scholarly journals Seed hairs of poplar trees as natural airborne pollen trap for allergenic pollen grains

Grana ◽  
2008 ◽  
Vol 47 (3) ◽  
pp. 241-245 ◽  
Author(s):  
Ya‐Qin Hu ◽  
David Kay Ferguson ◽  
Subir Bera ◽  
Cheng‐Sen Li
2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Marcel Polling ◽  
Chen Li ◽  
Lu Cao ◽  
Fons Verbeek ◽  
Letty A. de Weger ◽  
...  

AbstractMonitoring of airborne pollen concentrations provides an important source of information for the globally increasing number of hay fever patients. Airborne pollen is traditionally counted under the microscope, but with the latest developments in image recognition methods, automating this process has become feasible. A challenge that persists, however, is that many pollen grains cannot be distinguished beyond the genus or family level using a microscope. Here, we assess the use of Convolutional Neural Networks (CNNs) to increase taxonomic accuracy for airborne pollen. As a case study we use the nettle family (Urticaceae), which contains two main genera (Urtica and Parietaria) common in European landscapes which pollen cannot be separated by trained specialists. While pollen from Urtica species has very low allergenic relevance, pollen from several species of Parietaria is severely allergenic. We collect pollen from both fresh as well as from herbarium specimens and use these without the often used acetolysis step to train the CNN model. The models show that unacetolyzed Urticaceae pollen grains can be distinguished with > 98% accuracy. We then apply our model on before unseen Urticaceae pollen collected from aerobiological samples and show that the genera can be confidently distinguished, despite the more challenging input images that are often overlain by debris. Our method can also be applied to other pollen families in the future and will thus help to make allergenic pollen monitoring more specific.


Aerobiologia ◽  
2020 ◽  
Vol 36 (4) ◽  
pp. 669-682 ◽  
Author(s):  
Antonella Cristofori ◽  
Edith Bucher ◽  
Michele Rossi ◽  
Fabiana Cristofolini ◽  
Veronika Kofler ◽  
...  

AbstractArtemisia pollen is an important aeroallergen in late summer, especially in central and eastern Europe where distinct anemophilous Artemisia spp. produce high amounts of pollen grains. The study aims at: (i) analyzing the temporal pattern of and changes in the Artemisia spp. pollen season; (ii) identifying the Artemisia species responsible for the local airborne pollen load.Daily pollen concentration of Artemisia spp. was analyzed at two sites (BZ and SM) in Trentino-Alto Adige, North Italy, from 1995 to 2019.The analysis of airborne Artemisia pollen concentrations evidences the presence of a bimodal curve, with two peaks, in August and September, respectively. The magnitude of peak concentrations varies across the studied time span for both sites: the maximum concentration at the September peak increases significantly for both the BZ (p < 0.05) and SM (p < 0.001) site. The first peak in the pollen calendar is attributable to native Artemisia species, with A. vulgaris as the most abundant; the second peak is mostly represented by the invasive species A. annua and A. verlotiorum (in constant proportion along the years), which are causing a considerable increase in pollen concentration in the late pollen season in recent years.. The spread of these species can affect human health, increasing the length and severity of allergenic pollen exposure in autumn, as well as plant biodiversity in both natural and cultivated areas, with negative impacts on, e.g., Natura 2000 protected sites and crops.


Author(s):  
Nicoleta Ianovici

Many airborne pollen grains and fungal spores are important biopollutants responsible for human respiratory allergy. In the conditions of România the most important cause of pollinosis is allergenic pollen of some deciduous trees as well as grasses and weeds. The measurements of pollen concentration in the aeroplankton of Timişoara were carried out in 2003 by the volumetric method. The highest concentrations are noted in April and August. A total of 23 types of pollen taxa were recorded in the air of the study area in the 2003-year: Acer, Alnus, Ambrosia, Artemisia, Betula, Carpinus, Chenopodiaceae/Amaranthaceae, Corylus, Fraxinus, Juglans, Morus, Pinaceae, Platanus, Plantago, Populus, Poaceae, Rumex, Salix, Quercus, Taxaceae/Cupressaceae, Tilia, Urtica, Ulmus. The highest values of annual total of pollen grains in a group of trees were reached by Populus and Betula, as well as in a group of grasses and weeds – Ambrosia, Urtica and Poaceae. Trees pollen predominantly contributed to the total pollen sum with a percentage of 53.56%, followed by herbs 37.54% and grasses 8.9%.


2020 ◽  
Author(s):  
Marcel Polling ◽  
Chen Li ◽  
Lu Cao ◽  
Fons Verbeek ◽  
Letty de Weger ◽  
...  

Abstract Monitoring of airborne pollen concentrations provides an important source of information for the globally increasing number of hay fever patients. Airborne pollen are traditionally counted under the microscope, but with the latest developments in image recognition methods, automating this process has become feasible. A challenge that persists, however, is that many pollen grains cannot be distinguished beyond the genus or family level using a microscope. Here, we assess the use of a Convolutional Neural Network (CNN) to increase taxonomic accuracy for airborne pollen. As a case study we use the nettle family (Urticaceae), which contains two main genera (Urtica and Parietaria) common in European landscapes which pollen cannot be separated by trained specialists. While pollen from Urtica species have very low allergenic relevance, those from several species of Parietaria are severely allergenic. We collect pollen from both fresh as well as from herbarium specimens and use these to train the CNN model VGG16. The model shows that Urticaceae pollen can be distinguished with 98.3% accuracy. We then apply our model on Urticaceae pollen collected from aerobiological samples and show that the genera can be confidently distinguished, despite the more challenging input images that are often overlain by debris. Our method can also be applied to other pollen families in the future and will thus help to make allergenic pollen monitoring more specific.


2020 ◽  
Author(s):  
Xiaoxia Shang ◽  
Elina Giannakaki ◽  
Stephanie Bohlmann ◽  
Maria Filioglou ◽  
Annika Saarto ◽  
...  

Abstract. We present a novel algorithm for characterizing the optical properties of pure pollen particles, based on the depolarization values obtained in lidar measurements. The algorithm was first tested and validated through a simulator, and then applied to the lidar observations during a four-month pollen campaign from May to August 2016 at the European Aerosol Research Lidar Network (EARLINET) station in Kuopio (62°44′ N, 27°33′ E), in Eastern Finland. Twenty types of pollen were observed and identified from concurrent measurements with Burkard sampler; Birch (Betula), pine (Pinus), spruce (Picea) and nettle (Urtica) pollen were most abundant, contributing more than 90 % of total pollen load, regarding number concentrations. Mean values of lidar-derived optical properties in the pollen layer were retrieved for four intense pollination periods (IPPs). Lidar ratios at both 355 and 532 nm ranged from 55 to 70 sr for all pollen types, without significant wavelength-dependence. Enhanced depolarization ratio was found when there were pollen grains in the atmosphere, and even higher depolarization ratio (with mean values of 25 % or 14 %) was observed with presence of the more non-spherical spruce or pine pollen. The depolarization ratio at 532 nm of pure pollen particles was assessed, resulting to 24 ± 3 % and 36 ± 5 % for birch and pine pollen, respectively. Pollen optical properties at 1064 nm and 355 nm were also estimated. The backscatter-related Ångström exponent between 532 and 1064 nm was assessed as ~ 0.8 (~ 0.5) for pure birch (pine) pollen, thus the longer wavelength would be better choice to trace pollen in the air. The pollen depolarization ratio at 355 nm of 17 % and 30 % were found for birch and pine pollen, respectively. The depolarization values show a wavelength dependence for pollen. This can be the key parameter for pollen detection and characterization.


2019 ◽  
Vol 213 ◽  
pp. 311-325 ◽  
Author(s):  
Hassan Dehdari Rad ◽  
Mohammad-Ali Assarehzadegan ◽  
Gholamreza Goudarzi ◽  
Armin Sorooshian ◽  
Yaser Tahmasebi Birgani ◽  
...  

2014 ◽  
Vol 6 (4) ◽  
pp. 428-432 ◽  
Author(s):  
Tiwalade A. ADENIYI ◽  
Peter A. ADEONIPEKUN ◽  
James D. OLOWOKUDEJO ◽  
Idowu S. AKANDE

Data on the prevalence of pollen in the atmosphere is limited and almost non-existent for Lagos State and Nigeria. Pollen grains are known to be highly allergenic and thus they are potential causes of respiratory diseases. To investigate airborne incidence of pollen, so as to construct a pollen calendar and contribute to current trends in the development of aeropalynology/allergy study in Nigeria, three highly populated locations in Shomolu Local Government areas of Lagos State: University of Lagos, Bariga and Gbagada, were sampled. Aero-samplers were harvested monthly from January 2013 to December 2013. After acetolysis treatment and analysis, the total pollen count was 4393, belonging to 38 pollen taxa and 29 families. The main taxa include Poaceae, Cyperaceae, Amaranthaceae, Ludwigia and Alchornea. Monthly pollen counts were highest in October and lowest in June. Almost three-quarters of the total pollen content came from grasses and weeds. This composition reflects the ornamental and grassland flora of the town, as well as the natural vegetation surrounding the urban area. The total pollen concentration correlates positively with the temperature and negatively with the wind, rainfall and relative humidity, which was similar in the dominant taxa Amaranthaceae and Alchornea. Dominant taxa Cyperaceae and Ludwigia have significant positive correlation with wheezing cough. Results from this work will form the basis for a forecast service required to inform and educate the general public and allergy sufferers about pollen distribution in Lagos State.


2017 ◽  
Vol 584-585 ◽  
pp. 603-613 ◽  
Author(s):  
J.M. Maya-Manzano ◽  
M. Sadyś ◽  
R. Tormo-Molina ◽  
S. Fernández-Rodríguez ◽  
J. Oteros ◽  
...  

Author(s):  
Rachel N. McInnes

Allergenic pollen is produced by the flowers of a number of trees, grasses, and weeds found throughout the world. Human exposure to such pollen grains can exacerbate pollen-related asthma and allergenic conditions such as allergic rhinitis (hay fever). While allergenic pollen comes from three main groups of plants—certain trees, grasses, and weeds—many people are sensitive to pollen from one or a few taxa only. Weather, climate, and environmental conditions have a significant impact on the levels and varieties of pollen grains present in the air. These allergenic conditions significantly reduce the quality of life of affected individuals and have been shown to have a major economic impact. Pollen production depends on both the current meteorological conditions (including day length, temperature, irradiation, precipitation, and wind speed/direction), and the water availability and other environmental and meteorological conditions experienced in the previous year. The climate affects the types of vegetation and taxa that can grow in a particular location through availability of different habitats. Land-use or land management is also crucial, and so this field of study has implications for vegetation management practices and policy. Given the influential effects of weather and climate on pollen, and the significant health impacts globally, the total effect of any future environmental and climatic changes on aeroallergen production and spread will be significant. The overall impact of climate change on pollen production and spread remains highly uncertain, and there is a need for further understanding of pollen-related health impact information. There are a number of ways air quality interacts with the impact of pollen. Further understanding of the risks of co-exposure to both pollen and air pollutants is needed to better inform public health policy. Furthermore, thunderstorms have been linked to asthma epidemics, especially during the grass pollen seasons. It is thought that allergenic pollen plays a role in this “thunderstorm asthma.” To reduce the exposure to, or impact from, pollen grains in the air, a number of adaptation and mitigation options may be adopted. Many of these would need to be done either through policy changes, or at a local or regional level, although some can be done by individuals to minimize their exposure to pollen they are sensitive to. Improved aeroallergen forecast models could be developed to provide detailed taxon-specific, localized information to the public. One challenge will be combining the many different sources of aeroallergen data that are likely to become available in future into numerical forecast systems. Examples of these potential inputs are automated observations of aeroallergens, real-time phenological observations and remote sensing of vegetation, social sensing, DNA analysis of specific aeroallergens, and data from symptom trackers or personal monitors. All of these have the potential to improve the forecasts and information available to the public.


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