Influence of Temperature and Wetness on Taphrina deformans Ascospore and Blastospore Germination: Disease Forecasting and Validation

Thomas Thomidis () and Maria Paresidou
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Thomas Thomidis: Department of Nutritional Sciences and Dietetics, International Hellenic University, 57400 Sindos, Greece
Maria Paresidou: Department of Nutritional Sciences and Dietetics, International Hellenic University, 57400 Sindos, Greece

Agriculture, 2023, vol. 13, issue 10, 1-13

Abstract: Peach leaf curl is a fungal disease caused by Taphrina deformans , and it can severely affect the health and productivity of peach and nectarine trees ( Prunus persica ) if left unmanaged. This study was carried out to investigate the temperature and wetness conditions that affect the germination of blastospores and ascospores of local isolates of the fungus T. deformans . The results showed that the rate of both ascospore and blastospore germination was reduced as the temperature increased from 0 to 20 °C. A decrease in temperature from the range of 25 °C to 30 °C caused a reduction in the germination of conidia for both ascospores and blastospores. Ascospore and blastospore germination were totally inhibited at −3 and 35 °C. Under constant temperatures of 20 °C, the percentage of both ascospore and blastospore germination of T. deformans gradually increased as the wetness period increased from 9 to 15 h. However, there was no further increase in germination observed beyond the 15 h wetness period. Additionally, this study aimed to validate the predictive models of T. deformans , developed based on the favorable temperatures and leaf wetness durations, under the specific field conditions of Naoussa, Greece. The results indicate that while both the ascosporic and blastosporic models were capable of correctly predicting infection periods, there were differences in their predictions of infection risk. The ascosporic model predicted lower risk infection, which aligned well with the observed symptoms of the disease. In contrast, the blastosporic model predicted higher risk infection, but this did not match the actual intensity of the symptoms. Finally, this study also provided insights into the potential benefits of using predictive models to guide fungicide applications, potentially leading to more targeted and efficient disease management strategies for commercial peach orchards.

Keywords: disease model; leaf curl; nectarine; peach; validation (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2023
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