Articles by Jaromir Krzyszczak
Atmosphere, Oct 29, 2021
Severe thunderstorms are often accompanied by strong vertical air currents, temporary wind gusts,... more Severe thunderstorms are often accompanied by strong vertical air currents, temporary wind gusts, and heavy rainfall. The development of this atmospheric phenomenon over tropical shallow water zones, such as bays, can lead to intensification of atmospheric disturbances and produce a small-scale storm surge. Here, the storm surge that occurred on 19 March 2017 in the Persian Gulf coastal area has been investigated. Air temperature, precipitation, mean sea level pressure, wave height, wind direction, wind speed, geopotential height, zonal components, meridional winds, vertical velocity, relative humidity, and specific humidity obtained from the European Centre for Medium-Range Weather Forecasts (ECMWF) and Global Forecast System (FNL) were used to implement the Weather Research and Forecasting (WRF) model. The results showed that the main cause of the storm surge was the occurrence of a supercell thunderstorm over the Persian Gulf. The formation of this destructive phenomenon resulted from a downburst under Cumulonimbus cloud and high-velocity air subsidence, after collision with the sea surface coinciding with the high tide. This caused a severe, yet temporary, gust, which in turn caused the creation of the four waves of 3.1 m height along the coast of Bandar Dayyer.
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Pure and Applied Geophysics, Jun 1, 2021
The Middle East is an area characterized by strong gradients in meteorological conditions and var... more The Middle East is an area characterized by strong gradients in meteorological conditions and varied land cover. As a result, some of the hottest places in the world as well as very cold areas can be found in this region. The objective of this paper is to quantitatively assess land surface temperature (LST) variations in the countries of the Middle East to estimate the trends and determine whether relationships suggesting the impact of climate change can be observed. Spatiotemporal variability of LST was investigated through the analysis of MODIS Terra LST images (MOD11A2) from 2001 to 2018. The LST differences in both daytime series and seasonal and international means were assessed. The analyses showed that in spring (MAM), about 20,000 km2 of the study area has an LST higher than 50 °C, whereas 3700 km2 has LST lower than 0 °C. In summer (JJA), about 1 million km2 has LST higher than 50 °C. In the fall (SON), about 5 million km2 of the study area has a land surface temperature higher than 30 °C, with about 11 km2 hotter than 50 °C, whereas 320 km2 has LST lower than 0 °C. In winter (DJF), the hottest countries are Yemen, Oman, and Saudi Arabia, with 44.7, 41.8, and 39.8 °C, respectively, whereas the lowest LST values were recorded in Turkey, Iran, and Iraq, with −19.5, −18.1, and −10.5 °C, respectively. An upward trend in the minimum and a downward trend in the maximum value of the winter LST suggest that winters in the Middle East countries such as Iran, Israel, and Jordan have become milder during the considered period. Negative trends in the spring LST in Bahrain and Oman and the summer LST in Bahrain and Qatar suggest that these seasons in those countries became colder during the study period.
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BMC Plant Biology, Jan 7, 2021
Background: Modern agriculture strives to sustainably manage fertilizer for both economic and env... more Background: Modern agriculture strives to sustainably manage fertilizer for both economic and environmental reasons. The monitoring of any nutritional (phosphorus, nitrogen, potassium) deficiency in growing plants is a challenge for precision farming technology. A study was carried out on three species of popular crops, celery (Apium graveolens L., cv. Neon), sugar beet (Beta vulgaris L., cv. Tapir) and strawberry (Fragaria × ananassa Duchesne, cv. Honeoye), fertilized with four different doses of phosphorus (P) to deliver data for non-invasive detection of P content. Results: Data obtained via biochemical analysis of the chlorophyll and carotenoid contents in plant material showed that the strongest effect of P availability for plants was in the diverse total chlorophyll content in sugar beet and celery compared to that in strawberry, in which P affects a variety of carotenoid contents in leaves. The measurements performed using hyperspectral imaging, obtained in several different stages of plant development, were applied in a supervised classification experiment. A machine learning algorithm (Backpropagation Neural Network, Random Forest, Naive Bayes and Support Vector Machine) was developed to classify plants from four variants of P fertilization. The lowest prediction accuracy was obtained for the earliest measured stage of plant development. Statistical analyses showed correlations between leaf biochemical constituents, phosphorus fertilization and the mass of the leaf/roots of the plants.
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International Journal of Climatology, Jan 6, 2021
A comparison study has been performed to assess the dynamics of meteorological processes in Polan... more A comparison study has been performed to assess the dynamics of meteorological processes in Poland on the basis of meteorological time series of air pressure, air temperature and wind speed coming from 35 synoptic stations belonging to the Institute of Meteorology and Water Management-National Research Institute (IMGW-PIB) and from the nearest grid points of the Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) produced at NASA's Global Modelling and Assimilation Office from January 1, 2007 to October 31, 2016. Apart from comparative statistics, the differences in the multifractal properties of the time series were evaluated with the use of MultiFractal Detrended Fluctuation Analysis (MFDFA), both for hourly and daily data, showing a high degree of similarity between the MERRA-2 and IMGW-PIB series. For the air pressure and air temperature, not only were high determination coefficients (close to .99) between the time series coming from the two sources noticed, but there were also similarities with the MFDFA parameters. Lower correlations between the time series of the wind speed obtained from the two studied databases were observed, which was related to differences in the data structure and methodology of the measurements for specific IMGW-PIB stations. Additionally , to verify data similarities coming from the IMGW-PIB and MERRA-2 databases , the correlations between specific multifractal parameters and the orography were estimated and compared. For the air pressure and temperature, a remarkably high correlation was found between the multifractal parameter α 0 and the height above sea level of the measurement site. An analysis of the source of multifractality was performed, indicating that, for all studied meteorological elements and both data sources, the long-range correlations prevail.
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Atmosphere, Oct 18, 2020
The multifractal properties of six acknowledged agro-meteorological parameters, such as reference... more The multifractal properties of six acknowledged agro-meteorological parameters, such as reference evapotranspiration (ET0), wind speed (U), incoming solar radiation (SR), air temperature (T), air pressure (P), and relative air humidity (RH) of five stations in California, USA were examined. The investigation of multifractality of datasets from stations with differing terrain conditions using the Multifractal Detrended Fluctuation Analysis (MFDFA) showed the existence of a long-term persistence and multifractality irrespective of the location. The scaling exponents of SR and T time series are found to be higher for stations with higher altitudes. Subsequently, this study proposed using the novel multifractal cross correlation (MFCCA) method to examine the multiscale-multifractal correlations properties between ET0 and other investigated variables. The MFCCA could successfully capture the scale dependent association of different variables and the dynamics in the nature of their associations from weekly to inter-annual time scales. The multifractal exponents of P and U are consistently lower than the exponents of ET0, irrespective of station location. This study found that joint scaling exponent was nearly the average of scaling exponents of individual series in different pairs of variables. Additionally, the α-values of joint multifractal spectrum were lower than the α values of both of the individual spectra, validating two universal properties in the MFCCA studies for agro-meteorological time series. The temporal evolution of cross-correlation determined by the MFCCA successfully captured the dynamics in the nature of associations in the P-ET0 link.
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Journal of Climate Change Research, Nov 22, 2020
The agricultural drought, severely affecting human life, occurs unpredictably at different times ... more The agricultural drought, severely affecting human life, occurs unpredictably at different times with different intensities. The conventional methods for assessing drought often relay on indices obtained using meteorological data, but due to the low spatial coverage, incompleteness and inaccuracy of these data, meteorological indices cannot be considered as a comprehensive method. Therefore, it is suggested that remote sensing constitute more versatile approach, as it allows to assess the drought using the adequate spatial and temporal coverage for the study area. In the study, performed for the Panjshir river basin in Afghanistan, the 2010-2019 period is used to evaluate vegetation rate using NDVI data from MODIS. To calculate agricultural drought indices (DSI, VCI and TCI), May and June were selected, as the peak vegetation time occurs for these months. On the base of the remote sensing indicators it was shown that during the study period the drought conditions were normal in the region, except for 2011, 2017, and 2018, which were the driest years, and for 2019, which was the wettest year. Agricultural drought indices were compared to SPI index calculated using winter and spring precipitation data recorded at the meteorological stations. It was observed that the remote sensing indices showed the highest correlation with data from Kabul meteorological station, which is located at the same altitude and climate as the dense vegetation zone. Furthermore, the comparison showed that the ground precipitation data is characterized by higher amplitudes than the remote sensing data. From the above it steams that the vegetation in the Panjshir basin is influenced by both seasonal rainfall and rivers that continuously flood the area.
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Journal of Hydrology, Jul 8, 2020
Collected rainfall records by gauges lead to key forcings in most hydrological studies. Depending... more Collected rainfall records by gauges lead to key forcings in most hydrological studies. Depending on sensor type and recording systems, such data are characterized by different time-resolutions (or temporal aggregations), t a. We present an historical analysis of the time-evolution of t a based on a large database of rain gauge networks operative in many study areas. Globally, t a data were collected for 25,423 rain gauge stations across 32 geographic areas, with larger contributions from Australia, USA, Italy and Spain. For very old networks early recordings were manual with coarse time-resolution, typically daily or sometimes monthly. With a few exceptions, mechanical recordings on paper rolls began in the first half of the 20th century, typically with t a of 1 h or 30 min. Digital registrations started only during the last three decades of the 20th century. This short period limits investigations that require long time-series of sub-daily rainfall data, e.g, analyses of the effects of climate change on short-duration (sub-hourly) heavy rainfall. In addition, in the areas with rainfall data characterized for many years by coarse time-resolutions, annual maximum rainfall depths of short duration can be potentially underestimated and their use would produce errors in the results of successive applications. Currently, only 50% of the stations provide useful data at any time-resolution, that practically means t a = 1 min. However, a significant reduction of these issues can be obtained through the information content of the present database. Finally, we suggest an integration of the database by including additional rain gauge networks to enhance its usefulness particularly in a comparative analysis of the effects of climate change on extreme rainfalls of short duration available in different locations.
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Agricultural and Forest Meteorology, Feb 15, 2020
This paper explores the idea of combining Trigonometric Exponential Smoothing State Space model w... more This paper explores the idea of combining Trigonometric Exponential Smoothing State Space model with Box-Cox transformation, ARMA errors, Trend and Seasonal Components (TBATS) with Support Vector Machine (SVM) model to estimate time series of the minimum and maximum daily air temperatures in a period of six years for various climatic localizations in Europe. It was found that a combined SVM/TBATS model can predict not only seasonality but also local temperature variation between subsequent days observed in daily data. Because the SVM sub-model uses not only results of TBATS prediction as an input data, but also several meteorological values, such modelling cannot be treated as a future time series estimation. Therefore, it has a potential to be used for filling gaps in the air temperature data. As is shown in our results, the precision of air temperature prediction improves when using the combined SVM/TBATS modelling, compared with pure TBATS or SVM modelling. For various locations, which can be related with different climatic conditions, this improvement ranged from 3% up to 14% for the maximum daily air temperature and from 5% to 25% for the minimum daily air temperature. The temperature sums calculated on the base of air temperatures predicted with SVM/TBATS models and from measured values did not differ more than 300 °C (less than 1 °C per day) in majority of cases. The average error in wheat yield prediction by WOFOST and DNDC models did not exceed 12.8% and 13.3%, respectively.
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International Agrophysics, Oct 25, 2019
One unintended consequence of nitrogen use in agriculture is an increase in nitrate content in gr... more One unintended consequence of nitrogen use in agriculture is an increase in nitrate content in ground waters. Nitrogen content was evaluated in soil samples from specific hydrographic regions of Poland from the 60-90 cm soil layer, in which this nutrient is not readily available to the main root mass of crop plants and may negatively affect the environment. It was revealed that Nmin content in specific hydrographic regions was highly dependent on both the soil type and land use. Notably higher values of Nmin content were observed for organic soils. The highest N contents were found in the grasslands of the north-western area of Poland, while they were slightly lower in several regions of the main Odra River catchment and west of the Vistula River. The area with a high Nmin content in soils under maize was significantly larger compared to the grasslands area and primarily included the hydrographic regions of the Odra River basin in its south-western stretch, and of the Vistula River on its western and south-eastern side. With regard to the arable land under mixed cereals, the soils with the highest Nmin content in the non-root layer were predominantly located in hydrographic regions belonging to the main Odra catchment and to the catchment of the Vistula River in its upper course.
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Chaos, Solitons & Fractals, Oct 1, 2019
Spatial variability of the multifractal properties of a 36-year-long meteorological time series f... more Spatial variability of the multifractal properties of a 36-year-long meteorological time series for Poland coming from the MERRA-2 database was analysed. It constitute a very valuable source of meteorological data, as high similarity with ground data recorded at meteorological stations in the region of interest was stated by the analysis of similarity measures. The highest variability of multifractal spectra parameters was observed for the air temperature, whereas the lowest was for the air pressure. Spatial analysis of multifractal spectra parameters enabled to select the regions vulnerable to the occurrence of extreme events, correlated or uncorrelated processes, etc. Obtained maps of multifractal parameters give a new insight into climate dynamics in the region and are a valuable source of information for comparative analyses. The spatial variation of the parameters of multifractal spectra was also confirmed by geo-statistical analysis, which delivered important information about the range of influence, sill and nugget variance. The paper is the first attempt to use geo-statistical analysis in regard to multifractal properties of meteorological quantities.
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Theoretical and Applied Climatology, Aug 1, 2019
The results of the multifractal analysis performed for meteorological time series coming from fou... more The results of the multifractal analysis performed for meteorological time series coming from four stations in Poland and Bulgaria located in varying climatic zones are presented. To assess climatic shift response (in 2001/2002), the analysis was conducted separately for two subsets. To analyze long-distance power-law correlations within the studied time series and evaluate the differences in dynamics of the climate between the analyzed sites and periods of time, the multifractal detrended fluctuation analysis methodology (MF-DFA) was proposed. It was revealed that the multifractal properties of precipitation differ considerably from other analyzed quantities. The singularity spectra were susceptible to climatic shift, what was indicated by the changes of spectra parameters. It was especially apparent for asymmetry, which changed from being right- to left-skewed, implying the occurrence of more extreme events. Similarities in the dynamics of meteorological processes for each of the climatic zones were proven by the close relation of respective multifractal spectra parameters coming from closely spatially related localizations.
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Applied Ecology and Environmental Research, Jun 12, 2019
Evaluation of mineral nitrogen content (Nmin) was performed for the 60-90 cm layer of grassland s... more Evaluation of mineral nitrogen content (Nmin) was performed for the 60-90 cm layer of grassland soils relative to other selected agricultural fodder crops. Soil samples were collected two times per year, in spring and autumn, over the period 2010-2012 from fixed locations scattered across whole Poland territory. Additionally, particle-size distribution was assessed in the tested soil samples, which allowed to assign soil agronomic categories to them and assess the relationship between Nmin content and assigned categories. Regardless of sampling date and land use, agronomic category had a significant effect on Nmin content. Generally the relationships between the percentage of particles with dimensions below 0.02 mm and Nmin content were characterized by a negative correlations, but in maize crops they were found to be positively correlated. Based on the obtained correlations, linear regression equations were developed. Calculated relations were less pronounced in spring, before fertilization, than in the autumn, after harvest. These equations can be very important from the practical point of view, as they may be used by farmer to plan a rational and sustainable fertilization based on forecasting of losses of mineral nitrogen content in the soil depending on the percentage of fine particles (agronomic category) of cultivated soil.
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Applied Ecology and Environmental Research, Feb 14, 2019
This study attempted to evaluate the relationship between mineral nitrogen (Nmin) content and soi... more This study attempted to evaluate the relationship between mineral nitrogen (Nmin) content and soil pH in the 60-90 cm layer of grassland soils relative to other selected agricultural fodder crops. The area of the study uniformly covered the whole territory of Poland. The dependence between Nmin content and soil pH was expressed as correlation coefficients, while their significance was evaluated using the one-way non-orthogonal analysis of variance classification. Regardless of sampling date (spring or autumn) and land use (meadow, pasture, hay and pasture or alternate), soil pH had a significant effect on Nmin concentration. The correlation between Nmin and soil pH in grasslands on mineral soils was positive, regardless of soil sampling date. In turn, in organic soils a negative correlation between pH and Nmin content was observed in the spring period, whereas in autumn this trend did not persist and the correlation was positive. On the other hand, in the case of agricultural fodder crops (maize or mixed cereal) Nmin content in the 60-90 cm layer and soil pH were found to be positively correlated, regardless of spring or autumn sampling date, with a correlation coefficient higher than 0.9. The obtained results can be used for diminishing environmental hazards.
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Agricultural and Forest Meteorology, Jan 15, 2019
Climate change is expected to severely affect cropping systems and food production in many parts ... more Climate change is expected to severely affect cropping systems and food production in many parts of the world unless local adaptation can ameliorate these impacts. Ensembles of crop simulation models can be useful tools for assessing if proposed adaptation options are capable of achieving target yields, whilst also quantifying the share of uncertainty in the simulated crop impact resulting from the crop models themselves. Although some studies have analysed the influence of ensemble size on model outcomes, the effect of ensemble composition has not yet been properly appraised. Moreover, results and derived recommendations typically rely on averaged ensemble simulation results without accounting sufficiently for the spread of model outcomes. Therefore, we developed an Ensemble Outcome Agreement (EOA) index, which analyses the effect of changes in composition and size of a multi-model ensemble (MME) to evaluate the level of agreement between MME outcomes with respect to a given hypothesis (e.g. that adaptation measures result in positive crop responses). We analysed the recommendations of a previous study performed with an ensemble of 17 crop models and testing 54 adaptation options for rainfed winter wheat (Triticum aestivum L.) at Lleida (NE Spain) under perturbed conditions of temperature, precipitation and atmospheric CO2 concentration. Our results confirmed that most adaptations recommended in the previous study have a positive effect. However, we also showed that some options did not remain recommendable in specific conditions if different ensembles were considered. Using EOA, we were able to identify the adaptation options for which there is high confidence in their effectiveness at enhancing yields, even under severe climate perturbations. These include substituting spring wheat for winter wheat combined with earlier sowing dates and standard or longer duration cultivars, or introducing supplementary irrigation, the latter increasing EOA values in all cases. There is low confidence in recovering yields to baseline levels, although this target could be attained for some adaptation options under moderate climate perturbations. Recommendations derived from such robust results may provide crucial information for stakeholders seeking to implement adaptation measures.
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Przemysł Chemiczny, Nov 17, 2018
A mineral N content (Nmin) in the 60-90 cm layer of mineral and org. soils depending on the N dos... more A mineral N content (Nmin) in the 60-90 cm layer of mineral and org. soils depending on the N dose in the mineral fertilizer used for grassland as well as for the cultivation of maize and cereal mixes in 2010-2012 was detd. in spring and autumn to find a resp. correlation. The Nmin content and the dose of N fertilizer were positively correlated for (i) grassland on mineral soils, (ii) grassland on org. soils, and (iii) cultivations of maize and cereal mixes on mineral soils. Particularly high correlation coeffs. (higher than 0.8) were obsd. for cereal mixes cultivations. A negative correlation was obsd. only for grassland on org. soils during the autumn sampling.
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Acta Agrophysica, Oct 4, 2018
Mineral nitrogen occurring at the depth of 60-90 cm of the soil profile, which is unavailable to ... more Mineral nitrogen occurring at the depth of 60-90 cm of the soil profile, which is unavailable to the main root mass of grassland plants and arable land crops and which is located in this layer due to leaching to deeper soil layers, can pose a serious threat to water quality. This study attempted to evaluate N min content in grassland soils depending on soil type, land use, and farming intensity (i.e. livestock density). Regardless of observation period and natural factors evaluated, both land use and grassland use had a significant effect on mineral nitrogen content in the 60-90 cm soil layer. The lowest nitrogen content was shown in grassland mineral soils, whereas the cultivation of both maize and mixed cereals promoted greater accumulation of this nutrient in the soil profile at the depth of 60-90 cm. Mineral nitrogen content also depended on the use of grassland ecosystems. In mineral soils, the highest amounts of N min were found in hay grasslands, whereas in organic soils-in hay and pasture grasslands. The lowest amounts of nitrogen in the investigated soil layer were observed in alternate grasslands. It was also revealed that strong significant correlations exist between livestock density and the content of mineral nitrogen in the 60-90 cm soil layer. Calculated regression equation describing those relationships can help the farmer to plan sustainable fertilisation depending on livestock density of his farm.
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Agricultural Systems, Sep 5, 2018
Crop growth simulation models can differ greatly in their treatment of key processes and hence in... more Crop growth simulation models can differ greatly in their treatment of key processes and hence in their response to environmental conditions. Here, we used an ensemble of 26 process-based wheat models applied at sites across a European transect to compare their sensitivity to changes in temperature (−2 to +9°C) and precipitation (−50 to +50%). Model results were analysed by plotting them as impact response surfaces (IRSs), classifying the IRS patterns of individual model simulations, describing these classes and analysing factors that may explain the major differences in model responses. The model ensemble was used to simulate yields of winter and spring wheat at four sites in Finland, Germany and Spain. Results were plotted as IRSs that show changes in yields relative to the baseline with respect to temperature and precipitation. IRSs of 30-year means and selected extreme years were classified using two approaches describing their pattern. The expert diagnostic approach (EDA) combines two aspects of IRS patterns: location of the maximum yield (nine classes) and strength of the yield response with respect to climate (four classes), resulting in a total of 36 combined classes defined using criteria pre-specified by experts. The statistical diagnostic approach (SDA) groups IRSs by comparing their pattern and magnitude, without attempting to interpret these features. It applies a hierarchical clustering method, grouping response patterns using a distance metric that combines the spatial correlation and Euclidian distance between IRS pairs. The two approaches were used to investigate whether different patterns of yield response could be related to different properties of the crop models, specifically their genealogy, calibration and process description. Although no single model property across a large model ensemble was found to explain the integrated yield response to temperature and precipitation perturbations, the application of the EDA and SDA approaches revealed their capability to distinguish: (i) stronger yield responses to precipitation for winter wheat than spring wheat; (ii) differing strengths of response to climate changes for years with anomalous weather conditions compared to period-average conditions; (iii) the influence of site conditions on yield patterns; (iv) similarities in IRS patterns among models with related genealogy; (v) similarities in IRS patterns for models with simpler process descriptions of root growth and water uptake compared to those with more complex descriptions; and (vi) a closer correspondence of IRS patterns in models using partitioning schemes to represent yield formation than in those using a harvest index. Such results can inform future crop modelling studies that seek to exploit the diversity of multi-model ensembles, by distinguishing ensemble members that span a wide range of responses as well as those that display implausible behaviour or strong mutual similarities.
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Journal of Elementology, Jul 11, 2018
The level of macro- and microelements in soil and its reaction are among those physico-chemical p... more The level of macro- and microelements in soil and its reaction are among those physico-chemical properties that have a decisive impact on plant production, including orchard plantations. Evaluation of those properties provides extremely important information that can help the fruit farmer in making rational and correct decisions concerning the application of mineral, natural and organic fertilisers, as well as soil liming. Therefore, in the years 2009-2011 environmental studies were conducted, the aim of which was to evaluate the actual reaction and abundance of orchard soils (mainly apple tree orchards) of south-eastern Poland, as one of the largest fruit-growing regions in Poland, in the assimilable forms of macro- and micronutrients (phosphorus, potassium, magnesium, boron, copper, iron, manganese and zinc) and to determine the relations of these elements with the agronomic category and pHKCl. The research was conducted using the results of chemical analyses of 1,611 soil samples (3 replications per each soil sampling point) collected in the late autumn, after the fruit harvest and before all agrotechnical treatments, from the arable horizon 0-20 cm. In the samples, the particle size distribution and reaction were determined and agronomy categories and reaction classes were specified. The content of available forms of phosphorus, potassium and magnesium was determined in 1,611 samples, whereas the content of boron, copper, iron, manganese and zinc was assessed in 1,518 soil samples. It was found that the reaction of the investigated orchard soils was mainly in the slightly acidic range. In most cases, the content of assayed available forms of macro- (P, K, Mg) and microelements (B, Cu, Fe, Mn, Zn) displayed significant and positive correlation with the agronomic category and soil reaction class (except for iron) and also with the content of the other analysed elements.
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Acta Agrophysica, Jun 4, 2018
An environmental study, which was conducted at 45 agricultural farms located in south-eastern Pol... more An environmental study, which was conducted at 45 agricultural farms located in south-eastern Poland (Lubelskie Voivodeship) over the period of 2015-2016, evaluated the effect of some soil physicochemical properties and nitrogen fertilisation on winter wheat yield. Soil physicochemical analysis was performed using conventional methods at the accredited laboratory of the Regional Chemical and Agricultural Station in Lublin. Factorial analysis was carried out after classifying the soil according to soil textural classes, pH classes, and phosphorus, potassium and magnesium abundance classes, as well as after determining three nitrogen rates applied for wheat and its previous crop: I – 0-30; II – 31-60; III – 61-90 kg N ha–1. The study found a positive, but not always significant, effect of soil textural class (in particular, the content of silt and clay particles) and soil pH class (from acidic to alkaline) on winter wheat grain yield. Soil phosphorus, potassium and magnesium abundance was not found to have any significant effect on grain yield. However, these nutrients were observed to positively affect wheat grain yield. Nitrogen fertilisation applied for the evaluated crop and the previous crop was found to significantly affect winter wheat grain yield.
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International Agrophysics, May 25, 2018
The daily air temperature and precipitation time series recorded between January 1, 1980 and Dece... more The daily air temperature and precipitation time series recorded between January 1, 1980 and December 31, 2010 in four European sites (Jokioinen, Dikopshof, Lleida and Lublin) from different climatic zones were modeled and forecasted. In our forecasting we used the methods of the Box-Jenkins and Holt-Winters seasonal auto regressive integrated moving-average, the autoregressive integrated moving-average with external regressors in the form of Fourier terms and the time series regression, including trend and seasonality components methodology with R software. It was demonstrated that obtained models are able to capture the dynamics of the time series data and to produce sensible forecasts.
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