Saline–Alkali Tolerance Evaluation of Giant Reed (Arundo donax) Genotypes Under Saline–Alkali Stress at Seedling Stage

Abstract

Soil salinization and alkalization are serious global challenges that adversely affect crop growth and yield. In this study, six genotypes of giant reed (Arundo donax) seedlings (LvZhou_No.1, LvZhou_No.3, LvZhou_No.6, LvZhou_No.11, LvZhou_No.12 and LvZhou_Var.) originating from different regions of China and Rwanda were utilized as experimental materials. This study aimed to investigate the physiological and biochemical responses of various genotypes to saline–alkali stress and to identify stress-tolerant resources. A mixture saline–alkali solution with a molar ratio of NaCl: Na₂SO₄: NaHCO₃: Na₂CO₃ = 1:1:1:1 was prepared at three concentrations (75, 150 and 225 millimolar (mM)) for a 7-day pot experiment. Growth and physiological indices were measured at the seedling stage, and salt tolerance was evaluated accordingly. The results indicated the following: the growth indices were significantly reduced across seedlings of all genotypes when the concentration of stress exceeded 150 mM (p < 0.05). There was no significant difference in chlorophyll content (SPAD value) and maximum photochemical efficiency of PS II (F_v/F_m) with increasing saline–alkali stress. However, the photosynthetic rate (P_n), stomatal conductance (G_s) and transpiration rate (T_r) exhibited decreasing trends, reaching their lowest levels at 225 mM. In contrast, the intercellular CO₂ concentration (C_i) value decreased to its lowest at 150 mM but increased at 225 mM. Relative electrical conductivity (REC) and the contents of malondialdehyde (MDA), proline (Pro) and soluble sugar (SS) increased progressively with higher stress concentrations. The activities of superoxide dismutase (SOD), peroxidase (POD) and catalase (CAT) were significantly enhanced at stress concentrations above 150 mM. The saline–alkali tolerance of A. donax seedlings was comprehensively evaluated using principal component analysis and membership function analysis based on 15 parameters. The results indicate that P_n, T_r and G_s are effective physiological indicators for assessing saline–alkali tolerance of A. donax seedlings. The six genotypes were ranked for saline–alkali tolerance as follows: LZ_No.1 > LZ_No.11 > LZ_No.12 > LZ_Var. > LZ_No.3 > LZ_No.6. This indicates that LZ_No.1 shows the highest resistance to saline–alkali stress, whereas LZ_No.6 is the most severely affected, classifying it as a salinity-sensitive genotype. In conclusion, LZ_No.1 exhibits robust saline–alkali tolerance and represents a valuable germplasm resource for improving saline–alkali tolerance in A. donax propagation. The results not only support the development of resilient plants for saline–alkali environments but also offer insights into the mechanisms of salinity tolerance.

1. Introduction

Against the backdrop of global climate change, abiotic stresses such as strong winds, drought, soil salinization and extreme temperatures (including heat and cold stress) present significant challenges to plant growth. Among these, soil salinization stands out as a major environmental issue, leading to the loss of arable land, diminished crop yields and a decline in quality. The buildup of salt and alkalis in the soil is a significant environmental issue resulting from natural processes or improper human activities, and it represents a global ecological challenge [1]. Globally, there are 1.5 billion hectares of arable land, of which 340 million hectares, or approximately 23%, are affected by salinization and alkalization [2]. Normally, soil salinization can be classified into two types: salinization and alkalinization [3]. Salinization typically leads to the accumulation of neutral salts, such as NaCl and Na₂SO₄, which induce a cascade of detrimental effects in plants, including osmotic stress, ion toxicity, oxidative stress, nutrient imbalances and disruptions in metabolic processes. Such physiological disturbances significantly impair plant growth and development, ultimately reducing agricultural productivity and ecosystem stability. In contrast, alkali stress is characterized by similar adverse effects arising from the presence of excessive alkaline salts, such as NaHCO₃ and Na₂CO₃, and is accompanied by elevated pH levels. Currently, saline–alkali land predominantly exists in the form of mixed saline–alkali conditions, which can inflict irreversible damage on plants at any stage of their growth and development [4]. This damage manifests in various forms, including inhibition of seed germination inhibition [5], retardation of growth [6] and reduction in leaf area [7], among others. Additionally, saline and alkaline stress can lower the osmotic potential of the soil solution, disturb the soil’s physical and chemical properties and impair the biological functions of plants, thereby hindering nutrient absorption [8]. When plants are subjected to saline–alkali stress, excessive Na⁺ can occur. If Na⁺ reaches a critical concentration within plant tissues, it disrupts ionic balance, induces cytotoxic effects and causes osmotic imbalance at the tissue, cellular and subcellular levels. This leads to physiological drought and oxidative stress, which subsequently impair respiration and photosynthesis. As a result, photosynthetic rates are reduced, ultimately inhibiting plant growth [9]. Moreover, saline and alkaline stress lead to the accumulation of toxic metal ions, which trigger the excessive production of ROS in plants (reactive oxygen species). This, in turn, results in the disruption and disintegration of the cell membrane system [10]. Furthermore, when plants are exposed to saline–alkaline stress, a high pH value further inhibits ion absorption. As a result, plant roots cannot fully absorb the metal ions required for synthesis and metabolism, which in turn causes nutritional stress, leads to root nutrient deficiency, impairs root function and eventually results in plant death. Research [11] has demonstrated that the simultaneous presence of saline and alkaline stress exerts a synergistic and more detrimental effect on plant growth and physiological processes compared to the individual impacts of either salt or alkali stress alone. This interaction amplifies the negative effects, as alkali stress exacerbates the already harmful conditions induced by salt stress. Consequently, mixed stress poses a significantly greater challenge to plant health and productivity, emphasizing the need for comprehensive strategies to address the combined stresses rather than treating them as isolated factors [12]. In response to saline–alkali stress, plants have evolved a range of adaptive mechanisms to mitigate its adverse effects. These include alterations in growth patterns, such as reduced plant height and an increased root–shoot ratio, as well as physiological adjustments like osmotic regulation, ion exclusion and ion compartmentalization. Additionally, plants employ hormonal modulation, reactive oxygen species (ROS) scavenging and the activation of antioxidant defense systems to enhance their resilience under such challenging conditions [13,14].

At present, the improvement of plant resistance to saline–alkali stress is the key to reclaiming saline–alkaline lands, reducing the negative effects of salinity on plants and supporting sustainable agriculture and environmental health. Developing saline–alkali tolerance plant varieties enables crop cultivation in challenging conditions, restores soil productivity and lessens the ecological impact of salinity. Chen et al. [15] highlighted that the leaf potassium-to-sodium (K⁺/Na⁺) ratio and stomatal density are reliable indicators for screening salt-tolerant rice varieties, which provided valuable criteria for breeding programs aimed at improving salinity tolerance in rice; Al-Khayri et al. [16] focused on GABA’s physiological, biochemical and molecular mechanisms in enhancing plant resilience, highlighting its potential as a natural bio-stimulant to improve crop performance and sustainability in saline soils. The result of a review discussing the mechanisms by which PGPB improve stress tolerance in plants emphasized that PGPB induce the plant’s antioxidant system, maintain water balance and regulate ion homeostasis, contributing to enhanced salt tolerance [17]. The studies mentioned above offer promising solutions for improving plant resilience and reducing the detrimental effects of environmental stressors. These strategies enhance agricultural resilience while contributing to environmental sustainability and global food security [18]. Given the presence of genetic variations and diverse salt-responsive mechanisms, identifying salt-tolerant and salt-sensitive plant varieties represents a critical objective in plant propagation programs. This process not only facilitates the development of resilient crops suitable for saline–alkali environments but also provides valuable insights into the underlying mechanisms of salinity tolerance [15].

Giant reed (Arundo donax), a species belonging to the Poaceae family, is known as a novel energy crop, given its high biomass yield and low input requirements, that can be cultivated in degraded and marginal lands [19]. Its robust canes can grow to impressive heights of 8 to 10 m, with a diameter ranging from 3 to 4 cm, supported by deep-reaching roots that can extend up to 5 m into the soil [20]. The plant is further characterized by its long, lanceolate leaves, which can reach lengths of up to 1 m. Due to its large biomass, strong resilience to abiotic stresses and high capacity for comprehensive utilization, A. donax has been widely applied in various fields, including bioenergy development [21], edible and medicinal mushroom cultivation [22], feed processing [23], fiberboard production [24], sustainable construction material [25] as well as soil improvement and ecological restoration [26,27]. Although A. donax is a C₃ plant, its photosynthetic assimilation, biomass yields and potential rates are comparable to those of C₄ species [28]. With the growing interest in using A. donax as a biomass source for biofuels [29,30], further research into the basic biology, physiology, biochemistry, genetics and ecology of this species is necessary, particularly under abiotic stress conditions. Cultivating A. donax in saline–alkali regions, without occupying arable land resources required, offers significant potential to alleviate food security challenges and improve ecological environments. Consequently, studying the physiological responses and salt tolerance mechanisms of A. donax is critical for maximizing its utility in such areas.

Previous studies have predominantly focused on single salts as indicators of plant stress responses [31,32]. However, in saline soils, salinity and alkalinity often coexist, and the impact of solely salt stress fails to capture the complex interactions that occur in real-world conditions. To overcome this limitation, this study introduces an innovative approach by applying a mixed saline–alkali stress treatment to A. donax seedlings. To ensure a comprehensive evaluation of salt tolerance, growth and physiological indices were systematically compared across genotypes under mixed saline–alkaline stress conditions. Principal component analysis (PCA) was employed to identify key traits contributing to stress resilience, while membership function analysis (MFV) quantified and ranked the saline–alkali tolerance of each genotype. This integrated approach provides a thorough evaluation by capturing both the complexity of the stress environment and the adaptive responses of the genotypes, thus facilitating the identification and selection of highly salt-tolerant varieties. The aim of this study is to offer a deeper understanding of how A. donax responds to combined saline–alkaline stress, thereby facilitating more effective selection and breeding of stress-tolerant varieties.

2. Materials and Methods

2.1. Plant Materials and Growth Conditions

The experiment was conducted in the greenhouse of Fujian Agricultural and Forestry University, Fuhzou City, Fujian Province, China, in 2023. (Latitude 26°5′8″ N, longitude 119°14′13″ E, altitude 31.4 m). Based on previous research findings [33], six A. donax genotypes seedlings were collected and renamed from the National Engineering Research Center of Juncao Technology, as follows (

Table 1. Sources of A. donax materials.

Genotype’s Name	Code Number	Location	Source and Country Name
Lvzhou_No.1	LZ_No.1	Latitude 26.056579° N, longitude 119.180505° E,	Fujian Province, China (Asia)
Lvzhou_No.3	LZ_No.3	Latitude 25.870612° N, longitude 118.927801° E,	Fujian Province, China (Asia)
Lvzhou_No.6	LZ_No.6	Latitude 29.651045° N, longitude 94.360232° E,	Tibet Autonomous Region, China (Asia)
Lvzhou_No.11	LZ_No.11	Latitude 32.061551° S, Longitude 118.791562° E,	Jiangsu Province, China (Asia)
Lvzhou_No.12	LZ_No.12	Latitude 1.9706° S, Longitude 30.1044° E,	Kigali, Rwanda (Africa)
A. donax var. Versicolor	LZ_Var.	Latitude 26.082995° N, longitude 119.237382° E,	Fujian Province, China (Asia)

):

Healthy and robust rhizomes of six A. donax genotypes were collected and cut into the same size with sterilized tools, after which the surface was disinfected with 1% potassium permanganate solution for 5 min and carefully rinsed with sterilized distilled water and then immersed for 30 min. Subsequently, the rhizomes were planted in gallon-sized pots filled with 3.3 pounds of a substrate composed of loamy soil and sand in a 1:1 (v/v) ratio. The plants were cultivated in a greenhouse environment with an average daytime temperature of 25 °C, not exceeding 30 °C and a nighttime temperature above 14 °C. The greenhouse maintained a light transmittance of 70% and an average relative humidity of 75%, ensuring optimal growth conditions for the experiment. Pots were watered and managed regularly for one month. Plants exhibiting uniform growth within each genotype were selected as subjects for the saline–alkaline stress treatment.

Referring to Zhu et al. [34,35] and considering the situation of saline and alkaline land in northwest China [36], three concentrations, 75, 150 and 225 millimolar (mM) of salt solutions, were prepared using two neutral salts (NaCl and Na₂SO₄) and two alkaline salts (NaHCO₃ and Na₂CO₃) with a molar ratio of 1:1:1:1. Each treatment comprised 6 pots. Regular irrigation ceased two days prior to the initiation of the saline–alkaline treatment. A 100 mL mixed saline–alkaline solution of varying concentrations was applied to each pot until a small amount of leachate was observed at the base. Irrigation with the designated mixed solution was conducted daily during the morning hours (9:00–11:00 AM). Pots were placed on plastic trays to prevent leakage, and any spilled solution was returned to the respective pot once the substrate exhibited slight drying. Distilled water was used as the control treatment, with an equivalent volume applied. Routine maintenance of the seedlings was carried out throughout the experimental period. After seven days of treatment, a subset of seedlings was randomly sampled from each group for biomass determination, and the third fully expanded functional leaf was collected for the analysis of physiological and biochemical parameters.

2.2. Chemicals

Table 2. The list of chemicals used in the current study.

Name of Chemicals	Cas No.	Manufacturer	Country
Potassium permanganate	7722-64-7	Sinopharm Chemical Reagent Co., Ltd	Shanghai China
Sodium chloride	7647-14-5	Shanghai Macklin Biochemical Technology Co., Ltd.	Shanghai China
Sodium sulfite anhydrous	7757-83-7	Shanghai Macklin Biochemical Technology Co., Ltd.	Shanghai China
Sodium bicarbonate	144-55-8	Shanghai Macklin Biochemical Technology Co., Ltd.	Shanghai China
Sodium carbonate anhydrous	497-19-8	Shanghai Macklin Biochemical Technology Co., Ltd.	Shanghai China

presents a detailed overview of the chemicals used in the current study.

2.3. Morphological Measurements

Plant height was measured as the vertical distance from the stem base to the growing point using a ruler. Following the measurement, the shoots and roots were thoroughly rinsed with tap water to remove any adhering substrate. The aboveground and belowground portions were then separated, placed in cowhide bags and dried in an oven (DHG-9240A, Ningbo Jiangnan Instrument Factory, Ningbo, China). The samples were dried at 105 °C for 30 min, followed by 72 h at 70 °C. Subsequently, the dry weights of the shoot and root fractions were determined using an electronic analytical balance (Sartorius Scientific Instruments Co., Ltd. Beijing, China). The root–shoot ratio was determined as follows:

$${\displaystyle \frac{\mathrm{R}\mathrm{o}\mathrm{o}\mathrm{t}}{\mathrm{S}\mathrm{h}\mathrm{o}\mathrm{o}\mathrm{t}}} \left(\mathrm{\%}\right)={\displaystyle \frac{\mathrm{D}\mathrm{r}\mathrm{y} \mathrm{m}\mathrm{a}\mathrm{s}\mathrm{s} \mathrm{o}\mathrm{f} \mathrm{u}\mathrm{n}\mathrm{d}\mathrm{e}\mathrm{r}\mathrm{g}\mathrm{r}\mathrm{o}\mathrm{u}\mathrm{n}\mathrm{d} \mathrm{p}\mathrm{a}\mathrm{r}\mathrm{t}}{\mathrm{D}\mathrm{r}\mathrm{y} \mathrm{m}\mathrm{a}\mathrm{s}\mathrm{s} \mathrm{o}\mathrm{f} \mathrm{a}\mathrm{b}\mathrm{o}\mathrm{v}\mathrm{e}\mathrm{g}\mathrm{r}\mathrm{o}\mathrm{u}\mathrm{n}\mathrm{d} \mathrm{p}\mathrm{a}\mathrm{r}\mathrm{t}}}\times 100.$$

(1)

2.4. Determination of Photosynthetic Parameters

A sunny day was selected for determination, and the gas exchange parameters such as net photosynthetic rate (P_n), stomatal conductance (G_s), transpiration rate (T_r) and intercellular CO₂ concentration (C_i) of the first fully unfolded leaf were measured from 9 AM to 3 PM using the CIRAS-3 portable photosynthesis system (PP systems, America). The measured light intensity (PPFD) was 1200 µmol·m⁻²·s⁻¹, and the CO₂ concentration was 400 µmol·mol⁻¹; the RGBW control was set as follows: red (90), green (0), blue (5), white (5). The relative humidity of the standard blade chamber was maintained at 70%.

The maximum photochemical efficiency of PS II (F_v/F_m) was measured by a Pocket PEA plant efficiency analyzer (Hansha Scientific Instruments Co., Ltd., Taian, China). The chlorophyll content was measured using a SPAD meter (502Plus, Konica Minolta (China) Investment Ltd., Shanghai City, China), and the measurement results were averaged. A total of three replications of all the parameters were conducted.

2.5. Determination of the Relative Electrical Conductivity

The relative electrical conductivity (REC) was measured using a DDSJ-308F conductivity meter (INESA Scientific Instrument Co., Ltd, Shanghai, China) based on the method outlined by Ghalati et al. [37]. Approximately 0.1 g of fresh leaf tissue was immersed in 10 mL of deionized water and incubated at 25 °C for 30 min, after which the initial electrical conductivity (R₁) was recorded. The samples were subsequently boiled in water for 60 min, and the final electrical conductivity (R₂) was measured. REC, representing cell membrane permeability, was calculated using the following equation:

$$\mathrm{R}\mathrm{E}\mathrm{C} \left(\mathrm{\%}\right)={\displaystyle \frac{\mathrm{R}1}{\mathrm{R}2}}\times 100.$$

(2)

2.6. Measurement of Malondialdehyde (MDA) Levels

The content of malondialdehyde (MDA) was determined using an MDA content assay kit according to the manufacturer’s protocol (Beijing Solarbio Science & Technology, Co., Ltd. Beijing, China. Catalog numbers BC0025) [38]. In total, 0.1 g of shoot tissues from each A. donax seedling subjected to saline–alkali stress or control conditions were harvested and homogenized in liquid nitrogen. Samples were extracted using an appropriate extraction buffer, and the homogenates were centrifuged at 8000× g for 10 min at 4 °C. Then, the operating solution was added to the supernatant and incubated at 100 °C for 30 min. After that, the solution was cooled in an ice bath at room temperature and then centrifuged at 10,000× g for 10 min. The absorbance of each sample is measured at 532 nm and 600 nm by Microplate Readers (SpectraMax M2, Molecular Devices (Shanghai) Co., Ltd., Shanghai, China). The MDA content (nmol/g FW) was calculated using the following formula:

$$\mathrm{M}\mathrm{D}\mathrm{A} \mathrm{c}\mathrm{o}\mathrm{n}\mathrm{t}\mathrm{e}\mathrm{n}\mathrm{t} (\mathrm{n}\mathrm{m}\mathrm{o}\mathrm{l}/\mathrm{g})={\displaystyle \frac{\left[\Delta A\times V_{final}\right]÷\left(ϵ\times d\right)\times {10}^9}{\left(W\times V_{sample}÷V_{extract}\right)\times F}}$$

(3)

where ΔA is the absorbance change (ΔA = ΔA532 − ΔA600); V_final is the final volume of the reaction mixture; ϵ is the molar extinction coefficient; d is the path length; W is the weight of the sample; V_sample is the volume of the sample; V_extract is the volume of the extract; and F is a correction factor.

2.7. Measurement of Osmotic Adjustment Compounds

The proline (Pro) content was determined using a proline content assay kit (Beijing Solarbio Science & Technology Co., Ltd., Beijing, China. Catalog number BC0295). Approximately 0.1 g of shoot tissue was weighed and mixed with 1 mL of extraction buffer. The samples were then homogenized in an ice bath to ensure uniformity. The homogenates were subjected to oscillatory extraction in a boiling water bath for 10 min. Following extraction, the solution was centrifuged at 10,000× g for 10 min at room temperature to separate the soluble components. The supernatant was collected, cooled and prepared for analysis. Pro content was quantified by comparing the absorbance of the sample to a calibration curve generated from standard solutions.

The soluble sugar (SS) content was determined using a soluble sugar content assay kit (Beijing Solarbio Science & Technology Co., Ltd., Beijing, China. Catalog number BC0035). Approximately 0.1 g of the sample was weighed and 1 mL of distilled water was added to prepare a homogenate. The mixture was then transferred into a capped centrifuge tube and incubated in a boiling water bath for 10 min, ensuring the cap was securely fastened to prevent any loss of water. Following incubation, the sample was centrifuged at 8000× g for 10 min at room temperature. The supernatant was collected into a 10 mL test tube, and the volume was adjusted to 10 mL with distilled water. The operating solution was added to the supernatant and the solution was thoroughly mixed and incubated at 95 °C for 10 min. The absorbance was measured at 620 nm, and the SS content was determined by comparing the absorbance of the sample with a calibration curve derived from standard solutions.

2.8. Measurement of Antioxidant Enzyme Activities

The activities of key antioxidant enzymes, including cellular superoxide dismutase (SOD), peroxidase (POD) and catalase (CAT), were analyzed following the protocols provided by commercial antioxidant enzyme assay kits (Beijing Solarbio Science & Technology Co., Ltd., Beijing, China. Catalog numbers BC0175, BC0095, and BC0205). Briefly, 0.1 g of shoot tissues from A. donax seedlings subjected to saline–alkali stress or control conditions were harvested and homogenized in liquid nitrogen. Enzymes were extracted using an appropriate extraction buffer, and the homogenates were centrifuged at 10,000× g for 10 min at 4 °C. The resulting supernatant was used for subsequent enzymatic activity measurements. Enzymatic activities were quantified using a microplate reader, and the activity units were defined as specified in the assay kit instructions [39].

2.9. Salt Tolerance Evaluation

The principal component analysis (PCA) and the membership function values (MFVs) were calculated via a total of 15 salt tolerance indices (STIs) from six genotypes of A. donax seedlings [40], using the following formula:

$$\mathrm{S}\mathrm{T}\mathrm{I}={\displaystyle \frac{\mathrm{s}\mathrm{t}\mathrm{r}\mathrm{e}\mathrm{s}\mathrm{s}\mathrm{e}\mathrm{d} \mathrm{t}\mathrm{r}\mathrm{e}\mathrm{a}\mathrm{t}\mathrm{m}\mathrm{e}\mathrm{n}\mathrm{t} \left(\mathrm{S}\mathrm{T}\right)}{\mathrm{c}\mathrm{o}\mathrm{n}\mathrm{t}\mathrm{r}\mathrm{o}\mathrm{l} \left(\mathrm{C}\mathrm{K}\right)}}$$

(4)

where stressed treatment (ST) represents the mean value of a single trait under saline–alkali stress, and the control (CK) represents the mean value of a single trait under non-treatment.

For the calculation for PCA, we referred to the method of Li et al. [41], using the comprehensive assessment of salt tolerance; the comprehensive index for salt tolerance is expressed as P (j) = F₁X₁ + F₂X₂ + ⋯ +F_jX_j, where i = 1, 2, …n and i = 1, 2, …, n. Here, P (j) represents the composite index value for the j-th entity. Fj denotes the eigenvalue associated with the eigenvector of a specific indicator, and Xj refers to the standardized value of the corresponding individual indicator. The calculation method of the MFV was as follows:

R (X_i) = (X_i − X_min)/(X_max − X_min)

(5)

and the value of the inverse membership function was the following:

R (X_i) = 1 − (X_i − X_min)/(X_max − X_min)

(6)

Here, X_i denotes the specific measured value of the salt tolerance index for a given genotype, while X_max and X_min represent the highest and lowest values observed among all tested materials, respectively.

2.10. Statistical Analysis

Data were initially processed using Microsoft Excel 2010 and subsequently analyzed with SPSS 23.0 for ANOVA and Duncan’s multiple range tests. Two-way ANOVA was conducted to examine the individual and interactive effects of genotype and salinity. Principal component analysis (PCA) was utilized to condense 15 salt tolerance indices (STIs) from six A. donax genotypes, streamlining the evaluation process. Statistical significance was determined at p < 0.05, with additional thresholds set at p < 0.01 and p < 0.001. Pearson correlation and PCA were performed and visualized using Origin 2022. Saline–alkali tolerance was evaluated by comparing the mean MFVs across genotypes, where higher averages indicated stronger tolerance [42].

3. Result

3.1. Impact of Varying Salinity Levels on Plant Height and Root–Shoot Ratio Across Different Genotypes of A. donax at Seedling Stage

After 7 days of saline–alkali stress, the phenotypic characteristics of the six genotypes of A. donax exhibited varying responses to the increasing intensity of stress. However, no evidence of stress-induced leaf chlorosis, wilting or desiccation was observed in any of the genotypes. The growth height (H) of the six genotypes of A. donax seedlings is shown in Figure 1a. Compared to the CK, there were no significant differences in the 75 mM condition, and the height of LZ_No.1 was slightly higher than the control. However, the growth indices of seedlings from most genotypes declined significantly when the mixed saline–alkali concentration exceeded 150 mM, suggesting that this threshold represents a critical tipping point beyond which saline–alkali stress exerts severe inhibitory effects on seedling development (p < 0.05). Plant nutrient uptake and shoot growth and development can be inhibited by saline and alkaline stress; thus, in severe cases, plant root development will cease until the complete demise of the entire plant. Figure 1b shows that there were significant differences in the root–shoot ratio (R/S) among genotypes under stress. The R/S ratio of LZ_No.1 initially decreased under low concentrations of mixed saline–alkali stress but subsequently increased, reaching its peak at 225 mM. And the R/S ratio of LZ_No.11 followed a similar trend to that of LZ_No.1, but at lower concentrations, there was no significant difference between the treatment and control groups. In contrast, LZ_Var. exhibited a peak R/S ratio at 150 mM but experienced a sharp decline at 225 mM. These findings highlight the differential stress tolerance mechanisms among the tested genotypes. Furthermore, the R/S ratio was significantly influenced by the interaction between salinity and genotype, underscoring the critical role of genetic factors in mediating plant responses to saline conditions (

Table 3. Single- and two-factor analysis of variance.

Parameters	Salinity (S)		Genotypes (G)		S × G Interaction
	F	p	F	p	F	p
H	26.505	***	26.505	***	0.701	ns
R/S	3.544	*	4.571	**	3.338	**
Pn	45.821	***	9.666	***	1.070	ns
Tr	76.942	***	5.075	**	1.126	ns
Ci	24.694	***	5.783	***	1.245	ns
Gs	78.733	***	3.927	**	1.254	ns
SPAD	1.689	ns	6.638	***	1.149	ns
Fv/Fm	3.174	*	3.318	*	1.176	ns
REC	5.945	**	1.593	ns	0.147	ns
SOD	53.762	***	13.909	***	12.484	***
POD	58.358	***	31.378	***	19.153	***
CAT	12.769	***	42.907	***	6.603	***
MDA	94.051	***	1.951	ns	25.091	***
Pro	378.064	***	47.002	***	17.493	***
SS	29.127	***	12.557	***	1.989	ns

Note: Asterisks (*, **, ***) denote statistically significant differences at p < 0.05, p < 0.01 and p < 0.001, respectively, while ‘ns’ signifies no statistically significant difference. H: plant height; (R/S): root–shoot ratio; P_n: net photosynthetic rate; T_r: transpiration rate; C_i: intercellular CO₂ concentration; SPAD: relative value of leaf chlorophyll content; F_v/F_m: maximum photochemical efficiency of PSII; REC: relative electrical conductivity; SOD: superoxide dismutase; POD: peroxidase; CAT: catalase; MDA: the malondialdehyde content; Pro: proline content and SS: soluble sugar content.

).

3.2. Effects of Saline–Alkali Stress on Photosynthesis Parameters

The relative value of the leaf chlorophyll content (SPAD value) had a high correlation with the chlorophyll content in the plant [43]. In this study, there was no significant difference in SPAD value and maximum photochemical efficiency of PS II (F_v/F_m) of leaves under different concentrations of mixed saline–alkali stress in A. donax plants (Figure 2a,b). Nonetheless, the P_n, G_s and T_r of seedlings across the six genotypes demonstrated a progressively declining trend with increasing levels of saline–alkali stress, attaining their minimum values at a concentration of 225 mM. Relative to the control group, the C_i of the six genotypes declined to its lowest point at 150 mM but exhibited an increase at 225 mM. (Figure 2c–f).

3.3. Effects of Saline–Alkali Stress on MDA Content and REC

The MDA content and REC are reliable indicators of the extent of damage to plant cell membranes under abiotic stress conditions. In LZ_No.1 and LZ_No.11, both REC and MDA content exhibited an increasing trend as the mixed saline–alkali stress intensified, reaching their maximum levels at 225 mM (Figure 3a,b). In contrast, the MDA content of the other four genotypes increased significantly compared to the control at 150 mM but showed a decline at 225 mM. This differential response suggests varying degrees of membrane stability and stress tolerance among the genotypes, highlighting the complex physiological adaptations of plants under saline–alkali stress. The results indicate that saline–alkali stress caused notable damage to the cell membranes of all four seedling genotypes, though LZ_No.1 and LZ_No.11 demonstrated remarkable resilience under such stress conditions. Additionally, the interaction between salinity and genotype significantly influenced the MDA content, further highlighting the complex relationship between environmental stress and genetic tolerance (Table 3).

3.4. Effects of Saline–Alkali Stress on Osmotic Adjustment Substance

The accumulation of Pro and SS content was a defensive behavior induced by plants under saline–alkali stress, and it was also a signal that plants were subjected to abiotic stress. The overall trend of Pro and SS content in the six genotypes of giant reed seedlings increased progressively in response to the increasing concentrations of saline–alkali stress from 0 to 225 mM (Figure 3c,d). Pro content significantly increased under 225 mM compared with CK (p < 0.01) and reached the maximum. Compared to the control, the SS content significantly increased at 150 mM in most A. donax genotypes, except for LZ_Var., which remained unchanged across stress levels [42]. Moreover, the Pro content was markedly influenced by the interaction between salinity and genotype, emphasizing the complex interplay between environmental stress and genetic adaptation (Table 2).

3.5. Impact of Saline–Alkali Stress on Antioxidant Enzyme Activity

Reactive oxygen species (ROS) could lead to cell membrane dysfunction and apoptosis as by-products of osmotic stress and ionic toxicity. Excessive accumulation of ROS in plants is exacerbated by the reactive oxygen metabolism under abiotic stress.

As shown in Figure 4a–c, the SOD, POD and CAT activity of LZ_No.6 at 75 mM showed the highest increase and then decreased when the plants were exposed to 150 mM and 225 mM concentrations, while the activities of LZ_No.1 and LZ_No.11 increased and were much higher than that of other four genotypes when the stress concentration exceeded 150 mM. These findings suggest that the two genotypes exhibited enhanced antioxidant enzyme activities (SOD, POD and CAT), indicating a strong tolerance to salt stress. Notably, no significant difference was observed in the CAT activity of LZ_No.3 and LZ_Var. compared to the control. Moreover, the activities of SOD, POD and CAT were significantly influenced by the interaction between salinity and genotype, highlighting the complex relationship between environmental stress and genetic factors in mediating antioxidant responses (Table 3).

3.6. Comprehensive Evaluation of Salt Tolerance

3.6.1. Correlation Analysis

In this study, the interdependencies among key physiological and biochemical parameters were examined with correlation analysis to understand the underlying mechanisms driving plant responses to saline–alkali stress. As shown in Figure 5, the correlation coefficients between P_n and G_s and P_n and T_r were 0.884 and 0.848, respectively, indicating that P_n was strongly positively correlated with G_s and T_r, with the correlation coefficients closer to 1, as expected. However, Pro exhibited a negative correlation with T_r, P_n and G_s, with correlation coefficients of −0.825, −0.776 and −0.756, respectively. Furthermore, REC showed a significant negative correlation with P_n, T_r and G_s, further highlighting the inverse relationships between these parameters under saline–alkali stress.

3.6.2. Principal Component Analysis

Principal component analysis (PCA) was used as the statistical method for the comprehensive evaluation of the salt tolerance of plants, which could synthesize multiple indicators to evaluate the salt tolerance of plants. Eigenvalue and contributions in PCA are the main basis for selecting principal components. PCA was performed on a total of 15 dependent variables across the six genotypes of A. donax seedlings exposed to varying concentrations of saline–alkali stress (

Table 4. Eigenvalues, contribution and loading matrix of components of six genotypes of A. donax seedlings under different concentrations of saline–alkali stress.

Index	75 mM				150 mM				225 mM				Mean
	PC1	PC2	PC3	PC4	PC1	PC2	PC3	PC4	PC1	PC2	PC3	PC4	PC1	PC2	PC3	PC4
H	0.95	0.147	−0.232	0.145	−0.39	0.794	−0.392	−0.246	−0.285	0.817	0.418	−0.225	0.092	0.586	−0.069	−0.109
R/S	−0.483	0.833	−0.001	0.026	0.528	−0.618	−0.288	0.28	0.169	0.477	0.798	0.189	0.071	0.231	0.170	0.165
Pn	0.567	0.631	0.512	0.05	0.719	−0.307	−0.551	0.292	0.962	−0.255	0.027	−0.034	0.749	0.023	−0.004	0.103
Tr	0.766	−0.3	0.191	0.502	0.572	0.769	0.206	−0.196	0.912	−0.113	−0.306	−0.23	0.750	0.119	0.030	0.025
Ci	−0.186	0.661	−0.624	0.169	−0.769	0.03	0.439	0.391	−0.917	0.166	−0.227	0.249	−0.624	0.286	−0.137	0.270
Gs	0.568	0.669	0.068	0.417	0.923	0.274	0.094	−0.182	0.95	0.005	−0.114	−0.29	0.814	0.316	0.016	−0.018
SPAD	0.769	0.554	0.158	−0.278	0.605	0.726	−0.116	0.203	0.525	0.202	0.001	0.815	0.633	0.494	0.014	0.247
Fv/Fm	0.732	−0.253	−0.215	−0.594	0.242	0.56	−0.697	0.36	0.681	−0.406	−0.545	0.274	0.552	−0.033	−0.486	0.013
REC	0.532	0.416	−0.584	0.45	0.565	0.51	0.523	−0.381	0.669	0.711	0.033	−0.165	0.589	0.546	−0.009	−0.032
SOD	−0.545	0.786	0.233	−0.019	0.777	−0.382	0.41	0.033	0.207	−0.24	0.801	−0.005	0.146	0.055	0.481	0.003
POD	−0.21	0.075	0.958	−0.129	0.69	0.078	0.295	0.593	0.505	0.717	0.358	0.308	0.328	0.290	0.537	0.257
CAT	−0.793	0.338	−0.487	−0.123	0.771	−0.333	0.523	−0.112	0.159	−0.415	0.868	−0.214	0.046	−0.137	0.301	−0.150
MDA	−0.575	−0.595	−0.287	0.421	0.195	−0.717	−0.629	−0.158	0.908	−0.246	0.199	0.275	0.176	−0.519	−0.239	0.179
Pro	−0.012	−0.825	0.298	0.463	−0.178	0.864	0.103	0.457	−0.051	0.69	−0.554	0.116	−0.080	0.243	−0.051	0.345
SS	−0.495	0.451	0.492	0.446	−0.378	−0.312	0.825	0.278	−0.567	−0.626	0.366	0.383	−0.480	−0.162	0.561	0.369
Eigenvalues	5.358	4.607	2.783	1.735	5.349	4.496	3.174	1.441	6.269	3.385	3.270	1.429	5.659	4.163	3.076	1.535
Contribution/%	35.720	30.712	18.552	11.569	35.658	29.974	21.161	9.606	41.796	22.565	21.797	9.529	37.725	27.750	20.503	10.234
Cumulative Contribution/%	35.720	66.431	84.983	96.552	35.658	65.632	86.793	96.399	41.796	64.361	86.158	95.687	37.725	65.475	85.978	96.213

Note: H: plant height; (R/S): root–shoot ratio; P_n: net photosynthetic rate; T_r: transpiration rate; C_i: intercellular CO₂ concentration; SPAD: relative value of leaf chlorophyll content; F_v/F_m: maximum photochemical efficiency of PSII; REC: relative electrical conductivity; SOD: superoxide dismutase; POD: peroxidase; CAT: catalase; MDA: the malondialdehyde content; Pro: proline content and SS: soluble sugar content.

). According to the rule of eigenvalue > 1, four PCs based on their cumulative contribution > 95% were extracted from all three concentrations, which revealed that the four PCs under three concentrations retained most of the information of the original variables and could reflect the salt tolerance information of different treatment groups well, so these four PCs were selected as the comprehensive indices for salt tolerance evaluation. The mean eigenvalue of PC1 was 5.659 and explained 37.73% of the average differences between salt stress and the control; the traits of P_n, T_r and G_s had high values. The mean eigenvalue of PC 2 was 4.163, and the average contribution rate was 27.75%. The information on H, REC and MDA was mainly synthesized, with H and REC being positive indicators but MDA being a negative indicator. The mean eigenvalues of PC 3 and PC 4 were 3.076 and 1.535, with average contribution rates of 20.50% and 10.23%, respectively, containing the information of Pro, SS and POD. Based on the eigenvalues and principal component matrix, the eigenvectors of the four principal components were calculated and multiplied with the normalized data to obtain the scores (

Table 5. Scoring system matrix and total scoring formula of six genotypes of A. donax seedlings under different concentrations of saline–alkali stress.

Index	75 mM				150 mM				225 mM				Mean
	PC1	PC2	PC3	PC4	PC1	PC2	PC3	PC4	PC1	PC2	PC3	PC4	PC1	PC2	PC3	PC4
H	0.177	0.032	−0.084	0.083	−0.073	0.177	−0.123	−0.171	−0.045	0.241	0.128	−0.158	0.020	0.150	−0.026	−0.082
R/S	−0.090	0.181	0.000	0.015	0.099	−0.138	−0.091	0.194	0.027	0.141	0.244	0.132	0.012	0.061	0.051	0.114
Pn	0.106	0.137	0.184	0.029	0.134	−0.068	−0.174	0.202	0.153	−0.075	0.008	−0.024	0.131	−0.002	0.006	0.069
Tr	0.143	−0.065	0.069	0.289	0.107	0.171	0.065	−0.136	0.146	−0.033	−0.094	−0.161	0.132	0.024	0.013	−0.003
Ci	−0.035	0.144	−0.224	0.097	−0.144	0.007	0.138	0.271	−0.146	0.049	−0.069	0.174	−0.108	0.067	−0.052	0.181
Gs	0.106	0.145	0.025	0.240	0.173	0.061	0.030	−0.126	0.152	0.001	−0.035	−0.203	0.144	0.069	0.007	−0.030
SPAD	0.143	0.120	0.057	−0.160	0.113	0.161	−0.036	0.141	0.084	0.060	0.000	0.570	0.113	0.114	0.007	0.184
Fv/Fm	0.137	−0.055	−0.077	−0.343	0.045	0.124	−0.220	0.250	0.109	−0.120	−0.167	0.191	0.097	−0.017	−0.155	0.033
REC	0.099	0.090	−0.210	0.260	0.106	0.113	0.165	−0.265	0.107	0.210	0.010	−0.116	0.104	0.138	−0.012	−0.040
SOD	−0.102	0.171	0.084	−0.011	0.145	−0.085	0.129	0.023	0.033	−0.071	0.245	−0.004	0.025	0.005	0.153	0.003
POD	−0.039	0.016	0.344	−0.074	0.129	0.017	0.093	0.412	0.081	0.212	0.109	0.216	0.057	0.082	0.182	0.185
CAT	−0.148	0.073	−0.175	−0.071	0.144	−0.074	0.165	−0.078	0.025	−0.122	0.265	−0.149	0.007	−0.041	0.085	−0.099
MDA	−0.107	−0.129	−0.103	0.243	0.037	−0.159	−0.198	−0.109	0.145	−0.073	0.061	0.192	0.025	−0.120	−0.080	0.109
Pro	−0.002	−0.179	0.107	0.267	−0.033	0.192	0.032	0.317	−0.008	0.204	−0.169	0.081	−0.014	0.072	−0.010	0.222
SS	−0.092	0.098	0.177	0.257	−0.071	−0.069	0.260	0.193	−0.091	−0.185	0.112	0.268	−0.085	−0.052	0.183	0.239
Total scoring formula	F = 0.374F1 + 0.318F2 + 0.192F3 + 0.120F4				F = 0.370F1 + 0.311F2 + 0.220F3 + 0.100F4				F = 0.437F1 + 0.236F2 + 0.228F3 + 0.100F4				F = 0.394F1 + 0.288F2 + 0.213F3 + 0.106F4

Note: H: plant height; (R/S): root–shoot ratio; P_n: net photosynthetic rate; T_r: transpiration rate; C_i: intercellular CO₂ concentration; SPAD: relative value of leaf chlorophyll content; F_v/F_m: maximum photochemical efficiency of PSII; REC: relative electrical conductivity; SOD: superoxide dismutase; POD: peroxidase; CAT: catalase; MDA: the malondialdehyde content; Pro: proline content and SS: soluble sugar content.

).

3.6.3. Membership Function Analysis

The proportion of the eigenvalues associated with each principal component relative to the total eigenvalues of the four principal components was utilized as a weight function to derive the total score formula. This approach allowed for the calculation of the comprehensive scores for each genotype, providing a quantitative measure of their overall performance under varying conditions. As shown in

Table 6. Comprehensive scores and ranks of six genotypes of A. donax seedlings with salt tolerance under different concentrations of saline−alkali stress.

No.	75 mM		150 mM		225 mM		Mean
	Score	Ranking	Score	Ranking	Score	Ranking	Score	Ranking
LZ_No.1	0.622	1	0.852	1	0.884	1	0.786	1
LZ_No.3	0.396	4	0.432	5	0.308	5	0.379	5
LZ_No.6	0.102	6	0.377	6	0.274	6	0.251	6
LZ_No.11	0.610	2	0.724	2	0.340	4	0.558	2
LZ_No.12	0.490	3	0.502	3	0.402	3	0.465	3
LZ_Var.	0.323	5	0.438	4	0.459	2	0.407	4

, at 75 mM, the salt tolerance capacities of the six genotypes of giant reed seedlings were as follows: LZ_No.1 > LZ_No.11 > LZ_No.12 > LZ_No.3 > LZ_Var. > LZ_No.6. At 150 mM, the data sequence was as follows: LZ_No.1 > LZ_No.11 > LZ_No.12 > LZ_Var. > LZ_No.3 > LZ_No.6, while the data sequence at 225 mM was LZ_No.1 > LZ_No.11 > LZ_No.12 > LZ_Var. > LZ_No.3 > LZ_No.6.

4. Discussion

Morphological characteristics exhibit varying degrees of alteration when plants are subjected to saline–alkali stress, with their capacity to tolerate and adapt to such adverse conditions being determined by multiple physiological and morphological indices. Previous studies have demonstrated that the degree of growth inhibition increases with rising salt concentrations [44]. Among the most conspicuous phenotypic manifestations of abiotic stress are growth retardation and a reduction in plant height, particularly in the above-ground portions, which, despite being detrimental, also represent an essential adaptive strategy [45]. Observations of six giant reed (A. donax) genotypes under saline–alkali stress revealed that exposure to a low concentration (75 mM) had no significant impact on growth. However, when the concentration exceeded 150 mM, a marked inhibition in growth was observed across all genotypes. The trend in the R/S of LZ_No.1 indicated that under mild stress, LZ_No.1 prioritized aboveground growth to cope with adverse conditions, temporarily reducing the R/S ratio. However, as stress levels exceeded 150 mM, shoot growth was significantly inhibited, prompting the plant to allocate more resources to root development to enhance nutrient and water uptake, resulting in a higher R/S ratio. LZ_No.11 showed a similar trend, though its R/S ratio remained stable under low stress, suggesting balanced growth under mild conditions. In contrast, LZ_Var. reached its peak R/S ratio at 150 mM but sharply declined at 225 mM, indicating that extreme stress levels exceeded its tolerance, causing severe root damage and a disproportionate reduction in root growth compared to shoots. These results underscore the distinct stress response strategies among the genotypes.

The osmotic pressure change induced by increased saline–alkali concentrations can significantly impair plant water absorption. When the osmotic pressure of the soil solution exceeds that of plant cells, plants experience physiological drought, which may ultimately lead to desiccation and mortality [46]. However, plants employ various adaptive strategies to mitigate the effects of abiotic stress through water absorption, utilization and retention. The development and robustness of the root system are critical factors in enhancing stress resistance, as roots serve as the primary sensors of soil moisture. A well−developed root system enhances water uptake and transport, ensuring sufficient hydration to sustain normal physiological functions. Additionally, plants may adjust their biomass allocation by increasing the root–shoot ratio, which minimizes excessive transpiration losses, expands the root system’s reach and ultimately improves water acquisition and retention, thereby supporting overall plant growth under saline–alkali conditions.

In addition to enhancing water absorption, plants adapt to abiotic stress through the synthesis and accumulation of osmoregulatory compounds. A wide range of osmoregulatory substances, including amino acids, soluble sugars, soluble proteins, proline, betaine, organic acids and sugar alcohols, are synthesized within the cytoplasm to maintain cellular homeostasis under stress conditions [47]. Plants can absorb water from the soil to sustain their growth and development when their cellular osmotic pressure exceeds that of the surrounding soil [48]. In the present study, the genotypes LZ_No.1 and LZ_No.11 exhibited adaptive response strategies under progressively increasing saline–alkali stress. These strategies included a reduction in above-ground plant height, a continuous increase in Pro content and an elevated root–shoot ratio, all of which contributed to enhanced stress tolerance. These findings indicate that both genotypes improved their adaptability to saline–alkali environments, aligning with previous studies on the effects of saline–alkali stress on oat cultivars [49]. The SS content of most A. donax genotypes exhibited a significant increase under a mixed salinity stress concentration of 150 mM, except for LZ_Var. This suggests that soluble sugars play a critical role in osmotic regulation and stress adaptation when saline–alkali stress levels exceed 150 mM. In contrast, the SS content of LZ_Var. remained relatively unchanged as the stress concentration increased. This finding indicates that excessive abiotic stress may hinder soluble sugar accumulation in LZ_Var., potentially due to disruptions in metabolic regulation. Furthermore, it is possible that LZ_Var. reallocates energy toward alternative defense mechanisms, such as antioxidant enzyme activity or osmoprotectant synthesis, to mitigate the detrimental effects of severe stress conditions.

Photosynthesis is a complex series of metabolic processes that forms the foundation for the survival of life on Earth. It also plays a critical role in the global carbon and oxygen cycles, serving as a key mechanism for the exchange of these essential gasses in the environment [50]. However, saline–alkali stress may inhibit photosynthesis by reducing the synthesis of photosynthetic compounds, primarily due to its adverse effects on chloroplast content and ultrastructure, photosynthetic pigments, thylakoid membrane integrity, electron transport chains and photosynthetic phosphorylation. These disruptions ultimately compromise the efficiency of the photosynthetic apparatus, thereby limiting plant growth and productivity [51]. Khan et al. [52] have shown that dry matter yield and K⁺ concentration were decreased in two maize varieties under salt stress, and inefficient photochemical efficiency of Photosystem II was caused by the low absorption of water and mineral elements by plants. Previous studies have demonstrated that chlorophyll content in Chenopodium quinoa decreases with increasing salt concentration in saline environments [53]. But, in the present study, no significant differences were observed in the SPAD values and F_v/F_m ratios of the leaves among the A. donax genotypes compared to the control group. This finding suggests that saline–alkali stress did not impair leaf photosynthesis by reducing chlorophyll content. These results are consistent with previous research, further supporting the notion that giant reed exhibits a degree of resilience to saline–alkali stress in terms of photosynthetic efficiency [54,55]. The reduction in G_s indicates a diminished capacity of the plants to assimilate CO₂ from the environment, which directly impacts carbon assimilation efficiency. Consequently, the synthesis of photosynthetic products is reduced, further compromising the plants’ overall physiological performance. This response highlights the adverse effects of saline–alkali stress on key photosynthetic parameters and underscores the importance of understanding genotypic variations in stress tolerance [44]. Under high-saline–alkali stress conditions, the decline in P_n and G_s in the leaves of LZ_No.1 was less pronounced compared to the other genotypes. This suggests that it exhibits enhanced resilience, likely due to its ability to maintain higher organic matter production under stress conditions. Previous studies have similarly indicated that certain genotypes can mitigate the adverse effects of saline–alkali stress through improved physiological and biochemical adaptations. In this study, the significant differences in P_n, T_r and G_s between treated and untreated plants indicate that saline–alkali stress has a profound impact on the gas exchange processes in A. donax. Under stress conditions, stomatal closure restricts CO₂ uptake and reduces transpiration, leading to a decline in both P_n and T_r. The observed increase in C_i further suggests that limited gas exchange is the primary constraint on photosynthesis [56]. In contrast, the minimal variation in SPAD values and F_v/F_m indicates that the photosynthetic apparatus remains functionally stable despite stress exposure. The sustained F_v/F_m values suggest that the primary photochemical reactions within PSII were not significantly impaired, while the unchanged SPAD values imply that chlorophyll degradation did not occur within the experimental timeframe. These findings suggest that while A. donax retains its photosynthetic pigment content and photochemical efficiency under saline–alkali stress, gas exchange processes are more susceptible to stress-induced alterations.

Malondialdehyde (MDA) is commonly utilized as an indicator of membrane lipid peroxidation, reflecting the extent of cellular oxidative damage and the plant’s response to stress. In contrast, REC serves as a measure of the damage to plant cell membranes under stress conditions. Studies have demonstrated that MDA and REC content in the six genotypes increase with higher stress concentrations, indicating that varying levels of salt stress lead to lipid peroxidation of plant cell membranes and cause differential degrees of damage to plant cell structures [57]. The MDA content of LZ_No.1 and LZ_No.11 reached its highest level at 225 mM saline–alkali stress. In contrast, the MDA content of the other four genotypes increased at 150 mM but decreased at 225 mM, suggesting that the membrane systems of these genotypes were severely damaged under higher stress conditions. This observation indirectly indicates that LZ_No.1 and LZ_No.11 exhibit greater salt tolerance compared to the other four genotypes.

When plants are exposed to saline–alkali stress, the metabolic equilibrium of ROS is disrupted, leading to the accumulation of O₂⁻, H₂O₂ and ⁻OH. This imbalance accelerates the process of membrane lipid peroxidation, compromises the integrity of the membrane system and results in the leakage of electrolytes and small organic molecules. Consequently, the homeostasis of cellular material exchange is disturbed, triggering a cascade of physiological and metabolic dysfunctions [58]. To counteract these adverse effects, plants activate their antioxidant enzyme systems, synthesizing enzymes such as superoxide dismutase (SOD), peroxidase (POD) and catalase (CAT). These enzymes play a crucial role in scavenging excess ROS, thereby enhancing the plant’s resilience to stress. Among the six genotypes examined, LZ_No.1 and LZ_No.11 exhibited a more pronounced increase in SOD, POD and CAT activities compared to the other four genotypes. This suggests that salt-tolerant genotypes enhance their ROS-scavenging capacity by synthesizing greater quantities of antioxidant enzymes and other protective compounds, thereby improving their stress tolerance. These findings are consistent with the study conducted by Luo et al. [59].

Saline–alkali stress disrupts the morphological characteristics of plants during the seedling stage, but not all traits are equally effective or reliable for screening tolerance. Identifying and evaluating robust tolerance traits is critical for ensuring accurate and efficient selection. Given the complexity of plant responses to saline–alkali stress, precise trait selection is essential for breeding programs aimed at developing stress-resilient genotypes [60]. To establish a reliable method for evaluating saline–alkali tolerance in A. donax genotypes at the seedling stage, this study used principal component analysis (PCA) and membership function comprehensive evaluation (MFV). The results showed that photosynthetic parameters—specifically P_n, T_r and G_s—are reliable indicators of saline–alkali tolerance. These findings highlight the importance of photosynthetic traits in distinguishing tolerant genotypes and refining selection criteria for breeding programs. Genotypes such as LZ_No.1 and LZ_No.11, which maintain higher P_n, T_r and G_s under stress, exhibit greater tolerance, while more sensitive genotypes like LZ_No.6 show significant declines in these parameters. This aligns with previous studies on Portulaca oleracea [59] and Reaumuria soongorica [60], further supporting the link between these physiological traits and stress tolerance. Additionally, correlation analysis revealed a strong positive relationship between P_n and G_s, as well as T_r.

Most studies on plant salt tolerance have focused on individual salt stress factors. In this study, six genotypes of A. donax seedlings were exposed to saline–alkali stress, and their physiological responses were analyzed, providing insights with potential practical applications. However, in natural environments, saline–alkali stress is highly complex and variable, with soil salinization and alkalization often occurring simultaneously. This study was limited to a single molar ratio of saline and alkaline stress, underscoring the need for further research into the effects of different molar ratios of neutral and alkaline salts. Moreover, plant saline–alkali tolerance is regulated by multiple trait-associated genes, whose expression varies significantly across ecological conditions and developmental stages. Therefore, future research should aim for a more comprehensive evaluation of salt tolerance in different A. donax genotypes, particularly focusing on their physiological and biochemical responses, as well as the regulatory mechanisms of gene networks in saline–alkali soil environments.

5. Conclusions

This study investigated the growth, physiological and biochemical responses of six A. donax genotypes under saline–alkali stress. The primary effects observed included reduced plant height, impaired photosynthesis activity and membrane damage. Notably, chlorophyll content remained stable, indicating that the photosynthetic apparatus was not directly compromised. However, increased MDA and REC levels highlighted lipid peroxidation and oxidative stress. To mitigate these adverse effects, plants activated key defense mechanisms, including an increased root–shoot ratio for enhanced water and nutrient uptake, the accumulation of Pro and SS for osmotic balance, and elevated antioxidant enzyme activity (SOD, POD and CAT) for efficient ROS scavenging. PCA and MFV identified P_n, T_r and G_s as reliable indicators of saline–alkali tolerance. Based on overall tolerance rankings, the genotypes were ordered as follows: LZ_No.1 > LZ_No.11 > LZ_No.12 > LZ_Var. > LZ_No.3 > LZ_No.6; this ranking highlights that LZ_No.1 exhibits the highest resistance to saline–alkali stress, whereas LZ_No.6 is the most severely affected, classifying it as a salinity-sensitive genotype.