Skip to main content
Log in

Multivariate statistical forecasting modeling to predict Poaceae pollen critical concentrations by meteoclimatic data

  • Original Paper
  • Published:
Aerobiologia Aims and scope Submit manuscript

Abstract

Forecasting pollen concentrations in the short term is a topic of major importance in aerobiology. Forecasting models proposed in the literature are numerous and increasingly complex, but they fail in at least 25 % of cases and are not available for all botanical species. This work makes it possible to build a forecast model from meteorological data for estimating pollen concentration over a certain threshold of Poaceae, an allergenic family. In Italy, about 25 % of the population suffer from allergies, these in 80 % of cases being caused by airborne allergens, including taxa of agricultural interest such as Poaceae. The pollen dispersion in air is determined by both the phenological stage of plants and the meteorological conditions; the pollen presence varies according to the year, month and even the time of the day. There is a correlation between environmental factors, pollen concentrations and pollinosis. A partial least squares discriminant analysis approach was used in order to predict the presence of Poaceae pollen in the atmosphere with a time lag of 3, 5, 7 days, on the basis of a data set of 14 meteorological and pollen variables over a period of 14 years (1997–2010). The results show a high accuracy in predicting pollen critical concentrations, with values ranging from 85.4 to 88.0 %. This study is hopefully a positive first step in the use of a statistical approach that in the next future could have clinical applications.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Annie, S., & Liem, N. (1980). Effects of light and temperature on anthesis of Holcus lanatus, Festuca rubra and Poa annua. Grana, 19, 21–29.

    Article  Google Scholar 

  • Aznarte, J. L., Nieto Lugilde, D., Benítez, J. M., Alba Sánchez, F., & de Linares Fernández, C. (2007). Forecasting airborne pollen concentration time series with neural and neuro-fuzzy models. Expert Systems with Applications, 32, 1218–1225.

    Article  Google Scholar 

  • Bauchau, V., & Durham, S. R. (2004). Prevalence and rate of diagnosis of allergic rhinitis in Europe. European Respiratory Journal, 24, 758–764.

    Article  CAS  Google Scholar 

  • Benninghoff, W. S., & Edmonds, R. L. (1972). Ecological systems approaches to aerobiology. I. Identification of component elements and their functional relationships. international biological program. Aerobiology program. US/IBP aerobiology program handbook N. 2, University of Michigan, Ann Arbor.

  • Costa, C., Antonucci, F., Pallottino, F., Aguzzi, J., Sun, D. W., & Menesatti, P. (2011). Shape analysis of agricultural products: a review of recent research advances and potential application to computer vision. Food and Bioprocess Technology, 4, 673–692.

    Article  Google Scholar 

  • D’Amato, G. (2011). Effects of climatic changes and urban air pollution on the rising trends of respiratory allergy and asthma. Multidisciplinary Respiratory Medicine, 6(1), 28–37.

    Article  Google Scholar 

  • D’Amato, G., Cecchi, L., Bonini, S., Nunes, C., Annesi-Maesano, I., Behrendt, H., et al. (2007). Allergenic pollen and pollen allergy in Europe. Allergy, 62(9), 976–990.

    Article  Google Scholar 

  • Davies, R. R., & Smith, L. P. (1973). Forecasting the start and severity of the hay fever season. Clinical Allergy, 3, 263–267.

    Google Scholar 

  • Erbas, B., Chang, J. H., Dharmage, S., Ong, E. K., Hyndman, R., Newbigin, E., et al. (2007). Do levels of airborne grass pollen influence asthma hospital admissions? Clinical and Experimental Allergy, 37(11), 1641–1647.

    Article  CAS  Google Scholar 

  • Feo Brito, F., Mur Gimeno, P., Martínez, C., Tobías, A., Suárez, L., Guerra, F., et al. (2007). Pollution and seasonal asthma during the pollen season. A cohort study in Puertollano and Ciudad Real (Spain). Allergy, 62(10), 1152–1157.

    Article  CAS  Google Scholar 

  • Frenguelli, G., Bricchi, E., Mincigrucci, G., Fornaciari, M., Ferranti, F., & Romano, B. (1995). Time linkages between pollination onsets of different taxa over an 11-year period in Perugia, Central Italy. Aerobiologia, 11, 57–61.

    Article  Google Scholar 

  • Galán, C., Cariñanos, P., Alcázar, P., & Domínguez-Vilches, E. (2007). Spanish aerobiological network: Management and quality control. Servicio de Publicaciones, University of Córdoba, Córdoba, Spain.

  • Galan, C., Emberlin, J., Dominguez, E., Bryant, R. H., & Villamandos, F. (1995). A comparative analysis of daily variations in the Gramineae pollen counts at Còrdoba, Spain and London, UK. Grana 34:189–198. ISSN 0017-3134.

    Google Scholar 

  • Garcìa-Mozo, H., Chuine, I., Aira, M. J., Belmonte, J., Bermejo, D., Díaz de la Guardia, C., et al. (2009). Predicting the start and peak dates of the Poaceae pollen season in Spain using process-based models. Agricultural and Forest Meteorology, 149, 256–262.

    Article  Google Scholar 

  • Gioulekas, D., Balafoutis, C., Damialis, A., Papakosta, D., Gioulekas, G., & Patakas, D. (2004). Fifteen-year records of airborne allergenic pollen and meteorological parameters in Thessaloniki, Greece. International Journal of Biometeorology, 48, 128–136.

    Article  Google Scholar 

  • Green, B. J., Dettmann, M., Yli-Panula, E., Rutherford, S., & Simpson, R. (2004). Atmospheric Poaceae pollen frequencies and associations with meteorological parameters in Brisbane, Australia a 5-year record, 1994–1999. International Journal of Biometeorology, 48, 172–178.

    Article  Google Scholar 

  • Hilaire, D., Rotach, M. W., & Clot, B. (2012). Building models for daily pollen concentrations. The example of 16 pollen taxa in 14 Swiss monitoring stations. Aerobiologia, 28, 499–513.

    Article  Google Scholar 

  • Hirst, J. M. (1952). Changes in atmospheric spore content: Diurnal periodicity and the effects of weather. Transactions of the British Micological Society, 36(4), 375–393.

    Article  Google Scholar 

  • Hyde, H. A. (1972). Atmospheric pollen and spores in relation to allergy. Clinical Allergy, 2, 153–179.

    Article  CAS  Google Scholar 

  • Jato, V., Rodrìguez-Rajo, F. J., Seijo, M. C., & Aira, M. J. (2009). Poaceae pollen in Galicia (N.W. Spain): Characterisation and recent trends in atmosphere pollen season. International Journal of Biometeorology, 53, 333–344.

    Article  CAS  Google Scholar 

  • Jochner, S., Ziello, C., Böck, A., Estrella, N., Buters, J., Weichenmeier, I., et al. (2012). Spatio-temporal investigation of flowering dates and pollen counts in the topographically complex Zugspitze area on the German–Austrian border. Aerobiologia, 28, 541–556.

    Article  Google Scholar 

  • Laaidi, M. (2001). Forecasting the start of the pollen season of Poaceae: Evaluation of some methods based on meteorological factors. International Journal of Biometeorology, 45, 1–7.

    Article  CAS  Google Scholar 

  • Mandrioli, P. (1994). Metodica di campionamento e conteggio dei granuli pollinici e delle spore fungine aerodisperse. In Regione Emilia Romagna (Ed.) Il monitoraggio aerobiologico in Emilia Romagna, vol. 30, pp. 9–19.

  • Mandrioli, P., Comtois, P., & Levizzani, V. (1998). Methods in Aerobiology. Bologna: Pitagora Editrice.

    Google Scholar 

  • Menesatti, P., Antonucci, F., Costa, C., Mandalà, C., Battaglia, V., & La Torre, A. (2013b). Multivariate forecasting model to optimize management of grape downy mildew control. Vitis (in press).

  • Menesatti, P., Antonucci, F., Pallottino, F., Giorgi, S., Matere, A., Nocente, F., et al. (2013a). Laboratory versus in-field spectral proximal sensing for early detection of Fusarium head blight infection in durum wheat. Biosystems Engineering, 114, 289–293.

    Article  Google Scholar 

  • Ministero della Salute—Coordinamento Nazionale delle Associazioni dei Malati Cronici (CnAMC). (2011). Cittadinanzattiva, VIII rapporto annuale sulla cronicità.

  • Moreno-Grau, S., Elvira-Rendueles, B., Moreno, J., García-Sánchez, A., Vergara, N., Asturias, J. A., et al. (2006). Correlation between Olea europaea and Parietaria judaica pollen counts and quantification of their major allergens Ole e 1 and Par j 1–Par j 2. Annals of Allergy, Asthma & Immunology, 96, 858–864.

    Article  Google Scholar 

  • Moseholm, L., Weeke, E., & Petersen, B. N. (1987). Forecast of pollen concentration of Poaceae (grasses) in the air by time series analysis. Pollen and Spores, 29, 305–322.

    Google Scholar 

  • Norris-Hill, J. (1995). The modelling of daily Poaceae pollen concentrations. Grana, 34(3), 182–188.

    Article  Google Scholar 

  • Pawankar R., Canonica G. W., Holgate S. T., & Lockey R. F. (2011). White book on allergy 2011–2012: Executive summary. WAO—World Allergy Organization.

  • Ranzi, A., Lauriola, P., Marletto, V., & Zinoni, F. (2003). Forecasting airborne pollen concentrations: Development of local models. Aerobiologia, 19, 39–45.

    Article  Google Scholar 

  • Robertson, G. W. (1983). Weather-based mathematical models for estimating development and ripening of crops. WMOTN 180, pp. 99.

  • Rodrìguez-Rajo, F. J., Jato, V., & Aira, M. J. (2003). Pollen content in the atmosphere of Lugo (NW Spain) with reference to meteorological factors (1999–2001). Aerobiologia, 19, 213–225.

    Article  Google Scholar 

  • Sabariego, S., Pérez-Badia, R., Bouso, V., & Gutiérrez, M. (2011). Poaceae pollen in the atmosphere of Aranjuez, Madrid and Toledo (central Spain). Aerobiologia, 27, 221–228.

    Article  Google Scholar 

  • Sabatier, R., Vivein, M., & Amenta, P. (2003). Two approaches for discriminant partial least squares (14th ed., pp. 100–108). New York: Springer.

    Google Scholar 

  • Silva-Palacios, I., Tormo Molina, R., & Muñoz Rodríguez, A. F. (2000). Influence of wind direction on pollen concentration in the atmosphere. International Journal of Biometeorology, 44, 128–133.

    Article  CAS  Google Scholar 

  • Sjöström, M., Wold, S., & Söderström, B. (1986). PLS Discriminant Plots. North-Holland: Proceedings of PARC in Practice. Elsevier Science Publishers B.V.

    Google Scholar 

  • Skjøth, C. A., Ørby, P. V., Becker, T., Geels, C., Schlunssen, C., Sigsgaard, T., et al. (2013). Identifying urban sources as cause of elevated grass pollen concentrations using GIS and remote sensing. Biogeosciences, 10(541–554), 2013. doi:10.5194/bg-10-541-2013.

    Google Scholar 

  • Smith, M., & Emberlin, J. (2005). Constructing a 7-day ahead forecast model for grass pollen at north London, United Kingdom. Clinical Experimental Allergy, 35(10), 1400–1406.

    Article  CAS  Google Scholar 

  • Smith, M., & Emberlin, J. (2006). A 30-day-ahead forecast model for grass pollen in north London, United Kingdom. International Journal of Biometeorology, 50, 233–242. doi:10.1007/s00484-005-0010-y.

    Article  Google Scholar 

  • Scheifinger, H., Belmonte, J., Celenk, S., Damialis, A., Dechamp, C., Garcia-Mozo, H., Gehrig, R., Grewling, L., Halley, J. M., Hogda, K. A., Jager, S., Karatzas, K., Koch, E., Pauling, A., Peel, R., Sikoparija, B., Smith, M., Galan Sodevilla, C., Vokou, D., de Weger, L. (2012). Monitoring, modelling and forecasting of the pollen season. In M. Sofiev & K. C. Bergmann (Eds.), Allergenic pollen: A review of the production, release, distribution and health impacts (Hardcover). Springer Ed. ISBN 978-94-007-4880-4.

  • Spieksma, F. Th. M., & Nikkels, A. H. (1998). Airborne grass pollen in Leiden, The Netherlands: Annual variations and trends in quantities and season starts over 26 years. Aerobiologia, 14, 347–358.

    Article  Google Scholar 

  • Swierenga, H., de Groot, P. J., de Weijer, A. P., Derksen, M. W. J., & Buydens, L. M. C. (1998). Improvement of PLS model transferability by robust wavelength selection. Chemometrics and Intelligent Laboratory Systems, 41, 237–248.

    Article  CAS  Google Scholar 

  • Torrigiani Malaspina, T., Cecchi, L., Morabito, M., Onorari, M., Domeneghetti, M. P., & Orlandini, S. (2007). Influence of meteorological conditions on male flower phenology of Cupressus sempervirens and correlation with pollen production in florence. Trees—Structure and Function, 21(5), 507–514.

    Article  Google Scholar 

  • Travaglini, A., Albertini, R., & Zieger, E. (2009). Manuale di gestione e qualità della R.I.M.A.®. Bologna. Tipografia LEGO ISBN 978-88-900277-1-0.

  • Tripodi, S., Frediani, T., Lucarelli, S., Macrì, F., Pingitore, G., Di Rienzo Businco, A., et al. (2012). Molecular profiles of IgE to Phleum pratense in children with grass pollen allergy: implications for specific immunotherapy. Journal of Allergy and Clinical Immunology, 129(3), 834–839.

    Article  CAS  Google Scholar 

  • UNI. (2004). Qualità dell’aria—Metodo di campionamento e conteggio dei granuli pollinici e delle spore fungine aerodisperse. UNI, 11008, 2004.

    Google Scholar 

  • Ziello, C., Sparks, T. H., Estrella, N., Belmonte, J., Bergmann, K. C., Bucher, E., et al. (2012). Changes to airborne pollen counts across Europe. PLoS ONE, 7(4), e34076. doi:10.1371/journal.pone.0034076.

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to A. Travaglini.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Brighetti, M.A., Costa, C., Menesatti, P. et al. Multivariate statistical forecasting modeling to predict Poaceae pollen critical concentrations by meteoclimatic data. Aerobiologia 30, 25–33 (2014). https://doi.org/10.1007/s10453-013-9305-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10453-013-9305-3

Keywords

Navigation