A Simple Greenhouse Method for Screening Salt ...

Published January 22, 2016

Research

A Simple Greenhouse Method for Screening Salt Tolerance in Soybean Fernando Ledesma, Cindy Lopez, Diana Ortiz, Pengyin Chen,* Kenneth L. Korth, Tetsuaki Ishibashi, Ailan Zeng, Moldir Orazaly, and Liliana Florez-Palacios

ABSTRACT Salinity is an important limiting factor for crop production. Over 800 million ha of land globally are salt-affected. Soybean [Glycine max (L.) Merr.] is moderately salt-tolerant; however, excessive salt reduces yield. Developing a quick, reliable, and inexpensive screening method is critical for soybean breeding programs. This study aimed to develop a rapid method for screening salt tolerance in soybean and to determine the best growing media and NaCl concentrations for screening. Four soybean cultivars, known as Cl – includers (‘Williams’ and ‘Dare’) or excluders (‘S-100’ and ‘Lee 68’), were screened for salt tolerance. These four genotypes were grown in soil, sand, and potting mix and treated with 0, 80, 120, and 160 mM NaCl. Treatment was initiated at the first trifoliate leaf expansion in the second true node above the unifoliate leaves. Two weeks later, leaf scorch score on a 1–9 scale (1 = no chlorosis; 9 = necrosis) was taken. Additionaly, leaf and root Na+ and Cl- concentrations were analyzed. The clearest differences between tolerant and sensitive cultivars were obtained using 120-mM NaCl in soil. Once the best conditions to evaluate salt tolerance were established, 14 cultivars were screened to identify those with the most contrasting response. The most sensitive cultivars were Williams and ‘Clark’; the most tolerant were ‘HBK R5525’ and ‘AG5905’. To validate this method, 97 genotypes were evaluated under these conditions with differential responses. The proposed screening methodology was effective in identifying a range of sensitive and tolerant genotypes, allowing confirmation of salt tolerance in some previously reported genotypes.

F. Ledesma, C. Lopez, D. Ortiz, P. Chen, T. Ishibashi, A. Zeng, M. Orazaly, and L. Florez-Palacios, Dep. of Crop, Soil and Environmental Sciences, 115 Plant Sciences Building, Univ. of Arkansas, Fayetteville, Arkansas 72701; K. Korth, Dep. of Plant Pathology, Plant Sciences Building 217A, Univ. of Arkansas, Fayetteville, Arkansas 72701. F. Ledesma, C. Lopez, and D. Ortiz contributed equally to this work. Received 14 July 2015. Accepted 15 Sept. 2015. *Corresponding author ([email protected]). Abbreviations: LSS, leaf scorch score.

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alinity is an important type of abiotic stress that affects plants, causing significant damage such as a decrease in productivity and quality and whole-plant death (Chinnusamy et al., 2005). Saline soil can be caused by the frequent use of irrigation water with an elevated salt content, improper drainage, rainwater, sea spray, or air pollution. High salinity levels induce osmotic stress, nutrient deficiencies, and ion toxicity in plants (Munns et al., 2002). Saline soils are characterized by the presence and accumulation of Na+ and Cl- ions. Chloride is considered to be an essential micronutrient for plants that is important during the water-splitting reaction of photosynthesis (Marschner, 1995; Clarke and Eaton-Rye, 2000). However, high concentrations of Cl- or Na+ can cause injury and toxcity in plants (Lessani and Marschner, 1978). In soybean, Cl– accumulation has been associated with the presence of chlorosis and necrosis in leaves and stems, in addition to a general loss in productivity (Abel and MacKenzie, 1964; Parker et al., 1983; Wang and Shannon, 1999; Essa, 2002). More than 800 million hectares of land across the world are affected by salt (including both salinity and sodicity), which is equivalent to more than 6% of the global land area (Arzani, 2008) and about 20% of the arable land (Sairam and Tyagi, 2004). According to Blumwald and Grover (2006), the percentage of affected land area could increase drastically in the next years, and it is expected that nearly 50% of cultivated land will be affected by salt by 2050. Published in Crop Sci. 56:1–10 (2016). doi: 10.2135/cropsci2015.07.0429 © Crop Science Society of America | 5585 Guilford Rd., Madison, WI 53711 USA All rights reserved.

crop science, vol. 56, march– april 2016

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Therefore, efforts in plant breeding and genetics will play a fundamental role in crop improvement facing soil salinity. Parida and Das (2005) defined salt tolerance as the ability of plants to grow and complete their life cycle on a substrate with high concentrations of soluble salts. Soybean is a moderately salt-tolerant crop. It has been found that not all soybean genotypes show the same level of salt damage, which suggests the presence of genetic variability in soybean in response to salt stress (Abel and MacKenzie, 1964; Parker et al., 1983; Pantalone et al., 1997; Shannon, 1997; Lee et al., 2004). Therefore, plant breeders could improve salt tolerance by identifying the genetic variability of this trait to develop new cultivars that are adapted to salt stress. Because of the importance of identifying salt-tolerant soybean cultivars, several screening studies have been conducted (Parker et al., 1983; Yang and Blanchar, 1993; Pantalone et al., 1997; Xu et al., 1999; An et al., 2002; Lee et al., 2004, 2008; Valencia et al., 2008). Field screening evaluations of soybean genotypes planted in soils with high salt concentration were unsuccessful because of the variability of salt levels across the soil and the changing environmental conditions. Better results were found with the hydroponics method, in which a NaCl solution was supplied to the plants under greenhouse conditions. The advantage of this method is that the nutrient levels and environmental conditions are controlled (Valencia et al., 2008). However, during the experiment, nutrient solutions need to be constantly changed, which is considered to be expensive and inefficient. Recently, a simpler screening called the plastic cone-tainer method has been tested with good results. In this method, sandy soil was used as a growth medium instead of a nutrient solution (Lee et al., 2008). Even though the plastic cone-tainer method seems to be easy, less laborious, and less time consuming than previously reported methods, it is necessary to test more types of growing media and evaluate different levels of NaCl to develop an efficient method of screening soybean cultivars. Developing a quick, reliable, and inexpensive screening method is critical for soybean breeding programs and genetic studies. The objective of this study was to develop a rapid screening method for salt tolerance in soybean and to evaluate and identify genotypes with the most contrasting responses to salt stress for future genetic study.

(Essa, 2002; Lee et al., 2004; Pantalone et al., 1997). Six seeds of each genotype were planted in plastic pots (90 mm in diameter), which contained three different growing media: sandy loam soil (sandy loam, Kibler fine-loamy, micaceous, mesic Typic Dystrudepts), river sand, or potting mix (Rediearth, Vermiculita and Canadian Sphagnum peat moss, Sun Gro Horticulture Distribution Inc., Bellevue, WA). Subsequently, pots were placed in plastic trays to irrigate soybean plants from the bottom (Fig. 1). Once the seedlings emerged, four healthy and uniform plants were selected and maintained in each pot. At the beginning of V1 stage (expansion of the first trifoliate leaf ), salt treatment was initiated. Salt treatment consisted of four NaCl concentration levels: 0, 80, 120, and 160 mM. A volume of four liters of salt solution from each concentration was added to the plastic trays containing the pots and maintained for 2 h daily for 2 wk. Right after the 2-h treatment each day, the solution was removed from the trays, and no other type of irrigation was applied. Nutritional deficiencies were avoided with the application of water-soluble fertilizer (Miracle-Gro All Purpose Plant Food, The Scotts Miracle-Gro Company, Marysville, OH) once a week after the second trifoliate stage. The same methodology was repeated with 14 soybean genotypes (Table 1) using the best salt treatment identified in the first experiment. The genotypes Clark, Williams, S-100 and Lee 68 were included as checks. To validate the results of this methodology, a third experiment was performed evaluating a wider range of genotypes (Table 2).

MATERIALS AND METHODS

Measurements

Plant Materials and Growth Conditions The experiments were performed in the Rosen Center greenhouse at the University of Arkansas, Fayetteville, AR. Plants were maintained under 14 h light and 26°C/21°C (day and night respectively) throughout the experiment. In the first experiment, four soybean cultivars were screened for salt tolerance: Williams and Dare, known as Cl– – sensitive genotypes (Ping et al., 2002; Velagaleti and Marsh, 1989), and S-100 and Lee 68, known as Cl– –tolerant genotypes 2

Figure 1. View of soybean plants growing in pots filled with sandy soil, immersed in 120 mM saline solution in a plastic tray 10 d after treatment with NaCl.

Fifteen days after the salt treatment, two criteria were used to evaluate and classify tolerant and sensitive genotypes. First, plants were visually rated using a leaf scorch scale (LSS). Leaves were scored from 1 to 9 where 1 = healthy dark green leaves with no chlorosis and 9 = necrotic leaves (Fig. 2). After the evaluation of LSS, leaves and roots of individual plants from each treatment were harvested separately and oven-dried at 70°C for 5 d. Subsequently, the dried tissue was ground and 0.3 g of tissue was analyzed to determine the Cl- and Na+ content. Deionized water (Kalra, 1998) was used to extract Cl-. Acid

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Table 1. Leaf scorch score and Cl – concentration in 14 soybean cultivars 14 d after 120 mM NaCl treatment in soil. Cultivar

Leaf scorch score†

AG4605 Williams Dare AG4903 HBK R4924 Clark Hutcheson Forrest Hartwig LEE 68 AG5905 S-100 AG5605 HBK R5525

8.3 a 8.2 a 8.0 a 8.0 a 8.0 a 7.9 a 6.7 b 6.0 bc 5.7 cd 5.2 cde 5.1 cde 4.9 def 4.3 ef 4.0 f

Mean CV Tukey0.05

6.5 9.4 1.9‡

Symptom Necrosis Necrosis Necrosis Necrosis Necrosis Necrosis Chlorosis Chlorosis Chlorosis Light green Light green Light green Light green Light green

Response

Cl—

Classification

Sensitive Sensitive Sensitive Sensitive Sensitive Sensitive Segregating Segregating Segregating Tolerant Tolerant Tolerant Tolerant Tolerant

mg kg-1 71,370 abcd 97,110 a 79,710 abc 74,630 abcd 74,370 abcd 90,590 ab 53,640 cde 59,880 bcde 55,360 cde 35,600 ef 31,030 ef 45,570 def 34,020 ef 21,120 f

Includer Includer Includer Includer Includer Includer Mixed Mixed Mixed Excluder Excluder Excluder Excluder Excluder

59,778 16.9 31,028§

† Leaf scorch score (LSS): 1 = green or healthy leaves; 9 = necrosis. ‡ Based on Tukey’s honest significant difference = 1.9, LSS ³6.4 are includers; LSS £5.9 are excluders. § Based on Tukey’s HSD = 31,028 Cl- ³66,082 are includers; Cl- £52,148 are excluders. All others are mixed.

Figure 2. Leaf scorch score (LSS) system for evaluating soybean for salt tolerance (1 = no chlorosis; 9 = necrosis). Score 1 shows a completely healty green leaf from a soybean plant not subjected to salt stress, whereas Score 2 shows a stunted dark-green leaf typically found in tolerant cultivars under salt stress. Score 3 shows a leaf with slight chlorosis and Score 9 with severe necrosis. crop science, vol. 56, march– april 2016

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Table 2. Leaf scorch score (LSS), Cl – concentration in leaves, and percentage of dead plants for 98 genotypes after 14 d of 120 mM NaCl treatment in the greenhouse. Genotype

LSS†

Cl-

Dead plants Classification

R09–1237 Dare UARK-5798 Desha R04–1250RR R04–572 R05–1415 R05–4969 R07–7775 Walters R01–2731F Clark R09–1831 R98–209 R06–2082RR

8.2 8.0 7.7 7.5 7.5 7.5 7.5 7.5 7.5 7.5 7.4 7.3 7.3 7.3 7.2

mg kg-1 80,723 81,952 79,332 73,363 71,948 66,599 74,933 73,671 73,394 76,726 65,388 69,945 58,766 68,773 64,105

%‡ 95.3 ± 48 70.4 ± 43.4 58.2 ± 41 46.0 ± 36.2 55.6 ± 39.5 69.8 ± 37.3 38.5 ± 41.5 43.7 ± 45.8 66.7 ± 40.8 50.0 ± 54.7 62.5 ± 46 34.2 ± 39.2 40.6 ± 38.3 50.9 ± 19.6 33.1 ± 38.6

Includer Includer Includer Includer Includer Includer Includer Includer Includer Includer Includer Includer Includer Includer Includer

Narow Ozark R08–2776 R08–4002 R08–47 R01–416F UA 5014C R95–1705 R07–6669 Forrest Glenn Lonoke R05–1772 R09–5088 R09–5225 Caviness AG4907 Hutcheson R06–4475 R08–141 R08–3211 R09–1822 R09–3742 R09–4010 JTN-5503 R01–581F R07–1857

7.1 7.1 7.1 7.1 7.1 7.0 7.0 7.0 6.9 6.8 6.8 6.8 6.8 6.8 6.8 6.7 6.6 6.6 6.6 6.6 6.6 6.6 6.6 6.6 6.5 6.5 6.5

68,573 61,722 68,751 73,253 73,072 61,088 67,010 71,158 64,355 60,416 69,205 59,154 69,081 57,517 85,225 54,671 67,625 70,956 62,582 56,830 61,302 81,275 74,516 77,424 66,028 65,433 67,159

48.6 ± 46.7 47.5 ± 26.7 39.6 ± 37.9 69.6 ± 40.9 38.2 ± 35 31.4 ± 37.5 48.4 ± 41.6 56.7 ± 37.6 35.0 ± 36.3 38.3 ± 26.6 38.4 ± 33.2 32.1 ± 31.4 43.1 ± 46 31.2 ± 30 52.4 ± 44.9 43.5 ± 31.7 27.8 ± 27 38.5 ± 48.1 26.3 ± 30.1 33.7 ± 41.5 37.9 ± 42.5 37.5 ± 44 44.4 ± 50.2 44.4 ± 50.2 35.7 ± 42.1 26.7 ± 43.2 41.7 ± 49.1

Includer Includer Includer Includer Includer Includer Includer Includer Includer Includer Includer Includer Includer Includer Includer Includer Includer Includer Includer Includer Includer Includer Includer Includer Includer Includer Includer

UA 4805 R01–3474F R09–1589 R08–3119 5601T R04–122 R02–6268F UA 5612 R07–2001 R05–374

6.5 6.4 6.4 6.3 6.2 6.2 6.1 6.1 6.0 5.9

66,347 58,912 67,581 67,560 63,841 67,472 64,393 55,475 59,306 57,211

32.7 ± 40.9 26.8 ± 35.1 55.0 ± 34.3 33.2 ± 44.7 8.3 ± 20.4 30.6 ± 40 11.8 ± 22.3 32.2 ± 38.7 9.2 ± 16.6 9.7 ± 15.3

Includer Includer Includer Includer Includer Includer Mixed Mixed Mixed Mixed

Table 2. Continued. Genotype

LSS†

Cl-

R07–5351 R04–342 R09–209 R09–319 AG5606 UA 5414RR R09–4571 R01–327 R07–1826 Lee R09–1827 RM-22590 R01–976 R04–1274RR R08–3206 R07–10322 R08–527 R97–1634 RM-1639 RM-9508 AG5905 AG5605 R06–4433 R08–1178 UARK-5896 R05–1947 R07–190 R07–330 R09–2988 S-100 5002T R09–2567 AG4606 R07–129 R07–167 R02–3065 Jake Osage R05–235 R08–2797 R08–107 R03–1250 R09–430 UA 5213C R07–6654

5.9 5.8 5.8 5.8 5.7 5.7 5.7 5.6 5.6 5.5 5.5 5.4 5.3 5.3 5.3 5.2 5.2 5.1 5.1 5.1 5.0 4.9 4.9 4.9 4.9 4.8 4.8 4.8 4.7 4.7 4.6 4.6 4.5 4.5 4.5 4.4 4.3 4.3 4.3 4.3 4.0 3.8 3.8 3.7 3.5

49,440 59,356 65,714 59,795 61,937 52,706 62,786 62,552 38,893 56,026 53,024 66,416 56,316 56,050 55,740 63,235 58,006 61,894 58,469 45,743 55,147 55,544 61,942 38,081 57,698 49,531 55,973 57,996 56,369 58,279 58,159 59,230 54,612 39,910 51,819 58,189 54,627 40,105 55,106 56,407 45,388 51,787 47,521 52,170 42,152

Mean CV Tukey0.05

5.97 13.18 1.96

61,559.6 11.3 30,598.4

Dead plants Classification 16.7 ± 40.8 27.5 ± 32.5 30.0 ± 47 37.9 ± 33.9 20.0 ± 40 10.0 ± 24.5 27.1 ± 31.8 20.7 ± 27.3 13.1 ± 21.4 8.3 ± 13.9 10.7 ± 20 13.9 ± 22.1 20.5 ± 32.7 4.2 ± 10.2 8.3 ± 20.4 2.4 ± 5.8 26.4 ± 38.9 21.9 ± 34.1 0±0 5.6 ± 13.6 0±0 3.7 ± 14.9 16.1 ± 32 27.5 ± 39.2 0±0 9.7 ± 15.3 13.9 ± 26.7 16.8 ± 22.3 5.6 ± 13.6 0±0 0±0 9.8 ± 15 5.6 ± 13.6 14.3 ± 35 7.5 ± 11.7 9.7 ± 15.3 8.3 ± 20.4 16.7 ± 40.8 2.4 ± 5.8 3.3 ± 8.2 12.5 ± 30.6 0±0 0±0 0±0 0±0

Mixed Mixed Mixed Mixed Mixed Mixed Mixed Mixed Mixed Excluder Excluder Excluder Excluder Excluder Excluder Excluder Excluder Excluder Excluder Excluder Excluder Excluder Excluder Excluder Excluder Excluder Excluder Excluder Excluder Excluder Excluder Excluder Excluder Excluder Excluder Excluder Excluder Excluder Excluder Excluder Excluder Excluder Excluder Excluder Excluder

27 75.2 71.6

† Leaf scorch score: 1 = Green or healthy leaves; 9 = necrosis; based on Tukey’s honest significant difference = 1.96. LSS ³6.2 are includers and LSS £5.5 are excluders. All others are mixed. ‡ Percentage of dead plants ± SD. Genotypes with a percentage close to 50% and low SD: probable phenotypic segregation for the salt tolerance trait.

Cont’d.

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digestion with nitric acid and hydrogen peroxide was used to extract Na+ (Plank, 1992). The extracts were analyzed using a spectrophotometer (Model CIROS ICP, Spectro Analytical Instruments Inc., Mahwah, NJ).

Experimental Design and Data Analysis In the first experiment, the experimental design used was a splitsplit-plot with four levels of NaCl salt solution as main plot, three growing media as subplots, and four different genotypes with five replications as sub-subplots. The second experiment was a splitplot design with two levels of salt concentration and 14 genotypes with five replications. In the split-plot design, the salt treatment was considered as the main plot, and the 14 genotypes were subplots. ANOVA was used to evaluate the LSS and ion (Na+, Cl-) content. Significant differences among different treatments were calculated using the Tukey test (P < 0.05). A correlation test was performed to evaluate the relationship among variables. All statistical analyses were performed using SAS version 9.2 (SAS Institute Inc., 2010).

Validation of the Screening Methology After the evaluation of 14 cultivars in the greenhouse, additional genotypes were selected to confirm the results previously obtained with the screening method and to validate the method with random genotypes ( Table 2). The genotypes S-100 (excluder), Clark and Dare (includers) were used as checks. In addition, AG5605 and AG5905 were added as excluders, representing the lines that had the lowest LSS and Cl– accumulation values in the previous experiment. A split-plot design with six replications was performed using two levels of NaCl- solution (0 and 120 mM) as the main plot and the genotypes as subplots. As described above, LSS and Cl– content in leaves were measured. Additionally, the percentage of dead plants was evaluated to have another parameter to determine if there was segregation in the salt stress response within each genotype. The appearance and progression of symptoms were monitored and recorded throughout the 2 wk at 3-day intervals after the first day of the salt treatment application.

RESULTS AND DISCUSSION Leaf Scorch Score After 2 wk of salt treatment, the four varieties evaluated presented slower growth compared to the control; however, foliar symptoms of chlorosis and necrosis were observed only in sensitive varieties (Dare and Williams). Statistical differences in LSS were detected across all growing media and NaCl concentrations (Tables 3 and 4). The symptoms caused by salt damage were more severe with increased salt concentration. However, the 160 mM NaCl treatment affected both sensitive and tolerant cultivars, which did not allow a clear separation between genotypes in any growing media used in the experiments (Tables 3 and 4). Similar results have been previously observed using the hydroponic screening method (Valencia et al., 2008). The damage observed in the sensitive crop science, vol. 56, march– april 2016

cultivars treated with 80 mM NaCl was not enough to separate them easily from the tolerant ones. The clearest visual differences using LSS scale was found at 120 mM NaCl treatment with either river sand or sandy soil media (Tables 3 and 4). Previous research also reported comparable symptoms in sensitive cultivars under salt treatments (Abel and MacKenzie, 1964; Parker et al., 1983; Yang and Blanchar, 1993; Lee et al., 2004; Kao et al., 2006; Valencia et al., 2008). Tolerant cultivars (S-100 and Lee 68) displayed slight chlorosis and smaller leaf size compared to the control (0 NaCl level); however, overall they appeared to be healthier than sensitive cultivars. The stunting observed in tolerant and sensitive plants has been associated with shorter height, thinner shoot, smaller leaves, and fewer nodes (Essa, 2002; Hamayun et al., 2010). Significant differences in LSS between tolerant and sensitive cultivars were detected with sand, soil, and commercial potting mix (Tables 3 and 4). Plants growing in river sand and sandy soil showed similar visual damage in the leaves at the end of treatments; sensitive and tolerant varieties were also clearly differentiated. Nevertheless, initial chlorosis and necrosis symptoms appeared 2 d earlier in sensitive cultivars growing in river sand. The commercial mix was not an appropriate substrate for this screening method because visual symptoms of salt injury were observed later compared to other growing media. In addition, in some cases, sensitive genotypes growing in the commercial mix did not show foliar damage such as as necrosis or even chlorosis at the end of the treatments compared to the same genotypes growing in other substrates.

Accumulation of Na+ in Leaves and Roots Sodium accumulation in leaves was generally greater in sensitive genotypes than in tolerant ones. The opposite results were found in roots, where Na+ accumulation was greater in tolerant genotypes (Tables 3 and 4). These results agree with other studies, where tolerant soybean cultivars were able to keep the Na+ in the roots as a strategy to avoid the uptake of this ion by the stem and leaves, thereby preventing toxic injury in the plant (Phang et al., 2008). Clearer differences were found in Na+ accumulation in roots and leaves during the experiment performed in summer season (Table 4). This observation agreed with the hypothesis that plants exposed to high temperatures have greater transpiration and take more water in; as a consequence, a larger ion accumulation was observed (Yang and Blanchar, 1993; Essa, 2002; Pathan et al., 2007).

Accumulation of Cl- in Leaves and Roots

Significant differences in Cl- concentration between salttolerant and sensitive cultivars were found in leaves and roots even when no salt solution was applied. The clearest statistical differences were observed in Cl- concentrations

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Table 3. Average leaf scorch score (LSS), Na+ and Cl – content in leaves and roots of four soybean cultivars at different levels of NaCl treatment in three growing media evaluated in a greenhouse during the spring season. Growing medium

Leaf Na+

LSS NaCl

Tol†

Sens‡

Tol

Leaf Cl –

Sens

Tol

Sens

Root Na+ Tol

Sens

Root Cl – Tol

Sens

——————————————————————————— mg kg-1 ——————————————————————————— 25 a 39 a 2,317 b 5,466 a 1,309 a 1,258 a 13,508 a 12,588 a 20 b 53 a 2,797 b 6,021 a 3,602 a 3,465 a 10,324 a 8,439 b 22 b 39 a 2,402 b 7,862 a 2,657 a 2,471 a 13,166 a 9,680 b

Commercial mix River sand Sandy soil

0 mM

1.2 a§ 1.4 a 1.5 a

1.2 a 1.4 a 1.5 a


80 mM

3.2 b 2.9 b 3.0 b

4.7 a 7.6 a 6.6 a

19,086 a 33,771 a 20,085 b

22,714 a 30,676 a 25,869 a

48,084 b 76,205 b 50,870 b

67,500 a 82,350 a 75,985 a

18,967 a 27,446 a 25,887 a

18,503 a 22,638 a 22,070 a

23,405 a 29,285 a 38,742 a

22,104 a 35,415 a 23,190 b


120 mM

3.7 b 3.9 b 3.7 b

7.6 a 8.1 a 8.0 a

36,688 a 40,576 a 29,219 b

39,826 a 38,689 a 38,451 a

82,370 b 80,310 b 70,630 b

99,180 a 93,580 a 95,660 a

19,119 a 23,850 a 28,166 a

17,264 a 21,448 a 28,052 a

27,805 a 32,658 a 37,626 a

28,968 a 27,765 b 42,300 a


160 mM

5.2 b 6.6 b 6.5 b

7.5 a 8.8 a 8.9 a

32,727 a 45,743 a 43,336 b

36,685 a 56,804 b 55,625 a

72,585 b 96,600 b 87,880 b

99,030 a 101,125 a 106,055 a

25,621 a 23,909 a 23,046 a

20,586 b 22,957 a 28,262 a

39,810 a 33,150 a 44,618 a

47,766 a 31,253 a 34,583 a

† Tol, tolerant cultivars: Williams and Dare. ‡ Sens, sensitive cultivars: S-100 and Lee 68. § Values followed by different letters are significantly different at the 0.05 probability level.

Table 4. Average leaf scorch score (LSS), Na+ and Cl – content in leaves and roots of four soybean cultivars at different levels of NaCl treatment in three growing media evaluated in a greenhouse during the summer season. Growing Medium

Leaf Na+

LSS NaCl

Tol†

Sens‡

Tol

Leaf Cl –

Sens

Tol

Sens

Root Na+ Tol

Sens

Root Cl – Tol

Sens

——————————————————————————— mg kg-1 ——————————————————————————— 15 a 16 a 267 b 1,759 a 1,049 a 966 a 7,342 a 6,754 a 20 a 24 a 1,004 b 2,827 a 7,983 a 8,075 a 8,522 a 4,870 b 34 a 57 a 1,304 b 6,377 a 8,132 a 6,942 a 13,140 a 7,873 b


0 mM

1.2 a§ 1.3 a 1.6 a

1.2 a 1.3 a 1.6 a


80 mM

2.5 b 2.9 b 2.6 b

6.0 a 8.2 a 7.8 a

4,565 b 27,597 b 22,280 a

9,092 a 36,897 a 27,093 a

11,636 b 51,680 b 35,705 b

32,755 a 78,620 a 65,160 a

20,834 a 32,207 a 27,878 a

18,349 b 27,084 b 24,098 b

28,550 a 36,915 a 42,150 a

25,690 a 33,560 a 41,730 a


120 mM

3.7 b 4.0 b 3.8 b

6.9 a 8.7 a 8.5 a

17,237 b 35,693 b 35,212 b

28,232 a 40,194 a 40,492 a

40,655 b 61,910 a 68,140 b

78,460 a 69,370 a 96,645 a

26,066 a 28,983 a 28,551 a

21,154 b 23,979 b 24,095 b

32,140 a 34,630 a 48,255 a

29,905 a 30,410 a 37,885 b


160 mM

5.0 b 6.9 b 6.5 b

7.1 a 8.9 a 8.9 a

28,758 a 41,613 b 45,733 b

29,234 a 49,927 a 55,691 a

49,685 b 60,770 b 73,690 b

66,815 a 86,520 a 88,810 a

25,697 a 32,306 a 29,830 a

25,443 a 22,948 b 29,686 a

33,225 a 46,055 a 48,156 a

30,260 a 34,350 b 43,755 a

† Tol, tolteran cultivars: Williams and Dare. ‡ Sens, sensitive cultivars: S-100 and Lee 68. § Values followed by different letters are significantly different at the 0.05 probability level.

in leaves. Leaf Cl- content allowed a clearer separation between salt-tolerant and sensitive cultivars compared to the Na+ content in leaves and roots and the Cl- concentration in roots. Moreover, Cl- content in roots was similar in tolerant and sensitive cultivars; hence, root Cl– is not recommended as a good indicator for evaluating salt tolerance response in soybean. The high content of Cl– observed in sensitive genotypes (Tables 3 and 4) is in agreement with previous reports in which salt-sensitive genotypes or includers showed higher translocation of Cl- from soil to leaves compared to tolerant genotypes or excluders (Wieneke and Läuchli, 1979; Yang and Blanchar, 1993; Lee et al., 2008; Lenis, 2008; Valencia et al., 2008).

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Correlation between LSS and Ion Contents The results obtained with LSS evaluation were strongly and positively correlated with the ion contents in leaves and roots (Table 5). These results confirmed the accuracy of LSS in the identification of salt-sensitive and tolerant genotypes. The lowest correlation values were obtained between LSS and ion contents (Cl- and Na+) in roots (Table 5). In addition, the content of ions in roots was not statistically different in most of the treatments (growing media and NaCl concentration), indicating that ion content in roots did not produce consistent results and therefore is not an accurate parameter for evaluating the plant response to salinity and to classify cultivars. The strongest correlation (r = 0.87–0.88, P £ 0.001) was found between LSS and Cl- content in leaves. However, the

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opposite results were found by Lenis et al. (2011), where the increase in LSS was correlated with an increase in Na+ content rather than Cl-. Furthermore, the clearest statistical differences across all growing media and NaCl concentrations were obtained with Cl- content analysis in leaves. These data suggest that Cl- concentration in leaves provided the best indicator of plant response to salt stress. Similar results have been previously reported where clearer differences were obtained with Cl- analyses in leaves compared to those in stems or roots (Wieneke and Läuchli, 1979; Abel and MacKenzie, 1964; Lee et al., 2008; Lenis et al., 2011). Significant differences were found between tolerant and sensitive genotypes across all growing media and NaCl concentrations using LSS and Cl- content in leaves. Nevertheless, the clearest statistical differences in visual LSS evaluation and leaf Cl- content were obtained with 120 mM NaCl using either sandy soil or river sand growing media (Table 3). Lee et al. (2008) reported similar results and stated that leaf Cl- content is a good indicator of soybean response to salt and recommended a 100-mM NaCl level as the best treatment to find clear differences among cultivars using LSS or ion analysis. In a similar way, using the hydroponics method, Valencia et al. (2008) reported satisfactory results in the separation between salt-tolerant and sensitive soybean genotypes under a salt treatment of 120 mM and suggested Cl- content as a possible selection criterion to identify Cl- excluders and includers.

Screening of Soybean Cultivars Fourteen soybean cultivars were evaluated for salt response using the methodology previously described. The best results found in the first experiment were used to separate salt-sensitive lines from tolerant lines. A good classification was obtained with both sandy soil and river sand growing media at a 120-mM NaCl concentration. For the second validation experiment, a 120-mM NaCl concentration was used and sandy soil was selected as growing media, since plants growing in river sand are more susceptible to nutritional deficiencies, which could be misinterpreted as salt stress (Fig. 1). In addition, soil is a medium that closely simulates the real conditions where soybean plants are grown. As a selection criterion, the LSS scale and the leaf Cl- content were used. With this methodology, we were able to classify 14 different genotypes into three groups as tolerant, sensitive, or mixed (Table 1). The inital visual differences between tolerant and sensitive plants were observed 10 d after the treatment initiation (Fig. 3). Significant statistical differences in the LSS score and the leaf Cl- content were obtained 15 d after initiation of the salt treatment (Table 1). The most salt-sensitive cultivars were Williams, Clark, and Dare, since these genotypes had the highest LSS scores and the greatest Cl- accumulation (Table 1). crop science, vol. 56, march– april 2016

Table 5. Correlation coefficients (r) among leaf scorch score (LSS), Na+ and Cl– content across NaCl treatments and media. LSS‡ –

LSS†

Leaf Na+ Root Na+ Leaf Cl – 0.84***

0.72***

0.88***

0.63***

0.82***

0.93***

0.78***

0.81***

0.92***

+

0.82***

Root Na+

0.75***

0.83***

Leaf Cl –

0.87***

0.96***

0.88***

Root Cl –

0.73***

0.77***

0.88***

Leaf Na

–

Root Cl –

–

– 0.80***

0.74*** –

*** Significant at the 0.001 probability level. † Left bottom data from Experiment 1 (Spring). ‡ Right top data from Experiment 2 (Summer).

Similar results were found with AG4903, HBK R4924, and AG4605. These results agree with the classification of these cultivars reported previously (Lee et al., 2008; Valencia et al., 2008). Moreover, HBK R5525, AG5905, and AG5605 were the cultivars with the lowest Cl- accumulation and LSS scores, followed by Lee 68 and S-100 as excluders. The results obtained in the third experiment, which was implemented to validate this methodology, confirmed the significant differences between salt and non-salt treatment in all the variables measured (P ≤ 0.03). Stunting was observed in both excluders and includers under salt stress. The first symptom (light chlorosis) was observed 10 d after the initiation of the salt treatment; however, symptoms appeared earlier (7 d after treatment) in some susceptible genotypes: Clark, Dare, R98–209, Desha, R05–4969, R04–1250RR, UARK–5798, and Narow. The use of both LSS and Cl- content demonstrated clear and consistent results for the soybean genotypes classification after the screening process. The leaf Cl– concentration and the LSS for the most sensitive lines were about 2.3 times higher than the values obtained in the most tolerant lines (Table 2, Fig. 4). Chloride accumulation and mobility are affected by environmental conditions such as temperature. Some of the other aspects that largely determine Cl– intake include water flow, the nutritional status of the plant, and the ionic composition of the assay medium (White and Broadley, 2001). This may cause variability in the Cl– content measured on the genotypes, not only between tolerant and sensitive cultivars (given the difference in the inherent capacity of the root to restrict Cl- transport) but also among genotypes that have similar tolerance levels. However, Cl- concentration is a very useful parameter of classification and works very well as it is correlated with visual LSS evaluations to classify the cultivars. The percentage of dead plants did not offer a clear differentiation between includers and excluders, but showed potential genetic segregation. Some of the lines where data with a low SD showed about 50% of dead plants, suggesting a possible phenotypic segregation for salt stress and therefore classified as mixed (Table 2, Fig. 5). In contrast, the percentage of dead plants was close to 100% in some

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Figure 3. Chlorosis and necrosis symptoms in soybean 10 d after salt treatment. Plants (a) and (b) correspond to the includers reported in current and previous works, respectively. Plants (c) and (d) refer to the excluders reported in the current and previous works, respectively.

includers and 0% in some excluders, as expected. The segregation lines were expected as they were not selected by breeders for salt tolerance before. Genotypes Clark and Dare were confirmed to be includers, with a high LSS and high Cl– content. On the other hand, AG5605 and AG5905 consistently showed lower Cl– accumulation compared to S–100 (Fig. 6). Cultivars such as Osage and Jake showed lower LSS and

Cl- content than the excluders mentioned above, followed by the genotypes R07–6654, UA 5213C, R09–430, and R03–1250, which had the lowest values in the screening (Table 2). Osage and Jake were previously reported to be as tolerant cultivars (Huang, 2013). Similarly, Lee is a well-known salt-tolerant cultivar in which Cl– exclusion is reported to be controlled by a dominant gene, coming from its ancestor, S-100 (Abel, 1969; Lee et al., 2004) These results indicate that this screening methodology is an effective way to identify salt-tolerant and sensitive genotypes; furthermore, new sources of tolerant soybean cultivars could be used for breeding purposes. In addition, these results suggest that screening the available soybean germplasm may potentially find other sources of resistance to salinity. More studies are necessary to confirm the three classes of genotypes identified and to investigate the genetics of salt tolerance. Identifying the genetic variability of the salt stress response should be a main goal for breeders. The current research is a useful source of information and an important step that contributes to future plant breeding programs studying the salt response in soybean.

CONCLUSIONS In this work, we developed a simple, fast, and costeffective methodology to screen a large number of soybean genotypes for salt tolerance. Using this greenhouse method, we identified differences among soybean cultivars

Figure 4. Symptoms of stress observed 14 d after salt treatment. Excluders: S–100 (a) and UARK-5896 (c). Mixed: AG5606 (b). Includers: R05–4969 (d), R04–572 (e), and R09–1237 (f).

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Figure 5. Soybean plants classified as tolerant: Jake (a), moderately tolerant: R09–319 (b), and sensitive: R09–1589 (segregating) (c) and R04–572 (d).

in response to salt stress. The LSS and Cl- accumulation results were correlated and represented a good indicator to evaluate soybean response to salt stress. These parameters were useful for classifying soybean cultivars as includers or excluders. The average LSS observed was 4.7 and 7.0 for excluders and includers, respectively. The average Cl– content in leaves for excluders was 54,018 mg kg–1 and 68,473 mg kg–1 for includers. Most tolerant genotypes showed up to 2.3-fold more Cl– accumulation and LSS than the most susceptible genotypes. Based on the results of this screening method, new tolerant lines can be used as checks for future studies in salt stress or as parents for breeding for salt tolerance, given the low Cl– accumulation level, and LSS in leaves observed in some genotypes compared to the traditional tolerant checks (S-100, Lee, and Lee 68). These lines include R07–6654, UA 5213C, R09–430, R03–1250, HBK R5525, and AG5905. The variety UA 5213C is a high-yielding conventional cultivar released by the University of Arkansas in 2013 (Chen et al., 2014). Similarly, other susceptible lines such as R09–1237 and UARK-5798 displayed similar symptoms compared to the checks (Dare) and can be used as alternative sources to measure salt inclusion. The proposed method and the results obtained in this study constitute a useful guideline to perform future genetic research and practical breeding for salt tolerance. The methodology used was much easier than other time-consuming and expensive methodologies previously proposed, including the hydroponics method. The 2-h daily treatment was enough to observe symptoms in a short period of time using a LSS and Cl– content as accurate parameters for response to the stress. By using this greenhouse method, it was possible to observe clear differences among cultivars even 7 d after the initiation of the salt treatment, which allowed faster and easier classification.


Figure 6. Soybean plants used as checks after salt treatment. Includers: Clark (a) and Dare (b). Excluders: AG5605 (c) and S–100 (d).

Acknowledgments This work was supported by United Soybean Board and Arkansas Soybean Promotion Board. The authors express their gratitude to John Guerber and to the plant breeding soybean team for their collaboration and support.

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