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Mycosphaerella ribis in Blackcurrant: Overwintering Sources of Inoculum and Spore Release Patterns
Arne Stensvand1, Håvard Eikemo1, Anne-Grete Roer Hjelkrem2
1Norwegian Institute of Bioeconomy Research, Division of Biotechnology and Plant Health, Ås 1431, Norway.
Plant Disease
|November 18, 2025
Summary
Mycosphaerella leaf spot in blackcurrants can affect both leaves and fruit. Spore release, crucial for disease management, is influenced by temperature and moisture, with models predicting release patterns.
Area of Science:
- Plant Pathology
- Mycology
- Horticulture
Background:
- Mycosphaerella ribis causes Mycosphaerella leaf spot in blackcurrants.
- Disease management requires understanding inoculum sources and spore release dynamics.
- Previous studies have not fully characterized fruit lesions or detailed spore release patterns in organic systems.
Purpose of the Study:
- To investigate disease symptoms, inoculum sources, and spore release patterns of Mycosphaerella ribis.
- To observe Mycosphaerella leaf spot development in organic blackcurrant plantations without fungicide application.
- To develop predictive models for spore release based on environmental factors.
Main Methods:
- Three-year field study in organic blackcurrant plots.
- Spore trapping of ascospores (from leaf litter) and conidia (from overwintering fruit stalks).
- Development and validation of degree-day models incorporating rainfall and leaf wetness duration for spore maturation and release prediction.
Main Results:
- Both foliar and fruit lesions were observed.
- Ascospores were released from bud break to mid-July (peak before that), while conidia were released from bud break to early August (peak late May to mid-July).
- Dry conditions and nighttime moisture suppressed spore release; models accurately predicted release based on specific environmental triggers.
Conclusions:
- Mycosphaerella ribis poses a threat to both blackcurrant foliage and fruit.
- Understanding the distinct sources and timing of ascospore and conidia release is vital for effective disease control.
- Predictive models based on degree-days and weather patterns can aid in timing sanitary measures to reduce primary inoculum.
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