Potential Application of Selenium and Copper Nanoparticles in Improving Growth, Quality, and Physiological Characteristics of Strawberry under Drought Stress

Abstract

Drought stress can reduce strawberry yield and quality and is one of the main abiotic factors restricting strawberry production in China. Nano-agricultural technology has significant regulatory effects in improving crop yield and quality and reducing agricultural environmental pollution. We performed a pot experiment using FenYu No. 1 strawberry and applied copper nanoparticles (CuNPs) and selenium NPs (SeNPs) to study their effects on the growth, quality, photosynthetic parameter indexes, and physiological characteristics of strawberry plants under drought stress. The growth and photosynthesis of strawberry plants were significant adversely affected by moderate drought stress (DS, 60% field capacity (FC)) and severe drought stress (SS, 25% FC). Compared with normal water-holding conditions, the application of CuNPs, SeNPs, and their combination effectively increased the agronomic traits of strawberry plants; improved fruit quality; and enhanced the content of photosynthetic pigments (chlorophyll a, chlorophyll b, and total chlorophyll), photosynthetic characteristic parameters, chlorophyll fluorescence parameters, and water-use efficiency. In addition, the exogenous application of CuNPs and SeNPs improved the drought tolerance of plants by increasing the activities of antioxidant enzymes catalase, peroxidase, and superoxide dismutase, and decreasing the malondialdehyde content, with the following overall trend among the treatments: control < CuNPs < SeNPs < CuNPs + SeNPs. The results of the principal component analysis showed that the two extracted principal components could reflect 85.54% of the information of the original data, leaf photosynthetic pigments, photosynthetic characteristic parameters, chlorophyll fluorescence parameters, and strawberry agronomic traits indexes and could be used as the primary indexes for evaluating the improvement of strawberry growth by nanofertilizers under drought-stress conditions. Taken together, our results indicate that nanofertilizers have potential for improving the growth, quality, and physiological characteristics of strawberries under drought stress.

1. Introduction

As the climate continues to warm due to the greenhouse effect, water scarcity has become a major threat to plant development and growth, and safe crop production [1]. Currently, large areas of cultivated land in the world experience arid or semi-arid conditions, and severe drought significantly affects plant growth and development and physiological metabolism, including water-use efficiency, nutrient uptake, photosynthetic efficiency, total chlorophyll content, and hormone levels [2,3]. Although plants are able to reduce cellular water potential and enhance the water-extraction capacity in water-limited environments, water-deficient environments still have adverse effects on crop growth and development, yield, and quality [4,5]. Currently, related technologies to improve plant tolerance to environmental stresses have been reported, among which nano-agricultural technologies have significant regulatory effects in improving crop yield and quality, reducing resource inputs, and minimizing agricultural environmental pollution, which has become a research hotspot in the field of environment [6]. With the development of agricultural technology, nanofertilizers are increasingly used in agricultural production.

With the development of agricultural technology, nanofertilizers are increasingly used in agricultural production. Studies have shown that nanoparticles (NPs; size < 100 nm) are similar to biomolecules such as proteins and are able to cross cell membranes [7]. Their physical and chemical properties are functionally different from the conventional species of large particles [8]. Nanofertilizers have low toxicity and high bioactivity compared to conventional fertilizers and provide nutrients to plants in nano-form. They are expected to replace conventional fertilizers in promoting plant growth and yield [9]. In order to increase crop seed vigor and stress tolerance and improve crop quality, the application of several types of nanomaterials—mainly selenium (Se), copper (Cu), and zinc—has become a necessary measure in agricultural production [10,11]. Li et al. (2020) found that foliar spraying of 20 mg·L⁻¹ SeNPs activated phenylpropane and branched-chain fatty acid pathways, as well as related enzymes and gene expression, and promoted the synthesis of capsaicinoids, flavonoids, and total phenols in chili peppers, which have anti-inflammatory, anticancer, antioxidant, and other health functions [12]. Hafez et al. (2021) showed that 70 mg·kg⁻¹ CuNPs significantly increased the chlorophyll content of pear trees by 39.6% [13]. In tomato plants, 1 mg·kg⁻¹ CuNPs significantly increased the activity of ribulose diphosphate carboxylase, facilitated the fixation of CO₂, and increased leaf photosynthesis [14]. Zhao et al. (2017) [15] investigated the effect of exposure to different concentrations of CuNPs on cucumber fruits and showed that essential amino acids, leucine, isoleucine, and threonine were elevated in fruit to varying degrees. CuNPs and SeNPs are key enzymes in the antioxidant defense system of plants, helping them to scavenge free radicals more efficiently and reduce oxidative stress. Cu is a cofactor for many enzymes and is essential for processes such as photosynthesis, respiration, and nitrogen metabolism in plants. Se, on the other hand, is a trace element that is also important for antioxidant defense and metabolic activities in plants. CuNPs promote stomatal closure and reduce water evaporation, while SeNPs improve the osmoregulatory capacity of plants, helping them to better retain water under drought conditions. However, little research has been conducted on the role of Se and Cu bio-nanofertilizers in regulating crop growth and quality under drought stress.

Strawberries (Fragaria × ananassa) are part of the Fragaria genus of persistent perennial herbs of the Rosaceae, with the reputation as the queen of fruits, and are one of the world’s most widely eaten berries [16]. This is also an economically important fruit crop, with high yield, early marketability, and quick results. However, due to its rapid growth, strong fruiting ability, and shallow root system, the growth and development of the strawberry is strongly affected by environmental conditions such as soil moisture and temperature. Especially in the seedling stage, strawberries are very sensitive to drought conditions [17]. Strawberry fruits contain a high percentage of water, which means that they are easily affected by a lack or excess of irrigation water [18]. Modise et al. (2006) [19] found that deficit irrigation negatively affected strawberry fruit aroma [20]. Zahedi et al. (2023) [21] found that stomatal relationships and CO₂ diffusion into leaves were limited under drought stress, resulting in reduced leaf growth parameters, relative water content, photosynthetic pigments, and photosynthesis [22,23]. Water deficiency leads to chlorophyll degradation, which directly inhibits photosynthesis, which in turn adversely affects plant development by reducing cell division, expansion, and differentiation [20,24]. Furthermore, under drought stress, water deficit triggers an imbalance between reactive oxygen species (ROS) scavenging and production. This oxidative stress caused by high ROS concentrations disrupts the photosynthetic machinery containing chloroplast structures and reaction centers [25]. Photosynthesis is the basis of plant growth and crop yield, and the significant promotion of photosynthesis in plant leaves under drought conditions by Cu and Se has been observed in different plants [26]. It is evident that nanoparticles can effectively enable plants to thrive well under different environmental cues. Relative studies have shown the beneficial role of selenium nanoparticles (Se-NPs) in alleviating the adverse effects of soil drought on strawberry growth and yield. There is a lack of research on how the combined application of SeNps and CuNPs ameliorates the adverse effects of drought stress on strawberries. The foliar spraying of nanoparticles has obvious advantages in improving efficiency, reducing pollution, and enhancing crop performance, thus making it a nanoparticle application method worth promoting. However, fewer studies have been conducted on foliar nanoparticle application in ameliorating plant abiotic stresses.

We hypothesized that the (i) foliar spraying of CuNPs and SeNPs was able to increase the photosynthetic activity used for osmotic protection and enhanced plant tolerance to drought stress; and (ii) synergistic effects of the foliar spraying of CuNPs and SeNPs can alleviate drought stress-induced oxidative stress in plants. The objective of this study was to test whether the application of CuNPs and SeNPs suppresses the adverse effects of drought stress on strawberry growth, photosynthetic characteristics, and seeding enzymatic antioxidants of strawberry, and we also explored the positive effects of CuNPs and SeNPs on improving the nutritional value of strawberry fruits under drought stress. Our study will provide a theoretical basis for the study of exogenous nano-fertilizers for the healthy growth of strawberries under drought stress.

2. Materials and Methods

2.1. Preparation of Nanofertilizers

The SeNPs and CuNPs with diameters of 5–18 and 35–42 nm, respectively, were obtained from the Center for Applied Chemical Research, Saltillo, Mexico, and were both prepared using chitosan as a stabilizer, as described by Quiterio-Gutiérrz et al. (2019) [20]. SeNPs were synthesized by a procedure similar to that used by Kong et al. [24] Using a glass reactor equipped with mechanical stirring, temperature control, and an inert atmosphere system, an aqueous solution of selenious acid (H₂SeO₃) and a solution of Cs-PVA were mixed at 400 rpm at a temperature of 0 °C. Subsequently, N₂H₄ was added to perform the reduction. The copper nanoparticles were synthesized following the methodology described by Cadenas-Pliego et al. [25]. We prepared an ethanol solution of red phosphorus at a concentration of 5 mg·mL⁻¹ and a 0.01 mol·L⁻¹ aqueous copper acetate solution. We then mixed 20 mL of red phosphorus ethanol solution with 10 mL of copper acetate aqueous solution to obtain a mixture. After that, we stirred said mixture for 20 min at room temperature, with a stirring rate of 200 rpm, to react said mixture, separating the solids in the reacted mixture and then washing and drying said solids, which are copper nanoparticles. The CuNP and SeNP powders were added to ultrapure water and ultrasonicated (100 W, 40 kHz) for 30 min, so that the powder was uniformly dispersed to form a suspension solution for backup.

2.2. Experimental Setup

The experiment was carried out at the Zhijiang Base of Hangzhou Academy of Agricultural Sciences (29°39′25″ N, 119°35′38″ E) from 7 March to 25 June 2022 in a greenhouse, with a photoperiod of 14/10 h (light/dark), temperature of 25/20 ± 5 °C, and air relative humidity of 80 ± 5%. The strawberry cultivar was Fen Yu No. 1, cultivated by the Hangzhou Institute of Agricultural Science. Fenyu No. 1 is an early ripening, disease-resistant pink-peel strawberry cultivar (Fragaria × ananassa Duchesne) derived from a cross between Kaorino as a female parent and 2012-W-02 as a male parent.

The experimental setup had the substrate moisture content as the main treatment and the application of nanomaterials as the secondary treatment. The sub-treatments were CK (without CuNPs and SeNPs), CuNPs (CuNPs only), SeNPs (SeNPs only), and CuNPs + SeNPs (combined application of CuNPs and SeNPs), all of which were combined with the normal water content of the substrate (WW), mild drought stress (MD), and severe drought stress (SD), with a total of 12 combinations of treatments. For WW treatment, the water content of the substrate was 80 ± 5%, the DS treatment had a substrate water content of 55 ± 5%, and the SS treatment had a substrate water content of 20 ± 5%. Soil moisture content in the pots was determined using a configuration of ML2 probes (ThetaProbe soil moisture devices, DELTAT Ltd., Cambridge, UK) and HH2 moisture meter Delta-T Devices (HH2 moisture meter, Delta-T Devices Ltd., Cambridge, UK), with supplemental watering using drip irrigation to ensure that soil moisture was within the range set for the experiment. The potting unit was a plastic bucket of height 35 cm, top diameter 25 cm, and bottom diameter 23 cm. The soil samples were collected at five different sites of each plot and combined into a sample mixture (1:1:2 = sand/animal manure/topsoil) was used. Fertilizers were applied one week after planting: 10 mL of fertilizer solution (1:3000 = NPK:water) and (1:2000 = NPK:water) water-soluble fertilizer every 2 weeks until strawberry harvest.

During the growing season (10–25 March), plants were irrigated daily to 100% field capacity (FC) using graded cylinders, and then three levels of watering were applied: normal water-holding condition (WW, 100% FC), moderate drought stress (DS, 60% FC), and severe drought stress (SS, 25% FC). The FC was determined by the gravimetric method, according to Souza et al., 2000 [26]. Water treatments were maintained by daily weighing, replacing water lost by transpiration, with a precise scale. These methods were applied for 92 days during the growing season (25 March to 26 June) until harvest, and five fully expanded leaves (sampled 18 April) were subjected to non-drought (normal water-holding conditions) and varying degrees of drought (moderate and severe). On day 31 after the start of the drought treatments, the plants showed stress symptoms. On that day, the upper leaf surfaces of control and drought-treated strawberry plants were sprayed with a solution containing 100 mg·L⁻¹ SeNPs and 100 mg·L⁻¹ CuNPs until fully moistened (approximately 25 mL per plant) and were sprayed once a week until harvest (three sprays in total). Foliar sprays were applied before flowering and at sunset. The experiment was terminated after 98 d. Agronomic traits were recorded: plant height, dry weight, fresh weight, number of flowers and fruits, number of leaves per plant, leaf area, and yield.

2.3. Determination of Strawberry Plant Agronomic Traits Indicators

In each treatment, 10 strawberry plants were randomly selected after 98 d for the determination of relevant indexes, plant height, number of leaves, number of flowers, and number of fruits. The same median leaf position was used to determine the length and width of a single leaf. The leaf area was calculated: strawberry leaf area = leaf length × leaf width × 0.73 [27]. Strawberry aboveground parts and root systems were quickly cut and weighed on a balance for fresh weight (FW). Strawberry aboveground parts and root systems were killed at 105 °C for 30 min, dried at 70 °C until constant mass, and weighed and recorded. Yield consisted of the number of fruits and the average annual mass of fruits, recorded by manual counting and weighing method. Fruit firmness was determined using a texture analyzer with an 8 mm probe (Soil Testing Equipment Professional Systems GmbH, STEP-TII Beijing Co., Ltd., 10 Tianxiu Road, Beijing, China), and the firmness test speed is 1 mm·s⁻¹. Relative water content was determined by the method of Barrs and Weatherley, 1962 [28].

2.4. Measure of Photosynthetic Pigment Content and Photosynthetic and Fluorescence Parameters

The net photosynthetic rate (P_n), transpiration rate (T_r), intercellular CO₂ (C_i), and stomatal conductance (G_s) of leaves were determined using the LI-6200 Portable Photosynthesis Measurement System (LI-6200; LI-COR Environmental Ltd., Lincoln, NE, USA). The leaf-chamber temperature was set at 25 ± 1 °C, CO₂ concentration at 380 μmol·mol⁻¹, and light quantum density at 900 μmol/(m²·s); and five leaves were selected for each treatment for measurement.

The photosynthesis system equipped with a chlorophyll fluorescence system (LI-6200) was used to measure chlorophyll fluorescence parameters of the second fully expanded leaf. After 30 min of dark treatment, the minimum fluorescence (F_o), the saturated maximum fluorescence (F_m) of dark-adapted, the minimum fluorescence (F_o′), the fluorescence rises to the maximum fluorescence of the energized vesicle (F_m′), and the stabilized fluorescence (Fs) were determined under normal light, and each treatment was repeated three times. Among the chlorophyll fluorescence parameters, the maximum photochemical efficiency of photosystem II (PSII) [F_V/F_m = (F_m − F_o)/F_m], the actual photochemical efficiency [ΦPSII = (F_m′ − F_s)/F_m′], the effective quantum efficiency of PSII [Eq = (F_m′ − F_o′)/F_m′], and the photochemical fluorescence burst coefficient [qP = (F_m′ − F_s)/(F_m′ − F_o′)] were determined.

Of fresh leaves, 40 mg was ground with liquid nitrogen. Then, it was heated in 4 mL of 80% acetone at 68 °C (in darkness) for 15 min and filtered. The absorbance values of the solution were determined at 646 and 663 nm, using an enzyme marker, Varioskan LuX (Thermo Ltd., 81 Wyman Street, Waltham, MA, USA). There were three technical replicates for each biological sample. The formulas used for calculation follow:

W₁ = (12.21 A₆₆₃ − 2.81 A₆₄₆)v/(1000m)

(1)

W₂ = (20.31 A₆₄₆ − 5.03 A₆₆₃)v/(1000m)

(2)

where W₁ is the chlorophyll a content (mg/g), v is the solution volume (mL), W₂ is the chlorophyll b content (mg/g), and m is the mass of the leaf (g).

2.5. Measurement of Physiological Indexes

The malondialdehyde (MDA) content in the leaf samples was determined spectrophotometrically at 532 nm, according to Dhindsa et al. (1981) [29].

For each treatment group, 0.2 g of frozen strawberry leaves was taken, and 5 mL of buffer (3 mL for grinding and 2 mL for rinsing and fixing) was quickly added at low temperature, ground to homogenization in a pre-cooled mortar, and centrifuged at 7000 r/min for 20 min at 4 °C, and the supernatant was taken (i.e., crude enzyme extract). The superoxide dismutase (SOD) activity was determined by the nitrogen blue tetrazolium photochemical reduction method [30], and two control tubes were set up, with 0.1 mL of distilled water replacing the crude enzyme extract, one of which was shaded and darkened to serve as a sample blank, and the absorbance value of A560 was measured at the end of the reaction. Peroxidase (POD) activity was determined by the guaiacol colorimetric method, and a phosphate buffer replacing the enzyme solution was used to determine its activity. Phosphate buffer was used instead of enzyme solution apoptosis, and readings were taken at 1 min intervals, with a change of 0.01 in A470 per minute as 1 unit of enzyme activity. Catalase (CAT) activity was determined by UV absorption [30], and readings were taken at 1 min intervals, with a change of 0.0436 in A240 per minute set as 1 unit of enzyme activity. The SOD, POD, and CAT activities were calculated using Equations (3)–(5), and each enzyme activity was expressed in enzyme units per gram FW:

SOD = (A_o − A_s)V_T/(A_o × 0.5 × W × V_s)K

(3)

POD = (ΔOD₄₇₀ × V_T)/(W × vs. × 0.01 t)

(4)

CAT = (E₂₄₀ × V_T × K)/(0.0436 W × Vs)

(5)

where A_o is the blank absorbance value, A_s is the sample absorbance value, V_T is the total volume of the sample, vs. is the amount of sample determination, W is the FW of the sample, K is the sample dilution times, t is the reaction time, and E₂₄₀ is the average value of the reduction per minute of optical density at 240 nm.

2.6. Fruit Quality Determination

The total phenolic content was determined according to Luo et al. (2011) [31]. Of strawberry fruit samples, 3 g was ground in liquid nitrogen, 10 mL of 80% acetone added, and the sample was macerated at room temperature for 1 h, with shaking every 10 min; this was followed by centrifugation at 4500 rpm for 10 min at room temperature, and the supernatant crude extract was obtained. Of the supernatant, 12.5 μL was added to 250 μL of 2% Na₂CO₃, shaken well, and left at room temperature for 5 min; then, 12.5 μL of Folin’s reagent was added, and the absorbance measured at 655 nm after 30 min of reaction.

The total flavonoid content was determined according to Chirinos et al. (2007) [32]. Of fruit samples, 3 g was ground using liquid nitrogen, and 10 mL of 80% acetone was added. Then, it was macerated at room temperature for 1 h, with shaking every 10 min; centrifuged at 4500 rpm for 10 min at room temperature; and 30 μL of the supernatant taken and added to 90 μL of 95% ethanol, 6 μL of 1 mol·L⁻¹ potassium acetate, and 168 μL H₂O. This was shaken well and kept at room temperature for 40 min, when absorbance at 415 nm was measured.

The concentration of ascorbic acid (vitamin C) in the fruit extracts was determined by titration with a solution containing iodine (I) and potassium iodide (KI) (1.72 and 16 g, respectively, dissolved in 1 L of water). The titration was completed when the sample turned dark blue and the color was stable. The volume of I + KI solution was recorded, and the concentration of ascorbic acid was calculated as ([0.88 × V]/5 × 100), where V is the amount of I + KI solution consumed.

Total anthocyanins were determined by pH difference method, using two buffer systems: 25 mM KCl buffer (pH 1.0) and 0.4 M Na acetate buffer (pH 4.5). The samples were diluted with KCl buffer, and readings were taken at 510 and 700 nm after incubation for 15 min in both buffers; each sample was repeated five times, and total anthocyanin content was calculated according to Giusti and Wrosltad (2001) [33]:

Total anthocyanin content = [(A × MW × DF × 100)/MA]

(6)

where A = (A510 − A700), MW is the molecular weight, DF is the dilution factor, and MA is the molar absorptive coefficient of cyanidin-3-glucoside (C3G). The results were expressed as mg C3G per 100 g of juice.

2.7. Data Processing and Statistical Analysis

Excel 2003 software was used for data processing and plotting, and SPSS2019 software was used for data analysis. One-way and two-way analysis of variance (ANOVA) and Duncan’s method were used for ANOVA and multiple comparisons (α = 0.05), and the data were subjected to principal component analysis (PCA) and cluster analysis (CA). The experimental data were plotted using Origin 2022 software.

3. Results

3.1. SeNPs’ and CuNPs’ Effects on Agronomic Traits of Strawberry Plants under Drought Stress

The agronomic indicators of strawberry plants under WW were higher than those for the MD and SD treatments, indicating that drought stress adversely affected the growth of strawberry plants (

Table 1. Effect of foliar application of nanoparticles containing selenium and copper on agronomic traits in strawberry plants under drought-stress conditions.

Treatments		Height (cm)	Shoot Dry Weight (g)	Root Dry Weight (g)	Shoot Fresh Weight (g)	Root Fresh Weight (g)	Number of Leaves per Plant	Leaf Area (cm2)	Number of Inflorescences Per plant	Fruit Firmness (N)	Yield (g)
Drought (D)	NPs (mg·L−1)
WW	CK	20.16 ± 2.16 ab	8.56 ± 2.18 cde	4.78 ± 0.46 cd	30.53 ± 2.17 abcd	17.03 ± 1.78 a	7.87 ± 0.76 abc	54.09 ± 2.99 b	16.87 ± 2.26 cd	1.76 ± 0.26 bc	914.65 ± 16.12 b
(100% FC)	CuNPs	21.89 ± 2.16 a	11.43 ± 1.07 ab	7.96 ± 0.96 a	32.97 ± 1.98 ab	20.11 ± 1.34 ab	8.13 ± 1.22 ab	55.78 ± 1.29 b	19.42 ± 3.33 bc	1.89 ± 0.15 ab	936.77 ± 52.34 ab
	SeNPs	22.76 ± 2.96 a	10.23 ± 1.57 bc	7.13 ± 0.84 ab	31.15 ± 2.34 abc	19.05 ± 2.22 ab	8.45 ± 1.29 ab	56.36 ± 1.69 b	21.46 ± 3.78 ab	2.01 ± 0.22 ab	945.05 ± 27.94 ab
	CuNPs + SeNPs	24.17 ± 5.14 a	12.87 ± 2.1 a	9.07 ± 1.03 a	33.89 ± 4.29 a	22.19 ± 4.39 a	9.06 ± 3 a	68.52 ± 2.86 a	24.31 ± 2.74 a	2.23 ± 0.39 a	969.21 ± 16.4 a
DS	CK	11.43 ± 1.71 cde	5.67 ± 0.65 fgh	2.45 ± 0.81 ef	21.46 ± 2.73 d	7.94 ± 1.30 e	5.13 ± 0.82 d	36.25 ± 2.43 d	11.46 ± 2.59 ef	1.24 ± 0.18 de	345.12 ± 33.82 d
(60%FC)	CuNPs	13.56 ± 2.49 cd	7.86 ± 0.94 def	4.14 ± 0.85 cde	23.41 ± 2.29 cd	10.46 ± 2.09 cde	6.35 ± 1.33 bcd	41.36 ± 3.9 cd	14.67 ± 2.86 de	1.45 ± 0.08 cd	377.52 ± 36.45 cd
	SeNPs	14.38 ± 1.86 c	7.14 ± 0.84 efg	5.65 ± 0.99 bc	24.06 ± 2.72 bcd	11.85 ± 2.17 cd	6.52 ± 0.63 bcd	45.26 ± 3.93 c	15.04 ± 2.75 de	1.49 ± 0.17 cd	395.21 ± 28.04 c
	CuNPs + SeNPs	16.25 ± 3.21 bc	9.94 ± 1.56 bcd	7.12 ± 2.59 ab	24.97 ± 2.82 abcd	13.25 ± 2.01 c	7.94 ± 0.82 abc	56.04 ± 3.58 b	18.63 ± 2.57 bcd	1.53 ± 0.14 cd	423.13 ± 37.43 c
	CK	6.13 ± 0.69 f	2.75 ± 0.49 i	1.87 ± 0.43 f	6.13 ± 0.89 e	4.24 ± 0.61 f	2.85 ± 0.26 e	12.71 ± 1.23 f	2.04 ± 0.15 h	0.56 ± 0.1 g	1.36 ± 0.26 e
SS	CuNPs	8.12 ± 0.87 ef	4.21 ± 0.74 hi	2.98 ± 0.36 def	8.31 ± 1.64 e	7.42 ± 1.1 ef	4.78 ± 0.62 de	23.64 ± 4.1 e	5.26 ± 0.43 gh	0.78 ± 0.12 fg	25.26 ± 2.24 e
(30%FC)	SeNPs	8.93 ± 0.89 def	4.81 ± 0.86 ghi	3.54 ± 0.89 def	9.23 ± 1.35 e	8.73 ± 0.4 de	5.03 ± 0.55 d	27.53 ± 3.05 e	6.64 ± 0.89 g	0.84 ± 0.17 fg	29.24 ± 3.55 e
	CuNPs + SeNPs	9.21 ± 0.75 def	5.16 ± 0.96 gh	4.09 ± 0.87 cde	11.25 ± 2.62 e	9.35 ± 1.54 de	5.75 ± 0.91 cd	39.32 ± 2.81 d	7.67 ± 1.02 fg	1.04 ± 0.22 ef	39.42 ± 3.86 e
Significance
D		**	**	**	**	**	**	**	**	**	**
NPs		*	**	**	NS	**	*	**	**	*	*
D × NPs		*	*	**	*	*	**	*	*	**	**

Note: Values represent the means ± standard errors of three independent replications (n = 3). Different letters within the same column indicate significant differences at p < 0.05 and non-significant differences as p > 0.05 among the treatments, according to Duncan’s multiple range test. NS = non-significant; * = significant at 0.05, ** = significant at 0.01 levels.

). The agronomic indicators of strawberry plants under WW, MD, and SD conditions were CK < CuNPs < SeNPs < CuNPs + SeNPs, showing that moderate application of both CuNPs and SeNPs promoted growth of plants, and the combination of the two treatments was the most effective.

The statistical analysis revealed that the agronomic traits of strawberry plants were significantly lower under SD than WW treatment, with plant height, shoot dry weight, root dry weight, root FW, number of leaves, leaf area, number of inflorescences, and firmness reduced by 69.59%, 67.87%, 79.92%, 75.10%, 63.79%, 76.50%, 87.91%, and 68.18% under SD compared to WW treatment, respectively. Spraying SeNPs, CuNPs, and their combination promoted strawberry-plant growth at all drought-stress levels to different degrees. The aboveground dry weight, belowground dry weight, leaf area, number of inflorescences, and fruit hardness of strawberry plants sprayed with CuNPs and SeNPs were significantly higher for WW, MD, and SD treatments compared to CK.

3.2. SeNPs’ and CuNPs’ Effect on Leaf Photosynthetic Pigments under Drought Stress

Chlorophyll a, chlorophyll b, and total chlorophyll contents decreased with increasing drought-stress levels and were reduced by 61.47%, 69.85%, and 63.65% under SD compared to WW treatment, respectively (Figure 1). The chlorophyll a, chlorophyll b, and total chlorophyll contents were increased by spraying CuNPs and SeNPs and both in combination compared to CK treatment at all stress levels. Chlorophyll a content was increased by 24.78% and 67.98% under WW and SD, respectively, under the SeNPs and CuNPs + SeNPs treatments, as compared to the CK treatment (Figure 1a); and under MD spraying of CuNPs, SeNPs, and CuNPs + SeNPs, the chlorophyll b content increased by 72.64%, 83.08%, and 97.01%, respectively, compared with CK treatment (Figure 1b). For WW, MD, and SD treatments, total chlorophyll content was increased by 33.15%, 78.48%, and 90.09%, respectively, under the CuNPs + SeNPs treatment compared to the CK (Figure 1c).

3.3. SeNPs’ and CuNPs’ Effect on Leaf Chlorophyll Fluorescence Parameters of Strawberry Leaves under Drought Stress

In terms of the chlorophyll fluorescence parameters, the F_o value increased, and the F_v, F_m, and F_v/F_m values decreased with the increased drought stress (Figure 2). Spraying CuNPs + SeNPs was the most effective in increasing chlorophyll fluorescence parameters under MD and SD compared to the WW treatment. For the SS treatment, the F_o, F_v, and F_v/F_m values increased by 81.37%, 442.86%, and 1396.70%, respectively, with CuNPs + SeNPs spraying compared to CK; under the MD and SD treatments, the F_m contents increased by 29.44% and 92.38%, respectively.

3.4. SeNPs’ and CuNPs’ Effect on Photosynthetic Characteristic Parameters of Strawberry Leaves under Drought Stress

The P_n, C_i, T_r, and G_s of strawberry leaves were lower for the MD and SD than the WW treatment (Figure 3). Compared with their counterparts in CK, CuNPs, SeNPs, and their combined spraying improved the abovementioned photosynthetic parameters overall for the WW, MD, and SD treatments (Figure 3). The T_r and G_s were significantly higher for all treatments than for CK and were increased by 250% and 350%, respectively, with combined spraying of CuNPs + SeNPs compared to CK (Figure 3a,b). For the WW and MD treatments, C_i was significantly higher compared to CK, with C_i increased by 13.64% and 31.90% under combined spraying of CuNPs + SeNPs, respectively (Figure 3c). There was no significant difference in C_i among treatments under SS conditions; and there was no significant difference in P_n among treatments for WW, MD, or SD conditions (Figure 3d).

3.5. SeNPs’ and CuNPs’ Effect on Strawberry Quality under Drought Stress

Under SD conditions, the anthocyanin, total phenolic compounds, and total flavonoids contents increased by 214.55%, 130.95%, and 125.71%, respectively, compared with WW (Figure 4). On the contrary, the vitamin C content decreased by 63.51% under the SS compared to the WW condition (Figure 4a). Under control conditions, spraying of CuNPs, SeNPs, and their combination increased the vitamin C, anthocyanins, total phenolic compounds, and total flavonoids contents. Under the WW conditions, the vitamin C content was significantly higher (37.04%) under the combined CuNPs + SeNPs spaying compared to the CK treatment under DS and SS conditions. Under WW and SD conditions, the anthocyanin content under combined CuNPs + SeNPs was increased by 85.59% and 42.24%, respectively, compared with the CK treatment (Figure 4b); under DS conditions, the anthocyanin content increased with the spraying of CuNPs, SeNPs, and the combination by 58.26%, 88.39%, and 118.90% (Figure 4b). Under WW conditions, the application of CuNPs, SeNPs, and their combination significantly increased the total phenolic content by 67.86%, 75.00%, and 101.19% over the CK treatment, respectively (Figure 4d). Under WW and MD conditions, there was no significant difference in the total flavonoid content under different NP treatments; under SD conditions, the total flavonoid content under combined CuNPs + SeNPs spraying was significantly increased by 29.96% compared with CK (Figure 4d).

3.6. SeNPs’ and CuNPs’ Effect on Water Content under Drought Stress

The water content of strawberry plant leaves decreased with the increase of drought, and the spraying of CuNPs, SeNPs, and their combination significantly increased the water content under WW by 38.50%, 48.52%, and 77.55%, respectively, and under MD conditions by 107.14%, 118.87%, and 194.61%, respectively, compared with CK (Figure 5). The leaf water content of strawberry plants was increased by 237.02% and 368.32% under SD conditions with the spraying of SeNPs and CuNPs + SeNPs, respectively, compared with CK.

3.7. SeNPs’ and CuNPs’ Effects on MDA Content and Antioxidant Enzyme Activities of Strawberry under Drought Stress

Compared with the strawberry plants grown under WW conditions, the MDA content increased significantly with the increase in the degree of drought stress (Figure 6). Under WW and MD conditions, spraying CuNPs, SeNPs, and their combination effectively reduced the MDA content, but with no significant difference in MDA content among treatments; under SS conditions, the MDA content under spraying CuNPs, SeNPs, and their combination was reduced by 23.21%, 24.43%, and 37.52%, respectively, compared with CK.

As shown in

Table 2. Effect of foliar application of nanoparticles containing selenium and copper on the enzymatic antioxidants in strawberry plants under drought-stress conditions.

Treatments		SOD (Unit·mg−1 prot)	POD (Unit·mg−1 prot)	CAT (Unit·mg−1 prot)
Drought (D)	NPs (mg·L−1)
WW	CK	0.59 ± 0.07 e	0.38 ± 0.06 e	43.78 ± 5.77 e
(100% FC)	CuNPs	0.58 ± 0.08 e	0.4 ± 0.05 de	47.76 ± 3.32 de
	SeNPs	0.59 ± 0.08 e	0.42 ± 0.05 de	49.08 ± 3.95 de
	CuNPs + SeNPs	0.61 ± 0.07 e	0.46 ± 0.04 de	53.76 ± 4.77 d
DS	CK	0.73 ± 0.14 de	0.53 ± 0.094 cd	67.86 ± 5.36 cd
(60%FC)	CuNPs	0.8 ± 0.13 de	0.5 ± 0.06 cde	60.53 ± 4.19 cd
	SeNPs	0.84 ± 0.11 de	0.49 ± 0.03 cde	57.87 ± 4.6 d
	CuNPs + SeNPs	1.08 ± 0.25 cd	0.74 ± 0.07 c	75.91 ± 5.7 c
	CK	0.86 ± 0.16 bc	0.82 ± 0.08 b	97.29 ± 11.37 bc
SS	CuNPs	0.96 ± 0.19 abc	0.94 ± 0.05 b	104.76 ± 17.29 b
(30%FC)	SeNPs	1.10 ± 0.16 ab	1.02 ± 0.12 ab	107.88 ± 18.85 b
	CuNPs + SeNPs	1.41 ± 0.12 a	1.18 ± 0.13 a	126.98 ± 24.51 a
Significance
D	**	**	**	**
NPs	*	*	*	*
D × NPs	**	*	**	**

Note: Values represent the means ± standard errors of three independent replications (n = 3). Different letters within the same column indicate significant differences at p ≤ 0.05 and non-significant differences as p > 0.05 among the treatments, according to Duncan’s multiple range test. * = significant at 0.05, ** = significant at 0.01 levels.

, CAT, SOD, and POD activities increased with the increasing drought-stress level (Table 2). Under MD and SD conditions, CAT activity under CuNPs + SeNPs spraying increased by 47.95% and 63.95% compared to CK treatment, respectively. Under SD conditions, CuNPs, SeNPs, and their combination spraying were more effective than water spraying in enhancing SOD activities by 14.64%, 24.39%, and 43.90% compared with CK, respectively, and POD activities by 7.68%, 10.88%, and 30.52%.

3.8. PCA, Correlation, and Cluster Analysis

The 30 indicators were transformed using the affiliation function method and then factor-analyzed to extract with eigenvalues greater than 1, and a total of two components were extracted. As can be seen in Figure 7, strawberry plant morphology, yield, quality, and physiological and biochemical parameters were classified into two principal component axes (PC1 and PC2), which accounted for 85.54% of the total variance and reached the principle of 80%, which could better explain the original independent variables. Most of the studied traits were categorized as PC1, with a higher proportion of variance (75.22%), and PC2 represented only 9.99% of the variance. The principal component loading matrix showed that PC1 was dominated by the effect of F_v, CO₂, fold yield, T_r, G_s, and fruit hardness, followed by P_n, fruit hardness, P_n, number of flowers and fruits, plant height, leaf area, vitamin C, root fresh weight, F_m and F_m/F_v, shoot dry weight, root fresh weight, water content, chlorophyll a, and chlorophyll b, which mainly represent agronomic traits and photosynthetic parameters. The second principal component was dominated by the effect of MDA, followed by POD, SOD, total flavonoids, F_o, total phenolics, CAT, and anthocyanins, mainly representing antioxidant activity and the nutritional quality.

Strawberry plant yield and growth indexes were significantly positively correlated with photosynthetic parameters (p < 0.01) (Figure 8). Vitamin C was highly significantly negatively correlated with F_o and oxidative enzyme indexes and highly significantly positively correlated with chlorophyll a, chlorophyll b, total chlorophyll, Tr, C_i, P_n, and G_s. Atcy, TPC, and TFC were negatively correlated with photosynthetic parameters and positively correlated with oxidative enzyme indexes. Water utilization was highly and significantly positively correlated with yield and growth indexes, significantly negatively correlated with oxidase indexes, and positively correlated with photosynthetic parameters (except F_o).

Thirty indicators were clustered into one category according to CA (Figure 8). Among them, chlorophyll a, chlorophyll b, RDW, NI, SFW, yield, C_i, Tv, Po, WUE, LA, total chlorophyll, Fv/Fm, RFW, PHT, Vc, NFP, Tr, Gs, SDW, and Fm were clustered into class I. Class I was characterized by photosynthetic parameters; and class II included SOD, F_o, POD, TFC, TPC, CAT, Atcy, and MDA, mainly including antioxidant enzyme activities and nutritional quality indicators.

4. Discussion

In the present study, the application of CuNPs and SeNPs under drought stress significantly increased the amount of aboveground and belowground dry matter accumulated in strawberry plants, indicating that the application of CuNPs and SeNPs under drought conditions is potentially desirable. Compared with the control under normal water-holding conditions, all agronomic traits of strawberry under drought stress were significantly reduced, and these traits were enhanced by the application of CuNPs and SeNPs, and their combined application had the most significant effect on strawberry plant growth.

Significant reductions in growth parameters were reported for different species, such as tomato [34], olive [35], lettuce [36], and barley [37], under drought conditions. On the one hand, this might be due to the reduction in water content resulting in reduced cell division in meristematic tissues and, thus, stunted leaf growth. On the other hand, under drought stress, the reduction in water directly affects the biochemical process of photosynthesis, which in turn leads to reduced plant yield. The drought resistance and quality of plants can be improved by the appropriate application of nano-beneficial elemental substances, and it has been shown that 10 mg·L⁻¹ SeNPs significantly increased the contents of protein, soluble sugar, and carotenoids in tealeaves compared with the control [38]. In this study, the spraying of SeNPs or CuNPs was able to alleviate the negative effects of drought stress on strawberry plants (Table 1), which may be attributed to the fact that Cu and Se, as essential plant trace elements, have direct and indirect roles in the physiological processes of plants [39]. Nanomaterials on the surface of plant cells affect plant physiology and ultimately stabilize the basal cellular metabolism, thereby mitigating the effects of adversity on the plant [40].

Chlorophyll is the main pigment for photosynthesis in plants, which is involved in the absorption, transfer, distribution, and conversion of light energy. Se can affect plant chlorophyll synthesis by regulating the synthesis of two enzymes, 5-aminolevulinic acid dehydratase (ALAD) and cholesterogen deaminase (PB-GD). SeNPs can promote chloroplast synthesis by enhancing the activity of these two enzymes, thereby enhancing the photosynthetic capacity of strawberries. In this study, spraying CuNPs and SeNPs significantly alleviated the drought-induced decreases in chlorophyll a, chlorophyll b, and total chlorophyll content, which helped to improve the photosynthetic pigment content and, thus, ensure the photosynthesis of strawberry plant leaves. However, there were some differences in the effects of CuNPs and SeNPs on chlorophyll a, chlorophyll b, and total chlorophyll levels, which may depend on the physical properties of the nanomaterials themselves: the material properties, dimensions, and preparation processes determine the characteristics of the charge and free energy on their surfaces [41].

As the physiological basis of biomass formation, photosynthesis can provide substrates and energy for plant growth and development, and about 90% of dry matter is converted through photosynthesis [42]. However, drought conditions can affect photosynthetic performance. In this study, drought stress overall reduced the P_n, T_r, and C_i of strawberry plant leaves, and the factors leading to the decrease in P_n were mainly classified as stomatal and non-stomatal limitations under adverse stress conditions, and vice versa, by the decrease in the photosynthetic activity of teardrop cells [14]. The increased photosynthetic activity of the plant with the addition of Cu and Se can prevent plant damage from environmental stress and promote photosynthesis [43], consistent with our findings. Yang et al. (2021) found that the factors affecting P_n under mild drought stress were mainly stomatal limitation, whereas the factors affecting Pn under DS and SS stress were mainly non-stomatal [44]. In our experiment, the spraying of CuNPs and SeNPs increased the P_n of strawberry plant leaves under drought stress, and C_i, T_r, and G_s also increased significantly, indicating that CuNPs and SeNPs regulated the opening and closing of stomata and thus increased the P_n of strawberry plant leaves.

Chlorophyll fluorescence parameters are important indicators for evaluating the level of photosynthesis and its efficiency, and the combined application of CuNPs + SeNPs was more effective in increasing F_o, F_m, and F_v than spraying SeNPs and CuNPs alone. Nanoparticles are closely related to plant photosynthetic pigments, which protect chloroplast structures from severe oxidative damage, such as disruption of granule and matrix lamellae, and increase photosynthetic pigment biosynthesis by protecting chloroplast enzymes [45,46]. The chlorophyll fluorescence parameter, F_v/F_m, of strawberry plant leaves was reduced under the DS compared with the WW condition, while F_v/F_m was significantly increased by CuNPs and SeNPs treatments compared with CK, indicating that CuNPs and SeNPs can enhance photochemical responses. Chen et al. (2011) showed that the addition of appropriate amounts of nanomaterials can increase the F_v/F_m of rice under drought conditions, consistent with our findings, which may be because Cu and Se themselves are catalytic substances for major proteins in phytochemical and energy metabolism [47].

The increase in polyphenolic compounds under conditions of stress is related to the genetic structure of the plant and the environment in which it grows. Anthocyanins are phenolic compounds consisting of a large number of secondary metabolites with antioxidant properties [48]. Drought stress reduced strawberry fruit firmness, which was increased by spraying CuNPs and SeNPs under WW, MD, and SD conditions. This was likely due to the induction of ethylene production in the fruit under drought stress, which affected fruit firmness by regulating the expression of genes and enzymes involved in cell wall reactions [49]. In addition, drought had a strong effect on the nutritional indicators of strawberry fruits. Anthocyanins are phenolic compounds consisting of a large number of secondary metabolites with antioxidant properties [50]. The increase in polyphenolic compounds under conditions of stress is related to the genetic structure of the plant and the environment in which it grows. Ascorbic acid is an organic acid, and under drought stress, plant respiration increases, and the content of ascorbic acid, which plays the role of a substrate, decreases; the addition of appropriate Cu and Se increased the ascorbic acid content of the fruit.

Applied exogenously, Se can play an important role in improving the tolerance of plants to environmental stresses by increasing enzymatic antioxidant enzyme activities and maintaining photosynthetic organ properties in rapeseed (Brassica napus), wheat (Triticum aestivum), and rice (Oryza sativa) [51,52,53]. NPs can increase the antioxidant enzyme activity in plants and mitigate the loss of plants from the external environment [54], while the appropriate concentration of Se can increase the Se protein content in plants, so that Se exists in the form of the organic state and will promote the synthesis of certain essential amino acids, which will increase the protein content [55]. Under different environmental stress conditions, the presence of elemental Se induces an increase in antioxidant enzyme activity with the increase in assimilated products, thereby modulating the negative effects of plant stress and favoring plant growth. On the one hand, Se promotes plant growth, probably by increasing starch content in chloroplasts, and due to its antioxidant properties, Se protects cell membranes from lipid peroxidation [5]. On the other hand, exogenous Se application induced the expression of antioxidant defense-related genes in maize and ramie plants, which increased SOD, CAT, and ascorbate peroxidase activities, and ultimately improved their drought tolerance [4,56,57]. These results suggest that the Se- and Cu-mediated enhancement of antioxidant defense is one important mechanism to protect plants from drought oxidative stress.

While 93% of conventional ionic CuSO₄ applied to leaves is washed off with water after application on citrus leaves, 98% of the Cu in CuO NPs is retained under the same conditions. Furthermore, the Cu leaching from the leaves treated with nanoparticulate Cu forms (Cu(OH)₂, CuO, CuO, and Cu₂O-coated silica NP, or Cu²⁺ sorbed on graphene oxide) was mainly ionic (>75%), demonstrating that the nanostructures were better retained on the leaves than Cu ions [58]. Other work on Cu-based NPs has shown that the particle size distribution remains relatively constant over time and persisted at the leaf surface, supporting the assertion that metal and metal oxide NP species adhere to leaves better than ionic forms of metal and can present a higher foliar retention [59]. The ability of nanoparticles to attach to the leaves is affected in a variety of ways: in addition to the CuNP surface properties, such as charge and hydrophobicity, the NP adhesion is regulated by the affinity between the functional groups of the NPs, which can be linked to the interfacial functional groups (mainly methylene) by hydrogen or covalent bonding, as well as electrostatic or hydrophobic interactions [60]. The leaf surface is rich in specific compounds, including glucosides and proteins (hydroxyl, aldehydes, carboxylic, and amine groups) [61], which also facilitate the adsorption of nano-fertilizers. In addition, nano-fertilizers are associated with the microstructure of the strawberry-leaf surface: (1) strawberry leaves are densely packed on shortened stems, with a large leaf area, high water evaporation, and high humidity on the leaf surface; and (2) the leaf surface cuticle is relatively thin, and leaf stomata and trichomes are conducive to the adsorption of NPs.

At the sensing and signaling level, metal nanoparticles can act as signaling molecules to modulate plant responses to environmental signals. They have the ability to activate specific signaling pathways, including those involved in stress responses, nutrient uptake, and hormone signaling [62,63]. Moreover, metal nanoparticles have been shown to induce post-translational modifications of proteins, such as phosphorylation, acetylation, and ubiquitination, which can alter protein stability, activity, and localization. These modifications are critical for regulating various cellular processes, including hormone signaling, stress responses, and plant growth regulation [62,64]. The future need to understand the complex molecular interactions between metal nanoparticles and plants is crucial to increase the full potential in crop productivity and agricultural sustainability [65].

SeNPs is an effective antioxidant that can scavenge free radicals in the body and protect cells from oxidative damage. CuNPs also has some antioxidant capacity, but its antioxidant effect is mainly enhanced by synergizing with selenium, which improves the antioxidant capacity of cells and protects the health of the organism. In agriculture, CuNPs and SeNPs can be used as plant growth promoters to enhance the disease resistance of plants, promote plant growth, and increase crop yield. CuNPs can promote photosynthesis and increase the chlorophyll content of plants, while SeNPs can improve the antioxidant capacity of plants and protect plant cells from environmental stress. SOD, POD, CAT, and Vc are important in mitigating the drastic effects of drought stress in the strawberry. In conclusion, the combination of the two can capitalize on their respective advantages and enhance the overall effect.

5. Conclusions

Our study concluded that the foliar spraying of CuNPs and SeNPs is an effective strategy to improve drought tolerance in strawberries. The beneficial effects of CuNPs and SeNPs on the growth performance of the strawberry under different drought-stress conditions can be attributed to the (1) protection of photosynthetic pigments and enhancement of photosynthetic capacity, (2) activation of antioxidant system and effective maintenance of reactive oxygen species homeostasis, and (3) improvement of fruit quality by increasing the water use efficiency and enhancing the accumulation of root biomass and fruit biochemical compounds. The application of SeNPs alone was superior to that of CuNPs alone, and the combination of the two was the most effective. In conclusion, the application of nanomaterials provided significant protection for strawberry plants under drought stress, highlighting the promise of nanomaterials in agriculture.

Future in-depth research is needed in the following three areas: (1) In addition to pot experinment under controlled conditions, field trials could help to understand the potential applications of these advanced nanoparticles in agriculture under changing environmental conditions. (2) The potential mechanisms of nanoparticle-crop interactions need to be studied and explored in depth. (3) Toxicity evaluations of most nanomaterials have been limited to simple surface toxicity, and systematic studies of the biological effects of nanoparticles and their toxicity mechanisms are needed in the future.