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Comparison of three different statistical approaches (non-linear least-squares regression, survival analysis and Bayesian inference) in their usefulness for estimating hydrothermal time models of seed germination

Published online by Cambridge University Press:  01 May 2020

Elena Moltchanova Open the ORCID record for Elena Moltchanova [Opens in a new window] ,
Shirin Sharifiamina ,
Derrick J. Moot ,
Ali Shayanfar  and
Mark Bloomberg
Elena Moltchanova*
Affiliation:
School of Mathematics and Statistics, University of Canterbury, Christchurch, New Zealand
Shirin Sharifiamina
Affiliation:
Field Research Centre, Lincoln University, Canterbury, New Zealand
Derrick J. Moot
Affiliation:
Field Research Centre, Lincoln University, Canterbury, New Zealand
Ali Shayanfar
Affiliation:
Seed and Plant Certification and Registration Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran
Mark Bloomberg
Affiliation:
Kura Ngahere - New Zealand School of Forestry, University of Canterbury, Christchurch, New Zealand
*
Correspondence: Elena Moltchanova, E-mail: [email protected]
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Abstract

Hydrothermal time (HTT) models describe the time course of seed germination for a population of seeds under specific temperature and water potential conditions. The parameters of the HTT model are usually estimated using either a linear regression, non-linear least squares estimation or a generalized linear regression model. There are problems with these approaches, including loss of information, and censoring and lack of independence in the germination data. Model estimation may require optimization, and this can have a heavy computational burden. Here, we compare non-linear regression with survival and Bayesian methods, to estimate HTT models for germination of two clover species. All three methods estimated similar HTT model parameters with similar root mean squared errors. However, the Bayesian approach allowed (1) efficient estimation of model parameters without the need for computation-intensive methods and (2) easy comparison of HTT parameters for the two clover species. HTT models that accounted for a species effect were superior to those that did not. Inspection of credibility intervals and estimated posterior distributions for the Bayesian HTT model shows that it is credible that most HTT model parameters were different for the two clover species, and these differences were consistent with known biological differences between species in their germination behaviour.

Keywords

Bayesian inferencehydrothermal time model (HTT)seed germinationsubterranean clover (Trifolium subterraneum L.)survival analysiswhite clover (Trifolium repens L.)
Type
Technical Update
Information
Seed Science Research , Volume 30 , Issue 1 , March 2020 , pp. 64 - 72
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Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

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