Search

Chaenomeles japonica is an attractive ornamental shrub flowering in spring. It is also a valuable source of nectar and pollen for entomofauna. The study was carried out to investigate the structure of hypanthial nectaries present in the flowers of this species with the use of light and scanning electron microscopy. Nectary tissues were examined in three stages of flowering, with special focus placed on changes occurring in the epidermis and nectariferous parnechyma. Long-styled flowers, which produce nectar abundantly, were selected for the study. The nectary parenchyma was shown to consist of multiple cell layers (up to 20). The epidermis was initially single-layered, but the number of layers gradually increased to 2–3 during the following days of flowering. The outer walls of epidermis cells were covered by a strongly undulating cuticle with massive striae. Cracks and perforations, which are probably nectar release sites, were visible between the striae. The presence of the secretion in the intercellular spaces between the parenchyma layer and the epidermis may indicate apoplastic nectar transport. The presence of stomata, as well as pores in the cuticle layer of the nectary epidermis, suggests that C. japonica nectar is secreted in two ways: (i) through the nectarostomata and (ii) ordinary epidermis cells with the involvement of the cuticle. [ABSTRACT FROM AUTHOR]

In this work, the HYSPLIT model was used to reproduce birch pollen concentrations in Poland for the years 2015 and 2016, where there was significant variation in terms of pollen concentrations and start/end dates of the pollen season. The analysis of pollen observations showed that the seasonal pollen integral (SPIn) was low in 2015 with a shorter season compared to 2016. In 2016, SPIn was unusually high. The HYSPLIT model simulation, with a one-hour temporal resolution, was conducted during the birch pollen season (from March to May) for 2015 and 2016. Meteorological data were obtained from the WRF model. The birch coverage map of the European Forest Institute was used. The emission, introduced to the model, covered Central Europe with a resolution of 0.3° × 0.3°. The results were compared to data from 11 observation stations in Poland. The measured birch pollen concentrations for 2015 were overestimated by HYSPLIT at 8 of the 11 stations (normalized mean bias/NMB from 0.13 to 2.53) and underestimated for three stations (NMB from − 0.44 to − 0.15). For 2016, the model highly underestimated the pollen concentrations, with NMB ranging from − 0.45 to − 0.93. In general, the results show that the model can resolve the main peaks of pollen concentrations, which is a step forward in the application of the HYSPLIT model for birch pollen forecasting over Poland. We suggest the application of methods that can reduce the bias of temperature such as meteorological data assimilation or bias correction, which could improve calculation of the start of emissions and consequently the start of the pollen season as well as pollen concentrations. [ABSTRACT FROM AUTHOR]

In recent years, allergies due to airborne pollen allergens have shown an increasing trend, along with the severity of allergic symptoms in most industrialized countries, while synergism with other common atmospheric pollutants has also been identified as affecting the overall quality of citizenly life. In this study, we propose the state-of-the-art WRF-Chem model, which is a complex Eulerian meteorological model integrated on-line with atmospheric chemistry. We used a combination of the WRF-Chem extended towards birch pollen, and the emission module based on heating degree days, which has not been tested before. The simulations were run for the moderate season in terms of birch pollen concentrations (year 2015) and high season (year 2016) over Central Europe, which were validated against 11 observational stations located in Poland. The results show that there is a big difference in the model's performance for the two modelled years. In general, the model overestimates birch pollen concentrations for the moderate season and highly underestimates birch pollen concentrations for the year 2016. The model was able to predict birch pollen concentrations for first allergy symptoms (above 20 pollen m−3) as well as for severe symptoms (above 90 pollen m−3) with probability of detection at 0.78 and 0.68 and success ratio at 0.75 and 0.57, respectively for the year 2015. However, the model failed to reproduce these parameters for the year 2016. The results indicate the potential role of correcting the total seasonal pollen emission in improving the model's performance, especially for specific years in terms of pollen productivity. The application of chemical transport models such as WRF-Chem for pollen modelling provides a great opportunity for simultaneous simulations of chemical air pollution and allergic pollen with one goal, which is a step forward for studying and understanding the co-exposure of these particles in the air. [ABSTRACT FROM AUTHOR]

Centaurea cyanus L. is a valuable source of many different bioactive substances. It is used in herbal medicine, but the structure of its organs used as raw material and secretory tissues has been insufficiently examined. The aim of this paper was to investigate the microstructure of C. cyanus flowers, bracts, stems and leaves with particular emphasis on secretory structures. Moreover, the main classes of secondary metabolites present in the secretion were identified and the taxonomic value of some micromorphological and anatomical features was analysed. Histochemical, micromorphological and ultrastructural analyses of aboveground organs of C. cyanus were carried out using light, fluorescence, scanning and transmission electron microscopy. The analyses revealed the presence of petal papillae and a characteristic cuticular pattern on the petals, stamens and stylar hairs. There were four types of non-glandular trichomes on the bracts, leaves and stem surfaces. The epidermal cells of the bracts contained prismatic calcium oxalate crystals. Two kinds of secretory structures, i.e. glandular trichomes and ducts, were observed in the C. cyanus organs. The glandular trichomes were located on the bract and stem surfaces, and the ducts were detected in the leaves and stems. Ultrastructural analyses of the epithelium of the ducts showed the presence of strongly osmiophilic insoluble phenolic material in vacuoles as well as moderately osmiophilic insoluble lipidic material in elaioplasts and vesicles. The results of histochemical assays showed a heterogeneous nature of the duct secretion, which contained essential oil, lipids, flavonoids, tannins and terpenes containing steroids. [ABSTRACT FROM AUTHOR]

Prediction of allergic pollen concentration is one of the most important goals of aerobiology. Past studies have used a broad range of modeling techniques; however, the results cannot be directly compared owing to the use of different datasets, validation methods, and evaluation metrics. The main aim of this study was to compare nine statistical modeling techniques using the same dataset. An additional goal was to assess the importance of predictors for the best model. Aerobiological data for Corylus, Alnus, and Betula pollen counts were obtained from nine cities in Poland and covered between five and 16 years of measurements. Meteorological data from the AGRI4CAST project were used as a predictor variables. The results of 243 final models (3 taxa ×  9 cities × 9 techniques) were validated using a repeated k-fold cross-validation and compared using relative and absolute performance statistics. Afterward, the variable importance of predictors in the best models was calculated and compared. Simple models performed poorly. On the other hand, regression trees and rule-based models proved to be the most accurate for all of the taxa. Cumulative growing degree days proved to be the single most important predictor variable in the random forest models of Corylus, Alnus, and Betula. Finally, the study suggested potential improvements in aerobiological modeling, such as the application of robust cross-validation techniques and the use of gridded variables. [ABSTRACT FROM AUTHOR]

The aim of the study was to create and evaluate models for predicting high levels of daily pollen concentration of Corylus, Alnus, and Betula using a spatiotemporal correlation of pollen count. For each taxon, a high pollen count level was established according to the first allergy symptoms during exposure. The dataset was divided into a training set and a test set, using a stratified random split. For each taxon and city, the model was built using a random forest method. Corylus models performed poorly. However, the study revealed the possibility of predicting with substantial accuracy the occurrence of days with high pollen concentrations of Alnus and Betula using past pollen count data from monitoring sites. These results can be used for building (1) simpler models, which require data only from aerobiological monitoring sites, and (2) combined meteorological and aerobiological models for predicting high levels of pollen concentration. [ABSTRACT FROM AUTHOR]