Screening of drought-tolerant rice through morpho-physiological and biochemical approaches
Shamsun Nahara, Lingaraj Sahoob, Bhaben Tantia, *
aDepartment of Botany, Gauhati University, Guwahati 781014, Assam, India
bDepartment of Biosciences and Bioengineering, Indian Institute of Technology Guwahati, Guwahati 781039, Assam, India
*Corresponding author: Email: [email protected]
Drought is a major problem in rice for production and yield stability in rainfed ecosystems. In an effort to identify promising rice cultivars having tolerance against drought, the present study was aimed at investigating effect of low water potential generated by polyethylene glycol on growth. Seeds of twenty one traditional rice cultivars along with ‘Sahbhagi Dhan’ (tolerant) and ‘IR64’ (sensitive) were subjected to drought stress. Drought was imposed in 1 week old seedlings by 15% PEG-6000 in Yoshida medium for 7 days followed by 20% PEG-6000 for another 7 days until the drought symptoms appeared. All the experiments were conducted in randomized block design with three replicates. Germination percentage, root length, shoot length, root fresh and dry weight, shoot fresh and dry weight, chlorophyll content and relative water content (RWC) were evaluated after stress treatment. On the basis of Standard Evaluation Score, 8 rice varieties showing high drought tolerability were finally selected for further biochemical analyses. Proline content, lipid peroxidation level and hydrogen peroxide concentration in shoots and roots were investigated. Increase in proline content and decrease in hydrogen peroxide and lipid peroxidation implied its protective role in tolerant rice cultivars against drought stress. To identify the drought tolerant rice cultivars, a thorough understanding of the various mechanisms that govern the yield of rice under drought condition is a prerequisite.
Keywords: water stress, rice landraces, polyethylene glycol, drought tolerant and sensitive, morpho-physiological features
Water availability is the most important factor among the abiotic factors that have shaped and continue shaping plant evolution in general and rice crop in particular (Bray et al., 2000). Water is an important factor in agricultural and food production yet it is a highly limited resource (Wanget al., 2012). Drought affects the yield, inhibit growth and development, reduce production, and in severe conditions, result in death. Water deficit stress is a severe threat to sustainable rice cultivation as it causes extensive loss to productivity.
Rice is an important staple food for more than half of the world’s population and comprising 50% to 80% of their daily calorie intake (Khush, 2005). Of all the cereals, rice (Oryza sativa) is most susceptible to damage from water deficit (Lafitte and Bennet, 2003). Water deficit at early vegetative growth intensely affects the establishment of rice crops. Among different symptoms, leaf rolling is one of the acclimation responses of rice and is used as a criterion for scoring drought sensitivity. Rainfed upland rice is mainly dependent on rainfall for growth and grain yield and often experiences periods of water deficiency. There are several reports that rice is sensitive to water scarcity from 20 days before to 10 days after heading (Matsushima, 1962). Reduction of yield due to water deficit at flowering stage is mainly caused by reduction in number of filled spikelets per panicle without substantial decrease in spikelet number per panicle (O’Toole and Namuco, 1983). A given level of drought, at the vegetative stage, can cause a moderate reduction in yield but drought can entirely eliminate yield if it coincides with pollen meiosis or fertilization (O’Toole, 1982). With limited water resources, future increases in rice production will largely rely on rainfed production. Upland rice, which relies strictly on rainfall as a source of water, is often exposed to drought stress and has developed drought-resistant traits (Yadav et al., 1997).
Water deficit results in stomatal closure, which limits carbon dioxide fixation and reduces NADP+ regeneration (Satoh and Murata, 1998) that causes increasing reactive oxygen species (ROS) viz., hydrogen peroxide, superoxide, singlet oxygen and hydroxyl radicals through leakage of electrons to molecular oxygen during electron transport activities of chloroplasts, mitochondria and plasma membranes (Asada, 1994). In stress conditions, plants stimulate production of ROS that causes peroxidation of lipids, proteins denaturation, DNA mutation and cellular oxidative damages (Sgherri et al., 1996; Smirnoff, 1993). Membrane lipids peroxidation and oxidation of –SH groups of proteins have been considered as an index for oxidative stress (Boominathan and Doran, 2002). Plant adopts a protection mechanism against the detrimental effects of ROS by a complex antioxidant system comprising of both non-enzymatic as well as enzymatic antioxidants (Noctor and Foyer, 1998; Sarma et al., 2016; Nahar et al., 2016). To scavenge ROS, plants have evolved specific defence tactics involving both enzymatic and non-enzymatic antioxidant mechanisms. Rapid accumulation of free proline is a typical response to drought stress. Under drought stress, most of the plants accumulate high amounts of proline, in some cases several times the sum of all the other amino acids. Comparison of antioxidant defence mechanisms, lipid peroxidation, and proline contents of rice cultivars differing in drought tolerance may be helpful in developing a better understanding of tolerance mechanisms to drought stress (Fischer and Maurer, 1978; Lahkar and Tanti, 2017).
Polyethylene glycol (PEG) have been extensively used to simulate drought stress effect in plants (Murillo-Amador et al., 2002). It has been reported that PEG could be used to modify the osmotic potential of nutrient solution culture and thus induced plant water deficit in a relatively controlled manner, appropriate to experimental protocols (Lagerwerff et al., 1961). PEG is a widely used chemical compound and maintains lower osmotic potential at a comparatively lower temperature under hydroponic culture. PEG-treated hydroponic conditions create negative osmotic potential, which is compared with moisture deficit stress. Application of polyethylene glycol in a hydroponic solution causes osmotic stress, which results in changes in the water status of the tissues and a decrease of plant growth and biomass production (Robin et al., 2015).
Drought is a major abiotic stress that adversely affects the rice growth, mostly in the rainfed ecosystem that ultimately affects the biomass production and yield. Understanding the morphological, biochemical and molecular mechanisms involved in rice against drought is utmost necessary for rice breeders to improve the rice for drought tolerant/resistance varieties for future green revolution. Keeping in view, the present study was emphasised to screen the drought tolerance ability of few traditional rice cultivars of Assam, India to be used in further breeding programme.
2. Materials and methods
2.1. Collection of traditional rice samples
To investigate the effect of drought stress on the traditional rice in Assam, 21 rice cultivars were collected during 2013 – 2015 from six different agro-climatic zones (Fig. 1). ‘Sahbhagi Dhan’, a drought resistant variety (released by Central Rainfed Upland Rice Research Station, Hazaribagh, Jharkhand in October 2010) and ‘IR64’, a well known drought sensitive variety, used throughout the study as positive and negative control were collected from Regional Rainfed Lowland Rice Research Station, Gerua, Assam, (India).
Sample collection areas
Fig. 1. Map showing sample collection sites of traditional rice cultivars in Assam, India; the red symbols in the map represent the collections sites. (Map courtesy: www.mapsofindia.com)
The vernacular names along with laboratory assigned code of the collected rice varieties with respect to six different agroclimatc zones are mentioned viz., (i) North Bank Plains – Prosad Bhog (SN04), Dubori Bao (SN10), Sodiya Bao (SN09); (ii) Upper Brahmaputra Valley – Kola Joha (SN05), Helash Bora (SN06), Kola Kon Joha (SN07), Saliohoi Bao (SN08), Ronga Bao (SN11), Kola Amona (SN12), Deuri Lai (SN14), Makhan Bora (SN19), Ronga Bora (SN20); Central Brahmaputra Valley – Jahingia (SN17), Chokuwa (SN18), Kola Bao (SN13), Kola Ahu (SN15); Lower Brahmaputra Valley – IR64 (SN01), Sahbhagi Dhan (SN02), Bora (SN03); Barak Valley – Kola Sali (SN16) and Hilly areas – Sok-bonglong (SN11), Amo (SN22), Halyan Amo (SN23).
Collected rice samples were kept at 4°C for 3-4 months for regular uses and fresh new seeds were collected every year until the end of the experiments (Fig. 2).
Fig 2. Collected rice cultivars. A. IR64 (SN01), B. Sahbhagi Dhan (SN02), C. Bora (SN03), D. Prosad Bhog (SN04), E. Kola Joha (SN05), F. Helash Bora (SN06), G. Kola Kon Joha (SN07), H. Salihoi Bao (SN08), I. Sodiya Bao (SN09), J. Dubori Bao (SN10), K. Ronga Bao (SN11), L. Kola Amona (SN12), M. Kola Bao (SN13), N. Deuri Lai (SN14), O. Kola Ahu (SN15), P. Kolasali (SN16), Q. Jahingia (SN17), R. Chokuwa (SN18), S. Makhan Bora (SN19), T. Ronga Bora (SN20), U. Sok-bonglong (SN11), V. Amo (SN22), W. Halyan Amo (SN23)2.3. Growth conditions and drought induction
The rice seeds were surface sterilized with 0.1% mercuric chloride (HgCl2) before germination. Germinated seeds were initially allowed to grow in Yoshida solution with pH 5.8 (Yoshida et al., 1976) under controlled conditions (light/dark regime of 16/8 h at 25/20°C, relative humidity of 60-70%, photosynthetic photon flux density of 52 µmol m-2s-1) for 7 days, then drought was imposed by 15% PEG-6000 in Yoshida solution for 7 days followed by 20% for another 7 days.
After drought screening, the drought tolerant rice cultivars were selected for further biochemical analyses. After drought treatment, rice cultivars were again allowed to grow in fresh Yoshida medium for recovery.
2.4. Morpho-physiological analyses
The morpho-physiological parameters included germination index, root and shoot length, root and shoot fresh and dry weight, relative water content and chlorophyll content. All experiments were conducted for 3 times for authentication.
Germination indexes (G.I.) were counted by using the formula described in AOSA, (1983). Shoot relative water content was calculated by the method used by Smart and Bingham, (1974).
Chlorophyll a, b and total chlorophyll was determined by using the method of Kapoor and Pande (2015). Fresh leaves of 300 mg were crushed in mortar and pestle with 5 ml of 80% acetone. The absorbance was taken at 663 nm and 645 nm against 80% acetone as reference.
The standard evaluating scores were calculated which was scored according to standard evaluation system (IRRI, 1996) and scoring was done following the methods of Gregorio et al., (1997).
2.5. Biochemical analyses
For determination of H2O2, 0.2 g of the drought induced leaf and root tissue was homogenized in 5% trichloroacetic acid (TCA), centrifuged at 17,000 ×g at 0 °C for 10 min. The absorbance was then recorded at 480 nm with the reaction mixture containing 1.6 ml of the extract, 0.4 ml TCA (50%), 0.4 ml ferrous ammonium sulphate and 0.2 ml potassium thiocyanate and calculated according to Sagisaka (1976).
For lipid peroxidation, 0.2 g of fresh tissues was homogenized with 5 ml of 0.25 % thiobarbituric acid (TBA) containing 10% TCA. The homogenate was boiled for 30 min at 95 °C, centrifuged at 10,000 ×g for 10 min. Absorbance values were recorded at 532 nm and values corresponding to non-specific absorption at 600 nm were subtracted. The malondialdehyde (MDA) content was calculated with the formula of Heath and Packer (1968).
Proline estimation was performed following the method by Bates et al., (1973), where 0.5 g of tissues was homogenized with 5 ml of sulfosalicylic acid (3%); 2 ml of homogenate was filtered and incubated with 2 ml glacial acetic acid and 2 ml ninhydrin reagent at a ratio of 1:1:1 in boiling water bath for 30 min. After cooling, 4 ml toluene was added to the reaction mixture, mixed vigorously and the absorbance measured at 520 nm. The standard graph for proline was made and the proline content was calculated.
2.6. Statistical analyses
Statistical analysis was carried out using ANOVA and there were significant differences between treatments. Duncan’s multiple range statistical analysis had been carried out for noted observations using SPSS (Version 19).
3. 1. Effect of drought on morphological changes
3.1.1. Germination index (G.I.)
Drought treatment showed adverse effect on seed germination (Fig. 3).In all the varieties, G.I. decreased in treated condition due to water stress. The result showed that highest relative germination index was observed in Jahingia (SN17), Ronga Bora (SN20) and Helash Bora (SN06). Under drought stress, Jahingia showed highest germination index (93.95%). Germination index was considerably reduced in most of the varieties under stress condition as compared to control, where least G.I. was measured in Kola Sali (SN16) (26.16%) and Deuri Lai (41.11%) as compared with controls.
Sahbhagi Dhan (SN02), a well recognized drought tolerant variety used as positive control revealed 91.52% relative G.I. In contrast, IR64 (SN01), a drought sensitive rice showed relative germination index as 54.16% only. Fig. 3 indicates that drought poses the most significant effect on germination index with p ? 0.05.
Relative G.I. (%)
Fig. 3. Effect of drought on relative germination index among the 21 rice cultivars along with the controls (data presented as mean ± SE; n = 3); The analysis of variance (ANOVA) was applied to examine the statistical significance; the low p-values (< 0.05) indicated respectively by the rice cultivars as compared with controls is significant and well fitted. The lack of fit for both models with high p-value (> 0.05) further emphasizes that the models can be used to predict the responses. The high value of R2 (0.945) and adj-R2 (0.919) of the yield models further signify that the response and independent variables were well correlated.
3.1.2. Shoot and root growth on drought
Here growth of the rice growing in Yoshida solution along with 15% and 20% PEG-6000 was measured in terms of shoot and root length and found that the growth of most of the cultivars were arrested by imposed drought (Fig. 4).
Fig. 4. Different stages of growth in the in-vitro hydroponic culture conditions, A, seed in germination; B, rice in hydroponic culture (before treatment); C, after treatment; D, growth measurement
Among all the rice varieties shoot length and root length were measured in both controlled and treated conditions (Fig. 5.A-B). Maximum relative shoot length was observed in SN03 (Bora) (93.29%) and minimum was recorded in (Kola Ahu) SN15 (53.89%). Maximum relative root length was found in the rice (SN04, Prosad Bhog) and minimum in SN07 (Kola Kon Joha) with a range between 99.13%-51.70%.
Relative shoot length (%)
Relative shoot length (%)
Relative root length (%)
Relative root length (%)
Fig. 5. Effect of drought on growth; A, shoot length and B, root length among the 21 rice cultivars along with the controls (data presented as mean ± SE; n = 3); The analysis of variance (ANOVA) was applied to examine the statistical significance; the low p-values (< 0.05) indicated respectively by the rice cultivars as compared with controls is significant and well fitted. The lack of fit for both models with high p-value (> 0.05) further emphasizes that the models can be used to predict the responses. The high value of R2 (0.759) and adj-R2 (0.643) in case of shoot length; 0.814 and 0.725 in case of root length respectively which further signify that the response and independent variables were well correlated.
3.1.3. Effect of drought on shoot and root fresh and dry weight
Shoot fresh weight was highest (84.81%) in the variety Helash Bora (SN06) under drought stress and minimum (36.36%) was recorded in Bora (SN03). On the other hand, shoot dry weight was found in the range of 10.23% – 66.94% in Salihoi Bao (SN08) and Makhan Bora (SN19) respectively.
Among all the varieties, SN19 (Makhan Bora) (75.74%) was recorded highest root fresh weight and minimum in SN06 (Helash Bora) (22.47%), whereas in case of root dry weight, the range was recorded as 13.51% – 34.21% in Kola Kon Joha (SN07) and Ronga Bora (SN20) respectively (Fig. 6). Under drought, there were significant differences in root and shoot fresh weight among the rice varieties. Drought drastically decreased the shoot and root dry weight as compared with their fresh weight. The trend demonstrated by Bora (SN03) might be an indication of drought tolerability as compared with the controls.
Fig. 6. Effect of drought on fresh and dry weight among the 21 rice cultivars along with the controls; A, shoot and B, root (data presented as mean ± SE; n = 3); ANOVA was applied to examine the statistical significance; the low p-values (< 0.05) indicated respectively by the rice cultivars as compared with controls is significant and well fitted. The lack of fit for both models with high p-value (> 0.05) further emphasizes that the models can be used to predict the responses. The high value of R2 (0.983) and adj-R2 (0.975) in case of root fresh weight; 0.259 and -.095 for root dry weight which indicated negative correlation (D), whereas, shoot fresh and dry weight also revealed negative correlation.
3.1.4. Calculation of relative water content (RWC)
To understand the effect of water stress on experimental rice plants, relative water content (RWC) of the leaves was monitored relatively in both control and treated plants. Relative water content of rice leaves were found to be decreased under drought stress (Fig. 7).
Fig. 7. Effect of drought on relative water content of leaves (data presented as mean ± SE; n = 3); ANOVA was applied to examine the statistical significance; the low p-values (< 0.05) indicated respectively by the rice cultivars as compared with controls is significant and well fitted.
RWC was recorded lowest in Kola Ahu (SN15) and highest in Bora (SN03) which was 32.88% and 93.48% respectively. In this investigation, SN03 revealed significantly higher RWC followed by Prosad Bhog (SN04), Helash Bora (SN06) and Jahingia (SN17). However, relatively lower RWC was recorded in Salihoi Bao (SN08), Kola Sali (SN16) and Sodiya Bao (SN09).
3.1.5. Estimation of chlorophyll-a, chlorophyll-b and total chlorophyll
In the present investigation there was a significant decrease in the chlorophyll -a, b and total chlorophyll content in the drought treated plants as compared with control (Fig. 8). Chlorophyll – a was measured highest in SN03 (Bora) (85.90%) and lowest in SN09 (SodiyaBao) (67.60%). Chlorophyll – b was measured in a range of 45.35% – 88.77% in Sodiya Bao (SN09) and SN20 (Ronga Bora) respectively. Total chlorophyll was found highest in Amo (SN22) i.e., 81.67% and lowest in Deuri Lai (SN14) as 66.81%. Bora (SN03) also showed significantly high content of total chlorophyll as compared with the others.
Relative chlorophyll a (%)
Relative chlorophyll b (%)
Relative total chlorophyll (%)
Fig. 8. Effect of drought on chlorophyll content; A, chlorophyll-a; B, chlorophyll-b and C, total chlorophyll (data presented as mean ± SE; n = 3); ANOVA was applied to examine the statistical significance; the low p-values (< 0.05) indicated respectively by the rice cultivars as compared with controls is significant and well fitted.
3.2. Selection of drought tolerant varieties
On the basis of standard evaluating scores (SES), all the rice varieties could be clustered into certain groups with regards to drought tolerability. SES discriminated the susceptible from the tolerant and the moderately tolerant rice varieties. The standard evaluating score of drought stress method was used for screening the 21 traditional rice cultivars and compared with the two controls. It was found that 8 varieties were highly tolerant, 10 varieties were moderately tolerant and 3 varieties were found susceptible (Fig. 9). The lowest value indicates the highest drought tolerability as compared with Sahbhagi Dhan which was used as positive control throughout the experiments.
Number of rice cultivars
Fig. 9. Frequency distribution of rice varieties with different drought tolerance score (in SES scale 1 – 9).
Here, eleven different morpho-physiological parameters under water stressed condition were used for SES analysis. Out of 21 traditional rice screened for drought stress and on the basis of SES score, rice varieties showing high drought tolerability were finally selected for further biochemical analyses. In each experiment, Sahbhagi Dhan and IR64were used as control. A total of 8 rice varieties were identified as drought tolerant on the basis of morpho-physiological parameters viz., SN03 (Bora), SN04 (Prosad Bhog), SN05 (Kola Joha), SN06 (HelashBora), SN08 (Salihoi Bao), SN12 (KolaAmona), SN20 (RongaBora) and SN21 (Sok-Bonglong) respectively.
3.3. Effect of drought on biochemical aspects
3.3.1. Determination of proline content
Proline is one of the important osmolytes which accumulates during drought stress condition. Fig. 10 consists of the proline accumulation of rice varieties in control, treated and in recovery in shoot and root. High proline content is a good index for moisture resistance in rice varieties. Under moisture stress condition the protein degrades and consequently the proline content increases. In the present study, SN20 (Ronga Bora) and SN05 (Kola Joha) revealed highest proline content over control at drought stress followed by SN04 (Prosad Bhog) in shoot. However, in root highest proline content was found in SN05 (Kola Joha) followed by SN04 (Prosad Bhog) and SN06 (Helash Bora).
Proline µmol g-1(f.m.)
Fig. 10. Effect of drought on proline content in shoots (A) roots (B) in control, stressed and recovery conditions (data presented as mean ± SE; n = 3); ANOVA was applied to examine the statistical significance; the low p-values (< 0.05) indicated respectively by the rice cultivars as compared with controls is significant and well fitted where the high value of R2 and adjusted R2revealed 0.747 and 0.711 respectively.
3.3.2. Measurement of lipid peroxidation
When ROS level reaches above threshold, enhanced lipid peroxidation takes place in both cellular and organellar membranes, which, in turn, affect normal cellular functioning (Shah et al., 2001). The effect of drought stress on the concentration of lipid peroxides was measured in terms of thiobarbituric acid reactive substances. Lipid peroxidation level in shoot and root of the selected rice varieties in control, stressed and in recovery, measured as the content of MDA, are expressed (Fig. 11). A significant enhancement in the concentration of lipid peroxide was observed in drought stressed seedlings compared to controls. Increased thiobarbituric acid reactive substances (TBARS) was observed in drought susceptible variety IR64 (SN01) in stressed compared to unstressed seedlings. In contrast to this, Sahbhagi Dhan (SN02) – a drought resistant variety showed decreased MDA content in stress than the control condition. All other selected varieties showed results similar with Sahbhagi Dhan. In shoot lowest level of lipid peroxidation was observed in SN03 (Bora), could be suggested as most resistant variety. However, in case of root lowest lipid peroxidation observed in SN06 (HelashBora). Interestingly, all the variety had less amount of lipid peroxidation in recovery than treated condition.
MDA µmol g-1(f.m.)
Fig. 11. Effect of drought on MDA content in shoots (A) roots (B) in control, stressed and recovery conditions (data presented as mean ± SE; n = 3); ANOVA was applied to examine the statistical significance; the low p-values (< 0.05) indicated respectively by the rice cultivars as compared with controls is significant and well fitted.
3.3.3. H2O2 content
The effect of drought stress on the generation of hydrogen peroxide in control, treated and in recovery rice seedlings was shown (Fig. 12). Due to imposition of drought stress, a significant increase in hydrogen peroxide was observed in root and shoot of the variety SN01 (IR64) in treated condition than in control. As this variety was taken as negative control i.e. susceptible to drought stress, therefore, the results obtained from this experiment was in agreement with the expectation. However in recovery the level of hydrogen peroxide is decreased in this variety suggesting that the plant has an adopted stress escaping mechanism. Sahbhagi Dhan (SN02), which was used as positive control for drought, revealed decreased level of hydrogen peroxide in stressed than in control condition. All the other selected varieties showed similar results, concordance to the positive control. Among those, SN03 (Bora) was found significantly lowest H2O2 level in shoot and SN21 (Sok-Bonglong) had lowest H2O2 level in root. A decline in H2O2 concentration in recovery was observed in all the rice varieties compared to stress condition.
H2O2 µmol g-1(f.m.)
Fig. 12. Effect of drought on H2O2 concentration in shoots (A) roots (B) in control, stressed and recovery conditions (data presented as mean ± SE; n = 3); ANOVA was applied to examine the statistical significance; the low p-values (< 0.05) indicated respectively by the rice cultivars as compared with controls is significant and well fitted.
Water deficit is one of the most common environmental stresses that affects growth and development of plants (Nahar et al., 2016). Thereby, selection of drought tolerant rice genotypes is a major challenge for future rice improvement program. Drought stress is of high importance, particularly for drought-sensitive plants, such as rice. Rice varieties have differential responses to abiotic stresses because of the complexity of interactions between stress factors and various molecular, biochemical, and physiological processes that affect plant growth and development. Rice growth performance is subjected to environmental factors which affect the physiological processes inside rice plant cells. Improving rice physiological characteristics is considered to be desirable due to its agronomic importance towards the achievement of high rice yield. More than the 20 million hectares of rain-fed lowland rice worldwide suffer water deficit at different growth stages (Sarma et al., 2016). Rice is one of the most drought-susceptible crops, especially at the reproductive stage. It was reported that at rain-fed conditions, water deficit has a serious effect, especially at the booting stage, during which plants are particularly drought-susceptible, leading to low-crop productivity (Lahkar and Tanti, 2017). In the present study, 21 traditional rice varieties collected from six different agroclimatic zones of Assam were used for screening their drought tolerance ability both morpho-physiological and biochemical approaches. There are few reports of the similar kind of works but no any study for drought stress has been conducted on the traditional rice of Assam, India
In the present study, inhibition of seed germination at the treated condition might be due the lower osmotic potential caused by PEG-6000. Drought stress reduces the rice growth and severely affects different traits, such as seedling biomass, stomatal conductance, photosynthesis, starch metabolism, and plant-water relations (Chutia et al., 2012). Sarma et al., (2016) reported that grain yield of some rice varieties was tremendously reduced by up to 81% under drought condition and this reduction depended on duration, timing and severity of the plant water stress. Nahar et al., (2016) did extensive work and reported differential responses of rice genotypes to water deficit. They observed when rice genotype exposed to water stress; panicle length and fertile grains in two tolerant varieties were not only significantly decreased, but also leading to greater productivity than in two sensitive cultivars.
In water stress assays, it was observed that water deficit negatively imposed all evaluated morpho-physiological characters of rice plant, but the severity of loosed performance differed depending on the genotypes. In the present study, inhibition of seed germination and early seedling growth on water stress might be due to adverse effect of water scarcity and thereby hindered the physiological activity of the germinated seed. It was observed that the germination was significantly affected by the osmotic potential in water stress as compared to control.
RWC measures the water content of a leaf relative to the maximum Amount that the leaf can take under full turgidity and hence is considered as an appropriate measure of plant water status under stress. While leaf water potential has been used as an estimate of plant water status when dealing with water transport in the soil-plant-atmosphere continuum, it does not account for osmotic adjustment (OA) that commonly occurs in plant roots and leaves in response to stress. OA is a powerful mechanism for conserving cellular hydration under drought stress and can be accounted for when measuring leaf RWC. Hence RWC is an appropriate estimate of plant water status because it accounts for both leaf water potential and OA. This study was conducted to determine the association between RWC and drought tolerance in rice and to investigate the possibility of using RWC as screening criteria for breeders to incorporate tolerance to drought stress. In this study, the rice variety Bora (SN03) showed significantly higher RWC which was recorded as 93.48% along with the three more promising varieties viz., Prosad Bhog (SN04), Helash Bora (SN06) and Jahingia (SN17).
Photosynthesis is an essential process for crop growth and development, and it is well known that photosynthetic mechanisms in higher plants are most sensitive to water stress (Lahkar and Tanti, 2017). Chlorophyll is one of the major chloroplast components for photosynthesis, and relative chlorophyll content has a positive relationship with photosynthetic rate. Lahkar and Tanti, (2017) showed that chlorophyll content was reduced under PEG-induced water stress in rice seedlings. Reduction in chlorophyll content due to water stress at anthesis stage in wheat was also observed by Ganji Arjenaki et al., (2012). Exposure to drought stress leads to a significant effect in Chlorophyll a and Chlorophyll b contents (Ranjbarfordoei et al., 2000). In the present investigation, chlorophyll contents revealed considerable sensitivity to drought stress, even at 20 % PEG treatment, all chlorophyll contents were reduced as compared with control and their reduction was more visible. A reason for decrease in chlorophyll content as affected by water deficit is that drought stress by producing reactive oxygen species (ROS), such as O2*- and H2O2, can lead to lipid peroxidation and, consequently, chlorophyll destruction (Hirt and Shinozaki, 2004).
Reactive oxygen species (ROS) are produced in both water stressed and unstressed conditions. Plants have well developed defense systems against ROS which involves both limiting the formation of ROS as well as instituting its removal. Under unstressed conditions the formation and removal of ROS are in balance. However, the defence mechanisms when presented with increased ROS formation under water stressed conditions can be overwhelmed.
From the overall study, rice cultivar Bora (SN03) was found to be more promising with significantly positive in all the drought related traits, which could be targeted for future rice breeding programme for developing drought tolerant rice varieties.
The authors gratefully acknowledge the Regional Rainfed Lowland Rice Research Station (RRLRRS), Gerua, Kamrup (Assam) and also to farmers of different districts of Assam for providing the rice seeds throughout the course of research work. Ms. Lipika Lahkar, JRF, Botany Department, Gauhati University, India is acknowledged for technical support in statistical analysis. The financial assistance received from the UGC, Maulana Azad National Fellowship for Minority Students (MANF), Government of India is highly acknowledged.
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