Team: Prof. DSc Cezary Sławiński; PhD Jaromir Krzyszczak; PhD Wojciech Mazurek; PhD Monika Zubik; MSc Anna Siedliska; MSc Magdalena Gos
The premise of the proposed research is that the climate change will affect plants and crops and other natural systems in complex ways, and the changes in meteorological quantities such as temperature or precipitation can have a significant impact on agricultural production. In the temperate climate zone of our country the studies of trends in average air temperature, or average precipitation are not sufficient to understand the processes occurring in the atmosphere and the consequences of these changes for living organisms. Therefore, it is necessary to look for more sophisticated methods of analysis of long-term meteorological series to be able to determine the long-range correlations, which can also be associated with climate change. Such methods are multifractal analysis and chaos theory, which we believe, on the basis of preliminary studies, will determine the parameters easily linked to the dynamics of processes in the atmosphere being responsible for climate change.
The purpose is to develop mathematical and physical methods describing the state of the environment of plant growth and agricultural products, taking into account climate change and the selected factors that are responsible for the production of safe food. In particular, it is planned to:
– use the multifractal analysis and chaos theory to describe the long-range correlations in agro-meteorological time series (Fig. 1);
– model, on the base of historical and current data, the impact of various scenarios of climate change on grain yield (Fig. 2);
– monitor and model the greenhouse gas emissions from agricultural ecosystems (Fig. 3);
– develop methods for early detection of fungal and virus infections of plant leaves and fruit, taking into account the types of infections occurring as a result of climate change.
The result of the task will be the development of mathematical methods describing the elements of the soil-plant atmosphere system and the quality of selected agricultural products, taking into account possible scenarios of climate change. The sensitivity analysis of the selected models of plant growth and yield to changes in agro-meteorological parameters according to the existing scenarios of climate change will be performed. The hyperspectral method for early detection of recently found in Poland fungal infections of plants will be developed. Many research centres around the world are interested in the solution of these problems and the positive results of the task can make a significant contribution to the global research.
Methodological and practical results of the research in the form of ready-to-use identification procedures and the classification of certain fungal infections in the tissues of the soft fruit will be used for implementation activities, which will be the subject of separate projects submitted to national funding organizations (e.g. NCBiR).