As a threat to meeting the global demand for food created by the continued growth of population, different methods are being applied to enhance seed germination and plant growth. This study investigates the effect of hydrogen-rich water (HRW) and different plasma-activated waters (PAW) and their combinations including HRW, PAW1, PAW2, HPAW1, and HPAW2 on the seed germination of lentils. Different arc discharge reactors are generated under atmospheric pressure in the air. Optical emission spectroscopy was used to detect the radiative species formed in the plasma zone. Raman spectra and physicochemical properties of different waters were investigated. The results demonstrated significant differences in the properties of different activated waters compared to control water. On day 3 after treatment, the fraction and length of germinated seeds were evaluated. During germination, treated water significantly increased germination parameters such as final germination percentage, mean germination time, germination index, and coefficient of germination velocity. HPAW2 exhibited the highest germination index (GI), which combines germination percentage and speed. The plasma systems also effectively reduced the pH of PAW1 and PAW2, with a greater decrease observed in HPAW1 and HPAW1. Analysis of nitrite and nitrate levels revealed that HPAW2 had the highest concentrations, indicating more reactive processes in the presence of hydrogen. Based on our results, it can be concluded that lentil seed germination can be increased using PAW and hydrogenated PAW combined.
I. INTRODUCTION
A threat to meeting the global demand for food has been created by the continued growth of population worldwide. Global food demand is expected to increase by 60% by 2050 to feed an estimated population of 9.7 × 109 people.1–4 However, these methods also have several associated problems, including adverse impacts on crop health, pollution following treatments, and the introduction of toxins that can cause various diseases in animals and humans, which, in turn, can lead to significant economic challenges.2,5–8
Plasma-activated water (PAW) has been discovered, as a result of the efforts to find new methods for the promotion of sustainability and viability useful solutions that enhance seed germination and plant growth. PAW is created by transferring various reactive oxygen-nitrogen species (RONS) from the plasma phase to water.9 This process results in the formation of a range of primary species such as atomic oxygen, single oxygen, superoxide, ozone, hydroxyl radicals, and atomic nitrogen, which are then followed by secondary species such as hydrogen peroxide, peroxy-nitrite, nitric oxide, nitrates, and nitrite ions. These secondary species react with water to form PAW, potentially promoting healthy plant growth.10,11 Dissolution of plasma species in water causes the formation of short-lived species including oxygen atoms (O), hydroxyl radicals (OH), peroxynitrous acid (ONOO−), nitric oxide (ON), etc., and long-lived species including nitrate (NO3−), nitrogen dioxide (NO2), hydrogen peroxide (H2O2), dissolved ozone (O3), etc.12 The existence of these reactive radicals and species in PAW makes it a promising product that can be employed in countless applications, including eliminating or reducing the spread of pathogens;13 improving soil fertility,14 seed germination, and plant growth;11,15,16 resistance inducer against bacterial leaf spot,17 etc.
PAW and plasma treatments have been shown to affect seed germination and plant growth, with prior reports from various researchers.11,18–22 Rathore et al.18 have shown that water activated with a pencil plasma jet (PPJ) improves the germination rate, viability index, and mean germination time of peas (Pisum sativum L.). Sivachandiran et al.11 have reported the positive effect of air plasma and PAW with a DBD reactor on the germination rate and plant growth in three different seed species, including radish (Raphanus sativus), tomato (Solanum lycopersicum), and sweet pepper (Capsicum annum). Terebun et al.19 describe the significant improvement of PAW produced in an atmospheric pressure gliding arc reactor for the germination of beetroot (Beta vulgaris) and carrot (Daucus carota) seeds.
Additionally, a series of events in the growth and development of plants have been attributed to H2.23,24 Some researchers, such as Huang et al., investigated the role and basic mechanisms of H2 in promoting seed germination.25 In recent years, H2 is an entirely new antioxidant in animals and plants. As a new beneficial gaseous molecule, H2 can respond to physiological processes.26–28 In addition, H2 responds to certain abiotic stress factors, such as salinity,29 osmotic stresses,30 heavy metals,31 high light stress,32 and temperatures.33 For instance, an increase in the antioxidant system that counteracts the overproduction of ROS and lipid peroxidation has led to increased salt tolerance of Arabidopsis through hydrogen-rich water (HRW).29
Furthermore, cultivating food legumes, which provide more than 1 × 109 people with a critical source of digestible carbohydrate polymers, could offer opportunities to use in new plant protein-based foods and animal feeding stuff. Seeds of grain legumes are very popular as a source of digestible carbohydrates, compared to animal-based protein, which is environmentally costly.34,35 The value of food, handling characteristics, and gustatory qualities can be provided by carbohydrate polymers.36 Lentil seeds offer a significant source of dietary fiber, complex carbohydrates, iron, zinc, and vitamin B complex. These nutritional components are essential for maintaining a healthy diet and providing the body with nutrients for optimal performance.37 They also contain specific phenolic compounds, giving them a higher antioxidant activity than other legume species.38
The global challenge of meeting increasing food demand persists and PAW shows potential in promoting plant growth. Various research has revealed the impact of PAW on seed germination and plant growth, as well as the beneficial effects of hydrogen (H2) in supporting seed germination and acting as an antioxidant in plants. However, in prior research, there was a lack of combination in the study of the impact of both PAW and HRW on seed germination and plant growth. This current experiment focuses on optimizing the germination process to enhance the efficiency and quality of sprout production, particularly considering the substantial nutritional benefits of lentils. Our study aims to elucidate the influence of PAW, HRW, and their combination on these processes.
In prior research, a finite element simulation was used to study the two-dimensional dielectric barrier discharge and arc discharge in a bubble within water.39 The present study uses an HRW generator and two different atmospheric pressure air plasma generators to produce PAW. Species were evaluated in plasma columns by optical emission spectroscopy, and Raman spectra of water were investigated. Multifarious produced glasses of water were exposed to green lentil (Lens culinaris Medik.) seeds to study the various phenotypic growth parameters.
II. MATERIALS AND METHODS
A. Experimental setups
Figure 1 gives an overview of the water activator setups. The reactor was powered by an RMS (root-mean-square) voltage of 10.61 kV (15 kV peak voltage), a current of 20 mA, and a frequency of 50 Hz, with a power of 130 W. In this research, electric arc discharge plasma has been used for PAW production systems. The first layout can be seen in Fig. 1(a). Setup 1 comprises a glass tube, an air pump, a rubber tube, and two cylindrical electrodes with a diameter of up to 1 mm. The plasma arc is formed between two electrodes connected to the HV source inside the glass tube. The length of the glass tube is 20 cm, and the distance between the electrodes is 7 cm. The active species produced by the plasma are injected into water utilizing a pump.
The other configuration consists of a cylindrical electrode with a diameter of 0.7 mm placed at a height of approximately 3.5 cm from the water surface and a flat electrode placed in water. In this system, the plasma arc is formed between the cylindrical electrode and water [Fig. 1(b)].
The HRW generator is an electrolyzer (electrolysis cell) [Fig. 1(c)]. It consists of two electrodes, an anode, and a cathode, separated by a solid porous ceramic membrane that is surrounded by water. The anode and the cathode are made of titanium mesh. The electrode is connected to a 12 V DC power source with an electrical power of 13 W. When an electric current passes through the electrolysis cell, the following reactions occur at the anode and the cathode: At the anode, oxidation of water molecules occurs, leading to the release of oxygen gas. Formed hydrogen ions migrate through the electrolyte to the cathode. At the cathode, the reduction of protons occurs, leading to the production of hydrogen gas (H2). A plastic tube is designed to remove oxygen from the chamber.
B. Waters treatments
50 ml of distilled water (control) was taken in a 100 ml glass beaker. This water was exposed to plasma with two different PAW generators, namely, injection of electrically arc discharged air into water (PAW1) and arc discharge on the water surface (PAW2) with a 3 min exposure time. 50 ml of distilled water was taken in the HRW generator and enriched for 3 min. Then, it was activated by PAW generators for 3 min. Based on prior experimentation and optimization studies for achieving the desired effects of water activation, the minimum time required to observe changes in germination parameters was determined to be 3 min. Figure 2 shows the schematic of the production of various waters utilized in this study.
C. Preparation of lentil seeds and calculations of germination parameters
For this experiment, green dried lentil seeds (L. culinaris) were purchased from the local market. The experiment involved a total of 750 seeds, which were divided into six groups, each consisting of five sets of 25 seeds. Each group was given a unique label, including Control, PAW1, PAW2, HPAW1, HPAW2, and HRW. To begin the experiment, each set of 25 seeds was soaked in 7 ml of one of the water samples, including Control, PAW1, PAW2, HPAW1, HPAW2, and HRW. The soaking process lasted 72 h since the necessary time for lentil germination is typically 2–3 days40 and was carried out at 24 °C and a relative humidity of 26%.
Seed germination progress in different groups of lentils based on water was monitored daily for the first 3 days. Comparative analysis of germination data across groups was performed utilizing the following parameters: final germination percentage (FGP), mean germination time (MGT), germination index (GI), coefficient of velocity of germination (CVG), and germination rate index (GRI). The methodology of calculations of the mentioned parameters is as follows:41
MGT:
MGT refers to the average time required for seeds to germinate, considering the timing of most germination events,where n = number of seeds germinated on each day is different from N = total number of seeds germinated at the termination of the experiment.CVG
CVG solely measures the speed of germination based on the quantity of seeds and time without emphasizing the final percentage,41where N is the number of seeds germinated every day and T is the number of days from seeding corresponding to N.GI:
In the GI, seeds germinated on the first day are given more weight than those germinated later.
, where N1, N2, and N3 are the number of germinated seeds on the first, second, and third day, and the multipliers (e.g., 1, 2, and 3) are weights given to the days of germination.
ANOVA (analysis of variance) was utilized to statistically compare the results obtained from different experimental groups. ANOVA is a widely employed statistical technique that facilitates the comparison of means across three or more groups to ascertain if there are any statistically significant differences among them. This method is particularly valuable when dealing with multiple treatment groups or factors, as it offers a comprehensive analysis of variance and aids in determining whether observed differences are a result of actual treatment effects or random variability.42 Through the use of ANOVA, we were able to thoroughly evaluate the significance of any observed differences and ensure the validity and reliability of our experimental findings.
D. Examining water methods
Following the water production process, a 50 ml sample of water was tested to assess its physicochemical parameters. The testing device is capable of measuring pH with an accuracy of 0.01, total dissolved salts with an accuracy of 1 ppm, and electric current with an accuracy of 2 μs/cm.
Five minutes after the water was produced, it underwent examination. The Raman spectra of the water samples were analyzed using a Technooran (Microspectrophotometer, Ram-532-004) within the range of 134–4325 cm−1, with an exposure time of 500 ms and three accumulations. The amount of water tested in this analyzer was 20 ml.
Nitrate and nitrite concentrations in the water samples were measured using an ion chromatograph with a precision of 0.5 mg/l. Analysis was conducted at three time points: immediately after water production and at 24 and 72 h thereafter.
III. RESULTS
A. Optical emission spectra
Figure 3 illustrates the optical emission spectra of plasmas formed by (a) arc discharge in the air (setup1) and (b) electrical discharge on the water surface (setup2) at wavelengths ranging from 150 to 500 nm. An optical emission spectrometer, Technooran (Noora200) with a spectral resolution of 1 nm, was used to identify the reactive species present in the generated discharge. The x-axis represents the wavelength (nm), and the y-axis represents the emission intensity (a.u.).
At wavelengths ranging from 200 to 270 nm, low-intensity excited nitric oxide (NOγ-band) dominates the spectra.43 Existence of the hydroxyl radical (OH) is indicated by the signal at 309 nm. At wavelengths ranging from 315 to 380 nm, several high and low-intensity nitrogen molecules (N2—the second positive system) were also discovered.44 In the spectrum of arc on the water surface, the intensity of excited nitric oxide species and hydroxyl radicals is the highest due to the presence of water molecules. Low intensity (N2—the initial negative system) is also observed at wavelengths ranging from 390 to 430 nm.45 Oxygen (O2) is also present in the discharge, as shown by the emission spectrum's peak at 356 nm.46 All of these reactive species are short-lived (primary species) and produce long-lived reactive species (secondary species).10,44,47,48
B. Physicochemical properties of water
Activated water's pH, electrical conductivity, and total dissolved solids were measured to determine its physicochemical properties. The pH measures the concentration of hydrogen ions in the solution. Table I shows a decrease in pH levels in PAWs, but injecting hydrogen gas leads to a slight increase in pH. The pH changes in PAW acidification are consistent with other articles.11,14,18,19 Hopkins' paper indicates that pH levels should rise in HRW.49 Both PAW1 and PAW2 exhibit a decrease in pH. However, when HRW is plasma-activated, hydrogen molecules (H2) participate in the reactions, resulting in the production of more compounds in water. Consequently, the pH of HPAW1 and HPAW2 shows a more significant decrease.
. | Control . | HRW . | PAW1 . | PAW2 . | HPAW1 . | HPAW2 . |
---|---|---|---|---|---|---|
pH | 5.5 ± 0.01 | 5.73 ± 0.2 | 4.71 ± 0.015 | 3.96 ± 0.24 | 4.56 ± 0.09 | 3.39 ± 0.31 |
EC (μSiemens/cm) | 2 ± 1 | 14 ± 3.5 | 48 ± 2 | 194 ± 2 | 55 ± 1 | 470 ± 15.35 |
TDS (ppm) | 1 ± 1 | 7 ± 1 | 24 ± 1 | 97 ± 1 | 27 ± 1 | 240 ± 7.7 |
. | Control . | HRW . | PAW1 . | PAW2 . | HPAW1 . | HPAW2 . |
---|---|---|---|---|---|---|
pH | 5.5 ± 0.01 | 5.73 ± 0.2 | 4.71 ± 0.015 | 3.96 ± 0.24 | 4.56 ± 0.09 | 3.39 ± 0.31 |
EC (μSiemens/cm) | 2 ± 1 | 14 ± 3.5 | 48 ± 2 | 194 ± 2 | 55 ± 1 | 470 ± 15.35 |
TDS (ppm) | 1 ± 1 | 7 ± 1 | 24 ± 1 | 97 ± 1 | 27 ± 1 | 240 ± 7.7 |
C. Water Raman spectra
Activated water's Raman spectrum is illustrated in Fig. 4. Using the reference data available in the literature, the Raman spectrum of water can be seen in Fig. 4 lines (A) and (B), with vibration bands near 3400 and 3250 cm−1.50 The Raman Q branch of hydrogen dissolved in water is observed at wavelengths ranging from 3900 to 4170 cm−1.51 In Fig. 4, line (c) represents a peak of the Q-branch.
D. Nitrate and nitrite concentration
The graph depicted in Fig. 5 illustrates a comparison of nitrate and nitrite levels in various activated waters. PAW2 and HPAW2 show the highest nitrate concentration, while HPAW2 consistently exhibits the highest nitrite concentration among the activated waters. Conversely, PAW1 displays the lowest levels of nitrate and nitrite due to the plasma column's lack of direct interaction with water and the absence of additional hydrogen molecules, as seen in HPAW1, which would facilitate further reactions. In HPAW1, more complex nitrate species, similar to those in PAW1, were not produced, but there was an increase in nitrite concentration. As indicated by the experiment's short duration, no specific changes were observed in the concentration of nitrate and nitrite.
E. Length and germination parameters
The measurement results of 125 lentil bean sprouts in each group were taken for length and germination parameters in five replicates on the third day. Figure 6 shows a picture of cultivation containers.
A one-way ANOVA was performed to compare the effect of six different waters on germination parameters. The ANOVA revealed a statistically significant difference in mean germination parameters between at least two groups, as shown in Table II.
. | . | Sum of squares . | df . | Mean square . | F . | Sig. . |
---|---|---|---|---|---|---|
Average sprout length | Between groups | 328.498 | 5 | 65.700 | 36.137 | 0.000 |
Within groups | 43.633 | 24 | 1.818 | |||
Total | 372.131 | 29 | ||||
FGP | Between groups | 1284.267 | 5 | 256.853 | 14.594 | 0.000 |
Within groups | 422.400 | 24 | 17.600 | |||
Total | 1706.667 | 29 | ||||
MGT | Between groups | 0.349 | 5 | 0.070 | 25.451 | 0.000 |
Within groups | 0.066 | 24 | 0.003 | |||
Total | 0.415 | 29 | ||||
CVG | Between groups | 301.738 | 5 | 60.348 | 54.131 | 0.000 |
Within groups | 26.756 | 24 | 1.115 | |||
Total | 328.494 | 29 | ||||
GI | Between groups | 3836.667 | 5 | 767.333 | 180.549 | 0.000 |
Within groups | 102.000 | 24 | 4.250 | |||
Total | 3938.667 | 29 |
. | . | Sum of squares . | df . | Mean square . | F . | Sig. . |
---|---|---|---|---|---|---|
Average sprout length | Between groups | 328.498 | 5 | 65.700 | 36.137 | 0.000 |
Within groups | 43.633 | 24 | 1.818 | |||
Total | 372.131 | 29 | ||||
FGP | Between groups | 1284.267 | 5 | 256.853 | 14.594 | 0.000 |
Within groups | 422.400 | 24 | 17.600 | |||
Total | 1706.667 | 29 | ||||
MGT | Between groups | 0.349 | 5 | 0.070 | 25.451 | 0.000 |
Within groups | 0.066 | 24 | 0.003 | |||
Total | 0.415 | 29 | ||||
CVG | Between groups | 301.738 | 5 | 60.348 | 54.131 | 0.000 |
Within groups | 26.756 | 24 | 1.115 | |||
Total | 328.494 | 29 | ||||
GI | Between groups | 3836.667 | 5 | 767.333 | 180.549 | 0.000 |
Within groups | 102.000 | 24 | 4.250 | |||
Total | 3938.667 | 29 |
Fisher's LSD test for multiple comparisons indicated that there was no significant difference in the average stem length between HPAW2 and PAW2 (p = 0.407). However, their difference with other waters was found to be significant. In the comparison between HRW and PAW1, there was no statistically significant difference (p = 0.149); similarly, no significant difference was found between HRW and HPAW1 (p = 0.551). Additionally, it is worth noting that HRW showed no detectable nitrate and nitrite concentrations (Table III).
Dependent variable . | . | Category (I) . | Category (J) . | Mean difference (I–J) . | Std. error . | Sig. . | 95% Confidence . | |
---|---|---|---|---|---|---|---|---|
Lower bound . | Upper bound . | |||||||
Average sprout length | LSD | Control | HRW | −4.90400a | 0.85277 | 0.000 | −6.6640 | −3.1440 |
PAW1 | −3.63400a | 0.85277 | 0.000 | −5.3940 | −1.8740 | |||
PAW2 | −9.75800a | 0.85277 | 0.000 | −11.5180 | −7.9980 | |||
HPAW1 | −4.38800a | 0.85277 | 0.000 | −6.1480 | −2.6280 | |||
HPAW2 | −9.03800a | 0.85277 | 0.000 | −10.7980 | −7.2780 | |||
HRW | Control | 4.90400a | 0.85277 | 0.000 | 3.1440 | 6.6640 | ||
PAW1 | 1.27000 | 0.85277 | 0.149 | −0.4900 | 3.0300 | |||
PAW2 | −4.85400a | 0.85277 | 0.000 | −6.6140 | −3.0940 | |||
HPAW1 | 0.51600 | 0.85277 | 0.551 | −1.2440 | 2.2760 | |||
HPAW2 | −4.13400a | 0.85277 | 0.000 | −5.8940 | −2.3740 | |||
PAW1 | Control | 3.63400a | 0.85277 | 0.000 | 1.8740 | 5.3940 | ||
HRW | −1.27000 | 0.85277 | 0.149 | −3.0300 | 0.4900 | |||
PAW2 | −6.12400a | 0.85277 | 0.000 | −7.8840 | −4.3640 | |||
HPAW1 | −0.75400 | 0.85277 | 0.385 | −2.5140 | 1.0060 | |||
HPAW2 | −5.40400a | 0.85277 | 0.000 | −7.1640 | −3.6440 | |||
PAW2 | Control | 9.75800a | 0.85277 | 0.000 | 7.9980 | 11.5180 | ||
HRW | 4.85400a | 0.85277 | 0.000 | 3.0940 | 6.6140 | |||
PAW1 | 6.12400a | 0.85277 | 0.000 | 4.3640 | 7.8840 | |||
HPAW1 | 5.37000a | 0.85277 | 0.000 | 3.6100 | 7.1300 | |||
HPAW2 | 0.72000 | 0.85277 | 0.407 | −1.0400 | 2.4800 | |||
HPAW1 | Control | 4.38800a | 0.85277 | 0.000 | 2.6280 | 6.1480 | ||
HRW | −0.51600 | 0.85277 | 0.551 | −2.2760 | 1.2440 | |||
PAW1 | 0.75400 | 0.85277 | 0.385 | −1.0060 | 2.5140 | |||
PAW2 | −5.37000a | 0.85277 | 0.000 | −7.1300 | −3.6100 | |||
HPAW2 | −4.65000a | 0.85277 | 0.000 | −6.4100 | −2.8900 | |||
HPAW2 | Control | 9.03800a | 0.85277 | 0.000 | 7.2780 | 10.7980 | ||
HRW | 4.13400a | 0.85277 | 0.000 | 2.3740 | 5.8940 | |||
PAW1 | 5.40400a | 0.85277 | 0.000 | 3.6440 | 7.1640 | |||
PAW2 | −0.72000 | 0.85277 | 0.407 | −2.4800 | 1.0400 | |||
HPAW1 | 4.65000a | 0.85277 | 0.000 | 2.8900 | 6.4100 |
Dependent variable . | . | Category (I) . | Category (J) . | Mean difference (I–J) . | Std. error . | Sig. . | 95% Confidence . | |
---|---|---|---|---|---|---|---|---|
Lower bound . | Upper bound . | |||||||
Average sprout length | LSD | Control | HRW | −4.90400a | 0.85277 | 0.000 | −6.6640 | −3.1440 |
PAW1 | −3.63400a | 0.85277 | 0.000 | −5.3940 | −1.8740 | |||
PAW2 | −9.75800a | 0.85277 | 0.000 | −11.5180 | −7.9980 | |||
HPAW1 | −4.38800a | 0.85277 | 0.000 | −6.1480 | −2.6280 | |||
HPAW2 | −9.03800a | 0.85277 | 0.000 | −10.7980 | −7.2780 | |||
HRW | Control | 4.90400a | 0.85277 | 0.000 | 3.1440 | 6.6640 | ||
PAW1 | 1.27000 | 0.85277 | 0.149 | −0.4900 | 3.0300 | |||
PAW2 | −4.85400a | 0.85277 | 0.000 | −6.6140 | −3.0940 | |||
HPAW1 | 0.51600 | 0.85277 | 0.551 | −1.2440 | 2.2760 | |||
HPAW2 | −4.13400a | 0.85277 | 0.000 | −5.8940 | −2.3740 | |||
PAW1 | Control | 3.63400a | 0.85277 | 0.000 | 1.8740 | 5.3940 | ||
HRW | −1.27000 | 0.85277 | 0.149 | −3.0300 | 0.4900 | |||
PAW2 | −6.12400a | 0.85277 | 0.000 | −7.8840 | −4.3640 | |||
HPAW1 | −0.75400 | 0.85277 | 0.385 | −2.5140 | 1.0060 | |||
HPAW2 | −5.40400a | 0.85277 | 0.000 | −7.1640 | −3.6440 | |||
PAW2 | Control | 9.75800a | 0.85277 | 0.000 | 7.9980 | 11.5180 | ||
HRW | 4.85400a | 0.85277 | 0.000 | 3.0940 | 6.6140 | |||
PAW1 | 6.12400a | 0.85277 | 0.000 | 4.3640 | 7.8840 | |||
HPAW1 | 5.37000a | 0.85277 | 0.000 | 3.6100 | 7.1300 | |||
HPAW2 | 0.72000 | 0.85277 | 0.407 | −1.0400 | 2.4800 | |||
HPAW1 | Control | 4.38800a | 0.85277 | 0.000 | 2.6280 | 6.1480 | ||
HRW | −0.51600 | 0.85277 | 0.551 | −2.2760 | 1.2440 | |||
PAW1 | 0.75400 | 0.85277 | 0.385 | −1.0060 | 2.5140 | |||
PAW2 | −5.37000a | 0.85277 | 0.000 | −7.1300 | −3.6100 | |||
HPAW2 | −4.65000a | 0.85277 | 0.000 | −6.4100 | −2.8900 | |||
HPAW2 | Control | 9.03800a | 0.85277 | 0.000 | 7.2780 | 10.7980 | ||
HRW | 4.13400a | 0.85277 | 0.000 | 2.3740 | 5.8940 | |||
PAW1 | 5.40400a | 0.85277 | 0.000 | 3.6440 | 7.1640 | |||
PAW2 | −0.72000 | 0.85277 | 0.407 | −2.4800 | 1.0400 | |||
HPAW1 | 4.65000a | 0.85277 | 0.000 | 2.8900 | 6.4100 |
The mean difference is significant at the 0.05 level.
The shoot length for PAW2 and HPAW2 increased by 40% compared to the control. Figure 7’s graph illustrates that the sprout length increase compared to the control for other waters is 20%. Despite HRW having zero nitrate and nitrite concentrations, it is important to note that HRW can activate the sugar production mechanism, thereby allowing seeds to extract nutrients for growth independently.23
There was no statistically significant difference in MGT between HRW and PAW1 (p = 0.197) or HRW and HPAW1 (p = 0.288), although there are statistically significant differences between PAW2 and HPAW2 (p < 0.050) (Table IV). The lowest MGT value belonged to PAW2 and HPAW2, with a reduction of around 12.8% compared to the reference sample [Fig. 7(b)]. The control had the highest MGT, followed by HRW, PAW1, and HPAW1 with a 12% decrease. The lower the MGT, the faster the population of seeds germinated.52
Dependent variable . | . | Category (I) . | Category (J) . | Mean difference (I–J) . | Std. error . | Sig. . | 95% Confidence . | |
---|---|---|---|---|---|---|---|---|
. | Lower bound . | Upper bound . | ||||||
MGT | LSD | Control | HRW | 0.21000a | 0.03313 | 0.000 | 0.1416 | 0.2784 |
PAW1 | 0.25400a | 0.03313 | 0.000 | 0.1856 | 0.3224 | |||
PAW2 | 0.31600a | 0.03313 | 0.000 | 0.2476 | 0.3844 | |||
HPAW1 | 0.24600a | 0.03313 | 0.000 | 0.1776 | 0.3144 | |||
HPAW2 | 0.32200a | 0.03313 | 0.000 | 0.2536 | 0.3904 | |||
HRW | Control | −0.21000a | 0.03313 | 0.000 | −0.2784 | −0.1416 | ||
PAW1 | 0.04400 | 0.03313 | 0.197 | −0.0244 | 0.1124 | |||
PAW2 | 0.10600a | 0.03313 | 0.004 | 0.0376 | 0.1744 | |||
HPAW1 | 0.03600 | 0.03313 | 0.288 | −0.0324 | 0.1044 | |||
HPAW2 | 0.11200a | 0.03313 | 0.002 | 0.0436 | 0.1804 | |||
PAW1 | Control | −0.25400a | 0.03313 | 0.000 | −0.3224 | −0.1856 | ||
HRW | −0.04400 | 0.03313 | 0.197 | −0.1124 | 0.0244 | |||
PAW2 | 0.06200 | 0.03313 | 0.073 | −0.0064 | 0.1304 | |||
HPAW1 | −0.00800 | 0.03313 | 0.811 | −0.0764 | 0.0604 | |||
HPAW2 | 0.06800 | 0.03313 | 0.051 | −0.0004 | 0.1364 | |||
PAW2 | Control | −0.31600a | 0.03313 | 0.000 | −0.3844 | −0.2476 | ||
HRW | −0.10600a | 0.03313 | 0.004 | −0.1744 | −0.0376 | |||
PAW1 | −0.06200 | 0.03313 | 0.073 | −0.1304 | 0.0064 | |||
HPAW1 | −0.07000a | 0.03313 | 0.045 | −0.1384 | −0.0016 | |||
HPAW2 | 0.00600 | 0.03313 | 0.858 | −0.0624 | 0.0744 | |||
HPAW1 | Control | −0.24600a | 0.03313 | 0.000 | −0.3144 | −0.1776 | ||
HRW | −0.03600 | 0.03313 | 0.288 | −0.1044 | 0.0324 | |||
PAW1 | 0.00800 | 0.03313 | 0.811 | −0.0604 | 0.0764 | |||
PAW2 | 0.07000a | 0.03313 | 0.045 | 0.0016 | 0.1384 | |||
HPAW2 | 0.07600a | 0.03313 | 0.031 | 0.0076 | 0.1444 | |||
HPAW2 | Control | −0.32200a | 0.03313 | 0.000 | −0.3904 | −0.2536 | ||
HRW | −0.11200a | 0.03313 | 0.002 | −0.1804 | −0.0436 | |||
PAW1 | −0.06800 | 0.03313 | 0.051 | −0.1364 | 0.0004 | |||
PAW2 | −0.00600 | 0.03313 | 0.858 | −0.0744 | 0.0624 | |||
HPAW1 | −0.07600a | 0.03313 | 0.031 | −0.1444 | −0.0076 |
Dependent variable . | . | Category (I) . | Category (J) . | Mean difference (I–J) . | Std. error . | Sig. . | 95% Confidence . | |
---|---|---|---|---|---|---|---|---|
. | Lower bound . | Upper bound . | ||||||
MGT | LSD | Control | HRW | 0.21000a | 0.03313 | 0.000 | 0.1416 | 0.2784 |
PAW1 | 0.25400a | 0.03313 | 0.000 | 0.1856 | 0.3224 | |||
PAW2 | 0.31600a | 0.03313 | 0.000 | 0.2476 | 0.3844 | |||
HPAW1 | 0.24600a | 0.03313 | 0.000 | 0.1776 | 0.3144 | |||
HPAW2 | 0.32200a | 0.03313 | 0.000 | 0.2536 | 0.3904 | |||
HRW | Control | −0.21000a | 0.03313 | 0.000 | −0.2784 | −0.1416 | ||
PAW1 | 0.04400 | 0.03313 | 0.197 | −0.0244 | 0.1124 | |||
PAW2 | 0.10600a | 0.03313 | 0.004 | 0.0376 | 0.1744 | |||
HPAW1 | 0.03600 | 0.03313 | 0.288 | −0.0324 | 0.1044 | |||
HPAW2 | 0.11200a | 0.03313 | 0.002 | 0.0436 | 0.1804 | |||
PAW1 | Control | −0.25400a | 0.03313 | 0.000 | −0.3224 | −0.1856 | ||
HRW | −0.04400 | 0.03313 | 0.197 | −0.1124 | 0.0244 | |||
PAW2 | 0.06200 | 0.03313 | 0.073 | −0.0064 | 0.1304 | |||
HPAW1 | −0.00800 | 0.03313 | 0.811 | −0.0764 | 0.0604 | |||
HPAW2 | 0.06800 | 0.03313 | 0.051 | −0.0004 | 0.1364 | |||
PAW2 | Control | −0.31600a | 0.03313 | 0.000 | −0.3844 | −0.2476 | ||
HRW | −0.10600a | 0.03313 | 0.004 | −0.1744 | −0.0376 | |||
PAW1 | −0.06200 | 0.03313 | 0.073 | −0.1304 | 0.0064 | |||
HPAW1 | −0.07000a | 0.03313 | 0.045 | −0.1384 | −0.0016 | |||
HPAW2 | 0.00600 | 0.03313 | 0.858 | −0.0624 | 0.0744 | |||
HPAW1 | Control | −0.24600a | 0.03313 | 0.000 | −0.3144 | −0.1776 | ||
HRW | −0.03600 | 0.03313 | 0.288 | −0.1044 | 0.0324 | |||
PAW1 | 0.00800 | 0.03313 | 0.811 | −0.0604 | 0.0764 | |||
PAW2 | 0.07000a | 0.03313 | 0.045 | 0.0016 | 0.1384 | |||
HPAW2 | 0.07600a | 0.03313 | 0.031 | 0.0076 | 0.1444 | |||
HPAW2 | Control | −0.32200a | 0.03313 | 0.000 | −0.3904 | −0.2536 | ||
HRW | −0.11200a | 0.03313 | 0.002 | −0.1804 | −0.0436 | |||
PAW1 | −0.06800 | 0.03313 | 0.051 | −0.1364 | 0.0004 | |||
PAW2 | −0.00600 | 0.03313 | 0.858 | −0.0744 | 0.0624 | |||
HPAW1 | −0.07600a | 0.03313 | 0.031 | −0.1444 | −0.0076 |
The mean difference is significant at the 0.05 level.
CVG prioritizes the time taken to achieve the result and does not consider specific time details, only general averages.53 The LSD test for multiple comparisons revealed a significant difference in CVG between HRW and other activated waters. There was no statistically significant difference between PAW1 and HPAW1 (p = 0.722) or between PAW2 and HPAW2 (p = 0.479) (Table V). The CVG ratios for PAW2/HPAW2 and PAW1/HPAW1 samples were nearly identical. Compared to the control sample, similar CVG ratios were reported for samples 1.2 and 3.4, with increases of 18.4% and 14.7%, respectively [Fig. 8(a)]. Additionally, PAW's RONS have the potential to enhance germination rates by activating abscisic acid/gibberellic acid pathways and interrupting seed dormancy.
Dependent variable . | . | Category (I) . | Category (J) . | Mean difference (I–J) . | Std. error . | Sig. . | 95% Confidence . | |
---|---|---|---|---|---|---|---|---|
. | Lower bound . | Upper bound . | ||||||
CVG | LSD | Control | HRW | −5.94000a | 0.66778 | 0.000 | −7.3182 | −4.5618 |
PAW1 | −7.68000a | 0.66778 | 0.000 | −9.0582 | −6.3018 | |||
PAW2 | −9.04000a | 0.66778 | 0.000 | −10.4182 | −7.6618 | |||
HPAW1 | −7.44000a | 0.66778 | 0.000 | −8.8182 | −6.0618 | |||
HPAW2 | −9.52000a | 0.66778 | 0.000 | −10.8982 | −8.1418 | |||
HRW | Control | 5.94000a | 0.66778 | 0.000 | 4.5618 | 7.3182 | ||
PAW1 | −1.74000a | 0.66778 | 0.016 | −3.1182 | −0.3618 | |||
PAW2 | −3.10000a | 0.66778 | 0.000 | −4.4782 | −1.7218 | |||
HPAW1 | −1.50000a | 0.66778 | 0.034 | −2.8782 | −0.1218 | |||
HPAW2 | −3.58000a | 0.66778 | 0.000 | −4.9582 | −2.2018 | |||
PAW1 | Control | 7.68000a | 0.66778 | 0.000 | 6.3018 | 9.0582 | ||
HRW | 1.74000a | 0.66778 | 0.016 | 0.3618 | 3.1182 | |||
PAW2 | −1.36000 | 0.66778 | 0.053 | −2.7382 | 0.0182 | |||
HPAW1 | 0.24000 | 0.66778 | 0.722 | −1.1382 | 1.6182 | |||
HPAW2 | −1.84000a | 0.66778 | 0.011 | −3.2182 | −0.4618 | |||
PAW2 | Control | 9.04000a | 0.66778 | 0.000 | 7.6618 | 10.4182 | ||
HRW | 3.10000a | 0.66778 | 0.000 | 1.7218 | 4.4782 | |||
PAW1 | 1.36000 | 0.66778 | 0.053 | −0.0182 | 2.7382 | |||
HPAW1 | 1.60000a | 0.66778 | 0.025 | 0.2218 | 2.9782 | |||
HPAW2 | −0.48000 | 0.66778 | 0.479 | −1.8582 | 0.8982 | |||
HPAW1 | Control | 7.44000a | 0.66778 | 0.000 | 6.0618 | 8.8182 | ||
HRW | 1.50000a | 0.66778 | 0.034 | 0.1218 | 2.8782 | |||
PAW1 | −0.24000 | 0.66778 | 0.722 | −1.6182 | 1.1382 | |||
PAW2 | −1.60000a | 0.66778 | 0.025 | −2.9782 | −0.2218 | |||
HPAW2 | −2.08000a | 0.66778 | 0.005 | −3.4582 | −0.7018 | |||
HPAW2 | Control | 9.52000a | 0.66778 | 0.000 | 8.1418 | 10.8982 | ||
HRW | 3.58000a | 0.66778 | 0.000 | 2.2018 | 4.9582 | |||
PAW1 | 1.84000a | 0.66778 | 0.011 | 0.4618 | 3.2182 | |||
PAW2 | 0.48000 | 0.66778 | 0.479 | −0.8982 | 1.8582 | |||
HPAW1 | 2.08000a | 0.66778 | 0.005 | 0.7018 | 3.4582 |
Dependent variable . | . | Category (I) . | Category (J) . | Mean difference (I–J) . | Std. error . | Sig. . | 95% Confidence . | |
---|---|---|---|---|---|---|---|---|
. | Lower bound . | Upper bound . | ||||||
CVG | LSD | Control | HRW | −5.94000a | 0.66778 | 0.000 | −7.3182 | −4.5618 |
PAW1 | −7.68000a | 0.66778 | 0.000 | −9.0582 | −6.3018 | |||
PAW2 | −9.04000a | 0.66778 | 0.000 | −10.4182 | −7.6618 | |||
HPAW1 | −7.44000a | 0.66778 | 0.000 | −8.8182 | −6.0618 | |||
HPAW2 | −9.52000a | 0.66778 | 0.000 | −10.8982 | −8.1418 | |||
HRW | Control | 5.94000a | 0.66778 | 0.000 | 4.5618 | 7.3182 | ||
PAW1 | −1.74000a | 0.66778 | 0.016 | −3.1182 | −0.3618 | |||
PAW2 | −3.10000a | 0.66778 | 0.000 | −4.4782 | −1.7218 | |||
HPAW1 | −1.50000a | 0.66778 | 0.034 | −2.8782 | −0.1218 | |||
HPAW2 | −3.58000a | 0.66778 | 0.000 | −4.9582 | −2.2018 | |||
PAW1 | Control | 7.68000a | 0.66778 | 0.000 | 6.3018 | 9.0582 | ||
HRW | 1.74000a | 0.66778 | 0.016 | 0.3618 | 3.1182 | |||
PAW2 | −1.36000 | 0.66778 | 0.053 | −2.7382 | 0.0182 | |||
HPAW1 | 0.24000 | 0.66778 | 0.722 | −1.1382 | 1.6182 | |||
HPAW2 | −1.84000a | 0.66778 | 0.011 | −3.2182 | −0.4618 | |||
PAW2 | Control | 9.04000a | 0.66778 | 0.000 | 7.6618 | 10.4182 | ||
HRW | 3.10000a | 0.66778 | 0.000 | 1.7218 | 4.4782 | |||
PAW1 | 1.36000 | 0.66778 | 0.053 | −0.0182 | 2.7382 | |||
HPAW1 | 1.60000a | 0.66778 | 0.025 | 0.2218 | 2.9782 | |||
HPAW2 | −0.48000 | 0.66778 | 0.479 | −1.8582 | 0.8982 | |||
HPAW1 | Control | 7.44000a | 0.66778 | 0.000 | 6.0618 | 8.8182 | ||
HRW | 1.50000a | 0.66778 | 0.034 | 0.1218 | 2.8782 | |||
PAW1 | −0.24000 | 0.66778 | 0.722 | −1.6182 | 1.1382 | |||
PAW2 | −1.60000a | 0.66778 | 0.025 | −2.9782 | −0.2218 | |||
HPAW2 | −2.08000a | 0.66778 | 0.005 | −3.4582 | −0.7018 | |||
HPAW2 | Control | 9.52000a | 0.66778 | 0.000 | 8.1418 | 10.8982 | ||
HRW | 3.58000a | 0.66778 | 0.000 | 2.2018 | 4.9582 | |||
PAW1 | 1.84000a | 0.66778 | 0.011 | 0.4618 | 3.2182 | |||
PAW2 | 0.48000 | 0.66778 | 0.479 | −0.8982 | 1.8582 | |||
HPAW1 | 2.08000a | 0.66778 | 0.005 | 0.7018 | 3.4582 |
The mean difference is significant at the 0.05 level.
The GI measures both the percentage and speed of germination, with a higher value indicating a higher percentage and rate.54 According to the LSD test for multiple comparisons, germination index (GI) was found to be significantly different between HPAW2 and HRW when compared to other activated waters. However, there was no statistically significant difference between PAW1 and HPAW1 (p = 0.138) or between PAW1 and PAW2 (p = 0.138) (Table VI). The highest recorded value for GI is related to HPAW2, with a 42.9% increase compared to the reference. With an increase of 38%, it is followed by PAW2, PAW1, and HPAW1. HRW increased by 24.8 [Fig. 8(b)]. The GI is considered the most comprehensive measurement parameter, combining germination percentage, speed, spread, duration, and high/low events.41
Dependent variable . | . | Category (I) . | Category (J) . | Mean difference (I–J) . | Std. error . | Sig. . | 95% Confidence . | |
---|---|---|---|---|---|---|---|---|
Lower bound . | Upper bound . | |||||||
GI | LSD | Control | HRW | −19.00000a | 1.30384 | 0.000 | −21.6910 | −16.3090 |
PAW1 | −28.00000a | 1.30384 | 0.000 | −30.6910 | −25.3090 | |||
PAW2 | −30.00000a | 1.30384 | 0.000 | −32.6910 | −27.3090 | |||
HPAW1 | −30.00000a | 1.30384 | 0.000 | −32.6910 | −27.3090 | |||
HPAW2 | −33.00000a | 1.30384 | 0.000 | −35.6910 | −30.3090 | |||
HRW | Control | 19.00000a | 1.30384 | 0.000 | 16.3090 | 21.6910 | ||
PAW1 | −9.00000a | 1.30384 | 0.000 | −11.6910 | −6.3090 | |||
PAW2 | −11.00000a | 1.30384 | 0.000 | −13.6910 | −8.3090 | |||
HPAW1 | −11.00000a | 1.30384 | 0.000 | −13.6910 | −8.3090 | |||
HPAW2 | −14.00000a | 1.30384 | 0.000 | −16.6910 | −11.3090 | |||
PAW1 | Control | 28.00000a | 1.30384 | 0.000 | 25.3090 | 30.6910 | ||
HRW | 9.00000a | 1.30384 | 0.000 | 6.3090 | 11.6910 | |||
PAW2 | −2.00000 | 1.30384 | 0.138 | −4.6910 | 0.6910 | |||
HPAW1 | −2.00000 | 1.30384 | 0.138 | −4.6910 | 0.6910 | |||
HPAW2 | −5.00000a | 1.30384 | 0.001 | −7.6910 | −2.3090 | |||
PAW2 | Control | 30.00000a | 1.30384 | 0.000 | 27.3090 | 32.6910 | ||
HRW | 11.00000a | 1.30384 | 0.000 | 8.3090 | 13.6910 | |||
PAW1 | 2.00000 | 1.30384 | 0.138 | −0.6910 | 4.6910 | |||
HPAW1 | 0.00000 | 1.30384 | 1.000 | −2.6910 | 2.6910 | |||
HPAW2 | −3.00000a | 1.30384 | 0.030 | −5.6910 | −0.3090 | |||
HPAW1 | Control | 30.00000a | 1.30384 | 0.000 | 27.3090 | 32.6910 | ||
HRW | 11.00000a | 1.30384 | 0.000 | 8.3090 | 13.6910 | |||
PAW1 | 2.00000 | 1.30384 | 0.138 | −0.6910 | 4.6910 | |||
PAW2 | 0.00000 | 1.30384 | 1.000 | −2.6910 | 2.6910 | |||
HPAW2 | −3.00000a | 1.30384 | 0.030 | −5.6910 | −0.3090 | |||
HPAW2 | Control | 33.00000a | 1.30384 | 0.000 | 30.3090 | 35.6910 | ||
HRW | 14.00000a | 1.30384 | 0.000 | 11.3090 | 16.6910 | |||
PAW1 | 5.00000a | 1.30384 | 0.001 | 2.3090 | 7.6910 | |||
PAW2 | 3.00000a | 1.30384 | 0.030 | 0.3090 | 5.6910 | |||
HPAW1 | 3.00000a | 1.30384 | 0.030 | 0.3090 | 5.6910 |
Dependent variable . | . | Category (I) . | Category (J) . | Mean difference (I–J) . | Std. error . | Sig. . | 95% Confidence . | |
---|---|---|---|---|---|---|---|---|
Lower bound . | Upper bound . | |||||||
GI | LSD | Control | HRW | −19.00000a | 1.30384 | 0.000 | −21.6910 | −16.3090 |
PAW1 | −28.00000a | 1.30384 | 0.000 | −30.6910 | −25.3090 | |||
PAW2 | −30.00000a | 1.30384 | 0.000 | −32.6910 | −27.3090 | |||
HPAW1 | −30.00000a | 1.30384 | 0.000 | −32.6910 | −27.3090 | |||
HPAW2 | −33.00000a | 1.30384 | 0.000 | −35.6910 | −30.3090 | |||
HRW | Control | 19.00000a | 1.30384 | 0.000 | 16.3090 | 21.6910 | ||
PAW1 | −9.00000a | 1.30384 | 0.000 | −11.6910 | −6.3090 | |||
PAW2 | −11.00000a | 1.30384 | 0.000 | −13.6910 | −8.3090 | |||
HPAW1 | −11.00000a | 1.30384 | 0.000 | −13.6910 | −8.3090 | |||
HPAW2 | −14.00000a | 1.30384 | 0.000 | −16.6910 | −11.3090 | |||
PAW1 | Control | 28.00000a | 1.30384 | 0.000 | 25.3090 | 30.6910 | ||
HRW | 9.00000a | 1.30384 | 0.000 | 6.3090 | 11.6910 | |||
PAW2 | −2.00000 | 1.30384 | 0.138 | −4.6910 | 0.6910 | |||
HPAW1 | −2.00000 | 1.30384 | 0.138 | −4.6910 | 0.6910 | |||
HPAW2 | −5.00000a | 1.30384 | 0.001 | −7.6910 | −2.3090 | |||
PAW2 | Control | 30.00000a | 1.30384 | 0.000 | 27.3090 | 32.6910 | ||
HRW | 11.00000a | 1.30384 | 0.000 | 8.3090 | 13.6910 | |||
PAW1 | 2.00000 | 1.30384 | 0.138 | −0.6910 | 4.6910 | |||
HPAW1 | 0.00000 | 1.30384 | 1.000 | −2.6910 | 2.6910 | |||
HPAW2 | −3.00000a | 1.30384 | 0.030 | −5.6910 | −0.3090 | |||
HPAW1 | Control | 30.00000a | 1.30384 | 0.000 | 27.3090 | 32.6910 | ||
HRW | 11.00000a | 1.30384 | 0.000 | 8.3090 | 13.6910 | |||
PAW1 | 2.00000 | 1.30384 | 0.138 | −0.6910 | 4.6910 | |||
PAW2 | 0.00000 | 1.30384 | 1.000 | −2.6910 | 2.6910 | |||
HPAW2 | −3.00000a | 1.30384 | 0.030 | −5.6910 | −0.3090 | |||
HPAW2 | Control | 33.00000a | 1.30384 | 0.000 | 30.3090 | 35.6910 | ||
HRW | 14.00000a | 1.30384 | 0.000 | 11.3090 | 16.6910 | |||
PAW1 | 5.00000a | 1.30384 | 0.001 | 2.3090 | 7.6910 | |||
PAW2 | 3.00000a | 1.30384 | 0.030 | 0.3090 | 5.6910 | |||
HPAW1 | 3.00000a | 1.30384 | 0.030 | 0.3090 | 5.6910 |
The mean difference is significant at the 0.05 level.
IV. DISCUSSION
Plasma reacts to water, triggering a range of kinetic chemical reactions and giving rise to the existence of aqueous reactive species. Different processes, e.g., the transfer of gases to liquids and a chemical reaction between gas types and liquid molecules, are performed when PAW is generated at an interface layer.55 The interaction of water with the plasma results in the non-equilibrium dissociation of water molecules, leading to the formation of short-living species such as hydroxyl ions (OH−) and hydrated (solvated) electrons. More stable species, including superoxides, ozone, and H2O2, are formed by subsequent rapid reactions between hydroxyl ions and hydrated (solvated) electrons.56 Apart from ROS, PAW also contains nitric acid (HNO3) and nitrous acid (HNO2) and low-level transient RNS, e.g., peroxynitrous acid/peroxynitrite and nitrogen dioxide radicals. Nitrogen oxide, which then reacts with water to form acids, is formed in the presence of air when nitrogen and oxygen are separated from the gaseous phase.48,57
As shown in Fig. 3(b), the intensity of the species' spectra nearly doubled in the optical emission spectra of the second device, and a spectrum of nitrogen oxide species was also observed. This increase in intensity was likely due to the presence of water molecules, which led to the production of more species. The active plasma species dissolved in water, resulting in the formation of stable active nitrogen species (RNS) such as NO2¯ and NO3¯ ions.58
The reaction of water with the species produced in the plasma causes PAW to become acidic. PAW shall become more acidic as the quantity of ROS and RNS delivered to the water increases.59 Changes in ionic species within PAWs were first identified by measuring their electrical conductivity. The increases in conductivity are due to the formation of ROS and RNS when active water is prepared.
Hydrogen is the lightest gas, and it reacts with most elements under normal conditions, whereas H2 is not very reactive in its molecular state.60 At the plasma interface with water, hydrogen molecules are also decomposed in sample HPAW2. More reactions occur, and hydrogen radicals produce more of the secondary compounds. There is a growing possibility that more compounds will be dissolved in water.
The study of the physicochemical properties of activated waters shows that both HPAW1 and HPAW2 exhibit a greater decrease in pH compared to PAW1 and PAW2. Many bacteria and fungi cannot survive or thrive in highly acidic conditions because the low pH can disrupt their cellular processes and structures.61 As a result, when the pH of the solution decreases significantly, it can effectively kill or inhibit the growth of these microorganisms on the seeds.
The configuration of two hydrogen bonds and two covalent bonds between oxygen and hydrogens around the oxygen atom is consistent with the tetrahedral-like structure of five water molecules.62 As the impurities increase in water, the four-hole configuration is prevented from forming, and the Raman peak of water height is reduced (Fig. 4). Alternatively, hydrogen molecules can contribute to this structure's formation and intensify its peak. Water peak intensity has decreased in PAW2 compared to PAW1. Also, water peak intensity has decreased in HPAW2 compared to in HPAW1 due to the increasing number of substances soluble in water. By forming a symmetrical configuration, hydrogen molecules in HPAW1/HPAW2 have intensified the Raman Q-branch peak of water compared to PAW1/PAW2.
There is a progressive differentiation of organs and tissue in developing legume seeds. Maturation is governed by a signaling network composed of sugars, amino acids, and SnRK1 kinases. Changing levels of oxygen energy and the nutrient state activate maturation processes. Embryo cells become green and photosynthetically operative during the transition. Sucrose functions as a transport and nutrient sugar and as a signal molecule that activates storage-associated processes.63 HRW plays a vital role in the conversion of starch to sugars,64 which are simple carbohydrates made of carbon, hydrogen, and oxygen.65 The accumulation of soluble proteins not only aids water retention but also protects essential substances. This leads to maximizing plant growth and promoting good health.66
The presence of ROS acts as a signal that the seed is awake and shortens its germination period. The essential nutrients for seed growth are provided by RNS compounds.67 More reactions occur in the second plasma system with the direct contact of the arc with water, resulting in more RONS being produced and dissolved in water. Compared with the first plasma system, this improved the germination parameters in water produced by a second plasma system. The presence of hydrogen in HPAW2 activates storage-associated processes that not only accelerate seed maturation but also provide a boost to sprout health.
V. CONCLUSION
This study examined the impact of two different plasma systems and a hydrogen injecting system and their combinations including PAW1, PAW2, HRW, HPAW1, and HPAW2 on water and the effects on lentil seed germination. The results demonstrated significant differences in the properties of different activated waters compared to control water. Also, seeds that were irrigated with HRW exhibited superior characteristics compared to the control seeds, as indicated by the results. The plasma systems effectively reduced the pH of PAW1 and PAW2, with a greater decrease observed in HPAW1 and HPAW1. Analysis of nitrite and nitrate levels revealed that HPAW2 had the highest concentrations, indicating more reactive processes in the presence of hydrogen. These results suggest that more reactions occur in the plasma system with direct arc contact with water, resulting in the increased production and dissolution of RONS in water. Raman spectrum analysis indicates a decrease in water peak intensity in HPAW2 compared to HPAW1, attributed to the increased solubility of substances in water. HPAW2 exhibited the highest germination index (GI), which combines germination percentage and speed. The increase in active species in water led to improved germination parameters, such as sprout length.
Overall, this study demonstrated that a combination of plasma systems and HRW systems could alter the physicochemical properties of water and positively impact seed germination parameters. In particular, HPAW2 showed better effects on seed growth and germination due to the increased production of reactive species.
AUTHOR DECLARATIONS
Conflict of Interest
The authors have no conflicts to disclose.
Author Contributions
S. Mansory: Conceptualization (equal); Formal analysis (equal); Funding acquisition (equal); Investigation (equal); Methodology (equal); Software (equal); Validation (equal); Visualization (equal); Writing – review & editing (equal). M. Bahreini: Conceptualization (equal); Formal analysis (equal); Funding acquisition (equal); Investigation (equal); Methodology (equal); Project administration (equal); Resources (equal); Software (equal); Supervision (equal); Validation (equal); Visualization (equal); Writing – review & editing (equal).
DATA AVAILABILITY
The data that support the findings of this study are available within the article.