races 1, 4, 15, 25, 46, and 53 were found in commercial fields. Races 1 and 15 were the only races found in commercial fields in the soybean-growing areas of Australia up until 1989, with race 1 being the dominant race. Race 4 was found in central New South Wales in 1989 on cultivars with the Rps1a gene, and it is now the dominant race in central and southern New South Wales. Races 46 and 53 have only been found once, in southern New South Wales, and race 25 was identified in the same region in 1994 on a cultivar with the Rps1k gene. Only races 1 and 15 have been found in the northern soybean-growing regions, with the latter dominating, which coincides with the widespread use of cultivars with the Rps2 gene. Changes in the race structure of the P. sojae population from commercial fields in Australia follow the deployment of specific resistance genes.

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“…In natural epidemics, the rate of lesion expansion may be variable dependent on temperature (3,21,27,35,59,80,81,86) or leaf position (21), slowing with age of the lesion or host (15,37,71,72,76,92) or with increased density of lesions (71), or increasing with age (30,81,92) or with longer dew periods (23,73,86). In natural epidemics, the rate of lesion expansion may be variable dependent on temperature (3,21,27,35,59,80,81,86) or leaf position (21), slowing with age of the lesion or host (15,37,71,72,76,92) or with increased density of lesions (71), or increasing with age (30,81,92) or with longer dew periods (23,73,86).…”

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Lesion Expansion as an Epidemic Component

Berger¹,

Filho²,

Amorim³

1997

Phytopathology®

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A simulator for the enlargement of cohorts of circular lesions on cohorts of host tissue was used to examine five epidemiological parameters: radial rate (mm day(-1)) of lesion expansion, k (exp); maximum basic infection rate, R (m); proportion of lesion area as infectious, f; initial lesion size (mm(2)), z; and proportion of susceptible host sites, s. Based on the proportion of disease severity at day 50 and the proportion of the total disease that originated solely from lesion expansion, k(exp) was the most sensitive of the five parameters. A radial rate of only 0.1 mm day(-1) resulted in a proportion of >0.7 of the diseased area that came from lesion expansion. In an extensive survey of phytopathological literature, many plant pathogens had radial rates greater than 0.1 mm day(-1), which would result in a proportion of >0.95 of the total disease that comes from lesion expansion. Susceptible host sites, s, was a sensitive parameter, as this determined the host area into which lesions could expand. Naturally, R(m) was a sensitive parameter for the proportion of disease on day 50, as it controlled the overall speed of the epidemic. Initial lesion size was a relatively insensitive parameter, although z interacted significantly with s. The greatest proportion of disease that originated from lesion expansion occurred with fast k(exp), small z, and low values of s, R(m), and f. The model was validated with lesion numbers and severities obtained in natural epidemics of Cercospora medicaginis on alfalfa and Exserohilum turcicum on maize. We recommend that the 'epidemic quintuplet' used to describe polycyclic epidemics be expanded to the 'epidemic sextuplet' with the inclusion of k(exp), since lesion expansion is a major component of many polycyclic epidemics.

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Evaluation and Modeling of Rate-Reducing Resistance of Soybean Seedlings toPhytophthora sojae

Cited by 9 publications

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A Modified Method to Screen for Partial Resistance to Phytophthora sojae in Soybean

A Modified Method to Screen for Partial Resistance to Phytophthora sojae in Soybean

Changes in the Racial Composition ofPhytophthora sojaein Australia Between 1979 and 1996

Lesion Expansion as an Epidemic Component

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