Ladányi, M., Persely, S., Szabó, T., Soltész, M., Nyéki, J., & Szabó, Z. (2009). The application of A HEAT SUM MODEL for the budburst of sour cherry varieties grown at Újfehértó. International Journal of Horticultural Science, 15(4), 105–112. https://doi.org/10.31421/IJHS/15/4/851
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Experiences of the last decades showed univocally that the climatic changes, especially the warming up, influenced clearly the phenology, i.e. speed of growth and development of plants. To check the effects, the phenological studies became a topic of special interest. Our research has been performed at Újfehértó, the Research Institute of Fruit Growing and Extension, where the respective database accumulated observations during the period 1984–2005, where the meteorological data as well as the parallel phenological diary referring to the varieties ’Újfehértói fürtös’, ’Kántorjánosi’ and ’Debreceni bôtermô’ during the period 1984–1991 have been utilised. The method of calculating the sum of daily mean temperatures, “degree days”, is based on the observation that the plants are able to utilise cumulatively – in growth and development – the temperature above a set basic temperature. Our phenology model examined the correlation between the sum of degree days and the date of sprouting (budburst). The basic temperature has been determined by optimization, above which (threshold temperature) the accumulation of daily means was most active, or alternatively, below which the daily means are most sensitively expressed in the phenology. The model has been extended to the calculation of the end of rest period (endodormancy) – by optimization as well. Our phenology model will be suitable for two main purposes: for estimating the time of budburst for the Hungarian region during the next decades calculated on the basis of regionally downscaled climate models; on the other hand, by applying our model, the risk of damage caused by spring frosts could be estimated more exactly than earlier.