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Saudi Journal of Biological Sciences logoLink to Saudi Journal of Biological Sciences
. 2015 Jun 10;22(5):656–663. doi: 10.1016/j.sjbs.2015.06.002

Morphological and physiological characterization of different genotypes of faba bean under heat stress

Manzer H Siddiqui a,⁎, Mutahhar Y Al-Khaishany a, Mohammed A Al-Qutami a, Mohamed H Al-Whaibi a, Anil Grover b, Hayssam M Ali a, Mona Suliman Al-Wahibi a
PMCID: PMC4537876  PMID: 26288573

Abstract

Heat stress (HS) is the major constraint to crop productivity worldwide. The objective of the present experiment was to select the tolerant and sensitive genotype(s) on the basis of morpho-physiological and biochemical characteristics of ten Vicia faba genotypes. These genotypes were as follows: Zafar 1, Zafar 2, Shebam 1, Makamora, Espan, Giza Blanka, Giza 3, C4, C5 and G853. The experimental work was undertaken to study the effects of different levels of temperature (control, mild, and modest) on plant height (PH) plant−1, fresh weight (FW) and dry weight (DW) plant−1, area leaf−1, content of leaf relative water (RWC), proline content (Pro) and total chlorophyll (Total Chl), electrolyte leakage (EL), malondialdehyde level (MDA), hydrogen peroxide (H2O2), and activities of catalase (CAT), peroxidase (POD) and superoxide dismutase (SOD) enzymes. HS significantly affected growth performance of all genotypes. However, the magnitude of reduction in genotypes ‘C5’ was relatively low, possibly due to its better antioxidant activities (CAT, POD and SOD), and accumulation of Pro and Total Chl, and leaf RWC. In the study, ‘C5’ was noted to be the most HS tolerant and ‘Espan’ most HS sensitive genotypes. It was concluded that the heat-tolerant genotypes may have better osmotic adjustment and protection from free radicals by increasing the accumulation of Pro content with increased activities of antioxidant enzyme.

Keywords: Heat stress, Faba bean, Antioxidant system, Proline, Photosynthesis pigment

1. Introduction

Heat, cold, drought and salinity are the major environmental stresses that cause severe problem in many areas of the world. The ever-increasing temperature is one of the limiting factors for plants growth and their yield, and also for geographical distributions of plants. In the coming century, plants will be affected adversely and become more vulnerable to increasing high ambient temperature due to anthropogenic activities that increase gases particularly carbon dioxide, methane, chlorofluorocarbons and nitrous oxides. According to the Fourth Assessment of the Intergovernmental Panel on Climatic Change (IPCC), global average temperature will be increased between 1.8 °C and 4 °C in 2100 (Sánchez et al., 2014). The increasing rate depends on the level of greenhouse gases and can even be larger if the human population and global economy keeps growing at their current rate (Sánchez et al., 2014).

Temperature plays a key role in plant growth, development, reproduction, and yield (Mittler et al., 2012). Like other organisms, plants, the sessile organisms, are constantly exposed to above the normal optimal temperatures. Globally, agriculture has suffered heavily due to the heat stress (HS) or in combination with drought and other environmental factors (Mittler, 2006). According to Lobell et al. (2011), the world wheat and maize production decreased by 3.8% and 5.5% respectively due to heat stress (HS) over the past three decades (1980–2008). Similarly, in 2010, wheat price was decreased up to 50% due to the fact that more than 20% of Russian agricultural producing areas suffered by HS (FAO, 2010; NOAA, 2011). Ortiz et al. (2008) reported that a temperature rise of 3–4 °C might cause 15–35% loss of crop yield in Africa and Asia, and 25–35% in the Middle East.

Due to global warming HS causes a series of changes in plants at morpho-anatomical, physiological, biochemical and molecular levels resulting in a drastic loss of economic yield. The effect of HS starts from the seed germination to flowering, as various stages of plant’s life are temperature-dependent. Seed germination and seed vigor are adversely affected by HS that causes thermal injury or death of the seed (Khan, 1976; Grass and Burris, 1995). HS causes various physiological changes in plants such as scorching of leaves and stems, leaf abscission and senescence, shoot and root growth inhibition or reduction in number of flowers, pollen tube growth and pollen infertility, fruit damage, leading to catastrophic loss of crop yield (Bita and Gerats, 2013; Teixeira et al., 2013; Song et al., 2013; Hemantaranjan et al., 2014). HS affects the photosynthesis, respiration, water relations and membrane stability, and modulates levels of hormones, and primary and secondary metabolites (Hemantaranjan et al., 2014). HS impairs the stability of proteins, membrane integrity, RNA and activity of enzymes in chloroplast and mitochondria, resulting in an imbalance in the metabolic homeostasis (Mittler et al., 2012; Hemantaranjan et al., 2014). The disturbance in metabolic homeostasis leads to the accumulation of toxic by-products, such as reactive oxygen species (ROS) (Mittler et al., 2012). To survive or maintain steady-state balance of metabolic processes under HS, plants reprogram their transcriptome, proteome, metabolome and lipidome, thereby adjusting their composition of certain transcripts, proteins, metabolites and lipids (Mittler et al., 2012). Many heat shock proteins (HSP100s, HSP90s, HSP70s, HSP60s, HSP40s and the small HSPs (sHSPs) are accumulated in plants to mitigate the adverse effect of HS on plant metabolism (Singh and Grover, 2008; Al-Whaibi, 2011; Lavania et al., 2015a,b).

Both heat and drought stresses are detrimental factors for plant growth and development. A detectable inhibition in plant growth that starts at a value of daily mean temperature is called threshold temperature which varies with the plant species, and genotypes within the species (Wahid et al., 2007; Hemantaranjan et al., 2014). It is important to determine the threshold temperatures of plants that can survive under stress. It is crucial to understand the physiological processes and mechanisms involved in tolerance of plants to HS stress and possible strategies for improving crop thermotolerance. The knowledge of the physiological response of plants to stress is important for tailoring stress-tolerant crop using genetic approaches. However, we know that faba bean (Vicia faba L.) is an important legume crop and their cultivation particularly in arid and semi-arid regions is unsuitable because this crop is not sufficient drought and heat tolerant, as it is very susceptible to moisture and high temperature (Loss and Siddique, 1997). Keeping in view the importance of this crop for human as well as animal, the present experiment was planned to study the effect of HS on different genotypes of faba bean plants. The main objective of this experiment was to determine HS-tolerant and HS-sensitive genotypes on the basis of physio-morphological and biochemical parameters.

2. Materials and methods

To achieve the objective of the present study, ten improved genotypes of V. faba L. were collected from different geographical origins. Seeds of genotypes Zafar 1, Zafar 2 and Shebam1 from the General Organization for Agriculture Research, Yemen, genotypes Makamora and Espan from the local market of Riyadh, and genotypes Giza Blanka, Giza 3, C4, C5 and G853 from Agriculture Research Center, Egypt were collected. The experiments were conducted in a growth chamber (temperature 25 ± 3 °C, relative humidity 50–60%, light 90 μmol of photons m−2 s−1; 6/8-h light/dark cycle). Seeds were grown in pots containing a mixture of sand and peat (1:1). HS treatments were subjected after 60 days of sowing. The treatment details are as follows: (i) control (UN): ambient temperature (25 °C), (ii) mild level temperature (HT1): 6 °C more than ambient temperature and (iii) modest level temperature stress (HT2): 12 °C more than the ambient temperature. Different levels of HS were imposed on plants by placing pots at the requisite temperatures for 48 h at each temperature.

The experimental pots were arranged in a simple randomized design with five replicates per treatment. Before sowing, seeds of all genotypes were surface sterilized with 1% sodium hypochlorite for 10 min, then vigorously rinsed with double distilled water (DDW) and sown in sand and peat-filled pots supplied with Raukura’s nutrient solution (Smith et al., 1983). The salts used to make up the nutrient solution are as follows: Macronutrient stock solution A contained (gL−1) Mg(NO3)2·6H2O, 4.94; Ca(NO3)2·4H2O, 16.78; NH4NO3, 8.48; KNO3, 2.28. Macronutrient stock solution B contained (gL−1) KH2PO4, 2.67; K2HPO4, 1.64; K2SO4, 6.62; Na2SO4, 0.60; NaCl, 0.33. Micronutrient supplement (mgL−1) was constituted of H3BO3, 128.80; CuCl2·2H2O, 4.84; MnCl2·4H2O, 81.10; (NH4)6Mo7O24·4H2O, 0.83; ZnCl2, 23.45; ferric citrate pentahydrate, 809.84. The dilute solution applied to the plants was prepared by mixing 200 mL of each of the macronutrient stock solution with 100 mL of the micronutrient supplement and diluting to 4.5 L with DDW.

2.1. Determination of the morphological characteristics of plants

The sampling of all HS exposed plants was carried out immediately after given HS treatments for morphological analysis. Plants were sampled after 5 d of HS treatments for measurement of growth parameters. The growth performance of faba bean plants was assessed in terms of PH plant−1, FW and DW plant−1 and area leaf−1. The leaf area was measured directly using Leaf Area Meter (Model LI-3050A, LI-COR Inc, Lincon, NE, USA). The area of three leaves (upper, middle, and lower) of each plant of the sample (consisting of five plants) was determined.

2.2. Determination of physio-biochemical characteristics of plants

Leaf RWC (%) was determined using the methods of Gulen and Eris (2003). Leaf disks were taken from the fully expanded and uniform leaves of each of the three plants (replicates) per treatment. First, the FW was recorded, and then samples were placed in a petri dish having distilled water for 4 h. Turgid weight (TW) was then recorded, and the leaf samples were placed in an incubator at 70 °C for 24 h, to determine the dry weight. Leaf RWC% was calculated by

RWC(%)=[(FW-DW)/(turgid weight-dry weight)]×100.

For total chlorophyll (Total Chl) determination, the youngest fully expanded leaves were extracted using 80% acetone, and the absorbance was measured using UV–vis Spectrophotometer (SPEKOL 1500; Analytik Jena AG, Jena, Germany) at 663 nm and 645 nm. Total Chl content was determined by using the established formulae (Arnon, 1949). Pro concentration was determined spectrophotometrically using the ninhydrin method of Bates et al. (1973). Fresh leaf samples were homogenized in 3% sulfosalicylic acid, followed by the addition of 2 mL each of ninhydrin and glacial acetic acid, after which the samples were heated to 100 °C. The mixture was extracted with toluene, and the free toluene was quantified at 520 nm. Malondialdehyde (MDA) content was determined according to the method of Heath and Packer (1968). Leaf samples were weighed, and homogenates containing 10% trichloroacetic acid and 0.65% 2-thiobarbituric acid were heated at 95 °C for 60 min, then cooled to room temperature, and centrifuged at 10,000 g for 10 min. The absorbance of the supernatant was read at 532 nm and 600 nm against a reagent blank. Electrolyte leakage (EL) was used to assess membrane permeability in accordance with Lutts et al. (1995). Samples were washed 3 times with DDW to remove surface contamination, and leaf disks were cut from young leaves and placed in sealed vials containing 10 mL of DDW, followed by incubation on a rotary shaker for 24 h, after which the electrical conductivity of the solution (EC1) was determined. Then, the samples were autoclaved at 120 °C for 20 min, and the electrical conductivity was measured again (EC2) after the solution was cooled to room temperature. The electrolyte leakage was defined as EC1/EC2 × 100 and expressed as percentage. Hydrogen peroxide (H2O2) levels were measured as described by Velikova et al. (2000). Fresh leaf samples were homogenized in 5 mL of 0.1% (w/v) TCA. The homogenate was centrifuged at 12,000 rpm for 15 min and the supernatant was added to 10 mM potassium phosphate buffer (pH 7.0) and 1 M potassium iodide. The absorbance of the supernatant was recorded at 390 nm. The content of H2O2 was calculated by comparison with a standard calibration curve plotted using known concentrations of H2O2.

2.3. Determination of antioxidant enzymes activity

To determine the activities of antioxidant enzymes, a crude enzyme extract was prepared by homogenizing 500 mg of leaf tissue in extraction buffer (0.5% Triton X-100 and 1% polyvinylpyrrolidone in 100 mM potassium phosphate buffer, pH 7.0) using a chilled mortar and pestle. The homogenate was centrifuged at 15,000g for 20 min at 4 °C and the supernatant was used for the enzymatic assays described below. The method of Chance and Maehly (1955) was employed to determine peroxidase (POD) (EC 1.11.1.7) activity. The activity was assayed using 5 mL of enzyme reaction solution containing phosphate buffer (pH 6.8), 50 M pyrogallol, 50 mM H2O2 and 1 mL of the enzyme extract diluted 20 times. The assay mixture was incubated for 5 min at 25 °C, and the reaction was terminated by the addition of 0.5 mL of 5% (v/v) H2SO4. Purpurogallin production was measured spectrophotometrically at 420 nm. One unit of POD activity was considered the amount of purpurogallin formed per milligram of protein per minute. The method of Aebi (1984) was used to measure catalase (CAT) (EC 1.11.1.6) activity. The decomposition of H2O2 was measured as the decrease in absorbance at 240 nm. In this assay, 50 mM phosphate buffer (pH 7.8) and 10 mM H2O2 were used in the reaction solution. Activity of superoxide dismutase (SOD) (EC 1.15.1.1) was determined based on the inhibition of nitroblue tetrazolium (NBT) photoreduction according to the method of Giannopolitis and Ries (1977). The reaction solution (3 mL) contained 50 mM NBT, 1.3 mM riboflavin, 13 mM methionine, 75 μM ethylenediamine tetraacetic acid (EDTA), 50 mM phosphate buffer (pH 7.8), and 20–50 mL of enzyme extract. The reaction solution was irradiated under fluorescent light at 75 μM m−2 s−1 for 15 min. The absorbance at 560 nm was read against a blank (nonirradiated reaction solution). One unit of SOD activity was defined as the amount of enzyme that inhibited 50% of NBT photoreduction.

2.4. Statistical analysis

The data were expressed as the mean ± standard error and were analyzed statistically using IBM SPSS Ver.22 statistical software (IBM Corporation and Others, Armonk, NY, USA). The means were compared statistically using Duncan’s multiple-range test at the level of p < 0.05.

3. Results

3.1. Heat stress experiment

In the present experiment, the performance was assessed in terms of PH plant−1, shoot FW and DW plant−1, area leaf−1, RWC, Pro content, Total Chl EL and content of MDA and H2O2, and activities of CAT, POD and SOD. The effect of HS treatments on these studied parameters of genotypes was found to be significant (Tables 1–4).

Table 1.

Effect of heat stress on growth performance of faba bean genotypes.

Treatments Genotypes
Zafar 1 Zafar 2 Giza Blanka Espan Makamora Shebam 1 Giza 3 C4 C5 G853
Plant height (cm) plant−1
Control 59.00 ± 0.58fg 56.00 ± 0.58hi 61.00 ± 0.58ef 36.67 ± 0.88n 48.00 ± 0.58k 48.00 ± 0.58k 59.00 ± 0.58fg 79.00 ± 0.58c 116.33 ± 0.88a 55.00 ± 0.58i
HT1 56.00 ± 0.58hi 43.67 ± 0.88l 58.67 ± 0.88g 25.67 ± 0.88r 31.33 ± 0.33pq 31.33 ± 0.33pq 41.33 ± 0.88m 70.33 ± 0.33d 86.67 ± 0.88b 52.33 ± 0.88j
HT2 43.33 ± 0.88lm 30.67 ± 0.88q 33.67 ± 0.88o 13.67 ± 0.33t 21.67 ± 0.88s 21.67 ± 0.88s 33.33 ± 0.88op 58.00 ± 0.58gh 62.33 ± 0.88e 45.00 ± 0.58l



Shoot FW (g) plant−1
Control 5.10 ± 0.12cde 5.63 ± 0.48cd 3.63 ± 0.18fg 2.40 ± 0.06ij 5.13 ± 0.03cde 5.13 ± 0.03cde 5.00 ± 0.06de 6.00 ± 0.31c 9.20 ± 0.06a 4.40 ± 0.21ef
HT1 3.53 ± 0.82fgh 2.97 ± 0.87ghi 5.17 ± 0.15cde 2.20 ± 0.06ij 4.73 ± 0.12de 4.73 ± 0.12de 4.47 ± 0.26ef 4.87 ± 0.12de 7.17 ± 0.15b 2.53 ± 0.23ij
HT2 2.43 ± 0.75ij 2.63 ± 0.09hij 3.53 ± 0.27fgh 0.50 ± 0.06l 0.73 ± 0.09l 0.90 ± 0.25kl 3.50 ± 0.10fgh 2.70 ± 0.06ghij 4.17 ± 0.12ef 1.77 ± 0.09jk



Shoot DW (g) plant−1
Control 0.63 ± 0.06abcdef 0.56 ± 0.04bcdefgh 0.70 ± 0.23abc 0.40 ± 0.01ghij 0.59 ± 0.02abcdefg 0.59 ± 0.02abcdefg 0.57 ± 0.02bcdefgh 0.76 ± 0.16ab 0.81 ± 0.01a 0.73 ± 0.07ab
HT1 0.40 ± 0.12ghij 0.37 ± 0.07ghij 0.67 ± 0.06abcde 0.29 ± 0.01ij 0.46 ± 0.07defghij 0.46 ± 0.07defghij 0.45 ± 0.06efghij 0.46 ± 0.02defghij 0.68 ± 0.02ab- 0.50 ± 0.01cdefgh
HT2 0.23 ± 0.07j 0.25 ± 0.01j 0.41 ± 0.03fghij 0.01 ± 0.00k 0.24 ± 0.05j 0.24 ± 0.05j 0.28 ± 0.03ij 0.30 ± 0.01ij 0.35 ± 0.01hij 0.45 ± 0.05efghij



Area (cm2) leaf−1
Control 13.34 ± 0.69ghi 7.63 ± 0.15no 12.17 ± 0.58ijk 8.53 ± 0.34mn 14.79 ± 0.41fg 14.79 ± 0.41fg 12.59 ± 0.47hij 20.00 ± 0.58c 31.80 ± 0.75a 15.60 ± 0.74ef
HT1 11.82 ± 0.32ijk 6.56 ± 0.53opq 9.77 ± 0.79lm 7.07 ± 0.09nop 11.38 ± 0.35jkl 11.38 ± 0.35jkl 9.78 ± 0.53lm 17.00 ± 0.58de 23.37 ± 0.32b 13.91 ± 0.36gh
HT2 7.27 ± 0.92nop 5.03 ± 0.93qr 7.41 ± 0.89no 4.10 ± 0.32r 7.00 ± 0.47nop 7.00 ± 0.47nop 7.61 ± 0.26no 10.63 ± 0.55kl 17.50 ± 0.41d 5.65 ± 0.42pqr
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Means followed by a similar letter within a column for each parameter are not significantly different at the 0.05 level of probability by Duncan’s multiple-range test.

Table 2.

Effect of heat stress on leaf relative water content (RWC), proline (Pro) content and total Chlorophyll (Total Chl) content of faba bean genotypes.

Treatments Genotypes
Zafar 1 Zafar 2 Giza Blanka Espan Makamora Shebam 1 Giza 3 C4 C5 G853
RWC%
Control 69.14 ± 0.10e 66.92 ± 0.33f 83.17 ± 0.66a 62.71 ± 0.55i 73.03 ± 0.33c 73.03 ± 0.33c 78.15 ± 0.28b 76.89 ± 0.44b 73.23 ± 0.29c 71.05 ± 0.69d
HT1 65.09 ± 0.38gh 64.89 ± 0.50h 66.26 ± 0.37fgh 53.89 ± 0.05j 66.14 ± 0.89fgh 65.20 ± 0.50gh 71.24 ± 0.58d 74.03 ± 0.13c 71.24 ± 0.58d 66.51 ± 0.59fg
HT2 44.39 ± 0.30m 34.48 ± 0.46p 41.46 ± 0.73n 25.82 ± 0.65q 45.26 ± 0.45m 45.26 ± 0.45m 52.09 ± 0.14k 38.23 ± 0.94o 49.19 ± 0.11l 50.87 ± 0.26k



Pro (μg−1 FW)
Control 1.19 ± 0.04k 0.93 ± 0.01l 0.90 ± 0.06l 1.30 ± 0.03k 1.34 ± 0.05k 1.34 ± 0.05k 1.26 ± 0.02k 1.63 ± 0.30j 1.25 ± 0.02k 3.06 ± 0.04d
HT1 1.93 ± 0.03i 1.90 ± 0.03i 1.17 ± 0.03k 2.86 ± 0.02de 2.03 ± 0.05hi 2.03 ± 0.05hi 2.33 ± 0.07g 2.40 ± 0.04g 2.77 ± 0.05ef 2.27 ± 0.03gh
HT2 2.54 ± 0.03fg 2.93 ± 0.02de 3.40 ± 0.07c 1.44 ± 0.03jk 2.35 ± 0.01g 2.35 ± 0.01g 2.68 ± 0.05ef 4.73 ± 0.08b 7.44 ± 0.28a 1.62 ± 0.03j



Total Chl (mg g−1 FW)
Control 40.07 ± 0.74cde 40.47 ± 0.53cde 40.87 ± 0.59cd 35.00 ± 0.58g 38.77 ± 0.67ef 38.77 ± 0.67ef 37.67 ± 0.88f 41.97 ± 0.24bc 48.10 ± 0.76a 41.50 ± 0.42bcd
HT1 38.00 ± 0.85f 35.60 ± 0.60g 35.40 ± 0.23g 27.00 ± 0.58j 38.00 ± 0.58f 38.00 ± 0.58f 38.00 ± 0.06f 39.67 ± 0.39def 42.80 ± 0.23b 35.37 ± 0.35g
HT2 26.83 ± 0.44j 32.00 ± 0.58h 27.80 ± 0.20j 18.67 ± 0.88k 31.03 ± 0.98hi 31.03 ± 0.98hi 30.70 ± 0.55hi 29.73 ± 0.37i 32.23 ± 0.62h 29.90 ± 0.90i
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Means followed by a similar letter within a column for each parameter are not significantly different at the 0.05 level of probability by Duncan’s multiple-range test.

Table 3.

Effect of heat stress on electrolyte leakage (EL), malondialdehyde (MDA) content, and hydrogen peroxide (H2O2) content of faba bean genotypes.

Treatments Genotypes
Zafar 1 Zafar 2 Giza Blanka Espan Makamora Shebam 1 Giza 3 C4 C5 G853
Electrolyte leakage (%)
Control 34.33 ± 2.96n 40.67 ± 2.73lmn 39.67 ± 3.28lmn 38.33 ± 3.53mn 42.67 ± 5.36klmn 47.33 ± 2.40jklm 37.00 ± 1.53n 40.33 ± 1.45lmn 40.67 ± 4.26lmn 50.67 ± 4.70hijk
HT1 49.00 ± 1.73ijkl 53.00 ± 4.16ghij 49.33 ± 2.33ijkl 57.33 ± 4.26fghi 64.00 ± 3.61cdef 61.67 ± 3.18defg 54.33 ± 2.73ghij 49.33 ± 2.96ijkl 59.67 ± 2.60efgh 64.33 ± 3.48cdef
HT2 64.33 ± 2.91cdef 67.00 ± 1.15bcdef 69.00 ± 0.58abcde 76.00 ± 1.53ab 76.33 ± 2.19ab 72.33 ± 1.20abc 67.67 ± 1.33bcde 70.33 ± 0.88abcd 57.67 ± 5.04fghi 77.67 ± 1.45a



MDA (nmol g−1 FW)
Control 24.00 ± 3.06p 30.67 ± 2.73mnop 29.67 ± 3.28nop 28.33 ± 3.53op 32.67 ± 5.36lmno 37.33 ± 2.40klmno 27.00 ± 1.53p 30.33 ± 1.45mnop 30.67 ± 4.26mnop 40.67 ± 4.70ijkl
HT1 39.00 ± 1.73jklmn 43.00 ± 4.16hijk 39.33 ± 2.33jklm 47.33 ± 4.26ghij 54.00 ± 3.61defg 51.67 ± 3.18efgh 44.33 ± 2.73hijk 39.33 ± 2.96jklm 49.67 ± 2.60fghi 55.33 ± 3.71cdefg
HT2 60.33 ± 0.88abcde 55.33 ± 1.86cdefg 58.33 ± 1.20abcdef 64.33 ± 2.60abc 67.00 ± 1.53ab 62.33 ± 1.20abcd 57.67 ± 1.33bcdef 54.33 ± 2.91defg 51.00 ± 2.08efgh 67.67 ± 1.45a



H2O2 concentration (μmol g−1 leaf FW)
Control 19.67 ± 1.76hijk 21.00 ± 1.53hij 17.67 ± 1.20ijk 20.33 ± 1.45hijk 17.00 ± 1.53jk 21.33 ± 1.86hij 22.00 ± 1.53hi 21.00 ± 1.53hij 15.67 ± 1.20k 20.33 ± 1.86hijk
HT1 27.67 ± 1.45efg 27.00 ± 0.58efg 27.33 ± 1.76efg 27.67 ± 1.45efg 23.00 ± 2.08gh 29.67 ± 1.45def 31.33 ± 1.20cde 26.33 ± 0.88fg 20.33 ± 0.88hijk 30.33 ± 2.73cdef
HT2 34.67 ± 0.88bc 33.67 ± 0.88bcd 35.00 ± 0.58bc 37.67 ± 0.88b 31.33 ± 0.88cde 36.00 ± 0.58b 37.00 ± 0.58b 30.33 ± 2.19cdef 27.00 ± 2.08efg 43.67 ± 0.88a
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Means followed by a similar letter within a column for each parameter are not significantly different at the 0.05 level of probability by Duncan’s multiple-range test.

Table 4.

Effect of heat stress on activities of catalase (CAT), peroxidase (POD) and superoxide dismutase (SOD) in faba bean genotypes.

Treatments Genotypes
Zafar 1 Zafar 2 Giza Blanka Espan Makamora Shebam 1 Giza 3 C4 C5 G853
CAT activity (units mg−1 protein min−1)
Control 156.33 ± 2.19i 142.67 ± 1.45jk 143.00 ± 1.15jk 146.67 ± 1.86j 165.00 ± 1.73hi 136.00 ± 2.31 k 139.33 ± 0.88jk 171.67 ± 3.71gh 180.00 ± 3.61 fg 191.00 ± 2.08e
T1 at 32 °C 185.00 ± 2.31ef 186.33 ± 2.73ef 158.67 ± 0.88i 158.67 ± 2.03i 177.33 ± 2.19 fg 159.00 ± 4.36i 183.67 ± 2.60ef 206.33 ± 2.73 cd 224.00 ± 2.65b 209.00 ± 3.21 cd
T2 at 38 °C 223.67 ± 2.73b 201.67 ± 4.91d 185.33 ± 2.03ef 179.67 ± 0.33 fg 191.00 ± 3.79e 172.00 ± 1.73gh 213.67 ± 6.44c 237.33 ± 6.77a 244.33 ± 2.33a 236.33 ± 2.40a



POD activity (unit min−1 g−1 FW)
Control 10.20 ± 0.80 m 20.33 ± 0.32 h 13.63 ± 0.18kl 16.27 ± 0.27jk 19.83 ± 0.15hi 11.27 ± 0.27 lm 16.43 ± 0.24j 17.30 ± 0.76ij 22.50 ± 1.22fgh 13.70 ± 0.12kl
T1 at 32 °C 13.77 ± 1.29kl 24.37 ± 0.77cdefg 17.23 ± 1.29ij 20.10 ± 0.62 h 24.77 ± 1.07cdef 15.70 ± 1.60jk 21.87 ± 1.17gh 20.50 ± 0.23 h 26.17 ± 0.84bcde 17.50 ± 1.22ij
T2 at 38 °C 21.70 ± 0.61gh 26.27 ± 0.44bcd 23.90 ± 0.64defg 23.50 ± 0.91efg 27.57 ± 0.64ab 19.83 ± 0.71hi 25.93 ± 0.61 bcde 26.63 ± 0.68abc 29.00 ± 0.67a 23.67 ± 1.61defg



SOD activity (units mg−1 protein min−1)
Control 11.33 ± 1.86lmn 13.00 ± 1.53klm 12.33 ± 0.88klmn 8.67 ± 2.19n 9.33 ± 1.45mn 8.33 ± 0.88n 9.67 ± 0.67mn 9.33 ± 1.86mn 11.33 ± 0.88lmn 15.00 ± 1.53hijkl
T1 at 32 °C 17.33 ± 1.45fghij 18.67 ± 1.45defgh 18.33 ± 1.20efghi 16.33 ± 1.20ghijk 15.00 ± 2.08hijkl 12.00 ± 1.53lmn 14.00 ± 1.15jkl 14.33 ± 0.88ijkl 17.33 ± 1.20fghij 20.33 ± 1.76cdefg
T2 at 38 °C 24.00 ± 1.53bc 24.33 ± 0.33abc 25.00 ± 0.58ab 22.67 ± 0.88bcd 21.67 ± 0.88bcde 18.67 ± 0.33defgh 21.00 ± 0.58bcdef 18.67 ± 0.88defgh 24.00 ± 0.58bc 28.00 ± 0.58a
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Means followed by a similar letter within a column for each parameter are not significantly different at the 0.05 level of probability by Duncan’s multiple-range test.

The data revealed that the growth attributes of all genotypes were affected significantly depending on the temperature (Table 1). In all cultivars, PH, Shoot FW and DW, leaf area decreased gradually from the control (ambient temperature; 25 °C) to the modest temperature (37 °C). Off all the genotypes, ‘C5’ and ‘C4’ had the highest PH, Shoot FW and DW while genotype ‘Espan’ had the lowest at HS treatments. However, among all studied genotypes, ‘C5’ gave the maximum values for almost all parameters. Similarly, RWC, Pro accumulation, Total Chl content, EL, and MDA content were measured in all genotypes at different HS treatments (Tables 2 and 3). The effect of treatments on these parameters was found to be significant for all genotypes. Leaf RWC decreased with increasing temperature. A similar trend was observed in all cultivars. However, among the genotypes ‘C5’ and ‘Giza 3’ gave maximum values for RWC under HS. The accumulation of Pro increased with increasing levels of HS. The highest accumulation of Pro was observed in genotype ‘C5’ as compared to other genotypes at modest HS while content of Pro was higher in ‘Giza Blanka’ than all cultivars at ambient temperature (control). Total Chl content was found to be temperature dependent in all genotypes. Under HS, the lowest reduction of Total Chl was observed in genotypes ‘C5’ and ‘Zafar-2’ while the highest inhibition was found in genotype ‘Espan’. EL, and MDA and H2O2 content were increased with increasing levels of temperature (Table 3). Also, genotypes ‘C5’ showed the lowest EL, and MDA and H2O2 content in comparison to the remaining genotypes under HS. However, cultivar ‘Espan’ exhibited the highest EL, and MDA and H2O2 content.

Activities of antioxidant enzymes (CAT, POD, and SOD) were significantly increased with increasing levels of HS in plants of all genotypes (Table 4). Under severe HS conditions, genotypes ‘C5’ and ‘C4’ showed similar CAT activity. Also, under HS, the highest enzyme activity was noted in genotype ‘C5’ and ‘Zafar 1’ for SOD. However, genotype ‘C5’ gave the maximum value for POD enzyme activity. Moreover, the magnitude of increase in these enzymes activities in genotype ‘C5’ was higher than other genotypes of faba bean under HS. Genotype ‘Espan’ exhibited the lowest enzymes activities under HS.

4. Discussion

4.1. Heat stress treatments

V. faba genotypes responded comprehensively in terms of growth and physiological characteristics and differential resistance to HS (Table 1). The HS exhibited a negative effect on all studied faba bean genotypes. The observed decrease in growth parameters (PH, Shoot FW and DW, leaf area) with increasing levels of temperature over the control may be due to the loss of turgidity and RWC (Table 2) (Kesici et al., 2013). The high level of temperature stress might be altered cell division and cell elongation resulted in reduced leaf area in all genotypes (Table 1). Rahman (2004) and Ahamed et al. (2010) in wheat, Al-busaidi et al. (2012) in Jatropha curcas reported that high temperature causes a significant negative influence on the plant growth. Among the studied genotypes, ‘C5’ responded better by giving maximum values for these characteristics, and found to be tolerant to HS, whereas ‘Espan’ found to be sensitive to HS. Leaf RWC has been established as an indicator of state of water balance of plants essentially in terms of the physiological consequences of cellular water deficit. In the present experiment, leaf RWC of all genotypes decreased significantly depending on temperature (Table 2). In all genotypes, RWC declined linearly from ambient to modest temperature. Among the cultivars, ‘Giza-3’ and ‘C5’ exhibited the highest RWC while ‘Espan’ had the lowest RWC under HS. This finding coincides with earlier studies of Kesici et al. (2013). Therefore, it was revealed that among the genotypes differed leaf RWC could indicate a corresponding difference in leaf hydration, leaf water deficit and physiological water status in plants. Pro accumulation is an important metabolic parameter that has a significant effect on cellular redox potential thereby lowering the generation of free radicals that is associated with the tolerance of plants to stress (Alia et al., 1993; Hare and Cress, 1997; Siddiqui et al., 2009). In this study, Pro accumulation was recorded to be the highest in stressed plants as compared to the control. The maximum accumulation of Pro was found in genotypes ‘C5’ and minimum Pro accumulation was found in genotype ‘Espan’ (Table 2). Bohnert and Jensen (1996) reported that organic solutes at higher concentrations improved enzyme activity and maintained the intercellular biochemistry. We infer that accumulation of Pro might have a role in tolerance of genotype ‘C5’ to HS.

Total Chl is an important biomolecule in plants for photosynthesis. In all genotypes, Total Chl synthesis was impaired with increasing temperature (Table 2). The highest content of Total Chl was recorded in genotype ‘C5’ and ‘Zafar 2’. The change in Total Chl content in plant is a typical response of stress. Under stress, a decrease in Total Chl biosynthesis in faba bean cultivars may be due to inhibition of photosynthetic electron transport chain (Mohanty et al., 1989) and the enzymes of Chl biosynthesis, such as δ-aminolevulinic acid (ALA) synthase, ALA dehydratase, and porphobilinogenase (Tewari and Tripathy, 1998; Shalygo et al., 1999). Also, high temperature alters the anatomical structure in leaves, such as shape of chloroplasts, swelling of stromal lamellae, clumpy vacuoles that change the structural organization of thylakoids and form antenna-depleted PS II, and resulted in reduced photosynthetic and respiratory activities (Zhang et al., 2005; Lipiec et al., 2013). Therefore, the amount of Chl content strongly depends on the species’ physiological responses and their ability to tolerate stress. Under different environmental stresses, EL, and content of MDA and H2O2 in plants play a key role as an indicator for oxidative damage (Siddiqui et al., 2013, 2014). In all plants of genotypes, EL, and content of MDA and H2O2 increased with increasing levels of temperature (Table 3). However, the lowest EL, and content of MDA and H2O2 was reported in genotype ‘C5’. This indicates that cultivar ‘C5’ was more tolerant to HS than these nine cultivars. The lowest level of EL, and content of MDA and H2O2 in genotype ‘C5’ might be due to the highest accumulation of Pro (Table 2) that acts as an antioxidant and reduces the generation of free radicals and lipid peroxidation (Siddiqui et al., 2009; Alia et al., 1993). It is well established that antioxidant enzymes are extremely important as a part of defense mechanisms in plants, through which plants can endure under unfavourable environmental conditions by detoxifying reactive oxygen species (ROS), as we know that ROS causes harmful effect on plants by reacting with a large variety of biomolecules, such as DNA, protein and carbohydrates (Siddiqui et al., 2013). In the present experiment, activities of antioxidant enzymes (POD, CAT and SOD) in plants of all genotypes were substantially increased with increasing temperature (Table 4). However, under HS, the highest enzyme activities were noted in genotypes ‘C5’ and ‘C4’ for CAT, only ‘C5’ for POD, and ‘C5’ and Zafar-1 for SOD. Overall, genotypes ‘C5’ and ‘Espan’ exhibited the highest and lowest enzyme activities under HS, respectively. The highest activity of these enzymes might help genotype ‘C5’ to be more tolerant than the others.

5. Conclusion

From the findings of the present studies, we conclude that genotype ‘C5’ has a better ability to tolerate high temperature, while genotype ‘Espan’ is relatively more sensitive to HS than 9 cultivars of V. faba. Under HS, genotypes of faba bean exhibited genotypic variations due their differential responses for morpho-physiological and biochemical characteristics. All morphological, physiological and biochemical characteristics of 10 genotypes of faba bean were reduced under HS. We observed that genotype ‘C5’ was most resistant to HS, and it has a better ability to retain more RWC and accumulation of Pro. Also, genotype ‘C5’ was relatively more efficient to reduce oxidative damage by increasing activities of CAT, POD and SOD. For further study, theses genotypes can be used to find the molecular mechanism(s) involved in tolerance of faba bean plants to HS. These genotypes can be used for further studies to uncover relation of pollen heat shock proteins with pollen viability and to show whether lack/inadequate expression of specific heat shock proteins has any role in oxidative damage to faba bean plants as well as pollens.

Conflict of interest

The authors declare that they have no conflict of interest.

Acknowledgement

This project was supported by NSTIP strategic technologies program number (11-BIO1922-02) in the Kingdom of Saudi Arabia.

Footnotes

Peer review under responsibility of King Saud University.

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