Literature DB >> 21736262

The use of aerobiological data on agronomical studies.

Herminia Garcia-Mozo1.   

Abstract

Pollination is only one of the many events comprising the plant development cycle; however, it is extremely important for yield where seed is required. Although successful fertilization depends on a number of environmental and endogenous factors, including climate and plant nutritional status, a sufficient quantity of pollen must reach the receptive stigma in order to enhance fertilization potential. Aerobiological research focuses on the airborne dispersal of biological particles, including pollen grains from anemophilous plants. Airborne pollen data are currently used for various purposes in agricultural research. One major use is as a source of advance information concerning variations in the final fruit harvest of wind-pollinated species. This application, first introduced in the field of plant pathology in the 1940s, was further developed in the 1970s in French studies of vineyard yield; more recently, it has been successfully tested both in crops and in non-crop forest species such as oak or birch. Nowadays, aerobiological research into the influence of pollen emission on final fruit production takes into account a number of other variables, including weather-related factors and phytopathological data; it also uses new, computerized statistical tools to obtain more precise information on agricultural yield and phytopathological risks.

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Year:  2011        PMID: 21736262

Source DB:  PubMed          Journal:  Ann Agric Environ Med        ISSN: 1232-1966            Impact factor:   1.447


  4 in total

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Journal:  Int J Biometeorol       Date:  2015-02-06       Impact factor: 3.787

2.  Year clustering analysis for modelling olive flowering phenology.

Authors:  J Oteros; H García-Mozo; C Hervás-Martínez; C Galán
Journal:  Int J Biometeorol       Date:  2012-08-11       Impact factor: 3.787

3.  Assessment of Quercus flowering trends in NW Spain.

Authors:  V Jato; F J Rodríguez-Rajo; M Fernandez-González; M J Aira
Journal:  Int J Biometeorol       Date:  2014-08-10       Impact factor: 3.787

4.  Modeling pollen time series using seasonal-trend decomposition procedure based on LOESS smoothing.

Authors:  Jesús Rojo; Rosario Rivero; Jorge Romero-Morte; Federico Fernández-González; Rosa Pérez-Badia
Journal:  Int J Biometeorol       Date:  2016-08-04       Impact factor: 3.787

  4 in total

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