Draft - tspace.library.utoronto.ca · However, Michalak et al. (2015b) reported that seeds of this 83 species could tolerate cryopreservation at higher WC (ca. 20%) with seedling

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Cryopreservation of Prunus padus L. seeds: emphasising

the significance of Bayesian methods for data analysis

Journal: Canadian Journal of Forest Research

Manuscript ID cjfr-2016-0020.R1

Manuscript Type: Article

Date Submitted by the Author: 20-Mar-2016

Complete List of Authors: Popova, Elena; University of Guelph, Department of Plant Agriculture Moltchanova, Elena; University of Canterbury, 2 School of Mathematics and Statistics Han, Sim Hee; Korea Forest Research Institute, Division of Forest Genetic Resources Saxena, Praveen; University of Guelph, Plant Agriculture

Kim, Du Hyun; DongA University, Department of Genetic Engineering

Keyword: cryopreservation, Prunus padus, hydration window, Bayesian statistics, seed cryopreservation

https://mc06.manuscriptcentral.com/cjfr-pubs

Canadian Journal of Forest Research

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Cryopreservation of Prunus padus L. seeds: emphasising the significance 1

of Bayesian methods for data analysis 2

3

Elena Popova1, Elena Moltchanova

2 , Sim Hee Han

3, Praveen Saxena

1, Du Hyun Kim

4* 4

1 Gosling Research Institute for Plant Preservation (GRIPP), Department of Plant Agriculture, 5

University of Guelph, Guelph N1G 2W1, Ontario, Canada 6

2 School of Mathematics and Statistics, University of Canterbury, Christchurch 8041, New 7

Zealand 8

3 Department of Forest Genetic Resources, National Institute of Forest Science, Suwon 16631, 9

Republic of Korea. 10

4 Department of Life Resources Industry, Dong-A University, Busan 49315, Republic of 11

Korea 12

* Corresponding author. E-mail: [email protected] 13

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Abstract 14

Conservation of Prunus padus L., a tree of high ecological and pharmacological importance, has been 15

evaluated by storing seeds at subzero (-20°C, -80°C) and cryogenic (-196°C) temperatures for various 16

durations. The effect of seeds water content (WC) ranging from 3.5 to 21.1%, fresh weight basis, as 17

well as the effect of cooling and rewarming procedure on seed viability was investigated. Emergence 18

of seedlings was observed for 40-55% non-cryopreserved seeds with no significant effect of WC. 19

The same seedling emergence was recorded for seeds cryopreserved by direct immersion in liquid 20

nitrogen within the WC range between 3.5 and 15.0%. Seeds rehydrated above 17% WC were unable 21

to tolerate cryopreservation. Seedling emergence was not affected by cooling regime but decreased by 22

10% after step-wise rewarming compared to rapid rewarming in a water bath or on air. No reduction 23

in seedling emergence was recorded after storage at -20°C, -80°C and -196°C for 1h, 1 week and 1 24

month. We recommend seed storage at subzero or cryogenic temperatures as an effective conservation 25

option for P. padus and possibly other Prunus species. We also demonstrated high effectiveness and 26

reliability of Bayesian statistical methods for analyzing binomial data, such as the data obtained in 27

seed conservation experiments. 28

29

Keywords: Bayesian statistics, hydration window, Prunus padus, seed cryopreservation, water 30

content. 31

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Introduction 32

Rapid increase in human populations in the past decades accompanied by dramatic ecological changes 33

has been the cause of enormous worldwide depletion of plant biodiversity (Wang et al. 2014). Ex situ 34

conservation of orthodox seeds dried to 3–7 % water content (WC) at low temperature (-18 to -22°C) 35

is one of the most effective means of preserving diverse plant species (Pritchard and Nadarajan 2008). 36

However, recent studies have shown that sub-orthodox, or short-lived, seeds can age quicker in seed 37

banks than predicted from seed viability equations (Pritchard and Dickie 2003). Abnormal storage 38

behavior and high variations in desiccation tolerance has been recorded for large seeds with stone-like 39

endocarp and high lipid content such as in the genus Prunus (Chmielarz 2009b; Michalak et al. 40

2015b). 41

Prunus padus, or bird cherry, is considered ecologically important in Europe and Western and 42

Central Asia as it provides an early source of nectar and pollen for bees, while the cherries are eaten 43

by birds and mammals (Uusitalo 2004). Mature trees are valued for their attractive scented flowers 44

and dark-colored bark and are often planted for ornamental purpose. The plant is a potential source of 45

amygdalin, a cyanogenic diglucoside with a strong anticancer activity (Frank and Santamour 1998). In 46

contrast to the majority of cultivated Prunus genotypes, the need for conserving wild Prunus species 47

has been often neglected, while the loss of genetic diversity within these species continues to diminish 48

the genetic base on which breeding programmes depend (Vujović et al. 2015). In nature, seeds of 49

wild Prunus species remain viable for at least two years. However, recent studies recorded a marked 50

decline in viability from 79 % of one-year-old seeds to 27 % of two-year old seeds which caused their 51

erosion from soil seed banks (Flagstad et al. 2010). Therefore several researchers advocated the 52

necessity of conserving Prunus genetic material in ex situ genetic banks (Towill and Forsline 1999; 53

De Boucaud et al. 2002; Chmielarz 2009b; Cheong 2012; Michalak et al. 2015b; Vujović et al. 2015). 54

The research on ex situ storage behaviour of P. padus seeds and their longevity at different 55

storage regimes is fragmented. In Seed Information Database (SID 2015) of the Royal Botanic 56

Gardens, Kew the bird cherry seeds are referred to as orthodox. Gordon and Rowe (1982) 57

recommended 3°-5°C and 12 % water content (WC, fresh weight basis) as the conditions for their 58

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medium-term storage. Seeds of a related species Prunus avium (mazzard cherry) tolerated drying to 9-59

11 % WC followed by 3 years of storage at -1 to 3°C without a considerable loss of viability (Suszka 60

et al. 1996). However, storage behavior of Prunus padus seeds and their tolerance to subzero and 61

cryogenic temperatures have not been investigated. 62

Cryopreservation in liquid nitrogen (LN, -196°C) or its vapour phase (-160 ‒ -180°C) is an 63

alternative and potentially very effective method for the long-term storage of biological samples of 64

plant origin (Wang et al. 2014). At cryogenic temperatures, nearly all cell division and metabolic 65

activities of cells are arrested and the plant materials remain viable for much longer durations than at 66

any other storage regime (Walters et al. 2004). Consequently, cryopreservation may be of particular 67

importance for the long-term (10-100s years) storage of otherwise inherently short-lived orthodox 68

seeds and seeds with high lipid content (Pritchard and Nadarajan 2008; Popova et al. 2013; Michalak 69

et al. 2013). During the past decade, cryopreservation has been successfully tested for seeds of 70

important trees such as silver birch (Ryynänen and Aronen 2005; Chmielarz 2010a), ash (Chmielarz 71

2009a), elms (Harvengt et al. 2004; Chmielarz 2010b), European chestnut and cork oak (Vidal et al. 72

2010), willows and poplars (Popova et al. 2012; 2013; Michalak et al. 2013; 2015a), and others (see 73

Häggman et al. 2008 for a review). However, the possibility of cryogenic storage of P. padus seeds 74

remains to be evaluated. . 75

The key to successful cryopreservation of seeds is identification of the “hydration window”, 76

i.e. the safe range of water content at which seeds can be exposed to cryogenic temperatures without 77

decreasing their viability (Daws and Pritchard 2008). For Prunus species information on hydration 78

window for seed cryopreservation is scarce and often controversial. For example, seeds of Prunus 79

avium showed ca. 25% seedling emergence only if cryopreserved within a safe WC range of 9-16.9 % 80

(Chmielarz 2009b). Cryopreservation of seeds hydrated to WC above this level resulted in complete 81

loose of germination (Chmielarz 2009b). However, Michalak et al. (2015b) reported that seeds of this 82

species could tolerate cryopreservation at higher WC (ca. 20%) with seedling emergence of 47 to 83

57%, depending on seed provenance. By contrast, desiccation of seeds to WC ranging from 7.6 to 84

10.9% significantly reduced seedling emergence in both control and cryopreserved seeds (Michalak et 85

al. 2015b). In addition, the regimes of cooling and rewarming may significantly affect viability of 86

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lipid-rich seeds after cryopreservation (Dussert and Engelmann 2006). In this study we investigated 87

various temperature regimes and duration of storage to recommend efficient options for conservation 88

of P. padus seeds. The also determined, for the first time, the safe seed WC range and the effect of 89

different regimes of cooling and rewarming oncryopreservation of P. padus seeds and subsequent 90

seedling development. 91

Development of effective conservation programmes is commonly based on quantitative data 92

from scientific experiments and/or observations. Thus, the statistical methods of data analysis have a 93

significant impact on the decision making in developing conservation strategies, particularly when the 94

decisions are made under conditions of uncertainty, lack of observations or unknown interactions 95

between various factors (Ellison 1996; Marin et al. 2003; Muthusamy et al. 2005). Application of 96

Bayesian statistical methods for analysing data from biological experiments is increasing (Olge and 97

Barber 2008) due to their flexibility and success in resolving problems associated with classical 98

arcsine transformation required by ANOVA. Such problems include significant loss of information, 99

lack of interpretability and failure to guarantee normality and homoscedasticity (Warton and Hui 100

2011). In this communication we demonstrate successful application of Bayesian statistical methods 101

in the analysis of data from experiments in seed conservation research using Prunus padus as a model 102

species. 103

104

Materials and Methods 105

Conservation of Prunus padus seeds 106

Plant material 107

Mature seeds of Prunus padus L. were collected mid-September, 2011 from eight open-pollinated 108

trees of the same population in Chungcheongbuk-do province, Republic of Korea. Collected seed 109

were soaked in tap water to soften fruits. After fruits were removed and floating seeds and pulp 110

fragments were discarded, clean seeds were air-dried at room temperature in darkness. Dry seeds 111

with ca. 12 % WC were mixed together, packed in a plastic container and stored in the refrigerator at 5 112

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± 1°C for two months before the experiments. All experiments and water content measurements were 113

performed on seeds with the endocarp. 114

Water content of seeds 115

To determine the water content, 30 seeds were placed in pre-weighted open aluminum containers and 116

dried for 48 h in an oven at 105°C to a constant weight (Daws and Pritchard 2008; Chmielarz 2009b). 117

Water content was evaluated as the average of three independent replications and expressed on fresh 118

weight basis (% FW). 119

120

Hydration window for cryopreservation 121

Experiments were performed to determine the “hydration window”, i.e. the safe range of water 122

content, for P. padus seed storage at -196°C. At the first step, model desiccation and hydration curves 123

were plotted following desiccation or hydration of seeds to WC ranging from 3.5 to 21.1 % FW. For 124

desiccation, 120 seeds were placed on a mesh over 50 g of activated silica gel inside plastic containers 125

(110 x 110 x 35 mm) which were then sealed and kept at 20 °C. For hydration, 120 seeds were 126

dispersed on a mesh placed over 90 ml of distilled water in sealed containers of the same size and kept 127

at 20°C. Water content was monitored during desiccation and hydration by collecting the samples 128

after 2, 5, 8, 17, 24 and 48 h of desiccation and 1.5, 3, 5, 8, 17, 24, 48 and 72 h of hydration following 129

the method described above. The resulting model curves (Fig. 1) were used to predict desiccation or 130

hydration time required to achieve targeted WC for cryopreservation studies. 131

To determine hydration windows for cryopreservation, seeds were desiccated or hydrated to 132

targeted WC (Fig. 2), sealed in 5 ml cryo-tubes (Nunc, USA), which were attached to an aluminum 133

holder and immersed into LN directly. After 1 week of storage in LN, ampules were rewarmed in a 134

water bath at 37°C for 15 min. Four ampoules each containing 25 seeds (100 seeds in total) were used 135

for each WC treatment. Unfrozen seeds desiccated or hydrated to the same WC served as a control. 136

Stratification, germination and data collection were performed as described below. 137

138

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Effect of cryopreservation protocol 139

Untreated seeds of P. padus had 12.7 % WC which was within a safe range of WC for 140

cryopreservation based on the results of previous experiments. Therefore these seeds were used in the 141

second series of experiments to investigate the effect of cooling and rewarming procedures on 142

seedling emergence after cryopreservation. Seeds were sealed in 5 ml cryo-tube (Nunc, USA) which 143

was attached to aluminum holder and exposed, directly or step-wise, to liquid nitrogen (see Table for 144

the description of protocols). After one month of LN storage, seeds were rewarmed using different 145

regimes: slowly at ambient temperature (22 ± 1°C), step-wise at -80°C and -20°C, or rapidly in a 146

water bath at 37°C for various durations (Table1). Four ampoules each containing 25 seeds (100 seeds 147

in total) were used for each treatment. Untreated seeds were used as a control. Stratification, 148

germination and data collection were performed as described below. 149

Storage duration at different temperatures 150

The effect of storage duration on seedling emergence was studied for freshly collected P. padus seeds 151

(12.7 % WC) stored at -20°C, -80°C and -196°C for 1 h, 1 week and 1 month (Table 1). For each 152

combination of temperature and storage duration, four ampoules, each containing 25 seeds (100 seeds 153

in total) were treated. 154

Stratification, germination and data collection 155

Stratification and germination of P. padus seeds were performed according to Suszka (1967). Seeds 156

were stratified in the moist quartz sand fraction < 1 mm in 250 ml plastic bottles at 5°C in darkness 157

for 8 weeks. Stratified seeds were germinated on the top of double-layered filter paper moisturized 158

with distilled water in 9 cm Petri dishes at 20 ± 1°C under fluorescent light (16 h light/8 h dark). After 159

45 days, seeds that developed both shoots and roots were counted to assess “seedling emergence”, 160

which was expressed as percentage out of the total number of seeds sown for each treatment. In 161

addition, viability of control (non-cryopreserved) seeds at 12.7 % WC was tested by staining with 1 % 162

solution of 2,3,5-triphenyltetrazolium chloride (TTC) according to International Seed Testing 163

Association (ISTA, 1999). 164

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165

Statistical analysis 166

Bayesian Methods 167

Bayesian methods were followed to analyse the data obtained in cryopreservation studies. These 168

methods are different from the classical statistics, in which the data are assumed to result from an 169

experiment infinitely repeatable under unchanging conditions. The observed frequencies may thus 170

serve to estimate the unknown theoretical parameters – therefore, this methodology is often called 171

frequentist. In the Bayesian framework, a datum is supposed to result from a unique experiment, and 172

the unknown parameter is viewed as a realisation from an unobserved distribution, which is the object 173

of our inference. For example, in our study, the parameter of interest is the proportion of seeds 174

expected to develop seedlings under certain conditions. Bayesian inference is a process of updating 175

prior information about the parameter of interest θ with the observed data y to produce a posterior 176

distribution p(θ|y). The inference about θ can be made from this distribution in terms of estimated 177

posterior means and standard deviations, credible intervals (a Bayesian counterpart to confidence 178

intervals) and the Bayesian P-values. The latter refer to the probability that some statement of interest 179

is true given the observed data. This is in contrast to the classical p-value, which is the probability of 180

erroneously rejecting the null hypothesis. Therefore, Bayesian P-values are close to one, when the 181

statement is well supported by the data (see Ellison 1996 and Marin et al. 2003 for details). 182

Model comparison can be performed using the Deviance Information Criterion (DIC) 183

(Spiegelhalter 2002), which is a Bayesian measure of model fit, similar to classical AIC and BIC (see, 184

e.g., Hastie et al. 2009). The smaller DIC corresponds to a better model. DIC in a range from 5 to 10 185

can be considered substantial, while a difference of over 10 would definitely rules out the model with 186

the higher DIC. 187

One can also perform Bayesian ANOVA, i.e. estimation and comparison of variance 188

components via plots of credible intervals as suggested by Gelman (2005) and demonstrated by Qian 189

and Shen (2007) using several examples. In this approach the aim would be to assess estimated 190

standard deviations of the effects being sufficiently different from zero. 191

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Finally, Bayes Factors (BFs), which can sometimes be interpreted as the odds in favour of the 192

null hypothesis against the alternative hypothesis, that are given by the data can also be used for 193

testing the hypothesis (Lee 1997). 194

Bayesian model estimation is often not analytically feasible and is therefore normally 195

performed via numerical simulations. We used WinBUGS software (Lunn et al. 2000) and an R-196

package R2WinBUGS (R Core Team 2014) for graphing and posterior data analysis and simulation 197

chains of length 45000, thinned to 5000, after 5000 burn-in for determining the inference. 198

Convergence was assessed visually. 199

Binomial logistic regression 200

We used binomial logistic regression, a standard tool for analysing a response variable, which 201

represents a number of successes in a set of identical trials. Mathematically, the model can be 202

specified as follows. 203

In the equations below denotes the number of seeds that showed seedling emergence out 204

of taken for treatment and water content level . Then is binomially 205

distributed with some treatment- and WC-specific probability of seedling emergence : 206

(1)

The probability can then be modelled via logistic regression parametrised as follows: 207

(2)

where is the global mean log-odds, is the expected effect of treatment i, is the expected 208

effect of WC level , and is the effect of interaction between the treatment and the WC level. Since 209

we have only two different treatments, other obvious parametrisations are possible. 210

Note, that in order to test for the non-negligible interaction effect, one could fit the model 211

with it and without it and report the difference in the associated DIC values: . 212

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To complete the Bayesian model, we need to specify the prior distributions for the parameter 213

vectors , and . Since we do not have any particular information on them, a common solution is 214

to specify the so-called vague or uninformative Gaussian priors: 215

(3)

(4)

(5)

where and The WinBUGS code can be found in the Supplement A1. 216

It is noteworthy, that beta-prior can be used directly instead of (2-5) if separating the effects 217

of treatment and WC need not be analysed: 218

(6)

where and are hyperprior parameters, which we have set to resulting in uniform prior 219

distribution between 0 and 1 for . The code for this model formulation can be found in the 220

Supplement A2. 221

The two models: (1-5) and (1,6) provide alternative prior formulations for the same parameter 222

matrix and their results are interesting to compare for the purposes of sensitivity analysis, i.e. to 223

ensure that prior formulation does not affect posterior inference. 224

Credible intervals for water contents 225

The water contents, which can be considered an actual proportion observation (rather than a summary 226

of binomial trial as above), can be transformed via the logit transformation: 227

228

and can then be modelled using Gaussian distribution with standard vague priors for the parameters 229

and : 230

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(7)

231

where is the observation made after hours. 232

(8)

(9)

The () refers to the gamma distribution, and the implementation of model (7-9) in WinBUGS is 233

shown in Supplement A3. The means and 95 % credible intervals are then backtransformed using the 234

expit function (inverse of logit). 235

Results 236

Hydration Window for cryopreservation 237

Water content of Prunus padus seeds before the experiments was 12.7 %. Controlled 238

desiccation and hydration of seeds is a common approach which allows investigation of the effect of 239

seed WC on their longevity under different storage regimes ( Kim et al. 2008; Chmielarz 2010a). In 240

the present study, manipulations with WC allowed the construction of model desiccation and 241

hydration curves for P. padus seeds covering the WC from 3.1 to 22.8 % (Fig. 1). Within the first 24 h 242

over silica gel, seed WC dropped from 12.7 to nearly 5 % followed by gradual decrease to 3 % during 243

the next 24 h. Seeds could be hydrated to 17 % WC within 17 h and to 21 % within 72 h. Based on the 244

model curves presented in Figure 1, seeds were desiccated or hydrated to target WC (Fig. 2, X axis) 245

and cryopreserved in liquid nitrogen to determine the safe hydration window for their cryogenic 246

storage. Fig. 2 shows seedling emergence of control and cryopreserved seeds at different WC and the 247

associated 95 % credible intervals. Seedling emergence of control (non-cryopreserved) seeds varied 248

from 40 to 55 % with no evidence for WC having an effect on the probability of seedling emergence 249

( ). By contrast, there was a significant difference between seeds 250

cryopreserved at WC below 15 % and above 17.2 % ( ) with the 251

seedling emergence decreasing from an average of 47 % to 0.6 %, respectively (P>0.9999). In this 252

study seedling emergence of non-cryopreserved seeds was relatively low, therefore the safe hydration 253

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window was defined as a range of WC which allowed seeds to tolerate cryogenic temperatures and 254

ensured at least 40 % seedling emergence (expected probability of seedling emergence E(p|data) > 0.4 255

as indicated in Figure 2 by the horizontal dotted line). As Fig. 2 shows, all tested levels of WC 256

ensured germination of control seeds while only the range between 3.5 to 15% WC was safe for seed 257

cryopreservation. 258

It would also be pertinent to know the level of certainty with which at least 40 % seedling 259

development from the seeds can be predicted under each regime. In Bayesian framework, this 260

question can be answered easily by evaluating the posterior probability 261

. 262

The results expressed as Bayesian P-values are shown in the upper panel of Figure 2. The dotted 263

horizontal line corresponds to the posterior probability of 0.95. 264

265

Effect of cryopreservation protocol 266

As shown in Fig. 3, the cooling regime had no influence on seedling emergence of cryopreserved 267

seeds ( ). By contrast, the effect of rewarming method on seedling emergence was 268

highly significant ( ). The lowest seedling emergence of 30 % was recorded for seeds 269

subjected to stepwise cooling and cryopreservation followed by stepwise rewarming at -80°C and -20 270

°C (protocol 10 in the Table). Seeds that have been rewarmed rapidly showed 49-51 % seedling 271

emergence regardless of the cooling procedure (protocols 2 to 5 in Table 1). Interestingly, there was 272

no difference in seedling emergence after rewarming on air (22 ± 1 °C) or rapidly in a water bath at 273

37°C for various durations (Fig. 3). 274

Effect of storage temperatures and duration 275

There was no evidence of the effect of storage temperature (-20 °C, -80 °C or -196°C) and storage 276

duration (1h, 1 week or 1 month) on seedling emergence of P. padus seeds ( , Fig. 4). 277

Average seedling emergence varied from 47 to 55 % regardless of storage conditions. 278

279

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Discussion 280

Conservation of Prunus genetic diversity has been addressed by applying both in situ and ex situ 281

conservation programmes (Cheong 2012). Ex situ conservation methods included tree cultivation in 282

orchards, seed banks, storage of vegetative organs at low temperature and cryopreservation (Niino et 283

al. 1997; De Boucaud et al. 2002; Michalak et al. 2015b). Among available options of ex situ 284

conservation, seed banking is the most practical due to ease of application and the amount of diversity 285

which can be conserved using limited space (Pritchard and Nadarajan 2008). Prunus seeds can also 286

serve a convenient model to study storage behavior of large-sized seeds with high lipid and protein 287

content (SID 2015). In this study we accomplished cryopreservation of Prunus padus seeds and 288

applied the Bayesian statistical methods to evaluate the influence of various parameters such as seed 289

water content, cooling and rewarming method, short- and middle-term storage duration and storage 290

temperature on seedling emergence in order to develop methodology for ex situ conservation for this 291

species. 292

It has been previously shown that seed viability after treatment may be significantly 293

overestimated if the decision is based on germination test only (Popova et al. 2013; Michalak et al. 294

2015). Therefore, in this study, seedling emergence, i.e. the ability of seeds to produce healthy 295

seedlings with well-developed shoots and roots, was used as the main parameter for evaluation of 296

treatment impact. 297

In the present study, control (non-cryopreserved) seeds of Prunus padus at 12.7 % WC 298

showed seedling emergence of 43 % (Fig. 2), which was lower than 60.4 % viability determined by 299

the TTC test (data not shown). By contrast, higher seed germination (75 - 98 %) was reported for P. 300

arabica, P. andersonii, P. campanulata, P. domestica and P. mexicana (SID 2015). Michalak et al. 301

(2015) suggested that low seed germination observed for some Prunus species may result from pre-302

drying of seeds. Thus, germination was relatively low (44-59 %) for seeds of Prunus avium pre-dried 303

to ca. 13 % WC (Chmielarz 2009b) while freshly collected seeds of the same species at ca. 20 % WC 304

showed 76 and 86 % germination, depending on provenance (Michalak et al. 2015). This suggestion 305

was supported by another study, where germination of Prunus avium seeds decreased from 93 % to 306

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39-43 % when fresh seeds were dried for 3-5 days (Suszka 1962, cited by Michalak et al. 2015). It is 307

possible that low percentage of seedling emergence observed in our study was caused by drying the 308

seeds prior to the experiments. However, this suggestion does not correspond to the observation that 309

seeds of P. padus are desiccation tolerant (see below). Since the germination tests for the above-310

mentioned species were performed under similar conditions, these differences in germination ability 311

can be attributed to inner dormancy or other yet unknown mechanism in P. padus seeds. 312

According to the Royal Botanic Gardens Kew Seed Information Database (SID 2015), mature 313

seeds of Prunus padus are orthodox. This means that seeds withstand dehydration to around 5 % FW, 314

and their longevity increases with reducing seed WC and storage temperature in a mathematically 315

predictable and quantifiable way (Berjak and Pammenter 2004). Indeed, in our study seeds of P. 316

padus tolerated severe desiccation to 3.5 % WC without a reduction in viability. These results are 317

consistent with high dehydration tolerance reported earlier for mazzard cherry (Jensen and Eriksen 318

2001; Chmielarz 2009b) and other Prunus species (SID 2015). By contrast, seeds of Prunus avium 319

collected from two provenances showed noticeable decrease in seedling emergence when desiccated 320

to WC below 11 %, and were considered suborthodox (Michalak et al. 2015b). 321

For many trees such as of genus Citrus (Hor et al. 2005), Fraxinus (Chmielarz 2009a), Salix 322

(Popova et al. 2012; 2013), and Populus (Popova et al. 2013) the ability of seeds to germinate after 323

exposure to LN can be retained only within a short range of WC. In our study, seeds of Prunus padus 324

could be safely cryopreserved if their WC was below 15 %, The lower limit of WC remained unclear 325

as seeds were not desiccated to WC below 3.5 %. %. Yet, the hydration window of 3.5 – 15 % 326

determined for P. padus seeds is wider than that for oily and/or suborthodox seeds of other tree 327

species. For example, hydration window for cryopreservation was 9.0 - 16.9 % WC of Prunus avium 328

seeds (Chmielarz 2009b), 9.9 – 14.5 % for Populus nigra seeds (Michalak et al. 2015a), 9.1 – 14.5 % 329

for seeds of Salix gracilistyla (Popova et al. 2013) and 12.3 – 23.7 % for seeds of Salix hallaisanensis 330

(Popova et al. 2013). Oily seeds of Corylus avellana that were considered orthodox could only 331

tolerate cryopreservation at 7.4 – 9.1 % WC, and their germination and seedling emergence were still 332

lower than those of control seeds (Michalak et al. 2013). Not only the hydration window is species-333

dependent, it may be also affected by seed provenance and initial viability. For example, seeds of 334

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three clones of Salix caprea showed very different hydration windows: 4.8 – 21.9 %, 9.1 – 19.4 % and 335

16.7 – 27.0 % for seed lots with high, intermediate and low initial germination, respectively (Popova 336

et al. 2012). For both orthodox and intermediate seeds, it is important to determine their “high 337

moisture freezing limit” (HMFL). When seeds are cryopreserved above their HMFL, ice crystal 338

formation leads to cell damage and death (Pritchard and Nadarajan 2008). For seeds of P. padus, 339

HMFL was 15 % WC, as indicated by sharp decrease in seed viability above this point (Fig. 2). By 340

contrast, for seeds of some other species the upper limit was as high as 19-21 %, and even 27 % 341

(Popova et al. 2012; 2013). Michalak et al. (2015b) reported that seeds of Prunus avium could tolerate 342

cryopreservation by direct immersion in LN at 19.7 and 20.2 % WC. High seed tolerance for LN at 343

high WC was also observed for intermediate seeds of some coffee species (Dussert et al. 2001). These 344

differences in response to LN exposure at high WC species may be attributed to lipid composition in 345

seeds and the amount of unfrozen water (Dussert et al. 2001; Michalak et al. 2015b). However, further 346

studies are required to understand the mechanisms underlying the response of suborthodox seeds to 347

ultra-low temperatures. In the present study, the precision of critical WC determination between 15 348

and 17 % for P. padus seeds (Fig. 2) may raise concern, however, the situation is still better than that 349

for recalcitrant seeds where critical water content cannot be unequivocally determined due to high 350

variability of desiccation and storage responses within a species (Berjack and Pammenter 2004). 351

Using seeds within the safe range of WC is a necessary but not a sufficient prerequisite to 352

ensure seed germination after cryogenic storage. Other factors such as the regimes of cooling and 353

rewarming are particularly important for successful cryopreservation of some species (Dussert and 354

Engelmann 2006). Thus, among seeds of 103 plant species native to Russian Far East tested for 355

cryogenic storage, cryopreservation by direct immersion in LN reduced germination of 11 species 356

(Kholina and Voronkova 2008). Seeds of three of them (Cardamine impatiens, Plantago lanceolata 357

and Salicornia europaea) are known to be rich in lipids, triglycerides and fatty acids (Kholina and 358

Voronkova 2008). Another example includes seeds of mazzard cherry cryopreserved by direct 359

immersion in LN: even within the safe range of WC cryopreserved seeds showed reduced viability 360

and developed less seedlings compared to unfrozen seeds (Chmielarz 2009b). In the present study, 361

cooling regime did not produce significant effect on seedling emergence after cryopreservation. The 362

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effect of rewarming conditions was also insignificant, except for the protocol 10, where both cooling 363

and rewarming were performed step-wise at -80°C and -20°C. Interestingly, if step-wise precooled 364

seeds were rewarmed rapidly at 37°C, their post-cryostorage seedling emergence was not affected 365

(Fig. 3). In all experiments, plantlets developed from cryopreserved seeds appeared normal and their 366

morphology was the same as that of seeds from non-frozen seeds. 367

Since the information on storage behavior and cryopreservation of Prunus padus seeds is not 368

available, observations on other species may reveal a useful comparison. Slow rewarming decreased 369

emergence of seedling from coffee seeds cryopreserved either by direct immersion into LN or 370

precooled at -75°C (Dusset and Engelmann 2006), which is in agreement with our results. Seeds with 371

higher lipid content have been found to be more sensitive to cryogenic exposure (Pence 1991). Such 372

sensitivity may be associated with phase transitions/crystallization of lipids during the cooling-373

rewarming cycles (Pritchard and Nadarajan 2008). Lipid crystallization events normally occur during 374

cooling at onset temperatures ranging from +16°C to -59°C. Some authors suggested that lipid 375

composition is of primary significance for seed tolerance to dehydration and cooling (Crane et al. 376

2003; Hor et al. 2005; Kim et al. 2008). For instance, Crane et al. (2003) found that low viability of 377

seeds of some Cuphea species after storage at -18°C can be the result of phase transition in specific 378

groups of lipids. Hor et al. (2005) analysed storage behaviour of seeds of four Citrus, seven Coffee, 379

two Quercus, and one each of Azadirachta indica, pea and soybean species based on open literature 380

sources and found a prominent negative relationship between the amount of lipid content and 381

unfrozen water, which affected the ability of seeds to recover after cryopreservation. Earlier Dussert 382

et al. (2001) found no direct relationship between lipid content of coffee seeds and their survival after 383

LN exposure. However, there was a significant correlation between the percentage of seedling 384

emergence and the content of unsaturated fatty acids in the seeds (Dussert et al. 2001). 385

During cooling, time is often insufficient for the accumulation of ice-induced damage in seeds 386

while rewarming at low rate may give the ice crystals time to grow. During rewarming, the 387

temperature range between -130°C and -20°C seems to be particularly important as re-crystallization 388

and conformational changes in lipids are most likely to occur at these temperatures (Crane et al. 2003; 389

Walters et al. 2004). This idea is supported by the results of the experiments with Coffee seeds: 5 min 390

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exposure at -80°C had no effect on seed viability while maintaining seeds at this temperature for one 391

week caused complete loss of survival (Dussert and Engelmann 2006). In our study, however, seeds 392

of P. padus could be stored at -80°C for at least one month without a decline in their seedling 393

emergence ability (Fig. 4). A moderate detrimental effect of step-wise rewarming was only visible 394

with seeds cryopreserved in LN at -196°C and was probably caused by pere-crystallization events or 395

conformational changes in specific lipid groups provoked by cryogenic cooling (Walters et al. 2004). 396

For seeds of many plant species, cryoconservation at -196°C provides higher longevity and 397

thus has been considered more secure than storage at -20°C or -80°C. For example, seeds of silver 398

birch (Betula pendula) showed higher germination when stored for 3 years at -196°C compared to the 399

same seed lot stored at -3°C (Chmielarz 2010a). Seeds of some 400

American coniferous and deciduous trees fully retained their germination ability after being dried and 401

stored in LN for 3 years (Barbour and Parresol 2003). We found no evidence of the effect of storage 402

temperature and duration on seedling emergence of P. padus seeds. However, assuming that 403

germination remained the same under all temperature tested, cryopreservation can be still 404

recommended, at least for the short-term . Though some deterioration effects can be detected in 405

seeds during long-term cryogenic storage (Walters et al. 2004), the ability of cryogenic temperature to 406

arrest metabolic processes in cells and decrease mobility of molecules seems to be beneficial for 407

genebanking (Pritchard and Nadarajan 2008). Walters et al. (2004) estimated half-lives of fresh 408

lettuce seeds stored in the vapor and liquid phases of LN to be 500 and 3400 years, respectively. 409

Though this estimation cannot be projected directly to other species, it gives the conservation 410

specialist the first clue of how effective cryogenic storage can be for seed conservation. 411

Bayesian methods proved to be effective in plant conservation biology, for example, to assess 412

alternative actions in recovery plans, matrix population modeling, and predicting germination using 413

logistic models (Marin et al. 2013). It seems to be particularly useful when analysing the results of the 414

experiments with binomial data as an outcome (Bazán et al. 2014). Binomial data may be recorded as 415

a number of successes or failures out of the total number of tests such as germination of seeds in the 416

genetic collections (Walters et al. 2004; Pritchard and Nadarajan 2008). Such data are commonly 417

analyzed by assessing proportion of successes, data transformation (often with arcsine), and 418

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performing ANOVA on transformed data, followed by the test of significance using Tukey HSD, 419

Fisher or Duncan MRT (see e.g. Kim et al. 2008; Chmielarz 2009a; 2009b). There are several 420

problems associated with the arcsine transformation including loss of information (10 observed 421

successes out of 25 is not statistically the same as 1000 out of 2500, but the proportion of successes is 422

0.4 in both cases), lack of interpretability and failure to guarantee normality and homoscedasticity 423

required by ANOVA (Warton and Hui 2011). The methodological problem is not specific to 424

biological sciences, but is also of interest to, for example, epidemiologists and social scientists. 425

Recently, a move to binomial generalized linear (mixed) models GL(M)M has been advocated (Jaeger 426

2008; Warton and Hui 2011;). Although GL(M)M suffers from none of the above mentioned 427

problems, the maximum likelihood estimation fails in the cases of ‘degenerate’ estimates when 0 428

successes (or, alternatively, 0 failures) have been observed in any one category (Albert and Anderson 429

1984; Silvapulle 1981). This results in infinite parameter estimates and invalid inference. 430

Unfortunately for an inexperienced practitioner, statistical software often fails to alert the user to this 431

problem. For example, the GENLIN procedure in SPSS (IBM 2013) will give warning about the 432

convergence criteria not being satisfied, but will still proceed with the output. A glm function in R (R 433

Core Team 2014), on the other hand, will produce no warnings at all, although an experienced user 434

will recognize the problem from unreasonably high standard error estimates and, as a result, p-values 435

close to one. 436

This problem of observed zero counts, also called ‘separation’ has been known for some time 437

and methods have been developed to resolve it (see e.g. Heinze and Schemper 2002). In this paper, 438

however, we choose not to use the classical methods and followed Bayesian framework instead. The 439

use of Bayesian methods in plant physiology, ecology and genetics studies is increasing as more and 440

more practitioners are becoming familiar with them (Marin et al. 2003; Olge and Barber 2008). The 441

popularity of Bayesian statistics can be attributed to its flexibility in formulating models appropriate 442

to the questions of interest rather than molding questions according to what the model is able to do as 443

well as to the increasing computational capabilities and the availability of a free and reasonably user-444

friendly software WinBUGS (Lunn et al. 2000). 445

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In this study we have demonstrated successful application of Bayesian methods to analyze the 446

data obtained in conservation of Prunus padus seeds using a number of treatments and different 447

storage regimes. We have shown that within the Bayesian statistics it is possible to avoid a separation 448

problem caused by zero level of seedling emergence in some treatments. Direct application of arcsine 449

and similar transformations to such data would give a very poor approximation to normality. Also, the 450

assessment of the possibility of seedling emergence level in the performed treatments exceeding the 451

40 % threshold was straightforward within the Bayesian framework. Thus, we are in agreement with 452

Marin et al. (2003) in encouraging the use of Bayesian paradigms for data analysis in conservation 453

studies. 454

Conclusion 455

In conclusion, the results of this study show that freshly collected mature seeds of Prunus padus 456

tolerated dehydration to 3.5 % WC and thus can be considered orthodox. We determined, for the first 457

time, the safe hydration window for cryopreservation of P. padus seeds in LN to be 3.5-15 % and 458

showed that the majority of tested cooling and rewarming regimes had no profound effect on seed 459

viability after cryogenic storage. Our results suggest that seed storage in liquid nitrogen is an effective 460

conservation option for conservation of Prunus padus and possibly for other Prunus species. We also 461

demonstrated the simplicity and efficacy of Bayesian methods in analyzing binomial data obtained in 462

seed experiments and as such this approach may be very useful in developing effective conservation 463

technologies for a range of species. 464

Acknowledgments. This work was supported by the research fund of Dong-A University (Busan, 465

Republic of Korea) and by Gosling Research Institute for Plant Preservation (GRIPP), Guelph, 466

Canada. 467

References: 468

Albert, A. and Anderson, J.A. 1984. On the existence of maximum likelihood estimates in logistic 469

regression models. Biometrika 71(1): 1–10. doi: 10.2307/2336390 470

Page 19 of 33



Draft

20

Barbour, J.R. and Parresol, B.R. 2003. Effect of liquid nitrogen storage on seed germination of 51 tree 471

species. Seed Technol. 25(2): 183–190. Available from http://www.jstor.org/stable/23433271 472

[accessed 11 January 2016]. 473

Bazán, J.L., Romeo, J.S. and Rodrigues, J. 2014. Bayesian skew-probit regression for binary response 474

data. Braz. J. Probab. Stat. 28(4): 467–482. doi:10.1214/13-BJPS218 475

Berjack, P. and Pammenter, N.W. 2004. Recalcitrant seeds. In Handbook of seed physiology: 476

application to agriculture. Edited by R.L. Benech-Arnold and R.A. Sanchez. Haworth Press, New 477

York. pp. 305-345. 478

Cheong, E.J. 2012. Biotechnological approaches for improvement and conservation of Prunus 479

species. Plant Biotechnol. Rep. 6(1): 17–28. doi:10.1007/s11816-011-0195-y 480

Chmielarz, P. 2009a. Cryopreservation of dormant European ash (Fraxinus excelsior) orthodox seeds. 481

Tree Physiol. 29(10): 1279–1285. doi: 10.1093/treephys/tpp064 482

Chmielarz, P. 2009b. Cryopreservation of dormant orthodox seeds of forest trees: mazzard cherry 483

(Prunus avium L.). Ann. For. Sci. 66(4): 405. http://dx.doi.org/10.1051/forest/2009020 484

Chmielarz, P. 2010a. Cryopreservation of conditionally dormant orthodox seeds of Betula pendula. 485

Acta Physiol. Plant. 32(3): 591–596. http://dx.doi.org/10.1007/s11738-009-0437-6 486

Chmielarz, P. 2010b. Cryopreservation of the non-dormant orthodox seeds of Ulmus glabra. Acta 487

Biol. Hung. 61(2): 224–233. doi: 10.1556/ABiol.61.2010.2.10 488

Crane, J., Annette, L.M., Van Roekel, J.W. and Walters, C. 2003. Triacylglycerols determine the 489

unusual storage physiology of Cuphea seed. Planta 217(5): 699–708. 490

http://dx.doi.org/10.1007/s00425-003-1036-1 491

Daws, M.I. and Pritchard, H.W. 2008. The development and limits of freezing tolerance in Acer 492

pseudoplatanus fruits across Europe is dependent on provenance. CryoLett. 29(3): 189–198. 493

De Boucaud, M.T., Brison, M., Helliot, B. and Hervé-Paulus, V. 2002. Cryopreservation of Prunus.In 494

Cryopreservation of plant germplasm II. Biotechnology in agriculture and forestry, Vol. 50. 495

Edited by L.E. Towill and Y.P.S. Bajaj. Springer Verlag, Berlin, Heidelberg. pp. 287-311. 496

Dussert, S. and Engelmann, F. 2006. New determinants for tolerance of coffee (Coffea arabica L.) 497

seeds to liquid nitrogen exposure. CryoLett. 27(3): 169–178. 498

Page 20 of 33



Draft

21

Dussert, S. Chabrillange, N., Rocquelin, G., Engelmann, F., Lopez, M. and Hamon, S. 2001. 499

Tolerance of coffee (Coffea spp.) seeds to ultra-low temperature exposure in relation to 500

calorimetric properties of tissue water, lipid composition, and cooling procedure. Physiol. Plant. 501

112(4): 495-504. doi: 10.1034/j.1399-3054.2001.1120406.x 502

Ellison, A.M. 1996. An introduction to Bayesian inference for ecological research and environmental 503

decision-making. Ecol. Appl. 6: 1036–1046. http://dx.doi.org/10.2307/2269588 504

Flagstad, L., Cortés-Burns, H., Johnson, E., Simpson, L. and Brownlee, A. 2010. Viability of 505

European bird cherry (Prunus padus L.) seed after two-year retention in traps along the Chester 506

and Campbell Creek Trails, Anchorage, Alaska. University of Alaska Anchorage, Alaska Natural 507

Heritage Program, Alaska. 508

Frank, S. and Santamour, Jr. 1998. Amygdalin in Prunus leaves. Phytochem. 47(8): 1537–1538. 509

doi:10.1016/S0031-9422(97)00787-5 510

Gelman, A. 2005. Analysis of variance – why it is more important than ever. Ann. Stat. 33(1): 1–53. 511

doi:10.1214/009053604000001048 512

Gordon, A.G. and Rowe, D.C.F. 1982. Seed manual for ornamental trees and shrubs. Forestry 513

Commission Bulletin 59. Her Majesty's Stationery Office, London. 514

Häggman, H., Rusanen, M. and Jokipii, S. 2008. Cryopreservation of in vitro tissues of deciduous 515

forest trees. In Plant cryopreservation: a practical guide. Edited by B.M. Reed. Springer, New 516

York. pp 365–386. 517

Harvengt, L., Meier-Dinkel, A., Dumas, E. and Collin, E. 2004. Establishment of a cryopreserved 518

gene bank of European elms. Can. J. For. Res. 34(1): 43–55. doi:10.1139/x03-193 519

Hastie, T., Tibshriani, R. and Friedman, J. 2009. The elements of statistical learning, data mining, 520

inference and prediction, 2d edition. Springer, New York. 521

Heinze, G. and Schemper, M. 2002. A solution to the problem of separation in logistic regression. 522

Stat. Med. 21(16): 2409–2419. doi: 10.1002/sim.1047 523

Hor, Y.L., Kim, Y.J., Ugap, A., Chabrillange, N., Sinniah, U.R., Engelmann, F. and Dussert, S. 2005. 524

Optimal hydration status for cryopreservation of intermediate oily seeds: Citrus as a case study. 525

Ann. Bot. 95(7): 1153–1161. doi: 10.1093/aob/mci126 526

Page 21 of 33



Draft

22

IBM Corp. 2013. IBM SPSS Statistics for Windows, Ver 22.0. IBM Corp., Armonk, New York. 527

ISTA (International Seed Testing Association). 1999. International rules for seed testing. Seed Sci. 528

Technol. 27(Suppl). 529

Jaeger, F.T. 2008. Categorical data analysis: Away from ANOVAs (transformation or not) and 530

towards logit mixed models. J. Memory Lang. 59(4): 434–446. doi:10.1016/j.jml.2007.11.007 531

Jensen, M. and Eriksen, E.N. 2001. Development of primary dormancy in seeds of Prunus avium 532

during maturation. Seed Sci. Technol. 29(2): 307–320. 533

Kholina, A.B. and Voronkova, N.M. 2008. Conserving the gene pool of Far Eastern plants by means 534

of seed cryopreservation. Biol. Bull. 35(3): 262–269. 535

http://dx.doi.org/10.1134/S1062359008030060 536

Kim, H.H., Lee, J.H., Shin, D.J., Ko, H.C., Hwang, H.S., Kim, T., Cho, E.G. and Engelmann, F. 2008. 537

Desiccation sensitivity and cryopreservation of Korean ginseng seeds. CryoLett. 29(5): 419–426. 538

Lee, P.M. 1997. Bayesian statistics. An introduction, 2nd edition. John Wiley & Sons Inc., New York. 539

Lunn, D.J., Thomas, A., Best, N. and Spiegelhalter, D. 2000. WinBUGS - a Bayesian modelling 540

framework: concepts, structure, and extensibility. Stat. Comp. 10(4): 325–337. 541

http://dx.doi.org/10.1023/A%3A1008929526011 542

Marin, J.M., Montes Diez, R. and Rios Insua, D. 2003. Bayesian methods in plant conservation 543

biology. Biol. Conserv. 113(3): 379–387. doi:10.1016/S0006-3207(03)00124-1 544

Michalak, M., Plitta, B.P. and Chmielarz, P. 2013. Desiccation sensitivity and successful 545

cryopreservation of oil seeds of European hazelnut (Corylus avellana). Ann. Appl. Biol. 163(3): 546

351-358. doi: 10.1111/aab.12059 547

Michalak, M., Plitta, B.P., Tylkowski, T., Chmielarz, P. and Suszka, J. 2015a. Desiccation tolerance 548

and cryopreservation of seeds of black poplar (Populus nigra L.), a disappearing tree species in 549

Europe. Eur. J. For. Res. 134(1): 53–60. doi: 10.1007/s10342-014-0832-4 550

Michalak, M., Plitta-Michalak, B.P. and Chmielarz, P. 2015b. A new insight in desiccation tolerance 551

and cryopreservation of mazzard cherry (Prunus avium L.) seeds. Open Life Sci. 10(1): 354-364. 552

doi: 10.1515/biol-2015-0036 553

Page 22 of 33



Draft

23

Muthusamy, J., Staines, H.J., Benson, E.E., Mansor, M. and Krishnapillay, B. 2005. Investigating the 554

use of fractional replication and Taguchi techniques in cryopreservation: a case study using 555

orthodox seeds of a tropical rainforest tree species. Biodiv. Conserv. 14(13): 3169–3185. 556

http://dx.doi.org/10.1007/s10531-004-0385-9 557

Niino, T., Tashiro, K., Suzuki, M., Ohuchi, S., Magoshi, J. and Akihama, T. 1997. Cryopreservation 558

of in vitro shoot tips of cherry by one-step vitrification. Sci. Hort. 70(2-3): 155–163. 559

doi:10.1016/S0304-4238(97)00062-9 560

Ogle, K. and Barber, J.J. 2008. Bayesian data–model integration in plant physiological and ecosystem 561

ecology. In Progress in botany, Vol 69. Edited by U. Lüttge, W. Beyschlag and J. Murata. 562

Springer-Verlag, Berlin, Heidelberg. pp 281–311. 563

Pence, V.C. 1991. Cryopreservation of seeds of Ohio native plants and related species. Seed Sci. 564

Technol. 19: 235–251. 565

Popova, E.V., Kim, D.H., Han, S.H., Moltchanova, E., Pritchard, H.W. and Hong, Y.P. 2013. 566

Systematic overestimation of Salicaceae seed survival using radicle emergence in response to 567

drying and storage: implications for ex situ seed banking. Acta Physiol. Plant. 35(10): 3015–568

3025. http://dx.doi.org/10.1007/s11738-013-1334-6 569

Popova, E.V., Kim, D.H., Han, S.H., Pritchard, H.W. and Lee, J.C. 2012. Narrowing of the critical 570

hydration window for cryopreservation of Salix caprea seeds following ageing and a reduction in 571

vigour. CryoLett. 33(3): 219–230. 572

Pritchard, H.W. and Dickie, J.B. 2003. Predicting seed longevity: Use and abuse of seed viability 573

equations. In Seed conservation: turning science into practice. Edited by R.D. Smith, J.B. Dickie, 574

S.H. Linington, H.W. Pritchard and R.J. Probert. Royal Botanic Gardens, Kew, UK. pp. 653–575

722. 576

Pritchard, H.W. and Nadarajan, J. 2008. Cryopreservation of orthodox (desiccation tolerant) seeds. In 577

Plant cryopreservation: a practical guide. Edited by B.M. Reed. Springer, New York. pp. 485–578

501. 579

Qian, S.S. and Shen, Z. 2007. Ecological applications of multilevel analysis of variance. Ecol. 88(10): 580

2489–2495. http://dx.doi.org/10.1890/06-2041.1 581

Page 23 of 33



Draft

24

R Core Team. 2014. R: A Language and Environment for Statistical Computing. R Foundation for 582

Statistical Computing, Vienna, Austria. Available from URL http://www.R-project.org/ 583

[accessed 17 January 2015]. 584

Royal Botanic Gardens Kew Seed Information Database. Version 7.1. 2015. Available from 585

http://data.kew.org/sid/. [Accessed 26 November 2015]. 586

Ryynänen, L.A. and Aronen, T. 2005. Vitrification, a complementary cryopreservation method for 587

Betula pendula Roth. Cryobiol. 51(2): 208–219. doi:10.1016/j.cryobiol.2005.07.006 588

Silvapulle, M.J. 1981. On the existence of maximum likelihood estimators for the binomial response 589

models. J. Royal Stat. Soc. Series B 43(3): 310–313. 590

Spiegelhalter, D., Best, N., Carlin, B. and van der Linde, A. 2002. Bayesian measures of model 591

complexity and fit. J. Royal Stat. Soc. Series B 64(4): 583–639. doi: 10.1111/1467-9868.00353 592

Suszka, B. 1967. Studia nad spoczynkiem i kiełkowaniem nasion różnych gatunków z rodzaju Prunus 593

L. [Studies on dormancy and germination of seeds from various species of the genus Prunus L.]. 594

Arbor. Kórnickie 12: 221-282. (In Polish). 595

Suszka, B., Muller, C. and Bonnet-Masimbert, M. 1996. Seeds of forest broadleaves, from harvest to 596

sowing. Institut National de la Recherche Agronomique, Paris. 597

Towill, L.E. and Forsline, P.L. 1999. Cryopreservation of sour cherry (Prunus ceraceus L.) using a 598

dormant vegetative bud method. CryoLett. 20(4): 215–222. 599

Uusitalo, M. 2004. European bird cherry (Prunus padus L.) − a biodiverse wild plant for horticulture. 600

MTT Agrifood Research, Agrifood Research Reports 61, Finland. 601

Vidal, N., Vieitez, A.M., Fernández, M.R., Cuenca, B. and Ballester, Z. 2010. Establishment of 602

cryopreserved gene banks of European chestnut and cork oak. Eur. J. For. Res. 129(4): 635–643. 603

doi: 10.1007/s10342-010-0364-5 604

Vujović, T., Chatelet, P., Ružić, Ð. and Engelmann, F. 2015. Cryopreservation of Prunus spp. using 605

aluminium cryo-plates. Sci. Hort. 195: 173–182. doi:10.1016/j.scienta.2015.09.016 606

Walters, C., Wheeler, L. and Stanwood, P.C. 2004. Longevity of cryogenically stored seeds. Cryobiol. 607

48(3): 229–244. doi:10.1016/j.cryobiol.2004.01.007 608

Page 24 of 33



Draft

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Wang, B., Wang, R.R., Cui, Z.H., Bi, W.L., Li, J.W., Li, B.Q., Ozudogru, E.A., Volk, G.M. and 609

Wang, Q.C. 2014. Potential applications of cryogenic technologies to plant genetic improvement 610

and pathogen eradication. Biotechnol. Adv. 32(3): 583–595. 611

doi:10.1016/j.biotechadv.2014.03.003 612

Warton, D.I. and Hui, F.K.C. 2011. The arcsine is asinine: the analysis of proportions in ecology. 613

Ecol. 92(1): 3–10. http://dx.doi.org/10.1890/10-0340.1 614

615

616

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Table 1. Combinations of cooling, storage and rewarming procedures investigated in the present 617

study for conservation of Prunus padus seeds. 618

Variant

(Protocol)

Cooling Storage

tempe-

rature

Storage

duration

Rewarming

1 Untreated control seeds N/A N/A N/A

Effect of cooling regime

2 Direct to -196°C -196°C 1 month 37°C, 15 min

3 -20 °C (1 h) → -196°C -196°C 1 month 37°C, 15 min

4 -80 °C (1 h) → -196°C -196°C 1 month 37°C, 15 min

5 -20°C (1h) → -80°C (1 h) → -196°C -196°C 1 month 37°C, 15 min

Effect of rewarming regime

6 -80 °C (1 h) → -196°C -196°C 1 month 37°C, 7 min

7 -80 °C (1 h) → -196°C -196°C 1 month 37°C, 30 min

8 -80 °C (1 h) → -196°C -196°C 1 month Air (22°C), 15 min → 37°C, 7 min

9 -80 °C (1 h) → -196°C -196°C 1 month Air (22°C), 30 min

10 -20°C (1h) → -80°C (1 h) → -196°C -196°C 1 month -80°C, 1 h → -20°C, 1 h → air (22°C), 30 min

Effect of storage temperature and duration

11 Direct -20°C 1 h Air (22°C), 30 min

12 Direct -20°C 1 week Air (22°C), 30 min

13 Direct -20°C 1 month Air (22°C), 30 min

14 Direct -80°C 1 h 37°C, 15 min

15 Direct -80°C 1 week 37°C, 15 min

16 Direct -80°C 1 month 37°C, 15 min

17 -80 °C 1 h → -196°C -196°C 1 h 37°C, 15 min

18 -80 °C 1 h → -196°C -196°C 1 week 37°C, 15 min

19 -80 °C 1 h → -196°C -196°C 1 month 37°C, 15 min

N/A: not applicable 619

620

621

622

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Figure captions 623

624

Figure 1. Model desiccation and hydration curves recorded for Prunus padus seeds. Data are 625

presented as posterior estimated means and the respective 95 % credible intervals. Water content is 626

calculated on fresh weight basis. 627

Figure 2. A - Posterior probabilities of seedling emergence of at least 40 % for different water content 628

(WC) values under the control (-LN) and cryopreservation (+LN) treatments. The dotted horizontal 629

line corresponds to the posterior probability of 0.95. B - Estimated posterior mean proportions of 630

seedling emergence for different water content (WC) under the control (-LN) and cryopreservation 631

(+LN) treatments. Bars correspond to 95 % credible intervals. 632

633

Figure 3. Seedling emergence of Prunus padus seeds after different cooling and rewarming 634

treatments performed according to protocols (Variants) 1-10 in Table 1. Data are presented as 635

posterior estimated means and the respective 95 % credible intervals. 636

637

Figure 4. Seedling emergence of Prunus padus seeds after storage at -20°C, -80°C and -196°C for 638

various durations compared to untreated control. Data are presented as posterior estimated means and 639

the respective 95 % credible intervals. 640

641

642

643

644

645

646

647

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05

1015

Dessication (hours)

Wat

er c

onte

nt (

%)

0 5 24 4810

●

●

●

●

●

●

●

1015

2025

Hydration (hours)W

ater

con

tent

(%

)

0 10 24 48 725

●

●●

●

●

●●

●

●

Figure 1.

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0.0

0.2

0.4

0.6

0.8

1.0

Water content (%)

Pr(

p>.4

0|da

ta)

3.5 7.6 12.7 15.0 17.6 20.05.0 9.6 14.6 17.2 18.4 21.1

●

●

●

●

●

●●

●

●●

●

●

● − LN+LN

Water content (%)

See

dlin

g em

erge

nce

(%)

010

2030

4050

6070

3.5 7.6 12.7 15.0 17.6 20.05.0 9.6 14.6 17.2 18.4 21.1

− LN+LN

A

B

Figure 2.

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Draft

1 2 3 4 5

020

4060

8010

0

Variants

See

dlin

g em

erge

nce

(%)

● ●●

●●

020

4060

8010

0

VariantsS

eedl

ing

emer

genc

e (%

)

1 6 7 8 9 10

● ●

●

●

●

●

Figure 3.

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Draft

020

4060

8010

0

See

dlin

g em

erge

nce

(%)

Control1 hour1 week1 month

− 20°C − 80°C − 196°C

Figure 4.

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Draft

A1. Supplement: WinBUGS code for model (1-5)

model{

for(i in 1:N){

Y[i] ~ dbin(p[trt[i],fw[i]],25)

}

# logistic structure

for(ti in 1:2){

for(fi in 1:12){

p[ti,fi] <- 1/(1+exp(-logitp[ti,fi]))

}}

for(ti in 1:2){

for(fi in 1:12){

logitp[ti,fi] <- alpha0+alpha*(ti-1)+beta[fi]+gamma[fi]*(ti-1)

}}

# priors

alpha0 ~ dnorm(0,1.0E-5)

alpha ~ dnorm(0,1.0E-5)

beta[1] <- 0

for(fi in 2:12){

beta[fi] ~ dnorm(0,1.0E-5)

}

gamma[1]<- 0

for(fi in 2:12){

gamma[fi] ~ dnorm(0,1.0E-5)

}

}

A2. Supplement: WinBUGS code for model (1,6)

model{

for(i in 1:N){

Y[i] ~ dbin(p[trt[i],fw[i]],25)

}

# priors for p

for(ti in 1:2){

for(fi in 1:12){

p[ti,fi] ~ dbeta(1,1)

}}

}

A3. Supplement: WinBUGS code for model (7-9)

Please note, that the logit transformation has been performed prior to

running the code for reasons of computational efficiency.

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Draft

model{

for(i in 1:N){

Y[i] ~ dnorm(mu[hour[i]],tau)

}

for(h in 1:H){

mu[h] ~ dnorm(0,1.0E-5)

}

tau ~ dgamma(.01,.01)

}

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Documents

Draft - tspace.library.utoronto.ca · However, Michalak et al. (2015b) reported that seeds of this 83 species could tolerate cryopreservation at higher WC (ca. 20%) with seedling