3.1. Biosynthesis of ZnNPs using Crassula multicava leaf extract
The Zinc nanoparticle reaction mixture was incubated for about 24 hours. The reduction of zinc ions to zinc nanoparticles was monitored by a color change of the reaction mixture, which was observed after incubation (Paul et al., 2016). This indicated the synthesis of zinc nanoparticles (Figs. 1 & 2). Noorjahan et al., (2015) used Neem (Azadirachta indica) leaf extracts for the synthesis of zinc nanoparticles. Due to the Surface Plasmon Resonance phenomenon, a color change from pale white to brown happened as a result of exposure to leaf extracts, which allowed researchers to detect the reduction of zinc ions into zinc nanoparticles. The metal nanoparticles have free electrons, which helps in the formation of the Surface Plasmon Resonance absorption band, which is due to the united vibration of the electrons of metal nanoparticles in resonance with light waves. Using plant extract to synthesize metal oxide is of significant advantage due to the production of functional molecules that reduce metal ions (Rai & Ingle., 2012). Phenols, terpenoids, ketones, aldehydes, and amides are the primary phytochemicals involved in nanoparticle synthesis (Sundrarajan et al., 2011).
3.2. UV-Vis Spectrophotometry Analysis of Nanoparticles
The UV-Vis spectra showed peaks at 300 nm, 340nm and 360nm which are corresponding to ZnO nanoparticles. For ZnO nanoparticles, the absorbance peak is reported between 310 nm and 360 nm of wavelength (Ghamsari et al., 2017). After the addition of aqueous salt (ZnSO₄) into leaves extract (Crassula multicava), the spectra were taken at a different time interval (0 hrs, 24 hrs, 48 hrs, 72 hrs, 96 hrs, 120 hrs) between 200 nm to 800 nm (Fig. 3). The peak demonstrates the presence of ZnO Green Nps in the reaction mixture (Santhoshkumar et al., 2017; Jayachandran et al., 2021).
3.4. EDX Analysis of Nanoparticles
The elemental composition analyses of the ZnNPs from the EDX plot of the FESEM images are shown in Fig. 5, where the X-axis shows energy in KeV and the Y-axis depicts intensity count. From the EDX spectrum, the presence of Zn elements was determined from the ZnK peak at ~ 1.2 keV which confirmed the existence of ZnNPs in the sample. The carbon, oxygen, calcium, magnesium, chlorine and potassium could be the elements from the proteins or compounds present in the plant extracts, whereas the presence of sulphur could be due to the use of ZnSO₄ as the precursor for the synthesis of ZnNPs (Singh et al., 2022). The EDX Analysis of synthesized ZnNPs revealed that the elemental and quantitive weight composition of nanoparticles constituted are carbon 36.20%, oxygen 39.05%, calcium 10.34%, sulfur 6.99, zinc 3.58, magnesium 2.83, chlorine 1.01% (Table 1).
Table 1
Results of elemental analysis by EDX
Element | Wight percentage | Atomic percentage | Net Intensity |
Zn | 3.58 | 0.89 | 30.38 |
O | 39.05 | 39.8 | 1197.90 |
Na | 0.00 | 0.00 | 0.11 |
Mg | 2.83 | 1.90 | 253.43 |
S | 6.99 | 3.56 | 632.62 |
K | 0.00 | 0.00 | 0.00 |
Cl | 1.01 | 0.47 | 78.17 |
Ca | 10.34 | 4.21 | 533.59 |
3.6. FTIR Analysis of Nanoparticles
FTIR Spectroscopy was used to determine the functional groups that are present in the sample and to study the surface interaction of synthesized nanoparticles with other molecules that are involved in synthesizing and stabilizing the nanoparticles. The IR peaks of the zinc nanoparticles were observed at 3264.30 cm−1, 1555.56 cm−1, 1394.99 cm−1, and 1083.69 cm−1 (Table 2). Maher et al. (2023) reported FTIR spectral peaks of ZnONPs to be found at 3442, 2921, 2353, 1398, 419, 3414, 2345, 1391, and 436 cm−1. In a report, a large peak was visible at 3414 and 3442 cm−1 due to substantial O-H stretching of the hydroxyl moiety of phenols and alcoholic functionality in the highest energy state (Al-Trad et al., 2019). According to Agarwal et al. (2020), the characteristic peaks between 400 and 600 cm−1 are attributed to the Zn-O stretching vibration.
Table 2
Various peaks and corresponding functional groups as inferred from FTIR spectral report of zinc nanoparticles.
Absorption peak (cm− 1) | Functional group |
3264.30 cm− 1 | Corresponds to thestreching vibration of the hydroxyl (―OH) functional group. |
1555.56 cm− 1 | Associated with the stretching vibration of the carbonyl (C = O) functional group. |
1394.99 cm− 1 | Corresponds to the bending vibration of the methyl (CH3) functional group. |
1083.69 cm− 1 | Corresponds to the stretching vibration of the C-O bond in esters. |
3.7. Effect of ZnNPs treatments on wheat crops
The variety PBW 226 chosen for the experiment was late sown variety. The variety was widely adopted in the area of NWPZ (North Western Plain Zone) and released in 1989. This variety is suitable for late sown and irrigation conditions. The crop variety PBW was harvested after 121 DAS respectively. The impact of ZnNPs on morphological growth under salinity stress was measured in terms of Germination percentage (GP), Days of 50% heading (50% DH), Days of 50% anthesis (50% DA), Plant height (PH), No. of effective tillers per plant (TPP), Spike length (SL), Grain yield per plant (GYPP) and the number of grains per spike (GPS). The graphical representation of various growth and yield parameters of control and treatments is shown in Fig. 10).
Wheat crop plants treated with ZnNPs (2mM) and Zn ions significantly accumulated Zn that was measured by using an Atomic Absorption Spectrophotometer (AAS). After 1 week of ZnNPs treatment, the wheat leaves were collected from the control row and the other 4 rows of treatment and washed with distilled water. The wheat leaves were digested as per the method given by Homaee & Ehsanpour (2016) and analysed through AAS. This facility was accessed from Advance Research and Analytical Services, Ghaziabad, Uttar Pradesh, India. The results indicate that the concentration of Zn ions in the sample of control wheat leaves was found to be 0.72 mg/L because control wheat leaves that must have been naturally accumulated through soil. The concentration of Zn ions and ZnNPs in 100 mM, 75mM, 50mM, and 25mM salt stressed wheat plant leaves was found to be 0.69 mg/L, 1.08 mg/L, 1.03 mg/L and 1.11mg/L respectively. The 25mM salt stressed plants showed maximum accumulation.
3.7.1 Effect on GP
The count of germinated seeds was taken after 20 days of sowing. Germination percentage (GP) was counted after 20 days of sowing as per the following formula:
GP = seeds germinated × 100
----------------------------------------
Total seeds
The result of ANOVA with LSD at p ≤ 0.05 showed that the highest GP was observed in the T1 plants, whereas the lowest was recorded in the T4 plants. The LSD analysis depicted that the GP in control was insignificantly different with T1, T2, T3, and T4 plants. The T1 plants showed significantly higher GP as compared to T4, but there was no significant difference in the GP of T2 and T3. T4 plants showed significantly lower GP as compared to T1. The overall analysis showed that the GP significantly improved due to the application of different treatments except T4.
3.7.2 Effect on days to 50% heading
The result of ANOVA with LSD at p ≤ 0.05 showed that the earliest days to 50% heading was observed in the T4 plants, whereas the latest was recorded in control plants. The LSD analysis depicted that the days to 50% heading in control was significantly later than T1, T2, T3, and T4 plants. The T1 plants showed significantly later days to 50% headings compared to T3 and T4, but there was no significant difference in the days to 50% heading of T2 plants. T2 plants showed significantly later days to 50% heading as compared to T3 and T4. T3 and T4 plants showed significantly earlier days to 50% heading as compared to T1 and T2 plants. The overall analysis showed that the days to 50% heading significantly improved due to the application of different treatments except for control.
3.7.3 Effect on days to 50% anthesis
The result of ANOVA with LSD at p ≤ 0.05 showed that the earliest days to 50% anthesis was observed in the T4 plants, whereas the latest was recorded in control plants. The LSD analysis depicted that the days to 50% anthesis in control was significantly late than in T1, T2, T3, and T4 plants. The T1 and T2 plants showed significantly different days to 50% anthesisas compared to T3 and T4 plants, but there was no significant difference in the days to 50% anthesis of T1 and T2 plants. The T4 plants showed significantly early 50% anthesis as compared to T1, T2, T3, and T4. The overall analysis showed that the days to 50% anthesis significantly improved due to the application of ZnNPs.
3.7.4 Effect on plant height (PH)
The result of ANOVA with LSD at p ≤ 0.05 showed that the highest PH was observed in the T4 plants, whereas the lowest was recorded in the control plants. The LSD analysis depicted that the PH in control was significantly lower than T1, T3, and T4; however, it showed an insignificant difference with the T2 plant. The T1 plants showed significantly higher PH as compared to T2, but there was no significant difference in the PH of T1, T3, and T4. The T3 plants showed significantly lower PH as compared to T2. The overall analysis showed that the PH significantly improved in all the treatments except for T2.
3.7.5 Effect on no. of effective tillers per plant
The result of ANOVA with LSD at p ≤ 0.05 showed that the highest number of effective tillers per plant was observed in the T4 plants, whereas the lowest was recorded in the T1 plants. The LSD analysis depicted that the number of effective tillers per plant in control was significantly lower than T4; however, it showed insignificant differences with T1, T2, and T3 plants. The T1 plants showed a significantly lower no. of effective tillers as compared to T4, but there was no significant difference in the no. of effective tillers of T1, T2, and T3 plants. The T4 plants showed a significantly higher number of effective tillers per plant as compared to T1. The overall analysis showed that the number of effective tillers per plant significantly improved due to the application of different treatments except for T1.
3.7.6 Effect on Spike Length
The result of ANOVA with LSD at p ≤ 0.05 showed that the highest SL was observed in the T2 plants, whereas the lowest was recorded in the Control plants. The LSD analysis depicted that the SL in control was significantly lower than in T1, T2, T3, & T4 plants. The T1 plants showed significantly higher SL as compared to the control, but there was no significant difference in the SL of T2, T3 & T4. The overall analysis showed that the SL significantly improved due to the application of different treatments except for control.
3.7.7Effect on No. of Grains per Spike
The result of ANOVA with LSD at p ≤ 0.05 showed that the highest number of grains per spike was observed in the T4 plants, whereas the lowest was recorded in the Control plants. The LSD analysis depicted that the number of grains per spikein control was significantly lower than T3 and T4, however, it showed insignificant differences with T1 and T2 plants. The T1 plants showed significantly lower no. of grains per spike as compared to T3 and T4, but there was no significant difference in the no. of grains per spike of T2. The T2 plants showed a significantly lower number of grains per spikeas compared to T2. T4 plants showed significantly higher no. of grains per spikeas compared to T1 and T2. The overall analysis showed that the number of grains per spike significantly improved due to the application of different treatments except for control.
3.7.8 Effect on Grain Yield per Plant
The result of ANOVA with LSD at p ≤ 0.05 showed that the highest GYPP was observed in the T4 plants, whereas the lowest was recorded in control plants. The LSD analysis depicted that the GYPP in control was significantly lower than the T1, T2, T3, and T4 plants. The T1 plants showed significantly lower GYPP compared to T2, T3, and T4. The T4 plants showed significantly higher GYPP compared to the T1, T2, and T3 plants. The overall analysis showed that the GYPP significantly improved in treatments.
Various researchers reported that salinity stress can dramatically reduce the wheat plant growth and yield attributes due to the compromised water potential and osmoregulation (Sabagh et al., 2021). In this study, it was observed that a 100 mM salt stress imposed high salinity stress in wheat variety PBR 226. Results showed positive impact of ZnNPs on wheat plants with imposed salinity stress. According to Sturikova et al. (2018) ZnNPs can improve the Zn-uptake by plants under salinity stress which improves the growth and yield parameters. Nanoparticles have a higher ability and dynamism to be absorbed and accumulated in plants as attributed by their fine-size (Khalid et al., 2022).