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Nupur, Hannan, Islam, Sagor, and Robin: Root Development and Anti-Oxidative Response of Rice Genotypes under Polyethylene Glycol Induced Osmotic Stress


Osmotic stress is a kind of stress which is directly or indirectly related to all other abiotic stresses. Four rice varieties namely Binadhan-11 (with SUB1 gene), BRRI dhan52 (with SUB1 gene), Binadhan-7 and BRRI dhan71 were used to study the variation in root development and anti-oxidative response under osmotic stress conditions. Osmotic stress was induced by applying polyethylene glycol (4% PEG) in hydroponic solution. Treatment was given at the panicle initiation stage and leaf samples were collected at fourteen days after treatment to estimate antioxidant response in terms of ascorbate (APX) and peroxidase (POD) enzymatic activity. Roots were destructively harvested at 16 days after the stress imposition. The tested varieties showed significant differences in antioxidant responses under the stress condition such as high APX and POD in Binadhan-11 and BRRI dhan52. Significant injury at the 4th leaf position (the youngest leaf was the reference) was observed at 8 and 12 days after the treatment. Number of live leaves, shoot dry weight, density of second order lateral roots, number of phytomer (Pr) and total roots, number of roots at Pr2, main axis diameter at Pr1, main axis length at Pr1 varied significantly among the varieties × treatment combinations. Binadhan-11 and BRRI dhan52 showed comparatively higher osmotic stress tolerance compared to the other two varieties without SUB1 gene, viz., Binadhan-7 and BRRI dhan71. The varieties BRRI dhan52, and Binadhan-11 showed greater capacity to withstand osmotic stress can be further used to develop stress tolerant variety.


Rice occupies the position of the world’s third most important cereal crop growing on over 161.1 million hectares of land and giving a yield of 487.5 metric tons (milled rice) worldwide (Statista, Rice production faces severe threat due to various environmental stresses especially relating to water availability and salinity which are resulting from adverse climatic changes (Redman et al. 2011). Plants face osmotic stress through decreasing water absorption and cellular dehydration under abiotic stresses especially under drought (Zhu et al. 1997; Xiong and Zhu 2002). Osmotic stress is such a condition that causes water limitation around the plant cell inhibiting plant growth and development (Zhu et al. 1997). When plants face osmotic stress, they possess a wide range of responses at molecular, cellular and whole plant levels including morphological and developmental changes, adjustment in ion transport and metabolic changes (Greenway and Munns 1980; Zhu et al. 1997; Yeo 1998; Bohnert et al. 1999; Hasegawa et al. 2000).
The reproductive stage of plant is extremely affected by water deficit conditions (Saini and Westgate 1999). Reproductive stages of rice are highly susceptible to drought (i.e. panicle initiation grain filling and maturation stage) (Zhang et al. 2018). Water deficit conditions during the reproductive stage can cause late flowering or complete inhibition of flowering because of the inhibition in floral induction and development (Saini and Westgate 1999). Moreover, early grain initiation, loss of pollen fertility, failure of pollination, spikelet death, or zygotic abortion, changes in carbohydrate availability, changes in the kernel sink potential are also the consequences of water deficit conditions prior to reproductive phases or in the reproductive phases (Saini and Westgate 1999). Besides all of these effects, formation of reactive oxygen species (ROS) are other consequences of abiotic stresses such as drought, and ROS enhancement during stress condition act as an indicator of triggering the defense mechanism of plants (Cruz de Carvalho 2008). Plants possess their own mechanisms to fight against ROS by producing different enzymatic, non-enzymatic antioxidants and proteins (Nezhadahmadi et al. 2013). Varieties with high activities of antioxidant enzymes like catalase (CAT), ascorbate peroxidase (APX) and peroxidase (POD) show tolerance under stress conditions (Mafakheri et al. 2011).
The root is the most efficient plant organ that helps plants in water and mineral uptake from soil (Zhu et al. 2011). Roots are the first part of the plant body that can detect the osmotic stress. Roots not only take up water and minerals, but also send signals to other plant parts through the xylem sap (Zhang and Davies 1987; Davies and Zhang 1991; Hartung et al. 2002; Jiang and Hartung 2007). Under water deficit conditions, plants uptake more water from deeper region of the soil through root proliferation and changes in root parts (Zhu et al. 2011). A considerable change was found in both root elongation and diameter of all species due to the effect of osmotic potential in the root environment (Materechera et al. 1992). Proper root system architecture in a given environment permits plants to survive in water and nutrient deficit conditions, gives ability to utilize minimum resources efficiently (Malamy 2005). For studying the developmental plasticity and characteristic features of plant growth, the root system was given the first priority (Malamy 2005). Root system architecture refers to the spatial configuration of the root system, i.e. the clear geometric deployment of root axes (Lynch 1995). Generally, studies of root architecture do not comprise of fine structural details such as root hairs, but it actually concerns an entire root system or a large subset of the root system of an individual plant (Lynch 1995; Jung and McCouch 2013). In recent years, breeding for the development of larger and more efficient root systems has become the hotspot in research in some crops such as rice, as there is a relation between root system size and tolerance to water stress (Price et al. 2002; Tuberosa et al. 2002). Like other grasses, the form of a rice plant is best understood from the phytomer concept (Fig. 1). Phytomers are the building blocks of a rice tiller (McMaster and Hargreaves 2009). Each node including the leaf as well as the internode just after it are considered as a phytomer unit. Furthermore, many adventitious roots are produced from each phytomer till internodal elongation starts (Kawata et al. 1963; Arikado et al. 1990). A typical root system of a rice plant contains main root axis along with other root axes such as first order lateral root, second order lateral root, third order lateral root and root hairs which assist in anchorage and nutrition uptake of plants (Henry et al. 2011). Generally roots from the first few phytomers continue to elongate, and branching commence from third or fourth phytomer (Fig. 1, Robin et al. 2010).
In this research, four rice genotypes were grown in PEG-mediated hydroponic solution for studying the modifications of shoot, root system and biochemical responses under osmotic stress at the panicle initiation stage. This study was also designed to understand and model the efficient root system for rice genotypes adapted to osmotic stress.


Plant materials and growth condition

In this study, four rice genotypes were used from which BRRI dhan52 and BRRI dhan71 were collected from BRRI (Bangladesh Rice Research Institute) and Binadhan-7 and Binadhan-11 were collected from BINA (Bangladesh Institute of Nuclear Agriculture). Polystyrene sheets were used for seed germination. A total of 150 seeds of each variety were germinated in each plastic tray on a polystyrene sheet which was floating on clean tap water. About 3-4 days were required for seed germination. After eight days, seedlings were transplanted to the hydroponic solution in six individual trays and a completely randomized design was used with two treatments and three replicates where each treatment includes each of the four varieties. Following nutrient solution was used for plant growth: 1 mM NH4NO3, 0.6 mM NaH2PO4.H2O, 0.6 mM MgCl2.H2O, 0.3 mM K2SO4, 0.3 mM CaCl2.H2O, 50 mM H3BO3, 90 mM Fe-EDTA, 9 mM MnSO4.4H2O, 0.7 mM ZnSO4.7H2O, 0.3 mM CuSO4.5H2O, 0.1 mM NaMoO4.2H2O by dissolving in tap water (Robin et al. 2014; Hannan et al. 2020). The nutrient solution was changed every 7 days. A 16:8 hours day: night ratio was maintained in the plant culture room. The temperature of the culture room was maintained at 20 ± 2℃. All plants were under a similar environment until 75 days after germination. Two different polyethylene glycol-6000 (PEG-6000, Merck-Schuchardt, Hohenbrunn, Germany) treatments: 0% PEG (control) and 4% PEG were applied at 75 days old plants at the panicle initiation stage (Sattar et al. 1991) to induce osmotic stress.

Data recording on shoot and root traits

Leaf injury was scored in a non-destructive way by visual scoring at 2, 4, 8 and 12 days after imposing PEG treatment using a 1-9 scale (Table 1, Fig. 2) (Arif et al. 2019). Chlorophyll content of the top five youngest leaves of the main tiller was measured at 14 days after applying 4% PEG-6000 by a Chlorophyll meter (SPAD-502 Plus, 3 V; 200 Mw) in a non-destructive manner. At 16 days after application of stress, plants were destructively harvested and data were recorded on different traits. After counting total number of leaves and roots per main tiller, roots were arranged according to length and then total number of phytomer was counted. The main axis and first order lateral root lengths were measured by a centimeter scale. All other root traits (diameter and density) were measured under a light microscope at 100× magnification using a micrometer scale. Acetocarmine solution of 0.5% prepared by mixing 45% glacial acetic acid which was used to make roots and root hairs clearly visible under a light microscope. Roots and shoots were dried at 60℃ in an air draft oven for three days before recording their dry weights.

Biochemical trait analysis

Fully expanded flag leaves of all four varieties were collected at fourteen days after PEG application and were subjected to biochemical analysis. For antioxidant APX determination, reagents potassium phosphate buffer (50 mM), EDTA (2.5 mM), H2O2 ‒200 mM and ascorbate ‒2.5 mM were used as described by Nakano and Asada (1981) and for POD, 100 mM of guaiacol was used instead of ascorbate by following the procedure of Nakano and Asada (1981).

Statistical analysis of data

Data were analyzed using MINITAB 17 statistical software packages (Minitab, Inc., State College, Pennsylvania, USA) to perform a two-way analysis of variance (ANOVA) for different shoot, root and biochemical traits following a general linear model (GLM). Mean comparison for the significant traits was done by both Tukey’s and Fisher’s pairwise comparison. Principal Component Analysis (PCA) was done to find out the major traits responsible for variation and Pearson correlation analysis was performed to explore relationship among the traits.


Effect of PEG induced osmotic stress on shoot traits

In general, there were 5-6 live leaves per plant under the control condition (Fig. 3A). A significant increase or decrease in total number of live leaves was found among four rice genotypes under 4% PEG treatments (Table 2, Fig. 3A) and the highest increase was found in BRRI dhan52 (15.7%) while the highest decrease in Binadhan-7 (20%) (Fig. 3A). On the other hand, four rice genotypes showed a significant change in chlorophyll content at the 4th leaf position (Table 2). For 4th leaf the highest percent of increase of chlorophyll content was 4% PEG over control was found in BRRI dhan52. However, it was Binadhan-7 in which the highest reduction of chlorophyll content, 19.91%, was observed. In case of shoot dry weight, significant reduction was observed in all genotypes under 4% PEG treated condition in Binadhan-7 at 77.64% (Table 2, Fig. 3B).

Effects of osmotic stress on root traits

Total number of phytomers per main tiller ranged from 7 to 13 in four rice genotypes (Fig. 3C). Total number phytomers per main tiller was found to be significantly different under PEG stress (Table 2, Fig. 3C) and it only showed an increasing trend (Fig. 3C). BRRI dhan71 recorded the highest number of phytomers (28.6%) under 4% PEG treated condition compared to other interactions (Fig. 3C). There were 19 to 27 roots per main tiller in plants under the control treatment (Fig. 3C). Significant changes were noticed in all rice genotypes under 4% PEG treated condition where the highest increase was found in Binadhan-11 (10.9%) and the highest decrease was in BRRI dhan71 (12.31%) (Table 2, Fig. 3D). Number of roots at each phytomer was found to be significantly different under PEG stress (Table 2, Fig. 4A) which was the highest in Binadhan-7 and the lowest in Binadhan-11 (Fig. 4A). Main axis length at phytomer 1 of four genotypes ranged from 28 to 40 cm and demonstrated either significant increase or decrease under 4% PEG treatment (Table 2, Fig. 4B). The highest percent increase under 4% PEG over control was found in BRRI dhan52 (85.89%) and decrease in Binadhan-11 (18.31%) (Fig. 4B). The highest increase in main axis diameter at phytomer 1 was observed in BRRI dhan71 (1.73%) under PEG stress (Fig. 4C). Density of second order lateral root was found to be significant under PEG stress for variety (Table 2). The highest percent of increase in density of second order lateral roots was observed under 4% PEG over control in Binadhan-11 (94.93%) and was decreased in BRRI dhan71 (31.05%) (Fig. 4D).

Biochemical response under osmotic stress

Ascorbate peroxidase (APX) and peroxidase (POD) activity altered significantly in 4% PEG over control among the four rice varieties (Table 3, Figs. 5). Ascorbate peroxidase (APX) and peroxidase (POD) activities were the highest in Binadhan-11 and they were 116.24% and 84.32% higher, respectively, in 4% PEG over control (Fig. 5). A decrease in ascorbate peroxidase activity of 80% was observed in BRRI dhan71 while the peroxidase activity was decreased by 44% in Binadhan-7 under 4% PEG over control (Fig. 3A, B).

Trait association

Principal component analysis (PCA)

The first three principal components (PC) explained about 67.9% of the total data variation for the effect of polyethylene glycol (PEG) induced osmotic stress on shoot, root and biochemical traits. Eigenvalues (variances of PC scores) along with the contribution of each PC are given in Table 4. Three PCs were identified based on an eigenvalue higher than unity. PC1, PC2 and PC3 explained 30.1%, 23.5% and 14.3% variation, respectively, of the total data set (Table 4). PCA revealed that the majority of variation was explained by the first two principal components (Table 4). When a two-way ANOVA was performed, PC1 was found to be significant for variety while both PC2 and PC3 were found significant for treatment, variety and treatment x variety interaction (Table 4). Variation in PC1 is largely contributed by the positive coefficients of total number of live leaves, chlorophyll content of the 4th leaf, total number of phytomers, total number of roots, main axis length at phytomer 1, density of second order lateral roots and shoot dry weight (Table 4, Fig. 6). PC1 separated Binadhan-11, BRRI dhan52 both in treated and control condition from BRRI dhan71, Binadhan-7 both in control and treated condition (Table 4, Fig. 6). The variation in PC2 was accounted for due to positive coefficients of main axis diameter at phytomer 1 and negative coefficients of main axis length at phytomer 1, number of roots at phytomer 2 and ascorbate peroxidase activity (Table 4, Fig. 6). PC2 separated BRRI dhan52, BRRI dhan71 both in control and treated condition for their positive PC scores from Binadhan-7 in treated condition and Binadhan-11 both in control and treated condition for their negative PC scores (Table 4, Fig. 6).

Correlation analysis

A Pearson correlation analysis was done to reveal the association among the shoot, root and biochemical traits. Total number of live leaves per main tiller showed significant and positive relationship with chlorophyll content of the 4th leaf, total number of phytomers and shoot dry weight (Table 5). Chlorophyll content of the 4th leaf showed a significant and positive relationship with shoot dry weight (0.64) (Table 5). Total number of phytomers showed a strong positive significant relationship with total number of roots (0.753) (Table 5). Total number of roots showed positive and significant relationship with the main axis length at phytomer 1 (0.62) (Table 5). Main axis diameter showed significant and negative correlation with main axis length at phytomer 1 (‒0.41) and ascorbate peroxidase (‒0.53).


Changes in shoot traits

Under water stress, uptake of nutrients by the plant drastically decreases resulting in leaf senescence, reduction in photosynthetic area and ultimately reduction of number of live leaves (Munns 2002). Therefore, it can be said that the variety which possesses a greater number of live leaves under stress environment may have tolerance against water stress. In this experiment, BRRI dhan52 showed the highest increase in number of live leaves under the treated condition (Fig. 3A). Chlorophyll is one of the major components of chloroplast and the content of chlorophyll has a positive relationship to photosynthesis (Anjum et al. 2011a). During osmotic stress like drought conditions, degradation of chlorophyll is considered to be a typical symptom of oxidative stress (Anjum et al. 2011a). A decrease in chlorophyll content may cause lower light harvesting thus reducing rate of photosynthesis which leads to decrease in yield (Mafakheri et al. 2010). That indicates that if total chlorophyll content increases, light harvesting may be increased and ultimately the yield may increase. In the experiment, the highest increase in chlorophyll content was found in BRRI dhan52 and the lowest was found in Binadhan-7 which indicates BRRI dhan52 may possess osmotic stress tolerance while Binadhan-7 shows sensitivity to water deficit conditions. Osmotic stress mainly limits photosynthesis through stomata closure or through metabolic impairment which results in lower dry weight (Lawson et al. 2003). Therefore, water stress tolerant genotypes should have better shoot dry weight compared to that of the susceptible genotype.

Changes in root traits

Under salinity stress, the number of active root bearing phytomers increased with the decrease of live leaves in the tiller axis (Robin et al. 2016). Phytomers gives resistance to water flow during osmotic stress (Matsuura et al. 2000). In this experiment, all varieties showed an increase in total number of phytomers which was highest in BRRI dhan71 (Fig. 3C). Roots are the primary tool that face water stress, and plants may increase root growth for absorbing more water from deeper regions of the soil by compensating shoot growth (Singh et al. 1973). Thus, the variety which produces more roots may show more resistance to osmotic stress. In this study, the highest percent of total number of roots was found in the variety Binadhan-11 (Fig. 3D). Number of roots at each phytomer can vary depending on variety and environment. Some varieties may possess more roots while another may possess a smaller number of roots at each phytomer (Kondo et al. 2003; Hannan et al. 2020). In the present study, the highest increase of number of roots per tiller was found in Binadhan-7 and the highest decrease was found in Binadhan-11 (Fig. 4A). According to Gargallo-Garriga et al. (2014), during water stress the plant decreases its shoot growth to increase its root growth for the uptake of more water and nutrient to the deeper soil depth. Root elongation was found to be reduced with the enhancement of osmotic stress (Materechera et al. 1992).
Root length of tolerant varieties may increase under drought conditions (Fukai and Cooper 1995). In this study, the highest increase in length of main root axis was found in BRRI dhan52 (Fig. 4B) which means this variety may be able to withstand osmotic stress. Osmotic stress due to water deficit conditions is the major challenge for improving varieties nowadays which has a great influence on root diameter change, and it was found that root diameter increases significantly during osmotic stress in case of tolerant variety (Materechera et al. 1992; Jeong et al. 2013). In this experiment, the highest increase in root main axis diameter at phytomer 1 was found in BRRI dhan71 while Binadhan-7 showed highest decrease in diameter (Fig. 4C). This indicates Binadhan-7 may be osmotic stress susceptible. Changes in lateral root development under moisture fluctuation are the key traits for the growth of rice during water deficit condition (Banoc et al. 2000). Under osmotic stress, number of lateral root increases in water stress tolerant varieties (Banoc et al. 2000; Hannan et al. 2020).

Biochemical response

Mittler (2002) found that ascorbate peroxidase activity increased in drought tolerant species under PEG-treated condition compared to control. As an isoenzyme, ascorbate peroxidase in higher plant helps in scavenging H2O2 (Shigeoka et al. 2002). In this present experiment, APX activity was found both in increasing and decreasing patterns in PEG treated plants compared to control. According to Islam et al. (2015), peroxidase (POD) activity was higher in drought condition compared to control in tolerant varieties. Enzymatic antioxidants such as POD gives a strong protective defense against free radical induced oxidative stress in plants (Mafakheri et al. 2011). In the present study, the highest percent of increase in POD activity was observed in Binadhan-11 while the highest percent decrease was found in Binadhan-7 (Fig. 5B) that indicates Binadhan-11 have more capacity to withstand water stress than Binadhan-7.
Plants naturally face different kinds of biotic and abiotic stresses which cause changes in their metabolic system due to changes in biochemical components. Among all of the stresses, osmotic stress due to drought is the most limiting factor for plant growth and development (Anjum et al. 2011b). To combat this condition, some genotypes may possess better osmo-protectant abilities, whereas some might have better ROS scavenging abilities (Abid et al. 2018). Therefore, it is necessary to find out the interrelationship among the biochemical parameters. Peroxidase which is an antioxidant enzyme protects the plant cell from destructive effect of H2O2 by catalyzing the dehydrogenation reaction of H2O2 during stress conditions (Chen et al. 1999).

Trait association

PC1 clearly separated Binadhan-7 and BRRI dhan71 from Binadhan-11 and BRRI dhan52 both in control and treated conditions (Fig. 6). Varieties Binadhan-11 and BRRI dhan52 have stronger genetic composition which are responsible to combat the stress condition and the traits i.e. main axis length at phytomer 1, main axis diameter at phytomer 1, density of second order lateral root, live leaves, chlorophyll content at the 4th leaf, shoot dry weight, number of roots at phytomer 2, total number of phytomers per main tiller, total number of roots per main tiller (Fig. 6) were the traits associated with osmotic stress tolerance.
Root traits play significant roles in drought resistance and maintain strong leaf water potential during water stress (Ekanayake et al. 1985). From correlation analysis among shoot, root and biochemical traits, it was found that the total number of phytomers had a positive correlation with the total number of roots (Table 5). With the increase of root bearing phytomer, the total number of roots increases, and in a previous study, it was found that during water deficit the number of roots increased significantly (Wedderburn et al. 2010). A significant positive correlation was found between leaf chlorophyll content and shoot dry weight. High chlorophyll content may contribute to higher photosynthesis thereby yield increases (Mafakheri et al. 2010).
In conclusions, Osmotic stress creates physiological drought which has become the major barrier for desired crop yield. When plants face any kind of abiotic stress, it will face osmotic stress even if it is for a short period of time. In this study, shoot growth generally decreased compared to root growth and number of roots per phytomer increased under osmotic stress. It can be concluded from this study that the variety with SUB1 gene (Binadhan-11 and BRRI dhan52) showed better performance compared to the other two varieties. There may be some gene responsible for osmotic stress resistance. The results of this study can be used in future breeding programs. In addition, further extensive research may be conducted by including more varieties and mutants to map the gene responsible for osmotic stress tolerance.


This research was supported by the Ministry of Science and Technology, Government of the People’s Republic of Bangladesh (Grant no. 2019/1/MoST). NST fellowship of the first author is gratefully acknowledged.



AHKR conceived the idea and critically edited the manuscript. JAN and AH cultured plants and collected data. AUI assisted JAN in data collection. GHMS guided JAN in biochemical analysis. JAN wrote the manuscript.


The authors have declared that no competing interests exist.


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Fig. 1
A hypothetical architecture of root system of a rice plant under progressive root development. This figure illustrates first four root bearing phytomers. Phytomer 1 is the youngest root bearing phytomer. Main root axes elongates at phytomer 1 and 2. First and second order lateral roots form at phytomer 3. Third order lateral roots form at phytomer 4. Root hairs form at all root bearing phytomers (Robin et al. 2010).
Fig. 2
Leaf injury scores of leaves of rice genotypes under PEG treated hydroponic culture.
Fig. 3
(A) Total number of live leaves (LL). (B) Shoot dry weight (SDW). (C) Total number of phytomer (TPr). (D) Total number of roots (TRt) of four rice genotypes under control (0%) and treated (4% PEG) conditions. Vertical bars indicate standard error of mean against each variable. Different letters indicate statistically significant difference.
Fig. 4
(A) Number of roots at phytomer 2 (NRPr2). (B) Main axis length at phytomer 1 (MALPr1). (C) Main axis diameter at phytomer 1 (MADPr1). (D) Second order lateral root density (SAD) of four rice genotypes under control (0%) and treated (4% PEG) conditions. Vertical bars indicate standard error of mean against each variable. Different letters indicate statistically significant difference.
Fig. 5
(A) Leaf APX activity (B) Leaf POD activity of four rice genotypes under control (0%) and treated (4% PEG) conditions. Vertical bars indicate standard error of mean against each variable. Different letters indicate statistically significant difference.
Fig. 6
Biplot from principal component analysis of shoot, root and biochemical traits of four rice varieties under 0% (control) and 4% PEG treatments. Bina-11.C: Binadhan-11.Control, Bina-11.T: Binadhan-11.Treated, BRRI 52.C: BRRI dhan52.Control, BRRI 52.T: BRRI dhan52.Treated, Bina-7.C: Binadhan-7.Control, Bina-7.T: Binadhan-7.Treated, BRRI 71.C: BRRI dhan71.Control, BRRI 71.T: BRRI dhan71.Treated, LL: Total number of live leaves, NRPr2: Number of roots at phytomer 2, MADPr1: Main axis diameter at phytomer 1, MALPr1: Main axis length at phytomer 1, SAD: Second order lateral root density, SDW: Shoot dry weight, TPr: Total number of Phytomer, TRt: Total number of roots, CL4: Chlorophyll content of 4th youngest leaf, APX: Ascorbate peroxidase, POD: Peroxidase.
Table 1
Visual leaf injury scoring under osmotic stress at the panicle initiation stage of four rice varieties.
Description Score
Normal color and growth 1
Nearly normal conditions, but leaf tip discoloration 3
Most of the leaf portion discolored and started to dry 5
The leaf is mostly dried and totally discolored 7
The leaf is death or close to death 9
Table 2
Analysis of variance for total number of live leaves (LL), total number of roots (TRt), total number of phytomer (TPr), number of roots at phytomer 2 (NRPr2), main axis diameter at phytomer 1 (MADPr1), main axis length at phytomer 1 (MALPr1), second order lateral root density (SAD), shoot dry weight (SDW), chlorophyll content of 1st leaf (CL1), chlorophyll content of 2nd leaf (CL2), chlorophyll content of 3rd leaf (CL3), chlorophyll content of 4th leaf (CL4) and chlorophyll content of 5th leaf (CL5).
Source of variation dfz) Mean Square value with traits
Treatment (T) 1 0.041 2.66 5.042 0.375 0.096* 0.01 0.042 0.157 16.3 27.09 17.7 24.2 1.6
Variety (V) 3 6.81** 135** 25.48** 1.37* 0.096** 61.9*** 0.40 0.414* 24.45* 49.29** 40.1* 40.6** 40.9**
T × V 3 1.26 9.11 1.042 1.486* 0.04*** 2.98 6.52* 0.035 17.93* 20.18 18.6 29.0* 9.24
Error 16 0.83 18.37 4.33 0.42 0.017 2.24 1.57 0.116 5.526 6.97 9.12 6.30 6.35


Treatment (T) 0.82 0.708 0.297 0.357 0.031 0.947 0.873 0.262 0.105 0.066 0.183 0.068 0.622
Variety (V) 0.002 0.003 0.007 0.047 0.008 < 0.001 0.856 0.038 0.019 0.003 0.019 0.005 0.005
T × V 0.248 0.113 0.690 0.038 < 0.001 0.300 0.024 0.819 0.050 0.067 0.149 0.017 0.264

* , ** and ***Significant at 0.05, 0.01 and 0.001 probability levels, respectively.

z)df: degrees of freedom.

Table 3
Analysis of variance for ascorbate peroxidase (APX) and peroxidase (POD).
Source of variation Degrees of freedom Mean squares

Treatment 1 1.079 0.015
Variety 3 4.58 0.08
Treatment × variety 3 4.04 0.21
Error 16 0.06 0.02

P value

Treatment < 0.001 0.374
Variety < 0.001 0.016
Treatment × variety < 0.001 0.108
Table 4
Coefficient of principal components (PCs) and mean scores of principal components.
Variables PC1 PC2 PC3
Number of live leaves 0.347 0.269 ‒0.097
Chlorophyll content of 4th leaf 0.339 0.377 ‒0.033
Total number of phytomer per tiller 0.408 ‒0.178 ‒0.088
Total number of roots 0.456 ‒0.217 ‒0.011
Main axis diameter at phytomer 1 0.087 0.507 ‒0.194
Main axis length at phytomer 1 0.320 ‒0.380 ‒0.086
Number of roots at phytomer 2 0.099 ‒0.320 ‒0.339
Second order lateral root density 0.238 0.001 0.332
Shoot dry weight 0.438 0.126 ‒0.091
Ascorbate peroxidase 0.094 ‒0.318 0.587
Peroxidase 0.115 0.294 0.598
Eigenvalue 3.31 2.58 1.57
Variation explained (%) 30.1 23.5 14.3
P-value (treatment) 0.674 0.039 0.003
P-value (variety) < 0.001 < 0.001 < 0.001
P-value (treatment x variety) 0.077 0.002 < 0.001

Mean PC scores with standard error

Binadhan-11 (control) 1.75 ± 0.73ab ‒1.57 ± 0.33cd ‒2.12 ± 0.16d
Binadhan-11 (treated) 2.62 ± 0.61a ‒1.15 ± 0.30bcd 1.11 ± 0.17a
BIRRI dhan52 (control) 0.20 ± 0.47abcd 1.84 ± 0.66a ‒0.60 ± 0.25bc
BIRRI dhan52 (treated) 0.93 ± 0.25abc 1.41 ± 0.58a 0.57 ± 0.45ab
Binadhan-7 (control) ‒0.10 ± 0.27bcd 0.58 ± 0.24 ab 1.69 ± 0.30a
Binadhan-7 (treated) ‒1.96 ± 0.394d ‒2.51 ± 0.453ab 0.63 ± 0.09ab
BIRRI dhan71 (control) ‒1.51 ± 0.53cd 0.49 ± 0.27abc ‒0.34 ± 0.40bc
BIRRI dhan71 (treated) ‒1.91 ± 0.790d 0.90 ± 0.31ab ‒0.95 ± 0.20cd
Table 5
Correlation coefficient analysis for total number of live leaves (LL), total number of roots per main tiller (TRt), total number of phytomer per main tiller (TPr), number of roots at phytomer 2 (NRPr2), main axis diameter at phytomer 1 (MADPr1), main axis length at phytomer 1 (MALPr1), second order lateral root density (SAD), shoot dry weight (SDW), chlorophyll content of 4th leaf (CL4), ascorbate peroxidase (APX) and peroxidase (POD).
CL4 0.578**
TPr 0.409* 0.125
TRt 0.367 0.237 0.75***
MADPr1 0.384 0.53** ‒0.102 ‒0.097
MALPr1 0.004 0.155 0.476* 0.62*** ‒0.413*
NRPr2 0.026 ‒0.135 0.145 0.250 ‒0.117 0.437*
SAD 0.005 0.146 0.268 0.330 0.171 0.110 0.024
SDW 0.475* 0.64*** 0.440* 0.580* 0.233 0.386 ‒0.019 0.31
APX ‒0.088 ‒0.197 0.105 0.290 ‒0.535** 0.292 0.114 0.26 ‒0.046
POD 0.302 0.411* ‒0.065 ‒0.018 0.228 ‒0.169 ‒0.404* 0.24 0.093 0.338

* , ** and ***Significant at 0.05, 0.01 and 0.001 probability levels, respectively.

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