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Twardy, S., & Kopacz, M. (2014). Sustainable use of mountain lands as a basis of permanent quality maintaining of natural environment. Falenty-Krakow.
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Twardy, S., & Kopacz, M. (2015). The role of permanent grasslands in mountain areas: Study on agri-environmental importance of permanent grasslands – based on research carried out in the upper Dunajec River basin and Grajcarek Stream basin. Falenty-Krakow.
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Ventrella, D., Giglio, L., Charfeddine, M., & Castellini, M. (2012). Effects of climate change on soil fertility of a typical cropping system of Southern Italy. In F. Stoddard, & P. Mäkelä (Eds.), (pp. 480–481). Helsinki: University of Helsinki.
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Ventrella, D., Giglio, L., & Charfeddine, M. (2014). Climate change and nitrogen fertilization for winter durum wheat and tomato cultivated in Southern Italy..
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Toscano, P., Genesio, L., Crisci, A., Vaccari, F. P., Ferrari, E., La Cava, P., et al. (2015). Empirical modelling of regional and national durum wheat quality. Agricultural and Forest Meteorology, 204, 67–78.
Abstract: The production of durum wheat in the Mediterranean basin is expected to experience increased variability in yield and quality as a consequence of climate change. To assess how environmental variables and agronomic practices affect grain protein content (GPC), a novel approach based on monthly gridded input data has been implemented to develop empirical model, and validated on historical time series to assess its capability to reproduce observed spatial and inter-annual GPC variability. The model was applied in four Italian regions and at the whole national scale and proved reliable and usable for operational purposes also in a forecast ‘real-time’ mode before harvesting. Precipitable water during autumn to winter and air temperature from anthesis to harvest were extremely important influences on GPC; these and additional variables, included in a linear model, were able to account for 95% of the variability in GPC that has occurred in the last 15 years in Italy. Our results are a unique example of the use of modelling as a predictive real-time platform and are a useful tool to understand better and forecast the impacts of future climate change projections on durum wheat production and quality.
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