Comparative assessment of saline irrigation effects on germination, physiological responses, growth, and yield of durum wheat varieties grown on silty clay soil

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Durum wheat, a staple cereal crucial for food security, is highly sensitive to salinity, particularly during early growth. This study compared responses of two local Moroccan durum wheat varieties, Faraj and Nachit, grown on silty-clay soil under five salinity levels (0.2, 4, 8, 12, and 16 dS m⁻¹) in a randomized complete block design with three replications, aiming to identify tolerance thresholds and characterize physiological and agronomic responses. Key traits measured included germination percentage (PG), germination stress index (GSI), mean germination time (TMG), root length (RL), coleoptile length (CL), plant height, number of leaves, chlorophyll fluorescence (ChlF, Fv/Fm), grain yield (GY), 200-grain weight (200-GW), and straw yield (SY). Results showed PG declined markedly from 8 dS m⁻¹, with ISG decreasing and TMG increasing, indicating delayed germination. Vegetative growth was inhibited with higher salinity, affecting RL, CL, plant height, number of leaves, and ChlF. Both varieties maintained GY up to 8 dS m⁻¹ and SY, 200-GW up to 12 dS m⁻¹, with Nachit exhibiting superior resilience. At 16 dS m⁻¹, yield components declined sharply. Multivariate analyses (PCA and heatmaps) revealed strong correlations between electrical conductivity, Na, and Cl with reduced growth and yield, while K, Ca, and Mg correlated positively with vigor and productivity. These findings highlight the comparative performance of Faraj and Nachit and support their use in breeding programs and irrigation strategies to sustain durum wheat production under saline conditions. Agronomy Durum wheat Saline irrigation Germination Plant growth Yield components Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 1. Introduction Irrigation using saline water is becoming a strategic option to address the growing shortage of freshwater, especially in drylands where water demand is rising due to climatic pressures and demographic expansion. stress and threaten agricultural output and food security [ 1 ]. However, this practice also contributes to soil salinization a critical constraint on crop performance [ 2 , 3 ]. An estimated portion of arable land is already affected by salinity stress, especially in dry regions such as Morocco [ 4 ]. Climate change, combined with shifts in farming practices, continues to degrade soil and water quality, further aggravating these challenges [ 5 ]. Salinity disrupts vital physiological processes in plants, such as nutrient uptake and photosynthesis, resulting in impaired development and significant declines in productivity [ 6 ]. In Morocco, a country marked by arid to semi-arid conditions, salinity affects a substantial area of irrigated land, challenging sustainable agriculture [ 7 – 10 ]. Durum wheat ( Triticum turgidum L. subsp. durum ) is a major cereal crop widely grown in Mediterranean regions, including Southern Europe, North Africa, and West Asia, and constitutes a key source of staple products such as flour, pasta, and semolina [ 11 – 13 ]. It is particularly appreciated for its digestibility and high nutritional value, making it a fundamental component of the human diet [ 14 ]. Nevertheless, its productivity is increasingly constrained by environmental stresses, including irregular rainfall, high temperatures, soil degradation, and salinity [ 8 , 15 ]. Supplemental irrigation is often required under arid and semi-arid conditions to sustain cultivation; however, prolonged use of saline water can worsen soil salinization, disrupt ionic balance, impair cellular functions, and limit plant growth, biomass accumulation, and grain yield, with roots generally showing higher tolerance than aerial parts [ 16 – 22 ]. Increasing competition for water due to urbanization, industrial and service demands, together with declining water quality from overexploitation of marginal sources, further restricts irrigation resources in dryland regions [ 23 ]. Therefore, identifying durum wheat varieties with enhanced salinity tolerance, coupled with innovative management and efficient irrigation strategies, is essential to maintain yields and strengthen agricultural resilience under challenging environmental conditions [ 24 , 25 ]. Salinity imposes a dual stress on plants, initially creating osmotic or water stress that limits root water uptake and reduces leaf expansion, followed by ionic stress due to the accumulation of Na⁺ and Cl⁻ ions, which disrupts ionic balance and accelerates leaf senescence [ 3 , 26 ]. Water stress caused by salinity restricts growth and triggers stomatal closure, impairing photosynthetic efficiency [ 27 ] and affecting nitrogen metabolism [ 28 ]. The ionic stress component further compromises plant metabolism by altering mineral ratios, reducing photosynthetic pigments, especially chlorophyll [ 29 , 30 ], and modifying dry matter composition [ 31 ]. These physiological disruptions not only limit biomass accumulation but also reduce yield potential. Prolonged irrigation with saline water additionally leads to the build-up of soluble salts in soils, increasing electrical conductivity (EC) and sodium adsorption ratio (SAR), while decreasing organic matter and nutrient availability [ 32 ]. Such soil degradation hampers water infiltration, nutrient uptake, and microbial activity, creating an unfavorable environment for plant growth [ 33 , 34 ]. The intensity of these effects is influenced by soil texture, initial salinity, irrigation practices, climate, and cultivar characteristics [ 35 ]. Implementing strategies such as alternating saline and fresh water, controlled leaching, optimized irrigation scheduling, and cultivating salt-tolerant varieties can mitigate the negative impacts of salinity on both soil and crop performance [ 36 – 38 ]. Enhancing salt tolerance in durum wheat, particularly in local cultivars such as Faraj and Nachit, is critical for maintaining stable productivity under saline irrigation conditions. Salinity imposes both osmotic and ionic stresses that disrupt physiological processes, including water uptake, nutrient assimilation, and photosynthesis, ultimately limiting growth, biomass accumulation, and grain yield [ 39 ]. Local durum wheat varieties often exhibit differential responses to salt stress, reflecting inherent genetic variability that can be exploited in breeding and agronomic programs [ 40 – 42 ]. Evaluating growth and yield-related parameters such as plant height, leaf number, biomass, grain yield, and straw yield under controlled saline irrigation allows the identification of cultivars capable of sustaining performance under stress. This approach supports the selection of resilient varieties and contributes to the sustainability of cereal cropping systems in silty-clay soils under dryland conditions, ensuring both crop productivity and long-term soil health [ 34 , 43 ]. Ultimately, targeted evaluation and selection of durum wheat varieties adapted to salinity represent a cornerstone for improving food security and agricultural resilience in arid and semi-arid regions [ 24 , 26 , 44 , 45 ]. This study aims to evaluate durum wheat responses to saline irrigation in silty-clay soils. It compares the performance of two local durum wheat varieties, Faraj and Nachit, across key growth stages, including seed germination, vegetative development, physiological traits, and yield components. By assessing performance under varying salinity levels, the study aims to determine the tolerance thresholds of each variety at different stages, linking early stress responses to final agronomic outcomes. Specifically, the research seeks to (i) quantify the effects of salinity on growth, physiology, and yield, (ii) identify the variety with superior salt resilience, and (iii) establish actionable selection criteria for improved variety choice under saline irrigation. The findings are intended to provide practical recommendations for irrigation management and variety selection, promoting water-use efficiency and sustainable durum wheat production in dry and semi-dry regions. 2. Materials and Methods 2.1. Study Area, soil sampling, and assessment of physicochemical properties This study was carried out at the Regional Center of Rabat of the National Institute of Agricultural Research (INRA), within the Research Unit for Environment and Natural Resource Conservation (URECRN). The experiment was conducted in a greenhouse at this center. The site is located at 34°03′50″ N latitude and 06°50′40″ W longitude, approximately 70 m above sea level, representing the typical coastal area of Rabat, Morocco, characterized by a Mediterranean climate with oceanic influences. Seasonal temperatures range from 12°C in winter to 28°C in summer, with an annual rainfall of around 400 mm. Soil samples were manually collected from an agricultural field in the Temara region, approximately 30 km south of Rabat. This field was selected for its fine-textured soils, which are particularly prone to salinization and degradation due to irrigation. Samples were taken from the top 0–40 cm soil layer using an auger, as this layer represents the most biologically active and agriculturally important portion of the profile. A composite sample from the 0–20 cm layer was prepared and transported to the soil and water chemistry laboratory at URECRN, INRA, Rabat, for initial physicochemical analysis. The locations of the soil sampling site and the greenhouse experimental setup are shown in Fig. 1 . The assessment of the soil’s physicochemical characteristics was conducted following the procedures and data reported by Manhou et al. (2024) [ 39 ]. Soil samples were collected from the top 0–40 cm layer of a field in the Temara region and subsequently air-dried. The dried samples were spread on trays and left under a drying ramp overnight to stabilize moisture content. Following drying, the samples were sieved to separate particle sizes: material retained on a 2 mm sieve was used for the determination of pH, electrical conductivity (EC), and exchangeable cations (Na, K, Ca, Mg), while finer fractions passing through a 0.2 mm sieve were employed for the analysis of total nitrogen (N), available phosphorus (P), and organic matter (OM). Particle size distribution was determined using the sedimentation method [ 46 ]. Soil pH was measured potentiometrically in a 1:2.5 soil-to-water suspension using a Mettler Toledo Seven Easy-728 pH meter (Mettler Toledo, USA) [ 47 ]. Electrical conductivity (EC) was determined in a saturated soil paste using an Orion 162 conductivity meter (Thermo Fisher Scientific, USA)[ 48 ]. Organic matter (OM) was quantified using the Walkley–Black method [ 49 ]. Cation exchange capacity (CEC) was determined with 1 N ammonium acetate at pH 7 (Sigma, USA) [ 50 ]. Total nitrogen (N) was measured using the Kjeldahl method [ 50 ]. Available phosphorus (P) was extracted with 0.5 M sodium bicarbonate (pH 8.5) and quantified spectrophotometrically with a JENWAY 6405 spectrophotometer (Bibby Scientific, UK) [ 51 ]. Exchangeable potassium (K) and sodium (Na) were measured via flame photometry, whereas calcium (Ca) and magnesium (Mg) were determined using atomic absorption spectrophotometry with a novAA 800 D analyzer (Analytik Jena, Germany) or by complexometric titration with EDTA [ 47 , 52 ]. Chloride (Cl) concentrations were measured colorimetrically after precipitation with silver nitrate (AgNO₃). The soil was characterized as a silty-clay soil, comprising 52.6% clay, 34.3% silt, and 13.1% sand. The soil exhibits an alkaline pH of 7.80 and a low electrical conductivity (EC) of 0.20 dS m⁻¹, indicating non-saline conditions. Organic matter content is 1.33%, and the cation exchange capacity (CEC) is 0.65 cmol kg⁻¹, reflecting limited nutrient retention. Total nitrogen (N) is 0.078%, available phosphorus (P) is 120 mg kg⁻¹, and exchangeable potassium (K) is 229 mg kg⁻¹. The soil exhibited relatively low levels of sodium (Na), calcium (Ca), magnesium (Mg), and chloride (Cl). The initial physicochemical characterization of the soil is presentedin Table 1 . Table 1 Physicochemical properties of the soil prior to the experiment. Parameter Value Unit Granulometry Sand 13.1 % Silt 34.3 % Clay 52.6 % Chemical Properties pH 7.80 - EC 0.20 dS m⁻¹ OM 1.33 % CEC 0.65 cmol kg⁻¹ Macronutrients N 0.078 % P 120 mg kg⁻¹ K 229 mg kg⁻¹ Na 1.50 mg kg⁻¹ Ca 5.20 mg kg⁻¹ Mg 5.00 mg kg⁻¹ Cl 0.20 mg kg⁻¹ 2.2. Plant material, experimental setup, and crop management practices The experiment was conducted using the durum wheat variety Nachit (Triticum turgidum L. var. durum) under controlled greenhouse conditions. Seeds were sown in plastic containers measuring approximately 28 × 21 cm, each lined with a gravel layer at the base to ensure proper drainage. Containers were filled with silty-clay soil representative of the study area, and ten seeds were placed per container to maintain uniform plant density. The selection of the durum wheat variety Nachit was based on multiple agronomic and quality criteria, including adaptability to local agroclimatic conditions, growth cycle duration, yield potential under favorable and semi-arid environments, drought and salinity tolerance, and key quality traits such as protein content, baking quality, and yellow pigment index. These selection criteria are summarized in Table 2 , highlighting the suitability of Nachit for the experimental conditions. A randomized complete design (RCD) with three replicates per treatment was employed, resulting in a total of fifteen containers for the five salinity levels tested: I0 (0.2 dS m⁻¹, freshwater, control), I1 (4 dS m⁻¹), I2 (8 dS m⁻¹), I3 (12 dS m⁻¹), and I4 (16 dS m⁻¹) NaCl. The greenhouse temperature was maintained at 22 ± 1°C using a forced-air evaporative cooling system. Irrigation management followed a staged approach. During the first week, freshwater was applied in fine droplets to minimize seed displacement and ensure uniform emergence. Once seedlings reached approximately 3 cm in height, salinity treatments were initiated, with irrigation three times per week. Each container received 0.5 L per irrigation, maintaining the soil near field capacity without causing leaching or waterlogging. Saline solutions were prepared by dissolving NaCl in tap water to achieve the desired electrical conductivity levels. Nutrient management involved a split nitrogen fertilization scheme totaling 120 kg ha⁻¹, applied in three stages: one-third at sowing using ammonium sulfate (21% N), one-third at stem elongation, and one-third at heading using ammonium nitrate (33% N). Phosphorus and potassium were applied based on soil test recommendations. Pest management included monitoring black aphid infestations and applying Primor DG (Syngenta, Rabat, Morocco) according to integrated pest management (IPM) principles, ensuring crop safety while minimizing environmental impact. Standard agronomic practices, including monitoring of soil moisture and plant nutrient status, were maintained throughout the experiment to ensure optimal growth conditions. Table 2 Key characteristics of the durum wheat variety. Variety Registration Year Breeder / Origin Agroecological Adaptation Yield potentiel (t ha⁻¹) Key Quality Indicators Drought Response Growth Duration (days) Nachit 2018 INRA, Morocco Favorable & Semi-arid areas 5.9 (Favorable), 4.1 (Semi-arid) Protein: 15%; Baking: Good; Seed quality: Good; Yellow index: 27 Tolerant 150 2.3. Germination test and germination indicators The germination and early seedling development of durum wheat varieties Nachit and Faraj were evaluated under controlled greenhouse conditions. Seeds were carefully selected for uniform size, appearance, and soundness, treated with 0.5% sodium hypochlorite for surface sterilization and subsequently rinsed with distilled water. For each treatment, 75 seeds per variety were used, divided into three replicates of 25 seeds each. Seeds were then placed into sterile vessels lined with filter paper, and salinity treatments consisted of a control (0.2 dS m⁻¹ freshwater) and four NaCl concentrations: 4, 8, 12, and 16 dS m⁻¹. Containers were maintained in darkness at approximately 21°C, with germination recorded daily. A factorial design was applied, considering the two varieties and five salinity levels, with three replicates per treatment. This design allowed a precise assessment of the interaction between variety and salinity on germination and early seedling growth. Seedlings were continuously monitored for uniform emergence and early vigor, and moisture was maintained to prevent desiccation. To quantify germination, the following parameters were calculated: Germination Capacity (GC %) : Germination Capacity (GC %): This parameter helps determine the salinity level at which durum wheat seed germination starts to decline. It is calculated by expressing the percentage of seeds that successfully germinate by the end of the test relative to the total seeds sown [ 53 ]: where g is the number of germinated seeds and G is the total number of seeds. Germination percentage (GP %) This parameter indicates the fraction of seeds that have sprouted by a specific day (n), determined by dividing the total seeds germinated up to day n by the initial number of seeds planted. $$\:\text{}\text{}\text{G}\text{P}=\frac{{\text{g}}_{\text{n}}}{\text{N}\text{g}}\times\:100$$ 2 where gn denotes the total seeds sprouted up to day n, Ng refers to the initial seed count, and n indicates the specific day of observation (1, 2, ..., n). Germination speed index (GSI) calculated by tracking seed germination each day and computed using the formula [ 54 ] $$\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\varvec{G}\varvec{S}\varvec{I}=\sum\:_{\varvec{i}=1}^{\varvec{n}}\frac{\varvec{P}\varvec{i}}{\varvec{D}\varvec{i}}$$ 3 where Pi is the number of seeds that germinated on day i, and Di the number of days elapsed since the beginning of the test. Mean Germination Time (MGT ): This parameter indicates the average duration required for seeds to germinate under specific conditions. It was calculated using the formula [ 55 ] : $$\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\mathbf{M}\mathbf{G}\mathbf{T}=\frac{\sum\:_{\varvec{i}=1}^{\varvec{k}}(\varvec{n}\varvec{i}\times\:\varvec{t}\varvec{i})}{\sum\:_{\varvec{i}=1}^{\varvec{k}}\varvec{n}\varvec{i}}$$ 4 Where t_i is the time from day one to the last day of observation, n_i is the number of seeds germinated on day i, and k is the last day of germination. To evaluate the relationship between salinity levels and the mean daily germination percentage (DGP), linear regression analysis was performed. The mean DGP was calculated over 7 days (Day 1 to Day 8) using the following formula: $$\:\text{M}\text{e}\text{a}\text{n}\:\text{D}\text{G}\text{P}=\frac{\text{G}8-\text{G}1}{7}$$ 5 where G8​ and G1 ​ represent the cumulative germination percentages recorded on Day 8 and Day 1, respectively. Measurement of Seedling Length : Seedling Length Assessment: On day 6 of germination, five seedlings were randomly selected from each replicate for each variety and salinity treatment. Radicle and coleoptile lengths were measured using a graduated ruler, keeping seedlings on a moist surface to avoid desiccation. This final measurement provided an accurate evaluation of early growth responses to salinity stress. Figure 2 summarizes the germination test methodology, including seed selection and sterilization, placement on moistened filter paper, application of salinity treatments, and assessment of seedling growth parameters. 2.4. Measurement of Growth Parameters and Chlorophyll Fluorescence under Controlled Conditions All measurements were conducted at key phenological stages of durum wheat, namely tillering, stem elongation, heading, and maturation. Plant height was determined on three representative plants per container by measuring from the stem base to the tip of the uppermost leaf using a vertically oriented graduated ruler, and the mean values were calculated. Leaf number was recorded manually on the same plants at each stage to maintain consistency. The maximum quantum yield of photosystem II (PSII) was assessed on fully expanded leaves using a portable pulse-amplitude modulated fluorometer (OS-30p, Opti-Sciences, USA) equipped with red LEDs (660 nm) delivering a saturating light pulse of up to 6000 µmol photons m⁻² s⁻¹. Leaves were dark-adapted for a minimum of 30 minutes prior to measurement to ensure complete relaxation of PSII reaction centers. Minimum fluorescence (F₀) was determined, and maximum fluorescence (Fₘ) was recorded, allowing calculation of variable fluorescence (F v ) as follows [ 56 , 57 ]: Fv = Fm − F0 (6) The maximum quantum efficiency of PSII was then determined using the following formula: Fv/Fm= \(\:\:\frac{\:\:\:\text{F}\text{m}\:-\:\text{F}0\:\:\:\:\:\:\:\:\:\:}{\text{F}\text{m}}\) 2.5. Yield Component Analysis At the final growth stage, key yield-related traits of durum wheat were carefully assessed. Spikes were hand-harvested to avoid grain loss or damage. Grains were meticulously cleaned to eliminate debris and impurities. For uniformity in weight determination, a representative sample of 200 grains per batch was oven-dried at 105°C for 45 minutes to remove residual moisture and weighed using a high-precision balance (Ohaus, Parsippany, NJ, USA). The total grain count per container was determined with an automated seed counter (Numigral, Villeneuve-la-Garenne Cedex, France). Straw yield was measured as the remaining biomass after threshing, using the same high-precision balance to ensure consistency across treatments. Planting density (PD), considering each container covered 0.04 m², was calculated using the following formula: $$\:\text{P}\text{D}=\frac{\text{T}\text{S}\text{A}}{\text{T}\text{N}\text{P}}$$ where TSA is the total surface area in hectares, and TNP is the total number of plants. In this study, the total number of plants was 250 per hectare. . 2.6. Statistical analysis Statistical analyses were performed using SPSS software, version 25. To assess the effect of different salinity levels on germination parameters of the two durum wheat varieties, analysis of variance (ANOVA) was conducted. This analysis revealed significant effects of salinity treatments on key germination indicators, as well as varietal differences, enabling identification of the variety with the greatest tolerance to saline conditions. When significant differences were detected, a post hoc test was applied to determine which treatments differed statistically. Linear regression analyses were also performed between salinity concentrations and individual germination parameters, in order to quantify the strength and direction of these relationships. In the second phase of the experiment, conducted in a greenhouse, data related to growth parameters, chlorophyll fluorescence, and yield components were analyzed using two- or three-way ANOVA (variety, salinity, and, where applicable, sampling period). This approach allowed evaluation of main effects and interactions among factors. A significance level of 0.05 was adopted. When significant differences were found, Duncan’s post hoc test was used to identify homogeneous groups and perform pairwise comparisons. Additionally, a Principal Component Analysis (PCA) was performed to explore the overall responses of the two varieties to different salinity levels, considering the full set of measured variables. This multivariate analysis facilitated visualization of response patterns, identification of the most influential variables, and examination of correlations among agronomic, physiological, and soil chemical parameters. 3. Results 3.1. Daily germination progress of two durum wheat varieties under varying salinity levels The results indicate a progressive decline in the germination percentage of durum wheat seeds with increasing salinity levels (Fig. 3 ). Under control conditions, with irrigation using freshwater at 0.2 dS m⁻¹, both varieties exhibited excellent germination, reaching final percentages of 98.7% for Faraj and 98.8% for Nachit, indicating highly efficient seedling establishment in the absence of saline stress. Moderate saline irrigation (4 dS m⁻¹) caused a slight reduction in germination, with cumulative percentages of 88.2% for Faraj and 88.4% for Nachit over the eight-day observation period. This suggests that both varieties tolerate low levels of saline water without substantial impairment. At 8 dS m⁻¹, final germination decreased to 75.2% (Faraj) and 75.5% (Nachit), marking the onset of moderate stress. Notably, Nachit consistently demonstrated slightly higher germination than Faraj under these intermediate saline conditions. Severe saline irrigation at 12 and 16 dS m⁻¹ strongly inhibited seedling emergence. Final germination percentages dropped to 47.4% and 40.5% for Faraj, and 47.5% and 40.7% for Nachit, respectively, reflecting reductions of over 50% relative to the control. The daily germination percentage (DGP) analysis provided a detailed view of the germination dynamics of Faraj and Nachit under different salinity levels, highlighting the days on which the differences were most pronounced. Under control irrigation with freshwater (0.2 dS m⁻¹), germination was significantly high, with Faraj and Nachit reaching 25% and 28% on the second day, followed by 80–81% on the fifth day, and culminating at 98.7% and 98.8% on the eighth day.. At moderate salinity (4 dS m⁻¹), germination was significantly reduced, starting at 18–20% on the second day and achieving 65% on the fifth day, with cumulative germination exceeding 88% at the end of the period. Under higher salinity (8 dS m⁻¹), the inhibitory effect became more pronounced. Early germination on the second day was limited to 12–14%, reaching only 42–44% by the fifth day, and ultimately 75.2–75.5% at the end of eight days. Notably, Nachit consistently exhibited slightly higher germination than Faraj at each stage. Severe salinity conditions (12–16 dS m⁻¹) strongly suppressed germination. On the second day, only 8–8.5% of seeds emerged at 12 dS m⁻¹, and 5% at 16 dS m⁻¹. By the fifth day, cumulative germination barely reached 33–35% at 12 dS m⁻¹ and 22–22.4% at 16 dS m⁻¹, ultimately plateauing at 47–47.5% and 40–40.7% on the eighth day. 3.2. Effects of NaCl treatments on germination stress index (GSI) and mean germination time (MGT) in two durum wheat varieties The analysis results regarding the interaction between salinity levels and durum wheat varieties on the germination Stress Index (GSI) and Mean Germination Time (MGT) indicate notable variations depending on the level of saline irrigation for each variety (Table 3 ). For GSI, the highest values were recorded under freshwater irrigation (0.2 dS m⁻¹), with Nachit reaching 11.2 ± 0.14 and Faraj 10.8 ± 0.11. At moderate salinity (4 dS m⁻¹), GSI decreased to 9.5 ± 0.12 for Nachit and 8.9 ± 0.15 for Faraj, while further reductions were observed at 8 dS m⁻¹ (9.0 ± 0.13 and 8.4 ± 0.12, respectively). Severe salinity conditions (12–16 dS m⁻¹) resulted in the lowest GSI values, ranging from 2.5 ± 0.09 to 4.2 ± 0.09.egarding MGT, the shortest germination times were observed under freshwater irrigation, with 2.1 ± 0.05 days for Nachit and 2.3 ± 0.06 days for Faraj. As salinity increased, MGT progressively lengthened, reaching 2.8–4.0 days at moderate levels (4–8 dS m⁻¹) and 5.5–7.2 days under severe salinity (12–16 dS m⁻¹), ANOVA indicated tthat both salinity and variety had highly significant effects on GSI and MGT (p < 0.01). In contrast, the interaction between salinity and variety was not significant for GSI (p = 0.09) and only marginally significant for MGT (p = 0.06). Table 3 Effect of salinity and durum wheat varieties on germination speed index (GSI) and mean germination time (MGT, days). Values are presented as mean ± SE (n = 75, from three sets of 25 seeds). Means followed by different letters within a row are significantly different according to Duncan’s test (p < 0.05). The table also shows the ANOVA results for the effects of salinity, variety, and their interaction. Salinity (dS m⁻¹) Variety Nachit Faraj GSI MGT GSI MGT 0.2 11.2 ± 0.14 a 2.1 ± 0.05 a 10.8 ± 0.11 a 2.3 ± 0.06 a 4 9.5 ± 0.12 ab 2.8 ± 0.07 ab 8.9 ± 0.15 ab 3.1 ± 0.08 ab 8 9.0 ± 0.13 ab 3.7 ± 0.06 b 8.4 ± 0.12 ab 4.0 ± 0.05 b 12 4.2 ± 0.09 c 5.5 ± 0.09 c 3.7 ± 0.11 c 5.9 ± 0.07 c 16 2.8 ± 0.08 d 6.7 ± 0.08 d 2.5 ± 0.09 d 7.2 ± 0.09 d Variable Source GSI Df SS MS F p -value Salinity (S) 4 37.70 9.43 72.20 < 0.01 ** Variety (V) 1 3.40 3.50 26.90 < 0.01 ** (S)× (V) 4 1.10 0.27 2.20 0.09 ns MGT Df SS MS F p -value Salinity (S) 4 43.61 10.80 95.21 < 0.01 ** Variety (V) 1 5.10 5.10 44.52 < 0.01 ** (S)× (V) 4 1.30 0.35 3.01 0.06 ns Df: degrees of freedom; SS: sum of squares; MS: mean square; ns: not statistically significant; ** indicates strong significance (p < 0.01). 3.3. Response of durum wheat root and coleoptile growth to gradual salinity stress Root length (RL) and coleoptile length (CL) of the two durum wheat varieties, Nachit and Faraj, exhibited a gradual decline as NaCl concentrations increased from 0.2 to 16 dS m⁻¹ (Fig. 4 ). At the lowest salinity level (0.2 dS m⁻¹), Nachit showed an RL of 4.53 cm and a CL of 3.86 cm, while Faraj recorded slightly lower values with 4.25 cm and 3.59 cm for RL and CL, respectively. At 4 dS m⁻¹, both varieties experienced a reduction in growth, with RL decreasing to 3.98 cm in Nachit and 3.65 cm in Faraj, and CL to 3.27 cm and 2.94 cm, respectively. Further increases in salinity to 8 dS m⁻¹ resulted in RL values of 2.83 cm for Nachit and 2.51 cm for Faraj, whereas CL decreased to 2.28 cm and 1.96 cm. At 12 dS m⁻¹, RL dropped to 1.87 cm in Nachit and 1.59 cm in Faraj, while CL measured 1.45 cm and 1.22 cm, respectively. Under the highest salinity level of 16 dS m⁻¹, the most pronounced reductions were observed, with RL reaching 1.23 cm in Nachit and 1.04 cm in Faraj, and CL decreasing to 0.91 cm and 0.75 cm, respectively. Overall, the data show a consistent decline in both RL and CL across increasing salinity levels, with Nachit maintaining slightly higher measurements than Faraj at each concentration. 3.4. Relationships between salinity treatments, germination and early seedling growth parameters Linear regression analyses revealed strong relationships between salinity treatments and all measured germination and early seedling growth parameters (Fig. 5). Combining all salinity treatments, germination percentage (GP) exhibited a strong negative correlation with salinity, with the highest determination coefficient observed (R² = 0.94). Similarly, daily germination percentage (DGP) showed a pronounced negative relationship with salinity (R² = 0.96), indicating that increasing NaCl concentrations reduced both the speed and uniformity of germination. The germination speed index (GSI) also declined significantly as salinity increased (R² = 0.90), whereas mean germination time (MGT) was positively correlated with salinity (R² = 0.93), reflecting a prolongation of the germination process at higher salt levels.Early seedling growth parameters, including root length (RL) and coleoptile length (CL), were negatively affected by increasing salinity, with determination coefficients of 0.90 and 0.94, respectively. 3.5. Effects of salinity on plant development, leaf number, and chlorophyll fluorescence (Fv/Fm) in durum wheat Figure 6 illustrates the effects of increasing salinity on plant height, chlorophyll fluorescence (Fv/Fm), and leaf number in durum wheat cultivated on silty-clay soil throughout key vegetative and reproductive stages, including tillering, stem elongation, heading, and maturity. As salinity increased progressively, plant height declined gradually. The tallest plants were observed under control conditions (0.2 dS m⁻¹), measuring 25.02 ± 0.03 cm and 26.10 ± 0.04 cm at tillering for Faraj and Nachit, respectively, reaching maximum heights of 73.40 ± 0.05 cm for Faraj and 75.00 ± 0.06 cm for Nachit at maturity. Under moderate salinity (4 and 8 dS m⁻¹), plant height remained relatively stable during tillering and stem elongation, with Nachit consistently showing slightly higher values than Faraj (23.60 ± 0.05 cm vs. 22.80 ± 0.04 cm at tillering under 8 dS m⁻¹). High salinity (16 dS m⁻¹) at heading and maturity stages caused a more pronounced reduction in height, highlighting the inhibitory effect of elevated salt levels on vegetative growth, with Faraj and Nachit reaching 30.40 ± 0.03 cm and 31.50 ± 0.04 cm at maturity, respectively. Chlorophyll fluorescence (Fv/Fm) decreased progressively with rising salinity, with the largest reductions observed at heading and maturity. Control plants exhibited the highest Fv/Fm values, with 0.704 and 0.675 for Faraj, and 0.781 and 0.750 for Nachit at tillering and stem elongation, respectively. Irrigation with 12 and 16 dS m⁻¹ NaCl significantly reduced Fv/Fm, decreasing from 0.500 to 0.310 in Faraj and from 0.580 to 0.390 in Nachit during heading. At maturity, Fv/Fm declined further to 0.298 in Faraj and 0.319 in Nachit under the highest salinity. Leaf number per plant also decreased progressively with increasing salinity. Under control conditions, Faraj produced 18.00 ± 0.15 leaves at tillering, reaching 62.33 ± 0.28 at maturity, while Nachit developed 19.20 ± 0.12 leaves at tillering and 64.00 ± 0.31 at maturity. At 16 dS m⁻¹, leaf counts were markedly reduced, reaching 13.10 ± 0.10 for Faraj and 14.10 ± 0.09 for Nachit at tillering, and 47.33 ± 0.22 and 49.30 ± 0.20 at maturity, respectively, indicating a strong inhibitory effect of high salinity on leaf development.. 3.6. Evaluation of Yield Components and Salinity Tolerance Limits in Two Durum Wheat Varieties The interaction between durum wheat varieties (Faraj and Nachit) and salinity levels revealed marked differences in grain yield, 200-grain weight, and straw yield depending on the salinity conditions ( Table 4 ) . Table 4 Yield components of Faraj and Nachit durum wheat varieties under varying salinity levels.Values indicated by the same letter within each column are not significantly different at p < 0.05 according to Duncan’s post hoc test. Values in parentheses indicate standard deviations. ANOVA results show the significance of salinity effects. ns: Not significant; *p < 0.05; **p < 0.01; *p < 0.001. Salinity (dS m⁻¹) Variety Grain Yield (t ha⁻¹) 200-Grain Weight (g) Straw Yield (t ha⁻¹) 0.2 Faraj 1.12 (1.80) 67.0 (1.00) 1.24 (1.00) Nachit 1.20 (1.60) 69.5 (0.80) 1.30 (0.90) 4 Faraj 0.70 (15.60) 38.5 (7.60) 1.18 (0.40) Nachit 0.85 (12.50) 42.0 (6.50) 1.25 (0.35) 8 Faraj 0.38 (15.60) 34.6 (1.50) 0.97 (0.10) Nachit 0.55 (12.00) 37.5 (1.30) 1.05 (0.09) 12 Faraj 0.18 (0.20) 29.3 (1.50) 0.80 (0.70) Nachit 0.28 (0.18) 32.0 (1.10) 0.90 (0.60) 16 Faraj 0.16 (0.10) 11.6 (1.50) 0.55 (0.30) Nachit 0.20 (0.08) 15.0 (1.30) 0.60 (0.25) 0.2 4 8 12 16 Mean 1.16 a 68.25 a 1.27 a 0.78 b 40.25 b 1.22 b 0.47 c 36.05 c 1.01 c 0.23 d 30.65 c 0.85 c 0.18 d 13.30 d 0.58 d Yield Parameters Grain Yield (t ha⁻¹) 200-Grain Weight (g) Straw Yield (t ha⁻¹) Variable Source p-Value p-Value p-Value Variety (V) 0.023 * 0.045 * 0.062 ns Salinity (Sa) < 0.001 *** < 0.001 *** < 0.001 *** V × Sa 0.034 * 0.041 * 0.010 ** For grain yield, ANOVA results indicated significant effects of salinity (p < 0.001) and variety (p = 0.023), along with a significant variety × salinity interaction (p = 0.034). The highest yields were observed under control conditions (0.2 dS m⁻¹), reaching 1.20 t ha⁻¹ for Nachit and 1.12 t ha⁻¹ for Faraj. Moderate salinity at 4 dS m⁻¹ led to reductions to 0.85 t ha⁻¹ (Nachit) and 0.70 t ha⁻¹ (Faraj). Yields declined more sharply at 8 dS m⁻¹ to 0.55 t ha⁻¹ (Nachit) and 0.38 t ha⁻¹ (Faraj), with further decreases at 12 dS m⁻¹ to 0.28 t ha⁻¹ and 0.23 t ha⁻¹, respectively. At the highest salinity level (16 dS m⁻¹), grain yield dropped to 0.20 t ha⁻¹ for Nachit and 0.18 t ha⁻¹ for Faraj. Post hoc comparisons using Duncan’s test confirmed four significantly different groups, illustrating Nachit’s superior performance under moderate salinity conditions. For 200-grain weight, significant effects were also detected for salinity (p < 0.001) and variety (p = 0.045), with a notable interaction (p = 0.041). Under control conditions, the highest 200-grain weights were 69.5 g for Nachit and 67.0 g for Faraj. At 4 dS m⁻¹, these values declined to 42.0 g and 38.5 g, respectively. Further reductions occurred at 8 dS m⁻¹ (37.5 g for Nachit and 34.6 g for Faraj) and 12 dS m⁻¹ (32.0 g and 29.3 g). The lowest weights were recorded at 16 dS m⁻¹, with 15.0 g for Nachit and 11.6 g for Faraj. Duncan’s test again confirmed four distinct groups, emphasizing the significant impact of salinity and the consistently better performance of Nachit. Regarding straw yield, salinity significantly affected biomass (p < 0.001), whereas the effect of variety was not significant (p = 0.062); however, the variety × salinity interaction was significant (p = 0.010). Straw yield peaked under control conditions at 1.30 t ha⁻¹ for Nachit and 1.24 t ha⁻¹ for Faraj. Moderate salinity (4 dS m⁻¹) led to slight reductions (1.25 t ha⁻¹ for Nachit, 1.18 t ha⁻¹ for Faraj). At 8 dS m⁻¹, yields decreased to 1.05 t ha⁻¹ (Nachit) and 0.97 t ha⁻¹ (Faraj), and further at 12 dS m⁻¹ to 0.90 t ha⁻¹ and 0.80 t ha⁻¹. The highest salinity (16 dS m⁻¹) caused sharp declines to 0.60 t ha⁻¹ (Nachit) and 0.55 t ha⁻¹ (Faraj). Duncan’s post hoc test identified four distinct groups, confirming a progressive decrease in straw yield with increasing salinity, while Nachit maintained higher values than Faraj under moderate and high salinity conditions. 3.7. Relationships between grain performance and irrigation salinity in durum wheat Across all salinity treatments, salinity concentration was inversely related to the yield traits of durum wheat ( Fig. 7 ) . Grain yield exhibited the strongest response to increasing salinity, with a correlation value of r = -0.95 (p < 0.001), reflecting a very high sensitivity of overall productivity to NaCl stress. Similarly, 200-grain weight was markedly affected, showing a strong inverse relationship with salinity (r = -0.93; p < 0.001), indicating that grain filling and individual grain development are highly impacted by elevated salt levels. Straw yield also declined with increasing salinity (r = -0.87; p < 0.001), although the reduction in vegetative biomass was somewhat less severe than that observed for grain yield and 200-grain weight. 3.8. Heatmap of correlations between soil chemical parameters, growth traits, and yield components in durum wheat. The heatmap of correlations among soil parameters, growth traits, and yield components in durum wheat under increasing salinity levels ( Figue 8) highlighted distinct relationships between the measured variables. EC, Na, and Cl were strongly and positively correlated with each other, while exhibiting significant negative correlations with plant height (Pth), chlorophyll fluorescence (ChlF), number of leaves (NoL), grain yield (GY), 200-grain weight (200-GW), and straw yield (SY). Among yield components, GY and 200-GW displayed a strong positive correlation, and a moderate positive correlation was observed between 200-GW and SY. Potassium (K) was positively and strongly correlated with growth traits (Pth, ChlF, NoL) across all salinity levels, whereas its correlations with yield components were weakly positive. Similarly, calcium (Ca) exhibited strong positive correlations with vegetative traits, while correlations with GY, 200-GW, and SY were slightly negative under higher salinity. Magnesium (Mg) showed moderate positive correlations with growth traits and weak positive correlations with GY and 200-GW. Growth traits themselves were consistently positively correlated with yield components, with ChlF exhibiting particularly strong positive correlations with Pth, NoL, and GY. Number of leaves (NoL) was positively correlated with GY, 200-GW, and SY, while plant height (Pth) was moderately positively associated with all yield components. 3.9. Principal Component Analysis revealing the relationships among soil chemistry, growth, and yield under salinity. The principal component analysis (PCA) was conducted to explore the relationships among soil chemical properties, growth traits, and yield components of durum wheat under different salinity levels (Fig. 9 ). In this PCA, the observations corresponded to the two durum wheat varieties (Faraj and Nachit) evaluated under five salinity levels (I0, I1, I2, I3, and I4 dS m⁻¹), resulting in a total of ten observation points. Each point represents the combined response of one variety under a specific salinity treatment. To ensure data suitability given the limited number of observations, six key varia-bles were selected: EC, K, Pth, ChlF, GY, and 200-GW. PCA was applied as an explora-tory multivariate tool to visualize associations and identify the most discriminating factors influencing plant performance under saline conditions. The first three principal components had eigenvalues ≥ 1 and together explained 90.33% of the total variation,ensuring a robust representation of the dataset. PC1 (52.42%) represented the performance and yield axis, being strongly and positively as-sociated with Pth, ChlF, GY, and 200-GW. The EC vector was nearly perpendicular to this axis, suggesting that PC1 primarily reflects plant performance rather than direct salinity intensity. PC2 (25.68%) was mainly influenced by K, which showed a positive association with Pth, indicating its modulatory role in supporting plant growth under salinity stress. Conversely, EC contributed negatively to this axis, reflecting the contrasting behavior of salinity and nutrient availability. PC3 (12.43%) accounted for additional minor variability without altering the main relationships observed along PC1 and PC2Overall, the PCA clearly high-lighted the antagonistic relationship between EC and the performance-related traits (ChlF, GY, and 200-GW). 4. Discussion The germination and early seedling growth stages constitute crucial phases in the plant life cycle and are highly vulnerable to the quality of irrigation water, particularly its salinity.The impact of salt stress on durum wheat during these stages is reflected through several key indicators such as GP, DGP, GSI, MGT, RL, and CL. These early responses are influenced by both genetic predispositions and environmental cues, which together shape the seed’s capacity to initiate growth under optimal conditions. Elevated salinity often disrupts physiological balance, primarily due to ion toxicity and osmotic effects, which hinder water uptake and impair metabolic activity essential for germination and seedling development [ 58 , 59 ]. Salinity induces osmotic stress that restricts water uptake by seeds and causes ionic toxicity, primarily as a result of the high accumulation of Na⁺ and Cl⁻ ions. These conditions disrupt nutrient balance and interfere with essential metabolic processes such as germination, thereby reducing GP and GSI, and ultimately impairing seed vigor and early seedling development. Such physiological and biochemical disruptions have been widely reported in plants under saline conditions [ 60 ], and are particularly well documented in wheat, where salinity constitutes a major constraint during early growth stages [ 61 ]. In this experiment, elevated salinity levels in irrigation water led to a clear reduction in GP for both Faraj and Nachit varieties of durum wheat. However, at 8 dS m⁻¹, both genotypes maintained germination rates above 75%, suggesting a moderate level of salt tolerance, with Nachit exhibiting a slight edge in performance. This better response under intermediate salinity suggests an improved physiological adjustment. Differences in salinity tolerance among genotypes have also been documented in other studies involving tetraploid wheat under controlled conditions, emphasizing the relevance of early-stage physiological indicators for selecting salt-resilient lines [ 62 ]. Comparable variability in salt stress response at the germination stage has also been noted in other cereal species, reinforcing the relevance of early screening methods across diverse crop type, supporting the broader applicability of screening approaches across cereal crops [ 63 ]. Comparatively, studies on sorghum have demonstrated similar trends, where elevated salt concentrations delay germination and reduce seedling growth [ 64 ]. Salinity imposes osmotic and ionic stresses that affect physiological processes such as leaf water potential, stomatal conductance, and evapotranspiration, ultimately reducing crop yield. Wheat is classified among salt-tolerant crops based on soil salinity and water stress indices [ 65 ]. A similar trend was observed for root length (RL) and coleoptile length (CL), both progressively decreasing with increasing saline concentrations in the irrigation water for the Faraj and Nachit varieties. This reduction is widely reported across various species, as roots are the first organs to encounter salinity stress and play a crucial role in water uptake and its transport to aerial parts [ 66 , 67 ]. Moreover, salinity stress often inhibits cell expansion and division, thereby limiting elongation of both roots and coleoptiles in the Faraj and Nachit varieties under increasing saline irrigation. As roots are the first organs exposed to salinity, their early development is crucial for plant adaptation. Root branching and growth are tightly regulated processes involving genetic and hormonal controls that determine root length and function [ 68 ]. The more pronounced reduction in root length compared to coleoptile length observed in this study could be attributed to the higher sensitivity of root tissues to NaCl toxicity. This is consistent with findings in finger millet showing that salinity stress causes significant growth reduction and cellular damage in both coleoptile and root tissues, with roots being particularly affected under increasing NaCl concentrations [ 69 ]. These findings underline the importance of early root development as a critical factor for salinity tolerance in durum wheat and suggest that selecting genotypes with better root growth under saline irrigation could improve crop performance in salt-affected areas [ 70 ]. Overall, irrigation with fresh water promotes the best growth performance in durum wheat. The results indicate that sensitivity to salinity increases as the plant develops. Early growth stages, particularly tillering and stem elongation, are relatively less affected by moderate salinity levels (4–8 dS m⁻¹), with the Nachit variety demonstrating greater tolerance. However, at later stages such as heading and maturity, growth is significantly reduced under high salinity conditions (12–16 dS m⁻¹), although Nachit maintains a slight advantage over Faraj. These findings align with previous studies highlighting that salinity induces osmotic and ionic stress, which limits water uptake and results in more pronounced growth retardation during advanced developmental stages [ 22 , 71 , 72 ]. Moreover, the number of leaves also decreases as salinity levels increase. At 0.2 dS m − 1 , both varieties develop the maximum number of leaves, whereas at 16 dS m⁻¹, a significant reduction is observed. This decline reflects the plants’ limited ability to sustain leaf growth under salt stress, likely due to disruptions in the cell cycle and a reduction in cell division within actively growing tissues, as reported in various plant species [ 73 ]. Additionally, this reduction in leaf number may be associated with ionic imbalances, particularly increased competition between Na + and K + , leading to nutrient deficiencies that restrict foliar development [ 74 ]. Increased salinity was also associated with a marked reduction in chlorophyll fluorescence values (Fv/Fm), reflecting a decline in the efficiency of the photosynthetic machinery, particularly in the functioning of photosystem II. Our results show that plants exposed to low salinity maintain values close to optimal, whereas high NaCl concentrations (12–16 dS m⁻¹) cause a marked decline in Fv/Fm, reflecting substantial photosynthetic stress. This phenomenon is well-documented in the literature; for instance [ 75 ] ,demonstrated that chlorophyll fluorescence is a reliable indicator of salt-induced alterations in photosynthesis, particularly in relation to PSII activity and energy dissipation. Similarly, reductions in the peak photochemical efficiency of photosystem II, measured as Fv/Fm, under high NaCl concentrations have been observed in salt-sensitive genotypes of rice [ 76 ], soybean [ 77 ], and barley, where [ 78 ] reported significant fluorescence changes in response to combined salt and high-light conditions. These findings support the use of chlorophyll fluorescence as a non-invasive and effective screening tool for salinity tolerance. Advanced approaches such as kinetic chlorophyll fluorescence allow more precise quantification of photosynthetic performance under stress, highlighting the importance of physiological traits like non-photochemical quenching and quantum yield, which play critical roles in salt stress tolerance [ 79 ]. These indicators can therefore aid in identifying and selecting more resistant genotypes in breeding programs that combine high-resolution phenotyping with genomic analyses [ 80 ]. In addition to physiological parameters, the assessment of grain yield and its components is a crucial indicator for evaluating tolerance to salinity stress under agronomic conditions. The results indicate that both varieties maintain a tolerance threshold at 8 dS m⁻¹ for grain yield, which begins to decline beyond this salinity level, highlighting the heightened sensitivity of this trait. In contrast, the 200-grain weight and straw yield are only significantly impacted starting from 12 dS m⁻¹, demonstrating greater stability of these components under saline conditions, with the variety Nachit showing a slight advantage over Faraj. Numerous studies have highlighted that abiotic stresses, particularly salinity, pose a major challenge significantly reducing crop yields, especially during the reproductive stage, which is critical for agricultural productivity [ 81 , 82 ]. At this crucial phase, plants activate key physiological mechanisms, such as the partial exclusion of sodium from the leaves, to maintain ion homeostasis [ 83 ]. This regulation is especially important as the potassium-to-sodium ratio and grain dry matter content are strongly correlated with the rate and duration of grain filling under salt stress, directly influencing both yield quantity and quality [ 84 ]. Furthermore, saline irrigation imposes significant stress on crop growth and yield by disrupting water relations, nutrient uptake, and stomatal function, while inducing oxidative damage that collectively contribute to marked declines in productivity [ 85 – 87 ]. Salinity alters the plant’s morpho-physiological and biochemical pathways, leading to reduced photosynthetic efficiency, lower biomass accumulation, and impaired source-sink interactions, which in turn accelerate the aging process of reproductive organs [ 88 ]. This is particularly evident during key reproductive stages, such as anthesis and grain filling, when decreased water availability induces structural changes in leaves including thinner flag leaves and smaller mesophyll cells that negatively impact leaf area, turgor pressure, and assimilate synthesis, ultimately limiting yield potential [ 89 ]. The severity of salinity effects varies by developmental stage, with grain yield reductions of approximately 39.1%, 24.3%, and 13.4% observed at flowering, initial booting, and mid-grain filling stages, respectively [ 90 ]. Moreover, salinity impairs grain quality and nutrient content, diminishing components such as gluten, fiber, ash, and essential minerals including Mg, P, Ca, Zn, K, and Fe [ 91 , 92 ]. In some species like Brassica oleracea var. capitata, yield reductions of up to 62% have been documented at moderate salinity levels of 8 dS m⁻¹ [ 93 ]. Together, these physiological disturbances and declines in grain quality highlight the profound detrimental effects of salinity on crop reproductive success and overall productivity [ 94 – 96 ]. Furthermore, salinity compromises stomatal regulation and nitrogen metabolism, further limiting biomass and yield [ 97 , 98 ]. It also reduces photosynthesis, water use efficiency, and plant vigor during critical reproductive phases, thereby reducing the overall yield as well as its quality [ 99 ]. Overall, these multifaceted impacts underscore the major challenge salinity poses for sustainable agricultural productivity. The results from the heatmap and principal component analysis (PCA) highlight strong correlations between soil parameters (EC, Na, K, Ca, Mg, Cl) and the growth traits and yield components of durum wheat (Pth, ChlF, NoL, GY, 200-GW, SY), clearly revealing the detrimental impact of salinity on agronomic performance. Increases in Na and Cl concentrations, along with elevated soil EC, are strongly associated with significant reductions in growth parameters such as Pth, NoL, and ChlF, as well as major yield components, including GY, 200-GW, and SY. These findings are consistent with those of [ 3 ], who demonstrated that salinity hinders crop growth and reduces yield through combined osmotic and ionic effects. Previous studies have also demonstrated that irrigation with saline water reduces spike formation [ 100 ] and grain weight [ 101 ], resulting in a reduction of the final yield [ 102 , 103 ]. reduction of up to 90% in grain yield of durum wheat under a salinity level of 15 dS m⁻¹ has been reported, in contrast to our findings, which show an average yield decrease of approximately 40% at 10 dS m⁻¹ and 62% at 15 dS m⁻¹, highlighting a substantial degree of genetic variability in salinity tolerance [ 104 ]. Moreover, chlorophyll fluorescence emerges as a reliable indicator of plant response to salt stress, as it is closely correlated with growth traits and overall productivity. Although leaf chlorophyll content showed a slight decline under saline conditions, this reduction remained moderate and may be offset by morphological adaptations, such as increased leaf thickness, which could help maintain photosynthetic capacity despite the stress [ 105 , 106 ]. Finally, the presence of specific nutrients, particularly potassium (K) and magnesium (Mg), appears to influence plant responses to salinity. These elements are crucial for osmotic control, membrane stabilization, and photosynthetic activity, offering a promising avenue to alleviate the negative impacts of salt damage through optimized nutrient management [ 107 – 109 ]. 5. Conclusion This study aimed to thoroughly and comparatively evaluate how two local durum wheat varieties, Faraj and Nachit, respond to different salinity levels in irrigation water applied to silty-clay soil. By analyzing the effects of salt stress from germination to final yield, the study sought to deepen the understanding of underlying physiological and agronomic mechanisms, identify critical thresholds of tolerance, and provide a solid foundation for varietal selection and the optimization of agronomic practices under saline conditions ultimately enhancing the resilience and sustainability of cereal-based systems in arid and semi-arid regions. These findings are part of a broader framework in which plant adaptive responses to salinity rely on a dynamic coordination of key physiological mechanisms, including root-to-shoot signaling, water regulation, photosynthetic maintenance, and ion homeostasis. The Faraj and Nachit varieties stood out for their ability to limit toxic ion accumulation while preserving essential nutrients, making them promising candidates for breeding programs targeting traits associated with salt tolerance. To build on these advances, it is essential to adopt multidisciplinary approaches that integrate genomics, physiology, and agronomic management in order to better unravel the molecular and physiological bases of salt tolerance. Simultaneously, promoting tailored cultural practices such as improved irrigation management, the use of organic amendments, and farmer awareness of salt-tolerant varieties is vital for mitigating the adverse effects of salinity. Together, these efforts will contribute to sustainably improving durum wheat productivity and quality while supporting food security in vulnerable regions, particularly in a global context marked by shrinking freshwater resources and the increasing salinization of soils and irrigation water. The results indicate that salinity progressively affects germination, with moderate tolerance observed up to 8 dS m⁻¹. Nachit exhibited a greater ability to maintain high germination rates under saline stress compared to Faraj, suggesting a higher aptitude for overcoming challenging initial conditions. During the vegetative stages, plant growth measured through height, leaf number, and chlorophyll fluorescence (Fv/Fm) showed some resilience to salinity during tillering and stem elongation. However, at heading and maturity, the negative impacts became more pronounced, with significant reductions in photosynthesis and overall vigor, thereby compromising final productivity. Regarding yield components, both varieties tolerated salinity levels up to 12 dS m⁻¹ for 200-grain weight and biomass, while grain yield began to decline at 8 dS m⁻¹. Nachit outperformed Faraj, notably due to its more efficient regulation of toxic ion (Na⁺, Cl⁻) accumulation and superior retention of essential nutrients such as K⁺, Ca²⁺, and Mg²⁺. These findings align with a broader framework in which plant adaptive responses to salinity stress rely on the dynamic coordination of key physiological mechanisms, including root-to-shoot signaling, water regulation, sustained photosynthetic activity, and ion homeostasis. The Faraj and Nachit varieties demonstrate a notable capacity to limit the accumulation of toxic ions while preserving essential nutrients, positioning them as promising candidates for breeding programs targeting physiological traits associated with salt tolerance. To advance these findings, it is essential to adopt multidisciplinary approaches that integrate genomics, plant physiology, and agronomic management in order to better elucidate the foundations of salt tolerance. In parallel, the implementation of appropriate agronomic strategies such as improved irrigation practices, the application of organic amendments, and enhanced farmer awareness of tolerant varieties is crucial to mitigating the adverse effects of salinity. Together, these combined efforts will help ensure the sustainable improvement of durum wheat productivity and quality, while reinforcing food security in a context increasingly challenged by the depletion of freshwater resources and the rising salinization of soils and irrigation water. Declarations Conflict of interest: The authors declare that they have no known financial conflicts of interest or personal relationships that could have influenced the work. that would appear to affect the work reported in this manuscript. Ethical approval: Not applicable. Consent to participate: Not applicable. Consent to publish: All authors have read and approved the final version of this manuscript for submission and publication. Funding: This study received funding from the “MCGP” project, supported by INRA and ICARDA Acknowledgments The authors sincerely thank all collaborators who contributed to this work, including the teams involved in field sampling, laboratory analyses, and manuscript preparation at the National Institute of Agricultural Research (INRA), the Research Unit for Environment and Conservation of Natural Resources (URECRN), and the International Center for Agricultural Research in the Dry Areas (ICARDA) in Morocco. We are also grateful to the “MCGP” project (INRA and ICARDA) and the EiA Climber project for their valuable financial and technical support. Data Availability: Data supporting the findings of this study are available from the corresponding author upon reasonable request. References Khondoker, M.; Mandal, S.; Gurav, R.; Hwang, S. Freshwater Shortage, Salinity Increase, and Global Food Production: A Need for Sustainable Irrigation Water Desalination—A Scoping Review. 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06:00:50","extension":"png","order_by":46,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":62011,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-7909033/v1/5192366332ba3392501e6052.png"},{"id":94059522,"identity":"5503efb5-338e-45fa-8f95-4ee731b27f5d","added_by":"auto","created_at":"2025-10-22 06:08:50","extension":"xml","order_by":47,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":286610,"visible":true,"origin":"","legend":"","description":"","filename":"rs79090330structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7909033/v1/08a8fe60296f04bea820138b.xml"},{"id":94059155,"identity":"4ca44319-c404-46b1-b3c7-ba95fb53598a","added_by":"auto","created_at":"2025-10-22 06:00:50","extension":"html","order_by":48,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":305008,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7909033/v1/ca3d323c7fc4dbd65f99ba7f.html"},{"id":94059112,"identity":"833edb33-8e7d-4e29-8705-f07b06217694","added_by":"auto","created_at":"2025-10-22 06:00:49","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":331416,"visible":true,"origin":"","legend":"\u003cp\u003eLocation of the soil sampling site and the greenhouse experimental setup.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7909033/v1/8281e23f9beed0c458fd68ea.png"},{"id":94059111,"identity":"81328afa-d9c6-4b23-8048-91c662b44607","added_by":"auto","created_at":"2025-10-22 06:00:49","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":368278,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic overview of the germination test methodology for durum wheat varieties.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7909033/v1/80e920bba7dcfed0651aa97c.png"},{"id":94059113,"identity":"8843738e-6e81-4131-a23a-ed15c1909f6c","added_by":"auto","created_at":"2025-10-22 06:00:49","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":173862,"visible":true,"origin":"","legend":"\u003cp\u003eGermination dynamics of durum wheat varieties (Nachit and Faraj) under different salinity levels: total germination percentage and daily germination percentage over 8 days. (A) Days 1–2; (B) Days 3–4; (C) Days 5–6; (D) Days 7–8.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7909033/v1/52d91488fd808137d6a49082.png"},{"id":94059115,"identity":"70ce5fa3-78e8-4709-8312-1667e7ce907e","added_by":"auto","created_at":"2025-10-22 06:00:49","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":132071,"visible":true,"origin":"","legend":"\u003cp\u003eResponse of root length (RL) and coleoptile length (CL) in durum wheat varieties Faraj and Nachit under increasing salinity levels\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7909033/v1/08c7a9ffdcfb4bacf9ab1149.png"},{"id":94059117,"identity":"ceaaf2b1-078e-4141-b21c-11b311d0105f","added_by":"auto","created_at":"2025-10-22 06:00:49","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":68425,"visible":true,"origin":"","legend":"\u003cp\u003eLinear regression analysis of durum wheat germination responses under different salinity levels: (a) Germination capacity (GC) ; (b) Daily germination percentage (DGP) ; \u0026nbsp;(c) Germination speed index (GSI) ; \u0026nbsp;(d) Mean germination time (MGT) ; \u0026nbsp;(e) Root length (RL) and \u0026nbsp;(f) Coleoptile length (CL).\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7909033/v1/e0dcb86465b2eb9f058eddaa.png"},{"id":94060175,"identity":"6640d625-eb3f-433b-8949-9ef2368dbbf0","added_by":"auto","created_at":"2025-10-22 06:16:49","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":167772,"visible":true,"origin":"","legend":"\u003cp\u003eResponses of Plant Height, Chlorophyll Fluorescence (Fv/Fm), and Number of Leaves to Increasing Salinity in Two Durum Wheat Varieties Across Growth Stage.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7909033/v1/1b0511e5a2cda59990b4bf37.png"},{"id":94060428,"identity":"ab68ac06-2d60-4b9e-a08a-1923afcbe0de","added_by":"auto","created_at":"2025-10-22 06:24:49","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":109695,"visible":true,"origin":"","legend":"\u003cp\u003eLinear regression of yield components across increasing salinity concentrations in silty clay soil\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-7909033/v1/8439ff05bd4e80cbf16584d7.png"},{"id":94060631,"identity":"8315f0f0-5292-4dcc-94a8-83a8dd97e33e","added_by":"auto","created_at":"2025-10-22 06:32:49","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":81680,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap of correlation coefficients among soil parameters, growth traits, and yield components in durum wheat under increasing salinity levels. The heatmap shows the correlation matrix between all measured variables: soil parameters including electrical conductivity (EC), sodium (Na), potassium (K), calcium (Ca), magnesium (Mg), and chloride (Cl); growth-related traits such as plant height (Pth), chlorophyll fluorescence (ChlF), and number of leaves (NoL); and yield components including grain yield (GY), 200-grain weight (200-GW), and straw yield (SY).\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-7909033/v1/4335a5f355ff3b6ef523802d.png"},{"id":94059499,"identity":"16421843-2aec-4213-9545-96a859020e74","added_by":"auto","created_at":"2025-10-22 06:08:49","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":233748,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal Component Analysis (PCA) of selected soil and plant variables in durum wheat under varying salinity levels. The PCA includes six key variables: EC (electrical conductivity), K (potassium), Pth (plant height), ChlF (chlorophyll fluorescence), GY (grain yield), and 200-GW (200-grain weight). Observations correspond to the two varieties at five salinity levels: F = Faraj, N = Nachit; I0–I4 indicate salinity treatments from 0.2 to 16 dS m⁻¹.\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-7909033/v1/2fa21b9fdd1ca831617c1d56.png"},{"id":94489120,"identity":"50725ebd-8441-455a-846a-fc308c9c1f9a","added_by":"auto","created_at":"2025-10-27 17:03:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3433873,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7909033/v1/fd34b74f-23e7-4475-a7c9-99bc7c80ee4a.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eComparative assessment of saline irrigation effects on germination, physiological responses, growth, and yield of durum wheat varieties grown on silty clay soil\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eIrrigation using saline water is becoming a strategic option to address the growing shortage of freshwater, especially in drylands where water demand is rising due to climatic pressures and demographic expansion. stress and threaten agricultural output and food security [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. However, this practice also contributes to soil salinization a critical constraint on crop performance [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. An estimated portion of arable land is already affected by salinity stress, especially in dry regions such as Morocco [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Climate change, combined with shifts in farming practices, continues to degrade soil and water quality, further aggravating these challenges [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Salinity disrupts vital physiological processes in plants, such as nutrient uptake and photosynthesis, resulting in impaired development and significant declines in productivity [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In Morocco, a country marked by arid to semi-arid conditions, salinity affects a substantial area of irrigated land, challenging sustainable agriculture [\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDurum wheat (\u003cem\u003eTriticum turgidum\u003c/em\u003e L. subsp. \u003cem\u003edurum\u003c/em\u003e) is a major cereal crop widely grown in Mediterranean regions, including Southern Europe, North Africa, and West Asia, and constitutes a key source of staple products such as flour, pasta, and semolina [\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. It is particularly appreciated for its digestibility and high nutritional value, making it a fundamental component of the human diet [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Nevertheless, its productivity is increasingly constrained by environmental stresses, including irregular rainfall, high temperatures, soil degradation, and salinity [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Supplemental irrigation is often required under arid and semi-arid conditions to sustain cultivation; however, prolonged use of saline water can worsen soil salinization, disrupt ionic balance, impair cellular functions, and limit plant growth, biomass accumulation, and grain yield, with roots generally showing higher tolerance than aerial parts [\u003cspan additionalcitationids=\"CR17 CR18 CR19 CR20 CR21\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Increasing competition for water due to urbanization, industrial and service demands, together with declining water quality from overexploitation of marginal sources, further restricts irrigation resources in dryland regions [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Therefore, identifying durum wheat varieties with enhanced salinity tolerance, coupled with innovative management and efficient irrigation strategies, is essential to maintain yields and strengthen agricultural resilience under challenging environmental conditions [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eSalinity imposes a dual stress on plants, initially creating osmotic or water stress that limits root water uptake and reduces leaf expansion, followed by ionic stress due to the accumulation of Na⁺ and Cl⁻ ions, which disrupts ionic balance and accelerates leaf senescence [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Water stress caused by salinity restricts growth and triggers stomatal closure, impairing photosynthetic efficiency [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] and affecting nitrogen metabolism [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The ionic stress component further compromises plant metabolism by altering mineral ratios, reducing photosynthetic pigments, especially chlorophyll [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], and modifying dry matter composition [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. These physiological disruptions not only limit biomass accumulation but also reduce yield potential. Prolonged irrigation with saline water additionally leads to the build-up of soluble salts in soils, increasing electrical conductivity (EC) and sodium adsorption ratio (SAR), while decreasing organic matter and nutrient availability [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Such soil degradation hampers water infiltration, nutrient uptake, and microbial activity, creating an unfavorable environment for plant growth [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The intensity of these effects is influenced by soil texture, initial salinity, irrigation practices, climate, and cultivar characteristics [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Implementing strategies such as alternating saline and fresh water, controlled leaching, optimized irrigation scheduling, and cultivating salt-tolerant varieties can mitigate the negative impacts of salinity on both soil and crop performance [\u003cspan additionalcitationids=\"CR37\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eEnhancing salt tolerance in durum wheat, particularly in local cultivars such as Faraj and Nachit, is critical for maintaining stable productivity under saline irrigation conditions. Salinity imposes both osmotic and ionic stresses that disrupt physiological processes, including water uptake, nutrient assimilation, and photosynthesis, ultimately limiting growth, biomass accumulation, and grain yield [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Local durum wheat varieties often exhibit differential responses to salt stress, reflecting inherent genetic variability that can be exploited in breeding and agronomic programs [\u003cspan additionalcitationids=\"CR41\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Evaluating growth and yield-related parameters such as plant height, leaf number, biomass, grain yield, and straw yield under controlled saline irrigation allows the identification of cultivars capable of sustaining performance under stress. This approach supports the selection of resilient varieties and contributes to the sustainability of cereal cropping systems in silty-clay soils under dryland conditions, ensuring both crop productivity and long-term soil health [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Ultimately, targeted evaluation and selection of durum wheat varieties adapted to salinity represent a cornerstone for improving food security and agricultural resilience in arid and semi-arid regions [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThis study aims to evaluate durum wheat responses to saline irrigation in silty-clay soils. It compares the performance of two local durum wheat varieties, Faraj and Nachit, across key growth stages, including seed germination, vegetative development, physiological traits, and yield components. By assessing performance under varying salinity levels, the study aims to determine the tolerance thresholds of each variety at different stages, linking early stress responses to final agronomic outcomes. Specifically, the research seeks to (i) quantify the effects of salinity on growth, physiology, and yield, (ii) identify the variety with superior salt resilience, and (iii) establish actionable selection criteria for improved variety choice under saline irrigation. The findings are intended to provide practical recommendations for irrigation management and variety selection, promoting water-use efficiency and sustainable durum wheat production in dry and semi-dry regions.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Study Area, soil sampling, and assessment of physicochemical properties\u003c/h2\u003e\u003cp\u003eThis study was carried out at the Regional Center of Rabat of the National Institute of Agricultural Research (INRA), within the Research Unit for Environment and Natural Resource Conservation (URECRN). The experiment was conducted in a greenhouse at this center. The site is located at 34\u0026deg;03\u0026prime;50\u0026Prime; N latitude and 06\u0026deg;50\u0026prime;40\u0026Prime; W longitude, approximately 70 m above sea level, representing the typical coastal area of Rabat, Morocco, characterized by a Mediterranean climate with oceanic influences. Seasonal temperatures range from 12\u0026deg;C in winter to 28\u0026deg;C in summer, with an annual rainfall of around 400 mm. Soil samples were manually collected from an agricultural field in the Temara region, approximately 30 km south of Rabat. This field was selected for its fine-textured soils, which are particularly prone to salinization and degradation due to irrigation. Samples were taken from the top 0\u0026ndash;40 cm soil layer using an auger, as this layer represents the most biologically active and agriculturally important portion of the profile. A composite sample from the 0\u0026ndash;20 cm layer was prepared and transported to the soil and water chemistry laboratory at URECRN, INRA, Rabat, for initial physicochemical analysis. The locations of the soil sampling site and the greenhouse experimental setup are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe assessment of the soil\u0026rsquo;s physicochemical characteristics was conducted following the procedures and data reported by Manhou et al. (2024) [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Soil samples were collected from the top 0\u0026ndash;40 cm layer of a field in the Temara region and subsequently air-dried. The dried samples were spread on trays and left under a drying ramp overnight to stabilize moisture content. Following drying, the samples were sieved to separate particle sizes: material retained on a 2 mm sieve was used for the determination of pH, electrical conductivity (EC), and exchangeable cations (Na, K, Ca, Mg), while finer fractions passing through a 0.2 mm sieve were employed for the analysis of total nitrogen (N), available phosphorus (P), and organic matter (OM). Particle size distribution was determined using the sedimentation method [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Soil pH was measured potentiometrically in a 1:2.5 soil-to-water suspension using a Mettler Toledo Seven Easy-728 pH meter (Mettler Toledo, USA) [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Electrical conductivity (EC) was determined in a saturated soil paste using an Orion 162 conductivity meter (Thermo Fisher Scientific, USA)[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Organic matter (OM) was quantified using the Walkley\u0026ndash;Black method [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Cation exchange capacity (CEC) was determined with 1 N ammonium acetate at pH 7 (Sigma, USA) [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Total nitrogen (N) was measured using the Kjeldahl method [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Available phosphorus (P) was extracted with 0.5 M sodium bicarbonate (pH 8.5) and quantified spectrophotometrically with a JENWAY 6405 spectrophotometer (Bibby Scientific, UK) [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Exchangeable potassium (K) and sodium (Na) were measured via flame photometry, whereas calcium (Ca) and magnesium (Mg) were determined using atomic absorption spectrophotometry with a novAA 800 D analyzer (Analytik Jena, Germany) or by complexometric titration with EDTA [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Chloride (Cl) concentrations were measured colorimetrically after precipitation with silver nitrate (AgNO₃).\u003c/p\u003e\u003cp\u003eThe soil was characterized as a silty-clay soil, comprising 52.6% clay, 34.3% silt, and 13.1% sand. The soil exhibits an alkaline pH of 7.80 and a low electrical conductivity (EC) of 0.20 dS m⁻\u0026sup1;, indicating non-saline conditions. Organic matter content is 1.33%, and the cation exchange capacity (CEC) is 0.65 cmol kg⁻\u0026sup1;, reflecting limited nutrient retention. Total nitrogen (N) is 0.078%, available phosphorus (P) is 120 mg kg⁻\u0026sup1;, and exchangeable potassium (K) is 229 mg kg⁻\u0026sup1;. The soil exhibited relatively low levels of sodium (Na), calcium (Ca), magnesium (Mg), and chloride (Cl). The initial physicochemical characterization of the soil is presentedin Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003e.\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePhysicochemical properties of the soil prior to the experiment.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eValue\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUnit\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eGranulometry\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSand\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSilt\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e34.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClay\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e52.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eChemical Properties\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003epH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003edS m⁻\u0026sup1;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCEC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ecmol kg⁻\u0026sup1;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMacronutrients\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.078\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e120\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003emg kg⁻\u0026sup1;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eK\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e229\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003emg kg⁻\u0026sup1;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNa\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003emg kg⁻\u0026sup1;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCa\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003emg kg⁻\u0026sup1;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003emg kg⁻\u0026sup1;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCl\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003emg kg⁻\u0026sup1;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e\u003cb\u003e2.2. Plant material, experimental setup, and crop management practices\u003c/b\u003e\u003c/h2\u003e\u003cp\u003eThe experiment was conducted using the durum wheat variety Nachit (Triticum turgidum L. var. durum) under controlled greenhouse conditions. Seeds were sown in plastic containers measuring approximately 28 \u0026times; 21 cm, each lined with a gravel layer at the base to ensure proper drainage. Containers were filled with silty-clay soil representative of the study area, and ten seeds were placed per container to maintain uniform plant density. The selection of the durum wheat variety Nachit was based on multiple agronomic and quality criteria, including adaptability to local agroclimatic conditions, growth cycle duration, yield potential under favorable and semi-arid environments, drought and salinity tolerance, and key quality traits such as protein content, baking quality, and yellow pigment index. These selection criteria are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, highlighting the suitability of Nachit for the experimental conditions. A randomized complete design (RCD) with three replicates per treatment was employed, resulting in a total of fifteen containers for the five salinity levels tested: I0 (0.2 dS m⁻\u0026sup1;, freshwater, control), I1 (4 dS m⁻\u0026sup1;), I2 (8 dS m⁻\u0026sup1;), I3 (12 dS m⁻\u0026sup1;), and I4 (16 dS m⁻\u0026sup1;) NaCl. The greenhouse temperature was maintained at 22\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u0026deg;C using a forced-air evaporative cooling system. Irrigation management followed a staged approach. During the first week, freshwater was applied in fine droplets to minimize seed displacement and ensure uniform emergence. Once seedlings reached approximately 3 cm in height, salinity treatments were initiated, with irrigation three times per week. Each container received 0.5 L per irrigation, maintaining the soil near field capacity without causing leaching or waterlogging. Saline solutions were prepared by dissolving NaCl in tap water to achieve the desired electrical conductivity levels. Nutrient management involved a split nitrogen fertilization scheme totaling 120 kg ha⁻\u0026sup1;, applied in three stages: one-third at sowing using ammonium sulfate (21% N), one-third at stem elongation, and one-third at heading using ammonium nitrate (33% N). Phosphorus and potassium were applied based on soil test recommendations. Pest management included monitoring black aphid infestations and applying Primor DG (Syngenta, Rabat, Morocco) according to integrated pest management (IPM) principles, ensuring crop safety while minimizing environmental impact. Standard agronomic practices, including monitoring of soil moisture and plant nutrient status, were maintained throughout the experiment to ensure optimal growth conditions.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eKey characteristics of the durum wheat variety.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariety\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRegistration Year\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBreeder / Origin\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAgroecological Adaptation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eYield potentiel (t ha⁻\u0026sup1;)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eKey Quality Indicators\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDrought Response\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eGrowth Duration (days)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNachit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eINRA, Morocco\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFavorable \u0026amp; Semi-arid areas\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.9 (Favorable), 4.1 (Semi-arid)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eProtein: 15%; Baking: Good; Seed quality: Good; Yellow index: 27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eTolerant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e150\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Germination test and germination indicators\u003c/h2\u003e\u003cp\u003eThe germination and early seedling development of durum wheat varieties Nachit and Faraj were evaluated under controlled greenhouse conditions. Seeds were carefully selected for uniform size, appearance, and soundness, treated with 0.5% sodium hypochlorite for surface sterilization and subsequently rinsed with distilled water. For each treatment, 75 seeds per variety were used, divided into three replicates of 25 seeds each. Seeds were then placed into sterile vessels lined with filter paper, and salinity treatments consisted of a control (0.2 dS m⁻\u0026sup1; freshwater) and four NaCl concentrations: 4, 8, 12, and 16 dS m⁻\u0026sup1;. Containers were maintained in darkness at approximately 21\u0026deg;C, with germination recorded daily. A factorial design was applied, considering the two varieties and five salinity levels, with three replicates per treatment. This design allowed a precise assessment of the interaction between variety and salinity on germination and early seedling growth. Seedlings were continuously monitored for uniform emergence and early vigor, and moisture was maintained to prevent desiccation. To quantify germination, the following parameters were calculated:\u003c/p\u003e\u003cp\u003e\u003cb\u003eGermination Capacity (GC %)\u003c/b\u003e: Germination Capacity (GC %): This parameter helps determine the salinity level at which durum wheat seed germination starts to decline. It is calculated by expressing the percentage of seeds that successfully germinate by the end of the test relative to the total seeds sown [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]:\u003c/p\u003e\u003cp\u003e\u003cimg src=\"data:image/png;base64,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\" style=\"width: 378px; height: 44.4706px;\" width=\"378\" height=\"44.4706\"\u003e\u003c/p\u003e\u003cp\u003ewhere g is the number of germinated seeds and G is the total number of seeds.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eGermination percentage (GP %)\u003c/strong\u003e\u003cp\u003eThis parameter indicates the fraction of seeds that have sprouted by a specific day (n), determined by dividing the total seeds germinated up to day n by the initial number of seeds planted.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$\\:\\text{}\\text{}\\text{G}\\text{P}=\\frac{{\\text{g}}_{\\text{n}}}{\\text{N}\\text{g}}\\times\\:100$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ewhere gn denotes the total seeds sprouted up to day n, Ng refers to the initial seed count, and n indicates the specific day of observation (1, 2, ..., n).\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eGermination speed index (GSI)\u003c/strong\u003e\u003cp\u003ecalculated by tracking seed germination each day and computed using the formula [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv id=\"Equ3\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ3\" name=\"EquationSource\"\u003e\n$$\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\varvec{G}\\varvec{S}\\varvec{I}=\\sum\\:_{\\varvec{i}=1}^{\\varvec{n}}\\frac{\\varvec{P}\\varvec{i}}{\\varvec{D}\\varvec{i}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e3\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ewhere Pi is the number of seeds that germinated on day i, and Di the number of days elapsed since the beginning of the test.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMean Germination Time (MGT\u003c/b\u003e): This parameter indicates the average duration required for seeds to germinate under specific conditions. It was calculated using the formula [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e] :\u003cdiv id=\"Equ4\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ4\" name=\"EquationSource\"\u003e\n$$\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\mathbf{M}\\mathbf{G}\\mathbf{T}=\\frac{\\sum\\:_{\\varvec{i}=1}^{\\varvec{k}}(\\varvec{n}\\varvec{i}\\times\\:\\varvec{t}\\varvec{i})}{\\sum\\:_{\\varvec{i}=1}^{\\varvec{k}}\\varvec{n}\\varvec{i}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e4\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eWhere t_i is the time from day one to the last day of observation, n_i is the number of seeds germinated on day i, and k is the last day of germination.\u003c/p\u003e\u003cp\u003eTo evaluate the relationship between salinity levels and the mean daily germination percentage (DGP), linear regression analysis was performed. The mean DGP was calculated over 7 days (Day 1 to Day 8) using the following formula:\u003cdiv id=\"Equ5\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ5\" name=\"EquationSource\"\u003e\n$$\\:\\text{M}\\text{e}\\text{a}\\text{n}\\:\\text{D}\\text{G}\\text{P}=\\frac{\\text{G}8-\\text{G}1}{7}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e5\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ewhere G8​ and G1 ​ represent the cumulative germination percentages recorded on Day 8 and Day 1, respectively.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMeasurement of Seedling Length\u003c/b\u003e: Seedling Length Assessment: On day 6 of germination, five seedlings were randomly selected from each replicate for each variety and salinity treatment. Radicle and coleoptile lengths were measured using a graduated ruler, keeping seedlings on a moist surface to avoid desiccation. This final measurement provided an accurate evaluation of early growth responses to salinity stress. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e summarizes the germination test methodology, including seed selection and sterilization, placement on moistened filter paper, application of salinity treatments, and assessment of seedling growth parameters.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e\u003cb\u003e2.4. Measurement of Growth Parameters and Chlorophyll Fluorescence under Controlled Conditions\u003c/b\u003e\u003c/h2\u003e\u003cp\u003eAll measurements were conducted at key phenological stages of durum wheat, namely tillering, stem elongation, heading, and maturation. Plant height was determined on three representative plants per container by measuring from the stem base to the tip of the uppermost leaf using a vertically oriented graduated ruler, and the mean values were calculated. Leaf number was recorded manually on the same plants at each stage to maintain consistency. The maximum quantum yield of photosystem II (PSII) was assessed on fully expanded leaves using a portable pulse-amplitude modulated fluorometer (OS-30p, Opti-Sciences, USA) equipped with red LEDs (660 nm) delivering a saturating light pulse of up to 6000 \u0026micro;mol photons m⁻\u0026sup2; s⁻\u0026sup1;. Leaves were dark-adapted for a minimum of 30 minutes prior to measurement to ensure complete relaxation of PSII reaction centers. Minimum fluorescence (F₀) was determined, and maximum fluorescence (Fₘ) was recorded, allowing calculation of variable fluorescence (F\u003csub\u003ev\u003c/sub\u003e) as follows [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]:\u003c/p\u003e\u003cp\u003eFv\u0026thinsp;=\u0026thinsp;Fm\u0026thinsp;\u0026minus;\u0026thinsp;F0 (6)\u003c/p\u003e\u003cp\u003eThe maximum quantum efficiency of PSII was then determined using the following formula:\u003c/p\u003e\u003cp\u003eFv/Fm=\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\:\\frac{\\:\\:\\:\\text{F}\\text{m}\\:-\\:\\text{F}0\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:}{\\text{F}\\text{m}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5. Yield Component Analysis\u003c/h2\u003e\u003cp\u003eAt the final growth stage, key yield-related traits of durum wheat were carefully assessed. Spikes were hand-harvested to avoid grain loss or damage. Grains were meticulously cleaned to eliminate debris and impurities. For uniformity in weight determination, a representative sample of 200 grains per batch was oven-dried at 105\u0026deg;C for 45 minutes to remove residual moisture and weighed using a high-precision balance (Ohaus, Parsippany, NJ, USA). The total grain count per container was determined with an automated seed counter (Numigral, Villeneuve-la-Garenne Cedex, France). Straw yield was measured as the remaining biomass after threshing, using the same high-precision balance to ensure consistency across treatments. Planting density (PD), considering each container covered 0.04 m\u0026sup2;, was calculated using the following formula:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:\\text{P}\\text{D}=\\frac{\\text{T}\\text{S}\\text{A}}{\\text{T}\\text{N}\\text{P}}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ewhere TSA is the total surface area in hectares, and TNP is the total number of plants. In this study, the total number of plants was 250 per hectare.\u003c/p\u003e\u003cp\u003e.\u003cb\u003e2.6. Statistical analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eStatistical analyses were performed using SPSS software, version 25. To assess the effect of different salinity levels on germination parameters of the two durum wheat varieties, analysis of variance (ANOVA) was conducted. This analysis revealed significant effects of salinity treatments on key germination indicators, as well as varietal differences, enabling identification of the variety with the greatest tolerance to saline conditions. When significant differences were detected, a post hoc test was applied to determine which treatments differed statistically. Linear regression analyses were also performed between salinity concentrations and individual germination parameters, in order to quantify the strength and direction of these relationships. In the second phase of the experiment, conducted in a greenhouse, data related to growth parameters, chlorophyll fluorescence, and yield components were analyzed using two- or three-way ANOVA (variety, salinity, and, where applicable, sampling period). This approach allowed evaluation of main effects and interactions among factors. A significance level of 0.05 was adopted. When significant differences were found, Duncan\u0026rsquo;s post hoc test was used to identify homogeneous groups and perform pairwise comparisons. Additionally, a Principal Component Analysis (PCA) was performed to explore the overall responses of the two varieties to different salinity levels, considering the full set of measured variables. This multivariate analysis facilitated visualization of response patterns, identification of the most influential variables, and examination of correlations among agronomic, physiological, and soil chemical parameters.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.1. Daily germination progress of two durum wheat varieties under varying salinity levels\u003c/h2\u003e\u003cp\u003eThe results indicate a progressive decline in the germination percentage of durum wheat seeds with increasing salinity levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Under control conditions, with irrigation using freshwater at 0.2 dS m⁻\u0026sup1;, both varieties exhibited excellent germination, reaching final percentages of 98.7% for Faraj and 98.8% for Nachit, indicating highly efficient seedling establishment in the absence of saline stress. Moderate saline irrigation (4 dS m⁻\u0026sup1;) caused a slight reduction in germination, with cumulative percentages of 88.2% for Faraj and 88.4% for Nachit over the eight-day observation period. This suggests that both varieties tolerate low levels of saline water without substantial impairment. At 8 dS m⁻\u0026sup1;, final germination decreased to 75.2% (Faraj) and 75.5% (Nachit), marking the onset of moderate stress. Notably, Nachit consistently demonstrated slightly higher germination than Faraj under these intermediate saline conditions. Severe saline irrigation at 12 and 16 dS m⁻\u0026sup1; strongly inhibited seedling emergence. Final germination percentages dropped to 47.4% and 40.5% for Faraj, and 47.5% and 40.7% for Nachit, respectively, reflecting reductions of over 50% relative to the control. The daily germination percentage (DGP) analysis provided a detailed view of the germination dynamics of Faraj and Nachit under different salinity levels, highlighting the days on which the differences were most pronounced. Under control irrigation with freshwater (0.2 dS m⁻\u0026sup1;), germination was significantly high, with Faraj and Nachit reaching 25% and 28% on the second day, followed by 80\u0026ndash;81% on the fifth day, and culminating at 98.7% and 98.8% on the eighth day.. At moderate salinity (4 dS m⁻\u0026sup1;), germination was significantly reduced, starting at 18\u0026ndash;20% on the second day and achieving 65% on the fifth day, with cumulative germination exceeding 88% at the end of the period. Under higher salinity (8 dS m⁻\u0026sup1;), the inhibitory effect became more pronounced. Early germination on the second day was limited to 12\u0026ndash;14%, reaching only 42\u0026ndash;44% by the fifth day, and ultimately 75.2\u0026ndash;75.5% at the end of eight days. Notably, Nachit consistently exhibited slightly higher germination than Faraj at each stage. Severe salinity conditions (12\u0026ndash;16 dS m⁻\u0026sup1;) strongly suppressed germination. On the second day, only 8\u0026ndash;8.5% of seeds emerged at 12 dS m⁻\u0026sup1;, and 5% at 16 dS m⁻\u0026sup1;. By the fifth day, cumulative germination barely reached 33\u0026ndash;35% at 12 dS m⁻\u0026sup1; and 22\u0026ndash;22.4% at 16 dS m⁻\u0026sup1;, ultimately plateauing at 47\u0026ndash;47.5% and 40\u0026ndash;40.7% on the eighth day.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e3.2. Effects of NaCl treatments on germination stress index (GSI) and mean germination time (MGT) in two durum wheat varieties\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe analysis results regarding the interaction between salinity levels and durum wheat varieties on the germination Stress Index (GSI) and Mean Germination Time (MGT) indicate notable variations depending on the level of saline irrigation for each variety (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). For GSI, the highest values were recorded under freshwater irrigation (0.2 dS m⁻\u0026sup1;), with Nachit reaching 11.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14 and Faraj 10.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11. At moderate salinity (4 dS m⁻\u0026sup1;), GSI decreased to 9.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12 for Nachit and 8.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15 for Faraj, while further reductions were observed at 8 dS m⁻\u0026sup1; (9.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13 and 8.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12, respectively). Severe salinity conditions (12\u0026ndash;16 dS m⁻\u0026sup1;) resulted in the lowest GSI values, ranging from 2.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09 to 4.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09.egarding MGT, the shortest germination times were observed under freshwater irrigation, with 2.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05 days for Nachit and 2.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06 days for Faraj. As salinity increased, MGT progressively lengthened, reaching 2.8\u0026ndash;4.0 days at moderate levels (4\u0026ndash;8 dS m⁻\u0026sup1;) and 5.5\u0026ndash;7.2 days under severe salinity (12\u0026ndash;16 dS m⁻\u0026sup1;), ANOVA indicated tthat both salinity and variety had highly significant effects on GSI and MGT (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). In contrast, the interaction between salinity and variety was not significant for GSI (p\u0026thinsp;=\u0026thinsp;0.09) and only marginally significant for MGT (p\u0026thinsp;=\u0026thinsp;0.06).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eEffect of salinity and durum wheat varieties on germination speed index (GSI) and mean germination time (MGT, days). Values are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SE (n\u0026thinsp;=\u0026thinsp;75, from three sets of 25 seeds). Means followed by different letters within a row are significantly different according to Duncan\u0026rsquo;s test (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The table also shows the ANOVA results for the effects of salinity, variety, and their interaction.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"11\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eSalinity\u003c/p\u003e\u003cp\u003e(dS m⁻\u0026sup1;)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"10\" nameend=\"c11\" namest=\"c2\"\u003e\u003cp\u003eVariety\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u003cp\u003eNachit\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"6\" nameend=\"c11\" namest=\"c6\"\u003e\u003cp\u003eFaraj\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e\u003cb\u003eGSI\u003c/b\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e\u003cb\u003eMGT\u003c/b\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003e\u003cb\u003eGSI\u003c/b\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c11\" namest=\"c9\"\u003e\u003cp\u003e\u003cb\u003eMGT\u003c/b\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e11.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e2.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003e10.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c11\" namest=\"c9\"\u003e\u003cp\u003e2.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06 a\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e9.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12 ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e2.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07 ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003e8.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15 ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c11\" namest=\"c9\"\u003e\u003cp\u003e3.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08 ab\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e9.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13 ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e3.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003e8.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12 ab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c11\" namest=\"c9\"\u003e\u003cp\u003e4.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05 b\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e4.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09 c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e5.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09 c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003e3.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11 c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c11\" namest=\"c9\"\u003e\u003cp\u003e5.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07 c\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e2.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08 d\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e6.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08 d\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003e2.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09 d\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c11\" namest=\"c9\"\u003e\u003cp\u003e7.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09 d\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eVariable Source\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"10\" nameend=\"c11\" namest=\"c2\"\u003e\u003cp\u003eGSI\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eDf\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e\u003cb\u003eSS\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003e\u003cb\u003eMS\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e\u003cp\u003e\u003cb\u003eF\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u003cb\u003e-value\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSalinity (S)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e37.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003e9.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e\u003cp\u003e72.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01 **\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariety (V)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e3.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e3.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e\u003cp\u003e26.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01 **\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(S)\u0026times; (V)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e\u003cp\u003e2.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e0.09 ns\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"10\" nameend=\"c11\" namest=\"c2\"\u003e\u003cp\u003eMGT\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eDf\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e\u003cb\u003eSS\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e\u003cb\u003eMS\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e\u003cp\u003e\u003cb\u003eF\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u003cb\u003e-value\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSalinity (S)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e43.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e10.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e\u003cp\u003e95.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01 \u003cb\u003e**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariety (V)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e5.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e5.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e\u003cp\u003e44.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01 \u003cb\u003e**\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(S)\u0026times; (V)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e0.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e\u003cp\u003e3.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e0.06 ns\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eDf: degrees of freedom; SS: sum of squares; MS: mean square; ns: not statistically significant; ** indicates strong significance (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.3. Response of durum wheat root and coleoptile growth to gradual salinity stress\u003c/h2\u003e\u003cp\u003eRoot length (RL) and coleoptile length (CL) of the two durum wheat varieties, Nachit and Faraj, exhibited a gradual decline as NaCl concentrations increased from 0.2 to 16 dS m⁻\u0026sup1; (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). At the lowest salinity level (0.2 dS m⁻\u0026sup1;), Nachit showed an RL of 4.53 cm and a CL of 3.86 cm, while Faraj recorded slightly lower values with 4.25 cm and 3.59 cm for RL and CL, respectively. At 4 dS m⁻\u0026sup1;, both varieties experienced a reduction in growth, with RL decreasing to 3.98 cm in Nachit and 3.65 cm in Faraj, and CL to 3.27 cm and 2.94 cm, respectively. Further increases in salinity to 8 dS m⁻\u0026sup1; resulted in RL values of 2.83 cm for Nachit and 2.51 cm for Faraj, whereas CL decreased to 2.28 cm and 1.96 cm. At 12 dS m⁻\u0026sup1;, RL dropped to 1.87 cm in Nachit and 1.59 cm in Faraj, while CL measured 1.45 cm and 1.22 cm, respectively. Under the highest salinity level of 16 dS m⁻\u0026sup1;, the most pronounced reductions were observed, with RL reaching 1.23 cm in Nachit and 1.04 cm in Faraj, and CL decreasing to 0.91 cm and 0.75 cm, respectively. Overall, the data show a consistent decline in both RL and CL across increasing salinity levels, with Nachit maintaining slightly higher measurements than Faraj at each concentration.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e\u003cb\u003e3.4. Relationships between salinity treatments, germination and early seedling growth parameters\u003c/b\u003e\u003c/h2\u003e\u003cp\u003eLinear regression analyses revealed strong relationships between salinity treatments and all measured germination and early seedling growth parameters (Fig.\u0026nbsp;5).\u003c/p\u003e\u003cp\u003eCombining all salinity treatments, germination percentage (GP) exhibited a strong negative correlation with salinity, with the highest determination coefficient observed (R\u0026sup2; = 0.94). Similarly, daily germination percentage (DGP) showed a pronounced negative relationship with salinity (R\u0026sup2; = 0.96), indicating that increasing NaCl concentrations reduced both the speed and uniformity of germination. The germination speed index (GSI) also declined significantly as salinity increased (R\u0026sup2; = 0.90), whereas mean germination time (MGT) was positively correlated with salinity (R\u0026sup2; = 0.93), reflecting a prolongation of the germination process at higher salt levels.Early seedling growth parameters, including root length (RL) and coleoptile length (CL), were negatively affected by increasing salinity, with determination coefficients of 0.90 and 0.94, respectively.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e\u003cb\u003e3.5. Effects of salinity on plant development, leaf number, and chlorophyll fluorescence (Fv/Fm) in durum wheat\u003c/b\u003e\u003c/h2\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e6\u003c/span\u003e illustrates the effects of increasing salinity on plant height, chlorophyll fluorescence (Fv/Fm), and leaf number in durum wheat cultivated on silty-clay soil throughout key vegetative and reproductive stages, including tillering, stem elongation, heading, and maturity. As salinity increased progressively, plant height declined gradually. The tallest plants were observed under control conditions (0.2 dS m⁻\u0026sup1;), measuring 25.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03 cm and 26.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04 cm at tillering for Faraj and Nachit, respectively, reaching maximum heights of 73.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05 cm for Faraj and 75.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06 cm for Nachit at maturity. Under moderate salinity (4 and 8 dS m⁻\u0026sup1;), plant height remained relatively stable during tillering and stem elongation, with Nachit consistently showing slightly higher values than Faraj (23.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05 cm vs. 22.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04 cm at tillering under 8 dS m⁻\u0026sup1;). High salinity (16 dS m⁻\u0026sup1;) at heading and maturity stages caused a more pronounced reduction in height, highlighting the inhibitory effect of elevated salt levels on vegetative growth, with Faraj and Nachit reaching 30.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03 cm and 31.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04 cm at maturity, respectively. Chlorophyll fluorescence (Fv/Fm) decreased progressively with rising salinity, with the largest reductions observed at heading and maturity. Control plants exhibited the highest Fv/Fm values, with 0.704 and 0.675 for Faraj, and 0.781 and 0.750 for Nachit at tillering and stem elongation, respectively. Irrigation with 12 and 16 dS m⁻\u0026sup1; NaCl significantly reduced Fv/Fm, decreasing from 0.500 to 0.310 in Faraj and from 0.580 to 0.390 in Nachit during heading. At maturity, Fv/Fm declined further to 0.298 in Faraj and 0.319 in Nachit under the highest salinity. Leaf number per plant also decreased progressively with increasing salinity. Under control conditions, Faraj produced 18.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15 leaves at tillering, reaching 62.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28 at maturity, while Nachit developed 19.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12 leaves at tillering and 64.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31 at maturity. At 16 dS m⁻\u0026sup1;, leaf counts were markedly reduced, reaching 13.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10 for Faraj and 14.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09 for Nachit at tillering, and 47.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22 and 49.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20 at maturity, respectively, indicating a strong inhibitory effect of high salinity on leaf development..\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.6. Evaluation of Yield Components and Salinity Tolerance Limits in Two Durum Wheat Varieties\u003c/h2\u003e\u003cp\u003eThe interaction between durum wheat varieties (Faraj and Nachit) and salinity levels revealed marked differences in grain yield, 200-grain weight, and straw yield depending on the salinity conditions \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eYield components of Faraj and Nachit durum wheat varieties under varying salinity levels.Values indicated by the same letter within each column are not significantly different at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 according to Duncan\u0026rsquo;s post hoc test. Values in parentheses indicate standard deviations. ANOVA results show the significance of salinity effects. ns: Not significant; *p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; **p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; *p\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSalinity\u003c/p\u003e\u003cp\u003e(dS m⁻\u0026sup1;)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVariety\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eGrain Yield\u003c/p\u003e\u003cp\u003e(t ha⁻\u0026sup1;)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e200-Grain Weight\u003c/p\u003e\u003cp\u003e(g)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eStraw Yield\u003c/p\u003e\u003cp\u003e(t ha⁻\u0026sup1;)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFaraj\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1.12 (1.80)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e67.0 (1.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.24 (1.00)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNachit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1.20 (1.60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e69.5 (0.80)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.30 (0.90)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFaraj\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.70 (15.60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e38.5 (7.60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.18 (0.40)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNachit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.85 (12.50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e42.0 (6.50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.25 (0.35)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFaraj\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.38 (15.60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e34.6 (1.50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.97 (0.10)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNachit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.55 (12.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e37.5 (1.30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.05 (0.09)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFaraj\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.18 (0.20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e29.3 (1.50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.80 (0.70)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNachit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.28 (0.18)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e32.0 (1.10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.90 (0.60)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFaraj\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.16 (0.10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e11.6 (1.50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.55 (0.30)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNachit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.20 (0.08)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e15.0 (1.30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.60 (0.25)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e0.2\u003c/p\u003e\u003cp\u003e4\u003c/p\u003e\u003cp\u003e8\u003c/p\u003e\u003cp\u003e12\u003c/p\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1.16 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e68.25 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.27 a\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.78 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e40.25 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.22 b\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.47 c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e36.05 c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.01 c\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.23 d\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e30.65 c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.85 c\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.18 d\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e13.30 d\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.58 d\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eYield Parameters\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e\u003cb\u003eGrain Yield (t ha⁻\u0026sup1;)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e\u003cb\u003e200-Grain Weight (g)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e\u003cb\u003eStraw Yield (t ha⁻\u0026sup1;)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable Source\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e\u003cem\u003ep-Value\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e\u003cem\u003ep-Value\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e\u003cem\u003ep-Value\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariety (V)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e0.023 *\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e0.045 *\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e0.062 ns\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSalinity (Sa)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001 ***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001 ***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001 ***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eV \u0026times; Sa\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e0.034 *\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e0.041 *\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e0.010 **\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eFor grain yield, ANOVA results indicated significant effects of salinity (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and variety (p\u0026thinsp;=\u0026thinsp;0.023), along with a significant variety \u0026times; salinity interaction (p\u0026thinsp;=\u0026thinsp;0.034). The highest yields were observed under control conditions (0.2 dS m⁻\u0026sup1;), reaching 1.20 t ha⁻\u0026sup1; for Nachit and 1.12 t ha⁻\u0026sup1; for Faraj. Moderate salinity at 4 dS m⁻\u0026sup1; led to reductions to 0.85 t ha⁻\u0026sup1; (Nachit) and 0.70 t ha⁻\u0026sup1; (Faraj). Yields declined more sharply at 8 dS m⁻\u0026sup1; to 0.55 t ha⁻\u0026sup1; (Nachit) and 0.38 t ha⁻\u0026sup1; (Faraj), with further decreases at 12 dS m⁻\u0026sup1; to 0.28 t ha⁻\u0026sup1; and 0.23 t ha⁻\u0026sup1;, respectively. At the highest salinity level (16 dS m⁻\u0026sup1;), grain yield dropped to 0.20 t ha⁻\u0026sup1; for Nachit and 0.18 t ha⁻\u0026sup1; for Faraj. Post hoc comparisons using Duncan\u0026rsquo;s test confirmed four significantly different groups, illustrating Nachit\u0026rsquo;s superior performance under moderate salinity conditions. For 200-grain weight, significant effects were also detected for salinity (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and variety (p\u0026thinsp;=\u0026thinsp;0.045), with a notable interaction (p\u0026thinsp;=\u0026thinsp;0.041). Under control conditions, the highest 200-grain weights were 69.5 g for Nachit and 67.0 g for Faraj. At 4 dS m⁻\u0026sup1;, these values declined to 42.0 g and 38.5 g, respectively. Further reductions occurred at 8 dS m⁻\u0026sup1; (37.5 g for Nachit and 34.6 g for Faraj) and 12 dS m⁻\u0026sup1; (32.0 g and 29.3 g). The lowest weights were recorded at 16 dS m⁻\u0026sup1;, with 15.0 g for Nachit and 11.6 g for Faraj. Duncan\u0026rsquo;s test again confirmed four distinct groups, emphasizing the significant impact of salinity and the consistently better performance of Nachit. Regarding straw yield, salinity significantly affected biomass (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), whereas the effect of variety was not significant (p\u0026thinsp;=\u0026thinsp;0.062); however, the variety \u0026times; salinity interaction was significant (p\u0026thinsp;=\u0026thinsp;0.010). Straw yield peaked under control conditions at 1.30 t ha⁻\u0026sup1; for Nachit and 1.24 t ha⁻\u0026sup1; for Faraj. Moderate salinity (4 dS m⁻\u0026sup1;) led to slight reductions (1.25 t ha⁻\u0026sup1; for Nachit, 1.18 t ha⁻\u0026sup1; for Faraj). At 8 dS m⁻\u0026sup1;, yields decreased to 1.05 t ha⁻\u0026sup1; (Nachit) and 0.97 t ha⁻\u0026sup1; (Faraj), and further at 12 dS m⁻\u0026sup1; to 0.90 t ha⁻\u0026sup1; and 0.80 t ha⁻\u0026sup1;. The highest salinity (16 dS m⁻\u0026sup1;) caused sharp declines to 0.60 t ha⁻\u0026sup1; (Nachit) and 0.55 t ha⁻\u0026sup1; (Faraj). Duncan\u0026rsquo;s post hoc test identified four distinct groups, confirming a progressive decrease in straw yield with increasing salinity, while Nachit maintained higher values than Faraj under moderate and high salinity conditions.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e\u003cb\u003e3.7. Relationships between grain performance and irrigation salinity in durum wheat\u003c/b\u003e\u003c/h2\u003e\u003cp\u003eAcross all salinity treatments, salinity concentration was inversely related to the yield traits of durum wheat \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e7\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003eGrain yield exhibited the strongest response to increasing salinity, with a correlation value of r = -0.95 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), reflecting a very high sensitivity of overall productivity to NaCl stress. Similarly, 200-grain weight was markedly affected, showing a strong inverse relationship with salinity (r = -0.93; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), indicating that grain filling and individual grain development are highly impacted by elevated salt levels. Straw yield also declined with increasing salinity (r = -0.87; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), although the reduction in vegetative biomass was somewhat less severe than that observed for grain yield and 200-grain weight.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e3.8. Heatmap of correlations between soil chemical parameters, growth traits, and yield components in durum wheat.\u003c/h2\u003e\u003cp\u003eThe heatmap of correlations among soil parameters, growth traits, and yield components in durum wheat under increasing salinity levels (\u003cb\u003eFigue 8)\u003c/b\u003e highlighted distinct relationships between the measured variables.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eEC, Na, and Cl were strongly and positively correlated with each other, while exhibiting significant negative correlations with plant height (Pth), chlorophyll fluorescence (ChlF), number of leaves (NoL), grain yield (GY), 200-grain weight (200-GW), and straw yield (SY). Among yield components, GY and 200-GW displayed a strong positive correlation, and a moderate positive correlation was observed between 200-GW and SY. Potassium (K) was positively and strongly correlated with growth traits (Pth, ChlF, NoL) across all salinity levels, whereas its correlations with yield components were weakly positive. Similarly, calcium (Ca) exhibited strong positive correlations with vegetative traits, while correlations with GY, 200-GW, and SY were slightly negative under higher salinity. Magnesium (Mg) showed moderate positive correlations with growth traits and weak positive correlations with GY and 200-GW. Growth traits themselves were consistently positively correlated with yield components, with ChlF exhibiting particularly strong positive correlations with Pth, NoL, and GY. Number of leaves (NoL) was positively correlated with GY, 200-GW, and SY, while plant height (Pth) was moderately positively associated with all yield components.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e3.9. Principal Component Analysis revealing the relationships among soil chemistry, growth, and yield under salinity.\u003c/h2\u003e\u003cp\u003eThe principal component analysis (PCA) was conducted to explore the relationships among soil chemical properties, growth traits, and yield components of durum wheat under different salinity levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn this PCA, the observations corresponded to the two durum wheat varieties (Faraj and Nachit) evaluated under five salinity levels (I0, I1, I2, I3, and I4 dS m⁻\u0026sup1;), resulting in a total of ten observation points. Each point represents the combined response of one variety under a specific salinity treatment. To ensure data suitability given the limited number of observations, six key varia-bles were selected: EC, K, Pth, ChlF, GY, and 200-GW. PCA was applied as an explora-tory multivariate tool to visualize associations and identify the most discriminating factors influencing plant performance under saline conditions. The first three principal components had eigenvalues\u0026thinsp;\u0026ge;\u0026thinsp;1 and together explained 90.33% of the total variation,ensuring a robust representation of the dataset. PC1 (52.42%) represented the performance and yield axis, being strongly and positively as-sociated with Pth, ChlF, GY, and 200-GW. The EC vector was nearly perpendicular to this axis, suggesting that PC1 primarily reflects plant performance rather than direct salinity intensity. PC2 (25.68%) was mainly influenced by K, which showed a positive association with Pth, indicating its modulatory role in supporting plant growth under salinity stress. Conversely, EC contributed negatively to this axis, reflecting the contrasting behavior of salinity and nutrient availability. PC3 (12.43%) accounted for additional minor variability without altering the main relationships observed along PC1 and PC2Overall, the PCA clearly high-lighted the antagonistic relationship between EC and the performance-related traits (ChlF, GY, and 200-GW).\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe germination and early seedling growth stages constitute crucial phases in the plant life cycle and are highly vulnerable to the quality of irrigation water, particularly its salinity.The impact of salt stress on durum wheat during these stages is reflected through several key indicators such as GP, DGP, GSI, MGT, RL, and CL. These early responses are influenced by both genetic predispositions and environmental cues, which together shape the seed\u0026rsquo;s capacity to initiate growth under optimal conditions. Elevated salinity often disrupts physiological balance, primarily due to ion toxicity and osmotic effects, which hinder water uptake and impair metabolic activity essential for germination and seedling development [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. Salinity induces osmotic stress that restricts water uptake by seeds and causes ionic toxicity, primarily as a result of the high accumulation of Na⁺ and Cl⁻ ions. These conditions disrupt nutrient balance and interfere with essential metabolic processes such as germination, thereby reducing GP and GSI, and ultimately impairing seed vigor and early seedling development.\u003c/p\u003e\u003cp\u003eSuch physiological and biochemical disruptions have been widely reported in plants under saline conditions [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e], and are particularly well documented in wheat, where salinity constitutes a major constraint during early growth stages [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. In this experiment, elevated salinity levels in irrigation water led to a clear reduction in GP for both Faraj and Nachit varieties of durum wheat. However, at 8 dS m⁻\u0026sup1;, both genotypes maintained germination rates above 75%, suggesting a moderate level of salt tolerance, with Nachit exhibiting a slight edge in performance. This better response under intermediate salinity suggests an improved physiological adjustment. Differences in salinity tolerance among genotypes have also been documented in other studies involving tetraploid wheat under controlled conditions, emphasizing the relevance of early-stage physiological indicators for selecting salt-resilient lines [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. Comparable variability in salt stress response at the germination stage has also been noted in other cereal species, reinforcing the relevance of early screening methods across diverse crop type, supporting the broader applicability of screening approaches across cereal crops [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. Comparatively, studies on sorghum have demonstrated similar trends, where elevated salt concentrations delay germination and reduce seedling growth [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. Salinity imposes osmotic and ionic stresses that affect physiological processes such as leaf water potential, stomatal conductance, and evapotranspiration, ultimately reducing crop yield. Wheat is classified among salt-tolerant crops based on soil salinity and water stress indices [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eA similar trend was observed for root length (RL) and coleoptile length (CL), both progressively decreasing with increasing saline concentrations in the irrigation water for the Faraj and Nachit varieties. This reduction is widely reported across various species, as roots are the first organs to encounter salinity stress and play a crucial role in water uptake and its transport to aerial parts [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. Moreover, salinity stress often inhibits cell expansion and division, thereby limiting elongation of both roots and coleoptiles in the Faraj and Nachit varieties under increasing saline irrigation. As roots are the first organs exposed to salinity, their early development is crucial for plant adaptation. Root branching and growth are tightly regulated processes involving genetic and hormonal controls that determine root length and function [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]. The more pronounced reduction in root length compared to coleoptile length observed in this study could be attributed to the higher sensitivity of root tissues to NaCl toxicity. This is consistent with findings in finger millet showing that salinity stress causes significant growth reduction and cellular damage in both coleoptile and root tissues, with roots being particularly affected under increasing NaCl concentrations [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. These findings underline the importance of early root development as a critical factor for salinity tolerance in durum wheat and suggest that selecting genotypes with better root growth under saline irrigation could improve crop performance in salt-affected areas [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eOverall, irrigation with fresh water promotes the best growth performance in durum wheat. The results indicate that sensitivity to salinity increases as the plant develops. Early growth stages, particularly tillering and stem elongation, are relatively less affected by moderate salinity levels (4\u0026ndash;8 dS m⁻\u0026sup1;), with the Nachit variety demonstrating greater tolerance. However, at later stages such as heading and maturity, growth is significantly reduced under high salinity conditions (12\u0026ndash;16 dS m⁻\u0026sup1;), although Nachit maintains a slight advantage over Faraj. These findings align with previous studies highlighting that salinity induces osmotic and ionic stress, which limits water uptake and results in more pronounced growth retardation during advanced developmental stages [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. Moreover, the number of leaves also decreases as salinity levels increase. At 0.2 dS m\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, both varieties develop the maximum number of leaves, whereas at 16 dS m⁻\u0026sup1;, a significant reduction is observed. This decline reflects the plants\u0026rsquo; limited ability to sustain leaf growth under salt stress, likely due to disruptions in the cell cycle and a reduction in cell division within actively growing tissues, as reported in various plant species [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e]. Additionally, this reduction in leaf number may be associated with ionic imbalances, particularly increased competition between Na\u003csup\u003e+\u003c/sup\u003e and K\u003csup\u003e+\u003c/sup\u003e, leading to nutrient deficiencies that restrict foliar development [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e]. Increased salinity was also associated with a marked reduction in chlorophyll fluorescence values (Fv/Fm), reflecting a decline in the efficiency of the photosynthetic machinery, particularly in the functioning of photosystem II. Our results show that plants exposed to low salinity maintain values close to optimal, whereas high NaCl concentrations (12\u0026ndash;16 dS m⁻\u0026sup1;) cause a marked decline in Fv/Fm, reflecting substantial photosynthetic stress. This phenomenon is well-documented in the literature; for instance [\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e] ,demonstrated that chlorophyll fluorescence is a reliable indicator of salt-induced alterations in photosynthesis, particularly in relation to PSII activity and energy dissipation. Similarly, reductions in the peak photochemical efficiency of photosystem II, measured as Fv/Fm, under high NaCl concentrations have been observed in salt-sensitive genotypes of rice [\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e], soybean [\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e], and barley, where [\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e] reported significant fluorescence changes in response to combined salt and high-light conditions. These findings support the use of chlorophyll fluorescence as a non-invasive and effective screening tool for salinity tolerance. Advanced approaches such as kinetic chlorophyll fluorescence allow more precise quantification of photosynthetic performance under stress, highlighting the importance of physiological traits like non-photochemical quenching and quantum yield, which play critical roles in salt stress tolerance [\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e]. These indicators can therefore aid in identifying and selecting more resistant genotypes in breeding programs that combine high-resolution phenotyping with genomic analyses [\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn addition to physiological parameters, the assessment of grain yield and its components is a crucial indicator for evaluating tolerance to salinity stress under agronomic conditions. The results indicate that both varieties maintain a tolerance threshold at 8 dS m⁻\u0026sup1; for grain yield, which begins to decline beyond this salinity level, highlighting the heightened sensitivity of this trait. In contrast, the 200-grain weight and straw yield are only significantly impacted starting from 12 dS m⁻\u0026sup1;, demonstrating greater stability of these components under saline conditions, with the variety Nachit showing a slight advantage over Faraj. Numerous studies have highlighted that abiotic stresses, particularly salinity, pose a major challenge significantly reducing crop yields, especially during the reproductive stage, which is critical for agricultural productivity [\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e]. At this crucial phase, plants activate key physiological mechanisms, such as the partial exclusion of sodium from the leaves, to maintain ion homeostasis [\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e]. This regulation is especially important as the potassium-to-sodium ratio and grain dry matter content are strongly correlated with the rate and duration of grain filling under salt stress, directly influencing both yield quantity and quality [\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e]. Furthermore, saline irrigation imposes significant stress on crop growth and yield by disrupting water relations, nutrient uptake, and stomatal function, while inducing oxidative damage that collectively contribute to marked declines in productivity [\u003cspan additionalcitationids=\"CR86\" citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e]. Salinity alters the plant\u0026rsquo;s morpho-physiological and biochemical pathways, leading to reduced photosynthetic efficiency, lower biomass accumulation, and impaired source-sink interactions, which in turn accelerate the aging process of reproductive organs [\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e]. This is particularly evident during key reproductive stages, such as anthesis and grain filling, when decreased water availability induces structural changes in leaves including thinner flag leaves and smaller mesophyll cells that negatively impact leaf area, turgor pressure, and assimilate synthesis, ultimately limiting yield potential [\u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e]. The severity of salinity effects varies by developmental stage, with grain yield reductions of approximately 39.1%, 24.3%, and 13.4% observed at flowering, initial booting, and mid-grain filling stages, respectively [\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e]. Moreover, salinity impairs grain quality and nutrient content, diminishing components such as gluten, fiber, ash, and essential minerals including Mg, P, Ca, Zn, K, and Fe [\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e, \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e]. In some species like Brassica oleracea var. capitata, yield reductions of up to 62% have been documented at moderate salinity levels of 8 dS m⁻\u0026sup1; [\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e]. Together, these physiological disturbances and declines in grain quality highlight the profound detrimental effects of salinity on crop reproductive success and overall productivity [\u003cspan additionalcitationids=\"CR95\" citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e96\u003c/span\u003e]. Furthermore, salinity compromises stomatal regulation and nitrogen metabolism, further limiting biomass and yield [\u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e, \u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e98\u003c/span\u003e]. It also reduces photosynthesis, water use efficiency, and plant vigor during critical reproductive phases, thereby reducing the overall yield as well as its quality [\u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e]. Overall, these multifaceted impacts underscore the major challenge salinity poses for sustainable agricultural productivity.\u003c/p\u003e\u003cp\u003eThe results from the heatmap and principal component analysis (PCA) highlight strong correlations between soil parameters (EC, Na, K, Ca, Mg, Cl) and the growth traits and yield components of durum wheat (Pth, ChlF, NoL, GY, 200-GW, SY), clearly revealing the detrimental impact of salinity on agronomic performance. Increases in Na and Cl concentrations, along with elevated soil EC, are strongly associated with significant reductions in growth parameters such as Pth, NoL, and ChlF, as well as major yield components, including GY, 200-GW, and SY. These findings are consistent with those of [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], who demonstrated that salinity hinders crop growth and reduces yield through combined osmotic and ionic effects. Previous studies have also demonstrated that irrigation with saline water reduces spike formation [\u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e100\u003c/span\u003e] and grain weight [\u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e101\u003c/span\u003e], resulting in a reduction of the final yield [\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e, \u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e103\u003c/span\u003e]. reduction of up to 90% in grain yield of durum wheat under a salinity level of 15 dS m⁻\u0026sup1; has been reported, in contrast to our findings, which show an average yield decrease of approximately 40% at 10 dS m⁻\u0026sup1; and 62% at 15 dS m⁻\u0026sup1;, highlighting a substantial degree of genetic variability in salinity tolerance [\u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e104\u003c/span\u003e]. Moreover, chlorophyll fluorescence emerges as a reliable indicator of plant response to salt stress, as it is closely correlated with growth traits and overall productivity. Although leaf chlorophyll content showed a slight decline under saline conditions, this reduction remained moderate and may be offset by morphological adaptations, such as increased leaf thickness, which could help maintain photosynthetic capacity despite the stress [\u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e105\u003c/span\u003e, \u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e106\u003c/span\u003e]. Finally, the presence of specific nutrients, particularly potassium (K) and magnesium (Mg), appears to influence plant responses to salinity. These elements are crucial for osmotic control, membrane stabilization, and photosynthetic activity, offering a promising avenue to alleviate the negative impacts of salt damage through optimized nutrient management [\u003cspan additionalcitationids=\"CR108\" citationid=\"CR107\" class=\"CitationRef\"\u003e107\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e109\u003c/span\u003e].\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study aimed to thoroughly and comparatively evaluate how two local durum wheat varieties, Faraj and Nachit, respond to different salinity levels in irrigation water applied to silty-clay soil. By analyzing the effects of salt stress from germination to final yield, the study sought to deepen the understanding of underlying physiological and agronomic mechanisms, identify critical thresholds of tolerance, and provide a solid foundation for varietal selection and the optimization of agronomic practices under saline conditions ultimately enhancing the resilience and sustainability of cereal-based systems in arid and semi-arid regions. These findings are part of a broader framework in which plant adaptive responses to salinity rely on a dynamic coordination of key physiological mechanisms, including root-to-shoot signaling, water regulation, photosynthetic maintenance, and ion homeostasis. The Faraj and Nachit varieties stood out for their ability to limit toxic ion accumulation while preserving essential nutrients, making them promising candidates for breeding programs targeting traits associated with salt tolerance.\u003c/p\u003e\u003cp\u003eTo build on these advances, it is essential to adopt multidisciplinary approaches that integrate genomics, physiology, and agronomic management in order to better unravel the molecular and physiological bases of salt tolerance. Simultaneously, promoting tailored cultural practices such as improved irrigation management, the use of organic amendments, and farmer awareness of salt-tolerant varieties is vital for mitigating the adverse effects of salinity. Together, these efforts will contribute to sustainably improving durum wheat productivity and quality while supporting food security in vulnerable regions, particularly in a global context marked by shrinking freshwater resources and the increasing salinization of soils and irrigation water. The results indicate that salinity progressively affects germination, with moderate tolerance observed up to 8 dS m⁻\u0026sup1;. Nachit exhibited a greater ability to maintain high germination rates under saline stress compared to Faraj, suggesting a higher aptitude for overcoming challenging initial conditions. During the vegetative stages, plant growth measured through height, leaf number, and chlorophyll fluorescence (Fv/Fm) showed some resilience to salinity during tillering and stem elongation. However, at heading and maturity, the negative impacts became more pronounced, with significant reductions in photosynthesis and overall vigor, thereby compromising final productivity. Regarding yield components, both varieties tolerated salinity levels up to 12 dS m⁻\u0026sup1; for 200-grain weight and biomass, while grain yield began to decline at 8 dS m⁻\u0026sup1;. Nachit outperformed Faraj, notably due to its more efficient regulation of toxic ion (Na⁺, Cl⁻) accumulation and superior retention of essential nutrients such as K⁺, Ca\u0026sup2;⁺, and Mg\u0026sup2;⁺. These findings align with a broader framework in which plant adaptive responses to salinity stress rely on the dynamic coordination of key physiological mechanisms, including root-to-shoot signaling, water regulation, sustained photosynthetic activity, and ion homeostasis. The Faraj and Nachit varieties demonstrate a notable capacity to limit the accumulation of toxic ions while preserving essential nutrients, positioning them as promising candidates for breeding programs targeting physiological traits associated with salt tolerance. To advance these findings, it is essential to adopt multidisciplinary approaches that integrate genomics, plant physiology, and agronomic management in order to better elucidate the foundations of salt tolerance. In parallel, the implementation of appropriate agronomic strategies such as improved irrigation practices, the application of organic amendments, and enhanced farmer awareness of tolerant varieties is crucial to mitigating the adverse effects of salinity. Together, these combined efforts will help ensure the sustainable improvement of durum wheat productivity and quality, while reinforcing food security in a context increasingly challenged by the depletion of freshwater resources and the rising salinization of soils and irrigation water.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eConflict of interest:\u003c/h2\u003e\u003cp\u003eThe authors declare that they have no known financial conflicts of interest or personal relationships that could have influenced the work. that would appear to affect the work reported in this manuscript.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eEthical approval:\u003c/h2\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent to participate:\u003c/strong\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent to publish:\u003c/strong\u003e\u003cp\u003eAll authors have read and approved the final version of this manuscript for submission and publication.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e\u003cp\u003eThis study received funding from the \u0026ldquo;MCGP\u0026rdquo; project, supported by INRA and ICARDA\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e\u003cp\u003eThe authors sincerely thank all collaborators who contributed to this work, including the teams involved in field sampling, laboratory analyses, and manuscript preparation at the National Institute of Agricultural Research (INRA), the Research Unit for Environment and Conservation of Natural Resources (URECRN), and the International Center for Agricultural Research in the Dry Areas (ICARDA) in Morocco. We are also grateful to the \u0026ldquo;MCGP\u0026rdquo; project (INRA and ICARDA) and the EiA Climber project for their valuable financial and technical support.\u003c/p\u003e\u003ch2\u003eData Availability:\u003c/h2\u003e\u003cp\u003eData supporting the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKhondoker, M.; Mandal, S.; Gurav, R.; Hwang, S. Freshwater Shortage, Salinity Increase, and Global Food Production: A Need for Sustainable Irrigation Water Desalination\u0026mdash;A Scoping Review. \u003cem\u003eEarth\u003c/em\u003e \u003cstrong\u003e2023\u003c/strong\u003e, \u003cem\u003e4\u003c/em\u003e, 223\u0026ndash;240, doi:10.3390/earth4020012.\u003c/li\u003e\n\u003cli\u003eManchanda, G.; Garg, N. 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Machine Learning-Integrated Hydrogeochemical and Spatial Modeling of Groundwater Quality Indices for Seawater Intrusion and Irrigation Sustainability in Coastal Agroecosystems of Skhirat Region, Morocco. \u003cem\u003eJournal of Hydrology: Regional Studies\u003c/em\u003e \u003cstrong\u003e2025\u003c/strong\u003e, \u003cem\u003e62\u003c/em\u003e, 102848, doi:10.1016/j.ejrh.2025.102848.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Durum wheat, Saline irrigation, Germination, Plant growth, Yield components","lastPublishedDoi":"10.21203/rs.3.rs-7909033/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7909033/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eFreshwater scarcity in arid and semi-arid regions forces farmers to rely on saline irrigation, challenging crop productivity and sustainability. Durum wheat, a staple cereal crucial for food security, is highly sensitive to salinity, particularly during early growth. This study compared responses of two local Moroccan durum wheat varieties, Faraj and Nachit, grown on silty-clay soil under five salinity levels (0.2, 4, 8, 12, and 16 dS m⁻\u0026sup1;) in a randomized complete block design with three replications, aiming to identify tolerance thresholds and characterize physiological and agronomic responses. Key traits measured included germination percentage (PG), germination stress index (GSI), mean germination time (TMG), root length (RL), coleoptile length (CL), plant height, number of leaves, chlorophyll fluorescence (ChlF, Fv/Fm), grain yield (GY), 200-grain weight (200-GW), and straw yield (SY). Results showed PG declined markedly from 8 dS m⁻\u0026sup1;, with ISG decreasing and TMG increasing, indicating delayed germination. Vegetative growth was inhibited with higher salinity, affecting RL, CL, plant height, number of leaves, and ChlF. Both varieties maintained GY up to 8 dS m⁻\u0026sup1; and SY, 200-GW up to 12 dS m⁻\u0026sup1;, with Nachit exhibiting superior resilience. At 16 dS m⁻\u0026sup1;, yield components declined sharply. Multivariate analyses (PCA and heatmaps) revealed strong correlations between electrical conductivity, Na, and Cl with reduced growth and yield, while K, Ca, and Mg correlated positively with vigor and productivity. These findings highlight the comparative performance of Faraj and Nachit and support their use in breeding programs and irrigation strategies to sustain durum wheat production under saline conditions.\u003c/p\u003e","manuscriptTitle":"Comparative assessment of saline irrigation effects on germination, physiological responses, growth, and yield of durum wheat varieties grown on silty clay soil","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-22 06:00:44","doi":"10.21203/rs.3.rs-7909033/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"67a24f46-6077-4ec0-85c2-c11ae6bb5124","owner":[],"postedDate":"October 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":56606562,"name":"Agronomy"}],"tags":[],"updatedAt":"2025-10-22T06:00:44+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-22 06:00:44","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7909033","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7909033","identity":"rs-7909033","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}