Fitting hydro-thermal-time-models to seed germination data
Published at February 10, 2023 · 15 min read
This is a follow-up post. If you are interested in other posts of this series, please go to: https://www.statforbiology.com/tags/drcte/. All these posts exapand on a paper that we have recently published in the Journal ‘Weed Science’; please follow this link to the paper.
Germination assay
This dataset was obtained from previously published work (Mesgaran et al., 2017) with Hordeum spontaneum [C. Koch] Thell. The germination assay was conducted using four replicates of 20 seeds tested at six different water potential levels (0, −0.3, −0.6, −0.9, −1.2 and −1.5 MPa). Osmotic potentials were produced using variable amount of polyethylene glycol (PEG, molecular weight 8000) adjusted for the temperature level. Petri dishes were incubated at six constant temperature levels (8, 12, 16, 20, 24 and 28 °C), under a photoperiod of 12 h. Germinated seeds (radicle protrusion > 3 mm) were counted and removed daily for 20 days.
...Fitting thermal-time-models to seed germination data
Published at February 10, 2023 · 7 min read
This is a follow-up post. If you are interested in other posts of this series, please go to: https://www.statforbiology.com/tags/drcte/. All these posts exapand on a paper that we have recently published in the Journal ‘Weed Science’; please follow this link to the paper.
A motivating examples
In recent times, we wanted to model the effect of temperature on seed germination for Hordeum vulgare and we made an assay with three replicated Petri dishes (50 seeds each) at 9 constant temperature levels (1, 3, 7, 10, 15, 20, 25, 30, 35, 40 °C). Germinated seeds were counted and removed daily for 10 days. This unpublished dataset is available as barley in the drcSeedGerm package, which needs to be installed from github (see below), together with the drcte package for time-to-event model fitting. The following code loads the necessary packages, loads the datasets and shows the first six lines.
Analysing seed germination and emergence data with R (a tutorial). Part 6
Published at January 18, 2022 · 13 min read
This is a follow-up post. If you are interested in other posts of this series, please go to: https://www.statforbiology.com/tags/drcte/. All these posts exapand on a paper that we have recently published in the Journal ‘Weed Science’; please follow this link to the paper.
Fitting time-to-event models with environmental covariates
In the previous post we have shown that time-to-event curves (e.g., germination or emergence curves) can be used to describe the time course of germinations/emergences for a seed lot (this post). We have also seen that the effects of experimental factors on seed germination can be accounted for by coding a different time-to-event curve for each factor level (this post).
...Analysing seed germination and emergence data with R (a tutorial). Part 7
Published at January 18, 2022 · 4 min read
This is a follow-up post. If you are interested in other posts of this series, please go to: https://www.statforbiology.com/tags/drcte/. All these posts expand on a paper that we have recently published in the Journal ‘Weed Science’; please follow this link to the paper.
Exploring the results of a time-to-event fit: model parameters
In the previous post we have shown that time-to-event curves (e.g., germination or emergence curves) can be used to describe the time course of germinations/emergences for a seed lot (this post). We have also seen that the effects of experimental factors on seed germination can be accounted for by coding a different time-to-event curve for each factor level (this post).
...Analysing seed germination and emergence data with R (a tutorial). Part 8
Published at January 18, 2022 · 8 min read
This is a follow-up post. If you are interested in other posts of this series, please go to: https://www.statforbiology.com/tags/drcte/. All these posts expand on a paper that we have recently published in the Journal ‘Weed Science’; please follow this link to the paper.
Predictions from a parametric time-to-event model
In previous posts we have shown that time-to-event models (e.g., germination or emergence models) can be used to describe the time course of germinations/emergences for a seed lot (this post) or for several seed lots, submitted to different experimental treatments (this post). We have seen that fitted models can be used to extract information of biological relevance (this post).
...Analysing seed germination and emergence data with R (a tutorial). Part 9
Published at January 18, 2022 · 10 min read
This is a follow-up post. If you are interested in other posts of this series, please go to: https://www.statforbiology.com/tags/drcte/. All these posts expand on a manuscript that we have recently published in the Journal ‘Weed Science’; please follow this link to the paper. In order to work throughout this post, you need to install the ‘drcte’ and ‘drcSeedGerm’ packages, by using the code provided in this page.
Quantiles from time-to-event models
We have previously shown that time-to-event models (e.g., germination or emergence models) can be used to describe the time course of germinations/emergences for a seed lot (this post) or for several seed lots, submitted to different experimental treatments (this post). We have seen that fitted models can be used to extract information of biological relevance (this post).
...Analysing seed germination and emergence data with R: a tutorial. Part 5
Published at December 23, 2021 · 14 min read
This is a follow-up post. If you are interested in other posts of this series, please go to: https://www.statforbiology.com/tags/drcte/. All these posts exapand on a paper that we have recently published in the Journal ‘Weed Science’; please follow this link to the paper.
Comparing germination/emergence for several seed lots
Very often, seed scientists need to compare the germination behavior of different seed populations, e.g., different plant species, or one single plant species submitted to different temperatures, light conditions, priming treatments and so on. How should such a comparison be performed? For example, if we have submitted several seed samples to different environmental conditions, how do we decide whether the germinative response is affected by those environmental conditions?
...Analysing seed germination and emergence data with R: a tutorial. Part 4
Published at December 6, 2021 · 9 min read
This is a follow-up post. If you are interested in other posts of this series, please go to: https://www.statforbiology.com/tags/drcte/. All these posts exapand on a paper that we have recently published in the Journal ‘Weed Science’; please follow this link to the paper.
Time-to-event models for seed germination/emergence
The individual seeds within a population do not germinate/emerge altogether at the same moment; this is an undisputed fact, resulting from seed-to-seed variability in germination/emergence time. Accordingly, the primary reason why we organise germination assays is to describe the progress to germination for the whole population, by using some appropriate time-to-event model.
...Analysing seed germination and emergence data with R: a tutorial. Part 3
Published at October 19, 2021 · 12 min read
This is a follow-up post. If you are interested in other posts of this series, please go to: https://www.statforbiology.com/tags/drcte/. All these posts exapand on a paper that we have recently published in the Journal ‘Weed Science’; please follow this link to the paper.
Reshaping time-to-event data
The first thing we should consider before working through this tutorial is the structure of germination/emergence data. To our experience, seed scientists are used to storing their datasets in several formats, that may not be immediately usable with the ‘drcte’ and ‘drc’ packages, which this tutorial is built upon. The figure below shows some of the possible formats that I have often encountered in my consulting work.
...Analysing seed germination and emergence data with R (a tutorial). Part 2
Published at October 9, 2021 · 17 min read
This is a follow-up post: if you are interested in other posts of this series, please go to: https://www.statforbiology.com/tags/drcte/. All these posts exapand on a paper that we have recently published in the Journal ‘Weed Science’; please follow this link to the paper.
Survival analysis and germination/emergence data: an overlooked connection
Seed germination and emergence data describe the time until the event of interest occurs and, therefore, they can be put together in the wide group of time-to-event data. You may wonder: what’s the matter with time-to-event data? Do they have anything special that needs our attention? The answer is, definitely, yes!
...Analysing seed germination and emergence data with R (a tutorial). Part 1
Published at October 7, 2021 · 4 min read
Introduction to the tutorial
Germination/emergence assays are relatively easy to perform, by following standardised procedures, as described, e.g., by the International Seed Testing Association (see here ). In short, we take a sample of seeds and we put them in an appropriate container. We put the container in the right environmental conditions (e.g., relating to humidity content and temperature) and we inspect the seeds according to a regular schedule (e.g., daily). At each inspection, we count the number of germinated/emerged seeds and remove them from the containers; inspections are performed until no new germinations/emergences are observed for a sufficient amount of time.
...Published at May 30, 2019 · 1 min read
This blog is supported by a few R packages containing all functions, datasets and other utilities, which are necessary to work through posts, tutorials and books. The packages are:
The three packages ‘drcSeedGerm’, ‘drcte’ and ‘lmDiallel’ are already hosted on CRAN and they can be installed from within RStudio, by using the usual ‘install.package()’ function. For all packages, the development versions are hosted on gitHub and they can be installed from there. To do so, you need the ‘devtools’ package, so, if necessary, install this package first. Next, load this library and use the ‘install_github()’ function to install the three packages. For any problem, please, email me
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