Assessment of Physiological Traits of Fragaria vesca Genotypes Under Water Deficit Conditions

Abstract

Drought is one of the key challenges of climate change. The basic global problem related to the increasing water deficit is that the vast majority of crops are species and varieties that are the result of breeding work that did not anticipate such a rapid decrease in water availability in the soil. The main objective of the conducted research was to compare the physiological and biochemical response to water deficit of plants of the species Fragaria vesca—two cultivated varieties, and one collected from the natural environment. A two-year pot experiment was conducted in a polyethylene tunnel. The substrate moisture level was monitored using tensiometer readings. Measurements of gas exchange parameters, chlorophyll “a” fluorescence, content of photosynthetic pigments in leaves, index of relative water content in leaves, total fruit yield, single fruit mass and content of K, Ca, Mg, Na, Cu, Zn, Mn, Mo and the ratio of mono- to divalent cations in leaves, roots and plant crowns were taken three times each year during the experiments. Based on one-way and two-way analysis of variance, statistically significant differences were observed between wild-growing plants and cultivated varieties under control conditions, particularly in terms of chlorophyll fluorescence values and the content of photosynthetic pigments. A significant main effect of the soil moisture level was identified for most measured parameters across the majority of assessment time points. However, a significant interaction effect between soil moisture level and genotype was less frequently observed. Significant changes in response to water deficit varied depending on the parameter and genotype, ranging from 2.5% to 106.1%. For the content of chemical elements, the changes reached up to 157.1%. The results suggest that plants obtained from natural environments exhibit better adaptation to water deficit conditions, making them suitable for use in breeding programs aimed at developing varieties resistant to soil water deficits. However, the study’s limitations, particularly the absence of molecular analyses regarding the plants’ adaptive mechanisms, should be taken into consideration.

1. Introduction

Phenomena of drought and desertification, exacerbated by climate change, adversely impact global food security and human health and may even pose a threat to global peace [1,2,3]. Climate models project that drought severity could double across 30% of the global land area under rigorous mitigation scenarios, leading to substantial implications for water supply and demand deficits [4]. Water deficit stress poses a significant challenge to agriculture, making plant resilience to water scarcity of critical economic importance [5]. In Poland’s climate, periodic meteorological droughts [6] disrupt the water balance of affected areas, leading to soil droughts that impair crop productivity [7]. In temperate climates, drought is among the primary factors limiting crop yields [4,8]. A fundamental global challenge associated with the increasing water deficit is that the majority of cultivated crops, including those of the Fragaria genus, consist of species and varieties developed through selective breeding, often without adequate consideration for the current significant reductions in soil water availability [9].

The economically most significant species of the Fragaria genus is the cultivated strawberry (Fragaria × ananassa Duch.), whose fruits are among the most widely consumed globally [10,11]. In Poland, plants of the Fragaria genus also hold considerable economic importance [8,12]. In 2020, the share of Fragaria plants in the total fruit yield from fruit bushes and berry plantations reached 26.0% [13]. The wild strawberry (Fragaria vesca L.) is primarily cultivated on an amateur scale. Although F. vesca is not commercially grown, its valuable traits as a research model have been extensively highlighted, particularly due to its short generation time, well-defined cycles of seasonal flowering and vegetative growth, and single-gene traits controlling aspects such as flowering and fruit color [14].

Plants of the Fragaria genus are highly sensitive to water deficiency due to their large leaf surface area, high water content in fruits, and shallow root systems. This sensitivity has been highlighted in numerous studies, which report a decline in physiological parameters in plants exposed to water deficit conditions [3,15,16,17,18,19,20,21]. However, this trait is undesirable in commercial cultivation, as even minor deviations from optimal irrigation levels can result in reduced yields, diminished fruit quality, decreased profitability of crops, and failure to meet consumer and market demands. Consequently, a key objective for breeders is to develop varieties with enhanced tolerance to water deficits in the soil.

An essential preliminary step in breeding programs aimed at enhancing plant resistance to water deficit through improved water-use efficiency is to assess the degree of adaptation of various genotypes (cultivars) to limited water availability. For example, the development of drought-resistant wheat and cotton varieties has shown promise in maintaining agricultural productivity despite environmental stress [22,23]. Differences in physiological, morphological, and morphogenetic traits at the cultivar level have been documented in numerous studies [3,11,24,25,26,27]. Wild plant varieties possess genetic resources that enhance their resilience to abiotic stresses, as demonstrated in studies on species such as potato [28] and barley [29]. However, there is a lack of studies evaluating the differences in physiological traits and responses to soil water deficit between cultivated and wild Fragaria species.

Therefore, the aim of this study was to compare the physiological responses of Fragaria vesca plants—two cultivars (‘Rugia’ and ‘Baron von Solemacher’) and a wild strawberry specimen obtained from a natural habitat, to identify the genotypes with greater resistance. This will enable the determination of whether wild-growing plants exhibit lower sensitivity to drought stress, and consequently, whether their use in breeding programs aimed at developing water deficit-resistant varieties is justified. This objective was achieved by testing the following hypotheses: (1) there are physiological differences between cultivated varieties and wild-growing plants, (2) water deficit negatively affects the physiological traits of Fragaria vesca plants, and (3) wild-growing plants exhibit lower sensitivity to water deficit in the substrate compared to cultivated varieties.

2. Materials and Methods

2.1. Materials

The plants used in this study included Fragaria vesca cultivars ‘Rugia’ and ‘Baron von Solemacher’ (seedlings obtained from TOP-PLANT, Szczecin, Poland) as well as wild strawberry seedlings collected from a natural habitat in a forested area near the village of Ciemnik, close to Ińsko, Poland (53°23′ N, 15°34′ E; 105 m a.s.l.). The cultivated varieties used in the study are popular in Poland. Both varieties are high-yielding and produce fruit from June to September. However, ‘Baron von Solemacher’ exhibits lower frost resistance and greater susceptibility to diseases compared to ‘Rugia’ [30]. These characteristics made them suitable candidates for experimental analysis.

2.2. Methods

A two-year pot experiment was conducted during the period of 2018–2019, employing a completely randomized design with 15 replications (one plant per replication). The study was carried out in the vegetation hall of the Faculty of Environmental Management and Agriculture at the West Pomeranian University of Technology in Szczecin, Poland (53°25′ N, 14°32′ E; 25 m a.s.l.). Plastic containers with a capacity of 10 dm³ were used, filled with a substrate consisting of a 1:1 mixture (by volume) of sandy silty clay soil, collected from the arable humus horizon (0–30 cm) at the Agricultural Experimental Station of the West Pomeranian University of Technology in Szczecin, located in Lipnik (Poland), and sand. The physicochemical properties of the soil used in the experiment are presented in

Table 1. The physicochemical properties of the soil used in the experiment.

pH		Fine Soil Fractions [%]	S0 [g·cm−3]	Content of P	Content of K	Content of Mg	Salinity [g·NaCl·dm−3]	Wtv
H2O	KCl			[mg · 100 g−1]
6.70	5.98	21.00	1.25	5.87	12.66	5.98	0.45	37.10

Explanations: S₀—bulk density, W_tv—total water capacity volume.

. To allow for acclimatization to the new conditions, the plants were planted one year prior to the start of measurements (in June) of 3 plants per pot. The seedlings had three fully developed leaves.

Water potential was maintained at −10 kPa to −15 kPa under control conditions (Ctrl) and −30 kPa to −35 kPa under water deficit conditions (Def) in the substrate. Each pot was watered using individual drippers when the water potential in the substrate increased above −15 kPa under control conditions or above −35 kPa under water deficit conditions. Irrigation was carried out to a value of −10 kPa in the control variant and to −30 kPa under water deficit conditions. The adopted water potential range of −30 to −35 kPa was considered as stress conditions for the studied species, based on the findings of various authors [3]. The need for irrigation was determined based on readings from contact soil tensiometers placed at a depth of 20 cm in the pots of each experimental variant. Tensiometric measurements have been successfully employed in other studies investigating water deficit in plants [31,32,33,34,35].

During the vegetation period (from May to October), the pots were placed in the covered section of the vegetation hall. In the remaining months, they were kept in an unheated greenhouse, with a temperature maintained above 0 °C.

Fertilization was carried out twice during the growing season: prior to planting the plants, during pot filling, and after the plants had finished fruiting. In the second year of the study, fertilization took place in early spring, before the start of vegetation, and after the completion of fruiting. A multi-component fertilizer specifically designed for strawberries was used, which, according to the manufacturer (Agrecol Sp. z o.o., Mesznary 2, Poland), contains the following: 15.0% N (6.5% nitrate N, 8.5% ammonium N), 6.0% P₂O₅ (soluble in neutral ammonium citrate and in water, including 5.2% water-soluble P₂O₅), 11.0% water-soluble K₂O, 0.04% total B, 0.1% total Cu, 0.2% total Fe, 0.17% total Mn, 0.01% total Mo, and 0.035% total Zn. The fertilizer was applied at a rate of 4 g per pot each time.

Morphological observations of the plants were conducted systematically throughout the growing season, and emerging stolons were removed. Additionally, plants were regularly inspected for the presence of pests. When pest populations exceeded the economic threshold, chemical treatments were applied as follows:

• Decis Mega 50 EW, targeting aphids (Aphidoidea) at a dosage of 0.25 L/ha.
• Mospilan 20 SP, targeting thrips (Thysanoptera, aphids (Aphidoidea), and greenhouse whitefly (Trialeurodes vaporariorum) at a concentration of 4 g per 10 L of water, applied at 3 L per 100 m².

2.3. Measurements

In each year of the study, three times during the plant growing season, in the second ten days of July, August, and September, the following measurements and analyses were conducted:

• the content of photosynthetic pigments was assessed by the method of Arnon et al. [36] modified by Lichtenthaler and Wellburn [37] for chlorophyll “a”, “b” and total chlorophyll, and the method of Hager and Mayer-Berthenrath [38] for carotenoids;
• the relative leaf water content index (RWC) by the method of Yamasaki and Dillenburg [39];
• the gas exchange parameters, i.e., assimilation intensity CO₂ net (P_n), transpiration intensity (E), stomatal conductivity H₂O (g_s) and substomatal CO₂ concentration (c_i), were measured using a TPS-2 portable gas analyzer with a PLC-4 (PP Systems, Amesbury, MA, USA); the photosynthetic water utilization factor (WUE) was determined on the basis of the P_n/E quotient;
• the fluorescence parameters of chlorophyll “a” were determined using a Handy PEA spectrofluorometer (Hansatech Ltd., Kings Lynn, UK), based on the standard procedure of the apparatus (3 × 650 nm LED, maximum actinic light intensity 3000 μmol m⁻² s⁻¹). The measurement was carried out in each variant on 15 randomly selected, fully grown bean leaves (the repetition was the measurement on one leaf), in a place previously darkened for 20 min, using factory-made clips (the irradiation area was 4 mm). The following parameters were measured: initial (zero) fluorescence, index of excitation energy loss in power antennas (F₀), maximum fluorescence, after reduction of acceptors in PS II and after darkroom adaptation (F_M), variable fluorescence, determined after dark adaptation (the parameter depends on maximum quantum efficiency of PS II) (F_V = F_M − F₀), maximum potential efficiency of the photochemical reaction in PS II, determined after dark adaptation, after reduction of acceptors in PS II (F_V/F_M), chlorophyll fluorescence growth time from the beginning of the measurement to reaching maximum (T_FM), and the area above the fluorescence induction curve of chlorophyll “a” between points F₀ and F_M proportional to the size of the pool of reduced plastoquinone electron acceptors in PSII (A_M (Area)).

In each growing season, the total yield of fresh strawberry fruit was determined by weight, expressed in grams per pot, as well as the weight of a single fruit. Due to the fact that wild strawberries produce fruit throughout almost the entire growing season, harvesting was carried out successively as the fruit reached collective maturity, spanning the period from June to August each year of experiment.

After each experiment, the fresh and dry mass of the root system was determined. The content of K, Ca, Mg, Na, Cu, Zn, Mn, and Mo, as well as the ratio of monovalent to divalent elements in the leaves, roots, and plant crowns, was also measured. The content of calcium, magnesium, sodium, and microelements in plant tissues was determined by atomic absorption spectrometry (AAS) using an iCE 3000 series spectrophotometer (ThermoScientific, Waltham, MA, USA) in wet mineralized material, prepared with a mixture of nitric acid (HNO₃) and hydrochloric acid (HCl) in a 1:1 ratio. Phosphorus content was determined colorimetrically using a Marcel Mini spectrophotometer. Based on the obtained results, the equivalent ratio of monovalent to divalent elements, i.e., K: (Ca + Mg), was additionally calculated.

2.4. Meteorological Data

Szczecin is located in a sub-Atlantic climate zone, where the primary influencing factors include latitude, topography, distance from the sea, and the presence of large industrial and production facilities. These factors result in relatively high annual average air temperatures and a low annual temperature amplitude. Additionally, Szczecin typically experiences mild winters and cool summers.

The key meteorological elements relevant to the conducted research, along with comparisons to multi-year averages, are presented in

Table 2. Meteorological conditions during the growing seasons of the studied plants from 2017 to 2019, compared to multi-year averages for the Szczecin-Dąbie Meteorological Station.

Years	Months							Average/Sum
	IV	V	VI	VII	VIII	IX	X
Mean air temperature (°C)
2017	7.4	14.1	17.2	17.7	18.2	13.6	11.2	14.2
Deviation	−1.8	0.5	0.4	−1.2	−0.3	−0.7	1.7	−0.2
2018	12.3	16.6	18.5	20.0	20.0	15.4	10.3	16.2
Deviation	3.1	3.0	1.7	1.1	1.5	1.1	0.8	1.8
2019	10.1	12.1	21.5	18.8	20.1	14.5	10.7	15.4
Deviation	0.9	−1.5	4.7	−0.1	1.6	0.2	1.2	1.0
1991–2020	9.2	13.6	16.8	18.9	18.5	14.3	9.5	14.4
Sunshine duration (h)
2017	143.2	240.3	215.5	197.1	229.1	130.6	96.4	11,252.2
% of the norm	71.9	98.3	89.0	80.1	99.5	81.6	96.8	88.1
2018	257.6	349.8	253.6	301.0	269.2	204.0	170.36	1805.8
% of the norm	129.3	143.1	104.7	122.3	116.9	127.5	171.3	127.0
2019	285.7	198.2	345.5	222.3	239.1	168.5	-	1459.3
% of the norm	143.4	81.1	142.7	90.3	103.8	105.3	x	102.6
1991–2020	199.3	244.5	242.2	246.2	230.3	160.0	99.6	1422.1
Total precipitation (mm)
2017	42.2	90.8	132.7	192.5	43.8	30.4	93.9	626.3
% of the norm	135.3	162.7	224.5	252.6	72.6	63.7	215.9	167.5
2018	26.8	22.5	15.0	92.8	21.4	16.3	20.2	215.0
% of the norm	85.9	40.3	25.4	121.8	35.5	34.2	46.4	57.5
2019	10.7	68.7	70.8	23.5	41.8	63.2	46.1	324.8
% of the norm	34.3	123.1	119.8	30.8	69.3	132.5	106.0	86.9
1991–2020	31.2	55.8	59.1	76.2	60.3	47.1	43.5	373.8
Relative air humidity (%)
2017	73.8	70.9	74.5	79.4	76.5	82.1	85.6	77.5
Deviation	3.0	−0.6	1.6	5.0	0.6	0.9	0.1	1.5
2018	69.3	63.7	66.4	71.5	67.8	74.2	79.1	70.3
Deviation	−1.5	−7.8	−6.5	−2.9	−8.1	−7.0	−6.4	−5.7
2019	60.0	71.2	65.5	70.0	69.7	78.2	84.3	71.3
Deviation	−10.8	−0.3	−7.4	−4.4	−6.2	−3.0	−1.2	−4.8
1991–2020	70.8	71.5	72.9	74.4	75.9	81.2	85.5	76.0

-—no data available; x—irrelevant data. Source: IMGW Station in Szczecin-Dąbie.

. The data used in this study were sourced from the nearest meteorological station, IMGW Szczecin-Dąbie (Przestrzenna 10 Street).

In the first year of the study (2017), the average air temperature during the growing season was 0.2 °C lower than the multi-year average. The coldest month in the analyzed period was April (7.4 °C), while the warmest was August (18.2 °C). Sunshine duration during the growing season in 2017 was 21.9% below the multi-year average. No month recorded sunshine levels above the average values.

In the second year of the study (2018), the average air temperature during the growing season was 1.8 °C higher than the multi-year average. The lowest average temperature was observed in October (10.3 °C), while the highest was recorded in July and August (20.0 °C). Sunshine duration during the growing season was 27.0% above the multi-year average, with all months exceeding average values.

The third year of the study (2019) was characterized by an average air temperature during the growing season that was 1.0 °C higher than the multi-year average. The coldest month was April (10.1 °C), and the warmest was June (21.5 °C). Sunshine duration during the analyzed period was 2.6% above the multi-year average. April, June, August, and September recorded higher sunshine values compared to the same months in the multi-year period, while the remaining months had sunshine levels below the long-term average.

2.5. Statistical Analysis

The results of the study were statistically analyzed in STATISTICA version 13.3 (StatSoft, Poland). A one-way analysis of variance (ANOVA) was employed to compare genotypes grown under control conditions, while a two-way ANOVA was used to evaluate genotype × substrate moisture interactions in a completely randomized design. The significance of differences between means was determined using Duncan’s multiple range test at a significance level of α = 0.05. Identical single-letter labels were assigned to means that did not differ statistically. The analyses were conducted separately for each measurement period.

In the case of two-factor analysis of variance, means denoted by the same lowercase letter did not differ significantly within the context of a significant interaction effect. Similarly, means denoted by the same uppercase letter showed no significant differences with respect to the significant main effect (substrate moisture level; SML). The main effect of genotype (G) was not analyzed in the two-factor analysis due to the assumption that responses to water stress vary among genotypes and may follow different directions of change. Comparisons of genotype values were performed using one-way analysis of variance exclusively under control conditions.

2.6. Radar Charts

The radar charts present the values of selected analyzed parameters. The differences between the values for plants grown under control and water-deficient soil moisture conditions were used to calculate the parameter values shown in the charts.

For the S parameters—i.e., those for which a smaller decrease under water deficit conditions, compared to controlmoisture conditions, indicated better adaptation to stress (E, g_s, P_n, c_i, WUE, F₀, F_M, F_V, F_V/F_M, chla, chlb, chl total, carot, RWC, fruit fresh mass yield, single fruit mass)—the following formula was used:

$$S={\displaystyle \frac{S_{Def}\times 100}{S_{Ctrl}}}$$

(1)

where:

• S_Def—parameter value in conditions of deficit soil moisture;
• S_Ctrl—parameter value in conditions of control soil moisture.

For the D parameters—i.e., those for which a smaller increase under water deficit conditions, compared to control moisture conditions, indicated better adaptation to stress (T_FM, A_M)—the following formula was used:

$$D=100-({\displaystyle \frac{D_{Def}\times 100}{D_{Ctrl}}}-100)$$

(2)

where:

• D_Def—parameter value in conditions of deficit soil moisture;
• D_Ctrl—parameter value in conditions of control soil moisture.

The charts were constructed based on a series of analyses testing the significance of differences between means for individual object types, using one-way analysis of variance (ANOVA). For means that did not differ significantly from each other, as well as for values showing trends divergent from the general patterns—i.e., for S parameters, where values under deficit conditions were significantly higher than those under control conditions, and for D parameters, where values under deficit conditions were significantly lower than under control conditions—a value of 100 was assigned on the radar graphs.

Comparisons of the studied objects were made by calculating the area of the polygon formed by the chart line.

3. Results

3.1. Evaluation of Differences in Physiological Traits, Chemical Composition, and Yield Among Genotypes

3.1.1. Gas Exchange Parameters

The results showed that, for each measurement term, the highest values of transpiration intensity (E) under control substrate moisture conditions were characteristic of different varieties (

Table 3. Gas exchange parameters in leaves of F. vesca genotypes.

Parameters	Genotypes	Measurement Terms
		1st Year			2nd Year
		July	August	September	July	August	September
E [mmol H2O∙m−2∙s−1]	B	1.105 a*	0.502 b	0.967 a	0.707 a	0.841 ab	0.573 b
	R	1.017 b	0.645 a	1.036 a	0.571 b	0.992 a	0.525 c
	N	1.120 a	0.653 a	0.726 b	0.687 a	0.737 b	0.907 a
gs [mol H2O∙m−2∙s−1]	B	0.094 a	0.137 a	0.061 ab	0.064 a	0.043 b	0.063 b
	R	0.087 a	0.107 b	0.064 a	0.048 b	0.053 a	0.049 b
	N	0.086 a	0.150 a	0.050 b	0.060 a	0.038 b	0.120 a
Pn [mmol H2O∙m−2∙s−1]	B	6.747 a	2.200 b	4.727 a	3.760 a	1.520 b	2.513 b
	R	6.847 a	1.780 b	3.740 ab	3.487 a	3.873 a	4.107 a
	N	7.307 a	3.253 a	3.427 b	3.760 a	4.260 a	4.893 a
ci [μmol CO2∙mol−1]	B	311.00 a	421.33 ab	315.00 a	298.20 a	355.73 a	498.47 a
	R	299.93 a	426.20 a	302.53 a	280.87 a	289.40 b	371.47 b
	N	279.80 b	411.73 b	304.53 a	298.87 a	244.33 c	449.80 a
WUE	B	6.201 a	3.484 b	5.167 a	5.409 a	1.922 c	4.656 b
	R	6.747 a	3.812 b	3.799 a	6.253 a	4.028 b	5.432 b
	N	6.519 a	5.168 a	5.173 a	5.328 a	6.533 a	20.713 a

Explanations: B—‘Baron von Solemacher’ cultivar; R—‘Rugia’ cultivar; N—plants obtained from a natural habitat. *—means marked with the same letters do not differ significantly at the significance level of α = 0.05.

). On the first measurement date of each study year, the ‘Rugia’ variety exhibited a significantly lower E value compared to the ‘Baron von Solemacher’ variety (by an average of 13.6%) and plants obtained from the natural environment (by an average of 13.0%). For the remaining dates, except for the third measurement date of the second study year, the ‘Rugia’ variety most frequently exhibited the highest E value (by an average of 35.3%). On the final measurement date of the experiment, this variety again had the lowest E value among the tested genotypes (by 8.4% lower than ‘Baron von Solemacher’ and by 42.1% lower than wild plants).

Similar differences were observed for the stomatal conductance of H₂O (g_s). In the first term of the first year of the study, no significant differences were found between the genotypes. The ‘Rugia’ cultivar exhibited the lowest g_s value in the second term of the first year (by an average of 25.3%), the first term of the second year (by an average of 22.5%), and, together with the ‘Baron von Solemacher’ cultivar, in the third term of the second year (by an average of 53.3%). However, in the second term of the second year, the highest g_s value was observed for the ‘Rugia’ cultivar among the analyzed genotypes (by an average of 23.6%).

A significant differentiation between the analyzed genotypes, depending on the measurement date, was also observed for net CO₂ assimilation intensity (P_n). On the first measurement date of each year, no differences in P_n values were found among the genotypes. Plants collected from the natural environment exhibited the highest P_n value on the second measurement date of the first year (by an average of 38.8%), and, along with the ‘Rugia’ cultivar, on the second and third measurement dates of the second year (by an average of 53.1%).

Similar to other gas exchange parameters, the substomatal CO₂ concentration (c_i) also varied across the individual measurement dates. Across all dates, the ‘Baron von Solemacher’ cultivar most frequently exhibited the highest c_i value among the tested genotypes, particularly in the second term of the second year of the study, where the value was 18.6% higher than that of ‘Rugia’ and 31.3% higher than that of wild plants.

No differences were observed between the studied genotypes in terms of the photosynthetic water use efficiency (WUE) in the first and third terms of the first year, and in the first term of the second year of the study. In the remaining terms, the highest WUE values were observed in plants collected from the natural habitat (by an average of 53.2%).

3.1.2. Chlorophyll “a” Fluorescence Parameters

In most of the measurement terms, no differences were observed in the initial (zero) fluorescence value (F₀) between the tested genotypes (

Table 4. Chlorophyll “a” fluorescence parameters in leaves of F. vesca genotypes.

Parameters	Genotypes	Measurement Terms
		1st Year			2nd Year
		July	August	September	July	August	September
F0	B	600.786 a*	616.857 a	587.429 a	259.143 a	261.857 a	266.857 a
	R	594.375 a	612.857 a	598.250 a	268.625 a	273.125 a	278.188 a
	N	600.429 a	594.000 a	582.929 a	258.571 a	229.857 b	250.643 a
FM	B	2804.571 a	2523.143 b	2917.929 ab	1246.571 b	1222.714 b	1270.500 a
	R	2795.000 a	2680.688 ab	2821.563 b	1346.688 a	1398.500 a	1323.500 a
	N	2998.429 a	2782.643 a	3067.071 a	1333.143 a	992.571 c	1258.643 a
FV	B	2203.786 a	1906.286 b	2330.500 ab	987.429 b	960.857 b	1003.643 a
	R	2200.625 a	2068.250 ab	2223.313 b	1078.063 a	1125.375 a	954.313 a
	N	2398.000 a	2188.643 a	2484.143 a	1074.571 a	762.714 c	1008.000 a
FV/FM	B	0.782 a	0.754 b	0.796 ab	0.792 a	0.785 b	0.780 ab
	R	0.784 a	0.771 ab	0.785 b	0.799 a	0.804 a	0.772 b
	N	0.793 a	0.779 a	0.809 a	0.805 a	0.743 ab	0.801 a
TFM	B	373.571 b	240.714 b	305.000 ab	578.571 b	277.857 a	535.000 a
	R	404.375 b	236.875 b	279.375 b	493.751 c	324.375 a	518.750 a
	N	507.143 a	273.571 a	339.286 a	671.429 a	317.144 a	560.000 a
AM	B	52,530.786 b	31,023.786 b	45,809.500 b	28,356.286 b	16,458.857 b	22,092.714 b
	R	54,069.125 b	35,609.250 ab	42,670.813 b	30,417.688 b	23,104.000 a	23,176.813 b
	N	68,608.929 a	39,444.500 a	57,824.214 a	40,694.786 a	17,188.714 b	32,145.643 a

Explanations: B—‘Baron von Solemacher’ cultivar; R—‘Rugia’ cultivar; N—plants obtained from a natural habitat. *—means marked with the same letters do not differ significantly at the significance level of α = 0.05.

). The exception occurred on the second measurement term of the second year, when the lowest F₀ value was observed in plants collected from the natural environment (by an average of 14.0%).

For maximum fluorescence (F_M), no differences were observed between the tested genotypes during the first term of the first year and the third term of the second year of the study. For the remaining measurements, the highest F_M values were most frequently observed in plants collected from the natural environment (e.g., in the second term of the first year, where the value was 9.3% higher than that of ‘Baron von Solemacher’ and the first term of the second year—6.5%); however, these results were not consistent.

Similar to F_M, no differences in variable fluorescence (F_V) were observed between the tested genotypes in the first term of the first year and the third term of the second year of the study. In the remaining terms, the ‘Baron von Solemacher’ cultivar was most frequently characterized by the lowest F_V value, in comparison with the ‘Rugia’ cultivar and plants collected from the natural environment, particularly in the first term of the second year of the study, where the value was 8.4% lower than that of ‘Rugia’ and 8.1% lower than that of wild plants.

No differences were found between the compared genotypes in terms of the ratio of variable to maximum fluorescence (F_V/F_M) during the first term of both the first and the second years of the study. Although the results in the other terms were not consistent, it can be concluded that the ‘Baron von Solemacher’ cultivar most frequently exhibited the lowest F_V/F_M values (e.g., in the second term of the first year the value was 3.2% lower than that of wild plants, and in the second term of the second year the value was 2.4% lower than that of ‘Rugia’), while plants collected from the natural environment were characterized by the highest values (e.g., in the third term of the second year the value was 3.6% higher than that of ‘Rugia’).

In all measurement terms, except for the second and third terms of the second year, where no significant differences were observed, the highest fluorescence growth time (T_FM) was recorded in plants collected from the natural environment (by an average of 17.5%). However, it should be noted that during the third term of the first year, the results did not indicate this unambiguously.

For the area above the fluorescence induction curve (A_M), the highest values were most frequently observed in plants collected from the natural habitat (by an average of 25.3%). The exceptions were the second term of the first year, where the results were ambiguous, and the second term of the second year, when the highest A_M value was recorded for the ‘Rugia’ cultivar (by an average of 27.2%).

3.1.3. Content of Photosynthetic Pigments

In most measurement terms during both years of the study, the highest chlorophyll “a” content in the leaves was observed in strawberries collected from the natural environment—by an average of 29.8% (

Table 5. Content of photosynthetic pigments in leaves of F. vesca genotypes [mg · g⁻¹ FM].

Parameters	Genotypes	Measurement Terms
		1st Year			2nd Year
		July	August	September	July	August	September
Chlorophyll “a”	B	1.711 ab*	0.851 b	1.427 b	1.327 b	1.952 a	1.857 b
	R	1.360 b	1.090 b	1.042 c	1.355 b	1.528 b	1.641 b
	N	1.995 a	1.420 a	1.777 a	2.116 a	1.780 ab	2.201 a
Chlorophyll “b”	B	0.622 a	0.565 a	0.531 b	0.564 a	0.627 a	0.627 ab
	R	0.523 a	0.562 a	0.523 b	0.654 a	0.486 b	0.591 b
	N	0.702 a	0.700 a	0.855 a	0.846 a	0.508 ab	0.721 a
Chlorophyll “a” to chlorophyll “b” ratio	B	2.747 a	1.528 b	2.684 a	2.385 a	3.113 b	2.963 a
	R	2.632 a	1.932 a	2.074 a	2.208 a	3.154 b	2.780 b
	N	2.839 a	2.028 a	2.107 a	2.523 a	3.504 a	3.056 a
Total chlorophyll	B	2.333 ab	1.415 b	1.958 b	2.333 ab	1.415 b	1.958 b
	R	1.882 b	1.652 b	1.565 c	1.882 b	1.652 b	1.565 c
	N	2.697 a	2.119 a	2.631 a	2.697 a	2.119 a	2.631 a
Carotenoids	B	0.959 ab	0.672 b	0.866 b	0.683 b	0.966 a	0.933 b
	R	0.728 b	0.748 b	0.639 c	0.696 b	0.902 ab	0.825 b
	N	1.179 a	1.009 a	1.170 a	1.050 a	0.772 b	1.120 a

Explanations: B—‘Baron von Solemacher’ cultivar; R—‘Rugia’ cultivar; N—plants obtained from a natural habitat. *—means marked with the same letters do not differ significantly at the significance level of α = 0.05.

). In contrast, the lowest values were typically recorded for the ‘Rugia’ cultivar (e.g., in the third term of the first year the value was 27.0% lower than that of ‘Baron von Solemacher’ and 41.4% lower than that of wild plants).

In all three measurement periods, no statistically significant differences were found between the studied genotypes regarding chlorophyll “b” content in the leaves. In the third term of the first year, the highest chlorophyll “b” content was observed in the leaves of wild strawberry plants collected from the natural environment (by an average of 31.5%). In the second term of the second year, the ‘Baron von Solemacher’ cultivar exhibited a higher chlorophyll “b” content compared to the ‘Rugia’ cultivar (by 22.5%). In the third term of the same year, the leaves of wild strawberry plants from the natural environment had a higher chlorophyll “b” content, by 18.0%, than those of the ‘Rugia’ cultivar.

In the first and third terms of the first year, as well as in the first term of the second year of the study, no differences were observed between the compared genotypes regarding the ratio of chlorophyll “a” to chlorophyll “b”. For the remaining measurement terms, the highest values of this parameter were found in plants collected from the natural environment (e.g., in the second term of the second year the value was 11.2% higher than that of ‘Baron von Solemacher’, and 10.0% higher than that of ‘Rugia’).

The content of total chlorophyll in the leaves of the tested F. vesca genotypes exhibited similar trends to those observed for the previously discussed assimilation pigments. In all measurement terms, except for the first term of the first year and second term of the second year, the highest total chlorophyll content was found in the leaves of plants collected from a natural environment (by an average of 30.3%). In the first term of the first year, the ‘Baron von Solemacher’ cultivar also showed a similarly high value of this parameter.

Additionally, the content of carotenoids in the leaves of the studied genotypes was highest in plants collected from the natural environment in most measurement terms (by an average of 30.3%). The exception was the first measurement term of the first year, where the ‘Baron von Solemacher’ cultivar exhibited an equally high carotenoid content, and the second measurement term of the second year, when this cultivar surpassed by 20.1% the wild strawberry collected from a natural environment in carotenoid content.

3.1.4. Relative Water Content in Leaves (RWC)

In the first term of the second year of the study, no significant differences in relative water content (RWC) were observed among the genotypes studied. Additionally, the results obtained in the other terms did not allow for a clear identification of plants with the highest or lowest RWC values (

Table 6. Relative water content (RWC) in leaves of F. vesca genotypes [%].

Genotypes	Measurement Terms
	1st Year			2nd Year
	July	August	September	July	August	September
B	54.445 b*	54.765 b	56.308 ab	45.247 a	42.064 a	46.258 b
R	62.644 a	55.159 b	61.177 a	39.875 a	40.545 ab	58.035 a
N	58.285 ab	65.073 a	54.813 b	37.150 a	30.509 b	52.958 ab

Explanations: B—‘Baron von Solemacher’ cultivar; R—‘Rugia’ cultivar; N—plants obtained from a natural habitat. *—means marked with the same letters do not differ significantly at the significance level of α = 0.05.

). Only in the second term of the first year was the highest RWC observed in the leaves of wild strawberry plants collected from the natural environment (15.8% greater than ‘Baron von Solemacher’, and 15.2% greater than ‘Rugia’).

3.1.5. Fruit Yield and Weight of a Single Wild Strawberry Fruit

Throughout the two-year experiment, flowering, which was absent in plants collected from their natural habitats, led to the production of fruit yield. In the second year, the ‘Baron von Solemacher’ cultivar produced 29.7% higher yield of fresh fruit mass than the ‘Rugia’ cultivar. However, in both years of the study, no significant differences were observed between the ‘Rugia’ and ‘Baron von Solemacher’ cultivars in terms of single fruit mass (

Table 7. Total fruit yield from one plant and weight of a single fruit during the vegetation period (June–September) in F. vesca genotypes [g].

Parameters	Genotypes	1st Year	2nd Year
Fresh Fruit Mass Yield	B	23.79 a*	33.11 a
	R	22.20 a	23.27 b
	N	-	-
Single Fruit Mass	B	0.65 a	0.55 a
	R	0.59 a	0.54 a
	N	-	-

Explanations: B—‘Baron von Solemacher’ cultivar; R—‘Rugia’ cultivar; N—plants obtained from a natural habitat. *—means marked with the same letters do not differ significantly at the significance level of α = 0.05.

).

3.1.6. Fresh and Dry Mass of the Root System

Upon completion of the two-year experiment, the fresh and dry mass of the root system was measured. No significant differences were observed among the tested F. vesca genotypes regarding both fresh and dry root mass (

Table 8. Fresh and dry mass of the root system of F. vesca genotypes [g].

Genotypes	Fresh Mass of the Root System	Dry Mass of the Root System
B	11.81 a*	6.83 a
R	13.30 a	6.83 a
N	17.80 a	10.47 a

Explanations: B—‘Baron von Solemacher’ cultivar; R—‘Rugia’ cultivar; N—plants obtained from a natural habitat. *—means marked with the same letters do not differ significantly at the significance level of α = 0.05.

).

3.1.7. Chemical Composition

Analysis of the average elemental content in the tested F. vesca genotypes revealed no significant differences in the concentrations of K, Ca, Mg, Na, Zn, Mn, and Fe (

Table 9. Chemical composition of leaves, crowns and roots of F. vesca genotypes.

Plant Organ	Genotypes	K [g‧kg−1]	Ca [g‧kg−1]	Mg [g‧kg−1]	Na [g‧kg−1]	Cu [mg‧kg−1]	Zn [mg‧kg−1]	Mn [mg‧kg−1]	Mo [mg‧kg−1]	Fe [mg‧kg−1]
Leaves	B	97.6 a*	66.9 a	13.5 b	4.8 a	37.3 a	172.5 ab	201.8 a	11.7 a	1.9 a
	R	106.9 a	69.7 a	15.7 a	2.8 a	52.2 a	236.4 a	205.4 a	6.6 b	1.8 a
	N	96.5 a	51.9 b	17.2 a	2.7 a	45.6 a	146.8 b	139.2 b	12.8 a	0.7 b
Crowns	B	82.9 a	115.6 b	3.9 b	28.0 ab	87.9 ab	155.2 b	31.4 b	17.6 a	0.2 a
	R	92.2 a	91.4 b	3.4 b	37.4 a	117.1 a	141.3 b	30.8 b	16.4 a	0.2 a
	N	50.4 b	159.7 a	5.4 a	10.0 b	74.4 b	212.9 a	61.8 a	17.3 a	0.2 a
Roots	B	25.9 a	80.7 a	13.4 a	6.1 a	92.5 b	853.5 ab	373.3 b	12.4 a	6.3 b
	R	24.5 a	63.4 a	13.4 a	5.9 a	111.4 a	677.8 b	388.0 b	9.4 a	6.4 b
	N	12.9 b	60.2 a	9.8 b	5.9 a	71.8 c	883.8 a	940.8 a	14.6 a	13.7 a
Average	B	69.9 a	89.9 a	9.8 a	32.6 a	73.7 ab	375.4 a	189.0 a	14.2 a	2.6 a
	R	74.5 a	74.8 a	10.8 a	15.4 a	93.6 a	351.8 a	208.1 a	10.8 b	2.8 a
	N	53.3 a	90.6 a	10.8 a	6.2 a	63.9 b	414.5 a	380.6 a	14.9 a	4.9 a

Explanations: B—‘Baron von Solemacher’ cultivar; R—‘Rugia’ cultivar; N—plants obtained from a natural habitat. *—means marked with the same letters do not differ significantly at the significance level of α = 0.05.

). However, the ‘Rugia’ cultivar exhibited 25.7% lower Mo content compared to the other genotypes and 31.7% higher Cu content than plants collected from the natural environment.

An analysis of element content within specific plant organs revealed that wild strawberries collected from the natural environment exhibited lower concentrations of Ca (by an average of 24.0%), Mn (by 31.6%), and Fe (by 62.1%) in the leaves compared to the ‘Rugia’ and ‘Baron von Solemacher’ cultivars, as well as 37.9% lower Zn concentration than the ‘Rugia’ cultivar. The Baron von Solemacher variety showed the lowest Mg content in the leaves (by an average of 17.8%), while ‘Rugia’ had the lowest Mo content (by an average of 46.0%). No significant differences were observed among the genotypes in terms of K, Na, and Cu content in the leaves.

The genotypes studied showed no significant differences in Mo and Fe content within the crowns. However, plants collected from the natural environment exhibited higher concentrations of Ca (by an average of 35.2%), Mg (by 32.4%), Zn (by 30.4%), and Mn (by 49.7%) in the crowns compared to both cultivars, as well as lower levels of Na (by 274%) and Cu (by 57.4%) relative to the ‘Rugia’ cultivar. Additionally, these wild-sourced plants contained lower levels of K in the crowns than the other genotypes (by an average of 48.8%).

In the roots, the genotypes did not differ in Ca, Na, and Mo content. Nonetheless, plants from the natural environment displayed lower levels of K (by an average of 48.8%) and Mg (by 26.9%) but higher levels of Mn (by 147.2%) and Fe (by 115.8%) in the roots compared to the cultivars. These wild plants also had 30.4% higher Zn content in the roots than the ‘Rugia’ cultivar, while exhibiting the lowest Cu content (by an average of 29.0%), in contrast to the ‘Rugia’ cultivar, which showed the highest Cu concentration in the roots.

3.2. Evaluation of Differences in Physiological Traits, Chemical Composition, and Yield Among Genotypes in Various Soil Moisture Conditions

3.2.1. Gas Exchange Parameters

The two-factor analysis of variance (ANOVA) revealed a significant main effect of the substrate moisture level (SML) factor on various physiological parameters. Specifically, transpiration intensity (E) showed significant effects during the first four measurement terms, stomatal conductivity to H₂O (g_s) during the first five measurement terms, net CO₂ assimilation intensity (P_n) across all measurement terms, substomatal CO₂ concentration (c_i) during the first four and the final measurement dates, and the photosynthetic water use efficiency (WUE) during the first three and the fifth measurement dates (Table S1). In general, these parameters exhibited a decline under water deficit conditions, with the exception of g_s and c_i on the second measurement date, as well as WUE on the first measurement date, where an increase in values was observed (respectively, by 88.5%, 4.1% and 66.4%). The average decrease was 36.7% for E, 30.0% for g_s, 23.7% for P_n, 18.2% for c_i, and 57.6% for WUE (

Table 10. Gas exchange parameters in leaves of F. vesca genotypes in various soil moisture conditions.

Parameters	Genotypes	SML	Measurement Terms
			1st Year			2nd year
			July	August	September	July	August	September
E [mmol H2O∙m−2∙s−1]	B	Ctrl	1.105 ab	1.041 a	0.967 a	0.707 a	0.841 bc	0.573 c
		Def	0.417 d	0.645 a	0.727 b	0.465 c	1.097 a	0.499 cd
	R	Ctrl	1.017 b	1.021 a	1.036 a	0.571 b	0.992 ab	0.252 e
		Def	0.405 d	0.502 a	0.579 b	0.565 b	0.578 d	0.431 d
	N	Ctrl	1.120 a	1.059 a	0.726 b	0.687 a	0.735 cd	0.907 a
		Def	0.789 c	0.653 a	0.619 b	0.530 bc	0.733 cd	0.801 b
	Average	Ctrl	1.081 A	1.040 A	0.910 A	0.655 A	0.856 A	0.577 A
		Def	0.537 B	0.600 B	0.642 B	0.520 B	0.803 A	0.574 A
gs [mol H2O∙m−2∙s−1]	B	Ctrl	0.094 a	0.137 a	0.061 a	0.064 a	0.043 bc	0.063 a
		Def	0.039 c	0.254 a	0.045 a	0.036 c	0.050 ab	0.082 a
	R	Ctrl	0.087 a	0.107 a	0.064 a	0.048 b	0.053 a	0.055 a
		Def	0.043 c	0.182 a	0.038 a	0.046 b	0.026 e	0.049 a
	N	Ctrl	0.086 a	0.150 a	0.050 a	0.060 a	0.038 cd	0.113 a
		Def	0.066 b	0.305 a	0.042 a	0.045 b	0.032 de	0.120 a
	Average	Ctrl	0.089 A	0.131 B	0.058 A	0.058 A	0.045 A	0.083 A
		Def	0.049 B	0.247 A	0.042 B	0.042 B	0.036 B	0.077 A
Pn [mmol H2O∙m−2∙s−1]	B	Ctrl	6.747 a	2.200 a	4.727 a	3.760 a	1.520 d	2.513 c
		Def	4.313 a	1.667 a	3.873 a	2.787 b	3.133 bc	4.513 b
	R	Ctrl	6.847 a	1.780 a	3.740 a	3.487 a	3.873 ab	4.107 bc
		Def	5.380 a	1.773 a	2.607 a	2.060 c	2.300 cd	3.667 bc
	N	Ctrl	7.307 a	3.253 a	3.427 a	3.533 a	4.260 a	7.780 a
		Def	5.800 a	2.553 a	2.673 a	3.840 a	1.787 d	4.893 b
	Average	Ctrl	6.697 A	2.411 A	3.964 A	3.593 A	3.218 A	5.320 A
		Def	5.164 B	1.998 A	3.051 B	2.896 B	2.407 B	3.838 B
ci [μmol CO2∙mol−1]	B	Ctrl	311.000 a	421.333 a	315.000 a	298.200 ab	355.733 a	498.467 a
		Def	220.667 c	441.600 a	257.133 a	290.800 c	316.133 ab	361.333 a
	R	Ctrl	299.933 ab	426.200 a	302.533 a	280.867 bc	289.400 bc	371.467 a
		Def	225.933 c	434.200 a	282.533 a	320.133 a	300.533 b	323.800 a
	N	Ctrl	279.800 b	411.733 a	304.533 a	298.867 ab	244.333 c	449.800 a
		Def	250.000 c	434.733 a	286.467 a	255.400 c	319.000 ab	339.800 a
	Average	Ctrl	296.911 A	419.756 B	307.356 A	292.644 A	296.489 A	439.911 A
		Def	232.200 B	436.844 A	275.378 B	278.778 A	311.889 A	341.644 B
WUE	B	Ctrl	6.201 c	3.484 a	5.167 a	5.409 bc	1.922 c	4.656 c
		Def	11.071 b	1.668 a	0.196 a	6.593 b	2.938 bc	9.285 bc
	R	Ctrl	6.747 c	3.812 a	3.799 a	6.253 ab	4.028 b	20.713 a
		Def	13.763 a	1.806 a	0.231 a	3.979 c	3.760 b	9.805 b
	N	Ctrl	6.519 c	5.168 a	5.173 a	5.328 bc	6.533 a	5.432 bc
		Def	7.561 c	2.569 a	0.243 a	7.685 a	2.554 bc	9.967 b
	Average	Ctrl	6.489 B	4.155 A	4.713 A	5.663 A	4.161 A	10.267 A
		Def	10.798 A	2.014 B	0.223 B	6.089 A	3.084 B	9.686 A

Explanations: SML—substrate moisture level; Ctrl—control, Def—deficit; B—‘Baron von Solemacher’ cultivar; R—‘Rugia’ cultivar; N—plants obtained from a natural habitat. Uppercase letters indicate means that significantly differ in the presence of a significant main effect of the SML factor, while lowercase letters denote means that significantly differ in the presence of a significant interaction effect (SML × genotype).

).

A significant effect of the Genotype × SML interaction on transpiration intensity (E) was observed in all measurement terms except the second. For stomatal conductivity to H₂O (gs) and substomatal CO₂ concentration (c_i), significant effects were detected in the first, fourth, and fifth terms; for net CO₂ assimilation intensity (P_n), in the last three terms; and for photosynthetic water use efficiency (WUE), in the first and last three measurement terms (Table S1). Post hoc analysis revealed a more pronounced reduction in E under water deficit conditions in the cultivars ‘Rugia’ and ‘Baron von Solemacher’ (respectively, by an average of 48.7% and 40.4%, while in wild plants, it was 26.2%). For g_s, the cultivars exhibited a greater reduction in the first measurement term (58.5% in ‘Baron von Solemacher’, 50.6%—‘Rugia’, and 23.3%—wild plants). However, in the fourth term, ‘Rugia’ demonstrated a smaller change compared to plants from the natural environment (no statistically significant change compared to a 25.0% reduction), while in the fifth term, ‘Baron von Solemacher’ exhibited a smaller reduction compared to other plants (50.9% and no statistically significant change). In the case of P_n, the results were relatively inconsistent. For example, in ‘Baron von Solemacher’, an increase in P_n was observed in the last two measurement terms (by 106.1% and 79.6%). However, in the remaining terms, P_n values generally decreased, with the greatest reductions occurring in plants from the natural environment (by an average of 47.6%). Regarding c_i, plants from the natural environment exhibited the smallest decrease in value in the first measurement term (10.7% compared to an average of 26.9%). In the fourth term, c_i values increased in ‘Rugia’ by 14.0% similarly to the fifth term in plants from the natural environment (by 30.6%). In contrast, ‘Baron von Solemacher’ showed a 2.5% decrease in c_i values in the fourth term. Summarizing the changes in WUE values across the measurement terms, the most unfavorable changes were observed in ‘Rugia’, which predominantly responded to water deficit by decreasing this parameter (by an average of 44.5%) (Table 10).

3.2.2. Chlorophyll “a” Fluorescence Parameters

A significant main effect of the SML factor on F₀ was observed exclusively on the fourth measurement date. For F_M and Fᵥ, significant effects were noted in the second and last three measurement terms, while for T_FM, they were observed during the first two and last three terms. Similarly, A_M demonstrated significant effects on the last three dates. However, no significant differences were found for F_V/F_M in relation to the SML factor on any measurement date (Table S2). A general decrease in the values of F₀ (by 3.8%), F_V (by an average of 7.5%), and F_M (by an average of 12.1%) was observed across the analyzed dates, with the exception of the second measurement date, where F_V and F_M values were higher under water deficit conditions (respectively, by 6.6% and 5.1%). In contrast, T_FM and A_M values increased under water deficit conditions (respectively, by an average of 29.7% and 27.8%) (

Table 11. Chlorophyll “a” fluorescence parameters in leaves of F. vesca genotypes in various soil moisture conditions.

Parameters	Genotypes	SML	Measurement Terms
			1st Year			2nd Year
			July	August	September	July	August	September
F0	B	Ctrl	600.786 a	616.857 a	587.429 a	259.143 a	261.857 a	266.857 ab
		Def	598.333 a	620.000 a	585.933 a	252.200 a	266.733 a	274.867 ab
	R	Ctrl	594.375 a	610.143 a	598.250 a	268.625 a	273.125 a	278.188 a
		Def	608.929 a	612.438 a	594.000 a	258.214 a	267.500 a	271.857 ab
	N	Ctrl	600.429 a	594.000 a	582.929 a	258.571 a	229.857 a	250.643 b
		Def	603.867 a	593.200 a	593.600 a	247.200 a	223.067 a	211.933 c
	Average	Ctrl	598.341 A	607.977 A	589.932 A	262.409 A	255.773 A	265.818 A
		Def	603.591 A	907.727 A	591.114 A	252.409 B	252.091 A	252.455 A
FM	B	Ctrl	2804.571 a	2523.143 a	2917.929 a	1246.571 c	1222.714 b	1270.500 a
		Def	2936.867 a	2729.667 a	2959.667 a	1272.400 bc	1305.333 ab	1179.800 a
	R	Ctrl	2701.214 a	2680.688 a	2821.563 a	1346.688 a	1398.500 a	1232.500 a
		Def	2795.000 a	2733.000 a	2998.643 a	1201.357 c	1237.857 b	1162.857 a
	N	Ctrl	2998.429 a	2782.643 a	3067.071 a	1333.143 ab	992.571 c	1258.643 a
		Def	3005.067 a	2928.533 a	2922.600 a	1237.867 c	887.333 d	1097.000 a
	Average	Ctrl	2862.773 A	2663.000 B	2930.341 A	1310.523 A	1213.409 A	1525.909 A
		Def	2885.136 A	2798.523 A	2959.432 A	1238.023 B	1141.364 B	1146.182 B
FV	B	Ctrl	2203.786 a	1906.286 a	2330.500 a	987.429 cb	960.857 b	1003.643 a
		Def	2338.533 a	2109.667 a	2373.733 a	1020.200 ab	1038.600 ab	904.933 a
	R	Ctrl	2200.625 a	2068.250 a	2223.313 a	1078.063 a	1125.375 a	954.313 a
		Def	2092.286 a	2122.857 a	2404.643 a	943.143 c	970.357 b	891.000 a
	N	Ctrl	2398.000 a	2188.643 a	2484.143 a	1074.571 a	762.714 c	1008.000 a
		Def	2401.200 a	2335.333 a	2329.000 a	990.667 bc	664.267 d	885.067 a
	Average	Ctrl	2264.432 A	2055.023 B	2340.409 A	1048.114 A	957.636 A	987.091 A
		Def	2281.545 A	2190.795 A	2368.318 A	985.614 B	889.273 B	893.727 B
FV/FM	B	Ctrl	0.782 a	0.754 a	0.796 a	0.792 ab	0.785 a	0.780 a
		Def	0.796 a	0.769 a	0.800 a	0.801 a	0.795 a	0.765 a
	R	Ctrl	0.784 a	0.771 a	0.785 a	0.799 a	0.804 a	0.772 a
		Def	0.765 a	0.775 a	0.800 a	0.784 b	0.783 a	0.764 a
	N	Ctrl	0.793 a	0.779 a	0.809 a	0.805 a	0.743 a	0.801 a
		Def	0.797 a	0.796 a	0.796 a	0.800 a	0.737 a	0.805 a
	Average	Ctrl	0.786 A	0.768 A	0.796 A	0.799 A	0.779 A	0.783 A
		Def	0.787 A	0.780 A	0.798 A	0.795 A	0.772 A	0.778 A
TFM	B	Ctrl	373.571 a	240.714 a	305.000 a	578.571 d	277.857 a	535.000 a
		Def	506.667 a	266.667 a	341.333 a	726.667 b	500.000 a	611.333 a
	R	Ctrl	404.375 a	236.875 a	279.375 a	493.751 e	324.375 a	518.750 a
		Def	507.143 a	251.429 a	309.286 a	821.429 a	491.429 a	628.571 a
	N	Ctrl	507.143 a	273.571 a	339.286 a	671.429 c	317.144 a	560.000 a
		Def	620.000 a	276.000 a	356.667 a	806.667 a	462.000 a	713.333 a
	Average	Ctrl	427.273 B	249.773 B	306.591 A	577.273 B	307.273 B	537.045 B
		Def	545.455 A	265.000 A	336.364 A	784.091 A	484.318 A	651.591 A
AM	B	Ctrl	52,530.79 a	31,023.79 a	45,809.50 bc	28,356.29 a	16,458.86 c	22,092.71 a
		Def	62,576.73 a	36,214.73 a	52,129.73 ab	38,018.53 a	29,509.93 a	31,889.93 a
	R	Ctrl	54,069.13 a	35,609.25 a	42,670.81 c	30,417.69 a	23,104.00 b	23,176.81 a
		Def	52,151.14 a	34,992.36 a	50,287.57 abc	38,595.50 a	27,784.21 a	29,535.43 a
	N	Ctrl	68,608.93 a	39,444.50 a	57,824.21 a	40,694.79 a	17,188.72 c	32,145.64 a
		Def	73,210.20 a	43,184.27 a	50,782.27 abc	46,048.60 a	19,009.80 c	36,060.13 a
	Average	Ctrl	58,205.96 A	35,370.55 A	48,491.02 A	33,031.77 B	19,107.50 B	25,685.59 B
		Def	62,884.55 A	38,201.77 A	51,084.02 A	40,939.64 A	25,381.25 A	32,562.43 A

Explanations: SML—substrate moisture level; Ctrl—control, Def—deficit; B—‘Baron von Solemacher’ cultivar; R—‘Rugia’ cultivar; N—plants obtained from a natural habitat. Uppercase letters indicate means that significantly differ in the presence of a significant main effect of the SML factor, while lowercase letters denote means that significantly differ in the presence of a significant interaction effect (SML × genotype).

).

A significant effect of the genotype × SML interaction on F₀ was observed exclusively in the last measurement term. For F_M and F_V, significant effects were noted in the fourth and fifth measurement term, while for F_V/F_M and T_FM, they were observed in the fourth term. Significant effects for A_M were found in the third, fifth, and sixth measurement terms (Table S2). Regarding F₀, the most pronounced changes under water deficit conditions occurred in plants obtained from the natural environment (reduction of 15.4%). For F_M and F_V, the greatest decreases on the fourth and fifth measurement dates were observed in the ‘Rugia’ cultivar (respectively, by an average of 11.1% and 13.1%). A similar trend was evident for F_V/F_M, where a more substantial decrease was noted in ‘Rugia’ (by 1.9%). In the case of T_FM, the most adverse changes under water deficit conditions were recorded in ‘Rugia’ (an increase of 66.4%), but in the case of A_M it was ‘Baron von Solemacher’ (an increase of 79.3%) (Table 11).

3.2.3. Content of Photosynthetic Pigments

A significant main effect of the SML factor on chlorophyll “a” content was observed in the second, third, fourth, and fifth measurement terms. For chlorophyll “b,” significant effects were found in the first three and fifth terms. The chlorophyll “a” to “b” ratio showed significant effects in the second and fifth terms, while total chlorophyll content was significantly affected in the second, third, and fifth terms. Carotenoid content exhibited significant effects in the first five measurement terms (Table S3). The results, however, demonstrated notable variability. In the first, second, fourth, and fifth measurement terms, under water deficit conditions, an increase was observed in the contents of chlorophyll “a” (by an average of 23.5%), chlorophyll “b” (by an average of 28.2%), total chlorophyll (by an average of 27.5%), and carotenoids (by an average of 21.3%), accompanied by a decrease in the chlorophyll “a” to “b” ratio (by an average of 7.8%). Conversely, on the third measurement date, decreases were recorded for chlorophyll “a” (by 11.2%), chlorophyll “b” (by 19.3%), total chlorophyll (by 13.7%), and carotenoid content (by 9.0%) (

Table 12. Content of photosynthetic pigments in leaves of F. vesca genotypes in various soil moisture conditions [mg · g⁻¹ FM].

Parameters	Genotypes	SML	Measurement Terms
			1st Year			2nd Year
			July	August	September	July	August	September
Chlorophyll “a”	B	Ctrl	1.711 a	0.851 d	1.427 b	1.327 a	1.952 a	1.857 bc
		Def	1.727 a	1.409 b	1.386 b	1.852 a	2.372 a	1.717 bc
	R	Ctrl	1.360 a	1.090 c	1.042 c	1.355 a	1.528 a	1.641 bc
		Def	1.629 a	1.274 bc	1.460 b	1.553 a	2.143 a	2.009 ab
	N	Ctrl	1.995 a	1.420 b	1.777 a	2.116 a	1.780 a	2.201 a
		Def	2.194 a	1.629 a	0.923 d	2.250 a	2.034 a	1.685 bc
	Average	Ctrl	1.689 A	1.120 B	1.415 A	1.599 B	1.754 B	1.900 A
		Def	1.850 A	1.437 A	1.256 B	1.885 A	2.183 A	1.804 A
Chlorophyll “b”	B	Ctrl	0.622 a	0.565 c	0.531 b	0.564 a	0.627 a	0.627 abc
		Def	0.685 a	0.709 b	0.553 b	0.705 a	0.768 a	0.627 abc
	R	Ctrl	0.523 a	0.562 c	0.523 b	0.606 a	0.486 a	0.591 bc
		Def	0.741 a	0.652 bc	0.601 b	0.654 a	0.695 a	0.693 ab
	N	Ctrl	0.702 a	0.700 b	0.387 c	0.846 a	0.508 a	0.721 a
		Def	0.860 a	1.037 a	0.855 a	0.824 a	0.637 a	0.537 c
	Average	Ctrl	0.616 B	0.609 B	0.637 A	0.688 A	0.541 B	0.646 A
		Def	0.762 A	0.800 A	0.514 B	0.712 A	0.700 A	0.619 A
Chlorophyll “a” to chlorophyll “b” ratio	B	Ctrl	2.747 a	1.528 b	2.684 a	2.385 a	3.113 bc	2.963 ab
		Def	2.525 a	1.986 a	2.506 a	2.607 a	3.091 bc	2.730 c
	R	Ctrl	2.632 a	1.932 a	2.074 a	2.208 a	3.154 bc	2.780 c
		Def	2.190 a	1.950 a	2.429 a	2.565 a	3.083 c	2.898 bc
	N	Ctrl	2.839 a	2.028 a	2.107 a	2.523 a	3.504 a	3.056 ab
		Def	2.557 a	1.573 b	2.386 a	2.732 a	3.196 b	3.136 a
	Average	Ctrl	2.739 A	1.829 A	2.288 A	2.372 A	3.257 A	2.933 A
		Def	2.424 B	1.836 A	2.440 A	2.635 A	3.123 B	2.921 A
Total chlorophyll	B	Ctrl	2.333 a	1.415 a	1.958 b	1.890 a	2.579 a	2.483 abc
		Def	2.411 a	2.117 a	1.938 b	2.556 a	3.139 a	2.343 abc
	R	Ctrl	1.882 a	1.652 a	1.565 c	2.008 a	2.014 a	2.231 c
		Def	2.369 a	1.926 a	2.061 b	2.159 a	2.837 a	2.701 ab
	N	Ctrl	2.697 a	2.119 a	2.631 a	2.962 a	2.288 a	2.921 a
		Def	3.053 a	2.666 a	1.309 d	3.073 a	2.670 a	2.222 c
	Average	Ctrl	2.304 A	1.729 B	2.051 A	2.286 A	2.294 B	2.545 A
		Def	2.611 A	2.236 A	1.769 B	2.596 A	2.882 A	2.422 A
Carotenoids	B	Ctrl	0.959 a	0.672 a	0.866 b	0.683 a	0.966 a	0.933 bc
		Def	1.023 a	0.983 a	0.920 b	0.917 a	1.155 a	0.912 bc
	R	Ctrl	0.728 a	0.748 a	0.639 c	0.696 a	0.772 a	0.825 c
		Def	0.992 a	0.866 a	0.846 b	0.808 a	1.058 a	1.047 ab
	N	Ctrl	1.179 a	1.009 a	1.170 a	1.050 a	0.902 a	1.120 a
		Def	1.403 a	1.204 a	0.667 c	1.108 a	1.047 a	0.902 bc
	Average	Ctrl	0.955 B	0.810 B	0.891 A	0.810 B	0.880 B	0.959 A
		Def	1.139 A	1.018 A	0.811 B	0.944 A	1.087 A	0.954 A

Explanations: SML—substrate moisture level; Ctrl—control, Def—deficit; B—‘Baron von Solemacher’ cultivar; R—‘Rugia’ cultivar; N—plants obtained from a natural habitat. Uppercase letters indicate means that significantly differ in the presence of a significant main effect of the SML factor, while lowercase letters denote means that significantly differ in the presence of a significant interaction effect (SML × genotype).

).

A significant effect of the genotype × SML interaction on the content of chlorophyll “a” and chlorophyll “b” was observed in the second, third, and final measurement terms. For the chlorophyll “a” to “b” ratio, significant effects were noted in the second, fifth, and sixth terms, while for total chlorophyll and carotenoid content, significant effects were recorded in the third and sixth terms (Table S3). For chlorophyll “a,” all genotypes responded to water deficit on the second measurement date with an increase in its content, with the most pronounced change observed in the ‘Baron von Solemacher’ cultivar (by 65.6%). However, in the third and sixth terms, plants from the natural environment exhibited a decrease in chlorophyll “a” content (by an average of 35.8%). A similar pattern was observed for chlorophyll “b,” where an increase in content was noted in the earlier terms (by an average of 64.9%), but a 25.5% decrease occurred in wild plants in the final term. Consequently, the largest reductions in total chlorophyll content were recorded in wild plants (by an average of 37.1%). For the chlorophyll “a” to “b” ratio, a 30.0% increase was observed in cultivated plants in the second measurement term, while a 22.4% decrease occurred in wild plants. In the fifth term, the most substantial reduction in this ratio was recorded in wild plants (by 8.8%), whereas in the sixth term, the greatest decrease was observed in the ‘Baron von Solemacher’ cultivar (by 7.9%). Regarding carotenoids, a decrease in content was observed exclusively in wild plants during the third and sixth terms (by an average of 31.2%), whereas the ‘Rugia’ cultivar demonstrated the most significant increase in carotenoid content (by an average of 29.7%) (Table 12).

3.2.4. Relative Water Content in Leaves (RWC)

A significant main effect of the SML factor on relative water content (RWC) was observed in the first, second, and fifth measurement terms (Table S4). In all instances, RWC values decreased under water deficit conditions by an average of 14.4% (

Table 13. Relative water content (RWC) in leaves of F. vesca genotypes in various soil moisture conditions [%].

Genotypes	SML	Measurement Terms
		1st Year			2nd Year
		July	August	September	July	August	September
B	Ctrl	54.445 bc	54.765 a	56.308 a	45.245 a	42.064 a	46.258 a
	Def	57.062 bc	55.160 a	63.152 a	45.247 a	29.790 a	42.738 a
R	Ctrl	62.644 a	55.159 a	61.177 a	39.875 a	40.545 a	58.035 a
	Def	53.366 c	43.781 a	52.717 a	38.022 a	31.226 a	50.866 a
N	Ctrl	58.285 b	65.073 a	54.813 a	37.150 a	30.509 a	52.958 a
	Def	56.126 bc	60.660 a	56.865 a	35.471 a	18.812 a	47.108 a
Average	Ctrl	58.458 A	58.332 A	57.432 A	40.757 A	37.706 A	52.417 A
	Def	55.518 B	53.200 B	57.578 A	37.285 A	26.609 B	46.904 A

Explanations: SML—substrate moisture level; ctrl—Control, Def—deficit; B—‘Baron von Solemacher’ cultivar; R—‘Rugia’ cultivar; N—plants obtained from a natural habitat. Uppercase letters indicate means that significantly differ in the presence of a significant main effect of the SML factor, while lowercase letters denote means that significantly differ in the presence of a significant interaction effect (SML × genotype).

).

A significant effect of the genotype × SML interaction on RWC was observed only in the first measurement term (Table S4). During this time, the most substantial decrease in RWC was recorded in the ‘Rugia’ plants (by 14.8%) (Table 13).

3.2.5. Fruit Yield and Weight of a Single Wild Strawberry Fruit

In plants obtained from the natural environment, flowering was not observed, and consequently, they were excluded from the analysis of fruit mass as they did not produce any fruits. A significant main effect of the SML factor was identified across all study years for both Fresh Fruit Mass Yield and Single Fruit Mass (Table S5). In each case, plants subjected to water deficit conditions produced fruits with lower mass. This represented an average decrease of 62.9% in Fresh Fruit Mass Yield and an average decrease of 35.6% in Single Fruit Mass (

Table 14. Total fruit yield from one plant and weight of a single fruit during the vegetation period (June–September) in F. vesca genotypes in various soil moisture conditions [g].

Parameters	Genotypes	SML	1st Year	2nd Year
Fresh Fruit Mass Yield	B	Ctrl	23.79 a	33.11 a
		Def	5.29 a	14.83 a
	R	Ctrl	22.20 a	23.27 a
		Def	5.64 a	14.62 a
	N	Ctrl	-	-
		Def	-	-
	Average	Ctrl	23.00 A	29.19 A
		Def	5.46 B	14.72 B
Single Fruit Mass	B	Ctrl	0.65 a	0.55 a
		Def	0.36 a	0.38 a
	R	Ctrl	0.59 a	0.54 a
		Def	0.39 a	0.38 a
	N	Ctrl	-	-
		Def	-	-
	Average	Ctrl	0.62 A	0.55 A
		Def	0.37 B	0.38 B

Explanations: SML—substrate moisture level; Ctrl—control, Def—deficit; B—‘Baron von Solemacher’ cultivar; R—‘Rugia’ cultivar; N—plants obtained from a natural habitat. Uppercase letters indicate means that significantly differ in the presence of a significant main effect of the SML factor, while lowercase letters denote means that significantly differ in the presence of a significant interaction effect (SML × genotype).

).

However, no significant effect of the SML × genotype interaction was observed in any year of the study for either Fresh Fruit Mass Yield or Single Fruit Mass (Table S5).

3.2.6. Fresh and Dry Mass of the Root System

Neither the main effect of SML nor the SML × genotype interaction was significant for the fresh and dry mass of the root system of F. vesca (Table S6 and

Table 15. Fresh and dry mass of the root system of F. vesca genotypes in various soil moisture conditions [g].

Genotypes	SML	Fresh Mass of the Root System	Dry Mass of the Root System
B	Ctrl	11.81 a	6.83 a
	Def	6.74 a	4.40 a
R	Ctrl	12.30 a	6.53 a
	Def	8.26 a	4.40 a
N	Ctrl	17.80 a	10.47 a
	Def	23.80 a	15.31 a
Average	Ctrl	13.64 a	7.66 a
	Def	16.61 a	10.46 a

Explanations: SML—substrate moisture level; Ctrl—control, Def—deficit; B—‘Baron von Solemacher’ cultivar; R—‘Rugia’ cultivar; N—plants obtained from a natural habitat. Uppercase letters indicate means that significantly differ in the presence of a significant main effect of the SML factor, while lowercase letters denote means that significantly differ in the presence of a significant interaction effect (SML × genotype).

).

3.2.7. Chemical Composition

For the content of individual elements in leaves, a significant main effect of the SML factor was observed for potassium (K), magnesium (Mg), zinc (Zn), and manganese (Mn) (Table S7). In each case, the content of these elements increased under drought conditions (respectively, by 8.5%, 10.9%, 32.8% and 20.6%) (Table 15). A significant effect of the SML × genotype interaction was detected for calcium (Ca), manganese (Mn), and iron (Fe) (Table S7). The most pronounced changes were observed in plants obtained from the natural environment, which exhibited higher contents of Zn (by 96.3%), Mn (by 62.2%), and Fe (by 157.1%) (

Table 16. Chemical composition of leaves, crowns and roots of F. vesca genotypes in various soil moisture conditions.

Plant Organ	Genotypes	SML	K [g‧kg−1]	Ca [g‧kg−1]	Mg [g‧kg−1]	Na [g‧kg−1]	Cu [mg‧kg−1]	Zn [mg‧kg−1]	Mn [mg‧kg−1]	Mo [mg‧kg−1]	Fe [mg‧kg−1]
Leaves	B	Ctrl	97.6 a	66.9 ab	13.5 a	64.8 a	37.3 a	172.5 bc	201.8 ab	11.7 a	1.9 b
		Def	100.4 a	70.2 a	16.6 a	4.9 a	53.4 a	225.0 ab	241.8 a	12.8 a	2.6 a
	R	Ctrl	106.9 a	69.7 a	15.7 a	2.8 a	52.2 a	236.4 ab	205.4 ab	6.6 a	1.8 b
		Def	118.0 a	68.4 a	17.0 a	5.5 a	56.0 a	228.0 ab	186.4 b	6.7 a	1.2 bc
	N	Ctrl	96.5 a	51.9 bc	17.2 a	2.7 a	45.6 a	146.8 c	139.2 c	12.8 a	0.7 c
		Def	108.7 a	42.2 c	18.2 a	4.6 a	46.0 a	288.2 a	225.8 ab	12.4 a	1.8 b
	Average	Ctrl	100.5 B	62.5 A	15.6 B	20.5 A	45.6 A	186.1 B	180.7 B	10.3 A	1.4 A
		Def	109.0 A	60.6 A	17.3 A	5.0 A	51.8 A	247.1 A	218.0 A	10.6 A	1.8 A
Crowns	B	Ctrl	82.9 a	115.6 bc	3.9 a	28.0 a	87.9 a	155.2 a	31.4 a	17.6 a	0.2 a
		Def	92.2 a	129.7 b	4.2 a	49.8 a	84.1 a	160.8 a	49.8 a	14.6 a	0.5 a
	R	Ctrl	92.2 a	91.4 c	3.4 a	37.4 a	117.1 a	141.3 a	30.8 a	16.4 a	0.2 a
		Def	104.3 a	120.3 bc	3.9 a	56.6 a	85.6 a	164.1 a	34.5 a	13.9 a	0.3 a
	N	Ctrl	50.4 a	159.7 a	5.4 a	10.0 a	74.4 a	212.9 a	61.8 a	17.3 a	0.2 a
		Def	54.9 a	130.2 b	5.1 a	20.8 a	64.0 a	245.6 a	77.2 a	18.6 a	0.3 a
	Average	Ctrl	75.2 A	122.2 A	4.3 A	25.1 B	93.1 A	169.8 A	41.3 A	17.1 A	0.2 B
		Def	83.8 A	126.7 A	4.4 A	42.4 A	77.9 A	190.2 A	53.8 A	15.7 A	0.3 A
Roots	B	Ctrl	25.9 a	80.7 a	13.4 a	6.1 a	92.5 bc	853.5 bc	373.3 a	12.4 a	6.3 a
		Def	26.9 a	88.3 a	12.1 a	8.6 a	121.2 a	844.4 b	422.2 a	19.0 a	7.5 a
	R	Ctrl	24.5 a	63.4 a	13.4 a	5.9 a	111.4 a	677.8 c	388.0 a	9.4 a	6.4 a
		Def	29.0 a	103.3 a	13.1 a	8.9 a	107.6 ab	913.2 b	309.0 a	14.0 a	7.3 a
	N	Ctrl	12.9 a	60.2 a	9.8 b	5.9 a	71.8 d	883.8 b	940.8 a	14.6 a	13.7 a
		Def	20.9 a	77.6 a	12.9 a	9.6 a	93.0 c	1232.3 a	926.8 a	12.4 a	12.6 a
	Average	Ctrl	20.7 A	67.2 B	12.1 A	6.0 B	91.9 B	801.6 B	581.2 A	12.1 A	9.0 A
		Def	25.9 A	90.6 A	12.7 A	9.0 A	108.3 A	979.8 A	525.9 A	15.3 A	8.9 A

Explanations: SML—substrate moisture level; Ctrl—control, Def—deficit; B—‘Baron von Solemacher’ cultivar; R—‘Rugia’ cultivar; N—plants obtained from a natural habitat. Uppercase letters indicate means that significantly differ in the presence of a significant main effect of the SML factor, while lowercase letters denote means that significantly differ in the presence of a significant interaction effect (SML × genotype).

).

For the element content in the crowns, a significant main effect of the SML factor was observed for sodium (Na) and iron (Fe) (Table S7), with the content of both elements increasing under drought conditions (respectively, by 68.9% and 50.0%) (Table 16). A significant effect of the SML × genotype interaction was identified only for calcium (Ca) (Table S7). A significant decrease in Ca content was observed exclusively in plants collected from the natural environment (by 18.5%). In contrast, cultivated varieties showed an increase in Ca content (by an average of 21.9%); however, this increase was not statistically significant.

For the element content in roots, a significant main effect of the SML factor was observed for Ca, Na, Zn, and copper (Cu) (Table S7), with the content of each element increasing under drought conditions (respectively, by 34.8%, 50.0%, 22.2% and 17.8%) (Table 15). A significant effect of the SML × genotype interaction was identified for Mg, Cu, and Zn (Table S7). A significant increase in Mg content in roots under water deficit conditions was observed exclusively in plants obtained from the natural environment (by 31.6%). These plants, along with the ‘Rugia’ cultivar, also showed the most pronounced increase in Zn content (by 34.7% in ‘Rugia’ and by 39.4% in wild plants). In contrast, an increase in Cu content was observed in the ‘Baron von Solemacher’ cultivar (by 31.0%) and in plants obtained from the natural environment (by 29.5%) (Table 16).

3.2.8. Radar Charts

Figure 1 illustrates an analysis of changes in the mean values of parameters used to assess the physiological characteristics of F. vesca plants, grouped by specific measurement dates and genotypes. Based on the graph’s surface area, the ‘Baron von Solemacher’ cultivar showed the lowest adaptation to water deficit conditions in the substrate and the strongest adverse reaction to drought stress (as indicated by the smallest area under the curve) during the first and second terms of the first study year. The ‘Rugia’ cultivar exhibited the smallest adaptation in the third measurement terms of both study years, while plants collected from the natural environment showed the least adaptation in the first and second terms of the second year.

Conversely, the Baron von Solemacher variety demonstrated the highest level of adaptation to drought conditions (reflected by the largest area under the curve) on the third date of the first study year and on the second and third dates of the second study year. Plants obtained from the natural environment exhibited the greatest adaptation on the first measurement date of both years, while the Rugia variety showed the greatest adaptation on the second date of the first study year.

4. Discussion

Physiological traits of cultivated plant varieties, including those within the Fragaria genus, exhibit substantial variability due to both genetic and environmental factors. Research indicates that differences in gas exchange parameters, chlorophyll fluorescence, and yield are pronounced across Fragaria species and varieties, highlighting the critical role of genetic diversity in these traits [40,41,42]. These findings align with the results of our study. While differences in physiological traits among Fragaria varieties are well documented, it is essential to consider that environmental factors can also profoundly influence these characteristics, sometimes overshadowing genetic effects. This complexity underscores the need for continued research into genotype–environment interactions that shape plant physiological responses.

Physiological characteristics of F. vesca plants growing in natural environments, including chlorophyll fluorescence and assimilation pigment content, surpassed those observed in cultivated varieties in our study, likely reflecting their adaptation to natural conditions. These plants thrive in diverse and often challenging habitats, which enhances their capacity for physiological adaptation [43,44]. The mechanisms of drought stress adaptation in plants, both cultivated and wild-growing, share fundamental similarities. However, the scope and effectiveness of these mechanisms can vary significantly due to the distinct environmental pressures experienced by wild plants [45]. Wild plants exhibited a less pronounced reduction in transpiration in response to the same drought stress compared to cultivated plant varieties, suggesting a lower sensitivity to this type of stress.

The observed differences in gas exchange parameters between wild and cultivated F. vesca plants under water stress conditions can be attributed to the inherent genetic diversity and adaptive traits present in wild varieties. Wild F. vesca evolved in natural environments where water stress is a common challenge, leading to the development of physiological and biochemical mechanisms that enhance drought tolerance. In contrast, cultivated varieties have been selectively bred for traits that may not prioritize drought resistance, resulting in a more pronounced reduction in gas exchange under similar stress conditions [46,47]. The greater genetic variability present in natural populations, due to uncontrolled interbreeding and mutations, compared to cultivated varieties, results in a broader range of adaptive responses to environmental stressors [48]. This genetic variability is crucial for the expression of drought-responsive genes, which facilitate improved gas exchange under water-limited conditions. For example, studies on wild relatives of other crops, such as peanut (Arachis hypogaea L.), have shown that they possess alleles that confer resistance to abiotic stresses, including drought, which can be leveraged to improve cultivated varieties [49].

Cultivated varieties of F. vesca are often subjected to agricultural practices that prioritize yield over stress tolerance. Such selective breeding may reduce the expression of genes associated with drought tolerance, rendering these plants more susceptible to water stress. Consequently, cultivated varieties may show more pronounced declines in gas exchange parameters under water stress, as they lack the robust adaptive traits present in their wild counterparts [50].

Similar treatments may trigger opposite changes in other adaptive mechanisms. The observed greater reduction in leaf photosynthetic pigment content in F. vesca plants from natural environments under soil moisture deficit, as compared to cultivated varieties, may result from selective breeding practices favoring higher yields. Cultivated varieties may possess enhanced mechanisms for maintaining pigment levels under stress, such as improved water use efficiency and osmotic regulation [51,52,53]. Although plants may initially increase photosynthetic pigment production under mild stress, severe water deficits can inhibit this response, ultimately leading to a net reduction in pigment content [51,52]. Wild F. vesca plants, frequently exposed to fluctuating moisture levels and other abiotic stresses, may exhibit a more pronounced physiological response to additional stressors, such as drought [54]. In contrast, cultivated varieties, typically grown in more controlled environments, can better withstand water stress without a significant reduction in pigment content [54].

The analysis of mineral composition indicated that wild plants exhibited more substantial variation in the content of specific elements depending on soil moisture conditions, suggesting greater adaptive flexibility. Under control conditions, these plants had a higher calcium content, while under moisture deficit, levels of elements such as potassium and manganese increased. The increase in potassium content is associated with plant survival mechanisms during drought stress [55]. Elevated potassium levels may also function as a tolerance mechanism, limiting the absorption of toxic ions by the roots [56,57]. Manganese, a critical component of photosynthetic proteins and enzymes, plays a central role in the water-splitting reaction that supplies electrons for subsequent stages of photosynthesis. Its deficiency can significantly impair the activity of photosystem II (PSII) [58]. Therefore, the observed increase in manganese content in tissues of plants exposed to drought conditions likely reflects the activation of physiological processes aimed at mitigating the adverse effects of water deficit on plant metabolism.

In contrast, cultivated varieties exhibited fewer or less pronounced differences in mineral content under varying moisture conditions, affecting only select elements. For instance, the ‘Baron von Solemacher’ cultivar showed increased sodium and copper content under drought stress, whereas the ‘Rugia’ displayed greater stability in its mineral composition regardless of soil moisture levels. Sodium contributes to osmotic adjustment in plant tissues under conditions of low external water potential. In C4 species, sodium also plays a role in both the light and dark phases of photosynthesis; for example, it aids in the transport of pyruvate to the chloroplast mesophyll and supports the structural integrity of chloroplast granules [59]. Copper, meanwhile, is crucial at the cellular level, influencing transcriptional and protein transport mechanisms, oxidative phosphorylation, and iron accumulation, all of which significantly shape the plant’s response to drought stress [60].

Other research indicates that wild plants develop more versatile adaptation mechanisms to changing and challenging environmental conditions, a trait supported by their greater genetic diversity. Studies on various plant genotypes, for instance, reveal that wild plants produce higher levels of antioxidant enzymes and osmoprotectants, which enhance their survival under stress [61]. Wild plants also demonstrated more marked differences in elemental content depending on substrate moisture levels. Their leaves, grown under control conditions, contained more calcium (Ca), whereas under drought conditions, they showed elevated concentrations of potassium (K), sodium, manganese, and iron. This suggests an ability to dynamically adjust the internal transport and allocation of minerals in response to drought [62], a response characteristic of wild plants that must adapt to naturally fluctuating environmental conditions where water availability varies. In comparison, cultivated varieties, which have been selectively bred primarily for high yield efficiency and uniformity, may not exhibit such a broad range of adaptive responses under stress [63].

Elemental content differences between the roots of wild plants and cultivated varieties were even more pronounced. The roots of wild plants displayed higher concentrations of potassium, magnesium, sodium, copper, and zinc, indicating an enhanced ability to effectively absorb and store minerals under deficit conditions. While increased sodium and copper accumulation was observed in the roots of the ‘Baron von Solemacher’ cultivar and increased sodium and zinc in the roots of the ‘Rugia’, this response to water deficiency was more extensive in wild plants, with a broader range of mineral accumulation and redistribution [64]. Natural populations exhibit greater genetic diversity, enabling a wider spectrum of responses to environmental stressors, such as low soil moisture. This genetic variability is critical for the efficient uptake and translocation of essential minerals, as demonstrated in studies emphasizing the role of genetic biofortification in wild crop relatives [65]. Furthermore, wild plants frequently display considerable phenotypic plasticity, allowing them to modify root and leaf characteristics in response to fluctuating moisture levels, as shown in research on Plantago lanceolata [66]. Species adapted to low-nutrient soils also develop specialized root morphologies and nutrient acquisition strategies that enhance mineral uptake under stress conditions [67].

Cultivars have likely been selectively bred with an emphasis on yield rather than resilience to environmental variability, which may limit their capacity to adapt to low soil moisture conditions. This focus on yield can lead to reduced genetic diversity and a narrower range of functional traits, potentially impairing their ability to accumulate essential minerals in challenging environments.

Under conditions of water deficiency (drought stress), numerous physiological and molecular processes are either activated or inhibited to adjust plant growth and development, thereby enhancing stress tolerance. The terms “water deficiency” or “water stress” refer to a state in which a plant’s water content is reduced to levels that impair its physiological functions, such as growth, stomatal conductance, and photosynthesis rate. Determining water deficit in absolute terms is challenging due to the complex interplay among atmospheric, plant, and soil factors. Furthermore, a plant’s response to stress can be influenced by conditions preceding the stress event itself. Jacques et al. [68] highlight the concept of “stress memory,” suggesting that plants possess mechanisms to retain information from drought-related stress, potentially leading to enhanced tolerance in subsequent growing seasons. This phenomenon was also observed in our study, where the plant response to drought stress was less pronounced in the second year of the experiment.

The physiological advantages of wild Fragaria vesca result from evolutionary adaptations, extensive genetic diversity, and complex metabolic profiles, which are often diminished in cultivated forms. While cultivated varieties may display characteristics advantageous for commercial production, such as uniformity and increased fruit yield, they frequently lack the resilience and metabolic diversity inherent to wild populations. This trade-off underscores the significance of wild species in breeding programs, as they offer genetic material that can enhance stress tolerance and nutritional quality in cultivated varieties.

Although wild F. vesca demonstrates superior drought tolerance, it is important to recognize that cultivated varieties may possess other valuable traits, such as higher yield and improved fruit quality. This highlights the value of integrating wild genetic resources into breeding efforts to increase the resilience of cultivated strawberries while preserving desirable agronomic characteristics. Evidence suggests that naturally occurring plants exhibit considerable heritable genetic variability for traits associated with stress resistance, implying that wild F. vesca may contain untapped genetic resources valuable for improving cultivated varieties [69]. Balancing drought tolerance with other agronomic traits remains a crucial focus for future research and development in Fragaria breeding.

Our study, however, has several notable limitations. First, as the experiments were conducted under controlled pot conditions, the results may not fully translate to field conditions, where numerous additional factors influence physiological responses. Despite this, our aim was to isolate and examine a single factor, minimizing the influence of others as much as possible. Second, the absence of molecular and proteomic analyses prevented us from definitively identifying the mechanisms underlying plant adaptation to stress. Such analyses would have provided more detailed insights and likely corroborated our findings. Third, the lack of evapotranspiration data means we cannot unequivocally quantify total water loss by the plants and their environment, which includes both transpiration (water loss through stomata) and soil surface evaporation. Nonetheless, tensiometric measurements are widely regarded as a reliable method with high accuracy, offering an efficient alternative to the more labor-intensive gravimetric method. Finally, some measurements may appear slightly inconsistent due to the extended duration of the study and the influence of uncontrolled factors, such as wind, pests, and humidity, which were not accounted for in our analyses.

5. Conclusions

• This study enabled a comparative analysis of the physiological responses of Fragaria vesca plants, including two cultivated varieties (‘Rugia’ and ‘Baron von Solemacher’) and a wild strawberry population obtained from a natural habitat. The key findings are as follows:
• F. vesca genotypes exhibit differences in physiological traits. Wild plants display distinct physiological patterns compared to cultivated varieties, including higher chlorophyll fluorescence values and greater assimilation pigment content.
• Water deficiency in the substrate significantly impacts the physiological characteristics of F. vesca plants. Drought conditions lead to reductions in gas exchange parameters, water use efficiency, chlorophyll “a” fluorescence parameters, relative water content in leaves, and the mass of fruits. Conversely, drought increases the content of elements such as K, Ca, Mg, Na, Cu, Zn, and Mn in various plant organs.
• F. vesca genotypes differ in their physiological responses to water deficit in the substrate. Plants from the natural environment demonstrate lower sensitivity, in terms of physiological responses, to water deficit compared to cultivated varieties.