Silicon improves seed germination and alleviates drought stress in lentil crops by regulating osmolytes, hydrolytic enzymes and antioxidant defense system

Accepted Manuscript Silicon improves seed germination and alleviates drought stress in lentil crops by regulating osmolytes, hydrolytic enzymes and antioxidant defense system Sajitha Biju, Sigfredo Fuentes, Dorin Gupta PII:

S0981-9428(17)30292-9

DOI:

10.1016/j.plaphy.2017.09.001

Reference:

PLAPHY 4985

To appear in:

Plant Physiology and Biochemistry

Received Date: 10 July 2017 Revised Date:

30 August 2017

Accepted Date: 2 September 2017

Please cite this article as: S. Biju, S. Fuentes, D. Gupta, Silicon improves seed germination and alleviates drought stress in lentil crops by regulating osmolytes, hydrolytic enzymes and antioxidant defense system, Plant Physiology et Biochemistry (2017), doi: 10.1016/j.plaphy.2017.09.001. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Silicon improves seed germination and alleviates drought stress in lentil crops by regulating osmolytes, hydrolytic enzymes and antioxidant defense system

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Sajitha Biju1, Sigfredo Fuentes1, Dorin Gupta1* 1 School of Agriculture and Food, Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Australia *[email protected] Abstract Silicon (Si) has been widely reported to have beneficial effect on mitigating drought stress in plants. However, the effect of Si on seed germination under drought conditions is still poorly understood. This research was carried out to ascertain the role of Si to abate polyethylene glycol-6000 mediated drought stress on seed germination and seedling growth of lentil. Results showed that drought stress significantly decreased the seed germination traits and increased the concentration of osmolytes (proline, glycine betaine and soluble sugars), reactive oxygen species (hydrogen peroxide and superoxide anion) and lipid peroxides in lentil seedlings. The activities of hydrolytic enzymes and antioxidant enzymes increased significantly under osmotic stress. The application of Si significantly enhanced the plants ability to withstand drought stress conditions through increased Si content, improved antioxidants, hydrolytic enzymes activity, decreased concentration of osmolytes and reactive oxygen species. Multivariate data analysis showed statistically significant correlations among the drought-tolerance traits, whereas cluster analysis categorised the genotypes into distinct groups based on their drought-tolerance levels and improvements in expression of traits due to Si application. Thus, these results showed that Si supplementation of lentil was effective in alleviating the detrimental effects of drought stress on seed germination and increased seedling vigour. Keywords: silicon; lentil; drought stress; proline; superoxide anion; hydrogen peroxide. 1. Introduction Lentil (Lens culinaris Medik.) is the most ancient cultivated crop among legumes and an important source of protein, minerals and vitamins for the human diet (Yadav et al. 2007). Lentil is classified as a silicon (Si) excluder and is moderately tolerant to drought stress. Even though lentil is a moderately drought-tolerant crop and can grow in reduced water supply, plant productivity can decrease from 6-54 % under a range of drought stress conditions (Siddique et al. 1999). Severe water stress can lead to total crop failure, especially in semiarid regions, where they are commonly exposed to intermittent or terminal drought stress conditions. Lentil is highly sensitive to drought stress at key growth stages, such as seedling, flowering and grain filling (Shrestha et al. 2006). With the forecast of increased water scarcity in near future, drought stress will remain a major threat to global lentil production. Breeding for drought-tolerance remains challenging due to the variation in climatic conditions and multigenic origin of the adaptive responses of lentil plants to drought stress

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ACCEPTED MANUSCRIPT (Kumar et al. 2016; Idrissi et al. 2016). Therefore, another more sustainable approach is the use of exogenous compounds, which are easily available and cost effective to incorporate into agronomical practices with negligible detrimental effects to the environment.

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Silicon (Si) is the second most ubiquitous element in the earth’s crust which has been shown to be effective in improving drought-tolerance in some Si-accumulating monocot plants such as rice (Chen et al. 2011), sorghum (Hattori et al. 2007), maize (Sayed and Gadallah, 2014) and wheat (Pei et al. 2010). It has also been shown to be effective in a few dicot plants such as sunflower (Gunes et al. 2008), cucumber (Ma et al. 2004), soybean (Shen et al. 2010), tomato (Shi et al. 2016) and chickpea (Kurdali et al. 2013). Priming of seeds with silicon (Si) has been considered as one of the alternative methods to improve the drought stress tolerance in plants (Hameed et al. 2013; Ahmed et al. 2016). Si-seed priming may fortify plants against future stress events and appears to be a promising and costeffective procedure. Under drought stress conditions, Si is thought to act as a mechanicalbarrier to minimize transpiration losses and also mediates many metabolic, physiological and biochemical pathways which subsequently improve drought-tolerance. A number of possible mechanisms were proposed through which Si may increase drought-tolerance in plants, especially improving the water status of plants, increased photosynthetic activity and ultrastructure of leaf organelles (Coskun et al. 2016). However, as mentioned before, most of the studies are carried out in monocots which tend to be high Si accumulators and only little research has been conducted in dicot plants, which usually have low capability of Si accumulation. Thus, studying the role of Si in low Si-accumulating legumes (Meena et al. 2014) such as lentil would help to unravel the actual mechanism and function of Si-mediated drought-tolerance in plants and the ability of lentil crops to cope with drought stress conditions with a minimum impact on critical growth stages. Germination and seedling development are very important stages that determine the successful early establishment of a plant in its growing environment. Water plays a key role in germinating seeds through hydrolytic breakdown of food reserves, solubilisation and the transport of metabolites, osmotic adjustment and enzymatic reactions. However, water scarcity seriously hampers successful seedling establishment (Shi et al. 2016). Hydrolytic enzymes like α-amylase, β-amylase and α-glucosidase play a pivotal role during seed germination by hydrolysing starch into sugar. The activity of these enzymes is suppressed by drought stress with negative impacts on the carbohydrate metabolism. Accumulation of the osmolytes (proline, glycine betaine-GB and soluble sugar) under drought stress in many plants has been positively correlated with water stress tolerance and these compounds are thought to play adaptive roles in mediating osmotic adjustment and protecting subcellular structures in stressed plants (Ashraf & Foolad, 2007; Singh et al. 2015; Blum et al. 2017). Similarly, it is well known that the abiotic stresses including drought stress can cause oxidative damage to plants either directly or indirectly through the formation of reactive oxygen species (ROS), such as superoxide anion- O2 − and hydrogen peroxide- H2O2 (McCord, 2000; Das & Choudhary, 2016). Plants respond to this oxidative stress by increasing the production of antioxidant enzymes such as ascorbate peroxidase (APX: EC.1.11.1.11), catalase (CAT, EC 1.11.1.6) and superoxide dismutase (SOD, EC 1.15.1.1), which can scavenge ROS and in turn protect the plants from the oxidative damage (Noctor et

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al. 2014; Das & Roychoudhary, 2016). Since their activities and transcripts are altered when plants are subjected to stress conditions, changes in the levels of antioxidant enzymes and ROS have been used to assess the effect of drought stress in plants (Anjum et al. 2011; Hasanuzzaman et al. 2013). Enhanced germination of seeds by Si application has been shown in different monocots and dicots under controlled conditions (Torabi et al. 2012). Relatively few studies have investigated the effect of Si on seed germination rate and seedling growth under drought stress in plants such as wheat and tomato (Hameed et al. 2013; Shi et al. 2014). However, the effect of Si on the concentrations of osmolytes activity of hydrolytic enzymes, activity of antioxidant enzymes, the concentration ROS and the level of lipid peroxides (LPX) under drought stress has not been investigated so far in seed germination studies of crop plants. Moreover, to the best of our knowledge, no studies have been undertaken until this date to elucidate the role of Si in drought stressed lentil plants. Therefore, given the potential of Si for drought-tolerance (Liang et al. 2003; Coskun et al. 2016) and lentil being one of the most nutritious plants of the future, specifically the objectives of the present study were (1) to elucidate the role of Si in stimulating seed germination by evaluating the metabolism of osmolytes, antioxidants and the activity of hydrolytic enzymes under controlled and drought stress conditions and (2) to recommend Si as a source to improve drought stress tolerance in lentil crop. 2. Materials and Methods 2.1. Plant materials, germination conditions and experimental design Seeds from seven lentil genotypes i) ILL 6002 and ii) Indianhead (drought-tolerant); iii) Flash, iv) PBA Jumbo 2 and v) Nipper (moderately drought-tolerant); vi) PI 468898 and vii) ILL 1796 (drought-sensitive) were procured from The Australian Grains Genebank (AGG), Horsham, Victoria (Table 1). Among the genotypes, PBA Jumbo 2 is the newly released and the highest yielding lentil variety in Australia, outperforming all other current varieties in medium-rainfall lentil growing regions (www.pbseeds.com.au). Furthermore, ILL 6002 is a potential drought-tolerant genotype with a well-developed root system and high early biomass, which has been widely used in many breeding programs (Sarker et al. 2005; Kumar et al. 2016) and also for drought-related QTL mapping (Idrissi et al. 2016). The rest of the genotypes used in this study were selected and categorized based on a drought-tolerance screening study of 37 lentil genotypes using infrared thermal imaging, growth and productivity traits analysed using multivariate data analysis (under publication).

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Genotypes and colour code ILL 6002 Indianhead PBA Jumbo 2 Nipper Flash PI 468898 ILL 1796

Drought-tolerance

Abbreviations

Tolerant Tolerant Moderately tolerant Moderately tolerant Moderately tolerant Drought-sensitive Drought-sensitive

G1 G2 G3 G4 G5 G6 G7

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The seeds were selected by size homogeneity and were surface-sterilized for 20 minutes in 30 % (v/v) hydrogen peroxide (H2O2), rinsed and soaked in distilled water for 1 h. For each of the seven genotypes, five replicates of ten seeds were placed on a filter paper in 9 cm diameter petri dishes containing 3 cm3 of distilled water (control-C), 18 % of polyethylene glycol-6000 (PEG, MW 6000) concentration corresponding to final osmotic potentials of −0.58 MPa (Muscolo et al. 2014) (drought stress-D), 18 % PEG with 2 mM Si (drought stress with supplemented Si-DSi) and Si alone (Si). PEG is most commonly used to induce the osmotic stress in plants. PEG is used to induce the osmotic stress or water-deficit condition because it is not naturally produced in the plant tissue and cannot penetrate into cell from the media. PEG induced stress can eventually destroys the normal emergence, growth, biochemical attributes and yield of wheat (Pei et al., 2010). Preliminary experiment was conducted with 0, 15, 18, and 21% of PEG (MW 6000) concentration corresponding to final osmotic potentials of 0, -0.30, -0.51, -0.58, and -0.80 MPa, respectively (Muscolo et al. 2014) based on the results 18 % PEG concentration was found to induce moderate drought stress in the studied lentil genotypes. The source of Si was sodium metasilicate (Na2SiO3). The silicate supply generally causes medium basicity due to the capability of silicate ions (SiO32−) to protonate. Therefore, Na was replenished with sodium sulfate (Na2SO4) in control to minimize the medium basification as well as sodium effects originating from Na2SiO3 addition. A preliminary experiment using different Si concentrations (0, 0.5, 1.0, 1.5, 2.0, 2.5, 3 mM) showed that 2 mM of Si had the best effect on improving the negative influence of drought stress. Therefore, the experiment was designed with 2 mM of Si. The petri dishes were sealed with parafilm to prevent evaporation and kept accordingly to a completely randomized block design in a growth chamber at a temperature of 25 ± 1 °C in dark conditions with a relative humidity (RH) of 70 %.

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Table 1. Lentil genotypes and their abbreviations used in the different drought-stress treatments such as control (C), drought stress (D), drought stress + Si (DSi) and Si alone (Si).

2.2. Traits used to assess germination Seeds were considered to be germinated when the radicle extended for at least 2 mm. After four days of germination, germination percentage (GP), germination index (GI), and seedling vigour index (SVI) (Yan, 2016) were measured using the following equations:

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GP=n/N *100 Eq. 1 where, n is the number of germinated seeds and N represents the total number of seeds tested. GI=Σ(Gt/Dt)

Eq. 2

where, Gt is the number of seeds germinated at t day and Dt represents the corresponding day of germination. SVI=GP * mean of seedling length

Eq. 3

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The fresh and dry weights of the seedlings were measured before and after oven drying each sample at 80 0C for 48 hrs, respectively (Yan, 2016).

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[(µg proline/ml * X ml toluene)/115.5 µg/µmol]/ [(g sample)/5] = µmol proline/g fresh weight sample Eq. 4

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where, X= ml of toluene used to extract the reaction mixture (4 ml).

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2.4. Determination of glycine betaine (GB) Concentration of GB was estimated from finely ground lentil seedlings (500 mg), which was produced by mechanical shaking with 20 mL deionized water for 24 h at 25 °C. Extracts were filtered and subsequently diluted (1:1) using sulphuric acid (H2SO4) (2 N), with 0.5 mL of extract cooled in an ice bath for 1 h, after which 0.20 mL cold potassium iodide (KI–I2) reagent was added. The resultant solution was stirred and kept for 16 h at 4 °C, then centrifuged at 10,000 rpm for 15 min. Thereafter, the supernatant was carefully aspirated with a fine-tipped glass tube and 1, 2-dichloroethane was added to dissolve the periodide crystals; absorbance was measured at 365 nm using a single beam scanning UV/visible spectrophotometer (M501, Campspec Ltd, Cambridge, UK). The standard reference for GB was used for calculation (Grieve and Grattan, 1983).

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2.3. Determination of proline Free proline levels were determined by using the method proposed by Bates et al. (1973). Finely ground lentil seedlings (0.1 g) was homogenized in 10 mL of 3 % aqueous sulfosalicylic acid (C7H6O6S) and then the homogenate was filtered through Whatman no. 2 filter paper (GE Healthcare, New South Wales, Australia). Two ml filtrate was reacted with 2 ml acid-ninhydrin (C9H6O4) and 2 mL of glacial acetic acid (C2H4O2) in a 10 mL test tube for 1 h at 1000C, and the reaction was terminated in an ice bath. The reaction mixture was extracted with 4 mL toluene (C6H5-CH3), mixed vigorously with a test tube stirrer for 15–20 s. After 1 h, toluene (C6H5-CH3) was added and absorbance at 520 nm was measured by using a single beam scanning UV/visible spectrophotometer (M501, Campspec Ltd, Cambridge, UK). The standard curve for proline was prepared by dissolving proline in 3 % sulfosalicylic acid (C7H6O6S) to cover the concentration range 0.5–10 µg. mL-1. The proline concentration of the extract was determined from the standard curve and calculated on a fresh weight basis as follows:

2.5. Determination of total soluble sugar Total soluble sugar content was determined by the anthrone method (Dubois et al. 1951), a 100 mg sample was homogenized with 5 mL 80 % ethanol (C2H5OH). The extract was centrifuged at 4000 rpm for 15 minutes. The supernatant was separated, with the remaining residue being extracted twice using 5 ml of 80 % ethanol. Supernatant was collected in the same flask and total volume was maintained to 15 mL with 80 % ethanol. The residue was then used for the extraction and estimation of total soluble sugar. An extract volume of 0.1 mL was taken in a 10 mL test tube and oven dried at 60 °C. The final volume was made to 1.0 mL using distilled water. A volume of 5 mL anthrone reagent (0.2 % anthrone in concentrated sulphuric acid (H2SO4) was added. All tubes were placed in a 5

ACCEPTED MANUSCRIPT boiling water bath for 10 minutes and were cooled immediately in cold running water. A blank was prepared in a similar way by taking 1.0 mL distilled water. The absorbance was measured at 620 nm with a single beam scanning UV/visible spectrophotometer (M501, Campspec Ltd, Cambridge, UK). The amount of sugar from the samples was calculated by the standard curve (Dubois et al. 1951) and expressed as mg. g-1 fresh weight.

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2.6. Assay of hydrolytic enzymes The activities of the hydrolytic enzymes, α-amylase (E.C. 3.2.1.1), β-amylase (E.C. 3.2.1.2) and α-glucosidase (E.C. 3.2.1.21) were determined from the crude extracts of each lentil genotype. For this purpose, the seedlings of each genotype were homogenized in a chilled mortar with distilled water 1:4 (w/v) and centrifuged at 14,000 rpm for 30 minutes. The supernatant was filtered through a single layer of muslin cloth and was used for αamylase (Steup, 1988), β-amylase (Steup, 1988), and α-glucosidase (Bergmeyer et al. 1983) activity determination. For α -amylase, a mixture of 3 mL soluble starch (2 % v/v) and 3 mL extract was incubated for 60 minutes at 30 0C. After incubation, an equal volume of alkaline colour reagent was added to a 1 mL incubation mixture, was mixed and heated for five minutes in a boiling water bath. The absorbance at 546 nm was measured against a blank (1 mL distilled water + 1 mL alkaline reagent) using a single beam scanning UV/visible spectrophotometer. The standard curve was obtained by measuring the absorbance from the spectrophotometer of different known maltose concentrations in the range of 0-2.5 mM. L-1. The alkaline colour reagent was prepared by dissolving 1 g of 3, 5-dinitrosalycylic acid (C7H4N2O7) in a mixture of 40 mL 1 N sodium hydroxide (NaOH) solution and 30 mL of distilled water. Twelve grams of solid potassium sodium tartrate (KNaC4H4O6.4H2O) was added and dissolved. The mixture was brought to a final volume of 100 mL using distilled water. β-amylase activity was determined as described above but soluble starch was replaced by amylopectin. For α-glucosidase detection, the assay buffer was prepared by using 50 mM sodium acetate (C2H3NaO2) and 10 mM calcium chloride (CaCl2) and the final pH was adjusted to 5.2. The substrate was 10 mM. L-1 maltose. The samples were incubated for 60 minutes. The release of glucose was measured by changes in nicotinamide adenine dinucleotide phosphate (NADPH) at 340 nm absorption using the single beam scanning UV/visible spectrophotometer (M501, Campspec Ltd, Cambridge, UK) in a coupled enzyme reaction of hexokinase (EC 2.7.1.1) and glucose-6-P dehydrogenase (EC 1.1.1.49).

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2.7. Extraction and assay of antioxidant enzymes and reactive oxygen species (ROS) For extraction of the antioxidant enzymes, lentil seedlings were initially ground to powder in liquid nitrogen and then extracted with 50 mM sodium phosphate buffer (pH 6.8) for peroxidase (POX) and catalase (CAT) and 50 mM sodium phosphate buffer (pH 7.2) for ascorbate peroxidase (APX) and 100 mM potassium phosphate buffer (pH 7.6) for superoxide dismutase (SOD) using polyvinyl pyrrolidone under ice cold conditions. The homogenates were then centrifuged at 10,000 rpm for 10 min at 48 0C. Supernatants were used as crude enzyme extracts. Protein content in each of the extract was estimated following the method of Lowry et al. (1951) using bovine serum albumin (BSA) as standard curve. 2.7.1. Ascorbate peroxidase (APX: EC.1.11.1.11) 6

ACCEPTED MANUSCRIPT APX activity was assayed as decrease in absorbance by monitoring the oxidation of ascorbate at 290 nm with a UV/visible spectrophotometer (M501, Campspec Ltd, Cambridge, UK) according to the method of Chen and Asada (1989). The reaction mixture consisted of 0.01 mL of enzyme extract, 0.5 mM ascorbic acid (ASC), 30 % H2O2 (v/v) and 0.05 M sodium phosphate buffer (pH 7.2). The molar absorption coefficient of ASC (2.8 mM.cm−1) was used to calculate the enzyme activity. Enzyme activity was finally expressed as mmol ascorbate. mg-1 protein. min-1.

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2.7.2. Peroxidase (POX: EC 1.11.1)

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For determination of POX activity, 40 µL of freshly prepared crude enzyme extract was added to the reaction mixture containing 1 ml of 0.1 M phosphate buffer (pH 6.8), 1 mL of 20 mM guaiacol and 50 µL of 10 mM H2O2. POX activity was assayed spectrophotometrically in a UV/visible spectrophotometer (M501, Campspec Ltd, Cambridge, UK) at 470 nm for 10 min at 30 oC 460 nm by monitoring the oxidation of guaiacol in the presence of H2O2 (Goliber, 1989). Specific activity was expressed as mmol guaiacol. mg-1 protein. min-1.

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2.7.3. Catalase (CAT: EC.1.11.1.6) The CAT activity was assayed as described by Chance and Maehly (1955). Enzyme extract (40 µL) was added to 30 % H2O2 (v/v) in phosphate buffer pH 6.8 and the breakdown of H2O2 was measured at 240 nm in a UV/visible spectrophotometer (M501, Campspec Ltd, Cambridge, UK). An equivalent amount of buffer containing H2O2 was used as reference. The enzyme activity was expressed as mmol H2O2 mg-1 protein. min-1. The molar absorption coefficient of H2O2 (0.04 mM-1. Cm-1) was used to calculate the enzyme activity.

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2.7.4. Superoxide dismutase (SOD: EC 1.15.1.1) The SOD activity was assayed by monitoring the inhibition of the photochemical reduction of nitroblue tetrazolium (NBT) according to the method of Dhindsa et al. (1981). Three ml of the assay mixture constituted of 0.1 ml enzyme extract, 100 mM phosphate buffer (pH 7.6), 1.5 mM Na2CO3, 2.25 mM NBT, 200 mM methionine, 3 mM ethylene diamine tetra acetic acid (EDTA), 0.06 mM riboflavin and distilled water. The reaction tubes containing enzyme samples were illuminated with a 15 W fluorescent lamp for 10 min. The other set of tubes lacking enzymes were also illuminated and served as control. A nonirradiated complete reaction mixture served as blank. The absorbance of samples was measured at 560 nm with a UV/visible spectrophotometer (M501, Campspec Ltd, Cambridge, UK) and 1 unit of activity was defined as the amount of enzyme required to inhibit 50 % of the NBT reduction rate in the controls containing no enzymes. 2.7.5. Quantification of superoxide anion (O2 −) The O2 − concentration was quantified, following the method of Doke (1983). One gram tissue was homogenized in a pre-chilled mortar using 50 mM sodium acetate buffer containing 10 mM sodium chloride (NaCl) (pH 6.5). The homogenate was filtered by doublelayered cheesecloth and centrifuged at 10000 rpm for 10 min. The supernatant was collected and made up to a known volume. An aliquot (0.1ml) of the extract was taken and mixed with

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2.7.6. Quantification of hydrogen peroxide (H2O2) The H2O2 concentration in the incubation medium of the treated plant tissues was estimated as per the procedure of Bellincampi et al. (2000). It was based on the peroxidase mediated oxidation of ferrous ion (Fe2+) followed by the reaction of ferric ion (Fe3+) with xylenol orange. One gram of seedling sample was taken and homogenized in 10 ml of cold 10 mM phosphate buffer (pH 7) using a pre-chilled mortar and pestle. The homogenate was filtered and centrifuged at 10000 rpm for 10 min. the supernatant was collected and made up to a known volume using the buffer. The extract (1.5 ml) was added to an equal volume of assay reagent containing 500 µM ammonium ferrous sulphate, 50 mM H2SO4, 200 µM xylenol orange and 200 mM sorbitol. The assay mixture was incubated for 45 min and the absorbance of the Fe3+ xylenol orange complex at 560 nm with a UV/visible spectrophotometer (M501, Campspec Ltd, Cambridge, UK) was observed.

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27.7. Determination of lipid peroxidation (LPX) The level of lipid peroxidation was measured in terms of malondialdehyde (MDA) content (Heath and packer, 1968). The plant sample (0.5g) was homogenized in 10 mL 0.1 % trichloro acetic acid (TCA) using a mortar and pestle. The homogenate was centrifuged at 15000 rpm for 5 min. To 1.0 mL supernatant, 4.0 mL 0.5 % thiobarbituric acid (TBA) in 20 % TCA was added. The mixture was heated at 95 °C for 30 min, and then quickly cooled in an ice bath. After centrifugation at 10000 rpm for 10 min, the absorbance of supernatant was recorded at 532 nm with a UV/visible spectrophotometer (M501, Campspec Ltd, Cambridge, UK). The value for nonspecific absorption at 600 nm was subtracted. The concentration of lipid peroxides was quantified in terms of MDA level using an extinction coefficient of 155 mM. cm−1 and expressed as nmol g−1 fresh weight.

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the assay reagent containing 0.01 M potassium phosphate buffer (pH 7.8) with 0.05 % nitro blue tetrazolium sodium salt (NBT) and 10 mM sodium azide (NaN3). The assay mixture was incubated for 30 min and the initial absorbance at 580 nm was taken in a UV/visible spectrophotometer (M501, Campspec Ltd, Cambridge, UK). Final absorbance was taken after heating the mixture at 85 oC for 15 min.

2.8. Estimation of Silicon (Si) Si content was determined by a modified autoclave-induced digestion (AID) method (Elliot and Snyder, 1991). The seedlings were oven dried and grounded in a Retsch centrifugal mill ZM-200 (Retsch, Haan, Germany) into fine powder. The ground samples (0.1 g) were wetted with 3 ml of a 30 % hydrogen peroxide solution and 3.25 mL of 50 % sodium hydroxide (NaOH) in polyethylene tubes and gently mixed by vortex. The tubes were placed in an autoclave (SABAC, model T62) at 138 kPa for 1 h at 126oC. Digested samples were brought to 50 ml with distilled water. Si concentration was determined by the colorimetric molybdenum blue method (Liang et al. 2003). To 1.0 mL of digested sample, 9 mL of 20 % acetic acid and 2.5 mL ammonium molybdate (54 g.L-1, pH 7.5) was added in 50 mL of polypropylene volumetric flask. Then 1.25 mL of 20 % tartaric acid and 0.25 mL reducing solution containing 8 g.L-1 sodium sulphite (Na2SO3), 1.6 g.L-1 1-amino- 2-naphthol-4sulfonic acid and 100 g.L-1 sodium bisulphite (NaHSO3) were added immediately. After 30

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minutes, the absorbance was measured at 650 nm wavelength with a UV/visible spectrophotometer (M501, Campspec Ltd, Cambridge, UK). A standard curve was prepared from Si standard solutions (Si1000, Kanto Chemical Co. Inc., Japan).

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3.1. Effect of Si on the germination traits assessed by GP, GI and SVI in lentil genotypes

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The effects of drought stress and Si treatment on the germination percentage (GP) of seven lentil genotypes, calculated using the Eq.1, are shown in Figures 1 and 2a. PEG 6000stress significantly reduced the GP of each genotype as compared to the control. However, Si application under drought stress increased GP significantly in all of the genotypes (p ˂0.01), when compared to drought stressed plants. The effect of Si under drought stress was more pronounced in both the drought-sensitive genotypes, G6 (PI 468898) and G7 (ILL 1796) (2.5fold increase in GP). Interestingly, irrespective of the drought-tolerance capacity, all the studied genotypes exhibited 100 % GP by added Si under non-stress condition. The GI and SVI values were calculated using Equation 2 and 3. Similar to GP values, Si significantly increased GI and SVI values among all the genotypes under drought stress (Figures 2b and 2c). The Si application did not show any significant effect on the GI of each genotype under non-stress condition. However, Si application significantly affected the SVI values in all the studied genotypes under drought stress condition.

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2.9. Statistical analysis All the experiments described were performed in triplicates. The data were analysed statistically using analysis of variance (ANOVA), followed by a tukey pairwise comparison test for mean comparison between genotypes and treatments using Minitab®v17 (Minitab Inc., Pennsylvania, USA). Significant differences among genotypes and treatments were considered at p ≤ 0.05. The data were also analysed using multivariate analysis method based on principal component analysis (PCA), cluster analysis and covariance matrix algorithms through a customised code written in Matlab ver2016b (Mathworks Inc., Natick, MA, USA) to determine changes in drought-tolerance level by Si application for the studied lentil genotypes and to determine the relationships between drought-tolerance assessment traits.

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3. Results

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Figure 1. Seed germination of seven lentil genotypes under different drought stress treatments. ILL 6002 (G1), Indianhead (G2), PBA Jumbo 2 (G3), Nipper (G4), Flash (G5), PI 468898 (G6), ILL 1796 (G7) represents different lentil genotypes. Control (C), drought stress (D), drought stress + Si (DSi) and Si alone (Si) are the different drought-stress treatments. Different letters denote statistical differences at p ˂ 0.01 within genotypes.

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Figure 2a, b and c. Germination percentage (GP %), Germination index (GI) and Seedling vigour index (SVI-%) of the seven lentil genotypes under different drought-stress treatments. ILL 6002 (G1), Indianhead (G2), PBA Jumbo 2 (G3), Nipper (G4), Flash (G5), PI 468898 (G6), ILL 1796 (G7) represents different lentil genotypes. Control (C), drought stress (D), drought stress + Si (DSi) and Si alone (Si) are the different drought-stress treatments. Mean values provided with error bars representing the standard error. Different letters denote statistical differences at p ˂ 0.05 within genotypes.

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3.2. Effects of Si application on fresh and dry weight of the seedlings

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The fresh and dry weight of the seedlings decreased significantly with exposure to drought stress (Table 2). However, application of Si increased the fresh and dry weight under stress and non-stress conditions.

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374 375 376 377 378 379 380

Control (C)

120±0.002b 80±0.001b 120±0.001b 90±0.002b 120±0.001b 180±0.003b 50±0.001b

Fresh Weight (mg) Drought (D) Drought +Si (DSi) 80±0.001d 90±0.001c 50±0.002d 70±0.002c 70±0.001c 90±0.003c 70±0.003c 80±0.001c 90±0.002c 100±0.002c 80±0.002d 110±0.001c 100±0.001d 40±0.002c

Si (Si)

Control (C)

130±0.001a 140±0.002a 160±0.001a 150±0.002a 150±0.010a 190±0.001a 80±0.001a

9±0.0001b 5±0.0001b 9±0.0001b 5±0.0001b 7±0.0001b 1±0.0001b 1±0.0002b

Dry Weight (mg) Drought (D) Drought + Si (DSi) 4±0.0001c 9±0.0002b 3±0.0001c 6±0.0002b 0 7±0.0002c 0 4±0.0001c 0 5±0.0001c 0 2±0.0002b 0 2±0.0001b

Si (Si) 16±0.0001a 17±0.0002a 8±0.0002a 7±0.0001a 9±0.0001a 6±0.0002a 4±0.0002a

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ACCEPTED MANUSCRIPT Table 2. Fresh and dry weight (mg) of the seedlings of seven lentil genotypes under different drought-stress treatments. Mean values provided with error bars representing the standard error. Different letters denote statistical differences at p ˂ 0.01 within genotypes.

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3.3. Effects of Si application on the levels of osmolytes in seedlings of lentil plants

390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408

The concentrations of the osmolytes (proline, GB and total soluble sugar) significantly increased in all the lentil genotypes under drought stress, while Si treatment led to a reduction in their values (Figures 3a, 3b and 3c). Figure 3a shows the variation in proline concentration, obtained using the Eq. 4, in all the lentil genotypes under different droughtstress treatments. Drought stress alone increased the proline level almost 2-fold compared to the control treatment in all the genotypes. Interestingly, proline concentration was found to be higher in drought-tolerant genotypes, G1 (ILL 6002) and G2 (Indianhead), when compared to the drought-sensitive genotypes, G6 (PI 468898) and G7 (ILL 1796) in all the treatments. The application of Si lowered the proline level of drought-stressed seedlings by 20-25 %. Even though GB accumulation increased significantly in drought stressed seedlings, Si application resulted in 20-40 % reduction in GB content of drought stressed plants. However, there was no significant difference in GB content of Si treated lentil seedlings under non-stress condition, compared to control. The accumulation of GB was higher in drought-tolerant genotypes, G1 (ILL 6002) and G2 (Indianhead), when compared to the drought-sensitive genotypes, G6 (PI 468898) and G7 (ILL 1796) in all the treatments (Figure 3b). Similar to proline and GB, considerable variation in the total soluble sugar concentration was observed in all the studied genotypes under Si treated and non-Si treated drought-stress treatments (Figure 3c). However, the amount of total soluble sugar in only Si treated plants was similar to that of control treatment.

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ACCEPTED MANUSCRIPT Figure 3a, b and c. Concentration of proline (µm/g), glycine betaine (GB- µm/g) and total soluble sugars concentration (mg/g) in seven lentil genotypes under different drought-stress treatments. ILL 6002 (G1), Indianhead (G2), PBA Jumbo 2 (G3), Nipper (G4), Flash (G5), PI 468898 (G6), ILL 1796 (G7) represents different lentil genotypes. Control (C), drought stress (D), drought stress + Si (DSi) and Si alone (Si) are the different drought-stress treatments. Mean values provided with error bars representing the standard error. Different letters denote statistical differences at p ˂ 0.05 within genotypes.

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3.4. Effects of Si application on the activities of hydrolytic enzymes

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The activity of hydrolytic enzyme (α-amylase, β-amylase and α-glucosidase) decreased significantly in all the genotypes under PEG 6000-induced drought stress and the effect was reversed by the addition of Si (Figures 4a, 4b and 4c). Under control conditions, the drought-tolerant genotypes, G1 (ILL 6002) and G2 (Indianhead) showed the maximum αamylase activity of 1.5 and 1.4 µm-1.min-1.g tissue respectively. Whereas, the droughtsensitive genotypes G6 (PI 468898) and G7 (ILL 1796) displayed lower activity of this hydrolytic enzyme, i.e. 0.83 and 0.86 µm-1.min-1.g tissue, respectively. Similar levels of αamylase activity (1 µm-1.min-1.g tissue) was noticed in all the moderately drought-tolerant genotypes G3 (PBA Jumbo 2), G4 (Nipper) and G5 (Flash). The percentage of decrease in the α-amylase activity of the genotypes under drought stress was recorded as 30 % (G1), 35 % (G2), 57 % (G3), 54 % (G4), 58 % (G5), 77 % (G6) and 79 % (G7). Si supplementation significantly increased the enzyme activity in all the genotypes under drought-stress treatments as seen in figure 4a. A similar trend was observed for the activity profile of the hydrolytic enzymes, β-amylase and α-glucosidase. β-amylase activity under drought stress ranged from 20 % reduction in the drought-tolerant genotypes G1 (ILL 6002) and G2 (Indianhead) to 65 % in drought-sensitive genotypes G6 (PI 468898) and G7 (ILL 1796), when it was compared to the control (Figure 4b). However, the activity of α-glucosidase ranged from 20 % in the drought-tolerant genotypes G1 (ILL 6002) and G2 (Indianhead) to 50 % in drought-sensitive genotypes G6 (PI 468898) and G7 (ILL 1796) under drought stress. Si supplied under drought stress significantly enhanced the activity of β-amylase and α-glucosidase in all the genotypes (Figure 4c).

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Figure 4a, b and c. Activity of α-amylase, β-amylase and α-glucosidase (µmoles of reducing sugars formed min/g) of the seven lentil genotypes under different drought-stress treatments. ILL 6002 (G1), Indianhead (G2), PBA Jumbo 2 (G3), Nipper (G4), Flash (G5), PI 468898 (G6), ILL 1796 (G7) represents different lentil genotypes. Control (C), drought stress (D), drought stress + Si (DSi) and Si alone (Si) are the different drought-stress treatments. Mean values provided with error bars representing the standard error. Different letters denote statistical differences at p ˂ 0.05 within genotypes.

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3.5. Effects of Si application on the concentration of H2O2, O2

448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464

Table 3 shows that the concentration of H2O2, O2 − and LPX were significantly higher in response to drought stress in all the lentil genotypes, whereas the concentration in response to DSi treatment showed lower values when compared to control. The drought-tolerant genotypes G1 (ILL 6002) and G2 (Indianhead) showed lower accumulation of ROS and LPX when compared to the drought-sensitive genotypes G6 (PI 468898) and G7 (ILL 1796) in all the treatments. An increase of 55-70 % in H2O2 content was measured in the droughtstressed lentil seedlings, whereas a decrease of 60-65 % was observed in DSi treatment. Si treatment even lowered the H2O2 content in non-stressed lentil seedlings to 20-30 %. Added Si decreased the O2 − content in drought stressed lentil seedlings to 0.5-1 fold, when compared to 1.5-2.5 fold increase under drought stress treatments (Table 3). MDA is a final product of LPX and its content has been considered as an indicator of oxidative stresses in plants (Mittler, 2002). Significant changes in MDA content in lentil seedlings to drought stress and DSi treatments were observed when compared to their respective controls. Drought stress resulted in a significant increase in LPX in all the lentil genotypes. However, application of Si under drought stress significantly recovered the membrane damage in seedlings as shown from the lower values of LPX. Addition of Si to non-stressed plants didn’t reveal any significant changes in MDA content (Table 3). Thus, the application of Si

−

and LPX

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ACCEPTED MANUSCRIPT seemed to have a protective effect in terms of these parameters under drought stress conditions by lowering the concentration of ROS and LPX.

G3

G4

G5

G6

G7

O2

−

(µm-1.ml)

167.89 ± 0.23 425.36 ± 0.49 153.25 ± 0.52 165.28 ± 0.53 163.25 ± 0.27 414.25 ± 0.24 162.32 ± 0.78 160.25 ± 0.29 215.02 ± 0.25 598.21 ± 0.27 204.56 ± 0.45 210.89 ± 0.67 211.19 ± 0.59 564.32 ± 0.27 201.02 ± 0.46 200.07 ± 0.97 208.37 ± 0.83 546.32 ± 0.22 200.03 ± 0.25 207.90 ± 0.98 255.23 ± 0.21 642.35 ± 0.38 224.12 ± 0.27 213.25 ± 0.09 257.01 ± 0.27 655.02 ± 0.36 214.20 ± 0.97 220.01 ± 0.28

LPX (µmol-1.g) 0.08 ±0.01 1.98 ± 0.11 0.97 ± 0.02 0.06 ± 0.01 0.07 ± 0.01 1.87 ± 0.12 0.77 ± 0.01 0.07 ± 0.02 0.15 ± 0.04 2.79 ± 0.10 0.85 ± 0.11 0.09 ± 0.01 0.15 ± 0.02 2.58 ± 0.43 0.72 ± 0.03 0.13 ± 0.01 0.14 ± 0.05 2.86 ± 0.21 0.65 ± 0.11 0.11 ± 0.01 0.22 ± 0.02 2.34 ± 0.23 0.67 ± 0.03 0.15 ± 0.04 0.26 ± 0.10 2.45 ± 0.23 0.59 ± 0.11 0.11 ± 0.01

Si (% g-1 dry weight) 0.0042 ±0.006 0.0132 ± 0.002 0.0324 ± 0.021 0.0067 ± 0.001 0.0046 ± 0.003 0.0142 ± 0.003 0.0364 ± 0.022 0.0051 ± 0.002 0.0047 ± 0.011 0.0125 ± 0.010 0.0368 ± 0.011 0.0072 ± 0.003 0.0041 ± 0.023 0.0361 ± 0.014 0.0078 ± 0.004 0.0067 ± 0.014 0.0042 ± 0.011 0.0328 ± 0.021 0.0066 ± 0.013 0.0049 ± 0.002 0.0041 ± 0.023 0.0375 ± 0.014 0.0067 ± 0.020 0.0071 ± 0.004 0.0049 ± 0.021 0.0321 ± 0.011 0.008 ± 0.014 0.0052 ± 0.013

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Control Drought Drought+Si Si Control Drought Drought+Si Si Control Drought Drought+Si Si Control Drought Drought+Si Si Control Drought Drought+Si Si Control Drought Drought+Si Si Control Drought Drought+Si Si

H2O2 (µmol-1.g) 1.22 ± 0.33 2.08 ± 0.01 0.73 ± 0.32 0.87 ± 0.01 1.24 ± 0.31 2.12 ± 0.01 0.85 ± 0.11 0.98 ± 0.21 1.55 ± 0.02 3.65 ± 0.14 1.37 ± 0.01 1.15 ± 0.01 1.46 ± 0.23 3.58 ± 0.11 1.26 ± 0.02 1.02 ± 0.87 1.57 ± 0.24 3.56 ± 0.52 1.31 ± 0.05 1.13 ± 0.11 2.22 ± 0.31 3.75 ± 0.02 1.44 ± 0.03 1.63 ± 0.11 1.98 ± 0.03 3.25 ±0.03 1.21 ± 0.61 1.54 ± 0.04

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Table 3. Concentration of hydrogen peroxide (H2O2), superoxide anion (O2 −), lipid peroxides (LPX) and silicon (Si) of the seven lentil genotypes under different drought-stress treatments. Mean values provided with error bars representing the standard error. Different letters denote statistical differences at p ˂ 0.05 within the genotypes.

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3.6. Effects of Si application on the activities of antioxidant enzymes

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The activity of antioxidant enzymes, APX, POX, CAT and SOD in lentil seedlings increased significantly under drought stress as compared to normal plants. However, Si treatment was found to be effective in enhancing the activity of these enzymes under drought stress and normal conditions (Table 4). The drought-tolerant genotypes G1 (ILL 6002) and G2 (Indianhead) showed the maximum activity of all the antioxidant enzymes studied, whereas the drought- sensitive genotypes G6 (PI 468898) and G7 (ILL 1796) exhibited the minimum values of enzyme activities in all the treatments.

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APX

POX

CAT

SOD (units-1.mg 15

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G4

protein)

protein)

G6

G7

protein)

0.785 ± 0.012

0.321 ± 0.005

0.295 ± 0.006

0.52 ± 0.06

Drought

1.301 ± 0.014

0.687 ± 0.015

0.512 ± 0.026

1.56 ± 0.01

Drought+Si

2.010 ± 0.045

1.354 ± 0.008

0.655 ± 0.014

1.87 ± 0.02

Si

1.110 ± 0.023

0.567 ± 0.017

0.335 ± 0.062

0.88 ± 0.07

Control

0.775 ± 0.022

0.354 ± 0.012

0.275 ± 0.032

0.63 ± 0.01

Drought

1.400 ± 0.020

0.701 ± 0.012

0.495 ±0.008

1.67 ± 0.02

Drought+Si

2.130 ± 0.012

1.212 ± 0.007

0.665± 0.012

1.97 ±0.02

Si

1.010± 0.011

0.435 ± 0.031

0.401 ± 0.037

0.97 ± 0.01

Control

0.301 ± 0.032

0.346 ±0.013

0.201 ± 0.022

0.36 ± 0.05

Drought

0.454 ± 0.045

0.762 ± 0.017

0.327 ± 0.032

0.87 ± 0.02

Drought+Si

0.735 ± 0.001

1.301 ± 0.090

0.524 ± 0.014

1.27 ± 0.07

Si

0.387 ± 0.004

0.511 ± 0.075

0.268 ± 0.016

0.67 ± 0.08

Control

0.358 ± 0.087

0.265 ± 0.036

0.213 ± 0.061

0.32 ± 0.06

Drought

0.584 ± 0.014

0.529 ± 0.033

0.361 ± 0.030

0.97 ±0.01

Drought+Si

0.934 ± 0.011

1.125 ± 0.028

0.556 ±0.018

1.89 ± 0.06

Si

0.398 ± 0.042

0.398 ± 0.028

0.271 ± 0.008

1.1 ± 0.01

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0.324 ± 0.038

0.264 ± 0.003

0.221± 0.009

0.38 ± 0.03

Drought

0.476 ± 0.009

0.545 ± 0.009

0.374 ± 0.007

0.86 ± 0.02

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(mmol-1.mg

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(mmol-1.mg

Drought+Si

0.791 ± 0.089

1.324 ± 0.067

0.567 ± 0.013

1.76 ± 0.01

Si

0.443 ± 0.014

0.401 ± 0.024

0.312 ± 0.010

0.67 ± 0.03

Control

0.197 ± 0.033

0.234 ± 0.025

0.175 ± 0.007

0.15 ± 0.08

Drought

0.271 ± 0.002

0.561 ± 0.008

0.241 ± 0.035

0.28 ± 0.03

Drought+Si

0.497 ± 0.045

1.526 ± 0.045

0.485 ± 0.004

1.21 ± 0.04

Si

0.235 ± 0.014

0.339 ±0.023

0.265 ± 0.019

0.33 ± 0.08

Control

0.187 ± 0.012

0.231 ± 0.067

0.169 ± 0.015

0.18 ± 0.07

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ACCEPTED MANUSCRIPT Drought

0.278 ± 0.007

0.615 ± 0.012

0.301 ± 0.024

0.29 ± 0.09

Drought+Si

0.505 ± 0.003

1.465 ± 0.011

0.534 ± 0.023

1.35 ± 0.02

Si

0.261 ± 0.013

0.253 ± 0.023

0.245 ± 0.011

0.76 ± 0.03

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Table 4. Activity of the antioxidant enzymes ascorbate peroxidase (APX), peroxidase (POX), catalase (CAT) and superoxide dismutase (SOD) of the seven lentil genotypes under different drought-stress treatments. Mean values provided with error bars representing the standard error. Different letters denote statistical differences at p ˂ 0.05 within genotypes.

486 487 488 489 490 491 492 493 494 495 496

Although drought stress caused an increase in the activity of APX, it was higher in drought stress supplimented with Si (DSi) treatment than in the other treatments (Table 4). Compared to control, APX activity was significantly elevated up to 62-65 % in the drought tolerant genotypes, 50-60 % in moderately drought-tolerant and 35-50 % in droughtsusceptible genotypes under drought stress. Si treatment again alleviated the enzyme activity by 52-54 % in drought-tolerant seedlings, 65-70 % in moderately drought-tolerant and 80-85 % in drought-susceptible genotypes when compared to drought stress treatments (Table 4). Compared to control, POX activity was subsequently increased to 1-2 fold under drought stress treatments in all the studied lentil genotypes. Si application in DSi treatments caused 1fold, 0.5-1.5 fold and 1-2 fold increase in POX activity of drought-tolerant, moderately drought-tolerant and drought-susceptible genotypes, respectively (Table 4).

497 498 499 500 501 502 503 504 505 506 507 508

CAT activity in drought stressed lentil seedlings increased by 70-80 % in the droughttolerant genotypes, 60-70 % in moderately drought-tolerant and 30-40 % in droughtsusceptible genotypes when compared to the control. However with Si treatment, CAT activity enhanced by 25-35 % in drought-tolerant genotypes, 50-60 % in moderately droughttolerant and 75-85 % in the drought-susceptible genotypes. Similar to other antioxidant enzyme activity profiles, SOD activity also increased in drought stressed lentil seedlings, showing a similar trend to other antioxidant enzymes, under both drought stress condition and DSi treatments. Compared to control, 1.5-2 fold, 1-2 fold and 0.5-1 fold increase in SOD activity was noticed under drought stress in drought-tolerant genotypes, moderately-droughttolerant and drought-susceptible genotypes, respectively (Table 4). Even though Si application enhanced SOD activity under DSi treatments in all the genotypes, the enhancement was not much significant.

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3.7. Effect of Si on the concentration of Si in lentil seedlings

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In the present study, Si concentration of the drought stressed lentil seedlings increased significantly and is probably related to genotypic differences or concentration effect of Si caused by reduced growth due to drought stress (Table 3). Moreover, the exogenous application of Si increased Si concentrations of all the lentil seedlings under drought stress (Table 3).

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3.8. Multivariate data analysis

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The results from multivariate data analysis from all the four treatments are shown in Figure 5. The PCA obtained from the seven lentil genotypes under control (C), drought stress (D), drought stress supplimented with Si (DSi), and Si alone (Si) including the germination traits (GP, GI and SVI), osmolytes, hydrolytic enzymes, antioxoidant enzymes, H2O2, O2 −, LPX and Si content explained a total of 80.35 % (PC1 = 49.7 %; PC2 = 30.60 %) of variability in the data (Figure 5a). The drought-tolerance assessment traits (GI, GP, SVI, osmolytes hydrolytic enzymes, antioxidant enzymes and ROS) were significantly correlated among themselves (statistical significance at p ≤ 0.05, figure 6). Significant positive correlations were observed between GP and GI, SVI and β-amylase, proline and APX, αamylase and β-amylase, H2O2 and O2 − whereas, GP and LPX, GI and LPX, α-amylase and GB showed significant negative correlations (figure 6). From Figure 4a, four distinctive groups can be observed with group 1 corresponding to control treatments separated between tolerant, moderately tolerant and sensitive groups. The same pattern was observed for the rest of the groups. As expected, the drought stress treatment presented the lowest values for germination traits and hydrolytic enzymes (Figures 2a, 2b, 2c, 4a, 4b and 4c) with reduced variation for proline and sugar (Figures 3a and 3b). Group 3 from the DSi treatment exhibited increased drought-tolerance trait values for all the genotypes positioning the group in between the drought (group 2) and the control (group 1) treatments. The Si treatment, showed higher levels of the drought-tolerance trait values studied for drought-tolerance, positioning all the genotypes closer to the control treatment (group 1).

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Figure 5a and b. (a) PCA biplot for drought-tolerance related traits as vectors and (b) cluster analysis according to the effect of Si on the seven lentil genotypes under control (C), drought stress (D), drought stress + Si (DSi) and Si alone (Si). The abbreviations used in this figure 19

ACCEPTED MANUSCRIPT are ILL 6002 (G1), Indianhead (G2), PBA Jumbo 2 (G3), Nipper (G4), Flash (G5), PI 468898 (G6) and ILL 1796 (G7).

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Figure 6. Covariance matrix for the drought-tolerance related traits studied in seven lentil genotypes.

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The cluster analysis clustered the lentil genotypes into different groups based on different drought-stress treatments (Figure 5b). The drought-tolerant genotypes, G1 (ILL 6002) and G2 (Indianhead) always clustered together under different drought-stress treatments. Similar clustering was observed in moderately drought-tolerant and droughtsensitive genotypes at linkage distance 50.

551 552 553 554 555 556 557 558 559 560

4. Discussion 4.1. Seed germination traits Seed germination and seedling emergence are among the most critical and sensitive stages in the life cycle of plants. Seeds exposed to drought stress may compromise the subsequent seedling establishment and hence the productivity and quality of seeds. Drought is one of the most critical environmental factors limiting lentil productivity in many regions of the world. Some of the studies have shown that lentil plants are sensitive to drought stress during seedling emergence (Muscolo et al. 2014; Mishra et al. 2016). The decline in water potential gradient between seeds and their surrounding media by the effect of PEG 6000 affects seed germination. A decline in germination traits under drought stress has also been

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ACCEPTED MANUSCRIPT reported in other legumes such as pea (Okcu et al. 2005) and blackgram (Pratap and Sharma, 2010). Blackgram and pea showed a significant decrease in germination percentage, i.e. 70 % GP with the osmotic potential of -10 bars and 23 % GP with an osmotic potential of -8 bars, respectively. Results from the present study showed that drought stress negatively affected seed germination, which could be improved by the addition of Si, as it was clearly shown by increase in GP, GI and SVI values, especially for the drought-sensitive genotypes G6 (PI 468898) and G7 (ILL 1796) (Figures 2a, 2b and 2c). These results are consistent with studies done in tomato (a Si excluder), in which the GI, length and fresh weight of seedlings under PEG-simulated drought stress were significantly improved by Si application (Shi et al. 2014). Previous studies have suggested that Si has positive effect on the physiology and metabolism of different plants against drought stress (Torabi et al. 2012; Ma and Yamaji, 2008; Liang et al. 2003). These findings suggested that Si may be involved directly or indirectly in both morphological changes and physiological processes in plants. Results from the present study also showed that during drought stress Si played a protective role in normal seed germination. This ameliorative effect of Si may be due to its hydrophilic nature by protecting the plants from drought. Irrespective of the drought-tolerance capacity, all the lentil genotypes displayed 100 % seed germination with Si treatment. Thus, from the results of the current research Si is shown to be effective in securing 100 % seed germination and enhanced drought stress tolerance at the germination and seedling stages.

582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599

When a seed starts to germinate, its fresh weight will increase due to the absorption of water. In this study, the seedling fresh and dry weight of all genotypes declined as expected under drought stress condition, and there were significant differences among the genotypes (Table 2). Fresh weight of drought-tolerant genotypes G1 (ILL 6002) and G2 (Indianhead), and drought-sensitive genotypes G6 (PI 468898) and G7 (ILL 1796) decreased under drought stress. The drought-tolerant genotypes G1 (ILL 6002) and G2 (Indianhead) had a higher seedling dry weight than the sensitive ones G6 (PI 468898) and G7 (ILL 1796) under drought stress. The drought-tolerant and moderately drought-tolerant genotypes exhibited a reduction in seedling dry weight under drought stress while the drought-sensitive genotypes had negligible dry weight showing the sensitivity of these genotypes to drought stress. This could be attributed to reduced photosynthesis, biomass accumulation, respiration and nutrient metabolism (Jaleel et al. 2009). A reduction in plant dry weight under drought stress has also been reported in maize (Ashraf et al. 2007) and chickpea (Gunes et al. 2007). Si was able to enhance the seedling fresh and dry weight of all the genotypes under non-stress condition. These results are consistent with Liu et al. (2011) findings, where they reported that Si addition significantly increased the biomass of drought stressed alfalfa seedlings. Thus, this study shows that Si-mediated drought-tolerance of lentil seedlings is induced by increased water uptake ability and by modulating sugar levels under stress and non-stress conditions.

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4.3. Osmolytes (proline, GB and total soluble sugar) A common stress tolerance mechanism in plants against environmental stresses is the overproduction of different types of osmolytes, such as proline, GB and soluble sugars. The

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accumulation of these osmolytes in plants might be involved in one or more of the processes such as osmotic adjustment, detoxification of reactive oxygen species, protection of membrane integrity, and the stabilization of proteins/enzymes and thus contributes to drought-tolerance (Blum, 2016). In the present experiment, drought stress resulted in significant accumulation of proline in lentil seedlings. The proline concentration was higher in drought-tolerant genotypes, when compared to the drought-sensitive and moderately drought-tolerant genotypes, as was observed earlier in two drought-tolerant lentil genotypes (Muscolo et al. 2014). Contrary to our findings, Oktem et al. (2008) reported that proline amounts did not differ significantly under drought stress for Turkish lentil genotypes. The present result implies that the accumulation of proline is associated with drought-tolerance. Added Si led to a significant decrease in the proline concentration of drought stressed seedlings (Figure 3a), which can be related to the added tolerance effect mediated by Si based on proline biosynthesis/accumulation. The latter can be attributed to the reaction between proline and Si forming silaproline, similar to the mechanism which takes place in humans (Vivet et al. 2000). Similar results were obtained by Gunes et al. (2008) from sunflower genotypes and Mauad et al. (2016) in upland rice plants under drought stress.

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GB not only acts as an osmoregulator, but also stabilizes the structures and activities of enzymes and proteins, and maintains the integrity of cell membranes against the damaging effects of environmental stresses. PEG-induced drought stress enhanced the concentration of GB in all the lentil genotypes (Figure 3b). Moreover, the drought-tolerant genotypes accumulated more GB than sensitive genotypes in all the treatments. Added Si may be responsible for less GB accumulation in all the seedlings which might be a sign of stress injury alleviation. Consequently, regulated levels of GB would make possible for the plant to regulate low water potential that allows additional water uptake from the stress environment, thus buffering the immediate effect of drought stress within the organism (Blum, 2016). Drought stress increased the seedling soluble sugar concentration of all lentil genotypes (Figure 3c). This result is consistent with one recent study carried out under drought conditions in lentil genotypes showing an increase in total soluble sugar concentration (Muscolo et al. 2014, Mishra et al. 2016). Compared with the stressed seedlings without additional Si, seedlings with added Si had significantly lower soluble sugar concentration. This shows that drought stress conditions enhanced the anabolism of soluble sugar and adding Si decreased the anabolism of soluble sugar under drought stress. This observation was contradictory to a previous study in which increased soluble sugar levels were observed under Si treatment in drought stressed wheat seedlings (Si accumulator) (Pei et al. 2010). This may be related to the genetic difference between a Si accumulator such as rice, wheat, and sorghum and Si excluder such as lentil and tomato. Further studies using different crops from Si accumulators and Si excluders will ascertain such differences. This result also revealed that under control and Si treatment without stress conditions, no significant effect of Si on the total soluble sugar level was observed in all the genotypes, which may show that Si application is more effective under stress conditions. Similarly to the case of proline and GB, the highest concentrations of soluble sugar were observed in the drought-tolerant genotypes, G1 (ILL 6002) and G2 (Indianhead), when compared to the

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ACCEPTED MANUSCRIPT moderately drought-tolerant and drought-sensitive genotypes during all treatments. Similar to the present findings, high accumulation of soluble sugar was also noticed in drought-tolerant pea and wheat plants when compared to drought-sensitive ones (Okcu et al. 2005; Pei et al. 2010).

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4.4. Hydrolytic enzymes Starch is the principal storage carbohydrate and its degradation is essential for seed germination. In germinating seeds, starch degradation is initiated by hydrolytic enzymes such as amylases (α and β) and α-glucosidase producing soluble oligosaccharides. These are further hydrolysed by α-amylase to liberate maltose, which is finally broken down by αglucosidase into glucose, providing energy to the germinating seeds. Conversely, the activity of hydrolytic enzymes in germinating seeds is reduced by drought stress. In the present study, PEG 6000 application resulted in reduced water content in the cells of germinating seeds and as a result the activity of the hydrolytic enzymes also decreased (Figures 4a, 4b and 4c). However, applied Si resulted in an increased enzyme (β-amylase and α-glucosidase) activity in all the genotypes. The effect was more pronounced in drought-sensitive genotypes, G6 (PI 468898) and G7 (ILL 1796) with an almost 1.5-fold increase in enzyme activity. The seedlings of the drought-tolerant G1 (ILL 6002) and G2 (Indianhead), and moderately drought-tolerant genotypes PBA Jumbo 2 (G3), Nipper (G4) and Flash (G5) maintained high levels of enzyme activity compared to sensitive genotypes under all the treatments. The increased enzymatic activities of seedlings grown under Si might be explained due to the improved water status of the genotypes with added Si. The drought-tolerant genotypes G1 (ILL 6002) and G2 (Indianhead) showed a decline in the activity of α-amylase enzyme with added Si under drought stress when compared to other treatments. However, in the moderately drought-tolerant and drought-sensitive genotypes added Si resulted in an increase in α-amylase activity under drought stress. These results suggest that the effect of Si on the enzyme activity involved in carbohydrate metabolism is quite complex and speciesdependent. However, further studies are needed to explore how Si stimulates the desired activity of hydrolytic enzymes under drought stress. 4.5. Antioxidant enzymes and reactive oxygen species (ROS) Many metabolic processes in plant result in the production of reactive oxygen species (ROS), such as superoxide anion (O2 −), hydrogen peroxide (H2O2), and the hydroxyl radical (-OH). Environmental stresses also increase the formation of ROS that oxidizes membrane lipids, photosynthetic pigments, proteins and nucleic acids. The increase in lipid peroxidation has also been reported in many plants under various environmental stresses (Gunes et al. 2007). Plants with high levels of antioxidants, either constitutive or induced, have been reported to have greater resistance to this oxidative damage. Meanwhile, plants possess efficient antioxidant defense systems for scavenging ROS. APX, POX, CAT and SOD are the major antioxidant enzymes. SOD dismutates O2 − to H2O2 in the chloroplast, mitochondrion, cytoplasm and peroxisome, thus preventing the cellular damage under stress conditions like drought. APX is a component of the ascorbate-glutathione pathway, which plays a key role in scavenging H2O2. POX also plays an essential role in scavenging H2O2, which is a major by product produced by SOD. CAT eliminates H2O2 by breaking it down directly to form

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A significant increase in the O2 − coupled with H2O2 production and LPX observed under PEG-induced drought stress in lentil seedlings clearly indicates an oxidative burst, facilitating cellular damage (Table 3). The increase of O2 − and H2O2 content caused by drought stress followed by increase of lipid peroxidation in lentil seedlings appears to be alleviated by Si treatments which reduced O2 −, H2O2 accumulation and lipid peroxidation (Table 3). This might be due to the activity of the compatible solutes such as proline and G, which detoxify ROS by forming a stable complex with them and consequently inhibit lipid peroxidation (Gunes et al. 2007). These results similar to Si application decreased H2O2 and lipid peroxidation in leaves of another legume, chickpea (Gunes et al. 2007), sunflower (Gunes et al. 2008) and cereal crop such as wheat (Pei et al. 2010) under drought stress. Recently, it is reported that Si application decreased lipid peroxidation, O2 −, H2O2 accumulation and LPX in liquorice seedlings under drought stress (Zhang et al. 2015).

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This study confirmed that Si addition significantly increased the activity of all antioxidant enzymes and resulted in more effective H2O2 dismutation capacity and O2 − elimination power under DSi and Si treatments (Table 4). Higher activities of antioxidant enzymes in DSi than drought stress treatment might play a role in maintaining low levels of H2O2 in the cells under drought stress. Thus, these results suggest that improved activities of antioxidant enzymes induced by addition of Si might protect plant tissues from membrane oxidative damage under drought stress which could significantly contribute to the improvement of drought tolerance. These results are in agreement with the results of Pei et al. (2010), who found that under drought stress the addition of Si increased the antioxidant activity in wheat plants. This result speculates that Si might be involved in enhancing the expression of genes related to production and activation of antioxidant enzymes in response to drought stress. 4.6. Si content In the current investigation, Si content in lentil seedling was increased by drought stress (Table 3). However, there was no significant variation in Si content among the genotypes. Application of Si under drought stress significantly enhanced Si content in all the genotypes. Although added Si resulted in increased Si content in seedlings under drought stress, lentil is still regarded as a low accumulator of Si, i.e. less than 5 mg g dry weight−1 (Meena et al. 2014). The higher content of Si under drought stress in lentil under DSi treatment might be due to deposition of Si in cell walls which can reduce the impacts of drought stress. The deposited Si could strengthen the membranes of plant cells and change their permeability resulting in improved drought tolerance.

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The PCA results in this study are in agreement with the criteria established by Sneath and Sokal (1973), who showed that data should represent at least 70 % of the total data variability (Figure 5a). The positive correlations were observed among the drought-tolerance assessment traits, such as GI, GP, SVI, α-amylase, β-amylase, proline, GB, soluble sugars, antioxidant enzymes and ROS, where the main separator of the treatments was imposed (Figure 6). The latter showed that these traits can be used to assess drought-tolerance in plants. In the PCA, the biplot characterised the genotypes into four distinct groups (1 to 4). Under control (C) condition (group 1), all the genotypes were present near to the origin in the positive direction of the vectors, showing normal behaviour of drought-tolerance from the specific genotypes as expected. Whereas, under drought stress (D) treatment (group 2), all the genotypes, especially, the genotypes G6 (PI 468898) and G7 (ILL 1796) moved away from the origin in the negative direction showing less drought-tolerance according to germination traits and hydrolytic enzyme activity. With Si supplementation under drought stress (DSi), the genotypes moved closer towards the origin (group 3), showing improvement in droughttolerance. Interestingly, when Si was given alone without drought stress (Si), all the genotypes were sited away from the origin in the positive direction showing the positive effect of Si in improving the drought tolerance of lentil genotypes. Thus, this study clearly shows the positive role of Si in mitigating drought stress in lentil genotypes and furthermore, the results also showed that Si application can be used to increase seed germination and seedling vigour under drought stress and non-drought stress conditions by improving the response of moderately tolerant and sensitive genotypes. The distinct group formation was also observed through the cluster analysis, which categorized the genotypes into different clusters at a linkage distance 50 based on their drought-tolerance levels and the type of drought-stress treatment (Figure 5b).

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From the results showed here, Si application positively affected drought related parameters and consequently improved the seed germination of lentil genotypes under drought stress. Si ameliorated the effects of drought stress in lentil genotypes by induced water uptake ability, modulating levels of osmolytes, regulating the activities of hydrolytic enzymes and antioxidant machinery. This beneficial effect of Si might be linked to its hydrophilic nature and Si deposited in cell walls allows the plants to keep water, dilute salts and protect tissues from physiological drought. Again, it is worth noticing that Si modulates plant metabolism and alters physiological activities, especially in plants under stress than normal environmental conditions.

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Si effect was found to be the more pronounced for the drought-susceptible lentil genotypes compared to moderately drought-tolerant and drought-tolerant ones. This variation in stress sensitivity of the contrasting lentil genotypes might be linked to genetic difference in response of genotypes towards drought stress with added Si or it might be due to the significant role of Si in upgrading the water status of the susceptible genotypes more when compared to the moderately drought-tolerant and drought-tolerant genotypes. However, indepth investigation is needed to understand on how Si regulates plant tolerance to drought stress at the seed germination stage and also the interactions between Si application and plant responses which may help us to better understand the physiological and biochemical 25

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functions of Si. In addition, in future, the studied lentil genotypes are needed to be tested in the field condition to confirm the role of Si in drought tolerance as terminal moisture stress in arid and semi-arid regions is a serious threat that led to early maturity and low yields of lentil plants.

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Drought stress adversely affected seed germination and early seedling growth in all lentil genotypes. The addition of Si for lentil seed germination has been shown to be a beneficial strategy to effectively mitigate the adverse effects of drought stress. However, further studies are required to understand the physiological and biochemical mechanisms of Si-mediated drought stress in higher plants. This study also showed that G1 (ILL 6002) and G2 (Indianhead) are potential drought-tolerant lentil genotypes, along with the latest commercial genotype G3 (PBA Jumbo 2) being moderately drought-tolerant. These genotypes could be potentially used as genetic resources for drought-tolerance in lentil breeding programs. Furthermore, this is the first report demonstrating the significant role Si plays to alleviate drought stress during seed germination and seedling growth in lentil especially for moderately drought-tolerant and drought-sensitive genotypes. There is still the need to better understand Si functions in more species under different environmental conditions to validate the Si-mediated alleviation of drought stress on large scale. Again, more detailed studies are needed to explore the physiological, biochemical and molecular mechanisms of Si-mediated drought stress tolerance in plants. Taken together, well-designed, large-scale, and long-term field trials are required to evaluate the feasibility of Si application under drought stress in plants. These results are important and should be the part of longterm programs involving Si to boost lentil productivity under drought stress conditions in arid and semi-arid regions.

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Conflict of Interest Statement The authors declare that they have no competing interests. Authors and Contributors SB, DG and SF conceived and designed the experiment. SB conducted the experiment, collected and analysed the data, and wrote the manuscript. DG and SF assisted with the data analysis and manuscript preparation. All authors read and approved the final manuscript.

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5. Conclusion

Acknowledgements The authors are grateful to the University of Melbourne for the Australian Government Research Training Program Scholarship given to Sajitha Biju, and the Grains Research and Development Corporation (GRDC) for the Grain Industry Research Scholarship (GRS). References 26

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Silicon enhances drought tolerance of lentil seedlings by regulating the activity of antioxidant and hydrolytic enzymes. Silicon decreases concentration of osmolytes and reactive oxygen species in drought stressed lentil seedlings. Silicon positively influences the seed germination traits in lentil genotypes.

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Sajitha Biju (SB), Dorin Gupta (DG) and Sigfredo Fuentes (SF) conceived and designed the experiment. SB conducted the experiment, collected and analysed the data, and wrote the manuscript. DG and SF assisted with the data analysis and manuscript preparation. All authors read and approved the final manuscript.