The interplay of salinity stress and nitrogen management on gas exchange in quinoa

Abstract

This study evaluates the quinoa physiological responses to varying irrigation water salinity levels and nitrogen application rates. Over two years, a field experiment was conducted at Shiraz University in Iran using a Factorial Randomized Block Design with three replications to investigate the combined effects of irrigation water salinity levels (5, 10, 20, and 25 dS m⁻¹) and nitrogen rates (0, 150, and 300 kg N ha⁻¹). The study focused on key parameters, including gas exchange, leaf area index, leaf water potential, and root characteristics. The results indicated that the maximum leaf area index (LAI_max) decreased by 25% in 25 dS m⁻¹ compared to 5 dS m⁻¹, with no significant differences between 5 and 10 dS m⁻¹. Photosynthesis rate (A_n) reduced by 20% and 23% at 20 and 25 dS m⁻¹, respectively, compared to 5 dS m⁻¹, with minimal differences between 5 and 10 dS m⁻¹ or 20 and 25 dS m⁻¹. It also increased by 20% in 150 kg N ha⁻¹ and 43% in 300 kg N ha⁻¹ compared to non-fertilized control. Stomatal conductance (g_s) in 5 dS m⁻¹ increased by 25% and 100% by N application rate of 150 and 300 kg N ha⁻¹, respectively. The 300 kg N ha⁻¹ treatment improved g_s under salinity levels (5, 10, 20, and 25 dS m⁻¹) by 100%, 136%, 64%, and 70%, respectively, compared to non-fertilized crop. Leaf transpiration rate was enhanced by 10% in 150 kg N ha⁻¹ and 38% in 300 kg N ha⁻¹ compared to non-fertilized treatments. Therefore, although salinity harmed gas exchange parameters, nitrogen application mitigated the negative effect and improved these parameters. Despite these improvements, the 300 kg N ha⁻¹ treatment reduced water-use efficiency (A_n/g_s) due to disproportionately higher increases in g_s and leaf transpiration (T_r) compared to A_n. Leaf water potential was stable in salinity levels of 5 and 10 dS m⁻¹ but decreased significantly by 9% and 12% in 20 and 25 dS m⁻¹, respectively. Our findings showed a significant reduction in root length and weight density (RLD and RWD, respectively) in salinity above 10 dS m⁻¹, with greater reductions in higher salinity levels. Generally, higher salinity levels reduced RLD and RWD; however, applying higher nitrogen rates mitigated this negative effect. For instance, in salinity level of 25 dS m⁻¹, RLD and RWD decreased by 68% and 22% in non-fertilized treatments, respectively, whereas in fertilized treatments, the reduction was only 50%.

Introduction

Global food security is increasingly threatened by climate change, soil degradation, and water scarcity, which necessitate the exploration of resilient crops capable of thriving under harsh environmental conditions. Quinoa (Chenopodium quinoa Willd.), a highly nutritious pseudocereal [1–3], has received significant attention [4–6] due to its remarkable tolerance to salinity [7–11], drought [12–16], and poor soils [4, 17–19], which are important factors in limiting crop yields. Its ability to sustain yields under adverse conditions makes quinoa a promising candidate for sustainable agriculture in marginal lands and environments [20, 21]. It is also known for its remarkable adaptability to salinity [22] and offers a promising solution to mitigate the adverse effects of salinity, particularly in water-limited areas [23, 24]. These adjustments include the absorption and sequestration of salt ions in tissues and the osmotic adjustment that helps adjust leaf water potential. This adjustment maintains cell turgor and limits transpiration under saline conditions, thereby enabling the plant to thrive in high-salinity soils [10, 11, 25].

Irrigation with saline water is often unavoidable in arid and semi-arid regions where freshwater resources are scarce. It is crucial to explore ways to diminish the potential effects of salinity as a major limiting factor on photosynthesis and plant growth [26]. Salinity decreases total soil water potential due to the osmotic impacts [27] limits plant access to the soil water, and has toxic effects on crop growth and development by disrupting various physiological and biochemical processes, including nutrient uptake and assimilation [28]. Salinity affects plants through both ionic and osmotic mechanisms [29, 30]. The osmotic impact manifests immediately after salt exposure, leading to inhibited cell expansion and division, as well as stomatal closure [31, 32]. Salt stress disrupts various physiological processes at the leaf level, including enzyme activity, photosynthesis, and gas exchange. Specifically, it reduces stomatal and mesophyll conductance, lowering photosynthetic activity and efficiency [33–35]. In this regard, Razzaghi et al. [36] reported limited stomatal conductance and photosynthesis of quinoa because of both salinity and drought stress with increasing water-use efficiency. Talebnejad and Sepaskhah [37] evaluated the effects of saline groundwater depths and irrigation water salinity on quinoa and found a significant decrease in leaf water potential with rising salinity level leading to stomatal closure below − 1.0 MPa. Besides, the photosynthesis rate (An) dropped by 48% as water salinity increased from 10 to 40 dS m⁻¹, with stomatal conductance (gs) showing greater sensitivity to salinity than An. Roots growth was also affected by salinity and root length density declined at high levels of water salinity. Eisa et al. [38] discussed the salinity tolerance mechanisms of quinoa and realized that despite high salinity, the plant reduced its leaf water potential below soil water potential by accumulating Na⁺ and Cl⁻, maintaining favorable ion balances in roots and young leaves. High salinity severely reduced photosynthesis to 28% of control at 500 mM NaCl and growth, primarily due to impaired photosynthetic capacity, although water use efficiency improved. Quinoa demonstrated significant salt tolerance, supporting productive growth under moderate salinity up to 200 mM NaCl. While quinoa demonstrates impressive adaptability to salinity, understanding the physiological mechanisms that enable this tolerance is critical for optimizing its productivity.

Moreover, nitrogen (N) is a key nutrient influencing plant growth and stress responses [39–41]. Appropriate nitrogen management may mitigate the adverse effects of salinity [42, 43] by enhancing physiological traits such as photosynthesis, water-use efficiency, and ion balance. Alandia et al. [44] highlighted the interdependence of water status and gas exchange in quinoa, with N fertilization affecting both processes. They found greater stomatal conductance and more negative leaf water potential (greater water stress) in fertilized plants than in non-fertilized plants. However, excessive or insufficient nitrogen application can exacerbate stress, underscoring the need for balanced fertilization strategies.

Previous investigations focused on physiological response of quinoa to water stress [13], N fertilization [44] or irrigation water salinity [37] separately. Therefore, studying the simultaneous and interacting effect of irrigation water salinity and Nitrogen application rate on quinoa cultivation is a current knowledge gap in quinoa production in saline environments with scares water resources. Therefore, this study aims to evaluate the physiological responses of quinoa to different irrigation water salinity levels and nitrogen rates. By analyzing key parameters such as gas exchange, leaf area index and water potential, and root growth parameters, the research seeks to unravel how these factors interact to influence quinoa’s growth and productivity. The novelty of these findings will contribute to the development of effective management practices for cultivating quinoa in saline environments, providing valuable insights for sustainable agriculture in water-scarce regions.

Materials and methods

Field site and experimental layout

eld site and experimental layout A two-year field experiment (2020–2021) was conducted at the Experimental Research Station of the School of Agriculture, Shiraz University, Iran. The site is located in a semi-arid region (29º56′N, 52º02′E) at an elevation of 1810 m above mean sea level. Climatic conditions for the experimental period are illustrated in Fig. 1, which includes the maximum and minimum daily temperatures (T_max and T_min) and average relative humidity (RH_ave). During the first growing season, the average Tmax and Tmin were 34.2 °C and 13.6 °C, respectively. The second growing season was slightly warmer, with corresponding averages of 34.9 °C and 14.2 °C.

Fig. 1.

Daily maximum and minimum air temperature (T_max, T_min), and mean relative humidity (RH_avg) during both growing periods. a: 2020; b: 2021

The experiment followed a factorial arrangement in a randomized complete block design with 12 treatments (3 × 4) and three replications. Treatments consisted of four salinity levels of irrigation water: 5, 10, 20, and 25 dS m⁻¹ (designated as S1, S2, S3, and S4), and three nitrogen application rates: 0, 150, and 300 kg N ha⁻¹ (denoted as N0, N1, and N2). The study was carried out in 36 pre-constructed water balance lysimeters (Tarah Gostar Ab Ara, Tabriz, Iran), each with a dimension of 1.5 × 1.5 × 1.1 m, and a 0.05 m gravel layer was placed at the bottom, topped with 1.0 m of soil. The physical and chemical properties of the soil (Silty caly loam) are summarized in Table 1. Each lysimeter was equipped with a drainage tube to collect leachate.

Table 1.

Soil physical and chemical properties

Physical and chemical properties	Soil depth (cm)
	0–30	30–60	60–90
Sand (%)	35	23	21
Silt (%)	35	38	39
Clay (%)	30	39	40
Field capacity (cm cm− 3)	0.32	0.34	0.36
Permanent wilting point (cm cm− 3)	0.11	0.14	0.16
Bulk density (g cm− 3)	1.39	1.44	1.47
ECe	0.9	0.73	0.78
pH	8.26	8.46	8.18
Cl− (meq l− 1)	9.00	10.00	11.60
Na+ (meq l− 1)	1.60	2.10	2.40
Ca2+ (meq l− 1)	2.60	3.00	3.80
HCO3− (meq l− 1)	4.10	4.00	3.80
Organic matter (%)	1.2	1.2	1.2

Before planting, 30 kg ha⁻¹ of triple super-phosphate was manually incorporated into the soil surface. Five ridges, spaced 0.3 m apart, were formed, and quinoa seeds (Titicaca cultivar) were sown at a density of 22 kg ha⁻¹ and a depth of 0.02 m. Sowing dates were May 4th, 2020 in the first year and May 5th, 2021 in the second year. Throughout the growing season, weeds were controlled manually every two weeks, and Diazinon pesticide (0.1%) was applied to protect against pests, including Thrips and Nysius cymoid. Nitrogen applications (urea, 46% N) were split into two stages and applied to the soil surface before irrigation: one half during the vegetative stage and the other half at the seed-filling stage. The second application occurred 50 and 57 days after sowing in the first and second growing seasons, respectively.

Irrigation requirements and field data collection

The irrigation requirement was estimated based on the net irrigation depth (calculated using the equation below) with an irrigation application efficiency of 70%, applied at a 7-day interval as furrow irrigation. Before each irrigation event, soil water content was measured using a neutron meter (ICT International, Armidale, Australia) at depths of 0.3, 0.6, and 0.9 m.

1

Where d is the irrigation depth (m), ∆z_i represents the thickness of each soil layer within the root zone (m), θ_fci and θ_i (m^− 3 m^− 3) are the soil volumetric field capacity and soil water content at each soil layer, respectively; n is the total number of soil layers, and i denotes the specific soil layer number. In this study, root depth is estimated by the Borg and Grimes equation. Therefore, the root depth was estimated as following equation (Borg and Grimes 1986):

2

Where R_d, R_dmin and R_dmax are the root depth, the quinoa planting depth and the maximum root depth (m); D_ag and D_tm are the number of days after first irrigation and the number of days after first irrigation that root reaches the maximum depth, respectively.

To prepare the desired salinity levels in the irrigation water, a mixture of CaCl₂ and NaCl in equal proportions (on an equivalent weight basis) was added to freshwater. Salinity treatments began 35 days after sowing in the first growing season and 45 days after sowing in the second. The total water applied during the growing season was 1015 mm and 1007 mm in the first and second year, respectively. No rainfall occurred during the growing seasons of either year.

During the growing season, one plant for each treatment was selected to measure leaf length and width for all the green leaves. The leaf area index (LAI) was then calculated using the equation proposed by Talebnejad and Sepaskhah [45] for the quinoa leaf area (LA, cm²) as follows:

3

4

Where L and W represent the leaf length and width in cm, A denotes the total leaf area of a plant and, A_c refers to the occupied area by each plant (in cm²).

For each plot, three plants located in the middle of the plot were selected and one fully expanded leaf at the top of the palnt was used for physiological measurements. Following the initiation of salinity treatment, a fully expanded leaf was selected every two weeks to measure leaf water potential (LWP) using a pressure chamber (PMS Instrument Company, Model 1000, Albany, Oregon, USA). Measurements were conducted between 1:00 and 3:00 p.m., prior to irrigation when the crops experienced the highest water stress. In addition, gas exchange parameters, such as net photosynthesis rate (A_n), stomatal conductance (g_s), and leaf transpiration rate (T_r) were assessed twice during the growing season using an LCi analyzer (Li-Cor Inc., Nebraska, USA) when crops were at the highest water stress.

Quinoa was harvested 10 to 14 days after the last irrigation event, on August 21, 2020, and August 20, 2021. The upper parts of the plants were collected, and the panicles were removed and threshed. Following this the seeds, stems, and leaves were oven-dried at 72 °C for approximately 48 to 72 h to assess seed yield, straw dry weight, and total dry matter.

At the end of the growing season, an auger (include internal diameter of the auger) was placed on stubbles and driven into the soil, and three soil samples for each plot were collected from 0 to 30 cm, 30–60 cm, and 60–90 cm to measure root distribution. The samples were stored in plastic bags at − 20 °C. The soil samples were washed following the methods that Ahmadi et al. [46] described to separate the roots from soil particles and other organic matter. Root length (m) was estimated using the Newman method [47] and subsequently, root length density (RLD, m m^{− 3}), root mass density (RMD, kg m^{− 3}), and specific root length (SRL; the ratio of RLD to RMD) were calculated based on the soil section volume.

Statistical analysis

Statistical analyses were performed using SAS software. The interaction effects of irrigation water salinity levels and nitrogen (N) application rates were evaluated through analysis of variance. Normality and homogeneity of variance were tested prior to analysis. Additionally, it is specified that a two-way ANOVA was performed. Mean comparisons were conducted using Duncan’s multiple range test at a 5% significance level.

Results

Leaf area index

Since the interaction effect between irrigation water salinity and nitrogen application rates was insignificant (Table 2), only the main effects were presented. Table 3 represents the two-year average values for the maximum leaf area index (LAI_max). In this study, LAI_max refers to the maximum Leaf Area Index measured when the canopy is fully developed. Increasing irrigation water salinity to 25 dS m^− 1 reduced LAI_max by 25% compared to 5 dS m⁻¹. However, LAI_max remained relatively unchanged between 5 and 10 dS m⁻¹ salinity levels. The highest LAI_max among the salinity treatments was recorded in S1 (5 dS m⁻¹) at 3.12. In contrast, increasing N application rates significantly enhanced LAI_max, with 300 kg N ha^− 1 producing the highest LAI_max of 3.63. Applying 150 and 300 kg N ha^− 1 increased LAI_max by 56% and 94%, respectively, compared to no nitrogen application. These findings suggest that quinoa can tolerate salinity levels up to 20 dS m⁻¹, and higher N rates can enhance crop development under saline conditions.

Table 2.

Two- way analysis of variance of different water salinity levels and N application rates for maximum leaf area index (LAI_max), leaf water potential (LWP), photosynthesis rate (A_n), and leaf transpiration rate (T_r), stomatal conductance (g_s), leaf transpiration efficiency (A_n/T_r), and intrinsic water use efficiency (A_n/g_s), mean root length density (RLD), root weight density (RWD), and specific root length density (SRL)

Variable				N application rate (N)	Water salinity (S)	N×S
df				3	2	6
Trait
LAI max		Mean squares		18.98	2.18	0.32
		F-value		37.96**	4.36**	0.64 ns
LWP		Mean squares		0.12	0.21	0.035
		F-value		5.06*	8.79**	1.47 ns
An		Mean squares		32.88	14.5	0.79
		F-value		75.33**	33.22**	1.82 ns
Tr		Mean squares		14.98	2.15	0.20
		F-value		43.36**	6.22**	0.58 ns
gs		Mean squares		0.03	0.005	0.001
		F-value		205.21**	31.55**	7.13**
An/Tr		Mean squares		0.034	0.12	0.05
		F-value		1.80 ns	6.42 **	2.93 *
An/gs		Mean squares		116.65**	60.78	229.9
		F-value		18.67**	1.02 ns	3.84*
RLD		Mean squares		4.76	8.32	0.43
		F-value		39.77**	69.44**	3.61**
RWD		Mean squares		3.60	1.64	0.23
		F-value		64.78**	29.60**	4.21**
SRL		Mean squares		0.38	0.55	0.45
		F-value		4.54*	6.57**	5.36**

^ns not significant 

^**Significant at the 0.01 probability level

^*Significant at the 0.05 probability level

Table 3.

The two-year mean maximum leaf area index (LAI_max), leaf water potential (LWP), photosynthesis rate (A_n), and leaf transpiration rate (T_r) at different water salinity levels and N application rates

Treatments	LAImax	LWP (MPa)	An (µmol m− 2 s− 1)	Tr (mol m− 2 s− 1)
Irrigation water salinity level (dS m− 1)
5	3.12 ± 1.3 A*	-2.59 ± 0.11 A	10.32 ± 1.0 A	6.97 ± 1.26 A
10	3.01 ± 0.88 A	-2.68 ± 0.26 A	10.28 ± 1.65 A	6.88 ± 1.38 A
20	2.76 ± 0.92 AB	-2.84 ± 0.14B	8.24 ± 1.99B	6.40 ± 0.91B
25	2.33 ± 0.91 B	-2.92 ± 0.15B	7.98 ± 1.54 B	5.91 ± 0.95 B
p-value	< 0.0001	0.0046	< 0.0001	< 0.0001
N application rates (kg ha− 1)
0	1.87 ± C	-2.86 ± 0.16B	7.61 ± 1.56 C	5.62 ± 0.47 C
150	2.92 ± B	-2.76 ± 0.19B	9.10 ± 1.42B	6.21 ± 0.67 B
300	3.63 ± A	-2.65 ± 0.25 A	10.92 ± 0.89 A	7.78 ± 1.02 A
p-value	< 0.0001	0.0046	< 0.0001	< 0.0001

*Means followed by the same letter in each trait are not significantly different at the 5% level of probability

Gas exchange

Net photosynthesis rate (A_n)

The interaction effect between irrigation water salinity and nitrogen application rates on the net photosynthesis rate (A_n) was not significant (Table 2), therefore, only the main effects were evaluated in Table 3. Although increasing water salinity levels reduced A_n, the values were similar in 5 and 10 dS m⁻¹, with no significant difference between 20 and 25 dS m⁻¹. Increasing salinity levels from 5 to 20 and 25 d resulted in a reduction of 20% and 23% in A_n. Conversely, applying higher N rates significantly increased A_n, with the highest value observed in 300 kg N ha⁻¹, reaching 10.9 µmol m⁻² s⁻¹. Applying 150 kg N ha⁻¹ increased A_n by 20% while increasing the rate to 300 kg N ha⁻¹ led to a 43% increase.

Additionally, Fig. 2 illustrates the relationship between A_n and total dry matter (TDM). This relationship shows a linear correlation, where TDM increases rapidly with rising A_n.

Fig. 2.

The relationship between net photosynthesis rate (A_n) and total dry matter (TDM)

Leaf transpiration rate (T_r)

The average leaf transpiration rate (T_r) for both growing seasons is summarized in Table 3. Only the main effects were significant and presented. Irrigation water salinity had a significant impact on T_r. The results showed a general decrease in T_r as salinity increased, though no significant difference was observed between 5 and 10 dS m⁻¹ salinity levels. In higher salinity levels (20 and 25 dS m⁻¹), T_r decreased significantly, with no notable difference between these two levels. Specifically, 20 and 25 dS m⁻¹ salinity levels reduced T_r by 8% and 15%, respectively.

In contrast, N application rates significantly influenced T_r, leading to an increase as N rates rose. An application rate of 150 kg N ha⁻¹ improved T_r by 10% compared to the non-fertilized treatment, while 300 kg N ha⁻¹ increased T_r by 38% compared to the non-fertilized treatment and 25% compared to 150 kg N ha⁻¹.

Stomatal conductance (g_s)

As the interaction effect between irrigation water salinity and N application rates on the stomatal conductance (g_s) was significant, the interaction effect was also presented for this parameter. Table 3 presents the stomatal conductance (g_s) values, statistically compared across all treatments. The results showed that in the non-fertilized treatment, salinity did not affect stomatal conductance. However, under fertilized conditions, salinity significantly reduced g_s. For the 150 kg N ha⁻¹ treatment, the 10 dS m⁻¹ salinity level reduced g_s by 27% compared to 5 dS m⁻¹. However, in the 300 kg N ha⁻¹ treatment, salinity levels above 10 dS m⁻¹ negatively caused an average reduction of 33% in g_s. These findings suggest that higher N application rates can mitigate the adverse effects of salinity on g_s, enabling plants to better tolerate higher salinity stress.

In contrast, increasing N application rates to 150 and 300 kg N ha⁻¹ significantly enhanced g_s. At salinity level of 5 dS m⁻¹, g_s increased by 25% and 100% for the 150 and 300 kg N ha⁻¹ treatments, respectively. At higher salinity levels, the 300 kg N ha⁻¹ treatment was particularly effective, increasing g_s by 136%, 64%, and 70% compared to the non-fertilized treatment in salinity levels of 10, 20, and 25 dS m⁻¹, respectively.

Figure 3 illustrates the non-linear relationship between the 2-year average values of A_n and g_s. Initially, A_n increases sharply with g_s, but the rate of A_n increase diminishes in higher g_s values. A sigmoidal model [(Eq. (5)] highlights the positive effect of g_s on A_n and demonstrates the sensitivity of the net photosynthesis rate to small changes in g_s, particularly in lower g_s values.

Fig. 3.

The relationship between A_n and g_s for quinoa

5

Transpiration efficiency (A_n/T_r)

Transpiration efficiency (A_n/T_r), representing the ratio of leaf net photosynthesis to leaf transpiration rate, is presented in Table 4. The interaction effect between irrigation water salinity and N application rates on A_n/T_r was significant. In general, increasing salinity levels reduced A_n/T_r. However, the differences between 5 and 10 dS m⁻¹ and between 20 and 25 dS m⁻¹ were negligible. Raising salinity levels from 5 to 20 and 25 dS m⁻¹ decreased A_n/T_r by 15% and 8%, respectively. Specifically, the highest A_n/T_r values were observed in the 150 kg N ha⁻¹ rate. In contrast, applying 300 kg N ha⁻¹ had a negative impact on A_n/T_r, except in the salinity level of 20 dS m⁻¹. The highest A_n/T_r value, 1.67 µmol/mol, was achieved with 150 kg N ha⁻¹ in 10 dS m⁻¹. These results suggest that N application can enhance A_n/T_r; however, 150 kg N ha⁻¹ was the optimal rate under the experimental conditions. Higher N rates appeared to reduce A_n/T_r, indicating diminished returns at elevated application levels.

Table 4.

Stomatal conductance (gs), leaf transpiration efficiency (A_n/T_r), and intrinsic water use efficiency (A_n/g_s) at different water salinity levels and N rates (an average for both years)

Water salinity level (dS m− 1)	N application rates (kg ha− 1)
	0	150	300
gs (mol m− 2 s− 1)
5	0.12 ± 0.02ef*	0.15 ± 0.01 c	0.24 ± 0.03a
10	0.11 ± 0.03 ef	0.11 ± 0.03 ef	0.26 ± 0.02a
20	0.11 ± 0.02 ef	0.13 ± 0.02de	0.18 ± 0.05 b
25	0.10 ± 0.02f	0.11 ± 0.05ef	0.17 ± 0.01 bc
p-value	< 0.0001
(µmol/mol)
5	1.62 ± 0.17ab	1.47 ± 0.02abc	1.42 ± 0.16 abc
10	1.46 ± 0.29abc	1.67 ± 0.03a	1.42 ± 0.23abc
20	1.12 ± 0.14 d	1.27 ± 0.03 cd	1.44 ± 0.10abc
25	1.23 ± 0.02 cd	1.44 ± 0.18abc	1.37 ± 0.05 bc
p-value	0.0045
(µmol/mol)
5	78.82 ± 7.24 a	66.79 ± 2.79abc	48.13 ± 2.17 d
10	76.82 ± 11.8ab	73.89 ± 7.47 abc	46.29 ± 1.30d
20	60.30 ± 9.45abc	62.85 ± 8.22 bc	60.56 ± 3.89 cd
25	66.06 ± 8.27abc	76.79 ± 16.3 ab	59.36 ± 4.51 cd
p-value	0.0006

*Means followed by the same letter in each trait are not significantly different at the 5% level of probability

Intrinsic water use efficiency (A_n/g_s)

The main effects of N application rates and the interaction between N rates and salinity levels on intrinsic water use efficiency (A_n/g_s) were significant. At lower salinity levels (5 and 10 dS m⁻¹), with no significant difference between them, increasing N rates decreased A_n/g_s by an average of 10% and 39% for 150 kg N ha^− 1 and 300 kg N ha^− 1, respectively (Table 4). However, at higher salinity levels, applying 150 kg N ha^− 1 increased A_n/g_s by 4% and 16% in 20 and 25 dS m⁻¹, respectively, while 300 kg N ha^− 1 had no effect on A_n/g_s in 20 dS m⁻¹ and slightly decreased A_n/g_s in 25 dS m⁻¹. Overall, no significant difference was observed between the non-fertilized treatment and 150 kg N ha^− 1, whereas 300 kg N ha^− 1 significantly reduced A_n/g_s.

A relationship between A_n/g_s and stomatal conductance (g_s) was established for each pair of salinity levels, i.e., S1S2 and S3S4 (Fig. 4). Two negative linear relationships were identified, with a steeper slope observed at lower salinity levels (S1S2, 233.4) compared to higher salinity levels (S3S4, 136.9). This indicates greater sensitivity of A_n/g_s to reductions in g_s under lower salinity conditions (S1 and S2). Conversely, as salinity levels increased, A_n/g_s declined more gradually with increasing g_s.

Fig. 4.

Relationship between intrinsic water use efficiency and stomatal conductance

Leaf water potential

Table 3 represents the two-year average values for leaf water potential (LWP). The variance analysis (Table 2) revealed significant effect of irrigation water salinity and N rates on leaf water potential (LWP), with no significant interaction between treatments. LWP was comparable in salinity levels of 5 and 10 dS m⁻¹. However, increasing salinity beyond 10 dS m⁻¹ significantly reduced LWP, by 9% and 12% in 20 and 25 dS m⁻¹, respectively (Table 3). No significant difference in LWP was detected between 20 and 25 dS m⁻¹. Regarding N rates, there was no difference in LWP between 0 and 150 kg N ha⁻¹, but increasing the rate to 300 kg N ha⁻¹ significantly increased LWP by 7%.

In addition, a linear relationship was obtained between LWP (MPa) and g_s (mol m^− 2 s^− 1) (Fig. 5), indicating an increase in g_s with an increase in leaf potential (less negative). The g_s reached zero at LWP= -3.79 MPa, corresponding to the plant wilting point.

Fig. 5.

Relationship between leaf water potential and stomatal conductance

Root parameters

Root length density

The interaction between irrigation water salinity levels and nitrogen (N) application rates significantly affected root length density (RLD) (p < 0.0001). The mean RLD values in depths for quinoa crops are presented in Table 5. Increasing irrigation water salinity to 10 dS m⁻¹ did not significantly affect RLD in fertilized treatments but reduced it by 25% in non-fertilized treatments. The highest RLD, 4.24 cm cm⁻³, was observed in 300 kg N ha⁻¹ and 5 and 10 dS m⁻¹ salinity. Higher salinity levels significantly decreased RLD across N application rates. For instance, increasing the salinity level to 20 dS m⁻¹ reduced RLD by 35%, 42%, and 17% in non-fertilized, 150 kg N ha⁻¹, and 300 kg N ha⁻¹ treatments, respectively. Further increasing salinity from 20 to 25 dS m⁻¹ caused a substantial reduction in RLD, except in 150 kg N ha⁻¹, where RLD was not changed significantly. Overall, 25 dS m⁻¹ salinity level reduced RLD by 68% and 50% in non-fertilized and fertilized treatments, respectively.

Table 5.

Mean root length density (RLD), root weight density (RWD), and specific root length density (SRL) at different salinity levels and N application rates

Parameters	N application rates (kg ha− 1)	Water salinity level (dS m− 1)
		5	10	20	25
	0	3.60 ± 0.69b *	2.69 ± 0.28 cd	1.75 ± 0.10 e	1.14 ± 0.36 f
RLD (cm cm− 3)	150	3.80 ± 0.18ab	3.26 ± 0.40bc	1.88 ± 0.97 e	2.02 ± 0.31 e
	300	4.24 ± 1.20 a	4.27 ± 1.28 a	3.54 ± 0.36b	2.12 ± 0.39de
p-value	< 0.0001
	0	1.46 ± 0.29 cd	1.31 ± 0.27 cd	1.20 ± 0.17 d	1.14 ± 0.09d
RWD (mg cm− 3)	150	2.47 ± 0.27b	2.26 ± 0.25 b	1.66 ± 0.28c	1.26 ± 0.11 cd
	300	2.94 ± 0.40 a	2.61 ± 0.09ab	2.41 ± 0.04 b	1.51 ± 0.23 cd
p-value	< 0.0001
	0	2.52 ± 0.50 a	2.10 ± 0.41ab	1.48 ± 0.35 cd	1.01 ± 0.10d
SRL (cm mg− 1)	150	1.54 ± 0.12 cd	1.45 ± 0.11 cd	1.18 ± 0.97 cd	1.62 ± 0.30bc
	300	1.46 ± 0.21 cd	1.63 ± 0.23bc	1.46 ± 0.15 cd	1.42 ± 0.26 cd
p-value	0.0007

*Means followed by the same letter in each trait are not significantly different at the 5% level of probability

On the other hand, applying nitrogen at a rate of 300 kg ha⁻¹ resulted in an average increase of 34% in RLD (Table 5). However, no significant difference in RLD was observed between the non-fertilized treatment and the 150 kg N ha⁻¹ application, except under the 25 dS m⁻¹ salinity level. The higher nitrogen application rate has enhanced RLD.

Additionally, Fig. 6 illustrates RLD variations across different soil depths (0–30 cm, 30–60 cm, 60–90 cm). The results indicated that the highest RLD was consistently observed in the topsoil layer (0–30 cm) across all treatments, decreasing with soil depth. In a 5 dS m⁻¹ salinity level, there was only a slight difference in RLD in the topsoil layer between non-fertilized and fertilized treatments. However, this difference became markedly pronounced as salinity levels increased to 25 dS m⁻¹, particularly in the 300 kg N ha⁻¹ treatment. While at certain salinity levels (e.g., 20 dS m⁻¹), the 150 kg N ha⁻¹ treatment did not exhibit substantial differences in RLD compared to the non-fertilized treatment. This finding suggests that nitrogen application improved RLD. This enhancement in RLD, resulting from higher nitrogen rates and lower water salinity levels, likely improved water uptake by the crop roots. A relationship was established between crop transpiration rate and root length at a given depth (RL, cm cm⁻²) (Fig. 7), showing a direct linear correlation between T_r and root length. Notably, the transpiration rate per unit leaf area was scaled up to the whole-plant level based on the leaf area index (LAI).

Fig. 6.

Root length density and root weight density in the the soil depths (0–30 cm, 30–60 cm, 60–90 cm) across water salinity levels and N application rate

Fig. 7.

The relationship between daily leaf transpiration of plant in the unit area (Tr, mm/cm² d) and root length in root depth (RL, cm/cm²)

Root weight density

The interaction between irrigation water salinity and N application rates significantly influenced mean root weight density (RWD) (p-value < 0.0001). The highest RWD (2.94 mg cm⁻³) was observed at a salinity level of 5 dS m⁻¹ with the N rate of 300 kg ha⁻¹. Generally, RWD increased with higher N application rates, except at the highest salinity level (25 dS m⁻¹). For instance, in 5 dS m⁻¹, increasing N rates to 150 and 300 kg ha⁻¹ enhanced RWD by 69% and 101%, respectively, while in 20 dS m⁻¹, RWD increased by 38% and 100% for the same N rates. In 10 dS m⁻¹, RWD increased by 73% and 99% in the 150 and 300 kg ha⁻¹ treatments, respectively, compared to non-fertilized conditions, but no significant difference was found between these two N rates (Table 5).

Raising salinity levels generally decreased RWD, but no significant differences were observed across salinity levels in the non-fertilized treatment. In contrast, fertilizer treatments significantly increased RWD in all salinity levels. Increasing salinity from 5 to 25 dS m⁻¹ reduced RWD by 50% in both fertilizer treatments. No significant differences were observed between 5 and 10 dS m⁻¹ salinity levels for all N rates. In comparison, differences between 10 and 20 dS m⁻¹ were negligible, except for the 150 kg N ha⁻¹ rate.

The soil profile distribution (Fig. 6) revealed the highest RWD in the surface layer (0–30 cm), likely due to denser roots at this depth. Non-fertilized treatments showed the lowest RWD, characterized by lighter roots, whereas 300 kg ha⁻¹ significantly enhanced RWD across salinity levels. Applying 150 kg N ha⁻¹ (N1) also increased RWD at the soil surface, except at 25 dS m⁻¹. At 30–60 cm depth, RWD was similar across all salinity levels and N rates, except in 5 dS m⁻¹, where 300 kg N ha⁻¹ (N2) produced distinctly higher RWD compared to lower N rates. Figure 8 also illustrates the relationship between RLD and RWD, demonstrating two different linear correlations with different slopes between these two parameters at 0–30 cm soil layer and 30–90 cm soil layer. The slope of the relationship was 1.6 (mg cm^− 1) at 0–30 cm indicating thicker roots at this depth compared to 0.7 (mg cm^− 1) obtained at deeper layers.

Fig. 8.

The relationship between RLD and RWD

Specific root length

The interaction between irrigation water salinity and N application rates significantly influenced mean root weight density (RWD) (p-value = 0.0007). Mean specific root length density (SRL) across soil depths showed no significant differences across water salinity levels in fertilized treatments. However, increasing salinity levels generally decreased SRL with two exceptions in N1S4 and N2S2. The highest SRL (2.52 cm mg⁻¹) was observed in the non-fertilized treatment in 5 dS m⁻¹. While salinity significantly reduced SRL in the non-fertilized treatment, no consistent trend was observed across salinity levels in the 150 and 300 kg N ha⁻¹ treatments. Although 20 and 25 dS m⁻¹ significantly decreased SRL compared to lower salinity levels in non-fertilized treatment, it did not affect SRL in fertilized treatment (Table 5). Compared to the non-fertilized treatment, 150 and 300 kg N ha⁻¹ significantly reduced SRL in 5 and 10 dS m⁻¹ salinity levels. However, there was no significant difference in SRL between these two fertilizer treatments, suggesting that increasing N beyond 150 kg ha⁻¹ may not further impact SRL under the studied conditions.

Figure 8 illustrates SRL across different soil layers, revealing higher SRL at the lowest salinity level (S1), which indicates the production of longer and thinner roots under this condition. Moreover, nitrogen application reduced SRL at this salinity level, with N2 showing the lowest values compared to the non-fertilized treatment—completely opposite to the trend observed in S2. When comparing SRL across soil depths, higher values were observed at 30–60 cm in both S1 and S2 treatments. Higher salinity levels (S3, S4) exhibited a different trend, with slightly higher SRL values at deeper soil layers compared to the top layers.

Discussion

Water salinity stress and gas exchange parameters

Salinity impacts crop growth and development by interfering with key physiological and biochemical processes, such as water and nutrient uptake and assimilation [28, 48]. In contrast, halophytic plants like quinoa exhibit physiological adaptations that enable osmoregulation through the accumulation of inorganic ions, allowing them to thrive in saline conditions. One prominent effect of salinity is the reduction in CO₂ assimilation, primarily driven by limitations in stomatal conductance, which ultimately suppresses the photosynthetic rate [49]. Agirresarobe et al. [50] also proposed that reducing leaf area could effectively minimize water loss. In our study, the maximum leaf area index (LAI_max) decreased significantly under higher salinity levels (25 dS m⁻¹), aligning with this hypothesis it is a potential mechanism to reduce water loss through leaves. Notably, while the highest LAI_max in our study was observed in 5 dS m⁻¹, previous research by Wilson et al. [51] and Talebnejad and Sepaskhah [12] (under controlled laboratory conditions and a high groundwater table) reported peak LAI_max in 10 dS m⁻¹ for quinoa. The minimal variation in LAI_max across other salinity levels suggests that quinoa employs this strategy (i.e., reducing leaf area) primarily under severe salinity stress. One prominent effect of salinity is the reduction in CO₂ assimilation, mainly driven by limitations in stomatal conductance, which ultimately suppresses photosynthesis [49]. According to Adolf et al. [9], salt stress imposes stomatal and non-stomatal limitations on photosynthesis. Under salt-stress conditions, plants must regulate their water balance by reducing overall transpiration and minimizing excessive water loss through the stomata, which the osmotic effects of salt trigger stomatal closure. In our study, salinity stress reduced stomatal conductance (gs) with greater sensitivity in fertilized treatments, possibly due to enhanced crop growth and development in these treatments. Even lower salinity levels (10 dS m⁻¹) decreased gs aligning with findings by other studies [36, 37]. Our findings also highlighted the negative effect of salinity on net photosynthesis rate (A_n) specifically in 20 and 25 dS m⁻¹ (20% reduction) in agreement with the finding of Hussin et al. [52], who attributed salt-induced growth reduction to ion toxicity and impaired photosynthetic capacity. Similarly, Eisa et al. [38] reported a severe decline in photosynthetic rate under high salinity due to impaired photosynthetic capacity.

However, despite the adverse effects of salinity, Fig. 2 revealed a strong linear correlation between A_n and total dry matter (TDM) similar to findings by Talebnejad and Sepaskhah [12], indicating that increased photosynthetic activity directly enhances biomass accumulation. This suggests that quinoa’s ability to maintain growth under salinity stress is linked to its inherent physiological adaptations, including osmotic adjustment and water potential regulation, as highlighted by Hariadi et al. [11]. The ability of quinoa to reduce tissue osmotic potential and maintain a positive water balance, as supported by earlier studies [23, 35, 53], likely contributed to the observed maintenance of A_n at moderate salinity levels. These findings reinforce the notion that quinoa exhibits considerable tolerance to salinity through mechanisms such as osmotic adjustment and improved water use efficiency [38], enabling sustained photosynthesis and biomass production even under saline conditions. This relationship also indicated that as salinity and nitrogen conditions improved, the relationship slope became steeper, meaning that small changes in A_n had a greater impact on TDM.

Salt-induced photosynthesis inhibition is often accompanied by a marked decrease in transpiration rate, which helps maintain a positive water balance. In our study, high salinity levels reduced leaf transpiration rate (T_r) similar to A_n. This response is characteristic of water conservation strategies seen in many halophytic species subjected to saline environments [54–56]. A reduced transpiration rate under such conditions may serve as an adaptive mechanism to limit salt uptake into leaves, particularly younger ones [38], thereby mitigating salt toxicity.

Our findings reveal a distinct relationship between intrinsic water use efficiency (A_n/g_s) and stomatal conductance (g_s) across salinity levels, contrasting with Razzaghi et al. [36], who reported an increase in A_n/g_s with salinity. Instead, we observed no significant differences in A_n/g_s between the lowest and highest salinity levels. The identified negative linear relationships suggest greater A_n/g_s sensitivity to reductions in g_s at lower salinity levels (S1 and S2), as evidenced by a steeper slope (233.4 vs. 136.9). At higher salinity levels, A_n/g_s declined more gradually with increasing g_s, reflecting an adaptive moderation in response to extreme salinity conditions. This aligns with the higher sensitivity of TDM to small changes in A_n at lower salinity levels.

A higher turgor pressure as a crucial component of cell water potential supports cell wall expansion and prevents cell contraction. Additionally, it minimizes water loss via transpiration [57], promoting growth under challenging conditions [58]. Quinoa maintains lower osmotic and water potential to support metabolic processes, plant growth, and durability, even in saline environments [58, 59]. This underscores the importance of ion accumulation like K⁺ [9, 36] in facilitating plant adaptation and survival. In this study, leaf water potential declined significantly at higher salinity levels which could be a mechanism to improve plant adjustment capacities in raising turgor pressure [60]. Additionaly, this could be more significant if the the leaf osmotic potentioal has been measured.

Nitrogen and gas exchange parameters

Nitrogen is an essential nutrient that plays a crucial role in regulating defense mechanisms and supporting diverse cellular, physiological, and molecular processes vital for plant survival. It also influences signal transduction pathways involved in enhancing plant resilience to stress conditions, including salinity [61–63]. Some studies [64, 65] linked the detrimental effects of salt stress on plant metabolism to disruptions in nitrogen uptake and variation in the activity of enzymes and genes associated with nitrogen metabolism. Thus, effective nitrogen management has the potential to alleviate the negative impacts of salinity [42]– [43].

In this regard, increasing nitrogen (N) application rates positively increased LAI_max, with the highest value (94% increase) achieved at 300 kg N ha^{− 1}. This finding underscores the role of nitrogen in mitigating the adverse effects of salinity, consistent with the results reported by Alizadeh-Zoaj et al. [42]. Increasing the N rates showed a higher tolerance of photosynthetic rate, stomatal conductance, and transpiration rate aligning with findings by Alandia et al. [39] who found greater stomatal conductance in fertilized plants than in non-fertilized plants. However, despite increased A_n and g_s, the 300 kg N ha⁻¹ treatment reduced water-use efficiency (A_n/g_s), indicating that the gains in g_s and T_r were disproportionately higher than the increase in A_n. Lower N rates (150 kg N ha⁻¹) offer modest improvements in A_n and T_r without negatively impacting A_n/g_s, making them more suitable for optimizing water-use efficiency.

Recorded improvement in LWP suggested a beneficial role of higher nitrogen rates in mitigating salinity water stress, which was in contrast to the finding by Alandia et al. [39] which showed greater water stress in fertilized plants than in non-fertilized plants.

Salinity, nitrogen, and root development

Activities like root elongation and leaf expansion, which are turgor-dependent, are susceptible to water deficits. Our finding showed a significant reduction in root parameter values (RLD, RWD) in salinity above 10 dS m⁻¹, with greater reductions at higher salinity levels. The negative impact was more pronounced in non-fertilized treatments, which could be attributed to the lower water uptake by plants due to low soil osmotic potential. Generally, higher salinity levels reduced RLD and RWD; however, applying higher nitrogen rates mitigated this negative effect. For instance, at a salinity level of 25 dS m⁻¹, RLD and RWD decreased by 68% and 22% in non-fertilized treatments, respectively, whereas in fertilized treatments, the reduction was only 50%. Therefore, as noted by Ahmadi et al. [66], in non-fertilized conditions, root length growth for water uptake (RLD), which is a benefit, was more negatively affected by salinity than the translocation of additional photosynthetic assimilates to the root system (RWD), which represents the cost. Nitrogen application, especially at 300 kg ha⁻¹, partially offset the negative effects of salinity on RLD and RWD by promoting RLD and RWD, improving the plant’s ability to tolerate saline conditions [67]. Additionally, the improvement in root parameters was linearly correlated with the crop’s transpiration rate, proving enhanced water uptake by the root expansion.

In our study, the greater RLD and RMD values observed in the topsoil layer (0–30 cm) align with previous studies [67–69], which suggested that quinoa most effective rooting zone is confined to the upper 50 cm. However, it decreased with depth, reaching the lowest at 80 cm, which enhanced water uptake from lower soil layers [66]. Conversely, lower SRL values at 0–30 cm show shorter and thicker roots at the upper layers. Developing thick roots near the topsoil layer effectively supports a vigorous plant and promotes water absorption [70]. As Corneo et al. [71] reported, the plant allocates fewer photosynthetic assimilates (carbon) to root expansion while instead prioritizing the exploration of a larger soil volume for water and nutrients by producing long, thin roots (i.e., higher SRL at greater depths). Our study found that SRL was higher at the 30–60 cm soil layer under lower salinity conditions (S1, S2), whereas it peaked at 60–90 cm in higher salinity levels (S3, S4). This suggests that, even under high salinity, the crop continued to allocate photosynthetic assimilates to root expansion, enabling water uptake from deeper soil layers (Fig. 9). In contrast to findings by Mirsafi et al. [68], this study revealed a higher root thickness (the root length density to root mass density ratio) at the surface soil layer (slope = 1.6) compared to that obtained in the deeper layers (slope = 0.70).

Fig. 9.

Specific root length in the different soil depths across water salinity levels and N rate

Conclusions

This study demonstrated that salinity stress significantly reduces gas exchange parameters, with more pronounced effects at higher salinity levels. However, quinoa’s adaptive mechanisms, such as osmotic adjustment, help counteract these impacts. Nitrogen application further enhances quinoa’s resilience to salinity by improving photosynthetic performance, leaf water potential, and root development. According to this study nitrogen application rate of 150 kg N ha⁻¹ and irrigation water salinity of 10 dS m⁻¹ resulted in optimal physiological responses and root growth in quinoa. These findings underscore quinoa’s potential as a highly resilient crop for saline environments, with its performance further optimized through strategic nitrogen management.

Abbreviations

A_n

Photosynthesis rate

g_s

Stomatal conductance

LAI

Leaf area index

LWP

Leaf water potential

N

Nitrogen

RH_ave

Average relative humidity

RL

Root length in root depth

RLD

Root length density

RMD

Root mass density

SRL

Specific root length

TDM

Total dry matter

T_max

Maximum daily temperature

T_min

Minimum daily temperature

T_r

Leaf transpiration rate

Authors’ contributions

Conceptualization: R.T. and A.R.S. Data curation: F.A. Formal analysis: R.T., and A.R.S. Funding acquisition: R.T. Investigation and Methodology: F.A. Supervision: R.T. Validation: A.R.S., and R.T. Visualization: F.A. Writing—original draft: F.A. Writing – Review & editing: R.T. and A.R.S.

Funding

This research was supported in part by the Research Project funded by grant no. 2GCU1M222614 of Shiraz University Research Council, and Drought Research Center, Center of Excellence for On-Farm Water Management and Iran national Science foundation (INSF).

Data availability

Data could be available by reasonable request.

Declarations

Ethics approval and consent to participate

The quinoa seeds have been collected from the former experiments of the second and third authors Rezvan Talebnejad and Ali Reza Sepaskhah that had fulfilled and published the associated article. The reference to that experiment and article is: Bahrami M, Talebnejad R, Sepaskhah AR, Bazile D (2022) Irrigation regimes and nitrogen rates as the contributing factors in quinoa yield to increase water and nitrogen efficiencies. Plants 11(15): 2048. 10.3390/plants11152048.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.