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A note on the analysis of germination data from complex experimental designs

Published online by Cambridge University Press:  18 September 2017

Signe M. Jensen ,
Christian Andreasen ,
Jens C. Streibig ,
Eshagh Keshtkar  and
Christian Ritz
Signe M. Jensen
Affiliation:
Department of Plant and Environmental Sciences, Faculty of Science, University of Copenhagen, Højbakkegård Allé 13, DK-2630 Taastrup, Denmark
Christian Andreasen
Affiliation:
Department of Plant and Environmental Sciences, Faculty of Science, University of Copenhagen, Højbakkegård Allé 13, DK-2630 Taastrup, Denmark
Jens C. Streibig
Affiliation:
Department of Plant and Environmental Sciences, Faculty of Science, University of Copenhagen, Højbakkegård Allé 13, DK-2630 Taastrup, Denmark
Eshagh Keshtkar
Affiliation:
Department of Agronomy, Faculty of Agriculture, Tarbiat Modares University, PO Box 14115-336, Tehran, Iran
Christian Ritz*
Affiliation:
Department of Nutrition, Exercise and Sports, Faculty of Science, University of Copenhagen, Rolighedsvej 26, DK-1958 Frederiksberg C, Denmark
*
*Correspondence Email: ritz@nexs.ku.dk
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Abstract

In recent years germination experiments have become more and more complex. Typically, they are replicated in time as independent runs and at each time point they involve hierarchical, often factorial experimental designs, which are now commonly analysed by means of linear mixed models. However, in order to characterize germination in response to time elapsed, specific event-time models are needed and mixed model extensions of these models are not readily available, neither in theory nor in practice. As a practical workaround we propose a two-step approach that combines and weighs together results from event-time models fitted separately to data from each germination test by means of meta-analytic random effects models. We show that this approach provides a more appropriate appreciation of the sources of variation in hierarchically structured germination experiments as both between- and within-experiment variation may be recovered from the data.

Keywords

between-experiment variationGerbera hybridalog-logistic functionmeta analysismixed modelrandomized complete block designtime-to-event data
Type
Short Communication
Information
Seed Science Research , Volume 27 , Issue 4 , December 2017 , pp. 321 - 327
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Copyright
Copyright © Cambridge University Press 2017 

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