Soybean Sudden Death Syndrome Caused by <i>Fusarium virguliforme</i> is Impaired by Prolonged Flooding and Anaerobic Conditions

Abdelsamad, Noor; Baumbach, Jordan; Bhattacharyya, Madan K.; Leandro, Leonor F.S.

doi:10.1094/pdis-04-16-0534-re

Cited by 6 publications

(7 citation statements)

References 57 publications

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Section: Effect Of Farming Practices and Environmental Factorsmentioning

confidence: 99%

“…Nevertheless, a reduction of foliar and root rot severity caused by F. virguliforme was observed after continuous flooding of a greenhouse for 5 or 7 days (Abdelsamad et al, 2017). As flooding causes lack of oxygen in the soil, Abdelsamad et al (2017) also evaluated the effect of anaerobic conditions on the soybean-F. virguliforme interaction. After an exposure to anaerobic conditions for 6 hr, soybean genes related to defence responses and F. virguliforme candidate virulence genes were down-regulated (Abdelsamad et al, 2017).…”

Section: Effect Of Farming Practices and Environmental Factorsmentioning

confidence: 99%

“…As flooding causes lack of oxygen in the soil, Abdelsamad et al (2017) also evaluated the effect of anaerobic conditions on the soybean-F. virguliforme interaction. After an exposure to anaerobic conditions for 6 hr, soybean genes related to defence responses and F. virguliforme candidate virulence genes were down-regulated (Abdelsamad et al, 2017).…”

Section: Effect Of Farming Practices and Environmental Factorsmentioning

confidence: 99%

“…As flooding causes lack of oxygen in the soil, Abdelsamad et al . (2017) also evaluated the effect of anaerobic conditions on the soybean– F . virguliforme interaction.…”

Section: Fungi–soybean Interactionmentioning

confidence: 99%

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Soybean sudden death syndrome: Fungal pathogenesis and plant response

2020

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Soybean (Glycine max) is a commercial crop mainly grown in the Americas and Asia. World production is about 348.7 million tonnes over 124.9 million ha in 2018 (last published data, Food and Agricultural Organization, http://www.fao.org/faost at/en/#data/QC, accessed on 18 March 2020). However, yield can be reduced by diseases and insect pests (Allen et al., 2017; Hartman et al., 2016). One important disease, sudden death syndrome (SDS), is caused by soilborne fungal pathogens that infect plants through the roots. These fungi are generally restricted to roots, but symptoms can be found both below and above ground. Root symptoms include necrosis and discoloration of the xylem. Aboveground symptoms include interveinal leaf chlorosis and necrosis (Hartman et al., 2015; Navi and Yang, 2016). These aboveground symptoms are caused by toxins produced by the pathogen in the roots that are translocated to the foliage (Hartman et al., 2015). Given the widespread interest in this soybean disease, as evidenced by the large number of articles published recently (more than 80 since 2015), here, we review experimental evidence on fungal pathogenesis, fungus-soybean interactions and plant disease resistance, symptom evaluation, and treatments, reported over the last five years. We have not covered genome mapping studies because this topic was the focus of recent reviews (Chang et al., 2018;

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Section: Effect Of Farming Practices and Environmental Factorsmentioning

confidence: 99%

Section: Effect Of Farming Practices and Environmental Factorsmentioning

confidence: 99%

Section: Effect Of Farming Practices and Environmental Factorsmentioning

confidence: 99%

“…As flooding causes lack of oxygen in the soil, Abdelsamad et al . (2017) also evaluated the effect of anaerobic conditions on the soybean– F . virguliforme interaction.…”

Section: Fungi–soybean Interactionmentioning

confidence: 99%

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Soybean sudden death syndrome: Fungal pathogenesis and plant response

2020

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“…Soil temperature and moisture influence early season Fv infection, and canopy symptoms that are most common during the reproductive (late) growth stages [23,28]. The balance between environmental conditions influence on the pathogen and the host plays a role in the severity of the canopy symptoms [29] that can fluctuate from very light chlorosis to necrosis and complete premature defoliation in a matter of days. In cases of no apparent canopy symptoms, the pathogen can remain unnoticed in the soil, infected roots or plant residue as a potential risk for subsequent growing seasons.…”

Section: Introductionmentioning

confidence: 99%

Leaf and Canopy Level Detection of Fusarium Virguliforme (Sudden Death Syndrome) in Soybean

et al. 2018

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Pre-visual detection of crop disease is critical for food security. Field-based spectroscopic remote sensing offers a method to enable timely detection, but still requires appropriate instrumentation and testing. Soybean plants were spectrally measured throughout a growing season to assess the capacity of leaf and canopy level spectral measurements to detect non-visual foliage symptoms induced by Fusarium virguliforme (Fv, which causes sudden death syndrome). Canopy reflectance measurements were made using the Piccolo Doppio dual field-of-view, two-spectrometer (400 to 1630 nm) system on a tractor. Leaf level measurements were obtained, in different plots, using a handheld spectrometer (400 to 2500 nm). Partial least squares discriminant analysis (PLSDA) was applied to the spectroscopic data to discriminate between Fv-inoculated and control plants. Canopy and leaf spectral data allowed identification of Fv infection, prior to visual symptoms, with classification accuracy of 88% and 91% for calibration, 79% and 87% for cross-validation, and 82% and 92% for validation, respectively. Differences in wavelengths important to prediction by canopy vs. leaf data confirm that there are different bases for accurate predictions among methods. Partial least square regression (PLSR) was used on a late-stage canopy level data to predict soybean seed yield, with calibration, cross-validation and validation R 2 values 0.71, 0.59 and 0.62 (p < 0.01), respectively, and validation root mean square error of 0.31 t•ha −1. Spectral data from the tractor mounted system are thus sensitive to the expression of Fv root infection at canopy scale prior to canopy symptoms, suggesting such systems may be effective for precision agricultural research and management.

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