Variations in Root Morphology and Yield among Rice Varieties in Response to Potassium under Subtropical Conditions

Abstract

The relationship between rice root morphology and Potassium (K) is a major concern for its growth and development, and it has a substantial impact on yield as well. In light of this, the current pot research was run in the net house of the Department of Agronomy at the Bangladesh Agricultural University, Mymensingh, Bangladesh, throughout the boro (dry season irrigated) season of 2020–2021. Binadhan-10, Hira-2 and BRRI dhan29 were grown with five K fertilizers: 0 kg K ha⁻¹ (K₀), 32 kg K ha⁻¹ (K₃₂), 65 kg K ha⁻¹ (K₆₅), 98 kg K ha⁻¹ (K₉₈) and 130 kg K ha⁻¹ (K₁₃₀). Three replications of the investigation were conducted using a completely randomized design (CRD). The root number (RN), root length (RL), root volume (RV), root porosity (RP) along with leaf area index (LAI), total dry matter (TDM) and yield were assessed. Binadhan-10 with the K₆₅ treatment significantly increased the RN, RL, RV, LAI, TDM and yield. With the further increase in the dosage of K that was under K₉₈ and K₁₃₀, the value of the root traits and yield did not increase. A positive connection was documented between the grain yield (GY) and all the root traits, excluding the RP. Binadhan-10 can be grown with 65 kg K ha⁻¹ at field level for a satisfactory yield.

1. Introduction

Rice (Oryza sativa L.) is considered an extensively used cereal crop around the world, which is consumed as a regular diet by more than three billion individuals globally [1]. A crucial ingredient for plant growth and productivity is K. The requirement for potassium fertilizer has increased significantly in the last ten years with the rise in global food consumption [2]. Similar to nitrogen (N) and phosphorus (P), K is regarded as more crucial than most essential minerals needed for plant growth and development when present in relatively significant amounts. Enhanced rigidity to insects and pathogens, photosynthetic activity, osmotic regulation, enzymatic activities, activation and transfer of photosynthates, protein biogenesis, ionic equilibrium, consistency among monovalent and divalent cations in the water transportation through stomatal movement, support for plant turgidity, stress resistance, and the activation of several enzymes are just a few of the many functions of potassium in agricultural production systems [3,4]. The main organ for nutrient intake in plants is the root. There were significant differences in root morphological traits among rice cultivars and a positive association between root traits and yield [5]. Additionally, upland paddy’s root systems account for approximately 22% of the plant’s dry mass production and are primarily organized at the upper 20 to 40 cm soil depth; however, these characteristics may fluctuate depending on the soil’s chemical characteristics [6]. Highland rice plants collect a significant quantity of potassium from the soil [7,8]. The yield generated by the K application is not substantially higher compared to that produced by the N and P application, even after taking into consideration the diversity within the varieties [9].

Jia et al. [10] stated that in hydroponics, K absorption, as well as its transport to the shoot parts in rice plants, are regulated by root phenological factors, namely RL, RN, surface area, volume, the number of secondary roots, and the fineness (diameter 0.2 mm) as well as the thickness (diameter > 0.2 mm) of roots. Moreover, they found that compared to the varieties that produced at optimal K levels, K-efficient varieties generated 25% more fine roots at relatively lower potassium rates. Additionally, the potassium-efficient varieties generated 1.5-fold more roots and 1.3 times more surface area in comparison with the inefficient rice genotypes. Moreover, the roots of pea, barley, red clover, rye, perennial ryegrass and oil seed rape all have different root morphologies as a result of lower and moderate K levels [11]. In reaction to lower K concentrations, crops alter the length of their root hairs to sustain the absorption from scarcely dissolved potassium suppliers. Even with limited K availability, root systems can grow greatly to absorb water and minerals [12,13]. Researchers have looked at how K fertilization affects the development of plant roots [14]; however, few studies on upland rice are documented.

Finally, prior research was mostly focused on analyzing how K fertilization affected the upland rice variety’s yielding attributes, yield productivity and quality metrics [9,15]. Moreover, research has also been conducted on how K levels affect the root growth of rice seedlings and lowland rice varieties [16,17]. However, it is crucial to account for this information when adjusting the K rate recommendations for highland rice. Therefore, the current study emphasizes the evaluation of how K levels affect the upland rice variety’s root traits and its connection to yield and yield components.

2. Materials and Methods

2.1. Experimental Site and Plant Materials

The study was carried out under controlled conditions in the net house of the Department of Agronomy, Bangladesh Agricultural University, Mymensingh, Bangladesh (latitude: 24°42′55”, longitude: 90°25′47”) throughout the boro (dry season irrigated) period of 2020–21. The area is under the non-calcareous murky-grim floodplain soil below the Old Brahmaputra Floodplain Agro-ecological Zone (AEZ 9) [18]. Three different boro rice varieties, namely BRRI dhan29 (inbred), Binadhan-10 (inbred) and Hira-2 (hybrid), were selected as research materials based on previous superior findings.

Table 1. Inventory of the three rice varieties employed in this research for root attributes and yield, along with their genetic foundation and parental basis.

Sl. No	Variety	Genetic Source	Parental Origin/Accession Number	Source
1.	BRRI dhan29	Inbred	BG90-2 × BR51-46-5	BRRI
2.	Binadhan-10	Inbred	IR42598-B-B-B-B-12 × Nona Bokra	BINA
3.	Hira-2	Hybrid	-	Local market

lists the specifics of the above-mentioned rice varieties. Figure 1 displays the weather information during the study period in the mentioned area. The physicochemical parameters of the potting soil were examined before starting the experiment and have been shown in

Table 2. Properties of the soil in the pot prior to beginning the trial.

Soil Properties	Values
Textural class	Clay loam
Soil reaction	6.12
Electrical conductance (μs/cm)	649
Organic Carbon (%)	1.028
Total Nitrogen (N) (%)	0.121
Available Phosphorus (ppm)	29.1
Available Potassium (ppm)	84.61
Available Sulphur (ppm)	24.89

.

2.2. Experimental Design and Crop Management

Three replications of the investigation were run using a completely randomized design (CRD). The K levels, K₀-0 kg K ha⁻¹, K₃₂-32 kg K ha⁻¹, K₆₅-65 kg K ha⁻¹, K₉₈-98 kg K ha⁻¹ and K₁₃₀-130 K kg ha⁻¹, were used in the experiment. Fifteen pots per replication were arranged side by side with 15 to 25 cm of space between them. The treatments for each variety were randomly arranged to avoid any biases with placement.

The accumulated soil was sun-dried, grounded, well-mixed and then loaded into each 30 L plastic container (35 cm diameter) at a weight of 25 kg. Fertilizers, namely urea, Triple Super Phosphate (TSP), Gypsum and Zinc sulphate for the pot experiment were applied (AEZ basis) at 8.14 g, 2.5 g, 2.81 g and 0.09 g pot⁻¹, respectively [19]. The fields were fertilized at the end of ploughing, with one-third of urea and whole amounts of other fertilizers. The remaining amount of urea (5.43 g) per pot was applied at 20 and 40 days after transplanting (DAT), respectively. The source of K was Muriate of Potash (MoP), and for K₀-0 kg ha⁻¹ soil, 0 g MoP pot⁻¹ was applied; for K₃₂-32 kg ha⁻¹ soil, 1.6 g MoP pot⁻¹; for K₆₅-65 kg ha⁻¹ soil, 3.25 g MoP pot⁻¹; for K₉₈-98 kg ha⁻¹ soil, 4.9 g MoP pot⁻¹; and for K₁₃₀-130 kg ha⁻¹ soil, 6.5 g MoP pot⁻¹ was applied during the final pot preparation. The chosen varieties of seedlings, which had previously been grown in the seedbed, were transplanted into the pot at a maturity of forty days. At the time of transplanting, there was 4 cm of water in the pot. Prior to harvest, the irrigation was maintained for up to 15 days. Usually, weeds were found across the crop growing times, mainly during the early phases, and plucked by hand pulling. No harmful insect pests were recognized.

2.3. Determination of Root Morpho-Physiological Attributes

Data on root characters were documented at 20, 40, 60 and 80 DAT as well as at the harvest period. A deep dig was used to gently remove three plants from each pot, ensuring that the main tap root and all lateral roots could be safely uprooted. The tested plants were preserved for roughly 12 h in water-filled poly bags. To ensure that no roots were left and to facilitate easy root separation, the roots were thoroughly cleaned using 1 mm mesh sieves, and the recorded data of different attributes were then summed up.

2.3.1. Root Number (RN)

The entire count of roots for each plant in the crown area was numbered and documented.

2.3.2. Root Length (cm)

Root length (RL) was determined at all sampling dates from the core samples [20].

2.3.3. Root Volume (cm³ hill⁻¹)

Root volume (RV) was determined using Archimedes’ law. The root of a single plant was put inside a measuring cylinder filled with water. The water volume was replaced by the RV. The RV was computed as the variation between the water level in the graduated cylinder before and after the roots were added and expressed as cm³ hill⁻¹.

2.3.4. Root Porosity (RP, %)

The roots were kept in sealed polythene bags and conserved in water to safeguard the novel temperature. The pycnometer vials’ weights with and without water were measured, and the temperature of the water containing the vials was taken. For transferring extra water to the blotting paper, tissue paper was utilized to delicately wipe the roots. Using an electric measuring scale, the root weights were taken. The core root samples were submerged in the water containing the vials. To remove the air bubbles, the root samples submerged in the vials were managed with a sterilized needle. After taking the weight of the water and the whole core roots with an electric balance, the roots were collected from the vials and grounded with a glass mortar and pestle to make them homogenous. The total homogenate was loaded into the pycnometer vial to its capacity and weighed after reaching room temperature. The RP was computed using the following equation [21]:

$$\% \mathrm{porosity} =\frac{{\mathrm{W}}_{\mathrm{hr} + \mathrm{w}}-{\mathrm{W}}_{\mathrm{fr} + \mathrm{w}}}{{\mathrm{W}}_{\mathrm{w}}+{\mathrm{W}}_{\mathrm{fr}}-{\mathrm{W}}_{\mathrm{fr} +\mathrm{w}}}$$

Here, W _hr+w indicates the weight of the grounded root samples and the weight of the water containing the vials; W _fr+w indicates the weight of the fresh roots and the water containing the vials; W_w indicates the weight of the water containing the vials; and W_fr indicates the weight of fresh root.

2.3.5. Physiological Traits

Three leaves of the plants were taken, cleaned in water and subsequently dried using tissue paper in order to calculate the LAI. The surface area of the fresh, green leaves was calculated with a leaf area meter (Model LICOR 3000, Lincoln, NE, USA) and reported in cm² plant⁻¹. Extreme care was taken not to overlap any of the leaves when they were being placed on the roller. LAI was estimated using the equation mentioned by Evans [22].

$$\mathrm{LAI}=\frac{\mathrm{Total} \mathrm{leaf} \mathrm{area} \left({\mathrm{cm}}^2\right)/\mathrm{plant}}{\mathrm{Ground} \mathrm{area} \left({\mathrm{spacing} \mathrm{cm}}^2\right)/\mathrm{plant}}$$

Using the formulas outlined by Hunt [23], the crop growth rate (CGR), relative growth rate (RGR), and net assimilation rate (NAR) were estimated based on the plant dry matter accumulation over time.

2.3.6. Crop Growth Rate (g m⁻² day⁻¹)

The CGR was computed with the equation defined as:

$$\mathrm{CGR}=\mathrm{SA} \times \frac{\mathrm{Wii}-\mathrm{Wi}}{\mathrm{Tii}-\mathrm{Ti}}$$

Here, Wi and Wii denote dry weights (g hill⁻¹) during the periods of Ti and Tii, respectively. SA indicates the surface area covered by the hill.

2.3.7. Relative Growth Rate (mg g⁻¹ day⁻¹)

The RGR was determined by the equation defined as:

$$\mathrm{RGR}=\frac{\mathrm{loge} \mathrm{Wii}-\mathrm{loge} \mathrm{Wi}}{\mathrm{Tii}-\mathrm{Ti}}$$

Here, Wi and Wii denote dry weights (g hill⁻¹) during the periods of Ti and Tii, respectively. Loge (Natural log value) = 2.3

2.3.8. Net Assimilation Rate (mg m⁻² day⁻¹)

The Net Assimilation rate (NAR) was estimated using the formula defined as:

$$\mathrm{NAR}=\mathrm{CGR} \times \frac{\mathrm{loge} \mathrm{Lii}-\mathrm{loge} \mathrm{Li}}{\mathrm{Lii}-\mathrm{Li}}$$

Here, Li and Lii indicate the leaf area (m²) during the periods of Ti and Tii, respectively.

The CGR indicates the Crop Growth Rate (g m⁻² day⁻¹).

2.3.9. Total Dry Matter (TDM)

Three hills (plants) were removed per treatment during every growth period. Separated leaves, stems and inflorescences were kept in paper bags and dried in an oven. The weight of the dried materials was measured using an electronic balance, and afterwards, their mean scores (g hill⁻¹) were estimated. The dry masses of the above-mentioned crop organs were added up to determine the total dry matter.

2.3.10. Yield and Yield Components

Data on grain yields and associated attributes, such as plant height (PH), number of effective tiller plant⁻¹ (ET), panicle number (PN), panicle length (PL), grains number panicle⁻¹ (GNP), 1000-grain weight (TGW), grain yield (GY) and straw yield (SY) were documented with the procedures mentioned by Peng et al. [24].

2.4. Statistical Analysis

The analytical program JMP Pro 16 (SAS Institute Inc, North Carolina, America) was employed to perform the two-way analysis of variance (ANOVA) test, and the mean deviations were assessed with Tukey’s honestly significant difference (HSD) post hoc test at the 5% and 1% probability ranges. The dataset visualization and association matrix were constructed using the Sigma Plot v14 (Systat Software, Inc., San Jose, CA, USA, http://www.systatsoftware.com, (accessed on 30 August 2022) and R (R for Windows 4.1.2) [25].

3. Results

3.1. Root Morphological Traits, Total Dry Matter and Leaf Area Index

The RN of the three rice varieties was significantly impacted by the rate of K. At the K₆₅ level, the highest RN was recorded as 43.22, 143.78, 231.33, 358.67 and 359.33, respectively, at 20, 40, 60, and 80 DAT as well as at the harvest stage. It is evident that K₀ had the lowest RN at every observation when compared to other treatments. The RN grew from K₀ to K₆₅, but after that, it declined across all observations. The rice variety has a huge impact on the RN as well. Binadhan-10 generated the highest RN of 39.07, 137.60, 223.07, 351.07, and 352.20 at 20, 40, 60 and 80 DAT as well as at the harvest stage, accordingly. The interaction between K and each variety exerted a significant effect on RN as well (Figure 2). Binadhan-10 yielded the maximum RN of 45.33, 146.67, 235.33, 363.33 and 365.00 at 20, 40, 60 and 80 DAT as well as at the harvest stage, accordingly, along with K₆₅. In the case of Binadhan-10, the RNs at 80 DAT with K₃₂, K₆₅, K₉₈ and K₁₃₀ were 5.21, 11.34, 10.62 and 10.73% greater than with K₀ level, respectively.

Similar to the RN, K had a considerable impact on the RL of all the studied rice varieties as well. The largest RL was observed at the K₆₅ levels of 132.22, 680.78, 1125.83, 1640.44 and 1641.67 cm at 20, 40, 60 and 80 DAT as well as at the harvest stage, accordingly. On the other hand, the lowest RL was noticed at the K₀ level. Binadhan-10 generated the maximum RL of 123.87, 655.53, 1113.90, 1615.60 and 1617.00 cm at 20, 40, 60 and 80 DAT and at the harvest stage, correspondingly. The impact of the interaction between K and each variety also exhibited a substantial influence on the RL (Figure 2). Binadhan-10 with K₆₅ had the highest RL of 135.33, 686.00, 1132.17, 1650.33 and 1652.00 cm at 20, 40, 60 and 80 DAT as well as at harvest time, correspondingly. The RLs with K₃₂, K₆₅, K₉₈ and K₁₃₀ for Binadhan-10 at 80 DAT were 5.49, 8.22, 8.07 and 7.93% higher, respectively, than with K₀ level at 80 DAT.

The RP was significantly affected by the rice varieties and K treatments. The RP was found to be at its maximum level under the K₀ treatment, measuring 16.30, 18.26, 22.36, 25.33 and 25.34% at 20, 40, 60 and 80 DAT as well as at the harvest time. The RP increased with the decrease in K, and it might be due to the development of aerenchyma at the K deficit level. Binadhan-10 produced the greatest value of RP, i.e., 14.16, 14.43, 20.53, 23.14 and 23.1% at 20, 40, 60 and 80 DAT as well as at the harvest time. On the contrary, BRRI dhan29 had the lowest value of RP as 13.48, 16.00, 21.13, 22.64 and 22.66% at 20, 40, 60 and 80 DAT as well as at the harvest time. Binadhan-10 generated the greatest score of RP at the K₀ level as 16.40, 18.46, 22.56, 25.58 and 25.59% at 20, 40, 60 and 80 DAT as well as at the harvest time, accordingly (Figure 2).

When K was added to the three rice varieties, the RV of each variety was greatly enhanced; however, at greater concentrations, it tended to decline regardless of the type of variety. The maximum RV was observed at the K₆₅ level of 0.90, 3.65, 5.62, 8.55 and 8.55 cm³ hill⁻¹ at 20, 40, 60 and 80 DAT as well as at the harvest stage, accordingly. In the case of variety, Binadhan-10 generated the greatest RV of 0.79, 3.52, 5.42, 8.19 and 8.19 cm³ hill⁻¹ at 20, 40, 60 and 80 DAT as well as at the harvest stage, correspondingly. Binadhan-10 with K₆₅ had the highest root volumes of 0.93, 3.70, 5.74, 8.61 and 8.62 cm³ hill⁻¹ at 20, 40, 60 and 80 DAT as well as at the harvest stage, accordingly (Figure 2). The RVs of Binadhan-10 with K₃₂, K₆₅, K₉₈, and K₁₃₀ at 80 DAT were 14.08, 21.27, 20.70 and 20.42% higher, respectively, when compared with the K₀ level.

Figure 3 illustrates the influence of K and the type of variety on the TDM and LAI at several DATs. At 80 DAT, Binadhan-10 exhibited the maximum TDM (24.08 g plant⁻¹) and LAI (4.65), whereas BRRI dhan29 produced the smallest TDM (23.80 g plant⁻¹) and LAI (4.60). Under the K₆₅ treatment, the highest TDM (25.35 g plant⁻¹) and LAI (4.83) at 80 DAT were recorded, while the minimum value was documented at K₀ with the TDM of 19.25 g plant⁻¹ and the LAI of 3.92 at 80 DAT. When considering interactions, Binadhan-10 yielded the biggest TDM (25.37 g plant⁻¹) and LAI (4.85) at 80 DAT under the K₆₅ treatment, whereas BRRI dhan29 generated the smallest TDM (19.03 g plant⁻¹) and LAI (3.88) values.

3.2. Growth Parameters

The values of CGR, RGR and NAR at 20–40 DAT (1st), 40–60 DAT (2nd) and 60–80 DAT (3rd) of the examined varieties were also significantly varied under different K levels. The CGR value was at its minimum during the initial growth phases but reached its peak at 60–80 DAT. Irrespective of varieties and treatments, the RGR was higher at the earlier growth stages and tended to decline as the plant development phases progressed. At 60–80 DAT, BRRI dhan29 produced the greatest (7.71 g m⁻² day⁻¹) CGR score, while the least (7.63 g m⁻² day⁻¹) value was found in Binadhan-10. When considering the K treatments, K₉₈ generated the greatest (7.85g m⁻² day⁻¹) CGR, and K₀ yielded the minimum (7.03 g m⁻² day⁻¹) CGR. When considering the interaction between the varieties and potassium, the biggest CGR (7.93 g m⁻² day⁻¹) was noticed in BRRI dhan29 at K₉₈. BRRI dhan29 produced the biggest (9.98 mg g⁻¹ day⁻¹) RGR value during 60–80 DAT. Under different K treatments, the biggest (11.27 mg g⁻¹ day⁻¹) RGR was found in the K₀ treatment. In the case of the interaction between each variety and K, the greatest RGR (11.34 mg g⁻¹ day⁻¹) was noticed in BRRI dhan29 under K₀ at 60–80 DAT, while the lowest value (9.28mg g⁻¹ day⁻¹) was observed in BInadhan-10 with the K₆₅ treatment (Figure 4). In some cases, BRRI dhan29 with K₃₂ produced the highest CGR, and this might be due to the imbalance of the K application.

The NAR of different rice varieties continued to reduce from 20 to 40 DAT regardless of how often they were measured or how much K was supplied. Moreover, a consistent decline in the NAR was seen from 40 to 60 DAT of the variety. BRRI dhan29 generated the greatest NAR value (0.18 mg cm⁻² day⁻¹) during 60–80 DAT. On the other hand, in the case of K treatment, the greatest NAR score (0.20 mg cm⁻² day⁻¹) was recorded under K₀, but K₆₅ produced the minimum value of RGR (0.16 mg cm⁻² day⁻¹) during 60–80 DAT. When considering interactions, BRRI dhan29 with K₀ generated the greatest NAR score (0.19 mg cm⁻² day⁻¹), while Binadhan-10 produced the minimum value (0.17 mg cm⁻² day⁻¹) under the K₆₅ level at 60–80 DAT (Figure 4).

3.3. Grain Yield and Yield Component of the Rice Varieties

Yield attributes and yield influenced by the rice variety and K levels are presented in

Table 3. Yield components of the three rice varieties at the five K levels.

Variety	PH (cm)	ET (no.)	PL (cm)	GNP	TGW(g)	GY (g pot−1)	SY (g pot−1)	HI (%)
V1	85.87b	10.40b	18.48b	107.53c	23.33b	23.15c	23.30c	49.84
V2	81.47c	11.53ab	19.89ab	111.53b	24.15b	23.42b	23.56b	49.84
V3	92.47a	12.87a	22.19a	115.00a	25.73a	23.86a	24.01a	49.84
Potassium
K0	77.44c	6.56d	14.38d	93.67e	21.77d	18.11d	18.26d	49.80c
K32	87.56ab	11.89c	18.87c	109.00d	25.16b	22.28c	22.44c	49.83b
K65	92.00a	14.67a	24.35a	122.78a	26.58a	26.26a	26.40a	49.86a
K98	89.56ab	13.33b	22.69a	117.67b	25.05b	26.13a	26.28a	49.86a
K130	86.44b	11.56c	20.64b	113.67c	23.44c	24.59b	24.74b	49.85ab
Variety	**	**	**	**	**	**	**	ns
K	**	**	**	**	**	**	**	**
CV (%)	1.12	6.68	3.07	1.30	2.42	0.74	0.72	0.73

The mean values denoted by the identical letters in each column did not vary substantially from one another. According to the analysis of variance, the symbols ** and ns denote significance at the 1% level and non-significance, respectively. V₁ = BRRI dhan29, V₂ = Hira-2, V₃ = Binadhan-10.

. Binadhan-10 yielded the highest values of PH (92.47 cm), ET (12.87 cm), PL (22.19 cm), GNP (115.00 g), TGW (25.73 g) and grain yield (23.86 g pot⁻¹), while BRRI dhan29 yielded the smallest values of all the above-mentioned attributes (Table 3). When considering the K treatments, the K₆₅ level gave the highest values for the parameters PH (92.00 cm), ET (14.67), PL (24.35 cm), GNP (122.78), TGW (26.58 g) and grain yield (26.26 g pot⁻¹), while the smallest readings of these attributes were produced at K₀. Figure 5 displays that yield and yielding parameters were substantially influenced by the interaction between the varieties and K. The maximum values of ET (15.67), PL (26.50 cm), GNP (125.67), TGW (28.03 g) and GY (26.60 g pot⁻¹) were identified in Binadhan-10 at K₆₅, at the same time the lowest values were discovered in BRRI dhan29 at the K₀ level (Figure 5). The grain yield for Biandhan-10 was seen to be 19.89%, 41.79%, 40.88% and 33.26% higher with the K₃₂, K₆₅, K₉₈ and K₁₃₀ levels, respectively, than with K₀.

3.4. Relationship among Root Traits, Growth Indices, Yield and Yield Attributes

Figure 6 depicts the correlation matrix for root traits, growth indices, yield and yield components in order to investigate the relationships among them. The LAI and TDM had a significantly positive relationship with all root traits, apart from RP. The relationship of CGR with LAI and TDM is significantly positive, while for the RGR and NAR, it is negative. The GY, SY, BY and HI showed substantial positive correlations with all root traits, apart from RP. On the other hand, the relationships of GY, SY, BY and HI with CGR were positive and significant, whereas, with RGR and NAR, they were negative. Again, PH, ET, PL, GNP and TGW also had significant and positive relationships with RN, RL and RV, while with RP, there was a negative relationship.

4. Discussion

Numerous crop plants, including alfalfa [26], tomato [27], ramie [28], wheat [29] and barley [30], showed genotypic heterogeneity in potassium utilization efficacy. In low K soils, rice also exhibited genetic variations [31]. According to Shah et al. [32], rice is typically grown using five fertilizers, among which potassium becomes essential for crop development as well as fertility [33]. K deficiency limits plant establishment, root growth and yield [34]. K is needed for the proper functioning of a wide range of enzymes, such as those associated with carbohydrate metabolism, protein biosynthesis and solute transportation. By inhibiting the pathways for anion buildup and electron transfer, it also considerably enhances cell turgor, particularly in rapidly growing cells [35,36]. So, a relationship exists between K and plant roots and yield. Five potassium dosages were used in the current research in order to focus on this issue. In this study, we found that rice varieties and K doses had a substantial impact on root characteristics, growth dynamics and grain yield.

LAI and CGR were highest at 80 DAT and were then reduced regardless of all varieties and treatments, whereas RGR and NAR showed a diminishing trend from the very early stages. The rise in metabolically activated tissues, which provided less support for crop development, is probably responsible for the decline in the RGR. The shadowing of older leaves by upper leaves has also been proposed as a possible factor for the decline in RGR [37]. The NAR represents plant photosynthetic efficiency. At the advanced phases of plant development, the shadowing of the lower leaves, as well as the rise in photosynthetically inefficient older leaves, might be responsible for the decline in the NAR. This study showed that the PH, LAI, CGR, RGR and NAR increased markedly in plants treated with K₆₅ over those with K₀, K₃₂, K₉₈ and K₁₃₀. K is one of the three macronutrients most crucial for crop development and grain output, and its insufficiency in rice fields has emerged as one of the major limitations for enhancing rice plant development. Additionally, prior research has shown that K stress exerts a substantial impact on the physiological mechanism of various rice cultivars [38]. K has the potential to lessen the NH⁴ fixation in the soil and thereby promote the supply of nitrogen. The most likely reason is that K fertilization makes it possible for K ions to fill up non-exchangeable areas and lowers the spaces usable for NH⁴ absorption [39,40], which raises the N level of the soil. The enhanced N supply may boost the PH and the synthesis of dry mass, which in turn, raises the CGR, RGR and NAR.

The ultimate purpose of applying any input to a crop is dry matter production due to its close association with productivity. K is an essential plant nutrient that may contribute to as much as 10% of the plant’s dry matter [41]. It is hypothesized that large sink sizes can be produced by greater dry mass synthesis during the mid-development phases by stimulating grain differentiation, minimizing grain degradation and boosting endosperm cell growth during the initial phases of grain formation [42,43,44,45]. In this study, the TDM linearly increased up to K₆₅ and at 80 DAT; after that, at the harvest stage and at higher doses, it did not increase at all. Binadhan-10 produced the highest TDM at all observations, followed by Hira-2 and BRRI dhan29. Tabatabei et al. [46] reported that the elevated K levels might substantially enhance the TDM during the booting stage because K promotes N assimilation. The results of the current investigation indicated that the dry matter accumulation in rice was greatly boosted by K fertilization. The rise in the net photosynthetic activity, which was associated with greater chlorophyll levels because of K fertilization, might be the reason for the rise in dry matter deposition. Our findings supported the earlier research’s findings that K fertilization might boost chlorophyll concentrations and net photosynthetic rates [47].

In this study, the RN, RL and RV increase linearly up to K₆₅ irrespective of all varieties under all observations. After that, under a high dose of K, the root traits did not increase at all. Binadhan-10 generated the highest RN, RL and RV, followed by Hira-2 and BRRI dhan29 at the K₆₅ level. We found that moderate K concentrations (65 kg ha⁻¹) may encourage root development. In addition, inadequate K input rates substantially impeded root development which might be owing to the increased ethylene production as well as decreased indole-3-acetic acid (IAA) levels in the roots [48]. Root growth inhibition caused by excessive K input, however, might be responsible for the inadequate supply of photosynthates from leaves to roots. In order to maintain equilibrium with anions and osmotic potential, K is the most readily available cation in tissues, and its deficiency decreases the turgor pressure required for root development [49,50] and causes a charge ratio imbalance [51] that inhibits cell growth. Energy and photosynthates are used up during root growth, and the morphological properties of the roots exert a direct influence on the intake of moisture and minerals [52]. The RL, RV, and RN were lower at low K levels, whereas greater K levels resulted in the opposite. This reveals that the rice variety and variations in K levels were closely associated with the morpho-physiological attributes of the roots. The findings are in accordance with those reported for soybean [53], wheat [54] and ryegrass [55].

The value of RP is determined by the degree of aerenchyma growth, which permits the transport of crucial gases from the shoot sections to root parts [56]. The amount and size of aerenchyma in the roots are affected by the various K treatments. In our research, the following varieties produced the highest root porosity at the K₀ level, regardless of all the observations. This could indicate a variety’s ability to cope with adversity. A universal stress hormone that mediates responses to a variety of nutritional deficits is ethylene [57]. Ethylene plays a role in aerenchyma formation signalling [58]. A possible rise in ethylene synthesis based on a lack of potassium [59] may also result in increased aerenchyma formation, which is consistent with our findings.

In this study, the application of more potassic fertilizer raised the K content, which is the potential cause of the rise in plant height. Our findings corroborate with the observations of Zayed et al. [60], who studied inbred and hybrid rice varieties under different K levels and found that elevated K levels substantially promote cell proliferation and elongation, leading to the production of the longest plants. One of the greatest crucial elements of grain yield is the TGW, and greater yields result from heavier grain. K is crucial for synthesizing carbohydrates and the development of grains [61], and hence, a sufficient supply of K exhibited a positive impact on developing heavier rice grains [62]. In our research, grain yield increases linearly from K₀ up to K₆₅. Usually, K fertilization improves several biochemical processes, such as N metabolism, carbohydrate metabolism, enzyme activities, cell growth and development, protein biosynthesis, crop quality, as well as crop resilience to pathogens and insects [63], ultimately leading to an increase in grain yield. The K contribution, which favourably affects all the yield-contributing characteristics of rice plants, may account for the better yield with the increase in K dose [32]. Large amounts of starch are produced due to the increased potassium levels because of K-mediated carbohydrate metabolism. Additionally, it facilitates the effective transfer of photosynthates to growing sinks and grains [64], and it facilitates the use of entirely supplied nitrogen and potassium fertilizers by plants. Thereby, potassium contributes to the production of greater volume and heavier weight in the rice grains and straw. In this research, higher ETH, GNP and higher TDM were noticed in Binadhan-10 compared to BRRI dhan29 and Hira-2. Binadhan-10 ultimately produced higher grain yield over those of BRRI dhan29 and Hira-2. The variation in the productivity of different rice cultivars is thought to be responsible for the differences in their production capacities. Thakur et al. [65] also found identical variations in the productivity of different rice varieties.

The correlation between root traits and growth dynamics in this study was positive and significant. Similarly, the relation between RN, RL and RV with yield attributes was also positive and significant. The exact reason why high–yielding rice cultivars exhibit a superior yielding potential is not fully acknowledged. On the basis of earlier discoveries, several explanations could be offered. Firstly, higher root biomass and deeper root spread were found in high-yield rice. Many studies have claimed that substantial root biomass is needed to enhance a significant amount of above-ground biomass generation [66,67,68,69]. Secondly, high-yielding rice produced more dry matter at the mid-and late-development stages. As per the results, Binadhan-10 had superior root traits, produced more dry matter over Hira-2 and BRRI dhan29 and ranked highest at the K₆₅ level in regards to yield over Hira-2 and BRRI dhan29, which is reliable with the statement above.

Sustainable crop production is a key issue for maintaining soil health and proper resource use efficiency. Because of continuous rice cultivation in Bangladesh, it is crucial to maintain the soil nutrient balance for the proper growth and development of rice crops. Rice roots can uptake nutrients in a proper way if these are available in the root zone with available water. In our study, we observed that Binadhan-10 had the highest root characters with the recommended rate of K in the soil media that finally produced the highest yield, and this is due to the maintenance of soil water and K balance. In earlier studies, rice varieties varied in their reaction to small, reasonable and acceptable levels of K in the growth medium, and the K-efficient variety had a greater root architecture to adjust to a low K condition [10].

5. Conclusions

Based on this investigation, it has been observed that K fertilization has a positive impact on root traits, development indicators and grain output. At K₆₅, the value of RN, RL, RV, LAI, TDM, the yield attributes and the yield reached a peak, and after that, at K₉₈ and K₁₃₀, the value of these traits decreased. The highest values of RN, RL and RV were found at 80 DAT, and then these values were decreased at the harvest stage in most cases. Among the three varieties, Binadhan-10 outperformed others, followed by Hira-2 and BRRI dhan29 according to root traits, development indices and gain output. There was a positive correlation found between root parameters and yield, except for root porosity. The application of K fertilizer improved root characteristics, crop development and yield, although the intensity of such responses differed depending on the variety.