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      How to analyse seed germination data using statistical time-to-event analysis: non-parametric and semi-parametric methods

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      Seed Science Research
      Cambridge University Press (CUP)

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          Applied Regression Analysis

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            Is Open Access

            How and why to measure the germination process?

            In the last two centuries, papers have been published including measurements of the germination process. High diversity of mathematical expressions has made comparisons between papers and some times the interpretation of results difficult. Thus, in this paper is included a review about measurements of the germination process, with an analysis of the several mathematical expressions included in the specific literature, recovering the history, sense, and limitations of some germination measurements. Among the measurements included in this paper are the germinability, germination time, coefficient of uniformity of germination (CUG), coefficient of variation of the germination time (CVt), germination rate (mean rate, weighted mean rate, coefficient of velocity, germination rate of George, Timson’s index, GV or Czabator’s index; Throneberry and Smith’s method and its adaptations, including Maguire’s rate; ERI or emergence rate index, germination index, and its modifications), uncertainty associated to the distribution of the relative frequency of germination (U), and synchronization index (Z). The limits of the germination measurements were included to make the interpretation and decisions during comparisons easier. Time, rate, homogeneity, and synchrony are aspects that can be measured, informing the dynamics of the germination process. These characteristics are important not only for physiologists and seed technologists, but also for ecologists because it is possible to predict the degree of successful of a species based on the capacity of their harvest seed to spread the germination through time, permitting the recruitment in the environment of some part of the seedlings formed.
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              Statistical Methods for Survival Data Analysis

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                Author and article information

                Journal
                applab
                Seed Science Research
                Seed Sci. Res.
                Cambridge University Press (CUP)
                0960-2585
                1475-2735
                June 2012
                February 7 2012
                June 2012
                : 22
                : 02
                : 77-95
                Article
                10.1017/S0960258511000547
                9a4b5d94-b0a6-4e53-855b-fa9ac59d1c98
                © 2012
                History

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