Comprehensive Evaluation and Screening for Salt Tolerance Germplasms at Seedling Stage in Eggplant

Fang, Yu; Wang, Zhiguo; Du, Yingnan; Di, Shuaitao; Gao, Zhenwei; Chen, Xueping; Zhang, Weiwei; Song, Lijun; Luo, Shuangxia; Li, Qiang

doi:10.3390/horticulturae11060697

Open AccessArticle

Comprehensive Evaluation and Screening for Salt Tolerance Germplasms at Seedling Stage in Eggplant

by

Yu Fang

,

Zhiguo Wang

,

Yingnan Du

,

Shuaitao Di

,

Zhenwei Gao

,

Xueping Chen

,

Weiwei Zhang

,

Lijun Song

,

Shuangxia Luo

^*

and

Qiang Li

^*

Key Laboratory of Vegetable Germplasm Innovation and Utilization of Hebei, Collaborative Innovation Center of Vegetable Industry in Hebei, College of Horticulture, Hebei Agricultural University, Baoding 071000, China

^*

Authors to whom correspondence should be addressed.

Horticulturae 2025, 11(6), 697; https://doi.org/10.3390/horticulturae11060697

Submission received: 6 May 2025 / Revised: 12 June 2025 / Accepted: 14 June 2025 / Published: 17 June 2025

(This article belongs to the Special Issue Recent Advances in Genetics, Breeding, and Biotechnology of Solanaceous Crops)

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Abstract

:

Salt stress presents a major environmental constraint to global agricultural productivity and crop yield stability. Eggplant (Solanum melongena L.) is one of the most extensively cultivated Solanaceae crops worldwide, and the characterization of its germplasm for salt tolerance is essential to develop breeding programs to target its abiotic stress resilience. In this study, 200 mmol/L NaCl was identified as the initial screening concentration for the discrimination of salt tolerance levels in eggplant seedlings. Salt tolerance indices derived from 13 descriptors, including the plant height, stem diameter, and leaf number, were used to evaluate 165 germplasm resources (108 inbred lines and 57 commercial cultivars). These 165 germplasms were grouped into five groups, and six highly tolerant and eight highly sensitive germplasms were identified. Importantly, a stepwise multiple linear regression model incorporating the root surface area, leaf number, leaf water content, malondialdehyde content, and stem water content achieved 90.02% predictive accuracy, establishing a high-throughput screening protocol for germplasm selection. This systematic approach provides methodological advancements for precision breeding and identifies key physiological and morphological markers for salt tolerance improvement in eggplant.

Keywords:

eggplant; salt tolerance; comprehensive evaluation; linear regression model

1. Introduction

Soil salinization is an increasingly severe global phenomenon that significantly affects plant growth and agricultural production [1]. Currently, approximately 1 billion hectares of land worldwide are affected by excess salinity, accounting for about 7% of the global land area, and this is growing at a rate of 2 million hectares per year [2,3]. China ranks third globally in terms of its saline–alkali land area, with 99.13 million hectares, including 9.913 million hectares affected by excess salinity, which is equivalent to ~10% of the global total of 1 billion hectares [4].

Salt stress disrupts many stages of crop life cycles, including seed germination, vegetative growth, and reproductive development, and poses a critical threat to sustainable agricultural production and food security [5,6]. Crops employ a variety of morphological, physiological, biochemical, and molecular adaptive strategies to mitigate salt stress [7]. For example, osmotic regulation maintains ion homeostasis; vacuolar sequestration prevents cytotoxic ion accumulation; and enhanced antioxidant enzyme activity protects against oxidative damage [8]. Consequently, numerous screening or breeding programs have been developed to create salt-tolerant crop varieties and to improve saline–alkali land utilization and alleviate food shortages [9,10]. Notable examples include Nangengyan No. 1, a salt-tolerant rice cultivar developed by the Jiangsu Academy of Agricultural Sciences, which achieved an average yield of 544.2 kg/667 m² under 0.5% saline irrigation in 2019 while meeting the Grade 2 quality standards of China’s edible rice industry (NY/T 593–2021) [11]. The Chinese wheat breeding program includes over 700 lines under salt–alkali tolerance evaluation, with Hangmai 802 yielding over 0.675 kg/m² on moderately saline–alkali soils [12]. Similarly, the Chinese Academy of Sciences screened 2000 soybean accessions to breed Dongsheng 118, a high-yielding variety that produces 0.225 kg/m² on heavily saline–alkali soils (pH 9.0), surpassing the national average of 0.195 kg/m² on standard farmland [13]. These examples demonstrate the potential of breeding crops for both high salt tolerance and high yields.

Studies indicate that salt tolerance varies across plant growth stages. For example, pepper hybrids exhibit greater resilience during germination than at the seedling stage, with the germination rates declining significantly only at 150 mmol/L NaCl, whereas seedling growth descriptors (e.g., plant height, leaf area, biomass) are reduced at 10 mmol/L NaCl treatment [14]. Rice seedlings exposed to saline water (8–12 dS/m) for 24 days showed reduced root lengths, fresh/dry biomass, and root dry weights compared with controls [15]. Similarly, oat seedlings treated with 300 mmol/L NaCl for 15 days exhibited marked reductions in plant height, root elongation, and water content [16]. These findings underscore the importance of screening at the early growth stage for salt tolerance.

Principal component analysis (PCA) and membership function analysis (MFA) provide robust methods for salt tolerance evaluation and have been widely applied in crops such as oats and alfalfa [6,16,17]. For example, Zhang classified 100 oat varieties into three groups (17 salt-tolerant, 27 moderately tolerant, 56 sensitive) using PCA and MFA [16]. Benabderrahim identified three salt-tolerant alfalfa genotypes from 36 accessions using tolerance indices and PCA [17]. Yu et al. integrated PCA, MFA, cluster analysis, and stepwise regression to categorize 20 alfalfa germplasms into four tolerance classes and developed a predictive model (95.95% accuracy) based on the stem biomass, Na⁺/K⁺ ratio, and shoot–root fresh weight ratio [6]. Alternative approaches, such as salt tolerance indices (STIs), have also been used to classify maize [18,19]. Masuda grouped 20 maize lines into four categories (highly tolerant to sensitive) using STIs (0.49; 0.27 < STI < 0.40; 0.12 < STI < 0.24; STI < 0.10) [18], while Sultana identified BARI No. 5 as the most salt-tolerant of four maize varieties (BARI No. 5 > Mosaic Corn > BARI No. 7 and Common Corn) under saline–alkali conditions [19].

Eggplant (Solanum melongena L.) is a globally significant Solanaceous crop that is moderately sensitive to salt stress [20,21]. China leads global eggplant production, with 833,200 cultivated hectares and 39.28 million tons harvested in 2023 (FAOSTAT). Studies have shown growth stage-specific responses to salinity. For example, Kemer outperformed Pala and Aydin Siyahi during germination at 50–150 mmol/L NaCl, whereas Pala exhibited higher relative root and shoot biomass at 150 mmol/L [22]. Wu et al. identified the proline content and seedling vigor index as key indicators for rapid cultivar screening, classifying Funong Green Eggplant and Nongyou Long Eggplant as salt-tolerant varieties using PCA and MFA [23].

Despite advances in genetic and physiological research on eggplant salt tolerance, few salt-tolerant germplasms are currently available [24,25]. While the evaluation of natural populations has proven effective in maize, soybean, and rice [16,26,27], similar studies on eggplant remain limited. In this study, we evaluated 165 eggplant germplasms for seedling-stage salt tolerance and established a comprehensive evaluation model, providing insights for the precision phenotyping and breeding of salt-tolerant varieties.

2. Materials and Methods

2.1. Plant Materials

This study utilized 57 commercial eggplant varieties (Table 1) and 108 inbred lines (Table 2), provided by the Hebei Key Laboratory of Vegetable Germplasm Innovation and Utilization. A subset of 15 randomly selected germplasms (21C48, 21C41, 21C6, 21C170, 21C154, 21C9, 21C21, 21C16, 21C7, 21C207, 21C200, 21C4, 21C60, 21C243, and 21C145) was used to determine the appropriate NaCl concentration for subsequent experiments.

2.2. Determination of Optimal Salt Stress Levels

The fifteen germplasms listed in Section 2.1 were randomly selected and subjected to NaCl stress. Seeds were soaked in water at 55 °C and then sown into 12 × 12 × 9.4 cm square pots (five seeds per pot, three pots per treatment) containing peat moss, vermiculite, and perlite (1:1:1/v:v:v) on 12 June 2024. The seedlings were grown in a greenhouse at Hebei Agricultural University, Baoding (E 115°42′, N 38°81′). After cotyledon emergence, three seedlings were kept per pot. At the two-leaf stage, NaCl solutions (100, 200, 250, or 300 mmol/L) were applied as treatments on 29 June 2024, when the seedlings had at least three true leaves. Distilled water was used as the control. Each pot was treated with 250 mL of solution every 2–3 d, depending on the prevailing weather conditions, for a total of six applications over 15 days. Seedlings were harvested to measure the following growth descriptors: plant height (PH), root length (RL), leaf number (LN), leaf surface area (LSA), root fresh/dry weight (RFW/RDW), stem fresh/dry weight (SFW/SDW), and leaf fresh/dry weight (LFW/LDW).

The STI and salt sensitivity index (SSI) were calculated as

S T I = \frac{T r a i t v a l u e u n d e r s a l t s t r e s s}{T r a i t v a l u e u n d e r c o n t r o l}

S S I = 1 - S T I

2.3. Salt Tolerance Screening of Germplasm

The seeds of the 165 germplasms were sown on 4 September 2024. On 29 September, when the seedlings had at least three true leaves, they were subjected to 200 mmol/L NaCl treatment (170 mL per pot). This was followed by two applications each of 300 mmol/L, 400 mmol/L, 500 mmol/L, and 600 mmol/L NaCl solutions. The control group received an equal volume of distilled water instead of the NaCl solution at each step. Following these treatments, the PH, stem diameter (SD), LN, chlorophyll content (Chl), LSA, malondialdehyde content (MDA), RL, root volume (RV), root surface area (RSA), root tip number (RTN), and root/stem/leaf water content (RWC/SWC/LWC) were measured. The STI values were derived for each trait. The seed treatments, square pot sizes, and substances were as described in Section 2.2. This experiment was performed at the greenhouse at Hebei Agricultural University, Baoding (E 115°42′, N38°81′).

2.4. Descriptor Measurements

PH: Measured from the substrate surface to the growth point using a steel ruler (0.01 cm precision). SD: Recorded 3 cm above the substrate using a digital caliper (0.01 mm precision). LN: Counted as fully expanded leaves from the first true leaf. LSA: Quantified using an LI-3100C leaf area scanner (LI-COR Biosciences, Cambridge, UK). Root architecture (RL, RSA, RV, RTN): Analyzed using a plant image analysis system (LA-S, Hangzhou Wanshen Detection, Hangzhou, China).

2.5. Evaluation of Seedling Physiological Indices

The fresh weight (FW) and dry weight (DW) of the roots, stems, and leaves were determined before and after oven drying at 70 °C to a constant mass. The water content was calculated as

W a t e r C o n t e n t (%) = \frac{F W - D W}{F W} \times 100 .

The chlorophyll content of the 3rd–4th leaves was measured using a SPAD-502PLUS chlorophyll meter (Konica Minolta, Tokyo, Japan). The malondialdehyde (MDA) content was measured using a thiobarbituric acid (TBA) assay. Fresh tissue (0.2 g) was homogenized in 10% trichloroacetic acid, centrifuged (12,000× g, 10 min), and the supernatant reacted with 0.67% TBA. Absorbance at 450, 532, and 600 nm was measured after boiling (30 min) and cooling.

2.6. Statistical Analysis

The coefficient of variation (CV) was calculated for each trait as

C V = \frac{μ}{σ} \times 100 %,

where σ = standard deviation and μ = mean.

The subordinate function (U) and weight (W_i) were computed to derive the comprehensive salt tolerance descriptor (D):

U (X_{i}) = \frac{X i - X m i n}{X m a x - X m i n} W_{i} = \frac{P_{i}}{\sum_{I = 1}^{n} P_{i}} D = \sum_{I = 1}^{n} U (X_{i}) \times W_{i}

where Xi = trait value, Xmax/min = maximum/minimum values, and P_i = principal component contribution of the ith trait value.

The data were analyzed using IBM SPSS Statistics v.26 and visualized using Origin 2021. Stepwise regression linked STI values (independent variables) to D values (dependent variable) to establish an optimal predictive model.

3. Results

3.1. Optimal Salt Concentration for Screening

Following 15 days of exposure to different concentrations of NaCl, ten growth-related traits (PH, LN, LSA, RL, RFW, RDW, SFW, SDW, LFW, LDW) were measured across 15 germplasms. The linear regression of the SSI showed SSI values of >0.2 under 100–300 mmol/L NaCl. At 200 mmol/L, the mean SSI for all traits was 0.480, with six traits (PH, LN, RL, RFW, SFW, LFW) showing values close to 0.5 (i.e., 0.574, 0.494, 0.470, 0.587, 0.538, and 0.594, respectively), indicating ~50% physiological impairment. This concentration was selected as the baseline of salt treatment for subsequent evaluations (Figure 1).

3.2. Variations in Salt Tolerance Indices

As summarized in Table 3, the STI analysis of 13 traits across 165 germplasms showed coefficients of variation (CVs) ranging from 4.67% (RWC) to 49.44% (LSA). The root and leaf architectural traits showed the highest variability—LSA (49.44%), RV (45.25%), RTN (43.80%), and RSA (42.79%)—highlighting differential trait sensitivity to salinity (Table 3).

3.3. Correlation Analysis of STI Using Different Indices in Seedlings

The correlation analysis grouped the 13 traits into three clusters. These were Cluster I: Chl, MDA, LN, and RWC; Cluster II: root-related traits (RTN, RL, RV, RSA); and Cluster III: LWC, pH, SWC, LSA, and SD (Figure 2). The strongest correlations occurred between RL and RSA (r = 0.907, p < 0.01), RSA and RV (r = 0.901, p < 0.01), and RL and RV (r = 0.704, p < 0.01). Weaker inter-cluster correlations (r < 0.50) underscored the need for multivariate analysis (Figure 2).

3.4. Principal Component Analysis of STI

PCA suitability was confirmed using a Kaiser–Meyer–Olkin (KMO) score of 0.644 and Bartlett’s test (p = 0.00) (Table 4). Seven principal components (PCs) cumulatively explained >80% of the variance (Table 4). PC1 (22.998% variance) showed high loadings for root traits (RSA, RL, RV, RTN), while subsequent PCs captured contributions from physiological and morphological traits (Table 5).

3.5. Membership Function Evaluation

The comprehensive weights (W₁–W₇) for the seven PCs were 0.283, 0.165, 0.119, 0.111, 0.109, 0.108, and 0.106, respectively. The resultant comprehensive tolerance descriptors (D) ranged from 0.236 (21C60, highly sensitive) to 0.601 (24QX9, highly tolerant), enabling germplasm ranking (Table 6).

3.6. Germplasm Classification by Salt Tolerance

Hierarchical clustering based on the D values categorized the 165 germplasms into five groups: highly tolerant (6); tolerant (35); moderately tolerant (67); sensitive (49); and highly sensitive (8) (Figure 3, Table 7). Representative phenotypes of the extreme groups are shown in Figure 4.

3.7. Stepwise Regression Analysis of STIs Using Different Indices

In this study, the D value was used as the dependent variable and the salt tolerance STI of the 13 indices was used as the independent variable in a stepwise linear regression analysis, using the following equation:

D(F) = −0.424 + 0.206⋅RSA + 0.27⋅LN + 0.347⋅LWC + 0.049⋅MDA + 0.255⋅SWC

The model explained 90.1% of the variance (R² = 0.9002), with 90.02% prediction accuracy, thus validating RSA, LN, LWC, MDA, and SWC as critical screening indicators (Figure 5).

4. Discussion

The establishment of evaluation methods for salt tolerance is of great significance for eggplant. In the present study, we determined the optimal concentration for NaCl treatment using 15 germplasms at the three-leaf stage and found that 200 mM can be used as the baseline for NaCl treatment. In the following experiments, 165 germplasms were initially treated with 200 mM NaCl, followed by 300, 400, 500, and 600 mM NaCl treatment. It is worth noting that the growth rates of the 165 germplasms were different, so it was impossible to treat the seedlings at the same stage with the same number of true leaves. Therefore, the seedlings of the 165 germplasms were initially treated with NaCl when all seedlings had at least three true leaves. Some studies indicate that different growth stages show different salt tolerances [14]. However, the stages are entirely different, such as the germination stage, seedling stage, or adult plant stage. In the present study, although the growth stages among the germplasms were not exactly the same, all of them were at the seedling stage, with different numbers of true leaves. Therefore, the methods for the evaluation of salt tolerance in the present study are reasonable and can provide a reference for other crops in salt tolerance evaluation.

Crop salt tolerance is a complex trait governed by coordinated metabolic pathways and genetic mechanisms, necessitating multi-indicator evaluations for comprehensive assessment [28]. Current screening methodologies integrate correlation analysis, PCA, MFA, cluster analysis, and linear regression to minimize the errors inherent in single-index approaches, thereby enhancing the reliability [29]. Among these, the STI has proven particularly effective in evaluating stress resilience [30].

The experimental salt concentration applied critically influences the screening outcomes: suboptimal levels may inflate false positives for tolerance, while excessive concentrations risk overestimating the sensitivity [31]. Previous studies have employed diverse methods to identify the optimal stress levels. Choudhary established a screening concentration for 278 wheat varieties by regressing the SSI values to identify the NaCl level inducing 50% sensitivity [32]. Similarly, Geng determined that 0.5% NaCl exposure over 4–6 weeks during tillering effectively differentiated rice genotypes [33]. In eggplant, Cebeci identified four highly salt-tolerant accessions (S. linnaeanum, S. incanum L., BB, MK) in 150 mmol/L NaCl treatments [34], while Hannachi observed cultivar-specific thresholds: tolerant genotypes (Bonica, Galine) tolerated 80 mmol/L NaCl with minimal Na+/Cl− accumulation, whereas sensitive varieties (Adriatica, Black Beauty) exhibited ion imbalances at 40 mmol/L [25]. As in Choudhary’s research, our study established 200 mmol/L NaCl as the baseline concentration for the screening of 165 eggplant germplasms, based on an SSI regression analysis showing ~50% physiological impairment across ten traits (Figure 1).

The significant correlations among STI values (Figure 2) underscore the overlapping biological responses to salinity, invalidating single-trait evaluations [17,35]. For example, Tian linked rice salt tolerance to the relative shoot/root length, germination vigor, and vitality index (r > 0.7), reducing seven traits to three principal components (91.6% variance) for classification into four tolerance tiers [36]. Similarly, Chunthaburee condensed 12 rice traits into two principal components (72.04% variance) to categorize germplasms [37]. In this study, PCA reduced 13 seedling-stage traits to seven principal components (cumulative variance > 80%; Table 5), with root architecture factors (RSA, RL, RV, RTN) dominating PC1 (24.8% variance). A weighted membership function analysis yielded D values, enabling the classification of the 165 germplasms into five groups: highly tolerant (6), tolerant (35), moderately tolerant (67), sensitive (49), and highly sensitive (8) (Figure 3, Table 6).

Identifying key diagnostic traits simplifies screening protocols and reduces the costs. While the stem biomass, Na+/K+ ratio, and RDW are established indicators in alfalfa and cotton [6,38], eggplant-specific markers remain underexplored. Our stepwise regression model isolated five critical predictors: RSA, LN, LWC, MDA, and SWC. This model explained 90.1% of the variance (r² = 0.901), with 90.02% prediction accuracy (Figure 5), validating its utility for rapid, cost-effective eggplant salt tolerance screening.

5. Conclusions

In this study, 200 mmol/L was identified as the baseline for NaCl stress treatment in eggplant seedlings. A total of 13 traits were analyzed for 165 germplasms, and the traits showed different levels of sensitivity to salinity. A correlation analysis grouped these 13 traits into three clusters, and the strongest correlations occurred between RL and RSA. The 165 germplasms were classified into five distinct categories: six were highly salt-tolerant (HST), 35 were salt-tolerant (ST), 67 were moderately salt-tolerant (MST), 49 were salt-sensitive (SS), and eight were highly salt-sensitive (HSS). A predictive model for seedling-stage salt tolerance was developed, incorporating five key indicators: RSA, LN, LWC, MDA, and SWC. The model achieved 90.02% prediction accuracy (r² = 0.901). These findings provide a reliable framework for the evaluation of salt tolerance in eggplant germplasm.

Author Contributions

This manuscript was written by Y.F., who completed the experimental design and data analysis. Z.W., Y.D., S.D. and Z.G. were involved in data collection and photo acquisition. S.L., Q.L. and X.C. conceived the original screening and research plans; S.L. and Q.L. supervised the experiments; and W.Z. and L.S. helped to harvest the eggplant germplasm. All authors have read and agreed to the published version of the manuscript.

Funding

We appreciate the financial support provided by the “S&T Program of Hebei” (23327501D).

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors upon request.

Conflicts of Interest

The authors declare that they have no competing interest.

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Figure 1. Determination of the optimal sodium chloride concentration for the evaluation of salt tolerance. (A) SSI of plant height (PH), (B) SSI of leaf number (LN), (C) SSI of leaf surface area (LSA), (D) SSI of root length (RL), (E) SSI of root fresh weight (RFW), (F) SSI of root dry weight (RDW), (G) SSI of stem fresh weight (SFW), (H) SSI of stem dry weight (SDW), (I) SSI of leaf fresh weight (LFW), (J) SSI of leaf dry weight (LDW).

Figure 2. Correlation heat map of 13 indices of salt tolerance index. * indicates significant differences at the 0.05 level; ** indicates significant differences at the 0.01 level.

Figure 3. Cluster analysis of salt tolerance of 165 eggplant germplasms; (I) highly salt-tolerant germplasm; (II) salt-tolerant germplasm; (III) moderately salt-tolerant germplasm; (IV) salt-sensitive germplasm; (V) highly salt-sensitive germplasm.

Figure 4. Representative eggplant materials with different salt tolerances. Bar = 5 cm. (A) Highly salt-tolerant germplasm; (B) highly salt-sensitive germplasm.

Figure 5. Linear fit of the predicted value D (F) to the true value D (T).

Table 1. Information of 57 commercial germplasms.

Sequence	Number	Variety Name	Source
1	24QX2	Shenqie two	Shenyang Fengnong Agriculture
2	24QX3	Shenqie one	Shenyang Fengnong Agriculture
3	24QX4	Heibawang	Shenyang Fengnong Agriculture
4	24QX5	Huakui	Shenyang Jinming Hang Agricultural Technology
5	24QX6	Jinmingchang	Shenyang Jinming Hang Agricultural Technology
6	24QX7	Daguolv	Shenyang Jinming Hang Agricultural Technology
7	24QX8	Ziyue	Jinan Tianren Seed
8	24QX9	Yuanqieguanjun	Jinan Tianren Seed
9	24QX10	Jindunlvguan	Xi’an Kington Seed Technology
10	24QX11	New dahongbao	Xi’an Kington Seed Technology
11	24QX12	Zixianqie	Shenyang Fengnong Agriculture
12	24QX13	Yuanqie307	Unknown
13	24QX14	Yuanqieheiqiang	Unknown
14	24QX15	Yuanqieheijie	Unknown
15	24QX16	Gaoke189	Unknown
16	24QX18	Zihong two	Unknown
17	24QX19	Zihong three	Unknown
18	24QX20	Zihong four	Unknown
19	24QX21	Zihong five	Unknown
20	24QX22	Lvqie one	Unknown
21	24QX24	Nanhanheijiaolong	Xi’an Hangfeng Seed Industry
22	24QX25	Changjiangzilong	Xi’an Hangfeng Seed Industry
23	24QX26	Baimawangzi	Xi’an Hangfeng Seed Industry
24	24QX27	Nanhanbaiyuqie	Xi’an Hangfeng Seed Industry
25	24QX28	Heipangzi	Xi’an Hangfeng Seed Industry
26	24QX29	Meijiaozi six	Xi’an Hangfeng Seed Industry
27	24QX30	Zhusiqie	Xi’an Hangfeng Seed Industry
28	24QX31	Zirong six	Guangdong Gannong Agricultural Technology
29	24QX32	Meigui	Guangdong Gannong Agricultural Technology
30	24QX33	Zirong eight	Guangdong Gannong Agricultural Technology
31	24QX34	Feicui	Guangdong Gannong Agricultural Technology
32	24QX35	A116	Unknown
33	24QX36	Laolunsi	Beijing Zhongnong Kunchuang Seed
34	24QX37	AGC6317	Unknown
35	24QX38	Fengyuanheichangie	Xi’an Golden Seed Fengyuan Seed Industry
36	24QX39	Fengyuandaminqie	Xi’an Golden Seed Fengyuan Seed Industry
37	24QX40	Fengyuankuaiqie	Xi’an Golden Seed Fengyuan Seed Industry
38	24QX41	Fengyuanlvguanqie	Xi’an Golden Seed Fengyuan Seed Industry
39	24QX42	Fengyuanziguan	Xi’an Golden Seed Fengyuan Seed Industry
40	24QX43	Fengyuanziyuanqie	Xi’an Golden Seed Fengyuan Seed Industry
41	24QX44	Caoqingqie	Henan Dazheng Runhe Seed Industry
42	24QX45	Bailong332	Fangzhen Agriculture
43	24QX47	Hangqie one	Shouguang Xinxinran Horticulture
44	24QX48	Heibao two	Shouguang Xinxinran Horticulture
45	24QX49	Fenyanhua	Shouguang Xinxinran Horticulture
46	24QX51	Zidaichangqie	Shouguang Xinxinran Horticulture
47	24QX52	Guangshenxianqie	Shouguang Xinxinran Horticulture
48	24QX54	Heiliangzai	Jing Yan Yi Agricultural Seed Technology
49	24QX55	Yuhang	Shouguang Xinxinran Horticulture
50	24QX58	Zili	Xi’an Jinsheng Seed Industry
51	24QX59	Jingqieheiba	Jing Yan Yi Agricultural Seed Technology
52	24QX60	Jingqie130	Jing Yan Yi Agricultural Seed Technology
53	24QX62	Rongyaochangqie	Shouguang Jinpeng Seed
54	24QX63	Nongda601	Hebei Agricultural University
55	24QX64	Nongda604	Hebei Agricultural University
56	24QX67	Nongda702	Hebei Agricultural University
57	24QX68	Nongda703	Hebei Agricultural University

Table 2. Information of 108 natural population germplasms.

Sequence	Variety Name	Source	Sequence	Variety Name	Source
1	24-477	China	55	21C158	France
2	24-479	China	56	21C161	United States of America
3	14-345	China	57	21C162	United States of America
4	16-562	China	58	21C164	India
5	Sanyue	China	59	21C170	China
6	HQ1315	China	60	21C171	China
7	21C1	Turkey	61	21C172	China
8	21C4	Russian Federation	62	21C175	India
9	21C6	India	63	21C180	China
10	21C9	United Kingdom	64	21C181	Union of Soviet Soc. Rep.
11	21C12	India	65	21C185	Unknown
12	21C13	Union of Soviet Soc. Rep.	66	21C186	Italy
13	21C19	India	67	21C188	Ukraine
14	21C21	Turkey	68	21C198	China
15	21C26	Netherlands	69	21C199	Unknown
16	21C28	Japan	70	21C204	Turkey
17	21C29	Turkey	71	21C205	Turkey
18	21C32	Unknown	72	21C207	Turkey
19	21C34	Unknown	73	21C211	Turkey
20	21C35	United Kingdom	74	21C214	Turkey
21	21C37	Turkey	75	21C216	Turkey
22	21C38	Turkey	76	21C217	Turkey
23	21C41	Germany	77	21C218	Turkey
24	21C43	Japan	78	21C219	Turkey
25	21C44	Nepal	79	21C220	Turkey
26	21C45	India	80	21C221	Turkey
27	21C46	India	81	21C222	Turkey
28	21C48	Malaysia	82	21C226	Japan
29	21C50	India	83	21C228	United States of America
30	21C51	Japan	84	21C229	United States of America
31	21C57	Unknown	85	21C230	Japan
32	21C60	India	86	21C234	India
33	21C61	United States of America	87	21C236	China
34	21C64	India	88	21C241	Iran (Islamic Republic of)
35	21C68	Turkey	89	21C242	Iran (Islamic Republic of)
36	21C90	Turkey	90	21C243	India
37	21C91	Spain	91	21C245	India
38	21C95	Turkey	92	21C247	India
39	21C104	Japan	93	21C249	Turkey
40	21C105	Japan	94	21C250	Turkey
41	21C107	India	95	21C252	China
42	21C108	China	96	21C280	Maldives
43	21C111	Hungary	97	21C288	Ukraine
44	21C126	India	98	21C291	Syrian Arab Republic
45	21C127	India	99	21C293	Syrian Arab Republic
46	21C132	China	100	21C301	China
47	21C135	Iran (Islamic Republic of)	101	21C302	China
48	21C139	India	102	21C305	China
49	21C141	India	103	21C307	China
50	21C144	Turkey	104	21C316	China
51	21C147	Turkey	105	21C317	China
52	21C148	Turkey	106	21C323	China
53	21C154	India	107	21C331	China
54	21C155	Unknown	108	21C336	China

Table 3. Analysis of 13 indices of the salt tolerance index.

Trait	Maximum Value	Minimum Value	Average Value	Standard Deviation	Coefficient of Variation
PH	0.74	0.24	0.456	0.092	20.12%
SD	0.73	0.34	0.492	0.079	15.96%
Chl	1.73	0.79	1.261	0.143	11.32%
LN	0.79	0.33	0.546	0.090	16.45%
LSA	0.76	0.09	0.234	0.116	49.44%
RWC	1.28	0.72	0.961	0.045	4.67%
SWC	1.09	0.59	0.880	0.065	7.38%
LWC	1.10	0.71	0.934	0.058	6.17%
MDA	2.23	0.35	1.030	0.404	39.28%
RL	2.05	0.25	0.663	0.220	33.16%
RTN	4.12	0.21	0.968	0.424	43.80%
RSA	1.61	0.12	0.504	0.216	42.79%
RV	0.89	0.06	0.415	0.188	45.25%

Table 4. KMO and Bartlett ball tests for 13 indices of salt tolerance index.

KMO and Bartlett Ball Tests
Kaiser–Meyer–Olkin sampling adequacy measurement		0.644
	Approx. chi-squared	807.515
Bartlett ball test	df	78
	sig	0.00

Table 5. Principal component analysis of 13 indices of salt tolerance index.

Trait	Principal Component
Trait	1	2	3	4	5	6	7
RSA	0.963	0.076	−0.022	−0.024	−0.001	0.001	0.062
RL	0.918	0.026	0.069	−0.179	0.008	−0.115	0.162
RV	0.892	0.172	−0.107	0.069	0.026	0.149	−0.1
RTN	0.551	−0.042	0.407	−0.277	−0.386	−0.067	0.34
LSA	0.142	0.762	−0.04	−0.094	0.17	0.113	0.225
PH	0.001	0.68	0.318	−0.024	0.106	−0.294	0.04
SD	0.282	0.577	−0.464	−0.085	−0.03	0.304	−0.12
LN	0.020	0.132	0.813	0.208	0.031	0.165	−0.175
MDA	−0.108	−0.123	0.15	0.909	−0.024	0.073	−0.006
LWC	0.007	0.272	0.098	0.02	0.813	−0.033	0.084
RWC	0.003	0.45	0.204	0.406	−0.538	−0.055	−0.03
Chl	−0.006	−0.011	0.1	0.066	−0.001	0.936	0.042
SWC	0.096	0.156	−0.12	−0.001	0.083	0.04	0.925
Eigenvalue	2.99	1.746	1.259	1.17	1.149	1.146	1.119
Contribution rate	22.998	13.432	9.688	9.000	8.839	8.816	8.606
Cumulative contribution rate	22.998	36.430	46.118	55.118	63.956	72.772	81.378

Table 6. Membership function analysis of eggplant comprehensive index and comprehensive evaluation of 165 materials.

Variety Name	Comprehensive Index							Membership Function Value							D Value	Rank
Variety Name	PCA1	PCA2	PCA3	PCA4	PCA5	PCA6	PCA7	UX1	UX2	UX3	UX4	UX5	UX6	UX7	D Value	Rank
24QX2	−0.025	0.214	1.529	1.026	−0.222	1.357	−0.277	0.274	0.459	0.779	0.647	0.409	0.750	0.528	0.499	20
24QX3	−0.157	0.652	−0.639	1.158	−0.437	0.645	0.225	0.253	0.521	0.357	0.672	0.381	0.644	0.600	0.449	50
24QX4	−0.915	0.387	0.466	0.225	−0.490	−0.206	−0.487	0.137	0.483	0.572	0.495	0.374	0.518	0.498	0.391	115
24QX5	−0.185	0.518	−0.169	0.038	−0.238	−0.357	−0.788	0.249	0.502	0.448	0.459	0.407	0.495	0.454	0.404	105
24QX6	−0.650	0.089	0.786	0.835	−0.255	−0.783	−0.056	0.178	0.442	0.634	0.610	0.405	0.432	0.560	0.417	91
24QX7	−0.948	−0.379	1.685	−0.265	0.484	−0.208	−0.387	0.132	0.376	0.809	0.402	0.502	0.518	0.512	0.405	103
24QX8	0.162	−0.239	1.834	1.758	0.331	0.460	0.206	0.302	0.396	0.838	0.785	0.482	0.617	0.597	0.520	12
24QX9	1.479	1.091	1.263	1.150	0.150	2.189	−0.192	0.504	0.582	0.727	0.670	0.458	0.874	0.540	0.601	1
24QX10	−1.338	−0.567	2.184	0.194	−0.042	1.600	0.403	0.073	0.350	0.907	0.489	0.433	0.786	0.626	0.439	61
24QX11	−0.312	−0.094	0.616	1.059	0.060	0.988	−0.498	0.230	0.416	0.601	0.653	0.447	0.695	0.496	0.454	45
24QX12	−0.118	−0.958	0.638	2.319	0.293	1.307	−0.162	0.259	0.295	0.605	0.892	0.477	0.743	0.545	0.483	31
24QX13	0.930	−0.012	1.004	0.060	0.205	0.440	−2.925	0.420	0.428	0.677	0.464	0.466	0.614	0.147	0.454	46
24QX14	0.739	0.092	−0.055	1.616	0.088	0.755	−0.080	0.391	0.442	0.470	0.759	0.450	0.661	0.556	0.503	19
24QX15	0.094	−0.037	−0.402	1.398	0.267	2.715	−0.127	0.292	0.424	0.403	0.717	0.474	0.951	0.549	0.493	24
24QX16	−1.125	0.429	0.864	0.475	−0.296	0.832	−0.178	0.105	0.489	0.649	0.542	0.400	0.672	0.542	0.422	79
24QX18	−1.400	−0.443	1.583	2.103	−0.009	0.507	0.250	0.063	0.367	0.789	0.851	0.437	0.624	0.604	0.446	54
24QX19	0.445	−1.271	2.232	0.390	0.909	0.622	−0.686	0.346	0.252	0.916	0.526	0.558	0.641	0.469	0.487	28
24QX20	0.066	−0.050	1.038	−0.140	−0.448	−0.785	−0.535	0.287	0.422	0.683	0.426	0.380	0.432	0.491	0.420	87
24QX21	1.011	0.131	−0.184	1.426	−1.203	−1.108	−0.702	0.432	0.448	0.445	0.722	0.280	0.384	0.467	0.451	48
24QX22	−0.912	−0.696	1.507	−0.193	−0.890	0.158	−0.325	0.138	0.332	0.775	0.416	0.321	0.572	0.521	0.384	124
24QX24	−0.632	0.073	1.352	−0.027	−0.428	−0.123	0.269	0.181	0.440	0.745	0.447	0.382	0.530	0.607	0.425	75
24QX25	−0.158	−0.693	0.059	−0.071	−0.124	−0.869	−0.855	0.253	0.332	0.493	0.439	0.422	0.420	0.445	0.372	133
24QX26	1.199	1.435	0.431	−0.602	−0.790	0.677	−1.516	0.461	0.630	0.565	0.338	0.335	0.649	0.350	0.483	32
24QX27	−0.312	−0.289	−0.462	0.040	−0.290	0.807	−0.806	0.230	0.389	0.391	0.460	0.400	0.668	0.452	0.390	117
24QX28	0.131	−0.505	1.324	−0.161	−0.663	0.698	−0.429	0.297	0.359	0.739	0.422	0.351	0.652	0.506	0.440	60
24QX29	0.033	0.202	−0.947	0.758	−0.226	0.838	−1.697	0.282	0.458	0.297	0.596	0.409	0.673	0.323	0.408	99
24QX30	−0.170	−0.941	0.918	−0.765	0.612	0.319	−2.858	0.251	0.298	0.660	0.307	0.519	0.596	0.156	0.370	135
24QX31	−1.086	−0.327	0.448	0.807	−0.680	−1.020	−1.555	0.111	0.384	0.568	0.605	0.349	0.397	0.344	0.347	154
24QX32	−0.753	−0.362	0.416	−0.480	−0.216	−0.457	−2.676	0.162	0.379	0.562	0.361	0.410	0.481	0.183	0.331	156
24QX33	0.430	0.456	1.452	0.316	−0.751	−1.374	−0.797	0.343	0.493	0.764	0.512	0.340	0.345	0.453	0.449	51
24QX34	−0.764	−0.819	1.142	0.940	0.185	0.697	−0.795	0.160	0.315	0.703	0.630	0.463	0.652	0.453	0.420	85
24QX35	−0.307	−0.506	0.588	0.015	−0.380	−0.538	−0.721	0.230	0.359	0.596	0.455	0.389	0.469	0.464	0.388	120
24QX36	−1.013	0.593	0.061	0.700	−0.698	−0.880	−0.559	0.122	0.512	0.493	0.585	0.347	0.418	0.487	0.377	131
24QX37	−0.995	−0.480	−0.176	1.736	−0.091	−1.197	−0.197	0.125	0.362	0.447	0.781	0.427	0.371	0.539	0.379	129
24QX38	−0.133	−0.284	0.484	1.668	0.051	−0.835	−0.754	0.257	0.390	0.575	0.768	0.445	0.425	0.459	0.434	65
24QX39	1.354	0.301	0.723	0.203	−0.146	−0.464	−1.597	0.485	0.471	0.622	0.491	0.419	0.480	0.338	0.477	34
24QX40	−0.715	−1.405	1.505	1.267	0.854	0.769	0.184	0.168	0.233	0.774	0.692	0.551	0.663	0.594	0.450	49
24QX41	−1.702	−0.490	1.688	1.412	0.494	−0.139	0.481	0.017	0.361	0.810	0.720	0.504	0.528	0.637	0.420	84
24QX42	−0.196	0.378	0.830	0.678	0.254	0.326	0.132	0.247	0.482	0.643	0.581	0.472	0.597	0.587	0.469	39
24QX43	−0.105	−0.668	1.471	1.271	0.651	−0.837	0.394	0.261	0.336	0.768	0.693	0.524	0.424	0.625	0.467	40
24QX44	−0.557	−0.235	0.478	0.667	−0.024	−1.369	0.619	0.192	0.397	0.574	0.579	0.435	0.345	0.657	0.407	100
24QX45	0.631	−1.052	0.283	2.607	0.087	0.513	0.028	0.374	0.282	0.536	0.946	0.450	0.625	0.572	0.498	21
24QX47	0.209	−0.709	−0.277	2.374	0.109	1.258	0.447	0.309	0.330	0.427	0.902	0.453	0.735	0.632	0.489	27
24QX48	−0.334	0.297	−0.645	0.858	0.090	−0.998	−0.255	0.226	0.471	0.355	0.615	0.450	0.400	0.531	0.401	108
24QX49	0.509	−0.353	−1.274	0.845	−0.229	3.042	0.246	0.355	0.380	0.233	0.613	0.408	1.000	0.603	0.475	35
24QX51	−0.586	0.809	−0.220	0.066	−1.107	0.453	0.603	0.188	0.543	0.438	0.465	0.293	0.616	0.655	0.414	93
24QX52	0.927	−0.249	−0.687	0.385	0.411	0.046	−0.060	0.419	0.395	0.347	0.525	0.493	0.555	0.559	0.456	44
24QX54	−1.216	−1.128	−0.090	0.498	0.764	−0.657	0.936	0.091	0.272	0.463	0.547	0.539	0.451	0.703	0.368	138
24QX55	−0.519	−0.793	0.098	0.864	−0.862	−0.398	0.857	0.198	0.318	0.500	0.616	0.325	0.489	0.691	0.398	109
24QX58	−0.170	0.391	0.101	2.184	−1.933	−0.531	−0.093	0.251	0.484	0.501	0.866	0.184	0.470	0.554	0.436	62
24QX59	−1.014	0.960	−0.190	1.219	−0.658	−0.189	0.779	0.122	0.564	0.444	0.683	0.352	0.520	0.680	0.423	78
24QX60	0.024	−0.212	−0.091	1.196	−1.254	0.022	−1.285	0.281	0.400	0.463	0.679	0.273	0.552	0.383	0.406	102
24QX62	0.746	0.391	0.092	−0.204	−2.214	−0.295	−1.337	0.392	0.484	0.499	0.414	0.147	0.505	0.375	0.406	101
24QX63	−0.646	−1.055	−1.135	1.107	−1.980	0.574	1.184	0.179	0.282	0.260	0.662	0.178	0.634	0.738	0.367	141
24QX64	1.119	−0.688	0.518	2.890	−1.388	−0.827	1.301	0.449	0.333	0.582	1.000	0.256	0.426	0.755	0.516	13
24QX67	−0.955	−0.171	−1.217	0.100	−0.988	0.441	1.290	0.131	0.405	0.244	0.471	0.308	0.614	0.754	0.365	143
24QX68	−0.814	−0.380	−0.504	−0.215	−0.759	0.126	0.237	0.153	0.376	0.383	0.412	0.338	0.567	0.602	0.358	145
24-477	−0.557	−0.455	1.549	0.025	0.426	−0.293	−0.381	0.192	0.366	0.783	0.457	0.495	0.505	0.513	0.421	82
24-479	−0.339	−1.073	0.081	−0.314	0.673	−1.223	−1.611	0.225	0.279	0.497	0.393	0.527	0.367	0.336	0.345	155
14-345	0.470	−0.510	−0.549	0.751	0.059	−0.088	−1.040	0.349	0.358	0.374	0.595	0.446	0.535	0.418	0.419	88
16-562	1.638	0.916	−0.127	0.657	−0.305	0.195	−1.118	0.528	0.557	0.456	0.577	0.398	0.577	0.407	0.509	16
Sanyue	−0.747	−0.910	−0.725	−1.861	−3.328	0.545	−0.320	0.163	0.302	0.340	0.100	0.000	0.629	0.522	0.271	164
HQ1315	−0.284	−0.309	0.078	−1.252	−1.287	−0.139	−0.655	0.234	0.386	0.496	0.215	0.269	0.528	0.474	0.349	151
21C1	−0.488	1.621	−1.616	−0.488	−0.388	0.954	0.067	0.203	0.656	0.166	0.360	0.387	0.690	0.577	0.403	106
21C4	−1.600	−0.301	0.554	−1.361	−0.010	−2.174	−1.105	0.032	0.387	0.589	0.194	0.437	0.226	0.409	0.280	161
21C6	0.826	−0.111	−2.469	−0.841	−0.421	1.434	−1.007	0.404	0.414	0.000	0.293	0.383	0.761	0.423	0.384	125
21C9	0.165	−0.262	−0.660	−0.977	−0.395	−1.295	−2.132	0.303	0.393	0.352	0.267	0.386	0.356	0.261	0.330	157
21C12	1.046	−1.084	1.074	−1.029	−0.584	1.242	−2.100	0.438	0.278	0.690	0.257	0.362	0.733	0.266	0.427	72
21C13	−0.912	1.400	1.355	−1.439	−0.345	0.742	−0.279	0.138	0.625	0.745	0.180	0.393	0.659	0.528	0.421	83
21C19	−1.053	−0.162	−0.275	−0.288	0.496	1.033	1.231	0.116	0.407	0.427	0.398	0.504	0.702	0.745	0.405	104
21C21	−0.141	−0.180	−0.112	−0.471	0.060	0.660	0.069	0.256	0.404	0.459	0.363	0.446	0.647	0.578	0.414	94
21C26	−0.010	−0.119	−0.808	−0.598	−0.294	−1.066	0.692	0.276	0.413	0.324	0.339	0.400	0.390	0.667	0.379	128
21C28	−0.128	0.044	−0.951	−0.456	−0.711	0.698	−0.182	0.258	0.435	0.296	0.366	0.345	0.652	0.542	0.386	122
21C29	−0.553	0.674	−0.532	−1.066	−0.693	0.815	−0.142	0.193	0.524	0.377	0.250	0.347	0.670	0.547	0.382	127
21C32	1.575	−0.660	−0.728	0.282	−0.644	0.639	−0.064	0.519	0.337	0.339	0.506	0.354	0.643	0.559	0.466	41
21C34	−0.618	−0.061	−0.515	−0.167	−0.442	0.058	0.804	0.183	0.421	0.381	0.421	0.380	0.557	0.684	0.387	121
21C35	0.860	−0.711	−0.247	−1.131	−0.014	0.030	0.666	0.409	0.330	0.433	0.238	0.437	0.553	0.664	0.426	73
21C37	2.134	1.015	−0.077	−1.024	0.292	0.850	−0.175	0.604	0.571	0.466	0.258	0.477	0.675	0.543	0.532	9
21C38	3.279	0.519	−0.471	−0.294	−0.882	−1.697	0.562	0.779	0.502	0.389	0.397	0.322	0.297	0.649	0.530	10
21C41	−1.269	0.271	−0.429	−1.290	−1.189	1.786	−0.108	0.083	0.467	0.397	0.208	0.282	0.814	0.552	0.348	152
21C43	−1.812	−0.333	−1.158	−0.727	−1.717	0.177	0.259	0.000	0.383	0.255	0.315	0.212	0.575	0.605	0.278	163
21C44	−1.775	−1.415	0.270	−1.407	0.497	−0.684	0.593	0.006	0.231	0.534	0.186	0.504	0.447	0.653	0.296	160
21C45	−0.690	−0.863	−1.566	−0.580	0.565	−0.710	−0.817	0.172	0.309	0.176	0.342	0.513	0.443	0.450	0.310	158
21C46	−1.214	−0.465	0.245	−0.670	−0.565	1.944	−0.214	0.091	0.364	0.529	0.325	0.364	0.837	0.537	0.372	134
21C48	0.849	0.432	0.174	−0.943	−1.297	−0.981	−0.789	0.407	0.490	0.515	0.274	0.268	0.403	0.454	0.409	98
21C50	0.692	0.648	−1.893	−0.252	−0.169	1.785	−0.341	0.383	0.520	0.112	0.405	0.416	0.814	0.519	0.441	59
21C51	−0.335	0.244	−1.210	−0.906	−0.689	1.079	−0.513	0.226	0.463	0.245	0.281	0.348	0.709	0.494	0.368	140
21C57	0.485	−1.641	0.349	−0.552	−1.836	0.152	1.063	0.352	0.200	0.549	0.348	0.197	0.571	0.721	0.396	110
21C60	−1.507	0.252	−1.726	−0.101	−2.653	−3.695	0.743	0.047	0.465	0.145	0.433	0.089	0.000	0.675	0.236	165
21C61	−0.703	0.126	0.292	−0.314	0.079	0.036	1.521	0.170	0.447	0.538	0.393	0.449	0.554	0.787	0.422	81
21C64	−0.191	0.502	0.433	−0.215	0.644	−0.803	−0.709	0.248	0.500	0.565	0.412	0.523	0.429	0.466	0.418	89
21C68	1.279	−0.825	−0.466	0.200	0.171	−0.914	0.295	0.473	0.314	0.390	0.490	0.461	0.413	0.610	0.446	53
21C90	0.814	0.116	−0.176	−0.605	−0.060	−1.149	−0.142	0.402	0.446	0.447	0.338	0.431	0.378	0.547	0.424	76
21C91	0.639	0.092	1.532	−0.549	0.700	0.667	0.460	0.375	0.442	0.780	0.348	0.531	0.648	0.634	0.506	18
21C95	0.347	0.966	0.148	1.261	0.828	0.321	0.451	0.331	0.564	0.510	0.691	0.548	0.596	0.633	0.515	14
21C104	0.300	−1.730	−0.760	−1.132	1.856	0.086	0.135	0.323	0.187	0.333	0.238	0.683	0.561	0.587	0.386	123
21C105	0.695	−2.140	0.457	−0.755	1.563	0.294	0.117	0.384	0.130	0.570	0.309	0.645	0.592	0.585	0.428	69
21C107	0.254	1.002	−0.557	−0.916	0.194	0.826	0.215	0.316	0.569	0.372	0.279	0.464	0.671	0.599	0.445	56
21C108	−1.153	−0.680	0.918	−1.348	0.096	0.480	0.640	0.101	0.334	0.660	0.197	0.451	0.620	0.660	0.370	136
21C111	−1.059	−0.480	0.776	−1.053	0.861	0.623	0.633	0.115	0.362	0.632	0.253	0.552	0.641	0.659	0.395	111
21C126	0.656	0.671	0.710	−1.282	0.461	−1.478	−0.286	0.378	0.523	0.619	0.209	0.499	0.329	0.527	0.436	63
21C127	0.096	0.489	0.506	−0.966	0.914	−0.301	−0.336	0.292	0.498	0.580	0.269	0.559	0.504	0.519	0.434	64
21C132	−0.304	−0.076	−1.310	−0.319	0.204	−1.848	0.131	0.231	0.419	0.226	0.392	0.466	0.274	0.587	0.347	153
21C135	0.176	0.107	−0.936	−0.251	−0.048	2.327	−0.840	0.304	0.444	0.299	0.405	0.432	0.894	0.447	0.431	66
21C139	0.171	−0.845	−0.839	−0.788	−0.105	−0.124	0.248	0.304	0.311	0.317	0.303	0.425	0.530	0.603	0.376	132
21C141	−0.560	1.244	−0.327	−1.044	−0.644	0.611	−0.464	0.192	0.603	0.417	0.254	0.354	0.639	0.501	0.392	114
21C144	−0.476	1.307	−0.310	−0.239	0.793	0.395	0.420	0.205	0.612	0.421	0.407	0.543	0.607	0.628	0.445	55
21C147	−0.814	−2.426	−0.077	−1.944	4.260	0.528	0.038	0.153	0.090	0.466	0.084	1.000	0.627	0.573	0.360	144
21C148	1.504	−0.356	0.335	0.351	1.418	−0.049	0.548	0.508	0.380	0.546	0.519	0.625	0.541	0.647	0.524	11
21C154	−0.603	−0.226	−1.065	0.093	1.242	0.095	1.448	0.185	0.398	0.273	0.470	0.602	0.563	0.776	0.411	97
21C155	−0.178	−0.997	−0.130	−1.091	2.555	−0.723	−0.112	0.250	0.290	0.456	0.246	0.775	0.441	0.552	0.391	116
21C158	−0.506	−0.429	−0.110	−0.840	0.774	1.408	0.742	0.200	0.369	0.460	0.293	0.541	0.757	0.675	0.417	90
21C161	0.198	−1.027	0.633	0.437	0.426	−0.129	0.945	0.308	0.286	0.604	0.535	0.495	0.529	0.704	0.451	47
21C162	−0.080	−0.460	−1.531	−0.303	−0.259	0.008	0.853	0.265	0.365	0.183	0.395	0.404	0.550	0.691	0.377	130
21C164	−1.027	−0.944	−0.135	−1.091	−0.477	−0.081	1.976	0.120	0.297	0.455	0.246	0.376	0.537	0.852	0.354	148
21C170	−0.546	0.332	0.805	−1.232	−1.270	0.582	1.377	0.194	0.476	0.638	0.219	0.271	0.635	0.766	0.413	95
21C171	0.279	−1.546	−0.754	−0.161	−2.014	1.168	1.253	0.320	0.213	0.334	0.422	0.173	0.722	0.748	0.388	119
21C172	−0.087	−0.686	−0.847	−1.023	−1.970	0.418	0.783	0.264	0.333	0.316	0.258	0.179	0.611	0.681	0.354	149
21C175	1.390	−0.151	0.192	−0.929	−0.826	0.658	−0.490	0.490	0.408	0.518	0.276	0.330	0.646	0.497	0.457	43
21C180	−1.219	−0.396	0.207	−0.978	−0.490	−0.078	0.943	0.091	0.374	0.521	0.267	0.374	0.537	0.704	0.352	150
21C181	0.361	−0.739	−0.833	0.238	−0.869	0.881	0.764	0.333	0.326	0.319	0.497	0.324	0.679	0.678	0.422	80
21C185	0.467	−1.840	−1.392	2.246	−0.006	−0.814	0.720	0.349	0.172	0.210	0.878	0.438	0.428	0.671	0.415	92
21C186	3.769	−2.441	0.945	0.532	−1.200	0.191	1.418	0.854	0.088	0.665	0.553	0.280	0.577	0.772	0.572	4
21C188	4.719	−3.070	2.664	−2.387	−1.208	−2.768	2.380	1.000	0.000	1.000	0.000	0.279	0.138	0.910	0.544	7
21C198	−0.398	−0.808	−0.057	−0.964	0.058	−0.459	−3.944	0.216	0.316	0.470	0.270	0.446	0.480	0.000	0.300	159
21C199	−0.134	−1.406	−2.103	−0.049	−0.055	1.041	0.252	0.257	0.233	0.071	0.443	0.431	0.703	0.604	0.356	147
21C204	0.263	−0.786	−0.870	−0.823	0.408	−0.585	−0.452	0.318	0.319	0.311	0.296	0.492	0.462	0.503	0.369	137
21C205	0.376	−0.447	−1.127	−0.217	1.051	−1.473	−2.137	0.335	0.367	0.261	0.411	0.577	0.330	0.260	0.358	146
21C207	−0.061	−0.506	−1.406	1.254	0.098	−0.089	−0.949	0.268	0.359	0.207	0.690	0.451	0.535	0.431	0.389	118
21C211	−0.295	−1.038	−0.560	0.504	0.920	0.056	−1.116	0.232	0.284	0.372	0.548	0.560	0.557	0.407	0.382	126
21C214	−1.014	−0.751	−1.991	−0.479	0.612	−1.166	−1.089	0.122	0.324	0.093	0.362	0.519	0.376	0.411	0.280	162
21C216	−0.542	0.981	−0.631	0.427	1.194	−0.589	−0.141	0.194	0.566	0.358	0.533	0.596	0.461	0.548	0.423	77
21C217	0.079	−0.184	−1.801	1.497	1.045	−1.063	0.583	0.290	0.404	0.130	0.736	0.576	0.391	0.652	0.420	86
21C218	−0.617	−0.091	−1.504	0.440	1.639	−1.743	0.182	0.183	0.417	0.188	0.536	0.655	0.290	0.594	0.368	139
21C219	0.761	1.908	−1.790	0.448	1.371	0.895	−0.629	0.394	0.696	0.132	0.537	0.619	0.681	0.477	0.493	23
21C220	−0.069	−0.192	−0.696	0.738	1.855	−1.880	1.036	0.267	0.402	0.345	0.592	0.683	0.269	0.717	0.428	70
21C221	−1.207	0.524	−0.593	0.802	1.815	−1.261	0.612	0.093	0.503	0.365	0.604	0.678	0.361	0.656	0.402	107
21C222	2.012	1.522	−1.012	1.856	2.612	0.031	−0.454	0.585	0.642	0.284	0.804	0.783	0.553	0.503	0.593	2
21C226	−0.593	0.861	0.040	0.444	2.021	−1.113	0.537	0.187	0.550	0.489	0.536	0.705	0.383	0.645	0.448	52
21C228	−0.280	1.188	−0.258	0.678	0.830	−0.588	0.616	0.235	0.595	0.431	0.581	0.548	0.461	0.657	0.459	42
21C229	−0.223	0.225	−0.137	−0.374	0.400	−0.043	0.767	0.243	0.461	0.454	0.381	0.491	0.542	0.678	0.425	74
21C230	0.541	1.709	−0.238	−0.603	0.032	−0.710	−2.945	0.360	0.668	0.435	0.338	0.443	0.443	0.144	0.413	96
21C234	−0.101	1.284	−1.158	−0.669	0.475	−0.178	1.166	0.262	0.609	0.255	0.325	0.501	0.522	0.736	0.430	67
21C236	0.070	−0.738	0.030	−0.942	−0.146	−0.945	1.268	0.288	0.326	0.487	0.274	0.419	0.408	0.750	0.393	113
21C241	1.359	2.410	2.640	−1.419	0.161	−0.650	0.008	0.486	0.766	0.995	0.183	0.460	0.452	0.569	0.562	5
21C242	2.268	2.183	−1.014	−0.741	0.657	0.049	0.676	0.625	0.735	0.283	0.312	0.525	0.556	0.665	0.554	6
21C243	0.111	2.005	−0.571	0.442	0.435	−0.309	0.716	0.294	0.710	0.370	0.536	0.496	0.503	0.671	0.483	30
21C245	0.560	0.791	−0.239	−0.817	0.043	0.488	3.002	0.363	0.540	0.434	0.297	0.444	0.621	1.000	0.498	22
21C247	0.366	1.088	0.391	−0.414	0.087	0.801	0.113	0.333	0.582	0.557	0.374	0.450	0.667	0.584	0.481	33
21C249	0.103	1.222	0.533	−0.311	0.128	−0.028	0.356	0.293	0.600	0.585	0.393	0.455	0.544	0.619	0.469	38
21C250	−0.060	1.044	−0.875	−0.550	−0.023	0.779	1.148	0.268	0.575	0.310	0.348	0.436	0.664	0.733	0.443	57
21C252	1.473	0.360	−0.500	−0.809	0.703	0.325	0.479	0.503	0.480	0.384	0.299	0.531	0.597	0.637	0.490	26
21C280	0.754	0.063	−0.233	0.212	0.958	−0.016	0.962	0.393	0.438	0.436	0.492	0.565	0.546	0.706	0.485	29
21C288	0.924	1.852	0.006	−0.762	0.182	−0.345	1.155	0.419	0.688	0.482	0.308	0.463	0.497	0.734	0.506	17
21C291	1.452	−0.297	−1.180	0.022	0.737	0.281	0.170	0.500	0.388	0.251	0.456	0.536	0.590	0.592	0.471	37
21C293	2.493	1.270	−0.495	0.290	1.064	−0.043	0.424	0.659	0.607	0.385	0.507	0.579	0.542	0.629	0.577	3
21C301	−0.912	1.894	2.346	−1.869	0.874	1.360	0.937	0.138	0.694	0.938	0.098	0.554	0.750	0.703	0.492	25
21C302	−1.410	1.776	0.525	−0.055	1.440	−0.195	0.637	0.061	0.678	0.583	0.442	0.628	0.520	0.660	0.442	58
21C305	0.233	1.849	2.067	−1.049	0.921	0.562	0.700	0.313	0.688	0.884	0.254	0.560	0.632	0.669	0.536	8
21C307	−0.507	4.080	1.368	2.107	−2.553	−2.217	0.665	0.200	1.000	0.748	0.852	0.102	0.219	0.664	0.510	15
21C316	0.105	0.935	−1.045	−0.425	0.259	0.520	−0.050	0.293	0.560	0.277	0.372	0.473	0.626	0.561	0.428	71
21C317	−0.784	1.553	0.074	−0.890	−0.057	−1.609	0.765	0.157	0.647	0.495	0.284	0.431	0.310	0.678	0.394	112
21C323	−0.552	0.245	1.135	−0.036	1.281	0.237	1.238	0.193	0.464	0.702	0.446	0.607	0.584	0.746	0.472	36
21C331	−0.485	0.954	0.953	−0.899	−0.695	0.215	0.548	0.203	0.563	0.667	0.282	0.347	0.580	0.647	0.430	68
21C336	−0.953	0.262	−0.225	−0.603	0.417	−1.202	0.630	0.131	0.466	0.437	0.338	0.494	0.370	0.659	0.367	142

Table 7. Classification of salt tolerance of 165 eggplant germplasms.

Classification of Salt Tolerance	Variety Name	Quantity
Highly salt-tolerant (HST)	24QX9, 21C222, 21C293, 21C186, 21C241, 21C242	6
Salt-tolerant (ST)	21C188, 21C305, 21C37, 21C38, 21C148, 24QX8, 24QX64, 21C95, 21C307, 16-562, 21C288, 21C91, 24QX14, 24QX2, 24QX45, 21C245, 21C219, 24QX15, 21C301, 21C252, 24QX47, 24QX19, 21C280, 21C243, 24QX12, 24QX26, 21C247, 24QX39, 24QX49, 21C323, 21C291, 21C249, 24QX42, 24QX43, 21C32	35
Moderately salt-tolerant (MST)	21C228, 21C175, 24QX52, 24QX11, 24QX13, 21C161, 24QX21, 24QX40, 24QX3, 24QX33, 21C226, 21C68, 24QX18, 21C144, 21C107, 21C250, 21C302, 21C50, 24QX28, 24QX10, 24QX58, 21C126, 21C127, 24QX38, 21C135, 21C234, 21C331, 21C105, 21C220, 21C316, 21C12, 21C35, 21C229, 24QX24, 21C90, 21C216, 24QX59, 24QX16, 21C181, 21C61, 24-477, 21C13, 24QX41, 24QX34, 21C217, 24QX20, 14-345, 21C64, 21C158, 24QX6, 21C185, 24QX51, 21C21, 21C170, 21C230, 21C154, 21C48, 24QX29, 24QX44, 24QX62, 24QX60, 24QX7, 21C19, 24QX5, 21C1, 21C221, 24QX48	67
Salt-sensitive (SS)	24QX55, 21C57, 21C111, 21C317, 21C236, 21C141, 24QX4, 21C155, 24QX27, 21C207, 21C171, 24QX35, 21C34, 21C28, 21C104, 24QX22, 21C6, 21C211, 21C29, 21C26, 24QX37, 21C162, 24QX36, 21C139, 24QX25, 21C46, 24QX30, 21C108, 21C204, 24QX54, 21C218, 21C51, 24QX63, 21C336, 24QX67, 21C147, 24QX68, 21C205, 21C199, 21C164, 21C172, 21C180, HQ1315, 21C41, 21C132, 24QX31, 24-479, 24QX32, 21C9	49
Highly salt-sensitive (HSS)	21C45, 21C198, 21C44, 21C4, 21C214, 21C43, Sanyue, 21C60	8

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MDPI and ACS Style

Fang, Y.; Wang, Z.; Du, Y.; Di, S.; Gao, Z.; Chen, X.; Zhang, W.; Song, L.; Luo, S.; Li, Q. Comprehensive Evaluation and Screening for Salt Tolerance Germplasms at Seedling Stage in Eggplant. Horticulturae 2025, 11, 697. https://doi.org/10.3390/horticulturae11060697

AMA Style

Fang Y, Wang Z, Du Y, Di S, Gao Z, Chen X, Zhang W, Song L, Luo S, Li Q. Comprehensive Evaluation and Screening for Salt Tolerance Germplasms at Seedling Stage in Eggplant. Horticulturae. 2025; 11(6):697. https://doi.org/10.3390/horticulturae11060697

Chicago/Turabian Style

Fang, Yu, Zhiguo Wang, Yingnan Du, Shuaitao Di, Zhenwei Gao, Xueping Chen, Weiwei Zhang, Lijun Song, Shuangxia Luo, and Qiang Li. 2025. "Comprehensive Evaluation and Screening for Salt Tolerance Germplasms at Seedling Stage in Eggplant" Horticulturae 11, no. 6: 697. https://doi.org/10.3390/horticulturae11060697

APA Style

Fang, Y., Wang, Z., Du, Y., Di, S., Gao, Z., Chen, X., Zhang, W., Song, L., Luo, S., & Li, Q. (2025). Comprehensive Evaluation and Screening for Salt Tolerance Germplasms at Seedling Stage in Eggplant. Horticulturae, 11(6), 697. https://doi.org/10.3390/horticulturae11060697

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Comprehensive Evaluation and Screening for Salt Tolerance Germplasms at Seedling Stage in Eggplant

Abstract

1. Introduction

2. Materials and Methods

2.1. Plant Materials

2.2. Determination of Optimal Salt Stress Levels

2.3. Salt Tolerance Screening of Germplasm

2.4. Descriptor Measurements

2.5. Evaluation of Seedling Physiological Indices

2.6. Statistical Analysis

3. Results

3.1. Optimal Salt Concentration for Screening

3.2. Variations in Salt Tolerance Indices

3.3. Correlation Analysis of STI Using Different Indices in Seedlings

3.4. Principal Component Analysis of STI

3.5. Membership Function Evaluation

3.6. Germplasm Classification by Salt Tolerance

3.7. Stepwise Regression Analysis of STIs Using Different Indices

4. Discussion

5. Conclusions

Author Contributions

Funding

Data Availability Statement

Conflicts of Interest

References

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