Quantifying seed germination response of melon (Cucumis melo L.) to temperature and water potential: Thermal time, hydrotime and hydrothermal time models

South African Journal of Botany 130 (2020) 1
10

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Quantifying seed germination response of melon (Cucumis melo L.) to temperature and water potential: Thermal time, hydrotime and hydrothermal time models S.F. Saberalia,*, Z. Shirmohamadi-Aliakbarkhanib a b

Department of Horticulture Science and Engineering, University of Torbat-e Jam, Khorasan Razavi, Iran Department of Water Science and Engineering, University of Torbat-e Jam, Khorasan Razavi, Iran

A R T I C L E

I N F O

Article History: Received 2 October 2019 Revised 2 December 2019 Accepted 21 December 2019 Available online xxx Edited by I. Demirsource Keywords: Germination modelling Water stress Probit analysis Base temperature

A B S T R A C T

Quantifying the germination behaviour of seeds against fluctuating environmental conditions can use as a useful tool for seed ecological studies. The response of seed germination rate to temperature (T) and water potential (C) can be described using thermal time (TT), hydrotime (HT), and hydrothermal time (HTT) models. The germination behaviour of Persian melons (C. melo L.) were studied over a range of constant temperatures and water availability to assess the performance of hydro-thermal time models and to provide a data set of germination thresholds and parameters for the Persian melons. The seeds of melons were germinated in the laboratory over a water potential range from 0 to
1.25 MPa at 10, 15, 20, 25, 30, 35, 40 and 45 °C. The results showed that germination percentage was affected by water potential, temperature and their interactions. Germination increased with increasing temperature within the range of 15
25 °C, then decreased as temperature increased from 25 to 45 °C. Furthermore, final germination percentages were reduced with decreasing C, although significant reduction was observed at Cs less than
0.25 MPa. The model analysis showed that the dynamics of seed germination were generally well described by the TT model within Cs range <
1 MPa (R2 = 83
96), HT (R2= 0.77
0.93) and HTT models (R2=0.89
0.90). Using the models analysis, the base, optimum and ceiling germination temperatures were estimated to be 9.4, 27.3 and 41.4 °C, respectively. Thermal time analysis showed that thermal time required for germination of Persian melon, Tb and Tc were affected by water availability. Furthermore, the estimated minimum water potential threshold for germination was
1.19 MPa using the HT model, but it shifted towards a higher values with temperatures above or below 25 °C. The amount of hydrothermal time required to germinate was 33 MPa °C days on the suboptimal temperatures range and increased by 36% with increasing temperature from the suboptimal temperatures to the supraoptimal temperatures. The HTT model showed that the Cb(50) increased by 0.09 MPa with every degree increase in temperature above To. The interaction of C and temperature affected the model parameters and finally the performance of germination models, then varying model parameters with changing environmental condition should be considered for predicting germination time in a complex growth environment. © 2020 SAAB. Published by Elsevier B.V. All rights reserved.

1. Introduction Seed germination is a complex physiological process and a major developmental transition in the life cycle of plants that is responsive to environmental signals (Baskin and Baskin 2014). Knowledge of seed germination responses to fluctuating environmental factors is required not only to understand and predict the seeding date, but also to apply effective strategies for successful seedling establishment (Fenner and Thompson, 2005). Temperature and water availability in the seedbed are the two most important environmental factors

* Corresponding author. E-mail address: [email protected] (S.F. Saberali). https://doi.org/10.1016/j.sajb.2019.12.024 0254-6299/© 2020 SAAB. Published by Elsevier B.V. All rights reserved.

defining a species germinability and seedling emergence (Gummerson, 1986; Bradford, 2002). Seed germination models provide a quantitative description to understand why and how seed germination varies under different environmental conditions. The effect of temperature (T), water potential (C) and T £ C interaction on seed germination have been modelled by thermal time, hydrotime, and hydrothermal time models, respectively (Ellis et al., 1986; Allen et al., 2000; Bradford, 2002). The TT, HT and HTT models were developed based on underlying physiology, with parameters that have a clear physiological meaning (Allen et al., 2000). Thermal germination behaviour of seeds is governed by the accumulation of heat units within the range of cardinal temperatures. Germination rate usually increases linearly with increasing

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S.F. Saberali and Z. Shirmohamadi-Aliakbarkhani / South African Journal of Botany 130 (2020) 1
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temperature from a minimum (or base, Tb) temperature up to an optimum (To) and decreases linearly to a maximum (or ceiling, Tc) temperature (Steinmaus et al., 2000; Bradford, 2002; Rowse and Finch-Savage, 2003). Cardinal temperatures, Tb, Tc and To, are related to the range of ecological and geographical conditions in which a given species is adapted and serve to match germination timing to favourable conditions for subsequent growth and development. (Baskin and Baskin, 2014). Water availability is the other key factor which needs to be considered for quantifying seed germination. Seed imbibition rate and the rate and level of germination generally decrease as a seedbed C decrease. Indeed, a seed must absorb a certain amount of water to achieve a threshold hydration level for radical emergence, and species differ in the minimum C at which germination can occur. Hydrotime concept is similar to thermal time, which quantitatively describes the rate of progress toward germination as a function of seedbed water potential above a minimum threshold potential. However, water has more complicated effects on seed germination compared with temperature, because physiological adjustment may occur at low water potential (Bradford, 1995). The HTT model quantifies the rate of progress towards germination by integrating temperature and water interactions above the thresholds, which includes both the thermal time accumulation above the thermal threshold (Tb) and the hydro time accumulation above the hydro threshold (base water potential, Cb). The Tb and Cb are the temperature and water potential below which development ceases and above which development increases up to a maximum rate, respectively (Gummerson, 1986; Bradford, 2002). The TT, HT and HTT models have been successfully used to predict seed germination behavior of crops (Ellis et al., 1986; Finch-Savage and Phelps, 1993; Alvarado and Bradford 2002), and wild plants (Hu et al., 2015). Cucurbits are vegetable crops belonging to the family Cucurbitaceae, which are cultivated worldwide in warm regions, and appear in many shapes and sizes. Persian melons is one of the most cucurbit plants cultivated in warmer region of Iran and some surrounding countries. A low temperature and water shortage during seed germination of melon can lead to poor field emergence and erratic stands, so an asynchronous seedling emergence can lead to variation in plant development and finally yield reduction (Kotowski, 1962; Thompson, 1974). The number of hydro-thermal units required to reach a particular stage of development is known as the hydrothermal time constant and can be used to predict when a crop will reach germination stage in a region where temperature and moisture levels are known. The objectives of this study were: (1) to quantify the germination response of melon seeds to temperature and water potential; and (2) to explain germination behaviour of Persian melon seeds, using the concepts of thermal time, hydrotime and hydrothermal time, and provide a data set of germination thresholds and parameters for this melon.

medium. In a viability test before main germination test, seeds showed 90
100% germination at room temperature in distilled water. 2.2. Germination test The experiment was a completely randomized design with a factorial arrangement of treatments with four replications. Seeds were germinated in incubators across a combination of eight constant temperatures (10
45 °C § 1 °C) with 5 °C increments and six water potentials (0,
0.25,
0.5,
0.75,
1.0, and
1.25 MPa) at dark. Negative values of C represent decreasing level of water availability for seed germination. A C of 0 MPa was obtained using distilled water. The negative C levels were prepared with polyethylene glycol (PEG 6000; Merck, Germany) according to Michel and Kaufman (1973). Petri dishes and filter paper sterilized by UV lamp in clean air bench for 30 min. For each treatment, four 25-seed replicates were placed in 9cm Petri dishes containing one disk of Whatman No. 1 filter paper, with 7 mL of test solutions (Galíndez et al., 2019; Watt et al., 2010). Before placement seeds in Petri dishes, the filter papers were soaked in trays containing distilled water (control) or aqueous solutions of polyethylene glycol for 2 h. Petri dishes were enclosed in clear plastic bags to reduce water evaporation, and randomized in the incubators. The water level was adjusted daily with distilled water and also the solutions were renewed one time during the experiment, after the eighth day of the experiment, to avoid any changes in C due to evaporation. Seeds were counted as germinated when they had visible radicle emergence of more than 2 mm (Alvarado and Bradford 2002). Seeds were checked for germination every day for 16 day, and germinated seeds were removed at each counting. The time course of germination test were sufficient to see a plateau in the germination percentage. 2.3. Data analysis For estimation of the parameters describing the germination response to temperature (T) and water potential, germination time course data were analysed by repeated probit analysis based on the TT, HT and hydrothermal time HTT concepts. Cumulative germination percentage was transformed to probits and regressed against time log (Finney, 1971; Steinmaus et al., 2000), and the time taken for cumulative germination (tg) to reach subpopulation percentiles (10
90%) was estimated from this function according to Steinmaus et al. (2000). Then, germination rates (GR) were calculated as the inverses of the germination times for each percentile at each T or C. The preliminary estimation of the parameters in the TT, and HT models were obtained by plotting GR versus T and C for each percentile. Then using repeated probit analysis developed by Ellis et al. (1986), the exact parameters for the TT, HT and HTT models were determined for the whole seed population.

2. Materials and methods 2.4. Thermal time 2.1. Seed source and preparation Seeds of Persian melons (C. melo cv. Khatuni) were obtained from a commercial supplier. Some seed characteristics of Persian melon are shown in Table 1. Seeds were stored in sealed plastic bags at 4 °C until the start of the experiment. Seeds were surface-sterilized for 2 min in 5% (v/v) sodium hypochlorite solution, and rinsed thoroughly with deionized water. Seeds were screened to remove any obvious empty or broken seeds during sterilization process. Then, cleaned seeds were lightly dusted with fungicide (Thiram) before being placed on the germination Table 1 Some seed characteristics of Persian melon (C. melo cv. Khatuni). Life cycle

Annual

Seed viability (%)

100-seed weight (g)

Seed length (cm)

Seed width (mm)

93.0 § 3

4.9 § 0.4

1.0 § 0.15

0.45§0.05

The GR data were separated into a suboptimal and a supraoptimal temperature ranges. Indeed, the T with the highest germination rate (1/T50) was designated as the division between sub- and supra-optimal temperature ranges. The data for each germination fraction (different percentiles, 10
90%) and for each C were regressed against T to estimate the base temperature (Tb) and ceiling temperature (Tc) (Ellis et al., 1986). Optimum temperature (To) was estimated for each germination fraction as the point where regression lines of sub- and supraoptimal temperatures crossed each other. Thermal time to germination for g fraction of the population (u T(g)) at suboptimal and supraoptimal Ts can be expressed respectively as:

uT1 ðgÞ ¼ ðT
Tb Þtg

ð1Þ

and

uT2 ¼ ðTc ðgÞ
T Þtg

ð2Þ

S.F. Saberali and Z. Shirmohamadi-Aliakbarkhani / South African Journal of Botany 130 (2020) 1
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where uT is the thermal time (° days) to germination of fraction g, tg is actual time to germination of fraction g, T is germination temperature (°C), Tb and Tc are the base and ceiling temperatures, respectively, which below and above them a seed will not germinate. The thermal time model can be fitted by repeated probit analyses (Ellis et al., 1986), as all observed germination percentages on a probit scale for each C regressed against log thermal times to germination. The probit equation for the sub-optimal temperature can be expressed as: 
h i Probit ðg Þ ¼ log ðT
Tb Þtg
logð u T ð50ÞÞ =s uT ð3Þ where probit (g) is the probit transformation of cumulative germination percentage g, uT(50) is median thermal time to germination and s uT is the standard deviation of log uT requirements among individual seeds in the population. The iterative method was used to estimate the Tb for whole germination fractions, with varying Tb until the mean square residual term of the regression was minimized (Ellis et al., 1986). For the supraoptimal temperature range, the thermal time model can be fitted by repeated probit analyses with regressing the probit transformation of cumulative germination values for each C regressed versus a function of time and T. Then, varying the value of uTc until the best fit was attained (Ellis et al., 1986; Ellis and Butcher, 1988), according to the equation:     ð4Þ Probit ðg Þ ¼ T þ uTc =tg
Tc ð50Þ =s Tc where uTc is thermal time constant at supraoptimal temperature for whole subpopulations, Tc(50) is median ceiling temperature for germination, s Tc is standard deviation of the ceiling temperature among individual seeds in the population. 2.5. Hydrotime The hydrotime model was developed to quantify the effect of reduced water potential on seed germination course (Gummerson, 1986; Bradford, 1990). The hydrotime model can be defined as:   uH ¼ C
Cb ðgÞ tg ð5Þ where u H is the hydrotime constant (MPa days), C is the actual water potential of seedbed, and Cb(g) is the base (minimum) water potential that prevents germination of fraction g, and tg is the actual time to germination of fraction g. The parameters of Eq. (5) can be derived using the repeated probit analysis of the following equation (Bradford, 1990, 1995):     ð6Þ Probit ðg Þ ¼ C
u H =tg
Cb ð50Þ =s Cb where Cb(50) is the median Cb, and s Cb is the standard deviation in Cb among seeds within the population. The probit analysis was performed separately for each germination temperatures. 2.6. Hydrothermal time The thermal time and hydrotime models have been combined into a hydrothermal time model, which can describe seed germination patterns when temperature and C are both varied in the seedbed (Alvarado and Bradford, 2002). The germination time course in terms of hydrothermal time model for suboptimal and supraoptimal ranges of T can be described respectively by:   uHT ¼ C
Cb ðgÞ ðT
Tb Þtg ð7Þ and

uHT ¼

h


i

C
Cb ðgÞ
ðKT ðT
To ÞÞ ðT
TbÞ tg

Cb(g) versus T when T>To) (Alvarado and Bradford, 2002). Other variables are as defined for the above equations. The parameters in the hydrothermal time models can be estimated using repeated probit analysis, according to the following equations:     Probit ðg Þ ¼ C
uHT =ðT
Tb Þtg
Cb ð50Þ =s Cb ð9Þ Probit ðg Þ ¼

h

where u HT is the hydrothermal time constant (MPa °days), that has a constant value for the whole seed population, To is the predicted optimum T for germination, and KT is a constant (the slope of the





i

c
ðKT ðT
To ÞÞ
uHT =ðT
Tb Þtg
cbð50Þ =s cb

ð10Þ

Where all observed germination percentages on probit scale at sub- and supra-optimal temperature ranges were regressed separately against C
uHT/(T
Tb)tg and C
KT (T
To)
uHT/(T
Tb)tg, respectively. Then, varying the value of u HT, Tb, To and KT until the best fit was obtained (Bradford, 1995, 2002). All terms are the same as those used for previous equations. Germination data were transformed (arcsine) before analysis of variance to achieve normality. A two-way ANOVA was used to test the significance effect of temperature and water potential on seed germination. The ANOVA were performed using the SAS software (SAS, 2003) and treatment means were compared by least significant difference test at P<0.05. The germination modelling was performed using repeated probit analyses (Ellis et al., 1986), as percentage of germination was transformed to the probit scale using the PROBIT function in SAS (SAS, 2003). The TT, HT, HTT models were fitted to germination data using a non-linear model (PROC NLIN). Prior to this fitting, the preliminary estimation of the models parameters for each percentile were extracted manually by regression analysis using Excel software. Goodness of fit in each model was checked by constructing plots of germination percentage versus the thermal time or normalized thermal time (Bradford, 2002), using SigmaPlot11 software (Systat Software Inc., SanJose CA, USA). We also statistically evaluated models predictions by means of the coefficient of determination (R2) and normalized root mean square error (RMSE). 3. Results 3.1. Effect of temperature and water potential on germination Germination percentages of melon seeds were affected by T, C, and the interaction of T £ C (Table 2). There were no germinations at 10 and 45 °C, and maximum germination value of 93.3% was obtained at 25 °C under no water stress condition. Germination increased with increasing temperature within the ranges of 15
25 °C, then decreased as temperature increased from 25 to 45 °C. Final germination was reduced with decreasing C, although significant reduction was observed at Cs less than
0.25 MPa (Table 3). The negative effect of water availability on seed germination was associated with seedbed temperatures. For example, mean seed germination decreased by 50.7, 33.8, 30.3, 35.0, 41.5 and 62% in response to reduced Cs compared to the control (0 MPa) at 15, 20, 25, 30, 35 and 40 °C, respectively. 3.2. Thermal time analysis Plotting the germination rates (GRg) for different percentiles against T showed that linear increases and decreases in the GRg

Table 2 ANOVA significance levels for germination percentage of Persian melon affected by temperature and water potential. S.O.V

ð8Þ

3

Temperature (T) Water potential (C) T£C Error

df

Germination

7 5 35 144

15,210.89*** 7826.42*** 573.80** 27.81

** and *** indicates significance at P levels of 0.01 and 0.001, respectively.

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S.F. Saberali and Z. Shirmohamadi-Aliakbarkhani / South African Journal of Botany 130 (2020) 1
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10 15 20 25 30 35 40 45 Mean

Water potential (MPa) 0


0.25


0.5


0.75


1.0


1.25

Mean

0.00 aE 90.0 aAB 91.7 aAB 93.3 aA 86.7aB 65.0 aC 28.3 aD 0.0 aE 56.9 a

0.00aE 83.3aAB 86.7 abAB 88.3 abA 78.3 bB 60.0 aC 31.7 aD 0.0 aE 53.5 a

0.00 aE 73.3 bAB 78.3 bAB 81.7 bA 68.3 cB 48.3 bC 21.7 bD 0.0 aE 47.5 b

0.00 aD 55.0 cBC 68.3 cA 73.3 cA 65.0 cAB 41.7 cC 8.3 cD 0.0 aD 40.2 c

0.00 aC 10.0 dC 48.3 dAB 56.7 dA 51.7 dA 28.3 dB 1.7 deC 0.0 aC 25.8 d

0.00 aD 0.0 eD 21.7 eAB 25.3 eA 18.3 eB 11.7 eC 0.0 eD 0.0 aD 9.6 e

0E 51.9 C 65.8 AB 69.7 A 61.4 B 42.5 C 15.3 D 0E

In each row and column, means with the same letter are not significantly different (P  0.05). Small letters and capital letters signify differences among water potential and temperature treatments, respectively.

Table 4 Estimation of cardinal temperatures for seed germination of Persian melon at water potential of 0 MPa, using a linear regression analysis at different percentiles (10
90%). Percentiles 10 20 30 40 50 60 70 80 90

Fig. 1. The effect of temperature on the germination rate (1/tg) of melon seeds at water potential of 0 MPa. The symbols are the germination rate data at different temperatures and percentiles (10
90%). Lines were fitted according to Eqs. (1) and (2), for estimating cardinal temperatures in each germination fraction.

below and above the To (Fig. 1). These linear responses were used to preliminary estimations of Tb, To and Tc by the extrapolation method. At C of 0 MPa, the estimates of Tb, To and Tc, respectively, ranged from 9.5 to 10.2 °C, 24.8 to 25.3 °C and 38.9 to 41.8 °C across different percentiles (Table 4 and Fig. 2). The dynamic of seed germination in response to temperature was well described by the thermal time model at suboptimal and supraoptimal temperatures within the C range of 0 to ˗0.75 MPa (R2 = 83
96 and RMSE<28.9%; Table 5, Fig. 2 and Fig. 3). The thermal time model for the supraoptimal temperatures at
1.25 MPa explained a small amount of the variation in seeds germination (R2=0.33). Furthermore, the model performance was moderate, when it was used across all C treatments (Table 5). The estimated Tb and Tc values for whole seed populations were 9.4 and 41.4 °C, when seed germinated in water. At suboptimal temperatures, the median thermal time to germination (log uT(50)) and Tb increased by 57 and 4% as C decreased from 0 to
1.25 MPa, respectively. At supraoptimal temperatures, the ceiling temperature for 50% of seeds to germinate (Tc(50)) decreased by 13% as C decreased from 0 to
1.25 MPa. The values of the thermal time above optimum temperature (u TC) increased by 44% with decreasing C from 0 to
0.75 MPa, and followed by an increase of 320% as C decreased from
0.75 to
1.25 MPa.

3.3. Hydrotime analysis The hydrotime model well explained the majority of variation in seed germination times, when the germination responses to C were

Tb (°C)

To (°C)

TC (°C)

9.5 9.6 9.7 9.7 9.7 9.8 10.0 10.0 10.2

25.3 25.3 25.3 25.2 25.2 25.0 24.9 24.8 24.8

41.8 41.8 41.7 41.7 41.4 41.1 40.6 39.8 38.9

analysed separately for each temperature (R2= 0.77
0.93 and RMSE=17.8
49.4, Fig. 4 and Table 6). However, the goodness of fit of the model notably decreased with increasing T from 35 to 40 °C. Furthermore, the hydrotime model explained only a small amount of the variation in seed germination times (R2=0.33 and RMSE=75.2), when it was used across all temperature ranges. The estimated values of uH, Cb(50) and s ᴪb differed among the temperatures (Table 6).The amount of hydrotime required for germination (uH) increased by 24% at T below 25 °C, and by 10% at T above 30 °C compared with temperature range of 25
30 °C. The Cb(50) shifted towards a lower values (more negative) when T increased from 15 to 25 °C, whereas it shifted towards a higher value (less negative) with increasing T form 25 to 40 (Table 6). The variation in Cb(50) among the temperatures was as high as
1.35 MPa. The standard deviation of the base water potential (s ᴪb) increased with increasing temperature up to 35 °C, and above that it decreased again (Table 6). 3.4. Hydrothermal time analysis The combined effect of temperature and water potential on seed germination considered using hydrothermal time model. The model predictability was higher (R2= 0.90 and RMSE= 24.1) at suboptimal temperatures range than at supraoptimal temperatures range (R2= 0.89 and RMSE= 26.3, Fig. 5 and Table 7). The estimated value of base temperature in the HTT model was 9.4 °C and the water potential threshold for 50% of the germinated seeds was
1.19 MPa with a standard deviation of 0.44 MPa (Table 7). The HTT model above optimal temperature range showed that the estimated value of To was 27.3 °C (Table 7).The amount of hydrothermal time required to germinate (u HT) and the standard deviation of the base water potential (s Cb) in the HTT model were higher at the supraoptimal temperatures than at the suboptimal temperatures (Table 7). Finally, the HTT model above To estimated a value of 0.09 MPa °C
1 for kT, which indicates the Cb(50) increased by 0.09 MPa with every degree increase in temperature above the To.

S.F. Saberali and Z. Shirmohamadi-Aliakbarkhani / South African Journal of Botany 130 (2020) 1
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Fig. 2. Germination time courses for Persian melon seeds at suboptimal temperatures (15, 20, 25 °C) under water potentials of (A) 0, (B)
0.25, (C)
0.75, (D)
1.0, and (E)
1.25 MPa. The symbols indicate the observed germination data, and the lines indicate the germination time courses predicted by the thermal time model, based on the parameter estimates in Table 5.

4. Discussion The results showed that the percentage of seed germination was affected by temperature and water availability. The melon seeds germinated from 15 to 40 °C, and the highest final germination was 93.3% in water (0 MPa) at 25 °C. However, lower (<20 °C) or higher (>30 °C) temperatures significantly reduced the final germination percentage, and could have a negative effect on establishment of melon population in a field. The germination percentage significantly decreased as water potentials dropped below
0.25 MPa, and final

seed germination was 0 to 26% at
1.25 MPa, based on incubation temperature. Previous research has shown that temperature and water availability are the most important factors affecting seed germination and seedling establishment in a field (Allen et al., 2000; Gummerson, 1986). Melon seeds require relatively high temperatures for germination, which is optimal at 20
30 °C (Edelstein and Kigel, 1990). However, it was reported that the cardinal temperatures of melons is highly cultivar-dependent (Edelstein and Kigel, 1990). The germination temperature range of melon cultivars reported within the range of 12
45 °C (Kurtar, 2010; Edelstein and Kigel, 1990). The maximum final

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Table 5 Parameters of the thermal time model for prediction of Persian melon germination at each water potential at suboptimal and supraoptimal temperature ranges. Suboptimal temperature range (15
25 °C) Water potential level (MPa) 0 0.25 0.50 0.75 1 1.25 Overall

uT(50) (Log°C days)

Tb (°C)

1.54 1.58 1.67 1.79 2.10 2.58 1.84

9.4 9.4 9.4 9.4 9.8 9.8 9.4

s uT

R2

RMSE

0.89 0.85 0.82 0.83 0.82 0.80 0.33

17.8 20.2 22.3 22.5 32.8 44.3 58.6

(Log°C days) 0.13 0.22 0.36 0.38 0.48 0.54 0.38

Supraoptimal temperature range (25
40 °C)

0 0.25 0.50 0.75 1 1.25 Overall

uTC (°C days)

Tc(50) (°C)

s TC (°C)

R2

RMSE

41 42 51 59 78 189 45

41.4 41.3 40.3 39.5 37.2 36.2 37.0


7.1
7.2
7.3
7.5
7.7
8.2
7.3

0.96 0.93 0.92 0.86 0.73 0.33 0.67

13.4 16.1 18.7 28.8 45.2 81.1 60.5

germination percentage of watermelon was recorded at 20
30 °C, and the temperature ranges above and below 20
30 °C would reduce seed germination (Bakhshandeh et al., 2015). It also has reported that water potential had a strong inhibitory effect on seed germination (Alvarado and Bradford 2002; Bradford, 1995). A water potential threshold of
0.25 MPa, which begins to negatively affect melon germination, is in agreement with threshold value of
0.3 MPa that reported by Pinheiro et al., 2017. The interaction effect of T and C showed that the negative effect of water availability on seed germination increased at temperatures below and above the optimum temperature range. An interaction of T and C on the rate and percentage of seeds germination has been reported by many researches (Kebreab and Murdoch,1999; Wang et al., 2005; Bakhshandeh et al., 2015). The ability of seeds to germinate in a particular temperature range and water availability was positively correlated with the temperature range and soil water availability that a plant experience in the natal habitat (Cochrane et al., 2014; Bochet et al., 2007). The TT, HT and HTT models have been introduced as useful tools to quantify the germination behaviour of seed populations under varying environmental conditions (Allen et al., 2000; Bradford, 2002). Our study showed that the thermal time and hydrotime models could describe well the germination time course of melon seeds at various temperatures and water potentials, respectively. This is in agreement with previous studies on other species, suggesting that the most variation in seed germination timing could be explained by these models (Kebreab and Murdoch, 1999; Wang et al., 2005). Thermal time analysis showed that the values of Tb and Tc were 9.4 and 41.4 °C in water (0 MPa), respectively. However, the predictability performance of TT model and estimated values of parameters were associated with seedbed water availability. Indeed, seeds with lower Tb could accumulate more heat units in a given period of time, and would germinate faster than seeds with higher Tb. Knowing and comparing the thermal traits of species and cultivars can increase the ability of growers to fit a plant heat requirement into the available growing season window in each climatic condition. The previous studies showed that the base, optimum and maximum germination temperatures of melon genotypes were in the ranges of 10
15, 25
30 and 40
45 °C, respectively, and the cardinal temperatures varied among species and cultivars (Kurtar, 2010; Edelstein and Kigel, 1990). The field observations showed that the daily ambient air temperature must be above 11
12 °C for seedling emergence of Persian melon plants (unpublished data). It has been reported that the estimated

value of Tb based on filed data is generally higher than that obtained from laboratory data (Moot et al., 2000). In fact, seeds commonly incubate at a constant temperature in laboratory studies, but they experience a wide range of temperature fluctuations during the emergence period in fields. Gareca et al. (2012) reported that seeds under fluctuating temperatures accumulated less thermal time than under constant temperature conditions. The performance of TT model was reduced as water potential became more negative. Furthermore, thermal time required for germination of melon and Tb were increased with decrease in C, but Tc decreased when C became more negative. The increased Tb and decreased Tc associated with water stress would limit the temperature range of germination under water stress conditions. The most variation in the model parameters associated with varying C was related to thermal time constant compared with the other parameters. Under limited water supply, the increased Tb and thermal time would delay germination and could reduce final germination percentage. Previous researches on some plant species have shown that water availability could affect the estimated parameters in TT model (Kebreab and Murdoch, 1999; Gareca et al., 2012; Larsen et al., 2004). The hydrotime model accounted for the majority of the variation in germination timing at given temperatures. However, the accuracy of model prediction notably decreased at T below 20 °C and above 35 °C (RMSE > 32%). It has been reported that the hydrotime model worked well to characterize germination response to water potential in previous studies (Cheng and Bradford, 1999; Bradford, 2002; Gareca et al., 2012). The hydrotime analysis showed that the amount of hydrotime required for germination increased at the temperature ranges of below and above 25
30 °C. The increased hydrotime constant at sub and supra-optimal temperature ranges was reported in some previous studies (Cheng and Bradford, 1999; Gareca et al., 2012; Bakhshandeh et al., 2015).Our results also showed that the lowest value of the Cb(50) obtained at 25 °C, and shifted towards a higher values (less negative) with temperatures above or below 25 °C. The similar response of Cb(50) to temperature, with lower values at intermediate temperature range than either lower or higher temperatures, have been reported for watermelon (Bakhshandeh et al., 2015) and some other plant species (Kebreab and Murdoch, 1999; Alvarado and Bradford, 2002; Gareca et al., 2012). The increased Cb(50) in response to temperatures below and above optimum might be considered as an adaptive strategy, which would reduce the accumulated hydrotime required for germination and increase the probability of seed survival and seedling establishment under unfavorable conditions. Dutta and Bradford (1994) reported that the increased Cb at high incubation temperatures induced thermo-dormancy in lettuce seeds. Osmotic adjustment is generally considered as an adaptive strategy that helps seeds to survive in stressful conditions (Bradford, 2002; Baskin and Baskin 2014). Bradford (2002) showed that the germination time course of a seed population is controlled by the difference between C of seedbed and the Cb of seeds. Seeds with a lower Cb value will be faster to germinate and should be expected to have more drought-tolerant than seeds with a higher Cb value (Bradford, 2002). Therefore, the parameters of the hydrotime model can be used to characterize and compare germination behaviour of different species and cultivars (Allen et al., 2000). For example, based on the Cb(50) value obtained for muskmelon (Cucumis melo cv. Honey Dew;
0.64 MPa) by Casenave and Toselli (2010), it could be expected that Persian melon is more drought-tolerant than muskmelon at germination stage. Analysis of the combined effects of temperature and water potential using the HTT model was developed to explain the variation in germination timing across the combined range of temperatures and water potentials at which germination can occur (Gummerson, 1986). The hydrothermal time models, with a single value for Cb(50) (
1.19 MPa), explained a good proportion of germination variability below (RMSE= 24.1%) and above (RMSE=26.3%) optimum temperatures. Our result

S.F. Saberali and Z. Shirmohamadi-Aliakbarkhani / South African Journal of Botany 130 (2020) 1
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Fig. 3. Germination time courses for Persian melon seeds at supraoptimal temperatures (25, 30, 35, 40 °C) under water potentials of (A) 0, (B)
0.25, (C)
0.5, (D)
0.75, (E)
1.0, and (F)
1.25 MPa. The symbols indicate the observed germination data, and the lines indicate the germination time courses predicted by the thermal time model, based on parameter estimates in Table 5.

showed that the estimated optimum temperature was 27.3 °C in the HTT model. The optimum germination temperature predicted by an empirical model varied from 25.2 to 26.6 °C for different melon cultivars (Kurtar, 2010). Using the HTT model, Bakhshandeh et al. (2015) reported that the estimated optimum germination temperature was 28.3 °C for watermelon. The amount of hydrothermal time required to germinate increased by 33%, with increasing temperature from suboptimal temperature range (15
25 °C) to supraoptimal temperature (25
40 °C). The estimated single value for Cb and varying s ᴪb at below and above optimum temperatures is in agreement with previous estimates of

HTT parameters for watermelon (Bakhshandeh et al., 2015) and for potato (Alvarado and Bradford, 2002). In fact, the increase in seed base water potential at supraoptimal temperatures was taken into account with parameter of kT, which is the slope of the relationship between Cb and T in the supraoptimal range of T (Alvarado and Bradford, 2002). The value of kT was estimated from 0.08 to 0.12 MPa °C
1 for different plant species (Alvarado and Bradford, 2002; Gareca et al., 2012; Bakhshandeh et al., 2015), which this range covers the estimated value of 0.09 MPa °C
1 for Persian melon in current study. In order to simplify the modeling process, the hydrothermal time model assumes a fixed set of model parameters under any

8

S.F. Saberali and Z. Shirmohamadi-Aliakbarkhani / South African Journal of Botany 130 (2020) 1
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Fig. 4. Germination time courses for Persian melon seeds at a range of water potentials (0
1.25 MPa) and at temperatures of (A) 15, (B) 20, (C) 25, (D) 30, (E) 35, and (F) 40. The symbols indicate the observed germination data, and the lines indicate the germination time courses predicted by the hydrotime model, based on parameter estimates in Table 6.

germination condition in a seed population (Gummerson, 1986). Although, this study and some previous studies demonstrated that the parameters of the hydrothermal time model were highly affected by germination conditions and seed physiological status (Alvarado and Bradford, 2002; Bradford, 2002; Wang et al., 2005). Seed germination is the result of a balance between promotive and inhibitory hormones that are regulated by germination conditions (Baskin and Baskin 2014). Therefore, the expected change in the parameters of germination models under variable environmental conditions is consistent with the functional dynamics of plant growth.

Table 6 Parameters of the hydrotime model for prediction of Persian melon germination at each temperature. Temperature 10 15 20 25 30 35 40 45 Overall

uH (MPa days)

Cb(50) (MPa)

s ᴪb (MPa)

R2

RMSE


5.2 5 4.1 4.1 4.6 4.4
5.3



1.17
1.46
1.52
1.32
0.92
0.17

1.12


0.35 0.56 0.65 0.83 0.96 0.77
0.85


0.90 0.93 0.91 0.90 0.91 0.77
0.43


32.5 18.1 17.8 18.2 19.4 49.4
75.2

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Fig. 5. Germination time courses for Persian melon seeds at a range of water potentials and at suboptimal (left) and supraoptimal (right) temperatures. The symbols indicate the observed germination data, and the lines indicate the germination time courses predicted by the hydrothermal time model, based on parameter estimates in Table 7. The normalized thermal time courses of germination were calculated by multiplying the thermal time ((T
Tb)tg or (Tc
T)tg) by 1
(C/ Cb(g)).

Table 7 Parameters of the hydrothermal time model for prediction of Persian melon germination at the suboptimal and supraoptimal temperature ranges. Temperature range 15
25

25
40

uHT (MPa °C days)

Tb( °C)

33

Cb(50) (MPa)
1.19

9.4

s ᴪb (MPa)

R2

RMSE

0.44

0.90

24.1

uHT (MPa °C days)

Tb (°C)

To (°C)

KT (MPa °C
1)

Cb(50) (MPa)

s ᴪb (MPa)

R2

RMSE

45

9.4

27.3

0.09


1.19

0.59

0.89

26.3

5. Conclusion

Supplementary materials

Quantifying germination behaviour of seeds across a varying environment has been considered in ecological engineering. Hydrothermal time models were developed based on underlying physiology, which have parameters with a clear physiological meaning (Allen et al., 2000). Thus, the estimated parameters of HTT model allowed us to characterize the germination behavior of Persian melon seeds to temperature and water availability. The seed germination percentage notably was reduced by temperature and water stress, and germination delayed under unfavourable temperature and water availability conditions. Based on the models outputs, the cardinal temperatures of melon germination including base, optimum, and ceiling, were 9.4 °C, 27.3 and 41.4 °C, respectively. The estimated water potential threshold for 50% of the germinated seeds was
1.19 MPa with a standard deviation of 0.44 MPa. The results showed that the constancy of model parameters over all environmental conditions, as a basic assumption of hydrothermal time, was invalid for Persian melon. Seeds have a dynamic physiological mechanism to adjust the fraction of germinable seeds, germination rate and timing, which contribute to survival in varying environments. If accurate prediction of germination time in a complex environmental conditions is the objective, then we should accept varying model parameters with changing conditions.

Supplementary material associated with this article can be found in the online version at doi:10.1016/j.sajb.2019.12.024.

Declaration of competing interest The authors declare no conflicts of interest. Acknowledgements This work has been financially supported by the vice-chancellor for research of University of Torbat-e Jam.

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