Effects of Temperature and Moisture on the Infection and Development of Apple Fruit Rot Caused by Phytophthora cactorum

Author:

Liu Fang1,Li Bao-hua1ORCID,Lian Sen1,Dong Xiang-li1,Wang Cai-xia1ORCID,Zhang Zhen-fang1,Liang Wen-xing1ORCID

Affiliation:

1. College of Plant Health and Medicine, Qingdao Agricultural University; Key Lab of Integrated Crop Pest Management of Shandong Province; Qingdao 266109, P.R. China

Abstract

Phytophthora fruit rot, caused by Phytophthora cactorum, is an important disease of apple in China, often causing more than 50% fruit rot in rainy years. We examined the effects of temperature and moisture on the development of the disease and effects of the variables on zoospore release and germination, infection, and lesion development. In vitro, a temperature range of 5 to 20°C had no significant effects on zoospore release dynamics but did significantly affect the quantities of released zoospores. The largest quantity of zoospores was released at 9.9°C according to a fitted model. Zoosporangia released zoospores within 15 min at the test temperatures (0 to 20°C), which peaked at the fourth hour. Zoospores germinated in vitro, requiring free water, at temperatures from 5 to 35°C. The optimum germination temperature was 25.1°C according to a fitted model. The minimum wetness duration required for zoospores to complete the infection process and induce visible lesions on Fuji fruit was 0.40 h at the optimal temperature of 23.0°C according to the fitted model, whereas observed values were 4.5, 1.5, 0.5, 1.5 and 8.5 h at 10, 15, 20, 25, and 30°C, respectively. The number of zoospore infections on fruit at various temperatures and wetness durations were well fitted by the modified Weibull model; based on the model, the optimal temperature for zoospore infections was 23.0°C. Young apple fruit infected by zoospores developed visible lesions from 10 to 30°C, with a predicted optimum of 23.5°C; no lesions developed at 5 or 35°C. The shortest incubation period of the disease was 4 days. These results can be used to develop disease forecasting models for improved fungicide control.

Publisher

Scientific Societies

Subject

Plant Science,Agronomy and Crop Science

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