Effect of Short-Term Water Deficit on Some Physiological Properties of Wheat (Triticum aestivum L.) with Different Spike Morphotypes

Abstract

Water deficit is one of the most important stress factors affecting yield and production quality. Breeders are focusing on breeding wheat cultivars and crop lines that are more resistant to water deficit, so there is a possibility that plants with changes in their ear morphologies, such as long chaff and multi-rowed varieties, will be more resistant to water deficit. Therefore, our research focused on the study of changes in the physiological parameters of wheat cultivar ‘Bohemia’ (normal cob) with an altered morphotype (genotypes ‘284-17’ (long chaff) and genotype ‘29-17’ (multirow cob)), in relation to the duration of the water deficit. The experiment was set up as a container experiment under partially controlled greenhouse conditions. The experimental design included four treatments. The control (C) variant was irrigated regularly. The other treatments were stressed by water deficit, which was induced through the method of gradually drying the substrate: treatment D1 involved 10 days without irrigation, 4 days of watering, 10 days with a re-induced water deficit and 4 days of watering; treatment D2 involved 10 days of watering, and then stress was induced via water deficit until the end of the experiment; treatment D3 involved 10 days of stress and then irrigation until the end of the experiment. The pigment content, gas exchange rate, chlorophyll fluorescence and water potential were monitored in the juvenile wheat plants. The obtained results showed that the contents of photosynthetically active pigments (chlorophyll a and b and carotenoids) were influenced by the gene type. The chlorophyll and carotenoid content were higher in genotype ‘29-17’ (0.080 and 1.925 nM cm⁻², respectively) and lowest in cultivar ‘Bohemia’ (0.080 and 0.080 nM cm⁻², respectively). The chlorophyll content decreased due to water deficit most significantly in the D2 variant (0.071 nM cm⁻²), compared to the control (0.138 nM cm⁻²). The carotenoid content significantly decreased due to water deficiency in the cultivar ‘Bohemia’, D2 (0.061 nM cm⁻²) and the genotype ‘284-17’ (0.075 nM cm⁻²) and non-significantly decreased in ‘29-17’ (1.785 nM cm⁻²). In the control plants, the carotenoid content decreased in the following order: genotype ‘29-17’ (1.853 nM cm⁻²) > genotype ‘284-17’ (0.088 nM cm⁻²) > cv. ‘Bohemia’ (0.087 nM cm⁻²). Wheat plants had a decreased photosynthetic rate due to the closure of stomata and reduction in substomatal CO₂ levels, which were caused by water deficit. The above effect was observed in genotype ‘29-17’ and cultivar ‘Bohemia’. The transpiration rate increased by 0.099 mM m⁻² s⁻¹ (5.69%) in the variety ‘Bohemia’, due to water deficit. On the other hand, the transpiration rate of genotype ‘29-17’ and genotype ‘284-17’ decreased by 0.261 mM m⁻² s⁻¹ (88.19%) and 0.325 mM m⁻² s⁻¹ (81.67%), respectively, compared to the control. Among the genotypes studied, genotype ‘29-17’ showed higher photosynthesis and transpiration rates, compared to genotype ‘284-17’ and the variety ‘Bohemia’. The effect of genotype and water deficit on chlorophyll fluorescence parameters was also shown. In all genotypes studied, there was a significant decrease in water potential due to water deficit, most significantly in the Bohemia variety, then in the genotype ‘284-17’, and the least significant decrease in water potential was seen in the genotype ‘29-17’. Genotype ‘29-17’ appears promising with respect to drought tolerance and photosynthetic rate, despite increased transpiration and reduced water potential; it also appears promising for better water management, with respect to reduced water potential in aboveground organs. On the other hand, the variety Bohemia appears to be less suitable for dry areas, since, despite its relative plasticity, it shows not only high water potential values in the water deficit region but also the most significant decrease in water potential.

1. Introduction

Water deficit, which is caused by low water availability [1], is one of the most important factors limiting agricultural production, as it seriously affects plant growth and the basic physiological and metabolic responses of plants [2,3,4], including crop yield [5,6]. As a result, it also affects food production and supply [6]. According to Sekhon et al. [7], water deficit is secondarily affected by higher air temperatures and CO₂ concentration, more intense solar radiation and low relative humidity and air flow.

According to Jaleel et al. [8], water deficit results in a reduced water uptake into the roots, thereby reducing the transpiration rate and cellular tension, leading to the denaturation and inactivation of proteins, metabolic disorders and damage to the photosynthetic apparatus [9]. A reduction in water uptake further decreases leaf water content and water potential, which inhibits cell enlargement and plant growth [10]. Yang et al. [11] reported that transpiration, membrane permeability and nutrient transport were reduced under water stress. Thus, a soil water deficit (drought) causes a lack of water in plant tissues, which leads to a significant reduction in the photosynthetic rate [12] due to a reduction in photosynthetic pigments, which leads to a reduction in the CO₂ assimilation rate [13,14]. According to Zlatev and Lidon [15], a lower pigment content may lead to reduced energy utilization, carbon metabolism and chlorophyll synthesis [16]. In the case of carotenoids, as auxiliary dyes, their content may decrease, according to [17,18]; they are also reduced due to plant defense responses, as evidenced by the work of Jaleel et al. [8], who studied the effect of water deficit on maize. In addition to photosynthetic dyes, the reduction in photosynthesis due to water deficit is affected by stomatal closure, due to reduced CO₂ and CO₂ concentrations in mesophyll cells [19], or non-stomatal inhibition (a decrease in chlorophyll content, the inhibition of Rubisco activase and the lower photochemical efficiency of PSII) [20]. These changes were abolished after rewatering [21]. The limitation of photosynthesis and transpiration through stomatal and non-stomatal mechanisms depends not only on the intensity and duration of drought but also on the susceptibility/tolerance of plant species, as well as their developmental stage and age [22]. The photosynthetic rate is limited under water deficit conditions by the inhibition of electron transport through PSII [23]. The energy of photosynthetically active radiation is absorbed by the photosynthetic pigments located in the antenna complexes of thylakoid membranes [24] and is subsequently transferred as excitation energy to the reaction centers of photosystem I (PSI) and photosystem II (PSII), where it serves to initiate photochemical reactions.

Chlorophyll fluorescence is a rapid, non-invasive and sensitive method for assessing the efficiency of the photosynthetic apparatus, photosynthetic electron transport, related photosynthetic processes and the physiological state of the plant [25]. In principle, the Fv/Fm (maximum quantum yield of PSII) and Fv/F0 (non-QA-electron transport) ratios are considered the main indicators for assessing the damage to PSII due to various environmental stresses [26]. A key site of inhibition of photosynthetic electron transport is the donor part of PSII, and in particular the QB- site on the D1 protein in the PSII reaction center, which prevents QA- from reducing QB [27]. These negative effects result in reduced crop survival and yield. Moharramnejad et al. [18] reported that the reduction in plant growth and yield due to water deficit is due to its effect on key physicochemical processes.

These negative effects result in reduced plant survival and yield. In response to water deficit stress, plants activate their water deficit response mechanisms, such as morphological and structural changes [28], the expression of water deficit tolerance genes, the synthesis of hormones and osmotic regulators to alleviate water deficit stress, alterations in primary [29] and secondary metabolism [30], and an imbalance in nutrient uptake by maize [31].

In response to water deficit stress, plants activate their water deficit response mechanisms, such as morphological and structural changes [28], including a reduction in stomatal density in barley or wheat leaves, which could be one of the signs of resistance to this stressor according to [27,32,33]. There is also a reduction in leaf area, which is associated with reduced assimilate availability [34,35]. In wheat, Sewore et al. [36] found that there was significant leaf rolling in response to water deficit. A similar phenomenon has been observed in maize. These metabolic changes are related to a decrease in the water potential within cells and tissues, which in turn leads to stomatal closure.

According to Liu et al. [9] and Onyemaobi et al. [37], a decrease in turgor leads not only to stomatal closure, a decrease in photosynthesis, e.g., in wheat [38] and tomato [33], and changes in enzyme activity, especially RUBISCO [32], but also to an increase in membrane permeability, protein denaturation and inactivation, metabolic disorders, damage to the photosynthetic apparatus [27] and nutrient deficiency.

In barley leaves, water deficit reduces leaf stomatal density, which could be one of the signs of resistance to this stressor according to [39,40]. A similar phenomenon has been observed in wheat [41]. Furthermore, water deficit leads to photoinhibition, where the actual efficiency of photosystem II (ΦPSII) is simultaneously reduced [24] due to the decrease in RUBISCO activity. Furthermore, the chlorophyll content decreases and the ratio of chlorophyll a and b and carotenoids changes [42], which subsequently leads to changes in photosynthetic function [43]. On the other hand, according to Yang et al. [11], a cascade of defence reactions is triggered, including the formation of specific proteins such as LEA, dehydrins, AQP, OSM proteins, etc.

Common wheat (Triticum aestivum L.) is the most widely grown cereal in the world and therefore the most affected by water deficit stress. One way to mitigate the effects of climate change is to identify and select suitable stress-tolerant genotypes. Breeding for water deficit tolerance therefore requires the integration of different knowledge systems and methodologies from different plant science disciplines [44].

One way of breeding is to modify the morphotype of plants, especially the ear. This is a group of genes that control the occurrence of so-called supernumerary spikelets, where, unlike in common wheat, more than one spikelet can grow from a single node of the spike spindle [45,46,47]. Multi-rowed ear in wheat is caused by the recessive gene WFZP-D (Wheat Frizzy Panicle) on the short arm of chromosome 2D [48,49]. Another trait is long tiller, which occurs in two tetraploid species, T. polonicum L. (gene P1 on chromosome 7A) and T. ispahanicum Hesolt. (gene P2 on chromosome 7B), and in the hexaploid T. petropavlovskyi Udac. & Migusch [50,51].

Various physiological, molecular and genetic approaches are required to determine plant stress tolerance. However, all these approaches are very costly, time consuming and sometimes do not help in the development of desirable drought tolerance traits [28]. In this case, monitoring primary plant metabolism, pigment content, water potential and chlorophyll fluorescence seem to be suitable screening tools for detecting plant resistance to stressors. In particular, chlorophyll fluorescence is a rapid, non-invasive and sensitive method for assessing the efficiency of the photosynthetic apparatus, photosynthetic electron transport, related photosynthetic processes and the physiological status of plants [29,52]. The Fv/Fm (maximum quantum yield of PSII) and Fv/F0 (non-QA electron transport) ratios are considered to be the main indicators of stress damage to PSII [26]. It is expected that wheat genotypes with morphotype modification should be more tolerant to water deficit, since, for example, wheat genotypes with awns show higher drought tolerance compared to varieties without awns. Therefore, our research focused on studying the changes in physiological parameters of wheat with altered morphotype compared to an already grown wheat variety (reference variety) in relation to exposure to water deficit.

It is hypothesised that wheat genotypes with morphotype modification should be more water deficit-tolerant. Therefore, our research focused on investigating changes in the physiological parameters of morphotype-altered wheat compared to an existing wheat cultivar (reference cultivar) in relation to water deficit exposure. The hypotheses proposed were whether there are genotypic differences between an already cultivated variety and potentially drought-resistant breeding materials to water deficit exposure, whether plant physiological responses are influenced by genotype, whether water deficit affects the physiological responses of juvenile wheat plants and whether these methods can be used as appropriate for screening against stressors. The aim of this study was to determine the genotypic differences with respect to the possibility of using the new breeding material in further plant breeding for water deficit based on selected physiological parameters.

2. Materials and Methods

2.1. Plant Material and Experimental Conditions

The effect of short-term water deficit was monitored in breeding material and near-isogenic lines of seeded wheat: (i) ‘Bohemia’ (normal spike); (ii) genotype ‘284-17’ (long chaff); (iii) genotype ‘29-17’ (multirowed ear). The cultivar Bohemia was bred at the breeding station in Úhřetice, Selgen Plc. Praha, Czech Republic. It is an early to semi-early variety for food use, which is characterised by high hardiness, resistance to ear blight, moderate resistance to fusariosis and less resistance to grass rust. The variety is suitable for cultivation in all production areas. The variety is most abundant in the breeding fields. Seed was obtained from Agrotest Phyto, Inc. Kroměříž, Czech Republic. Winter wheat plants were grown in 11 × 11 × 19 cm pots in a greenhouse experiment. The volume of the growing pot is 1650 cm³. The greenhouse is located on the premises of the CZU in Prague, at an altitude of 240 m above sea level. GPS location: 50°07′52.6″ N 14°22′14.8″ E. The air temperature during the experiment was maintained at 25 °C during the day and 19 °C at night, with a natural light regime of 14 h of light and 10 h of darkness; relative humidity was 66%. Grains of the experimental genotypes were sown in containers with a total of 15 seeds. The containers were fully irrigated throughout the emergence period. The higher number of seeds was given with regard to germination. The germination rate of the seedlings was 92% for the Bohemia variety, 89% for the newly bred ‘284-17’ and 88% for the genotype ‘29-17’. All genotypes are early to medium-early. Emergence of the genotypes studied was in 10 days. At the 15th BBCH stage, the number of plants was reduced to the final number of 6 plants.

Six plants were grown in one container, which represents a sowing rate of about 500 seeds 1 m². The experiment was based on the method of successive sowings so that the plants were at the same developmental stage at the time of measurement. A delay in ontogenetic development was observed in variant D2, which averaged 10 days compared to the other developmental stages. The wheat plants were irrigated to a level of 70% of the substrate moisture by volume (150 mL of water per container). The experimental plants were grown in garden substrate (AGRO CS, Plc. Říkov, Czech Republic: pH 5–6.5, nutrient content: N 80–120 mg L⁻¹, P 22–44 mg L⁻¹, K 83–124 mg L⁻¹; 80% white peat, 20% black peat, 20 kg soil m⁻³, 0–10 mm texture and contained no weeds or pests). Furthermore, it contained 55% of combustible matter in the dried sample and a maximum of 5% of particles above 25 mm.

The experimental design included four variants (

Table 1. Scheme of the experiment showing the intervals of irrigation.

Variant	Day of Experiment
	0–5th	6th–10th	10th–14th	14th–19th	19th–24th	24th–28th
Control (C)	irrigation	irrigation	irrigation	irrigation	irrigation	irrigation
Water deficit 1 (D1)	water deficit	water deficit	irrigation	water deficit	water deficit	irrigation
Water deficit 2 (D2)	irrigation	irrigation	water deficit	water deficit	water deficit	water deficit
Water deficit 3 (D3)	water deficit	water deficit	irrigation	irrigation	irrigation	irrigation

). The control (C) was irrigated regularly. The other three treatments were stressed via water deficit induced by the method of gradual drying of the substrate, namely, (D1) 10 days of no irrigation, 4 days of watering, 10 days of water deficit re-induced and 4 days of watering; (D2) 10 days of watering and then stress induced until the end of the experiment; (D3) 10 days of stress and then irrigation.

The experiment was established at the 16th BBCH stage of plant development and lasted 28 days, when the physiological parameters of the plants were measured: 0, 5, 10, 14,18, 22 and 28 days from the start of the experiment. The experiment was terminated at BBCH stage 20 (beginning of tillering) for variants D1, D3 and C. In the case of variant D2, due to plant development and long-term exposure to water deficit, it was terminated at BBCH stage 19. The onset of the different developmental phases within the genotypes and variants studied in the experiment are shown in

Table 2. Onset of individual developmental phases within the genotypes and experimental variants studied.

Variant	Day of Experiment
	0–5th	6th–10th	10th–14th	14th–19th	19th–24th	24th–28th
Control (C)	16. BBCH	16. BBCH	17. BBCH	18. BBCH	19. BBCH	20. BBCH
Water deficit 1 (D1)	16. BBCH	16. BBCH	17. BBCH	17. BBCH	18. BBCH	19. BBCH
Water deficit 2 (D2)	16. BBCH	16. BBCH	17. BBCH	17. BBCH	18. BBCH	19. BBCH
Water deficit 3 (D3)	16. BBCH	16. BBCH	17. BBCH	18. BBCH	19. BBCH	20. BBCH

.

2.2. Pigments Contents

Pigment content (chlorophyl a and b and total—Chl a; Chl b; Chl tot; Car x + c) was determined according to the methodology of Porra et al. [53]. Targets of 1 cm² were taken from wheat leaves. Targets were placed in plastic vials and 1 mL of dimethylformamide (DMF; Merck KGaA, Darmstadt, Germany) was added. Within 24 h, the pigments were extracted in cold darkness under nonstop shaking. Twenty-four hours after collection, the samples were spectrophotometrically analysed using a UV-Vis Evolution 2000 instrument (Thermo Fisher Scientific Inc., Waltham, MA, USA). As blank, pure dimethylformamide was used.

The absorbance (A) measurements were obtained at wavelengths of 480, 648.8, 663.8 and 710 nm.

The equations for calculating the pigments are as follows:

Chl a = 12.0 A_663.8 − 3.11 A_646.8

(1)

Chl b = 20.78 A_646.8 − 4.88 A_663.8

(2)

Chl_tot = (7.12 A_663.8) + (17.67 A_646.8)

(3)

Car = (1000 A₄₈₀ − 1.12 Chl a − 34.07 Chl b)/245

(4)

2.3. Gas Exchange Parameters

The gas exchange rate was measured via a non-destructive method using an integrated fluorometer and gas exchange system—iFL (ADC Bioscientific Ltd., Hoddesdon, UK). The net photosynthetic rate (Pn) and transpiration rate (E) were measured on a photosynthetically mature leaf, in the central part of the leaf blade. The gas exchange rate and stomatal conductance (gs) were derived from Pn. The gas exchange rate was measured in the morning (8–13 h UTC) at an irradiance density of 650 μM m⁻² s⁻¹ and temperature of 25 °C, according to the methodology of Kuklova et al. [54].

The equations for calculating the gas exchange are as follows:

Net photosynthesis rate (Pn; μM CO₂ m⁻² s⁻¹)

$$\mathrm{P}\mathrm{n}=\mathsf{\delta }\mathrm{c}·\mathrm{u}\mathrm{s}$$

(5)

us—mass flow of air per m² of leaf area (M m⁻² s⁻¹);

δc—difference in CO₂ concentration through chamber, dilution corrected (μM M ⁻¹)

Transpiration rate (E; mM H₂O m⁻² s⁻¹).

$$\mathrm{E}=\frac{\mathsf{\delta }\mathrm{e} \mathrm{u}\mathrm{s}}{\mathrm{p}}$$

(6)

δe—differential water vapour concentration (mBar), dilution corrected;

us—mass flow of air into leaf chamber per m² of leaf area (M s⁻¹ m⁻²);

p—atmospheric pressure (mBar).

Stomatal conductance of water vapour (gs; M m⁻² s⁻¹):

$$\mathrm{g}\mathrm{s}=\frac{1}{\mathrm{r}\mathrm{s}}$$

(7)

rs—stomatal resistance to water vapour (m² s⁻¹ M⁻¹):

$$\mathrm{r}\mathrm{s}=\frac{(\mathrm{w}\mathrm{l}\mathrm{e}\mathrm{a}\mathrm{f}-\mathrm{w}\mathrm{m}\mathrm{a}\mathrm{n})}{\frac{\mathsf{\delta }\mathrm{u}\mathrm{e}\mathrm{s}}{\mathrm{p}}}·\mathrm{r}\mathrm{b}$$

(8)

wleaf—saturated water vapour concentration at leaf temperature (M M⁻¹):

$$\mathrm{w}\mathrm{l}\mathrm{e}\mathrm{a}\mathrm{f}=\frac{\mathrm{e}\mathrm{s}}{\mathrm{p}}$$

(9)

es—saturated vapour pressure at leaf surface temp (mBar);

p—atmospheric pressure (mBar);

δe—differential water vapour concentration (mBar), dilution corrected;

wman—water vapour concentration out of leaf chamber (M M⁻¹);

rb—boundary layer resistance to water vapour (m² s M⁻¹);

us—mass flow of air per m² of leaf area (M m⁻² s⁻¹).

2.4. Parameters of Fluorescence

Chlorophyll fluorescence parameters were analysed in juvenile wheat plants. Fluorescence was measured on the same leaves as the photosynthetic rate. These were the maximum quantum yield of photosystem II (Fv/Fm), the ratio of maximum fluorescence to initial fluorescence (Fm/F0) and the ratio of variable fluorescence to initial fluorescence (Fv/F0). An integrated fluorometer and gas exchange system—iFL (ADC Bio-scientific Ltd., Hoddesdon, UK)—was used to measure fluorescence parameters. Chlorophyll fluorescence parameters were measured: F0; Fm—minimum and maximum dark-adjusted fluorescence yield; Fv—variable fluorescence (Fv = Fm/F0). These parameters were used to calculate the Fv/F0 (potential photochemical efficiency) and Fv/Fm (maximum quantum efficiency of PSII) ratios, which are considered indicators of the efficiency of PSII in primary photochemical reactions. Fluorescence parameters were measured on five selected fully expanded upper leaves. The leaves were dark-adapted for 30 min before the measurements. The measurement time was 5 s and the irradiance was 3000 μM m⁻² s⁻¹.

2.5. Water Potential

Water potential (ψ_w; MPa) as the energy status of the water in the system was determined using the dewpoint with a water potential meter, WP4C (Decagon Devices Inc., Pullman, WA, USA). Leaves were packed in plastic syringes and airtight sealed with parafilm. Then, samples were frozen at −18 °C. After the thawing of samples at room temperature, a drop of liquid was extracted from the syringe and used for measurements.

2.6. Statistical Analysis

Four independent biological replicates were used in the experiments. Each replicate was a sample of plant material from a different pot. The variability of differences in the parameters of interest for all treatments was tested using two-way ANOVA (p < 0.05) followed by Tukey’s post hoc test for significant differences between treatments. Data were analysed using Statistica 13.5 software (StatSoft, Tulsa, OK, USA). To test the dependence of physiological scores on experimental variation and genotype, a linear regression was constructed using artificial variables at a significance level of α = 0.05. The ‘Bohemia’ control was selected as the baseline group. R software (v 4.0.5, The R Foundation, Vienna, Austria) was used to calculate the model.

3. Results

3.1. Pigments Contents

Changes in the content of photosynthetically active pigments were studied in juvenile wheat plants as a function of genotype and water deficit. The results are shown in

Table 3. Effect of water deficit on the content of photosynthetically active pigments (nM cm⁻²), total chlorophylls (Chl_tot) and carotenoids (Car), depending on wheat genotypes. Statistically significant differences at the α = 0.05 significance level are indicated by different lowercase letters.

Variant	Days	‘Bohemia’		‘287-17’		‘29-17’
		Chltot	Car	Chltot	Car	Chltot	Car
C	0	0.010 ± 0 e	0.010 ± 0 e	0.010 ± 0 g	0.010 ± 0 e	0.010 ± 0 d	1.330 ± 0.005 g
	5	0.138 ± 0.004 b	0.142 ± 0.003 ab	0.220 ± 0.005 c	0.138 ± 0.004 a	0.142 ± 0.003 ab	1.558 ± 0.153 f
	10	0.140 ± 0.003 b	0.146 ± 0.006 ab	0.282 ± 0.005 ab	0.140 ± 0.003 a	0.146 ± 0.006 ab	1.934 ± 0.041 cd
	14	0.020 ± 0 e	0.028 ± 0.001 d	0.258 ± 0.015 ab	0.097 ± 0.008 b	0.152 ± 0.010 ab	1.912 ± 0.268 e
	18	0.251 ± 0.005 a	0.202 ± 0.035 a	0.131 ± 0.007 d	0.097 ± 0.005 b	0.126 ± 0.009 b	1.923 ± 0.072 de
	22	0.036 ± 0.002 d	0.031 ± 0.003 d	0.041 ± 0.002 f	0.050 ± 0.004 d	0.031 ± 0.002 cd	2.085 ± 0.079 b
	28	0.047 ± 0.003 c	0.047 ± 0.003 c	0.070 ± 0.004 e	0.087 ± 0.003 c	0.019 ± 0.002 d	2.230 ± 0.021 a
	average	0.091 ± 0.006	0.087 ± 0.009	0.145 ± 0.008	0.088 ± 0.005	0.089 ± 0.005	1.853 ± 0.053
D1	0	0.010 ± 0 e	0.010 ± 0 e	0.010 ± 0 f	0.010 ± 0 f	0.010 ± 0 e	1.330 ± 0.005 f
	5	0.138 ± 0.004 a	0.142 ± 0.003 b	0.231 ± 0.005 b	0.123 ± 0.006 b	0.142 ± 0.003 b	1.556 ± 0.153 e
	10	0.140 ± 0.003 a	0.146 ± 0.006 b	0.270 ± 0.006 a	0.147 ± 0.009 a	0.146 ± 0.006 b	1.934 ± 0.041 a
	14	0.097 ± 0.008 bc	0.152 ± 0.010 a	0.020 ± 0 e	0.026 ± 0.001 e	0.028 ± 0.001 d	1.792 ± 0.078 b
	18	0.097 ± 0.005 bc	0.126 ± 0.009 c	0.020 ± 0 e	0.023 ± 0.002 e	0.202 ± 0.035 a	1.646 ± 0.160 c
	22	0.050 ± 0.004 d	0.031 ± 0.002 d	0.040 ± 0.004 d	0.042 ± 0.003 d	0.031 ± 0.003 d	1.591 ± 0.114 d
	28	0.087 ± 0.003 c	0.019 ± 0.002 e	0.050 ± 0.003 c	0.075 ± 0.003 c	0.047 ± 0.003 c	1.597 ± 0.118 de
	average	0.088 ± 0.007	0.089 ± 0.005	0.092 ± 0.006	0.064 ± 0.013	0.084 ± 0.015	1.635 ± 0.087
D2	0	0.010 ± 0 d	0.010 ± 0 e	0.010 ± 0 d	0.010 ± 0 e	0.010 ± 0 e	1.330 ± 0.005 d
	5	0.138 ± 0.004 b	0.142 ± 0.003 b	0.220 ± 0.005 b	0.138 ± 0.004 b	0.164 ± 0.030 ab	1.791 ± 0.034 b
	10	0.140 ± 0.003 b	0.146 ± 0.006 b	0.282 ± 0.005 a	0.140 ± 0.003 b	0.158 ± 0.005 ab	1.797 ± 0.239 b
	14	0.020 ± 0 d	0.028 ± 0.001 de	0.024 ± 0.001 cd	0.020 ± 0 de	0.026 ± 0.001 cd	1.796 ± 0.446 b
	18	0.251 ± 0.005 a	0.202 ± 0.035 a	0.026 ± 0.001 cd	0.251 ± 0.005 a	0.018 ± 0.001 e	1.714 ± 0.101 c
	22	0.036 ± 0.002 c	0.031 ± 0.003 d	0.026 ± 0.003 cd	0.036 ± 0.002 d	0.031 ± 0.002 cd	2.021 ± 0.310 a
	28	0.047 ± 0.003 c	0.047 ± 0.003 c	0.033 ± 0.003 cd	0.047 ± 0.003 c	0.020 ± 0.002 d	2.046 ± 0.320 a
	average	0.064 ± 0.005	0.061 ± 0.009	0.089 ± 0.003	0.075 ± 0.004	0.061 ± 0.009	1.785 ± 0.211
D3	0	0.010 ± 0 f	0.010 ± 0 d	0.010 ± 0 e	0.010 ± 0 f	0.010 ± 0 f	1.330 ± 0.005 d
	5	0.123 ± 0.006 c	0.164 ± 0.030 a	0.231 ± 0.005 b	0.123 ± 0.006 c	0.164 ± 0.030 a	1.791 ± 0.034 c
	10	0.147 ± 0.009 b	0.158 ± 0.005 a	0.270 ± 0.006 a	0.147 ± 0.009 b	0.158 ± 0.005 a	1.797 ± 0.239 c
	14	0.015 ± 0.001 f	0.015 ± 0.001 d	0.015 ± 0.001 e	0.015 ± 0.001 f	0.015 ± 0.001 f	3.214 ± 0.044 a
	18	0.160 ± 0.009 a	0.119 ± 0.006 b	0.217 ± 0.009 c	0.160 ± 0.009 a	0.119 ± 0.006 c	3.213 ± 0.042 a
	22	0.025 ± 0.002 e	0.071 ± 0.004 d	0.028 ± 0.002 d	0.025 ± 0.002 e	0.071 ± 0.004 d	2.902 ± 0.017 b
	28	0.042 ± 0.002 d	0.050 ± 0.003 c	0.035 ± 0.003 d	0.042 ± 0.002 d	0.050 ± 0.003 e	2.745 ± 0.052 b
	average	0.075 ± 0.006	0.084 ± 0.008	0.115 ± 0.005	0.075 ± 0.006	0.084 ± 0.009	2.427 ± 0.064
	average tot	0.080 ± 0.007	0.080 ± 0.008	0.110 ± 0.005	0.076 ± 0.008	0.080 ± 0.011	1.925 ± 0.114

. It shows that the effect of genotype on the content of pigments in the leaves was demonstrated, with the lowest average content of total chlorophylls and carotenoids found in cv. ‘Bohemia’ (0.080 nM cm⁻² and 0.080 nM cm⁻², respectively). On the other hand, the highest average pigment content was found in genotype ‘29-17’. It had a total chlorophyll content of 0.080 nM cm⁻² and a carotenoid content of 1.925 nM cm⁻².

Furthermore, the effect of variant on chlorophyll content was confirmed as stressed variants had lower chlorophyll levels compared to the control. The greatest decrease in chlorophyll content due to water deficit was found in variant D2, where the average chlorophyll content ranged from 0.061 nM cm⁻² (genotype ‘29-17’) to 0.089 nM cm⁻² (genotype ‘284-17’); in the case of control plants, the average content of total chlorophylls was lowest in genotype ‘29-17’ (0.089 nM cm⁻²) and highest in genotype ‘284-17’ (0.145 nM cm⁻²). The smallest decrease in chlorophyll content was observed in variant D3, where the content of total chlorophylls was inconclusively lower in all plants studied compared to the control. In the case of carotenoids, their content decreased significantly in variant D2 compared to the control plants. In plants of this variety, their average content ranged from 0.061 nM cm⁻² (cv. ‘Bohemia’) to 1.785 nM cm⁻² (genotype ‘29-17’), as shown in Table 3. The highest carotenoid content was found in genotype ‘29-17’ (1.925 nM cm⁻²) and the lowest in genotype ‘284-17’ (0.076 nM cm⁻²).

The highest reduction in chlorophyll content (see Table 3) due to water deficit was found in genotype ‘284-17’, by 0.056 nM cm⁻² in variant D2. Similarly, the chlorophyll content of this variant was reduced in cv. ‘Bohemia’ and genotype ‘29-17’, by 0.027 nM cm⁻² in the case of ‘Bohemia’ and 0.028 nM cm⁻² in the case of genotype ‘29-17’. There were no significant differences between these genotypes. The lowest reduction in total chlorophyll content was found in the D3 cultivar, where the pigment content decreased according to the effect of genotype in the following order: genotype ‘284-17’ (0.030 nM cm⁻²; 20.69%) > cv. ‘Bohemia’ (0016 nM cm⁻²; 17.58%) > genotype ‘29-17’ (0.009 nM cm⁻²; 5.62%).

The carotenoid content was clearly influenced by variant and genotype; see Table 3. It shows that for all genotypes studied, the carotenoid content of the D2 variant was clearly reduced compared to the control. The most significant reduction was observed in cv. ‘Bohemia’—0.061 nM cm⁻² (29.88% reduction compared to the control). On the other hand, in genotype ‘29-17’, there was an inconclusive decrease in carotenoid content of 3.67% (1.785 nM cm⁻²) between variant D2 and the control. In the case of variant D1, an inconclusive increase in carotenoid content was observed in cv. ‘Bohemia’ (0.089 nM cm⁻²; 2.30%), but on the contrary, in genotype ‘29-17’, the carotenoid content decreased to a mean value of 0.064 nM cm⁻² (decrease of 0.024 nM cm⁻² compared to the control). A statistically significant increase in carotenoid content was found in genotype ‘29-17’ and variant D3 (increase of 0.072 nM cm⁻² (30.98%) compared to the control). On the other hand, a significant decrease in carotenoids was observed in this variant in genotype ‘284-17’—a decrease of 0.013 nM cm⁻² compared to the control.

No significant difference was found between control and D3 plants. On the other hand, in genotype ‘29-17’, the carotenoid content decreased due to drought, with the most significant decrease observed in variant D2, which showed a decrease of 0.317 nM cm⁻² (12.03%). On the other hand, the lowest decrease was found in variety D3 (0.297 nM cm⁻²; 2.66%). On the other hand, an inconclusive increase of 1.10% (0.029 nM cm⁻²) was observed for variant D1. A similar trend was observed for genotype ‘29-17’, with a statistically significant decrease in variant D2 (0.191 nM cm⁻²; 0.60%) and an inconclusive decrease in variant D3 (0.048 nM cm⁻²; 2.66%). A significant increase in carotenoid content was observed in variant D1, with an increase of 0.551 nM cm⁻² or 30.58%.

3.2. Gas Exchange Parameters

Stomatal conductance (gs) functions as a measure of the opening of the stomata in response to environmental conditions. In case of stress, the stomata gradually close and thus the stomatal conductance decreases. This trend is confirmed by the results obtained in the evaluation of the different experimental treatments, where lower values were achieved by plants from the stressed treatments compared to the control, as shown in

Table 4. Effect of variation on the stomatal conductance (gs; M m⁻² s⁻¹), depending on wheat genotypes. Statistically significant differences at the α = 0.05 significance level are indicated by different lowercase letters.

Variant	Days	‘Bohemia’	‘284-17’	‘29-17’
C	0	0.010 ± 0 e	0.010 ± 0 e	0.010 ± 0 g
	5	0.138 ± 0.004 a	0.142 ± 0.003 b	0.220 ± 0.005 c
	10	0.140 ± 0.003 a	0.146 ± 0.006 b	0.282 ± 0.005 a
	14	0.097 ± 0.008 b	0.152 ± 0.010 a	0.258 ± 0.015 b
	18	0.097 ± 0.005 b	0.126 ± 0.009 c	0.131 ± 0.007 d
	22	0.050 ± 0.004 d	0.031 ± 0.002 d	0.041 ± 0.002 f
	28	0.087 ± 0.003 c	0.019 ± 0.002 e	0.070 ± 0.004 e
	average	0.088 ± 0.005	0.089 ± 0.006	0.145 ± 0.007
D1	0	0.010 ± 0 g	0.010 ± 0 e	0.010 ± 0 e
	5	0.123 ± 0.006 c	0.164 ± 0.030 a	0.231 ± 0.005 b
	10	0.147 ± 0.009 b	0.158 ± 0.005 a	0.270 ± 0.006 a
	14	0.015 ± 0.001 fg	0.015 ± 0.001 e	0.015 ± 0.001 e
	18	0.160 ± 0.009 a	0.119 ± 0.006 b	0.217 ± 0.009 c
	22	0.025 ± 0.002 ef	0.071 ± 0.004 cd	0.028 ± 0.002 d
	28	0.042 ± 0.002 d	0.050 ± 0.003 d	0.035 ± 0.003 d
	average	0.075 ± 0.006	0.084 ± 0.009	0.115 ± 0.009
D2	0	0.010 ± 0 f	0.010 ± 0 e	0.010 ± 0 e
	5	0.123 ± 0.006 b	0.164 ± 0.030 a	0.220 ± 0.005 b
	10	0.147 ± 0.009 a	0.158 ± 0.005 a	0.282 ± 0.005 a
	14	0.026 ± 0.001 e	0.026 ± 0.001 cd	0.024 ± 0.001 d
	18	0.023 ± 0.002 ef	0.018 ± 0.001 d	0.026 ± 0.001 d
	22	0.042 ± 0.003 d	0.031 ± 0.002 bc	0.026 ± 0.003 d
	28	0.075 ± 0.003 c	0.020 ± 0.002 d	0.033 ± 0.003 cd
	average	0.064 ± 0.006	0.061 ± 0.008	0.089 ± 0.004
D3	0	0.010 ± 0 f	0.010 ± 0 e	0.010 ± 0 d
	5	0.138 ± 0.004 b	0.142 ± 0.003 b	0.231 ± 0.005 a
	10	0.140 ± 0.003 b	0.146 ± 0.006 b	0.270 ± 0.006 a
	14	0.020 ± 0 e	0.028 ± 0.001 d	0.020 ± 0 cd
	18	0.251 ± 0.005 a	0.202 ± 0.035 a	0.020 ± 0 cd
	22	0.036 ± 0.002 d	0.031 ± 0.003 d	0.040 ± 0.004 b
	28	0.047 ± 0.003 c	0.047 ± 0.003 c	0.050 ± 0.003 b
	average	0.091 ± 0.004	0.087 ± 0.009	0.091 ± 0.005
	average tot	0.080 ± 0.005	0.080 ± 0.009	0.110 ± 0.007

.

From the above table, it can be seen that the lowest stomatal conductance values were recorded for variant D2. In this variant, stomatal conductance values ranged from 0.01 M m⁻² s⁻¹ (all genotypes, day zero) to 0.282 M m⁻² s⁻¹ (genotype ‘29-17’, day 10), with the lowest mean value over the period of interest being found in genotype ‘284-17’ (0.061 M m⁻² s⁻¹) and the highest in genotype ‘29-17’ (0.115 M m⁻² s⁻¹). Furthermore, significant differences were found between the different experimental variants. The highest stomatal conductance values were found in plants from control conditions, as shown in Table 4. Table 4 also shows that the stomatal conductance of the control plants was lowest at the beginning of the experiment, when it was 0.01 M m⁻² s⁻¹ for all genotypes, and on the contrary, it was highest in genotype ‘29-17’, on the 10th day of the experiment—0.282 M m⁻² s⁻¹.

Furthermore, the effect of genotype on stomatal conductance values was confirmed, with higher values being achieved by the newly bred cultivar compared to the conventionally bred cultivar. Statistically significant higher average stomatal conductance value was observed for genotype ‘29-17’ (0.110 M m⁻² s⁻¹) followed by ‘284-17’ (0.080 M m⁻² s⁻¹). No significant differences were found between genotype ‘284-17’ and the conventional variety, Bohemia. Due to these higher stomatal conductance values, CO₂ uptake and therefore photosynthesis also increased, as shown in the following results.

Photosynthetic rate (Pn) was significantly affected by experimental variant, genotype, and ontogenetic development at the α = 0.05 significance level, as documented in Figure 1A,C,E. These graphs show an increase in photosynthesis rate within the ontogenetic development of the plants without any difference in variant and genotype. However, it should be noted that the increase in photosynthesis rate in stressed variants was conclusively lower than in control plants. Furthermore, the graphs show that the photosynthetic rate is conclusively reduced under water deficit compared to the irrigation period. After subsequent rehydration, the photosynthetic rate increases again but does not reach the values of the control plants.

The highest values of photosynthetic rate were found in genotype ‘29-17’, Figure 1E, and the highest values of stomatal conductance but average values of photosynthetically active pigments were measured in this genotype. This shows that stomatal conductance has a significant effect on photosynthetic rate compared to pigment content. The photosynthetic rate of this genotype ranged from 7.847 μM m⁻² s⁻¹ (day zero) to 16.755 μM m⁻² s⁻¹ (28th day; C). On the other hand, the genotype ‘284-17’ had the lowest photosynthetic rate, as shown in Figure 1C. It shows that the lowest photosynthetic rate was measured to be 6.743 μM m⁻² s⁻¹ (28th day; D2) and, conversely, the highest was 10.465 μM m⁻² s⁻¹ (18th day; C).

The photosynthetic rate was conclusively affected by a variant of the experiment in which, due to the effect of water deficit, the stomata gradually closed, thereby reducing CO₂ uptake and decreasing leaf water potential, thereby reducing cell pressure (turgor) and subsequently leading to stomata closure. A statistically significant reduction in photosynthesis is observed for all variants, with the most significant reduction observed for variant D2. For this variant, the range of measured values was from 6.743 μM m⁻² s⁻¹ (28th day; ‘284-17’) to 12.900 μM m⁻² s⁻¹ (14th day; ‘29-17’). At the same time, the effect of genotype was demonstrated, with the lowest reduction recorded for genotype ‘29-17’ (7.847 μM m⁻² s⁻¹ (day zero) to 12.900 μM m⁻² s⁻¹ (14th day)) compared to the control (7.847 μM m⁻² s⁻¹ (day zero) to 16.755 μM m⁻² s⁻¹ (28th day)). On the other hand, the conclusively most reduced photosynthetic rate was in cv. ‘Bohemia’. In this cultivar, the photosynthetic rate ranged from 7.643 μM m⁻² s⁻¹ (day zero) to 9.815 μM m⁻² s⁻¹ (14th day), and in the case of the control between 7.643 μM m⁻² s⁻¹ (day zero) and 16.115 μM m⁻² s⁻¹ (28th day), as shown in Figure 1C,E.

In the case of variant D3, when irrigation was applied after a period of water deficit, it can be noted that the photosynthetic rate increased, with the highest increase again recorded in genotype ‘29-17’ and the lowest in cv. ‘Bohemia’. Similar results were also recorded for variant D1; see Figure 1 A,C,E.

As in the case of photosynthetic rate, it can be concluded that this characteristic is mainly influenced by genotype and experimental variant in the case of transpiration (E). The effect of developmental stage has not been demonstrated, as Figure 1B,D,F do not show a clear trend in the increase or decrease in transpiration during ontogenetic development of plants. These graphs show that only genotypes ‘284-17’ and ‘29-17’ show a conclusive decrease in transpiration rate compared to the irrigation period due to water deficit. In the case of cv. ‘Bohemia’, the decrease in transpiration rate due to water deficit was confirmed only in variant D1, but in variants D2 and D3, the transpiration rate increased conclusively. These results show that this cultivar is not suitable for drier areas because it is not able to manage water, which is also reflected in the water potential values, which are conclusively lower compared to the D1 variant. In the case of the remaining genotypes, the transpiration rate of the stressed variants is probably influenced by stomatal inhibition, although the transpiration values were higher compared to the D1 variant.

Consistent with the photosynthetic rate, the transpiration rate was highest in genotype ‘29-17’, Figure 1F; in this genotype, the transpiration rate ranged from 0.897 mM m⁻² s⁻¹ (day zero) to 3.245 mM m⁻² s⁻¹ (28th day; C). On the other hand, the ‘284-17’ genotype had the lowest transpiration rate, as shown in Figure 1D. It shows that the transpiration rate ranged from 0.655 mM m⁻² s⁻¹ (18th day; D1) to 2.685 mM m⁻² s⁻¹ (28th day; C).

The transpiration rate was conclusively affected by a variant of the experiment where the effect of water deficit causes a gradual closure of stomata while the water potential of the leaves decreases. The highest reduction in transpiration rate was found in all genotypes studied in variant D1 (0.655 mM m⁻² s⁻¹ (18th day; ‘284-17’) to 2.265 mM m⁻² s⁻¹ (18th day; ‘29-17’). The highest transpiration rate for this variant was exhibited by the genotype ‘29-17’, which had the lowest transpiration measured at the beginning of the experiment (0.897 mM m⁻² s⁻¹) and, conversely, the highest on the 18th day of the experiment (2.265 mM m⁻² s⁻¹); see Figure 1F. On the other hand, the lowest reduction in transpiration was recorded in cv. ‘Bohemia’ (0.767 mM m⁻² s⁻¹ (day zero) to 2.036 mM m⁻² s⁻¹ (28th day), as can be seen in Figure 1B.

3.3. Parameters of Fluorescence

The results presented in Figure 2A,C,E demonstrate that water deficit affects fluorescence parameters (Fv/Fm) depending on the experimental variant. The results show that the Fv/Fm values obtained were lower than the generally reported value of about 0.820 for all control plants of the genotypes studied. However, this reduction was not statistically significant. In stressed plants, a non-significant decrease of 0.001 in the Fv/Fm ratio value was observed compared to the control.

There were also no statistically significant differences in the value of the Fv/Fm ratio between genotypes. Nevertheless, it can be stated that the lowest fluorescence value was observed in ‘Bohemia’ (0.797) and the highest in genotype ‘29-17’ (0.800). The control plants of cv. ‘Bohemia’ and genotype ‘284-17’ had the lowest fluorescence at the beginning of the experiment (0.761, 0.774 and 0.803) and the highest fluorescence at the end of the experiment (0.816). On the other hand, for genotype ‘29-17’, the lowest value of the Fv/Fm ratio was detected at the end of the experiment (0.781) and on the contrary, the highest value was detected on the 18th day of the experiment (0.811). A similar trend was also found for the stressed variants of all genotypes studied, with variant D2 showing the lowest Fv/Fm ratio values compared to the other stressed variants.

Since no conclusive differences between genotypes and variants were found, another fluorescence parameter was used, which is the Fv/F0 ratio. The values obtained for this ratio are shown in Figure 2B,D,F. Significant differences were found between the genotypes studied, with the lowest value of the Fv/F0 parameter being found in the cv. ‘Bohemia’ (3.963) and the highest in genotype ‘29-17’ (4.083). A decrease in Fv/F0 values was observed in plants growing under water deficit conditions compared to control plants.

The exception is the plants from variant D3, which had a higher ratio compared to the control by 0.006. Plants from variant D2 had the lowest Fv/F0 ratio, which decreased by 0.049 to 3.991 compared to the control plants. No conclusive differences in Fv/F0 were found among the control plants of the genotypes studied within each measurement date. Differences were found only between day 1 (3.328 and 3.578) and day 18 (4.329 and 4.512) for the cv. ‘Bohemia’ and genotype ‘284-17’.

In the case of genotype ‘29-17’, the lowest Fv/F0 value was determined on day 5 (3.835) and the highest on day 18 (4.353). Consistent with the Fv/Fm fluorescence results, it can be concluded that the Fv/F0 ratio also decreased in the stressed variants of all genotypes studied, with the lowest values being achieved by the D2 variant compared to the other stressed variants. No conclusive differences were found within genotypes between measurement dates, except on day 18, when conclusive differences were found within measurement dates.

3.4. Water Potential (ψ_w)

The effect of water deficit on wheat plants was monitored based on water potential values (ψ_w); see Figure 3A–C. The measured values show a conclusive effect of genotype on this characteristic. Among the genotypes studied, the cv. ‘Bohemia’ showed the highest water potential (−1.44 MPa) and the genotype ‘284-17’ the lowest (−1.54 MPa).

The water potential decreased with water deficit; thus, the effect of the variant was confirmed. At a significance level of α = 0.05, the lowest water potential was the lowest in the D2 variant (−1.87 MPa) and the highest in the control plants (−1.14 MPa). Lower water potential was observed for variant D1 compared to variant D3.

For all genotypes studied, a clear reduction in water potential due to water deficit was found in the D2 variant. For this variant, the most significant decrease was observed in the genotype ‘284-17’ (reduction of 75.58%, −2.02 MPa), followed by genotype ‘29-17’ (60.04%, −1.84 MPa) and the smallest decrease in water potential was observed in the cv. ‘Bohemia’ (54.42%, −1.74 MPa). On the other hand, the lowest decrease in water potential was again the same for all genotypes. A statistically significant difference between the control and stressed variant was not found in genotype ‘284-17’. In this case, the decrease in water potential compared to the control was 0.75%, and its value was −1.14 MPa. On the other hand, in the ‘Bohemia’ it was the highest, with a decrease of 25.60% (−1.41 MPa), and for genotype ‘284-17’, 23,59% (−1.42 MPa).

3.5. Statistical Analysis

Table 5. Output from linear regression (yi = α + β1Di, d1 + β2Di, d2 + β3Di, d3 + γ1Di, v1 + γ2Di, v2 + εi) using dummy variables (coefficient significant at α = 0.05 significance level is indicated in bold).

Coefficient	Transpiration	Photosynthesis	Fv/Fm	Fv/F0	Total Chlorophylls	Carotenoids	Water Potential
constant	1.705	11.005	0.796	3.98	7.811	1.256	1.089
D1 (d1)	−0.244	−1.678	0.0002	0.0017	−1.553	0.143	−0.416
D2 (d2)	−0.086	−0.785	−0.0017	−0.0540	−1.608	−0.072	−0.725
D3 (d3)	−0.017	−1.655	0.0007	0.0050	−0.462	−0.109	−0.282
genotype ‘284-17’	0.021	−2.095	0.0025	0.0720	8.030	1.242	−0.099
genotype ‘29-17’	0.183	1.499	0.0039	0.0201	4.137	0.638	−0.063

shows that when changing the variant to D1, the total chlorophyll content is, on average, 1.55 nM cm⁻² lower than in the control plants. Similarly, a reduction in total chlorophyll content can be found when changing the variant to D2. In this case, the chlorophyll content decreased, on average, 1.61 nM cm⁻². When assessing the effect of genotype, it can be noted that in the case of genotype change under control conditions to genotypes ‘284-17’ and ‘29-17’, the content of total chlorophyll was measured to be an average of 8.03 nM cm⁻² and 4.14 nM cm⁻² higher than in the case of the variety ‘Bohemia’. Statistical analysis shows that water deficit and genotype have a statistically significant effect on total chlorophyll content.

The carotenoid content, a statistically significant effect of genotype was found; comparing the genotype under control conditions to genotypes ‘284-17’ and ‘29-17’, the content of carotenoids was on average 1.24 nM cm⁻² and 0.64 nM cm⁻² higher than in the case of the variety ‘Bohemia’. Rate of photosynthesis was significantly affected by water deficit, when changing the variant to D1, D2 and D3, the value of photosynthesis rate was on average 1.68 μM m⁻² s⁻¹, 0.79 μM m⁻² s⁻¹ and 1.65 μM m⁻² s⁻¹ lower than the control, respectively. Similarly, it was shown effect of genotype on changes in photosynthetic rate. Differences were found between genotypes ‘284-17’ and ‘29-17’ compared to the cv. ‘Bohemia’, where both new cultivars the rate of photosynthetic was, on average, 2.09 μM m⁻² s⁻¹ and 1.5 μM m⁻² s⁻¹ lower.

If the transpiration rate is changed to D1, its value is, on average, 0.24 mM m⁻² s⁻¹ lower than the control. If we change the genotype to genotype ‘284-17’, the rate of transpiration is, on average, 0.18 mM m⁻² s⁻¹ higher than in the control cv. ‘Bohemia’. It follows that the water deficit and genotype have a statistically significant effect on the transpiration rate.

The evaluation of the effect of genotype and water deficit on fluorescence parameters shoed that there was no statistically significant effect.

The results of the statistical analysis, as seen in Table 5, of the osmotic potential evaluation show that the osmotic potential value is, on average, −0.42 MPa lower than in the control when changing the variant to D1. When changing the variant to D2, the osmotic potential value is, on average, −0.72 MPa lower than the control. When the variant is changed to D3, the osmotic potential value is, on average, −0.28 MPa higher than the control. Thus, it can be concluded that water deficit has a statistically significant effect on the osmotic potential of plant leaves.

4. Discussion

The obtained results of the content of photosynthetically active pigments confirm the conclusions of Radzikowska et al. [55] for spelt, Sayed [56] for cereal crops, Zhang et al. [57] for carrot and Moharramnejad et al. [18] for maize, because the cv. ‘Bohemia’ showed the lowest chlorophyll content compared to the other monitored genotypes. At the same time, it was confirmed that the observed genotypes of wheat responded differently to the influence of water deficit through reducing the chlorophyll content; see the work on spelt and maize [58,59], when among the genotypes observed, the content of chlorophyll a and b in the leaves decreased the least due to the drought in the cv. ‘Bohemia’ and, on the other hand, the most in genotype ‘284-17’. As a result of the water deficit, the chlorophyll content in the leaves and the ratio of a to b decrease. This reduction can be caused not only by the degradation of chlorophyll, the formation of chlorosis and, above all, by the inhibition of chlorophyll synthesis but also by the formation of reactive oxygen species, which is also confirmed in their work on legumes [60,61] and chives [62]. For all monitored genotypes, the content of total chlorophylls increased after subsequent rehydration, but the values of the control plants were not reached. This conclusion is confirmed by, for example, [63,64]. The increase in the content of pigments is probably influenced by the increase in cell tension in the leaves, the reduction of oxidative stress and the restoration of chlorophyll formation.

Similarly, to the chlorophyll content in the leaves, the carotenoid content was influenced by genotype, with genotype ‘284-17’ showing the highest carotenoid content and the cv. ‘Bohemia’ the lowest. Genotypic differences in pigment content are reported, for example, in Catharanthus roseus by Ababaf et al. [65]. Carotenoids, as plant pigments, are involved in reducing the concentration of reactive oxygen species and free radicals, as evidenced by Ramel et al. [66] and Darawsha et al. [67]. Changes in the concentration of carotenoids due to water deficit are confirmed by works, for example, [68,69]. As a result of the water deficit, the content of carotenoids increased in variant D2, when it was the variant with the most pronounced stress, but this is a genotypic characteristic. Only the cv. ‘Bohemia’ responded to the most pronounced drought stress through increasing carotenoid concentrations. This conclusion is confirmed by Ababaf et al. [65] in Catharanthus roseus and Taheri et al. [70] in Anchusa italica.

A significantly higher decrease in carotenoid content indicates a higher sensitivity to drought stress [14], which was confirmed in the new breeding, but in the case of cv. ‘Bohemia’, their content increased, while this variety is sensitive to drought. This difference may probably be due to the slower degradation of carotenoids, but also to the effect of genotype, with cv. ‘Bohemia’ showing lower pigment values and therefore a lower ratio between chlorophylls and carotenoids.

The reduced content of photosynthetically active pigments in leaves (non-stomatal inhibition of photosynthesis) due to water deficit contributed to the reduced CO₂ assimilation. A similar conclusion is also confirmed by [71]. Similar results are described for maize [72], where they conclude that the reduction in photosynthesis is not only due to a reduction in pigment content but also due to the duration of water deficit, which was confirmed especially for the D2 and D1 variants. The reduction in the photosynthetic rate is also due to a reduction in leaf area and a lower demand for assimilates, which are preferentially transported to the root system at the expense of aboveground biomass. However, photosynthesis is not only limited by the pigment content but also by stomatal conductance, which decreases due to stomatal closure. This conclusion is confirmed, e.g., by [73]. According to Onyemaobi et al. [37], the decrease in photosynthesis is due to stomatal closure, a relatively fast process that also reduces water loss. A decrease in stomatal conductance due to water deficit was observed in all genotypes studied within the first few days after the induction of stress. The above conclusion is also supported by Figure 2 and Figure 3, which conclude that stomatal closure occurs within 4 days of stress. Furthermore, the effect of genotype on stomatal conductance was found, with genotype ‘29-17’ having the highest. Water deficit resulted in a decrease in photosynthetic rate in all genotypes studied, with the cv. ‘Bohemia’ and genotype ‘284-17’ showing the lowest photosynthesis.

This agrees with the findings of, e.g., Radzikowska et al. [55], who compared sown and spelt varieties, and also Khalil et al. [74], for durum wheat. The reduction in CO₂ assimilation due to stomatal closure (stomatal inhibition) leads to the limited growth of aboveground biomass, the disruption of the sink–source relationship and the distribution of ATP as well as NADPH. Photosynthesis is therefore one of the metabolic processes that is affected by water deficit [73,75,76]. At the onset of water deficit, it is likely that the stomatal inhibition of photosynthesis was due to a reduction in stomatal conductance, which was subsequently supplemented by non-stomatal inhibition caused by reduced pigment content, altered electron transport within photosystem II (PSII) and possibly altered enzyme activity, especially considering the work of Rubisco [75,76]. The photosynthetic rate increased after the re-watering, as also confirmed in maize [77] and Lupinus albus by Pinheriro et al. [78]. The increase in photosynthesis and transpiration rates is due not only to turgor recovery but also to cell growth and new tissue. Similar to the photosynthesis rate, the transpiration rate was limited by water deficit. The above reduction is not only related to the progressive loss of turgor, but subsequently to the closure of stomata [9,31,38], reducing nutrient uptake. The relationship between stomatal conductance and gas exchange (photosynthesis, transpiration) that was confirmed in our research is also in agreement with the results in maize [21], wheat [79,80,81] and soyabean [3]. The reduction in transpiration due to drought was further confirmed by the work Further; the effect of genotype on this characteristic was confirmed in agreement with the work of Wasaya et al. [64], Bakhshandeh et al. [82] and Poudel et al. [83].

The reported characteristics of Fv/Fm (the maximum quantum yield of PSII) [84] and Fv/F0 (non-QA- electron transfer) [85] are the main indicators of the degree of damage to PSII by stressors [86]. Fv/Fm is a measure of the maximum photochemical efficiency of PSII when all reaction centres are open, when its value is in the range of 0.83. Consistent with work on bean [87] and wheat [88,89], a decrease in the Fv/Fm fluorescence ratio values has been demonstrated in plants stressed by water deficit. The decrease in fluorescence may be a defence mechanism of the plant due to increased heat and energy dissipation, as well as a reduction in carboxylation activity. Thus, the effect of drought is to reduce electron transfer during photosynthesis. Furthermore, according to the results of Lu end Zhang [90], photoinhibition occurs, which reduces fluorescence. A decrease in Fm has been shown, as also stated by, e.g., Gilmore and Björkman [91] and Zlatev [92]. However, the effect of genotype on fluorescence changes was not confirmed; the above is in contradiction with the results on spelt, as researchers detected changes in the Fv/Fm ratio in the context of a comparison between sown wheat and spelt varieties. Nevertheless, lower fluorescence was detected in the cv. ‘Bohemia’ and higher in the genotype ‘29-17’.

The Fv/F0 ratio is a useful parameter for determining the degree of sensitivity or resistance of a given genotype to a stressor. It has been shown that the cv. ‘Bohemia’ is more sensitive to drought stress and that the genotype ‘29-17’ is tolerant. This confirms the results of [93]. This parameter was adversely affected by stress, with partial chlorophyll degradation and a reduced electron transfer rate. According to [20,94], the above parameter is influenced by increased F0, which is related to the inactivation of PSII and the change in the acceptor of reduced plastoquinone. The increase in F0 is accompanied by a decrease in Fm at high stress levels, indicating degradation of the PS II light-harvesting complex, as reported by [95]. The above was confirmed for the D3 variant.

From the results obtained, it is evident that the water deficit causes a gradual decrease in the water potential of the leaves. This effect is evident in all experimental variants, with the highest reduction in water potential observed in variant D2. In general, water potentials lower than −1.5 MPa already indicate a severe water deficit, with a point of permanent wilting as reported by Torres et al. [96]. Within this point, there is an irreversible reduction in turgor, membrane damage, and a decrease in plant water potential [97], as evidenced by our results.

This value was exceeded for all genotypes within the D2 variant from approximately the 14th day of the experiment. A further reduction was observed during the dehydration period for variants D1 and D3, with a lower water potential observed for variant D1 compared to variant D3. This phenomenon is due to the fact that water stress was re-induced in variant D1 after rehydration. After subsequent rehydration, an increase in water potential could be observed in these variants, but it did not reach the values of the control plants. An increase in water potential due to rehydration is also documented by Henry et al. [98]. The decrease in water potential is due to the impaired water uptake by the roots and also limited transpiration, which is limited by stomatal conductance and transpiration.

There were also clear differences within genotypes in response to water deficit. Furthermore, the effect of genotype was confirmed, with the highest reduction in water potential due to water deficit observed in genotype ‘284-17′ and the lowest in cultivar ‘Bohemia’. Genotypic differences in stress response were confirmed in wheat, for example, by [99,100]. In these two genotypes, transpiration is affected by stomata, but their water management is worse. Presumably, these are the genotypes that have higher values of the transpiration coefficient. Another possibility is the change in the structure of the stomata and their number per unit leaf area or the formation of cuticle. In the case of genotype ‘29-17′, the transpiration values were high, but the water potential values were between those of the remaining genotypes. Based on this, it can be concluded that there is a non-stomatal influence on water output, osmotic adjustment [101,102,103] and changes in water transport within organs.

5. Conclusions

The results show that the content of photosynthetically active pigments, the rate of gas exchange and stomatal conductance decreased in the stressed variants. Furthermore, due to the water deficit, the water potential of the leaves of the studied genotypes decreased. Only chlorophyll fluorescence values were not significantly affected by water deficit. Furthermore, the influence of the genotype on the monitored physiological characteristics and the different response of plants to water deficit was demonstrated. Genotype ‘29-17’ appears to be promising with regard to resistance to drought with respect to the rate of photosynthesis; despite the increase in transpiration and the reduction in water potential, it manages water better, with respect to the reduction in water potential in above-ground organs. On the other hand, the cv. Bohemia appears to be less suitable for dry areas because, despite its relative plasticity, it shows a deficit in the water zone not only in high values of water potential but also in a demonstrably most significant decrease in water potential.

These results show that wheat plants with a change in ear morphotype and with awns have potential not only as breeding material but also for growers under global climate change. Examining the physiological characteristics of not only juvenile plants but also mature ones is an appropriate method for assessing the resistance or sensitivity of plants to stressors in the screening of breeding material. Another objective will be to monitor not only anatomical–morphological, physiological and biochemical parameters but also genetic analyses during the ontogenetic development of plants, including yield formation.