Effect of Presowing Magnetic Field Stimulation on the Seed Germination and Growth of Phaseolus vulgaris L. Plants

Abstract

Background: The problem of the influence of magnetic fields (FMs) on the growth and development of common bean plants is still far from being fully explained due to its complicated physical nature and the geometry of the seeds. FMs can practically penetrate through living organisms. Aim: The present work aimed to determine the effect of the presowing FM stimulation of common bean seeds on plant growth and development elements. Material and Methods: The present study was based on a field experiment carried out between the years 2015 and 2017 in Żyznów (N 49°81′, E 21°84′, 239 m above sea level). The experiment was carried out using three repetitions of the randomized block method. The experimental factor was the amount of exposure to FM seed stimulation: (I) 15 s, (II) 30 seconds, and (III) the control object without seed stimulation. The plant material of the study was a common bean: cv. Gold Saxa. Results: The biostimulation of the sources with an FM improved the germination energy, strength, and capacity of the seeds. The presowing FM stimulation of the common bean seeds favourably affected the fresh weight of the first and fifth leaves but did not affect their dry weight. The leaves’ collection dates measured the new first and fifth plates and their dry weight content. The collection dates of the leaves determined the level of the fresh weight of the first and fifth leaves and the content of their dry weight. Conclusions: The biostimulation of the seeds with the FM contributed to a higher germination capacity, energy, and strength of the common bean seeds. The highest level of the leaves’ fresh weight was achieved during full flowering, and the highest dry matter content of the leaves was found in the phase of pod setting.

1. Introduction

The common bean (Phaseolus vulgaris L.) is one of the utmost consumed and documented legume species with high nutritional and antioxidant values [1]. The genotype and agroecological and physical factors affect the composition of common bean seeds [2,3,4,5]. In current years, there has been much discussion on the possibilities of the use of innovative physical factors [6,7,8,9,10,11]. Both FMs and electromagnetic fields (EFs) influence the functioning of live organisms. The effect of an FM on the biological objects placed in it is manifold, including electrodynamic interactions with organisms with electric currents (Lorentz force and Hall effect); the emergence of magnetomechanical effects inside organisms, consisting in the orientation of the structures of magnetic anisotropy in homogeneous fields and the shifts of ferromagnetic and paramagnetic substances in fields having nonzero gradients; influences on the uncompensated magnetic spins of paramagnetic elements and free radicals; the Dorfman effect, consisting in the reorientation of the proteins in a magnetostatic field due to the anisotropy of these molecules; some components of living organisms showing magnetostrictive properties (there is therefore a possibility of impacts on such components); changes in the energy of the intra- and interatomic interactions in living organisms; the induction of currents inside living organisms (caused by a sinusoidal alternating FM); and potential influences on the depolarization of cells [12,13]. Resonance phenomena, due to the penetration of an FM, can take place not only in the extracellular space but also in the cell membrane (i.e., in ion channels) and inside the cell; FMs also affect water, which, when exposed to an external FM, changes its properties: it increases the crystallization rate, concentration of dissolved gases, rate of coagulation, and settling of suspensions. The pH and wetting cause a capacity change [13,14,15,16,17,18,19,20,21] or antimicrobial activity [22,23,24,25]. The recognition and the understanding of an FM’s mechanisms of action on a plant organism are still challenges for researchers. According to Cakmak et al. [26], identifying an FM stimulation mechanism may be vital in regulating plants’ biological activity. It was reported earlier that magnetically treated water [27] and FM stimulation significantly affect plants [28,29,30,31]. According to many authors [3,4,5,32,33,34,35,36], similar effects can be achieved using low-temperature plasma, glow discharge, ultrasonic energy, and FMs. Repetitive FM stimulation (rTMS) is a promising noninvasive brain stimulation technique used in several countries for patients with refractory depression [37]. Physical plant simulation methods do not pollute the environment [28,38,39]. The lowest resistance is characterized by bean seeds with mechanical damage and pathogenic fungi infections and creates problems with germination and the initial growth stages [1,2]. Research on the influence of the magnetic field on the growth and development of plants is still needed and necessary due to the fact that they could be an excellent alternative to chemical methods that improve the size and quality of crops. Hence, this research aimed to determine the effect of the presowing FM stimulation of common bean seeds (Ph. vulgaris L.) on the germination energy, strength, and capacity of the seeds and on some plant growth and development elements. The present work, based on the presowing stimulation of common bean seeds with a variable FM, favorably affected the germination of the seeds, their growth, and the development of plants in subsequent development. The formation of the morphological characteristics determined the size of the seed and pod yields.

2. Materials and Methods

This study was based on a field experiment carried out between 2015 and 2017 in Żyznów, Podkarpackie Province (49°81′58 N, E 21°84′ E, 239 m above sea level), on brown, slightly acidic soil [40]. The experiment was carried out using the randomized block method in the 3 replications. The experimental factors were two exhibitions of FM seed stimulation: (A) 15 s, (B) 30 seconds, and (C) the control object without stimulation. The object of the study was the common bean cultivar Golden Sax.

2.1. Agrotechnical Conditions

The forecrop of bean was winter wheat, grown only with mineral fertilization and without manure. After harvesting the previous crop, cultivation was used, and, later, medium ploughing was used. In the spring, dragging and harrowing were employed, and mineral fertilizers were used in the doses 34.9 kg P and 91.3 kg K·ha⁻¹. Phosphorus–potassium fertilizers were used in the spring before the foundation of the experiment; phosphorus was in the form of triple superphosphate, and potassium was in the form of potassium sulphate. Before sowing, the seeds of beans were rated in terms of strength and energy of germination. Some seeds underwent stimulation with the FM, while the remaining seeds were the control object. Bean seeds were sown on May 6–8 depending on the meteorological conditions in the research years. Nest sowing was used. In each slot, three seeds were placed at a depth of approx. 2.5 cm. Row spacing was 40 × 33 cm. The surface of plots to be harvested was 12 m². Bean care included mechanical loosening and manual weeding. The protection of plants against diseases was based on the fungicide Amistar 250 S.C. (0.8 dm·ha⁻¹), and pest control was carried out using the formulation Nurelle D 550 EC (0.5 dm·ha⁻¹). Figure 1 shows a field experiment carried out in Żyznów, Krosno District, Podkarpackie Province.

2.2. Conditions of Irradiation with an FM

A few days before sowing, seeds were subjected to magnetic stimulation in the Department of Physics laboratory in the Vytautas Magnus University Agriculture Academy in Kaunas (Lithuania). The seeds were divided into three parts. The first part of the seeds was stimulated for 15 s; the second one was stimulated for 30 s. The seeds of the control part were not subjected to the process of stimulation. The induction of the constant FM was f = 45 mT. The selection of dose and radiation exposure was based on a pilot study. The position of the presowing FM stimulation station is shown in Figure 2.

2.3. Biometric Assessment

The germination of the seeds was carried out on Petri dishes lined with lignin. The test was carried out three days after radiation treatment with the FM. The humidity was maintained at a level of approx. 85–95%. The temperature in the device for seed sprouting was 22 °C. The quantity of germinated seeds was counted every 12 h for 10 days. We also marked their germination strength after seven days. The seed germination energy was determined after 3 days (72 h) according to the following formula:

$${\mathrm{E}}_{\mathrm{k}}=\frac{{\mathrm{L}}_3}{{\mathrm{L}}_0}·100\%$$

(1)

where E_k is germination energy, L₀ is the total number of seeds, and L₃ is the number of germinated seeds after 72 h. The germination rate is the percentage of seeds normally germinated within the time specified in the standards. It is one of the parameters of the seed sowing value.

Maguire’s germination rate (MGR) is calculated as the sum of the quotients of normally germinated seeds divided by the next day of germination. In fact, Maguire [13] gave a general mathematical expression that allows you to obtain a measurement for arbitrary time intervals. The mathematical expression is given as follows:

$$\mathrm{Rate}=\frac{\mathrm{number} \mathrm{of} \mathrm{normal} \mathrm{seedlings}}{\mathrm{days} \mathrm{to} \mathrm{first} \mathrm{count}}+\dots +\frac{\mathrm{number} \mathrm{of} \mathrm{normal} \mathrm{seedlings}}{\mathrm{days} \mathrm{to} \mathrm{final} \mathrm{count}}$$

(2)

High values obtained using this formula indicate a higher vigor of the seedlings of one sample in relation to the other. In seed technology, this value, called the germination or emergence rate index, is used to predict the relative viability of samples, especially crop species, since samples with the same number of germinated seeds may present different values of this index. Although Maguire [13] did not provide a unit of measure for this value, the value, when calculated with the proposed expression, is the number of normally sprouted seeds (seedlings) per day. A high value of this Maguire coefficient proves rapid germination of the tested seeds. It is very useful in assessing the germination rate [13]. Biometric measurements of plants were performed in 3 terms: after 20, 40, and 60 days of seedling growth, measurements were performed on 25% of plants in each combination of the field experiment in 3 repetitions. For all biometric measurements, the average value was separately calculated for each variant of the experiment. During the vegetation period of common bean growing, to carry out biometric analyses, leaf samples were collected from the second plant of beans at three development stages: (a) before flowering (51° in the scale BBCH), (b) during full flowering (65° in the BBCH scale), and (c) when 60% of the pods reached their typical length (76° in the BBCH scale). From 10 randomly selected plants in each plot, during the 3 terms, the 1st and 5th leaves of common bean were plucked, counting from the top to the bottom of the plant, in order to determine the fresh weight (FW) and dry weight (DW) of leaves. The fifth leaf is considered to be representative of the whole plant [13]. The dry weight of the leaves (including petioles and peduncles) and detached first and fifth leaves were determined after drying to dry weight at 75°C [13]. Monitoring the plant growth during the vegetation period, the plants’ growth rate was determined by measuring the plants’ height every 7 days, starting 20 days after sowing. Bean pods were harvested at BBCH phase 89 (Figure 3).

2.4. Statistical Analysis

Statistical development of results was performed through analysis of variance (ANOVA), analysis of regression, and correlation analysis. The significance of the sources of variation was tested with Fischer–Snedecor’s “F” test, and the importance of differences between compared averages was determined using Tukey’s confidence intervals. Analysis of variance, regression analysis, and correlation calculation were performed in SAS/STAT^® 9.2. The rate of seed germination was determined using polynomial, linear, and partly nonlinear regression [14]. Tukey’s multiple comparison test enables detailed comparative analyses of means by separating statistically homogeneous groups of means (homogeneous groups) and determining the so-called smallest significant differences in the means, which are marked as HSD in Tukey’s tests. The averaged letter indicators determine the so-called homogeneous (statistically homogeneous) groups. The occurrence of the same letter indicator as the means (at least one) means that there is no statistically significant difference between them [14,15]. Tukey’s HSD test is a post hoc test commonly used in statistics that was developed by J. Tukey. It is considered less conservative than the Scheffé test but more conservative than the Newman–Keuls test. To determine the rate of seed germination, a four-parameter logistic curve (4PL) was used [14]. SPSS Statistics 28 was used to calculate descriptive statistics. Some features of descriptive statistics were calculated, such as mean, standard deviation, kurtosis, skewness, and coefficient of variation. The coefficients of variation, V, are a measure of the dispersion of the obtained results. The lower its value, the more stable the feature is [14].

2.5. Soil Conditions

The soil on which the field experiment was performed was brown and slightly acidic (pH 5.43), was made from light and medium clay, and had humus content of 1.8%. It was characterized by a low content of available phosphorus (6.2 mg·100 g⁻¹ of soil P₂O₅) and high potassium (21 mg·100 g⁻¹ of soil K₂O) and magnesium (7.5 mg mg·100 g⁻¹ of soil MgO). The content of assailable manganese, copper, zinc, and iron were average (181.0 mg of Mn, 4.3 mg of Cu, 9.2 mg of Zn, and 1570 mg of Fe per kg⁻¹ of soil).

2.6. Meteorological Conditions

The weather station in Dukla (49°33′ N, 21°41′ E) is situated at an altitude of 324 m above sea level. The usual annual air temperature in this region is 7.3°C, and annual rainfall is 887 mm. The years 2015 and 2017 were reasonably dry, where the hydrothermal range fluctuated in the range of 1.1–1.3; though, in 2016, the Sielianinov ratio pointed to damp conditions (K = 1.9) (

Table 1. Meteorological conditions during bean growth in 2015–2017 according to the meteorological station in Dukla.

Years	Months					Mean IV-VIII
	IV	V	VI	VII	VIII
Rainfall (mm)
2015	30.6	80.5	126.6	30.2	33.1	60.2
2016	63.7	119.0	52.9	164.2	52.1	90.4
2017	28.2	98.2	63.1	10.6	15.8	43.2
SCN *	55.9	95.6	100.9	116.5	30.1	79.8
Air temperature (°C)
2015	9.5	14.5	17.6	18.7	19.1	15.9
2016	10.0	13.6	16.0	19.6	21.1	16.1
2017	8.3	12.6	15.7	20.1	18.1	15.0
SCN	9.2	13.6	16.4	19.0	19.4	15.5
HCS **
2015	1.1	1.8	2.4	0.5	0.6	1.3
2016	2.1	2.8	1.1	2.7	0.8	1.9
2017	1.1	2.5	1.3	0.2	0.3	1.1
SCN	2.3	2.1	2.0	0.5	2.0	1.8

* SCN—standard climatic norm of 1989–2014. ** HSC—hydrothermal coefficient of Sielianinov: extremely dry—≤0.4, very dry—0.4–0.7, dry—0.7–1.0, fairly dry—1.0–1.3, optimal—1.3–1.6, quite humid—1.6–2.0, wet—2.0–2.5, 2.5–3.0—very humid, and ≥3—extremely humid.

).

3. Results

3.1. Germination Rate

The germination rate of the bean seeds is shown in Figure 4. The weakest germination rate of the bean seeds was observed in the control object. The highest germination rate and the highest percentage of sprouted seeds were found in the objects with a longer exposure to the FM. All the regression curves were determined according to the four-parameter Boltzmann logistic equation (Figure 4). The coefficient of determination of the regression equations is a measure of the assessment of the fit of the regression function to the empirical data and informs what part of the variability of the explained variable Y is explained by the function of the explaining variable X. X was high, which proved the high reliability of this function (Figure 4).

The four-parameter logistic curve is a model frequently used to analyze biological tests, such as the seed germination rate or plant growth rate. It follows a sigmoidal or “s” shaped curve. This type of curve is particularly useful for characterizing bioassays because bioassays are often only linear over a certain range of concentrations (Figure 4). The Boltzmann regression equations are presented in

Table 2. Boltzmann regression results for the germination rate of common bean seeds.

Control Object
Parameter	Value
X50	68.3117
Equations (show alternative)
Equation	Y = −44.1229 + 106.4187 + 44.1229 × 68.31171 + ()−2.1089
Equation Form	Y = Min + Max − MinXX501 + ()Hill coefficient
Exposition I
Parameter	Value
X50	69.4106
Equations (show alternative)
Equation	Y = −12.1695 + 98.513 + 12.1695 × 69.41061 + ()−4.8941
Equation Form	Y = Min + Max − MinXX501 + ()Hill coefficient
Exposition II
Parameter	Value
X50	75.7738
Equations
Equation	Y = −2.1245 + 99.5213 + 2.1245 × 75.77381 + ()−5.6964
Equation Form	Y = Min + Max − MinXX501 + ()Hill coefficient

. Outside this linear response range, they quickly plateau and approach a minimum and maximum. The four-parameter logistic curve in the figure relates to the following four parameters: It relates to the minimum, or the point of least response; it can be an output response, a control, or a response when the value of the feature is zero. The maximum is the point of greatest response. The inflection point is the number of hours at which the curvature of the response line changes, where the rate of change changes signs, and it is often referred to as IC50 or EC50. IC50 is half of the maximum inhibitory concentration, which is a measure of the strength of a substance in inhibiting a specific biological or biochemical function. IC50 is a quantitative measure that indicates how much of a specific inhibitory substance is needed to inhibit a given biological process or biological component by 50% in vitro.

Two definitions of EC50/IC50s were considered: relative and absolute. The relative EC50/IC50 is parameter c in the four-parameter logistic model and is the concentration corresponding to a response midway between the estimates of the lower and upper plateaus. The absolute EC50/IC50 is the response corresponding to the 50% control (the mean of the 0% and 100% assay controls). The guidelines first describe how to decide whether to use the relative EC50/IC50 or the absolute EC50/IC50. Assays for which there is no stable 100% control must use the relative EC50/IC50. Assays having a stable 100% control but for which there may be a more than 5% error in the estimate of the 50% control mean should use the relative EC50/IC50. Assays that can be demonstrated to produce an accurate and stable 100% control and a less than 5% error in the estimate of the 50% control mean may gain efficiency as well as accuracy by using the absolute EC50/IC50. Next, the guidelines provide rules for deciding when the EC50/IC50 estimates are reportable. The relative EC50/IC50 should only be used if there are at least two assay concentrations beyond the lower and upper bend points. The absolute EC50/IC50 should only be used if there are at least two assay concentrations whose predicted response is less than 50% and two whose predicted response is greater than 50%.

The hill factor is the slope of the curve at the point of inflection. Note that the four-parameter logistic curves (4PL) were symmetrical around the inflection point (Table 2).

3.2. Germination Energy, Strength, and Capacity of Seeds

The stimulation of the seeds under the influence of an FM contributed to a significant increase in the germination strength, energy, and capacity of the common bean seeds (Figure 5).

The germination power, also called the use value, is the ratio of the seeds that sprouted to all that were sown. It turned out that a shorter exposure to the FM resulted in a higher germination power (Figure 5). By establishing this, we were able to predict whether the yield would be high.

The germination energy ranged from 85 to 98%, and the application of the FM significantly increased the value of this feature; the duration of the exposure had no significant effect on the germination energy of the common bean seeds, although an additional trend was observed (Figure 5).

The germination capacity was high and ranged from 95% to 100% (Figure 5). On the basis of the analysis of variance, a significant effect of the exposure time of the FM on the germination capacity of the beans was found.

3.3. Weight of the Leaf

The leaves’ weight was dependent on both the dates of their collection and the stimulation of the seeds with the FM (Figure 6).

The weight of the first leaf was increased on the fortieth day of vegetation. On day 60 of vegetation, we found a decrease in this feature’s value, which was connected with plant aging. On average, the presowing FM stimulation of the seeds significantly increased the weight of the first leaf compared with the control object but only in combination with a shorter stimulation time (Figure 6). The plant response to the FMs depended on the date of their harvesting. In the first period of their harvesting, there was an increase in the weight after both FM exposures in relation to the control object. The difference in the leaf weight between exposure I and II turned out to be irrelevant. In the second period of the harvesting of the leaves, a significant increase in the features was found only in the objects with a shorter FM stimulation compared with the control object. In the third period of the collection of leaves, no significant effect of FM seed stimulation on their weight was observed. Additionally, even in the object with more prolonged FM stimulation, there was a tendency towards the reduction of the weight of the leaf compared with the combination with a shorter stimulation of the field (Figure 7).

A significant increase in the weight of the fifth leaf compared with the control object occurred only in the objects with a shorter FM exposure time. The increase in the fresh weight of the fifth leaf depended on the date of its collection. In the first term of the collection of leaves, 28 days after sowing, there was an increase in this feature due to the stimulation of the seeds with the FM only in the conditions of the prolonged effects of this treatment compared to the control object. Additionally, the difference between a shorter and longer duration of exposure to the FM turned out to be irrelevant. In the second term of the collection of leaves, a significant increase in the weight of the leaf was only found in the object with a shorter exposure of the seed to the FM compared with the control object. Maximizing the impact of this field on the bean seeds caused a significant decrease in the weight of the leaf. In the third period of the collection of leaves, after 49 days after sowing, there was no significant effect of the FM stimulation of the seeds on the value of this feature; even in the object with a longer interaction of this field with the bean seeds, we observed a tendency towards the reduction of the weight of the leaves (Figure 7).

3.4. The Effect of Stimulation of Seeds and Deadlines of Collection on the Dry Weight of Leaves

During vegetation, we also determined the dry weight of the leaves. The water content in the leaves depended significantly on the dates of their collection and their exposure to the FM (Figure 8).

A significant impact of seed exposure to the FM on the value of this feature was found in the objects with a shorter exposure of the seeds to the FM. This regularity, however, proved to be dependent on the date of leaf harvest. The dry matter content in the leaves increased gradually with the prolongation of plant growth. A significant effect of seed stimulation with the FM on the value of this trait was observed only on the first date of the collection of leaves in the objects with a longer exposure of the seeds to the FM (30 s) in relation to the control object. On the other dates, the impact of this factor turned out to be insignificant; we observed an increase in the value of this feature in combination with a shorter exposure of the seeds to the FM only on the third date of the collection of leaves (Figure 8).

During the growing season, the first and fifth leaves of the common bean were plucked, counting from the top to the bottom of the plant, in order to determine their fresh and dry weight. The fifth leaf is considered to be representative of the whole plant [13].

3.5. Significant Differences in Plant Growth Were Observed Only between the Plant Measurement Terms

With respect to the meteorological conditions in the years of the research, neither FM stimulation time of the seeds had any significant influence on the value of this feature. Only tendencies towards higher plant growth were observed in the objects with a shorter exposure of the seeds to the FM (

Table 3. Effect of stimulation of seeds and dates of measurement on the amount of common bean plants (cm).

Experimental Factors	Specification	The Terms of Measurement, Days				HSDp0.05
		20	40	60	Mean
Magnetic field stimulation *	Control object Exposition I Exposition II	11.37 a 11.97 a 11.70 a	31.13 a 30.67 a 31.33 a	36.25 b 38.45 a 36.16 b	26.25 a 27.03 a 26.40 a	ns **
	HSD p0.05	1.36			-	ns
Years	2015	11.37 a	31.13 a	36.25 b		ns
	2016	11.97 a	30.67 a	38.45 a
	2017	11.70 a	31.33 a	36.16 b
	HSDp0.05	1.36
	Mean	11.68 c	31.04 b	36,9 a	26.56

* Control object—the seeds without stimulation with FM, exposition I—time of FM exposure was 15 s, and exposition II—time of FM exposure was 30 s. ** Not significant at p_0.05.; Letter indicators (a, b, c, etc.) next to averages refer to the so-called homogeneous (statistically homogeneous) groups. The occurrence of the same letter indicator next to the means (at least one) means that there are no statistically significant differences at p_0.05 between them.

).

Significant differences in the growth of the bean plants also occurred in the interaction of the FM with the plant measurement dates. After 60 days after the stimulation of the seeds with an FM, higher plant growth was found in the objects with a shorter exposure to the FM only in the last measurement period (Table 3).

3.6. Variability of Bean Features and Their Interdependencies

The variability of the selected morphological and physiological features and their descriptive statistics are presented in

Table 4. Descriptive characteristics of germination, plant growth, and leaf weight.

Specification	Plant Heigh	FW of the First Leaf	FW of Fifth Leaf	DW of the Leaves	Germination Energy	Seed Germination Power	Seed Germination Capacity
Mean	11.68	0.88	4.42	14.77	39.33	93.00	98.11
Standard dev.	0.67	0.09	0.43	1.10	5.60	5.88	2.33
Kurtosis	−0.61	0.98	0.96	−1.54	−1.48	−1.49	−1.14
Skewness	0.83	1.14	1.13	0.06	−0.44	−0.66	−0.80
V *	5.71	9.84	9.83	7.45	14.24	6.33	2.37

* Coefficients of variation (%).

.

The average value of the examined features and their standard deviations made it possible to calculate and track their kurtosis, skewness, and coefficients of variation. Kurtosis is one of the measures of the shape of the distribution of trait values and allows one to determine the intensity of the occurrence of extreme values in a given community, so it measures what is happening in the so-called “tails” of the distribution. Kurtosis is, therefore, a relative measure of the concentration and flattening of a normal distribution. It determines the distribution and concentration of values (collectives) close to the average. It comes in a form that uses a fourth-order central moment:

$$\mathrm{K}=\frac{m_4}{s^4}$$

(3)

where m₄ means the central moment of the fourth order and where s⁴ is the standard deviation raised to the fourth power. The relative kurtosis, calculated in this way, can take both negative and positive values. Positive values usually characterize more pointed distributions compared to the normal distribution, i.e., they are called leptokurtic. Negative values characterize distributions that are more flattened than the normal distribution and are called platykurtic. In the case of the traits under consideration, only the fresh weight of the first and fifth leaves were characterized by positive, right-sided kurtosis, while the others were characterized by left-sided, negative kurtosis on a platykurtic distribution (Table 4).

Skewness is a measure of the symmetry or asymmetry of a distribution. If the distribution is perfectly symmetric, the value of skewness is zero. On the other hand, its negative values indicate a left-skewed distribution (where the left arm of the distribution is elongated), and its positive values indicate a right-skewed distribution (where the right arm of the distribution is elongated). The physiological features related to seed germination were characterized by a negative coefficient of skewness, while the remaining features were characterized by a positive coefficient (Table 4).

One of the coefficients used in statistics is the coefficient of variation. This coefficient of variation, or CV, is a measure of relative volatility and is expressed as a percentage. It is the ratio of the standard deviation to the mean. This coefficient informs us about the variability of the results in relation to the “average”. This allows for the determination of a relative measure of dispersion and facilitates the comparison of the variability of given features regardless of the scale of the units. The coefficient of variation allows you to assess the strength of the differentiation of a given statistical population by showing the strength of the variable, and it also evaluates the arithmetic mean. It is assumed that a CV of <25% represents low volatility, a CV of 25–45% represents average volatility, a CV of 45–100% represents strong volatility, and a CV of >100% represents very strong volatility. In the case of the discussed traits, all of them were characterized by a low variability, but the lowest variability, and thus the greatest stability, was the germination capacity of the bean seeds (Table 4).

The extent to which the examined variables were interdependent was determined by Pearson’s linear correlation coefficient—a coefficient determining the level of linear dependence between random variables that was developed by Karl Pearson [14] (

Table 5. Simple correlation coefficients of morphological and physiological features of common bean.

Specification	Plant Height	FW of the First Leaf	FW of Fifth Leaf	DW of the Leaves	Germination Energy	Seed Germination Power	Seed Germination Capacity
Plant height	1.00
FW of the first leaf	0.58 **	1.00
FW of fifth leaf	0.58 **	1.00 **	1.00
DW of the leaves	0.95 **	0.50 **	0.50 **	1.00
Germination energy	0.89 **	0.75 **	0.74 **	0.90 **	1.00
Seed germination power	0.93 **	0.69 **	0.69 **	0.94 **	0.98 **	1.00
Seed germination capacity	0.65 **	0.86 **	0.86 **	0.62 **	0.88 **	0.78 **	1.00

** Significant at p_0.01.

).

All the assessed morphological features of the plants and the features related to seed germination were significantly positively correlated. The highest correlation coefficients were characterized by plant height, and it was most closely related to leaf dry weight (r = 0.96); the lowest correlation was with the fresh weight of the first and fifth leaves (Table 5).

4. Discussion

Modern agricultural engineering is looking for “safe” methods to increase the quality of crops using the interdisciplinary link between the sciences and the fields of biophysics, molecular biology, agriculture, and physics. Good quality and proper seed preparation are provided as two of the most important yield-generating factors. The use of some physical factors poses new possibilities for stimulating plant material to grow. The methods of presowing seed treatments are stimulating the course of physiological and biochemical changes, as they are safe for the environment. Among these methods, stimulating; ionizing; laser, infrared, ultraviolet, and ultrasound radiation; microwaves; and electric, magnetic, and electromagnetic fields are included [12,13,41]. The impact of the magnetic field was assessed on the basis of the average germination time (AGTC) coefficients according to Pieper and the coefficients of the germination rate (CGR) according to Maguire. These coefficients were compared for granulomas stimulated with a magnetic field and for the sample control, i.e., seeds not stimulated with a magnetic field. On the basis of these studies, it is possible to unequivocally state the influence of a constant magnetic field on common bean seeds. The conducted research showed that the theoretical assumptions turned out to be correct. The magnetic field had a positive effect on the bean seeds. The seeds stimulated with a constant magnetic field sprouted more than the nonstimulated seeds. Cieśla et al. [12] observed that the sprouts of wheat seeds stimulated with an FM were longer. They also observed that, in a dish with unstimulated kernels, several grains decomposed and that mold appeared. This was not observed in the stimulated seed plates. The results obtained during the research testify to the complexity of the subject matter. The time, speed, uniformity, and timing of germination are some of the characteristics that can be measured, thus informing the dynamics of the germination process. These features are important not only for seed physiologists and plant production technologists but also for ecologists because it is possible to predict the degree of success of a given species based on the seed’s ability to spread germination over time. The authors are aware that the problem of the influence of the magnetic field on plant germination and growth has only been outlined in this paper and requires further research.

The four-parameter logistic curve is a model frequently used to analyze biological tests, such as seed the germination rate or the plant growth rate. They follow a sigmoidal or “s” shaped curve. This type of curve is particularly useful for characterizing bioassays because bioassays are often only linear over a certain range of concentrations. Outside this linear response range, they quickly plateau and approach a minimum and maximum.

The presowing FM stimulation of the common bean seeds did not significantly affect plant growth or the dry weight of the leaves, but it preferably affected the fresh weight of the first and fifth leaves. Shine et al. [4] and Radhakrishnan and Kumari [5] proved that applying an FM in the laboratory can improve not only the parameters associated with the germination of soybean seeds but also the plant height and the fresh and dry weight. In the conducted research, the FM was used to stimulate the seeds before sowing, and a positive effect was observed in most cases; however, this was not always statistically proven.

FM studies are a very important tool for studying the electronic structure of condensed matter systems. The application of an FM in many cases has a relatively small effect on the overall electronic structure, making it possible to make experimental techniques that can reveal the properties of the underlying electronic structure available that would otherwise be unavailable. It can be assumed that this effect is achieved due to the acceleration of the biochemical processes that occur during the process of seed germination of a species, as Bing and al. [35] proved that the use of the FM intensifies the function of protective enzymes. A similar effect under the influence of the presowing magnetic stimulation of the fava bean, with the induction of an FM of 30 and 85 mT and with an interaction time of 15 s, was found by Podleśny et al. [8]. Owing to that, an earlier and more uniform emergence of the plants occurred. Podleśny and Pietruszewski [16], Kornarzyński and Pietruszewski [10], Romankiewicz [11], and Aladjadjiyan [38] also noted a higher efficiency of germination due to FM seed stimulation. This effect was observed for peas by Yamashita et al. [42], for fava beans by Podleśny [7], for white lupines and peas by Podleśny and Pietruszewski [9,16] and by Romankiewicz [11], for beans by Kornarzyński and Pietruszewski [10], and for lentils and onions by Aladjadjiyan [38]. This effect was also observed by Maffei [43] for beans, peas, watercress, sunflowers, wheat, barley, and potatoes. Yamashita et al. [42] suggest that the cell elongation of pea epicotyls results from the fact that the osmotic pressure of the seedlings is significantly higher at low values of FMs. Despite the correct structure of the seeds, as they contained a viable embryo, and despite being in compliance with all the recommendations of the International Seed Testing Association, no effect of FM exposure on the strength and energy of the germination of the bean seeds was observed. Similar results in terms of germination were obtained by Winiarczyk [44]. Despite additional scarification and stratification treatments, these authors did not improve the germination dynamics of the tested seeds. Broszkiewicz et al. [31] found the growth rate of a cultivar of large roots among seeds exposed to a static FM. The germination rate varied depending on the field strength—the time of exposure to the field. Furthermore, pea seedlings under the influence of an FM accumulated lipid bodies while reducing the ferritin in plastids. Belyavskaya [28] recognized that the low-FM effects in the ultrastructure of root cells are due to the interference of various metabolic systems, including the impact of Ca²⁺ on homeostasis. According to Liu et al. [36], this benefit results from the fact that FMs and ultrasound radiation can increase cell membrane permeability and susceptibility to mechanical impacts. The increase in the cell membrane’s permeability can influence the rate of seed germination, plant growth, and the yield. The cell wall, which chiefly comprises cellulose and pectin, has total permeability and may support and protect the cell membrane and cytoplasm. The cell membrane is very close to the cell wall and is flexible. It accepts the vibration induced by the FM, which can lead to the resonance of the cell membrane and can increase its permeability, resulting in several biophysical effects. Çelik et al. [45], in turn, claimed that, in plant cells, FMs create a state of stress. In response to this stress, defence systems against reactive oxygen forms are needed. Accordingly, soybeans were treated with an FM of 2.9–4.6 MT for 2.2, 9.8, and 33 s. The activities of superoxide dismutase and catalase significantly increased during the germination of the soybean, respectively, by 21.15% and 15.2% in relation to the control. The increase of the FM with different exposure times did not, however, result in a linear rise in the enzymes’ activity in both the in vitro and in vivo examinations. The effect of the 130 mT FM stimulation (FMS) on the growth and selected biochemical parameters of a common bean (P. vulgaris L.) in laboratory conditions was described by Mroczek-Zadyrska et al. [20]. Their results indicate that the FMS of plants with a weak and constant FM (130 mT) increased the mitotic activity in the meristematic cells of the common bean (P. vulgaris L.), whereas there was no effect of FMT at 130 mT on the development of the aboveground parts of the plants. They, however, proved that there was a noticeable increase in the activity of GPOX in the leaves after 130 mT magnetic stimulation, which gives hope for the use of this treatment for presowing seed stimulation.

Kouchebagh et al. [46] showed in laboratory conditions that the stimulation of sunflower seeds with an FM has a more substantial effect on seed germination and initial plant growth compared to such physical factors as laser light, ultrasound, gamma, and beta irradiation and soaking seeds in water before sowing (hydropriming) for 24 h.

Podleśny et al. [47], in an experiment with the use of an FM in the preparation of pea seeds for sowing, proved that the activity of amylolytic enzymes (in the seeds of this species?) increased with the duration of the experiment, reaching the highest value 144 h after sowing the seeds. The FM also increased the seed stimulating effect, with a higher dose of the FM having a greater effect on the enzymatic activity. The use of FM seed stimulation increased the content of the studied phytohormones in the germinating seeds and in the above-ground parts and roots of the pea seedlings. These authors found a significant effect of both FM doses on all the biochemical and physiological parameters of the pea seedlings. Seed stimulation influenced the growth of the stem and roots of the pea seedlings. Seed stimulation also resulted in an increase in the weight of the pea seedlings, where a higher dose of the FM had a more favorable effect on this morphological feature of Pisum sativum.

The presowing FM stimulation of common bean seeds did not significantly affect either plant growth or the dry weight of the leaves. However, it preferably affected the fresh weight of the first and fifth leaves. [4,5] proved that an FM can improve not only the parameters associated with soybean seeds’ germination but also plant height and the fresh and dry weight. There are also controversial figures. The exposure to a near-zero FM of different species of the plants of the genus Solanum in in vitro cultures proved to be either stimulatory or inhibitory to the plants’ growth. This effect was also clearly dependent on the species, genotype, primary explant type, treatment duration, and even the type of medium [48]. According to Sarraf et al. [49], to increase the seed germination, growth, and development of common beans, the right combination of FM intensity and exposure time is essential. Many studies have shown that it can have a positive effect on seed germination, root and shoot length, water and CO₂ absorption, and photosynthetic pigment content and, finally, that it can cause an increase in agricultural production.

The differences in the FM effects on the seeds can result from different FM doses and exposure times; the quality of the seed material used—the lower the quality of the stimulation, the better the effects are; the seed moisture content, which affects the absorption of the energy of the FM; the phenotypic variability of the species and varieties of crops; and the meteorological conditions during the plants’ growth [8,10,32,38]. Mroczek-Zdyrska et al. [20] confirmed that plants’ responses to FM stimulation (FMS) are varied and depend on many factors, such as the intensity, exposure time, and application form. Their results indicate that the stimulation of plants with a weak, constant FM (130 mT) increases the mitotic activity in common beans’ meristematic cells The differences in the FM effects on the seeds can result from different FM doses and exposure times.

The Stimulant Effect on Plants in the Early Stages of Their Growth

Seed germination is considered to be one of the most critical steps in successful seed sowing and efficient plant growth and development. Successful germination depends on many factors, such as seed moisture and growing conditions, such as humidity and air temperature, but it also depends on biotic and abiotic factors [14,31,39]. The FM treatment in our own research was also used to induce changes in the genetic improvement programs for this species in the future. The improvement of the morphological, physiological, and individual characteristics is urgently needed, mainly to break seed dormancy, improve seedling growth, and induce genetic variation in order to select desired traits.

Plant growth is a genetically determined feature but may be modified by environmental conditions. Plant height can be varied by biotic (environmental) and abiotic factors. The study showed no significant effect of the FM on the growth of plants. There was only a trend towards increasing seedling growth in the objects with the presowing use of the FM. Podleśny [7] demonstrated the significant impact of the 15 s treatment of fava beans with an FM of 30 and 85 mT on the plants’ growth in the early stages of the growing period. The Tim and Nadwiślański fava bean varieties, at the end of the growing season, were characterized by a significantly higher increase in aerial parts. Kornarzyński and Pietruszewski [10] demonstrated that the most significant changes under the influence of the FM take place in the early stages of the germination of bean seeds (only in old seeds), lasting from a few to several hours. Podleśny and Pietruszewski [9] also observed a faster growth of the fava beans in the early stages depending on the inductance and the FM frequency. Podleśny and Pietruszewski [16] observed that, with age, the plant growth of previously stimulated lupine seeds was reduced to the control object’s level or remained higher. The best effects of an FM under experimental conditions were obtained by Aladjadjiyan [38], with the induction of an FM of 150 mT and with exposure times of 6 and 9 min, for the parameters measured 2 weeks after emergence. The current research and the research of Podleśny [7], Sowiński [50], and Carbonell et al. [51] showed significantly higher plant growth during the last measurement. Differences in plant growth may result from both the inductance and frequency of the applied FM, the treatment time, and the species’ phenotypic variability or different varieties as well as the site conditions [2,5,9,21,24,32,33,38,39,43,50,52].

The mechanism by which plants perceive an FM and regulate the signal transduction pathway is not fully understood. Various authors have suggested that FM perception/signalling in plants is mediated by blue light photoreceptors—the so-called cryptochromes. It has also been found that ROS and NO are signal molecules for magnetopriming-induced seed germination. However, this aspect of magnetobiology still needs to be explored in depth, and there are potential genotoxic side effects of FMs [24]. All the authors emphasized the need for further research in order to broaden the current knowledge on the molecular mechanisms related to the fixation of seed germination, increasing the vigour of seedlings and their strengthening [4,21,24,39,41,49,53,54]. The photosynthetic capacity of crops subjected to an FM under abiotic stressors is a separate issue. In general, despite all the efforts and research carried out on FMs, there is still a knowledge gap, so further and better experiments are needed.

Iderawumi and Eneminyene [55] proved that FM effects can be strong enough to drastically alter the nature of the electronic state itself. Boix et al. [56], conducting research with common beans fed with magnetized water and control water, proved that the concentrations of chlorophyll a, chlorophyll b, and carbohydrate dyes in the plants grown with magnetically treated water were stimulated compared to the control plants, obtaining increases of 13, 21, and 26%, respectively. The technology used in the research did not have a negative impact on the plants, neither on the presence of structures nor on the net content of the evaluated compounds. These authors concluded that Ph. vulgaris L. may be a viable alternative for plant improvement in organic production. Jakubowski et al. [57] proved that a variable FM can modify the processes related to the growth and development of plants. In addition, they showed that the reaction of the tested plants to the physical factor used in the experiment (the best effect was obtained using a dose of 143.2 kJ·m⁻³) depended on the variety. In addition, they proved the significant influence of a variable FM on some ontogenetic parameters of the plants.

Although the influence of the FM on living organisms, including seed germination and plant growth, was already known at the end of the 19th century, no thorough research on this phenomenon was undertaken. A rapid increase in the interest in the influence and use of FMs for the biostimulation of seeds or seedlings developed only in the second half of the 20th century [4,5,58,59]. This problem is still far from being fully explained due to its complex physical nature and the geometry of the objects. FMs can penetrate living organisms practically undisturbed. Therefore, all tissues and cell interiors are subjected to this field. FMs can affect living organisms through the following:

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electrodynamic interactions with electric currents occurring in organisms (Lorentz force and Hall effect) [56,60];

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the movement of a living organism in relation to the FM, which may be the reason for inducing currents;

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the magnetomechanical effects occurring inside organisms, consisting in the orientation of structures with magnetic anisotropy in homogeneous fields and the shifts of ferromagnetic and paramagnetic substances in fields with nonzero gradients;

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there may also be an impact on the uncompensated magnetic spins of paramagnetic elements and free radicals;

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the Zeeman effect is possible, i.e., the splitting of the spectral lines of atoms placed in a static FM in components that differ slightly in wave numbers;

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there may also be the Dorfman effect, consisting in the reorientation of proteins in the magnetostatic field due to the anisotropy of these molecules;

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the external FM changes the properties of liquid crystals and, therefore, affects the properties of membranes; cell organelles; and, consequently, more complex systems;

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some components of living organisms exhibit magnetostrictive properties. It is therefore possible to influence such components;

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a static FM can affect water, which changes its properties when subjected to an external field: the rate of its crystallization, the concentration of dissolved gases, the rate of coagulation, and the settling of suspensions increase. The pH and wetting ability change [4,5,60,61,62].

In general, despite all the efforts and research carried out on FMs, there is still a knowledge gap, so further and better experiments are needed.

5. Conclusions

• The biostimulation of the seeds with an FM contributed to a higher germination capacity, energy, and strength of the common bean seeds. The biological optimum of the seed germination of the common bean determined the regression curves of the second and third degree.
• The presowing FM stimulation of the common bean seeds favourably affected the fresh weight of the first and fifth leaves.
• The highest fresh weight of the leaves was obtained in the full flowering phase of the plants, and their dry weight was obtained in the pod setting phase.
• The biostimulation with an FM led to a significant increase in dry matter accumulation in the plants and leaves. The more remarkable ability of the roots, stems, and leaves of the plants obtained from the seeds treated with a variable FM to accumulate dry matter suggests a beneficial effect on the plants’ development and health.
• The physical method of treating seeds with an FM applied before sowing is a noninvasive method and is environmentally friendly and useful, especially in the seed production not only of legumes but also of other crops and vegetables in ecological systems.
• The obtained results may be a premise to continue research in this direction, taking into account not only other solenoid operating parameters but also the features of the physical raw materials and semifinished products obtained from the bean seeds subjected to an FM.