Promising Bacillus subtilis strains BZR 336g and BZR 517 for biocontrol of blackcurrant against Septoria leaf spot under unfavorable climate conditions

Штерншис, М. В.; Асатурова, А. М.; Shpatova, T.V.; Жевнова, Н. А.; Homyak, A.I.

doi:10.1007/s42161-020-00660-w

Cited by 4 publications

(2 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The parameters responsible for disease occurrence in tomato plants are maximum and minimum temperature, dewpoint, relative humidity, and rainfall. The temperature in the range 22-38°C and relative humidity in the range of 55 to 90% are favorable for fungal diseases in tomato plants (6)(7)(8)(9)(10). The bacterial disease in tomato plants occurs favorably in the temperature range of 24-32°C with a relative humidity of more than 80% (11).…”

Section: Favorable Conditions For Tomato Plant Diseasementioning

confidence: 99%

Prediction of Tomato Plant Disease with Meteorological Condition and Artificial Intelligence

Wagle¹

2022

ECS Trans.

View full text Add to dashboard Cite

Predicting disease in advance plays a vital role in taking preventive measures towards plant protection. The work proposes predicting tomato plant disease with meteorological conditions and artificial intelligence. Support Vector Regression (SVR) and Random Forest Regression (RFR) models are employed for the time-series forecasting of temperature and relative humidity. The models are optimized with GridSearchCV to fine-tune the hyperparameters to better forecast weather parameters. The RMSE for temperature is 0.0369; relative humidity is 1.8442 for the SVR model, 0.0246 for temperature, and 0.5918 for relative humidity with the RFR model. The R2 values show a good prediction performance. The correlation between actual and predicted test values is positive.

show abstract

Section: Favorable Conditions For Tomato Plant Diseasementioning

confidence: 99%

Prediction of Tomato Plant Disease with Meteorological Condition and Artificial Intelligence

Wagle¹

2022

ECS Trans.

View full text Add to dashboard Cite

show abstract

“…The bacteria have been proven to be effective on various crops and in different climate regions. B. velezensis showed great antagonist activity in the south of Russia [18], as well as in the extreme weather of Western Siberia [19,20]. These microorganisms promote plant growth [21], making them excellent candidates for the development of the new bioproducts.…”

Section: Introductionmentioning

confidence: 99%

Efficacy of New Local Bacterial Agents against Pyrenophora tritici-repentis in Kuban Region, Russia

et al. 2022

Self Cite

View full text Add to dashboard Cite

The phytopathogenic fungus Pyrenophora tritici-repentis is a causal agent of tan spot. Antagonistic microorganisms can be used as a non-chemical alternative treatment against the tan spot of wheat. Bacillus velezensis BZR 336 g and BZR 517 stains were selected as the most active microorganisms and potential biocontrol agents. We found that B. velezensis strains BZR 336 g and BZR 517 exhibited antagonistic activity against P. tritici-repentis Kr-15/2016 in vitro: they inhibited mycelium growth by 72.4–94.3% and caused its degenerative changes. Treatment of seeds and plants with strains BZR 336 g and BZR 517 provided a biological efficiency of 31.2–38.4% against tan spot, while artificial inoculation of plants provided only 28.4–43.8% biological efficiency. Treatment of seeds and plants with BZR 336 g and BZR 517 in a three-year field trial demonstrated 24.6–50% biological efficiency. BZR 336 g and BZR 517 provided 5.0–7.6% additional yield. We conclude that BZR 336 g and BZR 517 are promising options for novel bioproducts that can control P. tritici-repentis tan spot.

show abstract

Tan spot of wheat: can biological control interact with actual management practices to counteract this global disease?

Reynoso

Sautua²,

Carmona³

et al. 2023

Eur J Plant Pathol

View full text Add to dashboard Cite

Promising Bacillus subtilis strains BZR 336g and BZR 517 for biocontrol of blackcurrant against Septoria leaf spot under unfavorable climate conditions

Cited by 4 publications

References 7 publications

Prediction of Tomato Plant Disease with Meteorological Condition and Artificial Intelligence

Prediction of Tomato Plant Disease with Meteorological Condition and Artificial Intelligence

Efficacy of New Local Bacterial Agents against Pyrenophora tritici-repentis in Kuban Region, Russia

Tan spot of wheat: can biological control interact with actual management practices to counteract this global disease?

Contact Info

Product

Resources

About