Literature DB >> 30812895

Temperature and Wetness-Duration Requirements for Grape Leaf and Cane Infection by Phomopsis viticola.

O Erincik1, L V Madden1, D C Ferree2, M A Ellis3.   

Abstract

In 1998 and 1999, controlled-environment studies were conducted in growth chambers to determine the temperature and wetness-duration parameters required for leaf and cane infection of grape by Phomopsis viticola. Greenhouse-grown 'Catawba' (Vitis labrusca) and 'Seyval' (French hybrid) grapes were inoculated with P. viticola and incubated at constant temperatures of 5, 10, 15, 20, 25, 30, and 35°C and at wetness durations of 5, 10, 15, and 20 h for each temperature. Data from each cultivar were analyzed by nonlinear regression analysis to determine the relationship between disease severity and temperature and wetness duration. A generalized form of the Analytis Beta model was found to provide the best fit to the data. Disease severity on leaves and canes increased with increasing wetness duration at most temperatures. Minimum and maximum temperatures for infection were around 5 and 35.5°C, respectively. Optimum temperatures for leaf and cane infection were between 16 and 20°C. In the 2000 and 2001 growing seasons, the generalized Beta model was validated in 'Catawba' and 'Seyval' vineyards by inoculating vines during natural rain events. Average temperature and hours of wetness for each event and inoculation were recorded and used in the model equation to predict disease severity on leaves and internodes. Correlation coefficients between observed disease severities following field inoculations and predicted disease severities for both cultivars were between 0.71 and 0.81 and always significant (P < 0.01). These results indicate that the model reliably predicted leaf and cane infection on both cultivars over a wide range of wetness durations and temperatures. The model may be useful in developing disease-forecasting systems for Phomopsis cane and leaf spot on grapes.

Entities:  

Year:  2003        PMID: 30812895     DOI: 10.1094/PDIS.2003.87.7.832

Source DB:  PubMed          Journal:  Plant Dis        ISSN: 0191-2917            Impact factor:   4.438


  2 in total

1.  Rotten Hazelnuts Prediction via Simulation Modeling-A Case Study on the Turkish Hazelnut Sector.

Authors:  Taynara Valeriano; Kim Fischer; Fabrizio Ginaldi; Laura Giustarini; Giuseppe Castello; Simone Bregaglio
Journal:  Front Plant Sci       Date:  2022-04-04       Impact factor: 5.753

2.  Development and Validation of a Mechanistic Model That Predicts Infection by Diaporthe ampelina, the Causal Agent of Phomopsis Cane and Leaf Spot of Grapevines.

Authors:  Elisa Gonzalez-Dominguez; Tito Caffi; Aurora Paolini; Laura Mugnai; Nedeljko Latinović; Jelena Latinović; Luca Languasco; Vittorio Rossi
Journal:  Front Plant Sci       Date:  2022-04-07       Impact factor: 5.753

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.