Quantifying Osmotic Stress and Temperature Effects on Germination and Seedlings Growth of Fenugreek (Trigonella foenum-graecum L.) via Hydrothermal Time Model

Abstract

Germination models are really useful in predicting seed germination, attributed to their application in economic crop management. Hence, we evaluated cardinal temperatures (Ts), seed germination behavior, and model coefficients of fenugreek under varying temperatures (Ts; 10, 20, 30, and 40 °C) and water potentials (ψ_s 0, −0.01, −0.02, and −0.05 MPa). We observed that the maximum and minimum hydrotime constant (θH) values at 20 °C, respectively. The base water potential at 50 percentiles (Ψb 50) exhibited an asymmetrical pattern with the highest (−0.9 MPa) value computed at 40 °C and the lowest (−0.13 MPa) at 10 °C. Furthermore, the ceiling temperature (TC), base temperature (Tb), and optimal temperature (To) of Fenugreek were determined to be 34.5 °C, 7.8 °C, and 18 °C, respectively. In addition, we observed that germination index, germination rate index, germination percentage, germination energy, Timson germination index, seed vigor index I and II, and root-shoot ratio are at their highest values at 20 °C and lowest at −0.05 MPa at 40 °C. Based on our findings, we suggest that the hydrothermal time model (HTT) can be used to explore the independent and synergistic effects of both T and ψ on the germination of seeds in different environmental conditions. The obtained model coefficients indicate that fenugreek is temperature-sensitive and suitable for agriculture in irrigated regions.

1. Introduction

Fenugreek (Trigonella foenum-graecum L.) is a herbaceous plant species that belongs to the family Leguminosae. It is cultivated in different countries various worldwide, including Pakistan, India, Canada, China, Egypt, Greece, Turkey, and Morocco [1]. As a multipurpose crop, it is used as a culinary spice, a condiment to flavor different syrups, and in manufacturing steroids and other hormones utilized in the nutraceutical, pharmaceutical, and functional food industries [2]. Fenugreek seeds and leaves contain volatile essential oils that are used for various medicinal purposes, including anti-diabetes, anti-cancer, antimicrobial, etc.). Further, it is also used to produce edibles, pesticides, and perfume in different countries [3]. There is no doubt that the germination of seeds is a complex physiological scenario that is sensitive to external factors, including salinity, water potential, drought, and temperature [4,5,6,7,8,9]. The development of germination models has led to a better understanding of why and seeds germinate differently in varying environmental conditions.

Seed germination and early seedlings’ growth are the most sensitive phases in a plant’s life cycle, which depend on the genetic makeup and environmental stress factors. For instance, temperature and osmotic potential are the two most important factors influencing the germination of seed [10]. Because of the relationship between seed germination, temperature, and dormancy, a rise in temperature can have a diminishing impact on the emergence and establishment of plant species. It is widely known that temperature influences seed germination (SG) [11]. The values of three cardinal Ts of SG must be understood when determining the suitable planting date for species, namely Tb (stands for low temperature; SG = zero); To (stans for optimal temperature; SG = maximum); and Tc (stands for ceiling temperature; SG = zero) [12,13]. A lack of water is a major concern for seed germination, seedlings growth, and productivity as a result of fluctuations in temperature, rainfall, and atmospheric humidity [14]. Several basic aspects of crop plants, including Fenugreek, require a deeper understanding to optimize their management in changing climate conditions, including their geographic locations and the behavior and physiological metabolism of germinating seeds. Therefore, the understandings and use of germination models are effective in forecasting the phenomenon of seed germination and subsequent seedling emergence in response to changing temperatures and water availability.

For example, the thermal time model (TT) determines the impact of varying Ts on seed germination, whereas hydrotime models (HT) estimate how ψ affects seed germination [15]. Further, the results of both the TT and HT models may help the investigators to evaluate the attributes of seed succession attributes. Hydrothermal time models assess the synergistic effect of Ts and ψ on seed germination [16]. HTT is a useful and important population-based threshold model that describes germination times to varying ψ and T in the supraoptimal range (To to Tc) and suboptimal range (Tb to To) [17]. There have been reports of plants adopting the HTT model approach, including Carthamus tinctorius L. [18], Lathyrus sativus max L. [19], Eruca sativa L. [8], Hordeum vulgare L. [9], and Triticum aestivum L. [12]. Considering the impact of temperature and water availability on fenugreek cultivation in semi-desert regions, the research objectives were as follows: Considering the effects of temperature and water availability on fenugreek cultivation in semi-desert regions, the research objectives were as follows, (i) to determine seed germination rate, and its related attributes, seedlings length in response to varying T and ψ, independently or synergistically (ψ × T), (ii) to evaluate osmotic tolerance threshold and (iii) to compute the cardinal temperatures of fenugreek via HTT coefficients.

2. Materials and Methods

2.1. Experimental Protocol and Seed Germination

We obtained Fenugreek seeds (97% viability rate) from Nuclear Institute for Food and Agriculture (NIFA), Peshawa, Pakistan. We selected healthy seeds of similar size and shape, surface sterilized them (91% ethanol) for 2 min, then washed them with distilled water and shade dried them at room temperature [20]. A complete block design (CBD) experiment was conducted in Petri dishes at the Department of Botany, University of Peshawar, KP, Pakistan, between October and December 2021. The fenugreek seeds were subjected to four constant Ts (10, 20, 30, and 40 °C) and four ψ_s (0, −0.01, −0.02, and −0.05 MPa) by using an incubator (Memmert Beschickung-Loading Model 100–800). The Petri dishes contained 40 seeds, which were moistened with double distilled water (0 Mpa) and polyethylene glycol (PEG-6000) at four varying concentrations. The treatments were replicated three times, with the data being collected daily for five consecutive days. Germination time courses were analyzed at various accelerated aging periods, and the parameters of thermal time (TT), hydro time (HT), and hydrothermal time (HTT) models were determined using repeated Probit regression analysis [17,18]. We determined the fresh and dry weights based on the inverse of the times to radicle development and germination for specific percentiles of seed populations.

2.2. Data Analysis

Repeated Probit regression was used to analyze germination data using the HT, TT, and HTT germination models [16,21].

2.3. Thermal Time (TT) Model

Based on the HTT model concept, the supra and suboptimal (Ts) were obtained as follows.

$${\mathrm{TT}}_{\mathrm{sub}}=\left(\mathrm{T}-\mathrm{Tb}\right)\mathrm{tg} (\mathrm{suboptimal} \mathrm{T})$$

(1)

$${\mathrm{TT}}_{\mathrm{supra}}=\mathrm{Tc}\left(\mathrm{g}\right)-\mathrm{T}) \mathrm{tg} (\mathrm{supra}-\mathrm{optimal} \mathrm{T})$$

(2)

Therefore, seed emergence is indirectly proportional to germination rate, and Equations (1) and (2) can be combined to drive Equation (3):

$${\mathrm{TT}}_{\mathrm{sub}}=1/\mathrm{tg}=\left(\mathrm{T}-\mathrm{Tb}\left(\mathrm{g}\right)\right)/\theta \mathrm{T}$$

(3)

where TT_sub and TT_supra represent the thermal time constant, Tb represents the base temperature for germination fraction, T exhibits temperature, and g represents the actual time to germination fraction.

2.4. Determination of Hydro Time (HT) Model

To improve the model prediction, the proposed hydro time constant (HT) was utilized, which determines the relationship between the solute potential (PEG) and germination rate (tg). The hydro time model was determined as suggested previously [21]:

$${\theta \mathrm{H}}_{\left(\mathrm{g}\right)}=\left(\mathsf{\psi }-\mathsf{\psi }\mathrm{b}\right)\mathrm{tg}$$

(4)

$$\mathrm{GR}\left(\mathrm{g}\right)=1/\mathrm{tg}=\left(\mathsf{\psi }-\mathsf{\psi }\mathrm{b}\right)/\theta \mathrm{H}$$

(5)

where GR(g) is the germination rate, tg is the seed population time for radicle emergence, and θH is the hydro time constant (MPa·h). Moreover, Ψ and Ψb stand for water potential and the base water potential, respectively.

2.5. Determination of Hydrothermal Time Model (HTT)

We can combine the HT and TT models into a new HTT model for calculating and characterizing SG responses to various T and Ψ. The hydrothermal time model can report tg at all Ψ and T in the sub-opt T (from Tb to To).

$$\theta \mathrm{HTT}=\left(\mathsf{\psi } \mathrm{b}\left(\mathrm{g}\right)- \mathsf{\psi }\right)\left(\mathrm{T} -\mathrm{Tb}\right)\mathrm{tg},$$

(6)

For further analysis, Equation (7) is a modified version of Equation (5).

$$\theta \mathrm{HTT}= \left[\mathsf{\psi } \mathrm{b}\left(\mathrm{g}\right)- \mathsf{\psi } – \left(\mathrm{kT} \left(\mathrm{T}-\mathrm{To}\right)\right)\right]\left(\mathrm{T}-\mathrm{Tb}\right)\mathrm{tg},$$

(7)

2.6. Determination of Germination Parameters

Based on the germination rate, plumule length, radicle length, and dry and fresh weight of plumules and radicles, the following indices were calculated.

2.6.1. Determination of Germination Percentage (G%)

We calculated the G% as follows [22].

$$\mathrm{Germination} \mathrm{Percentage} (\mathrm{G}\%)=\frac{\mathrm{Final} \mathrm{number} \mathrm{of} \mathrm{seedlings} \mathrm{emerged}}{\mathrm{Total} \mathrm{number} \mathrm{of} \mathrm{seeds} }\times 10$$

(8)

2.6.2. Determination of Seed Vigor Index I (SVI-I)

SVI-I was calculated according to a method [23]:

$$\mathrm{SVI-I}=\mathrm{Seedlings} \mathrm{length}\left(\mathrm{cm}\right)\times \mathrm{Seed} \mathrm{Germination}$$

(9)

2.6.3. Determination of Seed Vigor Index II (SVI-II)

Seed vigor index II was calculated as follows [24]:

$$\mathrm{SVI-II}\mathrm{Seed} \mathrm{dry} \mathrm{weight} \left(\mathrm{mg}\right)\times \mathrm{Seed} \mathrm{Germination}$$

(10)

2.6.4. Determination of Root-Shoot Ratio (RSR)

The shoot and root were weighed after drying for 24 h in the oven. The RSR was recorded according to the following equation [25].

$$\mathrm{RSR}=\frac{\mathrm{root} \mathrm{dry} \mathrm{weight}}{\mathrm{shoot} \mathrm{dry} \mathrm{weight}}$$

(11)

2.6.5. Determination of Mean Germination Time (MGT)

The MGT was determined as follows [26].

$$\mathrm{MGT}=\frac{\in \mathrm{fx}}{\in \mathrm{f}}$$

(12)

2.6.6. Determination of Mean Germination Rate (MGR)

The MGR was calculated using the following equation [27]:

$$\mathrm{MGR}=\frac{1}{\mathrm{MGT}}$$

(13)

2.6.7. Determination of Coefficient of Variation of Germination Time (CVt)

The value of CVt was determined using the following equation [27]

$$\mathrm{CVt}=\left(\frac{\mathrm{St}}{\mathrm{tm}}\right) \times 100$$

(14)

2.6.8. Determination of Coefficient of Velocity of Germination (CVG)

CVG exhibits the seed germinate rate, and it was calculated as follows [27].

$$\mathrm{CVG}=\frac{\mathrm{N}1+\mathrm{N}2+\mathrm{N}3\dots \mathrm{Nx}}{100}\times \mathrm{N}1\mathrm{T}1\dots \mathrm{NxTx}$$

(15)

2.6.9. Determination of Germination Rate Index (GRI)

The germination rate index (GRI) reflects the percentage of seeds germinating at a particular time and day. It was calculated as follows [28].

$$\mathrm{GRI}=\frac{\mathrm{G}1}{1}+\frac{\mathrm{G}2}{2}+\frac{\mathrm{G}3}{3}\dots \frac{\mathrm{Gx}}{\mathrm{x}}$$

(16)

2.6.10. Determination of Germination Energy (GE)

The germination energy (GE) was determined using the following formula [29].

$$\mathrm{GE}=\frac{\mathrm{X}1}{\mathrm{Y}1}+\left(\frac{\mathrm{X}2-\mathrm{X}1}{\mathrm{Y}2}\right)+\left(\frac{\mathrm{Xn}-\mathrm{Xn}-1}{\mathrm{Yn}}\right)$$

(17)

2.6.11. Determination of Timson Germination Index (TGI)

The TGI index was determined using the following method [30].

$$\mathrm{TGI}=\frac{\in \mathrm{G}}{\mathrm{T}}$$

(18)

where G denotes the germination percentage, and the time for germination is denoted by T.

2.6.12. Determination of Time to 50% Germination (T50%)

T50% was determined using a mathematical formula [31].

$${\mathrm{T}}_{50\%}=\frac{\mathrm{ti}+\left(\frac{\mathrm{N}}{2}-\mathrm{ni}\right)\left(\mathrm{tj}-\mathrm{ti}\right)}{\left(\mathrm{nj}-\mathrm{ni}\right)}$$

(19)

2.7. Statistical Analysis

An analysis of variance (ANOVA) was conducted to investigate the effects of temperatures (TT model), water potentials (HT model), as well as their interactive effects (HTT model) on the germination of our test species using IBM SPSS Statistics 26. Further, Excel was used to perform the fundamental statistical computations. The germination parameters (n = 3) were used to analyze the analysis of variance. Linear Probit regression analysis was followed to find out the values of the following parameters: θH, σΨb, ψb₅₀, R, R², SE, F, and Sig. in SPSS.

3. Results

3.1. Evaluation of Germination Coefficients

Our results indicated that varying water potentials (ψ_s) and temperatures (T) values influence germination rate and percentage of fenugreek (p < 0.05) independently and interactively (ψ × T). Furthermore, as estimated from the osmotic tolerance threshold using the HTT, the high θH and R² values were obtained at 20 °C optimal temperature and minimum at 40 °C ceiling temperature, respectively. When compared to 0 MPa (distilled water controlled), the highest TT_sub value was found at −0.02 MPa at 20 °C, and the TT_supra value was observed at 30 °C is −0.05 MPa. Moreover, the values of GR(g) exhibit statistically significant (p < 0.01) increment with lowering Ψ at all T. Further, at all Ts, the standard deviation σψb values showed substantially fewer changes. Hence the highest and lowest σψb were recorded at 20 °C and 40 °C, respectively. In addition, the maximum base water potential in 50% germination (ψb50) was also at −0.05 MPa. The coefficient of determination (R) and variability between the means values (F) was also noted to be lowest and highest at 40 °C and 20 °C, respectively. For fenugreek seed, the HTT model shows a base temperature of 7.8 °C, an optimum temperature of 18 °C, and a ceiling temperature of 34.5 °C as the germination temperature.

The HTT model for fenugreek seed exhibits a base or minimum temperature of 7.8 °C, an optimum temperature of 18 °C, and a ceiling temperature of 34.5 °C. Thus, the germination at suboptimal T may be described using thermal time, or T greater than Tb multiplied by time to a certain germination percentage (tg). Moreover, the seed germination of Fenugreek was significantly affected by T and Ψ (p ≤ 0.05). Further, the rate and speed of germination decrease when the water potential decreases.

3.2. Temperature and Water Potential Effects on Germination Attributes

Our study exhibits that the germination percentage (G%) of Trigonella foenum-graecum is significantly affected by the independent or interactive effect of T and Ψ (T × Ψ). At optimum osmotic potential (control), the lowest G% was observed at 40 °C, whereas the highest was at 20 °C. In general, the maximum germination of 76.6% was perceived at 20 °C under −0.01 MPa and a minimum of 30% at 40 °C under −0.05 MPa, irrespective of the distilled water (0 MPa). Hence, G% reduces with decreasing the Ψ at each T, as the G% surged with the accelerated aging period (AAP) and dropped considerably (p ≤ 0.05) with increasing T. Moreover, results obtained from the HTT parameters showed that germination parameters of fenugreek were significantly affected by T and Ψ (Figure 1, Figure 2, Figure 3 and Figure 4). For instance, the G%, SVI-II, SVI-I, and RSR were optimum in seeds subjected to 20 °C induced with distilled water (0 MPa), followed by second maximum values at 20 °C induced in −0.01 MPa (Figure 2).

In addition, the highest mean germination time was recorded at 10 °C induced with −0.05 MPa, while the lowest at 30 °C induced with distilled water (Figure 2). Similarly, the MGR was determined as the reciprocal of MGT, and the CVG was noticed to be highest at 30 °C induced with distilled water (0 MPa). The highest CVt was observed at 30 °C at −0.01 and the minimum at 40 °C induced with distilled water. Moreover, Figure 4 illustrates that the highest and lowest GE, GRI, and TGI were observed at 20 °C in −0.01 MPa and 40 °C in −0.05 MPa, indicating that increasing T and ψ there would be a significant reduction in the growth phases of the germinating seed.

4. Discussion

Germination patterns are assessed under different environmental conditions in order to determine a species’s optimal geographical location for a species. The population-based threshold model, commonly known as the HTT model, reflects the noticed responses of germinating seeds to stress, hormones, age, and other factors. The population-based threshold model, commonly known as the HTT model, reflects the observed response of germinating seeds to stress, such as temperature and water availability [8]. In the present experiment, we investigated cardinal temperatures (Ts), seed germination behavior, and model coefficients of fenugreek under varying temperatures (Ts; 10, 20, 30, and 40 °C) and water potentials (ψ_s 0, −0.01, −0.02, and −0.05 MPa) via HTT model. We found that θH values for Fenugreek increased with an increase in Ts up to To (optimal temperature), then fell linearly with a decrease as Tc > To. T is one of the most important factors that can affect seed germination in many plants [32]. The same results in which the θH values were increased with increasing temperature up to To were documented in previous studies [8,32,33], corroborating our findings. Moreover, it has been reported that both germination percentage (G%) and time to 50% germination (GR₅₀) decreased with decreasing osmotic potential and with increasing osmotic potential in the medium at each tested T [33]. The results also demonstrated that at all Ts, GR(g) values enhanced (p ≤ 0.01) with negative Ψ (

Table 1. Calculated model coefficients of Trigonella foenum-graecum via hydro time concept to describe seed germination under different Ts and Ψs.

Fenugreek	T	θH	σΨb	Ψb(50)	R	R2	SE	F	Sig.
		(MPah−1)	(MPa)	(MPa)
	10 °C	1.66	0.9	−0.13	0.858	0.735	1.09	5.556	0.142
	20 °C	2.11	0.13	−0.18	0.925	0.855	0.71	11.8	0.075
	30 °C	1.87	0.11	−0.15	0.888	0.789	1.03	7.494	0.112
	40 °C	1.32	0.5	−0.9	0.472	0.223	1.2	0.573	0.528

θH = hydro time constant, Ψb(50) = base water potential at 50 percentiles, σΨb = standard deviation of base water potential, R and R² = coefficient of determination, SE = standard error, F = variability between different means, Sig = significant value.

). A decrease in ψ also decreased the germination rate in comparison with the control condition. Moreover, the effect of ψ on G% and GR was more than AAP [34]. Seeds have a base or minimum temperature (Tb = at which germination reduces), an optimal temperature (To, at which germination is normal), and a ceiling temperature (Tc, above which germination is halted). Furthermore,

Table 2. Estimated parameters of Trigonella foenum-graecum using hydrothermal time model for describing seed germination under different Ts and Ψs.

Hydrothermal Time Model Parameters
Variables	Trigonella foenum-graecum L.
Ψb(50) (MPa)	0.18
σΨb (MPa)	0.13
θH (MPa °C h−1)	2.11
kT (MPa °C h−1)	0.102
Cardinal Temperature
Tb (°C)	7.8
To (°C)	18
Tc (°C)	34.5
R2	0.855

kT = thermal energy of the seed, Tb = base temperature of the seed, To = optimum temperature of the seed, Tc = ceiling temperature of the seed.

shows that the Tb for fenugreek is 7.8 °C, beyond which the GR declines, and it becomes impossible for a plant to optimize its physio-biochemical activities [33]. Moreover, To for maximal Fenugreek germination was 28 °C, whereas the Tc value was 34.5 °C, indicating that fenugreek cannot continue its physio-biochemical activities above this range. Our findings agree with the results of Hatfield and his colleagues, who demonstrated that the aforementioned three checkpoints of temperature affect seed germination [32].

The predictions at the significance level (p ≤ 0.05), the germination parameters of fenugreek were significantly affected by T and Ψ. We observed that T and Ψ independently as well as interactively (T × Ψ) caused significant effects on GR and G%. of the seed germination as the maximum G% of 76.6% was reported at 20 °C under −0.01 MPa and a minimum of 30% at 40 °C under −0.05 MPa, irrespective of the distilled water (0 MPa). It means that G% reduces with decreasing in Ψ at each T value. The G% declines in conjunction with a reduction in Ψ, indicating a reduction in water availability for resource seed germination. Our findings align with previous studies that reported that T is a key factor affecting G% [35] and GR [36]. Furthermore, osmotic potential stress is another key environmental element restricting seed germination and early seedling growth. Moreover, the results also revealed a significant decrease in G% with high T and an increase in the accelerated aging period (AAP).

The G% decreased with a decrease in ψ from 0 to −0.01, −0.02, and −0.05 MPa compared with distilled water (0 MPa) by 93.3%, 76.7%, 46.7%, and 56.7%, respectively, i.e., the average for all levels of AAP. Similar findings were reported by previous studies that reported a longer accelerated aging period and lower ψ (more negative) decreased both G% and GR in various crops [8,9,12,37].

In addition, Figure 2, Figure 3 and Figure 4 illustrate that the maximum G%, SVI-I, SVI-II, RSR, GE, GRI, and TGI were observed at 20 °C at −0.01 MPa. The minimum values of G%, SVI-I, SVI-II, RSR, and CVG were noted at 30 °C at −0.05 MPa. Further, the highest MGT and lowest MGR values were recorded at 10 °C at −0.05 MPa. In contrast, the lowest MGT, highest MGR, and CVG values were observed at 30 °C in distilled water, indicating that with an increase in T and ψ, there is a significant decline in the growth cycles of the germinating seed. These findings corroborate previous studies, which reported that temperature is a key factor affecting SG [13,38]. In addition, the differences in ψ_s affect and hinder SG differently via osmotic and ion-specific effects [39]. For instance, low ψ_s may hinder chemical reactions and physiological mechanisms within the seed, inhibiting seed germination [35]. Hence, salinity and variation in T and ψ affect SG independently or interactively. Identifying their impact on seed germination and early seedlings’ emergence is vital for optimum agricultural yield and species ecological ranges [40].

5. Conclusions

Our study concluded that the germination time course of fenugreek is precisely anticipated using the hydrothermal time model of Fenugreek (Trigonella foenum-graecum) in response to varying Ts and Ψ_s. The maximum and minimum θH and R² values were recorded at 20 °C and 40 °C, respectively. The Ψb₅₀ was predicted as −0.18 MPa, the value of σΨb was 0.13 MPa at kT 0.102 MPa, and the cardinal Ts were recorded as 10 °C (Tb), 20 °C (To), and 40 °C (Tc). Through the finding of germination parameters (G%, SVI-I, SVI-II, RSR, MGT, MGR, CVt, CVG, GE, GRI, TGI, and T_50%) of fenugreek were recorded maximum at the 20 °C is −0.01 MPa whereas their value recorded at 30 °C is −0.05 MPa. Our study determined that the HTT provided an understanding of the synergistic effect of T and Ψ on the seed germination of Fenugreek. Considering future climate change and rising food demands, predicting germination models might provide an understanding of the ideal conditions for the optimum germination, growth, and productivity of the economy. A more detailed examination of the parameters of the model should be carried out in conjunction with a study of the physiological responses of the Fenugreek seed populations to environmental stress.