Response of Sunflower Genotypes to Salinity Stress Under Laboratory Conditions

Abstract

Sunflower (Helianthus annuus L.) is an essential oilseed crop known for its adaptability to harsh environments including drought. However, salinity stress, affecting over 20% of global agricultural land, poses a serious threat to its productivity. This study evaluated the response of 17 sunflower genotypes under salinity stress (200 mM NaCl) and optimum (0 mM NaCl) conditions in the laboratory. The experiment was arranged in a completely randomized design with three replications and was validated through a second experimental run. Measured parameters included germination percentage and speed, root and shoot length, biomass, and water content. Stress tolerance indices (STIs) for germination, seedling length, and biomass were calculated. Combined ANOVA showed that genotype and environment interactions significantly (p < 0.001) affected all measured traits. Salinity stress significantly reduced germination, seedling growth, and biomass across genotypes, with some experiencing complete germination inhibition. Genotypes 9, 14, 16, and 17 consistently maintained higher germination, seedling length, and biomass under stress, with high STIs, indicating tolerance to salinity stress during the early growth stages. These results identified genotypes 9, 14, 16, and 17 as promising candidates for breeding programs aimed at enhancing salinity tolerance, offering sustainable solutions for the utilization of saline soils and for enhancing food security. Future research should focus on the field-based validation of these genotypic responses.

1. Introduction

Sunflower (Helianthus annuus L.) is an important oilseed crop from which oil for human consumption can be extracted and the residues of which are used as protein-rich animal feed [1]. Its resilience under adverse conditions, particularly drought, makes it a strategic crop for farmers in dry land production regions [2]. In South Africa, sunflower is the third-largest grain produced after maize (Zea mays L.) and wheat (Triticum aestivum L.) [3]. It contributes approximately 60% of all oil seeds produced in the country and adds to the value chain of many commodities such as bread and butter [4,5].

Sunflower production is threatened by both biotic and abiotic stressors, just like other field crops [6,7]. One of the major abiotic factors affecting sunflower production is salinity stress [8]. It is projected that by 2050, half of the world’s arable land will be salt-damaged [9], primarily due to low precipitation, high evaporation rates, irrigation with saline water, sea water intrusion, improper agricultural practices, and geological influences [10,11]. According to [12], 40% of the total land in South Africa is saline, with the Eastern Cape and Free State Provinces being the most affected with 50% and 31% of soils being affected by saline, respectively.

Common salts present in saline soils are chlorides, carbonates, and sodium. These salts negatively affect soil structure and nutrient availability, thereby disrupting plant biochemical processes and growth [13]. Under saline conditions, plants experience multiple repercussions, resulting in hormonal imbalances, nutrient deficiencies, and toxicity due to the uptake of sodium and chloride ions [14]. Naturally, sunflower is known to be moderately tolerant to salinity stress [15], with no significant yield loss observed up to 4.8 ds.m⁻¹. However, each 1 ds.m⁻¹ increase in soil salinity above this threshold can reduce sunflower yield by 10–14% [16]. Severe salinity conditions alter the osmotic potential of the soil solution, resulting in physiological drought. This reduces photosynthesis, protein synthesis, and lipid metabolism, causing a decline in total yield and quality [17].

Salinity stress reduces the yield potential of many crops across all growth stages [18]. However, literature shows that crops are more sensitive to salinity at germination and early seedling establishment stages [19,20]. High salinity levels (200–300 mM NaCl) significantly delay and inhibit the germination of sunflower seeds [15,21], while concentrations of 25–200 mM NaCl reduce sunflower seedling length and weight [17,22]. Furthermore, there is a clear reduction in tissue water content when sunflower seedlings are exposed to 100 mM and 200 mM NaCl [21]. According to [23], rapid germination and the uniform emergence of seedlings lead to good stand establishment. Therefore, seeds which germinate under saline conditions are likely to have good seedling establishment and increased yield.

Several management and amelioration strategies, such as the application of gypsum, sulfuric acid, and calcium chloride, and the leaching of salts from the root zone, can be adopted to mitigate the negative effects of saline soils [24,25]. However, the widespread adoption of these methods by smallholder farmers is unrealistic due to excessive costs. Furthermore, leaching is increasingly becoming impractical due to increased competition for freshwater among industries, agriculture, and municipalities [26]. As a result, there is pressure to utilize water sources with a high salt content for irrigation purposes, such as underground water, drainage water, and treated wastewater. Breeding sunflower genotypes for tolerance to salinity stress presents a sustainable alternative to cope with soil salinization, particularly at the early growth stages where crops are extremely sensitive to salt stress. It is also difficult and uneconomical to employ other management strategies during the early growth stages. Fortunately, genetic variability for salinity tolerance has been reported in sunflower [27]. However, there is a need to screen locally adapted sunflower genotypes for salinity tolerance. Identifying salt-tolerant sunflower genotypes can benefit both smallholder and commercial farmers in salt-affected areas by bringing marginalized lands into cultivation and lowering the cost of production, thereby increasing food security in a sustainable way.

Screening for salinity tolerance at the early seedling stage has been conducted in several crops including maize [28], wheat [29], and soybean [30]. Screening techniques for salinity tolerance include assessment under controlled conditions (conducted in laboratories, growth chambers, and glasshouses) and field trials. Most controlled studies use the hydroponic system which enables the precise adjustment of salt concentrations exposed to the plants [20], while reducing the confounding factors normally associated with field-based screening. Various traits are used to assess genotypic responses to salt stress at the germination and early growth stages. Stress tolerance indices measure a genotype’s performance under stress relative to controlled conditions. Genotypes that show a higher index value are considered to be stress tolerant [31]. Stress tolerance indices, such as the germination stress tolerance index and the fresh and dry weight stress tolerance indices, have been used to screen for tolerance to abiotic stresses such as drought and salinity in several crops such as chickpea, sunflower, and wheat [15,32,33,34]. Given the above background, this study sought to evaluate the response of 17 sunflower genotypes to salinity stress using the hydroponic technique, with the goal of identifying salt-tolerant genotypes at early growth stages. The identified tolerant genotypes may be used in future breeding programs aimed at developing saline-tolerant varieties upon further evaluation under glasshouse and field conditions. It was hypothesized that genetic variability would exist among the sunflower genotypes in response to salinity stress at the early growth stages. The diverse range of genotypes used in this study provided a representative pool of locally adapted cultivars that can also be grown in regions similar to those of South Africa.

2. Results

The combined ANOVA is presented in

Table 1. Mean square values and significance tests for all measured traits from combined analysis of variance involving 17 sunflower genotypes under salinity and non-salt-stressed conditions.

SV	DF	GS	G%	RL	SL	TL	RDW	SDW	TDW	WC%
Rep	2	0.19 ns	116.20 ns	0.02 ns	0.04 ns	0.01 ns	0.28 ns	1.39 ns	2.50 ns	0.10 ns
G	16	3.80 ***	1357.40 ***	10.64 ***	13.75 ***	33.66 ***	5.35 ***	1442.49 ***	1498.20 ***	8.82 ***
E	1	185.85 ***	300,533.8 ***	42.49 ***	47.27 ***	179.02 ***	93.35 ***	4340.60 ***	5707.06 ***	107.99 ***
G × E	16	4.64 ***	634,90 ***	0.37 ***	0.33 ***	1.06 ***	2.01 ***	86.19 ***	96.38 ***	4.63 ***

SV: source of variation, DF: degrees of freedom, GS: germination speed, G%: germination percentage, RL: root length, SL: shoot length, TL: total seedling length, RDW: root dry weight, SDW: shoot dry weight, TDW: total dry weight, WC%: water content in percentage, E: environment, G: genotype, G × E: the interaction between genotype and environment, ^ns: non-significant at 0.05 probability level, ***: treatment significant at 0.001.

below. There was a significant genotype × environment interaction (GEI) (p < 0.001) for all measured parameters. Similarly, the environment and genotypes showed significant differences (p < 0.001) for all measured traits. The results obtained from the partial eta squared (η²p), as presented in Appendix A 

Table A1. Sum of squares and partial eta effect (η²p) for germination percentage, germination speed, root length, shoot length, and total seedling length.

SV	DF	GP		GS		RL		SL		TSL
		SS	η2p	SS	η2p	SS	η2p	SS	η2p	SS	η2p
Rep	2	232.35	0.05	0.37	0.01	0.03	0.01	0.07	0.02	0.02	0
Gen	16	21718.63	0.82	60.8	0.56	170.26	0.98	219.95	0.98	538.55	0.99
Env	1	300,533.8	0.98	185.85	0.79	42.49	0.95	47.27	0.92	179.02	0.97
G × E	16	10,157.84	0.69	74.24	0.61	5.86	0.74	219.95	0.98	16.95	0.73
Error	168	4617.65		48.18		2.03		4.16		6.27

SV: source of variation, DF: degrees of freedom, SS: sum of squares, η2p: partial eta effect, RDW: root dry weight, SDW: shoot dry weight, TDW: total dry weight, WC%: water content in percentage, E: environment, G: genotype, G×E: the interaction between genotype and environment.

and

Table A2. Sum of squares and partial eta effect (η2p) for root dry weight, shoot dry weight, total dry weight, and water content.

SV	DF	RDW		SDW		TDW		WC
		SS	η2p	SS	η2p	SS	η2p	SS	η2p
Rep	2	0.02	0	2.78	0	4.98	0.01	0.19	0.01
Gen(G)	16	538.55	0.96	23,079.8	0.96	23,971.16	0.96	141.17	0.8
Env(E)	1	179.02	0.88	4340.6	0.83	5707.06	0.86	107.99	0.76
G × E	16	16.95	0.41	1379	0.61	1542.02	0.63	74.08	0.68
Error	168	24.11		866.73		919.19		34.5

SV: source of variation, DF: degrees of freedom, SS: sum of squares, η2p: partial eta effect, RDW: root dry weight, SDW: shoot dry weight, TDW: total dry weight, WC%: water content in percentage, E: environment, G: genotype, G×E: the interaction between genotype and environment.

, show that genotype, environment, and genotype × environment interactions had large effects (η²p > 0.14) on all measured traits.

2.1. Germination Speed (GS)

A higher GS was observed under the control conditions in comparison to saline stress (

Table 2. Mean comparisons among the sunflower genotypes based on the germination speed under the control and saline-stressed environments.

Genotype	Control +	Saline +
G1	3.79 a ± 0.36	0.93 de ± 0.58
G2	3.24 ab ± 0.48	0 e ± 0
G3	2.55 bc± 0.19	1.48 cd ± 0.39
G4	2.95 ab± 0.75	0.29 de ± 0.10
G5	2.76 ab+ 0.71	0.81 de± 0.74
G6	3.40 ab ± 0.19	1.12 de ±0.46
G7	2.74 ab ± 0.19	1.12 de ± 1.02
G8	3.00 ab± 0.88	0.29 de ± 0.44
G9	2.69 ab ± 0.40	3.56 ab ± 0.93
G10	2.83 ab ± 0.14	0.83 de ± 0.74
G11	2.64 abc ± 0.27	0.56 de ± 0.43
G12	3.07 ab ± 0.62	0 e ± 0
G13	2.52 bc ± 0.39	0 e ± 0
G14	2.98 ab ± 0.47	3.10 ab ± 0.97
G15	3.62 ab ± 0.48	0 e ± 0
G16	3.10 ab ± 0.35	2.95 ab ± 0.75
G17	2.83 ab ± 0.25	1.21 d ± 0.45

⁺ Mean ± standard error. Means sharing the same lowercase letter within the trait column were not significantly different (p ≤ 0.05) according to Tukey’s test under the control and saline environments.

). The germination speed ranged between 3 and 4 seeds/day under optimum conditions and 0–4 seeds/day under salt stress. The highest GS under stress was recorded in G9 (4 seeds/day), while no germination was observed in some genotypes (G2, G12, G13, and G15). Although the GS of most genotypes significantly differed across both environments, the GSs of G9, G14, and G16 did not significantly differ across the environments.

2.2. Germination Percentage (GP)

Germination percentage significantly varied across both environments for all genotypes. Under the control environment, the highest GP recorded was 100% (G1, G3, G11, G14, and G16), while the lowest GP was 80% (G15) (Figure 1). Under the saline environment, the highest GP was 55% (G9), while its control had a GP of 93%. This shows that germination was reduced by 38% for this genotype. In other genotypes (G2, G12, G13, and G15), germination was completely inhibited by salinity.

2.3. Morphological Parameters

2.3.1. Root Length (RL)

Generally, a decrease in RL was observed for all genotypes under the saline environment, with genotypes showing significant differences in RL across environments (

Table 3. Mean comparisons among the sunflower genotypes based on root length, shoot length, and total seedling length under the control and saline-stressed environments.

	Root Length (cm)		Shoot Length (cm)		Total Seedling Length (cm)
Genotype	Control +	Saline +	Control +	Saline +	Control +	Saline +
G1	8.80 f ± 0.09	7.58 kl ± 0.18	12.38 cd ± 0.08	10.92 kl ± 0.08	21.18 de ± 0.15	18.50 j ± 0.13
G2	7.80 k ± 0.15	6.52 p ± 0.08	11.37 hij ± 0.05	10.68 l ± 0.34	19.17 i ± 0.12	17.20 lmn ± 0.40
G3	7.15 mn ±0.10	6.20 q ± 0.11	11.92 ef ± 0.08	11.15 ijk ± 0.05	19.07 i ± 0.15	17.35 klm ± 0.15
G4	8.53 gh ± 0.05	7.18 m ± 0.13	11.13 ijk ± 0.14	10.12 no ± 0.16	19.67 gh ± 0.12	17.30 klm ± 0.17
G5	8.75 fg ± 0.12	7.37 lm ± 0.08	10.68 l ± 0.08	9.75 p ± 0.10	19.40 hi ± 0.09	17.12 mn ± 0.15
G6	7.75 k ± 0.14	6.77 o ± 0.08	11.62 fgh ± 0.08	10.90 kl ± 0.09	19.37 hi ± 0.19	17.67 k ± 0.05
G7	6.93 no ± 0.10	6.08 q ± 0.15	9.85 op ± 0.10	8.53 r ± 0.05	16.78 n ± 0.20	14.62 o ± 0.17
G8	9.55 ab ± 0.05	8.27 ij ± 0.12	10.32 mn ± 0.08	9.15 q ± 0.05	19.87 fg ± 0.08	17.42 klm ± 0.12
G9	9.10 de ± 0.11	8.70 fg ± 0.13	11.00 kl ± 0.09	10.67 lm ± 0.04	20.10 f ± 0.15	19.37 hi 0.08
G10	8.05 j ± 0.19	7.23 m ± 0.08	10.97 kl ± 0.08	9.87 op ± 0.12	19.02 i ± 0.15	17.10 mn ± 0.13
G11	9.08 de ± 0.04	8.40 hi ± 0.20	10.18 no ± 0.16	9.00 q ± 0.09	19.27 hi ± 0.16	17.40 klm ± 0.19
G12	8.90 ef ± 0.11	7.80 k ± 0.13	11.12 jk ± 0.10	9.87 op ± 0.05	20.02 fg ± 0.19	17.67 k ± 0.10
G13	9.35 bc ± 0.05	8.25 ij ± 0.10	11.48 ghi ± 0.08	9.95 op ± 0.66	20.83 e ± 0.10	18.20 j ± 0.69
G14	9.70 a ± 0.06	9.37 bc ± 0.05	12.85 bc ± 0.14	12.15 de ± 0.05	22.55 ab ± 0.08	21.52 d ± 0.10
G15	7.67 k ±0.10	6.80 o ± 0.06	11.75 fg ± 0.05	10.80 kl 0.08	19.42 hi ± 0.10	17.60 kl ± 0.11
G16	9.63 a ± 0.05	9.27 cd ± 0.08	13.28 a ± 0.13	12.70 bc ± 0.07	22.92 a ± 0.10	21.97 c ± 0.12
G17	9.32 bcd ± 0.10	8.77 fg ± 0.08	13.05 ab ± 0.08	12.38 cd ± 0.17	22.37 bc ± 0.18	21.17 de ± 0.24

⁺ Mean ± standard error. Means sharing the same lowercase letter within the trait column were not significantly different (p ≤ 0.05) according to Tukey’s test under the control and saline environments.

). The lowest and highest RLs recorded under the control conditions were 6.9 cm (G7) and 9.7 cm (G14), respectively. Salinity stress caused the greatest and lowest RL reductions in G1 (18%) and G14 (4%) relative to the control.

2.3.2. Shoot Length (SL)

High SLs were recorded under the control compared to the saline environment (Table 3). The highest SL recorded under optimum conditions was 13.3 cm (G16) while G7 recorded the shortest SL of 9.9 cm. Under salinity stress, G16 recorded the highest (12.7 cm) SL, while the lowest SL (9 cm) was recorded in G11. Although the SL of most genotypes significantly differed across the environments, that of G9 did not significantly differ.

2.3.3. Total Seedling Length (TSL)

Lower TSLs were recorded for all genotypes under the saline environment compared to the control, with all genotypes showing significant differences in TSL across environments (Table 3). The highest TSLs recorded under the control and saline environments were 22.9 cm (G16), and 22 cm (G16), respectively. The lowest TSLs under control and saline environments were 16.8 cm (G7), and 14.6 cm (G7), respectively. Salinity stress caused the highest and lowest TSL reductions in G7 (13%) and G9 (4%), respectively.

2.3.4. Root Dry Weight (RDW)

Salinity stress reduced the RDW of all genotypes (

Table 4. Mean comparisons among the sunflower genotypes based on root dry weight, shoot dry weight, total dry weight, and water content under control and saline-stressed environments.

Genotype	Root Dry Weight (mg)		Shoot Dry Weight (mg)		Total Dry Weight (mg)		Water Content (%)
	Control +	Saline +	Control +	Saline +	Control +	Saline +	Control +	Saline +
G1	4.50 bcde ± 0.55	2.83 hijk ± 0.41	53.33 mn ± 2.66	40.67 q ± 4.23	57.83 lmn ± 3.06	43.50 r ± 4.32	89.70 efgh ± 0.61	87.20 k ± 1.33
G2	4.67 bcd ± 0.52	2.17 jk ± 0.41	64.67 fghij ± 3.27	55.17 lm ± 2.93	69.33 fghij ± 3.08	57.33 mn ± 2.94	90.80 abcd ± 0.44	87.00 k ± 0.52
G3	4.00 cdef ± 0	2.83 hijk ± 0.45	65.50 fghi ± 2.59	43.67 q ± 1.63	69.50 fghi ± 2.59	46.50 qr ± 1.64	90.80 abcd ± 0.27	88.40 ij ± 0.46
G4	6.17 a ± 0.98	3.67 efgh ± 0.52	52.33 mn ± 1.75	40.00 q ± 0.63	58.50 lm ± 1.76	43.67 r ± 0.52	91.00 abcd ± 2.34	89.70 efgh ± 0.23
G5	4.67 bcd ± 0.52	2.00 k ± 0	52.33 mn ± 3.39	46.00 op ± 4.20	57.00 mn ± 3.03	48.00 pqr ± 4.20	90.90 abcde ± 2.66	90.40 bcdef ± 0.89
G6	5.00 b ± 0	3.83 defg ± 0.41	62.33 hijk ± 1.37	53.50 mn ± 2.07	67.33 ghijk ± 1.4	57.33 mn ± 2.34	90.80 abcd ± 0.22	89.10 ghi ± 0.44
G7	4.33 bc ± 0.46	2.83 hijk ± 0.41	46.33 op ± 0.82	31.83 r ± 2.48	51.17 opq ± 0.98	34.67 s ± 2.66	90.80 abcd ± 0.18	87.60 jk ± 1.03
G8	4.00 cdef ± 0	3.83 defg ± 0	58.67 kl ± 1.51	49.00 no ± 2.19	62.67 kl ± 1.51	52.83 nop ± 2.40	90.90 abcd ± 0.24	88.90 hi ± 0.48
G9	5.00 b ± 0.13	3.17 fghi ± 0.13	59.83 jkl ± 0.75	53.50 mn ± 0.84	64.83 ijk ± 0.75	56.67 mn ± 1.1	91.00 abcd ± 0.11	90.70 abcde ± 0.16
G10	5.00 b ± 0.05	3.83 defg ± 0.37	67.50 efg ± 1.05	63.00 ghijk ± 2.00	72.50 efg ± 1.05	66.83 hijk ± 2.40	90.50 bcdef ± 0.18	90.10 cdefg ± 0.33
G11	6.00 a ± 0	3.83 defg ± 0.41	69.67 def ± 1.03	52.83 mn ± 1.33	75.67 cde ± 1.03	56.67 mn ± 1.03	90.90 abcd ± 0.10	87.60 jk ± 0.24
G12	3.17 fghi ± 0.41	3.00 ghij ± 0	61.00 ijk ± 0.63	53.00 mn ± 1.55	64.17 jk ± 0.98	56.00 mno ± 1.6	90.10 abcd ± 0.19	89.10 jk ± 0.29
G13	3.00 ghij ± 0	2.33 ijk ± 0.50	66.17 fgh ± 2.04	55.00 lm ± 1.10	69.17 fghij ± 2.04	57.33 mn ± 1.21	91.10 abcde ± 0.26	90.10 defg ± 0.25
G14	5.00 b ± 0	4.67 bcd ± 0.52	74.83 bc ± 1.47	73.33 bcd ± 1.03	79.83 bc ± 1.47	78.00 bcd ± 1.10	91.20 ab ± 0.18	91.10 abc ± 0.15
G15	4.17 bcde ± 0.41	3.17 fghi ± 0.41	71.67 cde ± 4.13	68.83 def ± 3.71	75.83 cde ± 4.54	72.00 efgh ± 4.1	91.20 ab ± 0.53	91.00 abcd ± 0.47
G16	5.00 b ± 0	4.00 cdef ± 0	85.67 a ± 1.97	78.17 b ± 2.23	90.67 a ± 1.97	82.17 b ± 2.23	90.90 abcd ± 0.20	90.80 abcd ± 0.25
G17	4.83 bc ± 0.41	4.00 cdef ± 0	72.00 cde ± 1.55	69.50 def ± 2.26	76.83 cde ± 1.17	73.50 def ± 2.26	91.60 a ± 0.19	91.30 ab ± 0.26

⁺ Mean ± standard error. Means sharing the same lowercase letter within the trait column were not significantly different (p ≤ 0.05) according to Tukey’s test under the control and saline environments.

). Under the control environment, the highest RDW was observed in G4 (6.17 mg) followed by G11 (6 mg), while the lowest RDW was observed in G13 (3 mg) followed by G3 (4 mg) and G8 (4 mg). Under the saline-stressed environment, the RDW varied between 2 mg (G5) and 4.67 mg (G14). The lowest reduction in RDW was observed in G8 (4%), while the highest reduction was observed in G5 (57%). Generally, the RDW significantly differed across the environments for all genotypes, except for G8, G12, G13, G14, and G17.

2.3.5. Shoot Dry Weight (SDW)

The findings of this study show that salinity stress significantly reduced the SDW of all genotypes (Table 4). The highest SDW recorded under the control environment was 85.30 mg (G16) followed by 74.83 mg (G14), while the lowest SDW was 46.33 mg (G7) followed by 52.33 mg (G4 and G5). Under salinity, the highest SDW observed was 78.17 mg (G16) followed by 73.33 mg (G14), and the lowest SDW was 31.83 mg (G7) followed by 40 mg (G4) and 40.67 mg (G1). Salinity stress caused a 2–33% reduction in SDW. Although SDW significantly differed across the environments for most of the genotypes, no significant difference was observed for G14, G15, and G17.

2.3.6. Total Dry Weight (TDW)

Salinity stress reduced the TDW of all genotypes (Table 4). The highest TDWs recorded under the control and saline environments were 90.67 mg (G16), and 82.17 mg (G16), respectively, whereas the lowest TDWs recorded under the control and saline environments were 51.70 mg (G5) and 34.67 mg (G7), respectively. Generally, the TDW significantly differed across the environments in all genotypes, except for G14, G15, and G17.

2.4. Seedling Water Content (WC)

Generally, salinity stress reduced the WC in all genotypes (Table 4). The highest WC under the control environment was recorded in G17 (91.6%), closely followed by G14 (91.2%), while the lowest WC was recorded in G1 (89.7%), followed by G10 (90%). Under stressed conditions, G17 (91.3%) recorded the highest WC, closely followed by G14 (91.1%), while G2 (87%) had the lowest WC, followed by G1 (87.2%). Water content did not significantly differ in most genotypes across environments, but it significantly differed in G1, G2, G3, G4, G6, G7, G8, and G12.

2.5. Stress Tolerance Indices (STIs)

The genotypes showed different responses to germination (GSTI), root length (RLSTI), shoot length (SLSTI), fresh weight (FWSTI), and dry weight (DWSTI) (

Table 5. Ranking of sunflower genotypes based on the stress tolerance indices.

G	G	Rank	G	RL	Rank	G	SL	Rank	G	TFW		G	TDW	Rank
Code	STI		Code	STI		Code	STI		Code	STI	Rank	Code	STI	STI
G9	0.59	1	G14	0.97	1	G9	0.97	1	G14	0.96	1	G14	0.98	1
G14	0.47	2	G9	0.96	2	G16	0.96	2	G15	0.93	2	G17	0.96	2
G16	0.42	3	G16	0.96	3	G17	0.95	3	G17	0.92	3	G15	0.95	3
G17	0.26	4	G17	0.94	4	G14	0.95	4	G16	0.89	4	G10	0.92	4
G3	0.23	5	G10	0.94	5	G6	0.94	5	G10	0.89	5	G16	0.91	5
G7	0.17	6	G11	0.92	6	G3	0.94	6	G9	0.84	6	G9	0.87	6
G6	0.15	7	G6	0.87	7	G2	0.94	7	G5	0.80	7	G12	0.87	7
G10	0.13	8	G15	0.89	8	G15	0.92	8	G12	0.76	8	G6	0.85	8
G5	0.13	9	G12	0.88	9	G5	0.91	9	G13	0.75	9	G5	0.84	9
G1	0.13	10	G13	0.88	10	G4	0.91	10	G6	0.72	10	G8	0.84	10
G4	0.09	11	G7	0.88	11	G10	0.90	11	G8	0.69	11	G13	0.83	11
G11	0.08	12	G3	0.87	12	G12	0.89	12	G4	0.65	12	G2	0.82	12
G8	0.04	13	G8	0.87	13	G11	0.88	13	G1	0.61	13	G1	0.75	13
G15	0	14	G5	0.84	14	G1	0.88	14	G2	0.58	14	G4	0.75	14
G13	0	15	G2	0.84	15	G13	0.87	15	G11	0.55	15	G11	0.75	15
G12	0	16	G4	0.84	16	G8	0.87	16	G3	0.53	16	G7	0.68	16
G2	0	17	G1	0.82	17	G7	0.87	17	G7	0.50	17	G3	0.67	17

G Code: genotype code, GSTI: germination stress tolerance index, RLSTI: root length stress tolerance index, SLSTI: shoot length stress tolerance index, TFWSTI: total fresh weight stress tolerance index, TDWSTI: total dry weight stress tolerance index.

). The highest GSTI was recorded in G9 (0.59), while G2, G12, G13, and G15 recorded the lowest values of zero. The highest (RL) STI value of 0.97 was recorded in G14, followed by G9 with an index of 0.96. The lowest RLSTI was recorded in G1 (0.82). The SLSTI ranged between 0.87 (G7) and 0.97 (G9).

Genotype 14 had the highest total fresh weight (TFW) STI value of 0.96, while G7 had the lowest (0.50). For the total dry weight (TDW) STI, G14 exhibited the highest (0.98), while G3 had the lowest (0.67). Although the STIs of most genotypes were high, G14, G16, and G17 were consistently ranked as top performers for all calculated indices.

Correlations Between the Stress Tolerance Indices

Most stress tolerance indices showed significant positive correlation coefficients (

Table 6. Correlation coefficients between stress tolerance indices.

	GSTI	RLSTI	SLSTI	TFWSTI	TDWSTI
GSTI	1
RLSTI	0.69 **	1
SLSTI	0.69 **	0.60 **	1
TFWSTI	0.39 ns	0.63 **	0.58 *	1
TDWSTI	0.25 ns	0.58 *	0.54 *	0.94 ***	1

GSTI: germination stress tolerance index, RLSTI: root length stress tolerance index, SLSTI: shoot length stress tolerance index, TFWSTI: total fresh weight stress tolerance index, TDWSTI: total dry weight stress tolerance index, ^ns: non-significant (p > 0.05), *: significant at p < 0.05, **: significant at p < 0.01, ***: significant at p < 0.001.

). These indices included GSTI, which was positively correlated with RLSTI (0.69) and SLSTI (0.69). The root length stress tolerance index was positively correlated with SLSTI (0.60), TFWSTI (0.63), and TDWSTI (0.58). The shoot length stress tolerance index was positively correlated with TFWSTI (0.58) and TDWSTI (0.54). The total fresh weight stress tolerance index was highly and positively correlated with DWSTI (0.94).

3. Discussion

This study elaborates on the effects of salinity stress on germination, growth, and biomass accumulation in sunflower genotypes. It provides insights into how different genotypes adapt to saline environments at the early seedling stage by possibly employing various physiological and biochemical mechanisms.

3.1. Effects of Salinity Stress on Germination

Reduced germination speed and percentage can be attributed to decreased water absorption by seeds due to the low osmotic potential created by salinity [35]. According to [36], the delay in germination is due to the toxic environment created by the accumulation of Na⁺ and Cl⁻. These ions disrupt protein metabolism, hormone balance, and the activity of enzymes, such as α-amylase, which is responsible for converting starch stored in the endosperm into sugars. These sugars serve as an energy source for the growing embryo and their shortage hampers plant growth and development [37]. A study by [38] showed how reduced α-amylase activity was pronounced in saline-sensitive wheat genotypes, leading to germination inhibition. Furthermore, a low sugar concentration alters the cell’s osmotic potential [39], resulting in low water uptake and a delayed germination process.

Reduced capacity in the production of a germination stimulus, such as gibberellic acid, and reduced membrane permeability during salinity stress can potentially limit the germination rate [40]. This may explain the reduced germination observed, including the complete inhibition in some genotypes. These findings corroborate previous observations in maize, tomato (Solanum lycopersicum L.), and pumpkin (Cucurbita pepo L.) [41,42,43]. Genotypes which had a high germination speed and germination percentages such as G9 and G14 potentially possess mechanisms for osmotic adjustment, allowing them to absorb water, maintain higher enzyme activity, and germinate faster under saline conditions. According to [15], germination index and seedling vigor are efficient traits, and they are highly recommended for use when screening sunflower genotypes for salt tolerance.

3.2. Effects of Salinity Stress on Seedling Morphology

Salinity stress induces osmotic stress by limiting water uptake through the roots, thereby reducing cell elongation and expansion in both shoots and roots. According to [44], turgor pressure, which is essential for cell expansion, is the basis of crop growth; hence, its reduction under stress leads to reduced shoot and root length. Furthermore, the abundance of toxic Na⁺ and Cl⁻ ions, which compete with major ions such as K⁺ or Ca²⁺ under saline conditions, can induce nutrient deficiency [13,18]. Potassium and calcium ions are vital in maintaining cellular processes like protein synthesis and enzyme activity [45]. As such, their deficiency significantly reduces the plant’s ability to maintain its physiological processes under saline environments, resulting in an overall growth reduction [46].

During salinity stress, an excessive accumulation of Cl⁻ may result in low shoot nitrogen caused by the antagonism between Cl- and NO⁻₃ [47]. Additionally, an increase in Cl⁻ accumulation reduces the uptake of phosphorus [48], thus further inhibiting plant growth. In severe cases, salinity causes the overproduction of reactive oxygen species (ROS) leading to oxidative damage, which also reduces plant growth [49,50,51]. Similar findings were obtained in several studies at early growth stages in different crops such as maize [41], sorghum (Sorghum bicolor (L.) Moench) [35], and sunflower [21]. Generally, G9, G14, G16, and G17 maintained relatively longer shoot and root lengths than other genotypes, indicating better salinity tolerance at the early seedling stage. The ability to withstand stress by these genotypes can be attributed to mechanisms such as ion exclusion or selective ion compartmentalization in vacuoles [18,52,53], which help plants to maintain normal metabolic processes.

3.3. Effects of Salinity Stress on Water Content

Water content was significantly lowered in saline-stressed plants relative to the control, indicating dehydration caused by osmotic stress. Salinity reduces the water potential of the growing medium [54], thereby limiting water uptake by plants. This dehydration leads to reduced cellular turgidity [20], further limiting growth and biomass accumulation. The low seedling water content observed in this study may also have been attributed to root growth inhibition or reduced root function, which negatively affect the water uptake of plants exposed to saline environments. Moreover, salinity may have induced damage to the root membrane, thus reducing its permeability to water [55]. However, G14 and G16 maintained a relatively higher water content, suggesting that they possess more effective osmotic adjustment mechanisms under stress. Such mechanisms may involve the accumulation of osmolytes, such as proline, glycine betaine, or soluble sugar, which help plants to maintain turgor pressure by retaining water under salt stress [56].

3.4. Effects of Salinity Stress on Biomass Accumulation

The reduced biomass accumulation may be attributed to the reduced water and nutrient uptake, which lead to cellular dehydration and limited cell expansion, and a decline in photosynthesis and metabolic activities [57]. This observation is consistent with findings on sunflower [17], rice (Oryza sativa L.) [58], and wheat [59] grown under saline conditions. The disruption of the nutrient balance, particularly nitrogen (N), phosphorus (P), and potassium (K), which are essential for metabolic activities that facilitate growth, can reduce biomass production and accumulation [45].

Although biomass accumulation was reduced in all genotypes, G9 and G14 maintained a relatively higher biomass across environments. This may be attributed to mechanisms such as the activation of antioxidant defense systems which reduce the oxidative stress caused by ROS commonly produced under salinity stress [60]. Furthermore, ion exclusion mechanisms assist such genotypes in regulating ion uptake, thereby preventing ion toxicity, and allowing plants to absorb essential nutrients under salinity stress [61,62], thereby facilitating biomass accumulation.

3.5. Stress Tolerance Indices

According to [34], genotypes that show high STI values are considered tolerant to the stress imposed. Generally, all genotypes had high STIs except for GSTI, thereby exhibiting some tolerance to salinity stress at the early seedling stage. Genotypes 9, 14, 16, and 17 were consistently the top performers in most of the indices calculated, including GSTI, indicating their superiority under saline stress. Genotypes that consistently tolerated salt stress at the seed germination and early seedling growth stages likely possessed genetic traits that enabled them to perform well. Most of these stress tolerance indices showed a significant positive correlation with one another, indicating their reliability for identifying salt-tolerant genotypes at the early seedling stage. According to [15], the success of most conventional breeding programs for salt tolerance is greatly limited by the lack of accurate and reliable salt tolerance evaluation traits.

4. Materials and Methods

The experiment was conducted at the University of Fort Hare, Plant Genetics Laboratory (32°46′ S latitude, 26°50′ E longitude). Seventeen sunflower genotypes (G1, G2, G3, G4, G5, G6, G7, G8, G9, G10, G11, G12, G13, G14, G15, G16 and G17) were assessed in this study. Seeds of each genotype were sourced from five different seed companies operating in South Africa.

4.1. Experiment 1: Germination Assay

The protocol described by [29] was used to conduct the germination experiment with moderate modifications. Sodium chloride (NaCl) at a 200 mM concentration was used to induce salinity stress, since sodium and chloride are the two salts mainly associated with salinity conditions in soils [15,63]. The concentration of sodium chloride used in this study was chosen based on previous protocols [15,17,64], with minimum modifications.

Ten seeds of the same size from each variety were selected and surface-sterilized using 1% sodium hypochlorite solution for five minutes and were rinsed three times with deionized water. Thereafter, seeds of each genotype were placed in Petri dishes containing filter papers moistened with 5 mL of 200 mM NaCl. Deionized water (0 mM NaCl) was used for the control. The Petri dishes were placed in an incubator set at 25 °C and were arranged in a completely randomized design with three biological replicates. Each replicate occupied a different shelf and the randomize design option in GenStat software version 24.1 was used to assign a specific position to each Petri dish. The Petri dishes were kept moist by the daily addition of 200 mM NaCl and deionized water to the stressed and non-stressed treatments, respectively. The experiment was terminated after seven days.

4.2. Experiment 2: Hydroponic Experiment

A total of six healthy seedlings of each genotype germinated under non-stressed conditions for seven days were selected and transferred to plastic trays containing Hoagland nutrient solution (

Table 7. List of nutritional elements in the Hoagland solution.

Nutritional Element	K	Ca	N	Mg	Na	Cu	Cl	Mn	Mo	Zn	B	Fe
Concentration (mg/L)	23.5	48.1	42.6	14.6	0.06	0.06	0.03	0.03	0.03	0.16	0.32	1.67

K: Potassium, Ca: Calcium, N: Nitrogen, Mg: Magnesium, Cu: Copper, Cl: Chloride, Mn: Manganese, Mo: Molybdenum, Zn: Zinc, B: Boron, Fe: Iron.

) for two days of acclimatization. The seedlings were then transferred to a new Hoagland nutrient solution supplemented with NaCl to achieve a final concentration of 200 mM (NaCl), where they were maintained for three days. Three biological replicates were used, and randomization was performed using the randomize design option in GenStat software version 24.1. The control experiment had 0 mM of NaCl. In both treatments, the pH was maintained at 5.9. The seedlings were placed on a perforated polystyrene sheet which floated on top of the nutrient solution. Each seedling occupied a hole of 2 mm in diameter, and only the roots were immersed in the nutrient solution. The experiment was terminated after five days. Two runs of both experiments were conducted between September and November 2024.

A schematic representation of the experimental workflow used to evaluate the response of the sunflower genotypes to salinity stress using the germination and hydroponic assays is shown in Figure 2.

4.3. Data Collection

In experiment one, the number of germinated seeds was recorded every day for seven days. Seeds with a radicle protrusion that was at least 2 mm long were considered germinated. In experiment two, morphological traits such as root and shoot length were measured using a flexible ruler at termination, that is, 12 days after initiating the hydroponic experiment. The fresh root and shoot weights were measured using an analytical digital scale (Preciso EJ-323A+, A&D Company, Tokyo, Japan) with a sensitivity of 0.001 g. Dry root and shoot weights were determined after oven-drying the seedlings at 60 °C for 24 h (until a constant weight was reached).

The germination percentage and germination speed were calculated using the following formulas:

Germination percentage (GP) was calculated according to [65]:

$$Germination percentage={\displaystyle \frac{Number of seeds germinated }{Total number of seeds}}\times 100$$

The speed of germination (SG) was calculated according to [66]:

$$Speed of germination={\displaystyle \frac{N1}{T1}}+\dots +{\displaystyle \frac{Nn}{Tn}}$$

where N is the number of germinated seeds and T is the number of days taken to germinate.

Water content (WC) was calculated according to [56]:

$$Water content={\displaystyle \frac{ Fresh weight \left( FW\right)-Dry weight (D W)}{FW}}\times 100\%$$

Total seedling length was determined by adding the root and shoot lengths. Similarly, the total fresh weight and dry weight were determined by adding the root and shoot fresh and dry weights, respectively.

Stress tolerance indices for germination, root length, shoot length, and fresh and dry weights for each variety were calculated using the formula by [15]:

$$STIi= {\displaystyle \frac{Vin}{Vic}}$$

STI_i is the STI of trait i, and V_ic and V_ic represent the values of trait i in the salt-stressed treatment and the control, respectively.

4.4. Statistical Analysis

Data were analyzed using JMP software package version 17.0. The Shapiro–Wilk test was used to confirm data normality. Bartlett’s test was used to assess the homogeneity of variances. A combined two-way analysis of variance (ANOVA) was conducted to determine significance of the data. Post hoc analysis was conducted using Tukey’s HSD test at the 5% probability level.

5. Conclusions

Genotypes 9, 14, 16, and 17 consistently exhibited high STIs, thereby indicating their tolerance to salinity stress at the early growth stages under laboratory conditions. These genotypes can form the basis of the genetic resources needed in salinity tolerance breeding initiatives, given the lack of commercially available tolerant sunflower cultivars in South Africa, to the best of our knowledge. However, there is a need for further research focusing on evaluating these genotypes at different growth stages under greenhouse and field conditions, although previous similar studies showed a high correlation between results obtained under laboratory and field conditions [67]. Future research should incorporate a gradient of salinity treatments to establish precise tolerance thresholds to better understand genotype-specific responses. In addition, physiological, proteomic, and molecular studies should be conducted to investigate the intricate mechanisms underlying salinity tolerance. Such comprehensive approaches will enhance the development of sunflower genotypes with improved performance in salt-affected agricultural lands, contributing to sustainable crop production in such environments.

6. Limitations

This study was conducted under controlled laboratory conditions and therefore does not reflect genotype performance under field environments, where multiple and interacting stress factors occur. The evaluation was limited to a single salinity level based on recommendations from previous studies, which restricted the ability to assess genotype responses across a gradient of salt concentrations, thereby determining salinity tolerance thresholds. Furthermore, the short duration of the experiments captured the early seedling responses and did not allow for the assessment of the long-term impacts on further phenological development or grain yield and quality. Moreover, this study lacked physiological, biochemical, or molecular analyses, such as ion accumulation, osmolyte profiling, or gene expression data, which are essential to understand the underlying mechanisms of salinity tolerance. Future research should address these limitations to ascertain the selection and development of salt-tolerant sunflower genotypes.