The individual effect of external application of GA3 and ABA on seed germination
The seeds were externally treated with six different concentrations each of GA
3 and ABA ranging from 5 mg/L to 125 mg/L. All the seeds treated with ABA showed a poor percentage of germination. But the seeds treated with GA
3 showed a better rate of germination. Paired t-test showed that the percentage of germination is significantly higher in GA than ABA at 1% level of significance (Table 1). At 10 mg/L GA
3 concentration more than 90 of the seeds germinated. But at higher concentrations, the rate of germination began to decline.
In this work, when ABA and GA were externally given, separately, all the ABA treated seeds showed a poor percentage of germination while the seeds treated with GA
3 showed a better rate of germination, especially at 10 mg/L GA
3 concentration.
Mukherjee (2016) reported better seed germination rate in Swertia seeds pre-soaked with GA
3. Increased rate of germination of Guava seeds was also reported by the exogenous treatment with GA
3 and this has been attributed to the fact that either GA
3 might have involved in the activation of cytological enzymes which stimulate seed germination of an amylase enzyme for converting insoluble starch into soluble sugars or might have antagonized the effect of inhibitors present in seeds
(Kalyani et al., 2014). It has been reported by Copeland and
Mc Donald (1995) that GA induces
de novo synthesis of proteolytic enzymes like Amylase and ribonuclease. Amylases hydrolysing starch and providing essential sugars for growth initiation processes and liberating chemical energy which is used in the activation of the embryo as well as suppression of inhibition. But at higher concentrations of GA, the rate of germination began to decline. This can be due to GA toxicity at higher levels. According to
Chetouani et al., (2017), a surplus of GA used has been considered as an onset of toxicity.
The combined effect of different concentrations of GA3 and ABA on seed germination
No seed germinated in sample 3 and hence it is not considered for the analysis of significance in the difference in the percentage of germination. Analysis of variance of repeated measures is administrated to compare the significance of differences in the germination of seeds among control, S1 and S2 and among days. There is a significant difference in the mean percentage of germination among samples (F=180.942, p-value <.01) at 1% level of significance. Also, there is a significant difference in the mean percentage of germination among days (F=76.94, p-value <.01) at 1% level of significance. The estimated mean germination in control is 52.29%, in S1 is 55.29% and in S2 is 82.43% and Duncan’s post hoc multiple comparison test shows that there is no significant difference in germination in between control and S1 but the number of germinations is significantly higher in S2 than control and S1 at 5% level of significance. The one-way ANOVA showed that there is a significant difference in the percentage of germination on all days among various treatments (control, S1, S2) at a 1% level of significance (Table 2).
When the combined effect of GA
3 and ABA on germination and growth, was studied against a control (distilled water), sample 3 (S3) showed almost no response as it had a greater concentration of ABA. Sample 1 and 2 (S1 and S2) showed a better response when compared to Control (C) that is, distilled water, where S2 showed the best response with respect to C and S1. It can be seen that GA when present in same or more level, than ABA, suppressed the physiological inhibition caused by ABA. Similar results were obtained in the seeds of
Phellodendron amurense var. wilsonii, where exogenous ABA inhibited germination, but the addition of GA
3 balanced the ABA effect and promoted germination
(Chen et al., 2009). The inhibitory effects of ABA on seed germination are through delaying the radicle expansion and weakening of endosperm, as well as the enhanced expression of transcription factors, which may adversely affect the process of seed germination
(Graeber et al., 2010). Application of certain exogenous hormones may correct a deficiency in the endogenous level of that hormone or change the balance of hormones in the seed.
Toyomasu et al., (1994), showed that the endogenous ABA contents were reduced by GA
3 treatment in lettuce seeds. There are studies revealing the antagonistic effects of GA on the expression of ABA-inducible genes in dormant beechnut seeds
(Nicolas et al., 1997; Lorenzo et al., 2001).
The combined effect of different concentrations of GA3 and ABA on seedling growth
Growth parameters like length of the radicle, length of the plumule, number of leaves emerged as well as the length and width of the leaves were analysed to study the combined effect of GA
3 and ABA on growth.
Length of the plumule
Analysis of variance of repeated measures was administrated to compare the significance of differences in the mean Plumule length among control, S1 and S2 and days (Table 3). There was a significant difference in mean plumule length among days and among samples at 1% level of significance. The estimated mean plumule length in control was 2.392 cm, in S1 was 3.955 cm and in S2 was 6.29 cm and Duncan’s post hoc multiple comparison test showed there is a significant difference in mean plumule length in S2 than control and S1 at 5% level of significance. There was a significant difference in the mean plumule length on days 9,10,11,13,16 and 19 among various treatments (control, S1, S2) at 1% level of significance, as shown by one-way ANOVA.
Length of the radicle
A significant difference in mean radicle length among days (F=64.477) and among samples (F=18.983) at 1% level of significance can be found. The estimated mean radicle length in control was 3.6 cm, in S1 was 6.22 cm and in S2 was 7.97 cm and Duncan’s post hoc multiple comparison tests showed a significant difference in mean radicle length at 5% level of significance along with all the three pairs (Table 3). The one-way ANOVA showed that there was a significant difference in the mean radicle length on days 9,10,11,12,16 and 19 among various treatments (control, S1, S2) at a 1% level of significance. On day 13 and 15, it was significant at 5% level of significance.
Number of leaves
There was a significant difference in the mean number of leaves among days (F=57.569) and among samples (F=14.396) at 1% level of significance. The estimated mean number of leaves in control was 2.4, in S1 was 3.633 and in S2 was 4.267 and Duncan’s post hoc multiple comparison test showed a significant difference in the mean number of leaves in S1 and S2 and significantly more than control at 5% level of significance (Table 3). There was a significant difference in the mean number of leaves on days 12 among various treatments (control, S1, S2) at 5% level of significance as shown by one-way ANOVA. On day 16, it was significant at 5% level of significance.
Length of leaves
The difference in mean leaf length among days (F=40.717) was significant at 1% level of significance and among samples (F=4.662) significant at 5% level of significance. The estimated mean leaf length in control was 1.863 cm, in S1 was 2.217 cm and in S2 was 3.930 cm and Duncan’s post hoc multiple comparison tests showed a significant difference in mean leaf length in S2 than control and S1 at 5% level of significance. The one-way ANOVA showed that there was a significant difference in the mean leaf length on days 11,12 and 15 among various treatments (control, S1, S2) at a 1% level of significance. On day 13, it was significant at 5% level of significance and on the day 15 at 10% level of significance (Table 3).
Width of leaves
The estimated mean leaf width in control was 1.02 cm, in S1 was 1.065 cm and in S2 was 2.12 cm and Duncan’s post hoc multiple comparison tests showed a significant difference in mean leaf width in S2 than control and S1 at 5% level of significance. A significant difference in mean leaf width among days (F=13.338) significant at 1% level of significance and among samples (F=8.121) significant at 1% level of significance can be found. The one-way ANOVA showed that there was significant difference in the mean leaf width on days 13 and 15 among various treatments (control, S1, S2) at a 1% level of significance. On day 16, it was significant at 10% level of significance (Table 3).
GAs and ABA are plant growth regulators, that act in an antagonistic manner to control plant developmental processes, like root and stem elongation, floral induction, anther development and seed germination (
Yamaguchi 2008). It has been reported by
Philosoph-Hadas et al., 2005 and
Kucera et al., 2005, that germination is regulated by a balance between the relative amounts of endogenous GA
3 and ABA in seeds. GA levels normally decrease and ABA increase during later stages of orthodox seed maturation and very high levels of GA causes precocious germination
(White et al., 2000). The GA and ABA antagonistic crosstalk comprises two main aspects, one is the metabolic homeostasis of ABA and GA, which are controlled by distinct regulators in response to specific endogenous and environmental signals, leading to opposite patterns of ABA and GA accumulation and the other one is the direct molecular interaction between core ABA and GA- signaling components, which orchestrates a rapid and efficient response to developmental changes and external challenges by quickly mediating the antagonistic interaction of ABA and GA
(Vishal et al., 2018). It is well known that GA
3 and ABA are antagonistic in action especially in physiological processes like seed germination and growth, GA
3 promoting it and ABA retarding the same process (
Kermode, 2005). Phytohormones and plant growth regulators have been used as pre-sowing seed treatment agents (
Nascimento 2003,
Tiwari et al., 2011). According to
Shu et al., (2016), the interactions of diverse hormonal signals in seed dormancy and germination maybe by the ABA: GA balance.
In the present study, all growth processes like seed germination and development, stimulation of stem and root growth, increase in the number and size of leaves, increase of seed germination rate, all are found to be better in a combination where GA is more than or equal to ABA level when compared to control. Exogenous GA application and enhanced seedling growth were also reported in other experiments
(Khan et al., 2003, Tiwari et al., 2011, Khodadadi et al., 2018). Exogenous application of GA
3 was reported to be highly effective for plumule growth in
Withania somnifera (Kumar et al., 2012). It can be assumed that the exogenous GA enhances the ABA catabolism.
Schmitz et al., (2002) suggested that dormancy-breaking treatments including GA
3 applications enhance ABA degradation in yellow-cedar seeds. Keeping a low level of ABA in the embryo is a strategy shown by many recalcitrant and viviparous seeds to facilitate faster germination without dormancy
(Prajith et al., 2017). According to
White et al., (2000), high levels of GA have been associated with vivipary and desiccation sensitivity in the case of recalcitrant seeds. During later stages of orthodox seed maturation, GA levels are normally decreased and those of ABA increased. At seed maturation, ABA is responsible for the acquisition of desiccation tolerance in orthodox seeds
(Gutierrez et al., 2007). However, this cannot be seen in recalcitrant seeds like
Vateria indica L. Recalcitrant seeds do not have any mechanisms that facilitate the acquisition and maintenance of desiccation tolerance as orthodox seeds (
Berjak and Pammenter, 2013).