Algorithm for forecasting the total amount of airborne birch pollen from meteorological conditions of previous years

Algorithm for forecasting the total amount of airborne birch pollen from meteorological... Agricultural and Forest Meteorology 249 (2018) 35–43 Contents lists available at ScienceDirect Agricultural and Forest Meteorology journal homepage: www.elsevier.com/locate/agrformet Algorithm for forecasting the total amount of airborne birch pollen from meteorological conditions of previous years a a, b b Yi-Ting Tseng , Shigeto Kawashima , Satoshi Kobayashi , Shinji Takeuchi , Kimihito Nakamura Graduate School of Agriculture, Kyoto University, Kitashirakawa-Oiwakecho, Sakyo-Ku, Kyoto 606-8502 Japan Hokkaido Institute of Public Health, 12 Chome Kita 19 Jonishi, Kita Ward, Sapporo, Hokkaido Prefecture 060-0819 Japan ARTICLE I NFO ABSTRACT Keywords: The birch tree (genus Betula L.) disperses airborne pollen annually from April to June, causing severe symptoms Total airborne pollen in pollinosis sufferers. Because of interannual variations in pollen levels, there is an urgent need to develop a Pollinosis forecasting model with greater precision in order to provide accurate information to patients and medical Birch (Betula L.) personnel regarding airborne pollen levels. We developed an algorithm for forecasting the total amount of Forecast modeling airborne birch pollen. This equation suggested that the total amount of airborne pollen in a given season could Meteorological factors be estimated using only the meteorological data from previous years. In order to discover potential predictive relationships, a data http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Agricultural and Forest Meteorology Elsevier

Algorithm for forecasting the total amount of airborne birch pollen from meteorological conditions of previous years

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Publisher
Elsevier
Copyright
Copyright © 2017 Elsevier B.V.
ISSN
0168-1923
D.O.I.
10.1016/j.agrformet.2017.11.021
Publisher site
See Article on Publisher Site

Abstract

Agricultural and Forest Meteorology 249 (2018) 35–43 Contents lists available at ScienceDirect Agricultural and Forest Meteorology journal homepage: www.elsevier.com/locate/agrformet Algorithm for forecasting the total amount of airborne birch pollen from meteorological conditions of previous years a a, b b Yi-Ting Tseng , Shigeto Kawashima , Satoshi Kobayashi , Shinji Takeuchi , Kimihito Nakamura Graduate School of Agriculture, Kyoto University, Kitashirakawa-Oiwakecho, Sakyo-Ku, Kyoto 606-8502 Japan Hokkaido Institute of Public Health, 12 Chome Kita 19 Jonishi, Kita Ward, Sapporo, Hokkaido Prefecture 060-0819 Japan ARTICLE I NFO ABSTRACT Keywords: The birch tree (genus Betula L.) disperses airborne pollen annually from April to June, causing severe symptoms Total airborne pollen in pollinosis sufferers. Because of interannual variations in pollen levels, there is an urgent need to develop a Pollinosis forecasting model with greater precision in order to provide accurate information to patients and medical Birch (Betula L.) personnel regarding airborne pollen levels. We developed an algorithm for forecasting the total amount of Forecast modeling airborne birch pollen. This equation suggested that the total amount of airborne pollen in a given season could Meteorological factors be estimated using only the meteorological data from previous years. In order to discover potential predictive relationships, a data

Journal

Agricultural and Forest MeteorologyElsevier

Published: Feb 15, 2018

References

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