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Krzyszczak, J., Baranowski, P., & Slawinski, C. (2014). Chamber system measurements of carbon dioxide fluxes from winter wheat field in a Lubelskie province..
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Krzyszczak, J., Baranowski, P., & Slawinski, C. (2014). Field experiment in Lubelskie region to validate crop growth models in temperate, climate..
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Murat, M., Malinowska, I., Hoffmann, H., & Baranowski, P. (2016). Statistical modelling of agrometeorological time series by exponential smoothing. International Agrophysics, 30(1), 57–65.
Abstract: Meteorological time series are used in modelling agrophysical processes of the soil-plant-atmosphere system which determine plant growth and yield. Additionally, longterm meteorological series are used in climate change scenarios. Such studies often require forecasting or projection of meteorological variables, eg the projection of occurrence of the extreme events. The aim of the article was to determine the most suitable exponential smoothing models to generate forecast using data on air temperature, wind speed, and precipitation time series in Jokioinen (Finland), Dikopshof (Germany), Lleida (Spain), and Lublin (Poland). These series exhibit regular additive seasonality or non-seasonality without any trend, which is confirmed by their autocorrelation functions and partial autocorrelation functions. The most suitable models were indicated by the smallest mean absolute error and the smallest root mean squared error.
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Baranowski, P., Slawinski, C., & Krzyszczak, J. (2013). Short presentation of partner’s P139 involvement in CropM..
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Baranowski, P., Mazurek, W., & Pastuszka-Wozniak, J. (2013). Supervised classification of bruised apples on the base of hyperspectral imaging data..
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