Biological control of oilseed rape Sclerotinia stem rot byBacillus subtilisstrain Em7

2013 ◽  
Vol 24 (1) ◽  
pp. 39-52 ◽  
Author(s):  
Xiaoning Gao ◽  
Qingmei Han ◽  
Yafei Chen ◽  
Huqiang Qin ◽  
Lili Huang ◽  
...  
2007 ◽  
Vol 97 (9) ◽  
pp. 1186-1194 ◽  
Author(s):  
S. Koch ◽  
S. Dunker ◽  
B. Kleinhenz ◽  
M. Röhrig ◽  
A. von Tiedemann

Sclerotinia stem rot (SSR) is an increasing threat to winter oilseed rape (OSR) in Germany and other European countries due to the growing area of OSR cultivation. A forecasting model was developed to provide decision support for the fungicide spray against SSR at flowering. Four weather variables—air temperature, relative humidity, rainfall, and sunshine duration—were used to calculate the microclimate in the plant canopy. From data reinvestigated in a climate chamber study, 7 to 11°C and 80 to 86% relative humidity (RH) were established as minimum conditions for stem infection with ascospores and expressed as an index to discriminate infection hours (Inh). Disease incidence (DI) significantly correlated with Inh occurring post-growth stage (GS) 58 (late bud stage) (r2 = 0.42, P ≤ 0.001). Using the sum of Inh from continuous infection periods exceeding 23 h significantly improved correlation with DI (r2 = 0.82; P ≤ 0.001). A parallel GS model calculates the developmental stages of OSR based on temperature in the canopy and starts the model calculation at GS 58. The novel forecasting system, SkleroPro, consists of a two-tiered approach, the first providing a regional assessment of the disease risk, which is assumed when 23 Inh have accumulated after the crop has passed GS 58. The second tier provides a field-site-specific, economy-based recommendation. Based on costs of spray, expected yield, and price of rapeseed, the number of Inh corresponding to DI at the economic damage threshold (Inhi) is calculated. A decision to spray is proposed when Inh ≥ Inhi. Historical field data (1994 to 2004) were used to assess the impact of agronomic factors on SSR incidence. A 2-year crop rotation enhanced disease risk and, therefore, lowered the infection threshold in the model by a factor of 0.8, whereas in 4-year rotations, the threshold was elevated by a factor 1.3. Number of plants per square meter, nitrogen fertilization, and soil management did not have significant effects on DI. In an evaluation of SkleroPro with 76 historical (1994 to 2004) and 32 actual field experiments conducted in 2005, the percentage of economically correct decisions was 70 and 81%, respectively. Compared with the common practice of routine sprays, this corresponded to savings in fungicides of 39 and 81% and to increases in net return for the grower of 23 and 45 €/ha, respectively. This study demonstrates that, particularly in areas with abundant inoculum, the level of SSR in OSR can be predicted from conditions of stem infection during late bud or flowering with sufficient accuracy, and does not require simulation of apothecial development and ascospore dispersal. SkleroPro is the first crop-loss-related forecasting model for a Sclerotinia disease, with the potential of being widely used in agricultural practice, accessible through the Internet. Its concept, components, and implementation may be useful in developing forecasting systems for Sclerotinia diseases in other crops or climates.


Plant Disease ◽  
2002 ◽  
Vol 86 (9) ◽  
pp. 999-1004 ◽  
Author(s):  
L. E. del Rio ◽  
C. A. Martinson ◽  
X. B. Yang

Field studies were conducted to evaluate the effectiveness of Sporidesmium sclerotivorum to control Sclerotinia stem rot of soybean (SSR) at Ames, Humboldt, and Kanawha, IA, between 1996 and 1998. Experimental plots (3 × 3 m) were infested with S. sclerotivorum macroconidia once at a rate of 0, 2, or 20 spores per cm2 in the fall of 1995 or the spring of 1996, under two crop rotation schemes. A randomized complete block design with four replications in each location was used. Plots infested with 20 spores per cm2 had 62% less SSR (P = 0.05) than control plots at Humboldt in 1996. No differences were detected between fall and spring applications. In 1998, plots treated with either 2 or 20 spores per cm2 had 51 to 63% less SSR (P = 0.05) than control plots at Ames and Kanawha. In 1998, SSR was completely suppressed in all plots at Humboldt, while the commercial field surrounding the experimental plots had 17% SSR. S. sclerotivorum was retrieved from all infested plots at all locations 2 years after infestation with sclerotia of Sclerotinia sclerotiorum as bait. At Humboldt, S. sclerotivorum was also retrieved from control plots. Two larger plots (10 × 10 m) were infested with 20 or 100 spores per cm2 in the fall of 1996 or spring of 1997 in six commercial fields. SSR incidence, which was measured in transects up to 20 m from the infested area at 5-m intervals, was reduced 56 to 100% (P = 0.05) in four fields compared with the surrounding uninfested areas in the commercial fields. Dispersal of the control agent was evident by the fact that SSR incidence gradually increased from the edge of the infested macroplots up to about 10 m into noninoculated areas of the commercial field. This paper constitutes the first report describing the biocontrol of a disease on field crops that may be employed economically.


2006 ◽  
Vol 5 (2) ◽  
pp. 228-232 ◽  
Author(s):  
J. Abdollahza ◽  
E. Mohammadi Goltape . ◽  
H. Rouhani .

Sensors ◽  
2018 ◽  
Vol 18 (6) ◽  
pp. 1764 ◽  
Author(s):  
Wenwen Kong ◽  
Chu Zhang ◽  
Feng Cao ◽  
Fei Liu ◽  
Shaoming Luo ◽  
...  

2020 ◽  
Vol 112 (6) ◽  
pp. 5143-5157
Author(s):  
Jianglin Zhang ◽  
Jing Li ◽  
Guotao Geng ◽  
Wenshi Hu ◽  
Tao Ren ◽  
...  

2019 ◽  
Vol 62 (1) ◽  
pp. 123-130
Author(s):  
Fei Liu ◽  
Fei Liu ◽  
Tingting Shen ◽  
Jian Wang ◽  
Yong He ◽  
...  

Abstract. In this study, a novel approachser-induced breakdown spectroscopy (LIBS) is proposed to rapidly diagnose stem rot (SSR) in oilseed rape ( L.). A rapid diagnostic method is important to prevent this worldwide disease and promote growth of oilseed rape. A total of 120 fresh leaves, including 60 healthy and 60 SSR-infected leaves, were collected to acquire LIBS spectra. Robust baseline estimation (RBE) and wavelet transform (WT) were applied to preprocess the raw LIBS spectra for baseline correction and denoising. K-nearest neighbor (KNN), radial basis function neural network (RBFNN), random forest (RF), and extreme learning machine (ELM) methods combining full LIBS spectra were chosen to establish classification models to identify healthy and SSR-infected leaves, and the ELM model obtained classified accuracy of more than 80.00% in the prediction set. Twenty-four emission lines were selected by second-derivative spectra as the most relevant to distinguish healthy and SSR-infected leaves. The ELM model using the optimal emission lines improved the classified accuracy to more than 85% and the specificity to 95.00%. Compared with full-spectra models, the number of variables in the models based on optimal wavelengths was reduced from 22,036 to 24, a reduction of 99.89%. This study indicates that LIBS combined with appropriate chemometric m. Keywords: Chemometrics, Laser-induced breakdown spectroscopy, Oilseed rape, Sclerotinia stem rot.


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