Effect of Herbicidal Weed Control Method on the Yield of T. Aman Rice Varieties

Rice (Oryza sativa L.) is the most extensively cultivated crop and the staple food in Bangladesh. Annual rice production is 37.6 million tons from 11.7 million ha of land, which contributes 11.5% of total GDP (BBS, 2022). However, despite its pivotal role, rice cultivation, particularly the aman rice varieties, frequently faces considerable yield reductions due to weed proliferation (Ali et al., 2022). In Bangladesh, where rice is a staple, weed infestation is a leading problem in rice cultivation (Islam et al., 2017). These weeds compete with rice plants for essential resources such as nutrients, water, and sunlight, leading to significant yield losses estimated at 15% to 60% (Paul et al., 2025; Humaira et al., 2025). Furthermore, uncontrolled weed growth can also reduce grain quality and interfere with harvesting operations, thereby diminishing overall agricultural productivity and economic returns for farmers (Ferdous et al., 2016; Fiza et al., 2024). To mitigate these substantial losses, effective weed management strategies are imperative for sustainable rice production (Sultana et al., 2025; Islam et al., 2025). Various weed control methods, including manual weeding, chemical control with herbicides, and integrated approaches, have been developed to address this persistent challenge (Ferdous et al., 2016; Mia et al., 2024). Among these, chemical control utilizing herbicides has gained prominence due to its efficiency in managing diverse weed populations and reducing labor requirements, particularly in direct-seeded rice systems where weeds present a major hindrance (Janghel et al., 2025).

However, the singular application of herbicides often falls short of achieving complete weed eradication, necessitating integrated approaches that combine pre-emergence and post-emergence herbicide applications, sometimes supplemented by manual weeding (Ali et al., 2022; Shahabuddin et al., 2016). For instance, sequential applications of pendimethalin as a pre-emergence herbicide followed by bispyribac sodium 10 SC as a post-emergence treatment have demonstrated significant inhibition of diverse weed types, leading to higher paddy yields (Chandra and Walia, 2025). Similarly, research has shown that applying bispyribac acid 40% SC at 70 g a.i ha^-1 at 10 DAT, followed by two hand weedings at 20 and 40 DAT, significantly enhances plant height, leaf area index, and dry matter production, ultimately resulting in increased grain and straw yields (Suseendran et al., 2017). This multi-faceted approach underscores the necessity of integrating various control mechanisms to achieve optimal weed suppression and maximize agricultural output in rice cultivation (Choudhary et al., 2025). Despite the advancements in herbicidal weed control, exclusive reliance on chemical methods is often insufficient and can lead to the evolution of herbicide-resistant weed biotypes, thereby necessitating a broader integrated weed management framework (Butts et al., 2022; Matloob et al., 2014). This issue is particularly pronounced in regions heavily reliant on chemical controls, where intensive herbicide use has driven the selection for resistant weed populations and altered weed community structures (Kumar et al., 2021). Therefore, a comprehensive integrated weed management strategy, incorporating cultural, mechanical, and chemical methods, is crucial for sustainable rice production (Ali et al., 2024). Such an integrated approach optimizes control efficacy, minimizes environmental impact, and mitigates the development of herbicide resistance, thereby ensuring long-term agricultural viability (Dhakal and Poudel, 2020; Singh, 2018).

The continuous use of pre-emergence herbicides at high doses can lead to a shift in weed flora and the development of herbicide resistance, necessitating the incorporation of post-emergence herbicides for broader-spectrum control (Rathika et al., 2020). This emphasizes the importance of tank-mixing different herbicides to target a wider array of weed species and reduce the selection pressure for resistance (Ashraf et al., 2018). Integrated weed management strategies, incorporating both pre-emergence and post-emergence herbicides alongside other control methods, are essential for effective, broad-spectrum weed control in transplanted rice (Ahmed et al., 2021; Chaudhary and Dhakal, 2023). Therefore, this experiment was conducted to evaluate how different herbicidal weed control and hand weeding methods affect weed dynamics and yield of transplanted aman rice. The study focused on weed composition, density, and dry weight, as well as comparing the efficiency of different control methods on crop growth and yield. The findings aim to support practical and effective weed management strategies for improving rice productivity.

Experimental Location

The field experiment was carried out at the Agronomy Field Laboratory of Bangladesh Agricultural University, Mymensingh (24.75° N latitude and 90.50° E longitude, 18 m above sea level) from July to November 2022.

Experimental Soil and Climate

The soil of the experimental field belongs to the Old Brahmaputra Alluvium under AEZ-9. The land was medium-high, with a silt loam texture and a pH of 6.8. The area experiences a subtropical climate, characterized by hot, humid, and rainy conditions from April to September, and cooler, drier weather from October to March. Detailed soil physicochemical properties and weather data are presented in Table 1 and Figure 1.

Table 1. Physiochemical composition of the initial soil (0-15 cm depth) at the research area.

Figure 1. Monthly average temperature (°C), humidity (%), rainfall(mm) and sunshine (hrs) during July to November 2022.

Experimental treatment and design

The experimental treatments included two varieties, viz. BR11 (V₁), BRRI dhan49 (V₂) and six herbicidal weed control methods viz. control (T₁), hand weeding at 25DAT (T₂), application pre-emergence herbicide (Superhit 500 EC) (T₃), application pre-emergence herbicide with one hand weeding at 35 DAT (T₄), application post emergence herbicide (Livina 18 WP) (T₅), application post emergence herbicide with one hand weeding at 35 DAT (T₆). The trial followed the RCBD method and was replicated thrice. 36 plots in all, each measuring 2.5 m by 2.0 m and spaced 0.5 m within units and 1.0 m between blocks, were set up in a 2 × 6 × 3 configuration. The treatments were randomly allocated to each plot.

Crop Husbandry

Rice seeds were collected from the Bangladesh Rice Research Institute (BRRI), Joydebpur, Gazipur. The land was prepared with two power-tiller ploughings 15 days before transplanting, followed by additional plowing, cross-plowing, and ladder leveling. Experimental plots were then laid out according to the design and treatments. Recommended fertilizers: urea (150 kg ha^-1), TSP (100 kg ha^-1), MoP, gypsum (70 kg ha^-1), and zinc sulfate (10 kg ha^-1) were applied, with TSP, MoP, and gypsum incorporated during final land preparation. Urea was applied in three splits at 15, 30, and 45 DAT. Sprouted seeds were sown on July 1, 2022, in a well-prepared seedbed. Thirty-one-day-old seedlings were transplanted on August 1, 2022, using two seedlings per hill in well-puddled soil. Intercultural operations such as gap filling, weeding, irrigation, and drainage were carried out as needed to ensure normal crop growth. Missing hills were replanted within seven days. Pest infestation was minimal; however, Basudin was applied at 17 kg ha^-1 during the tillering stage, and Diazinon 60 EC at 850 ml ha^-1 to control rice bugs and stem borers. The crop was harvested on November 15, 2022, when about 90% of the grains turned golden yellow. Plants from each plot were harvested, bundled, tagged, and sun-dried to constant weight before recording grain and straw yields.

Collection and Calculation of Data

Weed data were recorded at 50 DAT using two 1 m² quadrats per plot, leaving the central area untouched for yield measurement. Weeds inside each quadrat were identified, counted, and expressed per m². They were then uprooted, cleaned, sun-dried, oven-dried at 60°C for 72 hours, and weighed to determine dry biomass (g m^-2). Data on rice growth (plant height, number of total tillers hill^-1, number of effective tillers hill^-1, number of non-effective tillers hill^-1), yield, and yield components (grains panicle^-1, sterile spikelets panicle^-1, grain yield, straw yield, biological yield, harvest index) were collected from sample plots. Yield-related data were recorded from randomly selected plants in each plot. The following formula calculates harvest index:

Harvest index =  × 100

Statistical analysis

The analysis of variance (ANOVA) technique was used to examine all of the data that was gathered, and Duncan's Multiple Range Test (DMRT) (Gomez and Gomez, 1984) was used to determine the mean differences using MSTAT-C and R.

Infested Weed Species

Table 2: Weed species found in the experimental plots in transplanted aman rice

Weed density and dry weight

Effect of variety

The total number of weeds varied significantly due to varietal treatments (Table 3). It was observed that the total number of weeds (19.54) was higher in V₂ at 50 DAT. However, the total number of weeds (14.58) was lower in V₁ at 50 DAT. The maximum dry weight (3.49 g m^-2) was found in V₂, while the minimum (2.99 g m^-2) was in V₁.

Figure 2. Effect of variety on weed density and weed dry weight of T. aman rice. V₁ = BR11, V₂ = BRRI dhan49

Table 3: Effect of variety on weed density and weed dry weight

** = Significant at 1% level of probability, NS = Not significant

Effect of herbicidal weed control method

The total number of weeds varied significantly due to various weed control treatments. The highest number of weeds (30.56) was recorded in T₁ (No Weeding), and the lowest number of weeds (5.513) was recorded in T₄ (Table 4). The total number of weeds was highest in unweeded treatments, and the lowest weed population was recorded in pre-emergence herbicide with one hand weeding treatment. There was a significant effect of weeding treatment on total weed dry weight (g m^-2) at 50 DAT. At 50 DAT, the highest weed dry weight (5.06 gm^-2) was observed in the T₁ (no weeding) treatment. The lowest dry weight (1.12 g m^-2) was observed in the T₄ (Application of pre-emergence herbicide with 1 hand weeding at 35 DAT) treatment.

Figure 3. Effect of different treatments on weed density and weed dry weight. Where, T₁ = No weeding, T₂ = Hand weeding at 25 DAT, T₃ = Application of pre-emergence herbicide (Superhit 500 EC), T₄ = Application of pre-emergence herbicide with 1 hand weeding at 35 DAT, T₅ = Application of post-emergence herbicide (Livina 18 WP), T₆ = Application of post-emergence herbicide with 1 hand weeding at 35 DAT

Table 4. Effect of herbicidal weed control method on weed density and weed dry weight of T. aman rice

** = Significant at 1% level of probability. All other details are as described in Figure 3.

Interaction effect of variety and herbicidal weed control method

The interaction effect of variety and weed control treatments had a significant effect on the total number of weeds in T. aman rice fields. It was observed that the treatment combination V₁T₁ (BR11 × No Weeding) resulted in the highest (27.62) total number of weeds, which was statistically similar to V₂T₆ (BRRI dhan49 × Application of post-emergence herbicide with 1 hand weeding at 35 DAT). However, the combination of V₁T₄ (BR11 ×Application of pre-emergence herbicide with 1 hand weeding at 35 DAT) showed the lowest (4.48) total number of weeds, which was statistically similar to V₁T₃ (BR11 × Application of pre-emergence herbicide), V₂T₄ (BRRI dhan49 × Application of pre-emergence herbicide with 1 hand weeding at 35 DAT) (Table 5).

A significant effect was observed on weed dry weight at 50 DAT due to the interaction effect of variety and the herbicidal weed control method. At 50 DAT, the highest weed dry weight (5.38g m^-2) was observed in V₂T₁ (BRRI dhan49 × no weeding) treatment, and the lowest weed dry weight (0.84 g m^-2) was observed in V₁T₄ (BR11 × Application of pre-emergence herbicide with 1 hand weeding at 35 DAT) treatment (Table 5).

Table 5: Combined effects of variety and herbicidal weed control method on weed density and weed dry weight of T. aman rice

All other details are as described in Figures 2 and 3.

Yield and Yield Contributing Character at Harvest

Effect of variety

Plant height varied significantly due to varietal treatments. The higher plant height (106.91 cm) was observed in V₁, and the lower plant height (99.59 cm) was observed in V₂. The varietal treatment significantly influenced the number of total tillers hill^-1. The higher number of total tillers hill^-1 (10.42) was observed in V₁, and the lower number of total tillers hill^-1 (9.94) was observed in V₂. The varietal treatment significantly influenced the number of effective tillers hill^-1. The higher number of effective tillers hill^-1 (9.01) was recorded in V₁, and the lower number of effective tillers hill^-1 (8.7) was recorded in V₂. The number of non-effective tillers hill^-1 was not significantly influenced by variety (Table 6).

The varietal treatment significantly influenced the number of grains panicle^-1. The higher number of grains panicle^-1 (107.27) was observed in V₁, and the lower number of grains panicle^-1 (90.61) was observed in V₂. The varietal treatment significantly influenced the number of sterile spikelets panicle^-1. The higher number of sterile spikelets panicle^-1 (15.22) was observed in V₁. The lower number of sterile spikelets panicle^-1 (8.77) was observed in V₂ (Table 6). The varietal treatment significantly influenced the weight of 1000 grains. The higher weight of 1000 grains (26.27 gm) were observed in V₁, and the lower weight of 1000 grains (19.62 gm) was observed in V₂. The varietal treatment significantly influenced the grain yield. The higher (5.65 t ha^-1) grain weight obtained from V₁ was mainly due to the favorable effect of the highest number of grains panicle^-1 (107.27) and other yield attributes, and the lower (5.22 t ha^-1) grain weight obtained from V₂. This difference was observed due to different rice plant cultivar characteristics. The varietal treatment significantly influenced the straw yield. The higher (7.45 t ha^-1) straw yield was observed in V₁, and the lower (6.63 t ha^-1) straw yield was observed in V₂. The varietal treatments significantly influenced the biological yield. The higher (13.11 t ha^-1) biological yield was observed in V₁, and the lower (11.86 t ha^-1) yield was observed in V₂. The varietal treatment significantly influenced the harvest index. The higher (45.06%) harvest index was observed in V₁, and the lower (44.02%) harvest index was observed in V₂

Figure 5. Effect of variety on yield and yield-contributing characters of T. aman rice at harvest. All other details are as described in Figure 2.

Effect of herbicidal weed control method

Plant height was significantly influenced by different weed control methods. It was observed that T₂ treatment produced the tallest plant (104.22 cm), which was statistically identical to T₅ and T₆. The lowest plant height (101.34 cm) was observed in T₁. Among the different weed control methods, the highest number of total tillers hill^-1 (11.4) was observed in T₄, which was statistically similar to T₃. The T₁ treatment gave the lowest number of total tillers hill^-1 (8.83). No weeding treatment failed to produce more tillers due to severe weed infestation in the experimental plots. The highest (9.72) number of effective tillers hill^-1 was obtained in T₄ treatment, which was statistically similar to T₃, and T₁ treatment produced the lowest (8.22) number of effective tillers hill^-1. The highest number of non-effective tillers (1.72) was obtained by the treatment, which was statistically similar to T₂ and T₃, and the lowest number of non-effective tillers (0.61) was obtained from the T₁ treatment (Table 7). The highest number of grains panicle^-1 (105.91) was obtained in the T₄ treatment, which was statistically similar to T₂, and the lowest number of grains panicle^-1 (92.87) was observed in the T₁ treatment. The highest number of sterile spikelets panicle^-1 (12.73) was obtained from the T₂ treatment. The lowest number of sterile spikelets panicle^-1 (11.19) was observed in the T₆ treatment (Table 7). The 1000-grain weight was highest (23.1 g) in the T₄ treatment and lowest (22.72 g) in the T₆ treatment. The highest (5.88 t ha^-1) grain yield was obtained from the treatment, which was statistically similar to T₆. The lowest (4.88 t ha^-1) grain yield was obtained from the T₁ treatment. The highest (8.25 t ha^-1) straw yield was obtained from the T₄ treatment. Significantly, the lowest straw yield (6.22 t ha^-1) was obtained from the T₁ treatment. Straw yield increased with weed-free conditions, as weed-free conditions increased plant growth. The highest (14.13 t ha^-1) biological yield was observed in the T₄ treatment. The T₁ treatment produced the lowest (11.11 t ha^-1). The highest (47.45%) harvest index was observed in the T₁ treatment. The lowest harvest index (41.45%) was observed in treatment T₄. 

Figure 6. Effect of herbicidal weed control method on yield and yield-contributing characters of T. aman rice at harvest. All other details are as described in Figure 3.

Interaction effect of variety and herbicidal weed control method

The highest plant height (108.33cm) was observed in the V₁T₆ treatment, which was significantly similar to V₁T₁, V₁T₂, V₁T₃, and V₁T₅. The lowest plant height (95.67) was observed in the V₂T₁ treatment. The highest number of total tillers hill^-1 (11.7) was observed in V₁T₄, and the lowest number of total tillers hill^-1 (8.66) was observed in V₂T₁. The highest number of effective tillers hill^-1 (9.99) was recorded in V₁T₄, which was statistically identical to V₁T₃, and the lowest number of effective tillers hill^-1 (7.88) was recorded in V₂T₁. The highest number of non-effective tillers hill^-1 (2.22) was observed in V₁T₅. The lowest number of non-effective tillers hill^-1 (0.44) was observed in V₁T₁ (Table 8). The highest number of grains panicle^-1 (115.07) was observed in the V₁T₂ treatment, which was statistically similar to V₁T₄. The lowest number of grains panicle^-1 (85.32) was observed in the V₂T₁ treatment, which was statistically similar to V₂T₃ and V₂T₆. The highest number of sterile spikelets panicle^-1 (17.13) was observed in V₁T₂. The lowest number of sterile spikelets panicle^-1 (8.33) was observed in the V₂T₂ treatment (Table 8). The highest weight of 1000 grains (26.42 gm) were observed in the V₁T₅ (BR11 × Application of post-emergence herbicide Livina 18 WP) treatment. The lowest weight of 1000 grains (19.42 g) was observed in V₂T₆ treatment.

The highest grain weight (6.19 t ha^-1) was observed in V₁T₄. The lowest grain weight (4.77 t ha^-1) was observed in V₂T₁ (BRRI dhan49 × No weeding), which was statistically similar to V₁T₁ and V₂T₅. The interaction of variety and different weed control methods had a significant influence on straw yield. The highest straw yield (9.43 t ha^-1) was observed in V₁T₄. The lowest straw yield (5.98 t ha^-1) was observed in V₂T₁. The interaction of variety and different weed control methods had a significant influence on biological yield. The highest (15.62 t ha^-1) biological yield was observed in V₁T₄, and the lowest (10.75 t ha^-1) biological yield was observed in V₂T₁. The interaction of variety and different weed control methods had a significant influence on harvest index. The highest harvest index (50.54%) was observed in V₁T₁, and the lowest harvest index (39.64%) was observed in V₁T₄.

PCA, Heatmap and Correlation analysis

The PCA biplot (Figure 7) explained 78.5% of total variation (Dim1 = 56.1%, Dim2 = 22.4%), clearly separating weed management treatments and their effects. Treatments under no weeding (T₁) clustered with higher weed density (WD) and weed dry weight (WDW), indicating strong weed pressure. In contrast, integrated approaches, especially pre-emergence herbicide combined with hand weeding (T₄) and post-emergence herbicide plus hand weeding (T₆), were positioned opposite weed traits and aligned with yield-related variables (GY, BY, SY), suggesting better crop performance. T₃ and T₅ showed moderate effects, lying between extremes. The strong vector alignment of yield traits confirms their positive association. Overall, integrated weed management significantly improves productivity by effectively suppressing weeds.

The correlation matrix reveals clear agronomic patterns among weed traits and yield components (Figure 8). Weed density (WD) and weed dry weight (WDW) show a strong positive association, indicating consistent weed pressure buildup. Both WD and WDW are negatively correlated with key productivity traits (TT, ET, GY, SY, BY), confirming that higher weed burden suppresses crop performance. Growth parameters such as GP, PH, and SSP exhibit strong positive interrelationships and are positively linked with yield traits, suggesting their combined contribution to productivity. Notably, TT and ET show significant positive correlations with grain and biological yield, highlighting their importance in yield formation. Overall, effective weed management treatments (e.g., integrated herbicide + hand weeding) likely enhance growth traits, thereby improving yield outcomes.

The clustered heatmap highlights distinct treatment-driven patterns in weed suppression and crop performance (Figure 9). Treatments combining herbicides with hand weeding (T₄ and T₆) group closely and show strong positive associations (green) with growth and yield traits (GP, PH, TGW, GY, SY, BY), indicating superior crop performance. In contrast, the no-weeding treatment (T₁) clusters separately and is strongly associated with higher weed density (WD) and weed dry weight (WDW), while showing negative relationships with yield attributes. Sole herbicide applications (T₃ and T₅) are moderately effective but remain inferior to integrated approaches. The clustering pattern clearly demonstrates that integrated weed management enhances yield-linked traits while minimizing weed pressure, supporting its adoption for sustainable productivity improvement.

 
Figure 7. Principal Component Analysis illustrating the combined influence of rice variety and herbicide-based weed management on weed dynamics and yield-attributing traits in T. aman rice. Where, WD=Weed density, WDW= Weed dr weight, PH= Plant height, TT=Total tiller, ET= Effective tiller, NET= Noneffective tiller, GP= Grain panicle^-1, SSP= Sterile spikelet panicle^-1, TGW= 1000 grain wight, GY= Grain yield, SY= Straw yield, BY= Biological yield, HI= Harvest index. All other details are as described in Figures 2 and 3.

Figure 8. Correlation matrix depicting relationships among weed parameters and yield-contributing traits under different varietal and herbicidal weed control treatments in T. aman rice. All other details are as described in Figures 2, 3 and 7.

Figure 9. Heatmap visualization of treatment-wise interactions between rice varieties and herbicide strategies affecting weed dynamics and yield-related attributes in T. aman rice. All other details are as described in Figures 2, 3 and 7.

This study clearly demonstrates that weed management practices and rice variety choices are pivotal in determining weed populations and yield outcomes in transplanted aman rice. The markedly higher weed density and dry biomass in the no-weeding treatment highlight the intense competitive effects from a wide range of weed species in rice fields. This intense competition for resources light, water, and nutrients directly translates into reduced growth and development for the rice crop, ultimately leading to significant yield penalties (Verma et al., 2023). Among the weed control strategies tested, the integrated approach combining pre-emergence herbicide with hand weeding was most effective at reducing weed density and biomass.  This efficacy is attributed to the herbicide's initial suppression of weed germination and early growth, complemented by hand weeding that addresses escaped weeds and later-emerging flushes, thereby minimizing competition throughout critical growth stages (Roy et al., 2017). In particular, treatments combining pre-emergence herbicide application with hand weeding, such as pretilachlor followed by one manual weeding, consistently produced the highest grain, straw, and biological yields while minimizing weed biomass, in direct contrast to unweeded controls that exhibited the lowest productivity across these parameters (Shahabuddin et al., 2016).

Although sole herbicide applications exhibited moderate efficacy in weed suppression, they proved inadequate for providing season-long control, resulting in elevated weed densities and diminished yields relative to integrated management approaches. This outcome suggests that while herbicides offer an initial advantage, the prolonged weed-free period critical for optimal rice development necessitates a multifaceted strategy (Sahu et al., 2020). This integrated strategy optimizes resource allocation for the rice crop, leading to enhanced physiological processes and ultimately greater yield potential (Arthanari, 2023; Popy et al., 2017). This finding corroborates previous research indicating that a single herbicide application often falls short in fully managing weed infestations throughout the entire cropping cycle, underscoring the need for supplemental control measures (Akter et al., 2020; Parthipan and Ravi, 2014).

Significant varietal differences influenced weed infestation and yield performance. Compared to BRRI dhan49, BR11 exhibited lower weed density and superior yields, owing to its enhanced competitive ability, taller stature, and greater tillering. BR11's higher yields stemmed primarily from increased grains per panicle and elevated 1000-grain weight, highlighting its strong genetic potential under effective weed management. These findings are consistent with earlier reports demonstrating that cultivar selection significantly modulates crop-weed interference and yield stability in varied agricultural contexts (Afroz et al., 2019; Hossen, 2020). Significant variety × weed management interactions were observed. BR11 with integrated control (T₄) produced the highest grain yield (6.19 t ha^-1) from the V₁T₄ interaction, reflecting strong synergy that minimized weed competition and maximized yield traits. In contrast, BRRI dhan49 without weeding (V₂T₁) gave the lowest yield, due to poor competitive ability against weeds. This synergistic effect underscores the importance of matching appropriate weed management practices with high-performing cultivars to optimize agricultural productivity and resource use efficiency (Ferdous et al., 2016). This observation underscores the necessity of considering genotypic traits in conjunction with specific weed control interventions to achieve maximal agronomic benefits. 

Multivariate analyses demonstrated that elevated weed density and dry weight markedly suppress yield, whereas enhanced crop growth traits boost productivity (Acharya et al., 2026). The clustering patterns validated that integrated treatments excel in weed suppression and overall crop performance enhancement. Specifically, treatments combining pre-emergence herbicides with subsequent mechanical or manual weeding consistently exhibited superior yield parameters, which is congruent with findings from similar studies (Dolie et al., 2023; Negalur and Halepyati, 2016). This is further supported by observations that integrated approaches incorporating both pre-emergence and post-emergence herbicides, especially when supplemented with hand-weeding, achieve superior broad-spectrum weed control compared to single-application strategies (Verma et al., 2025).

The integration of pre-emergence herbicide application and hand weeding, particularly when combined with the BR11 rice variety, substantially improves yield attributes and promotes sustainable weed suppression.  This comprehensive approach optimizes resource allocation for the rice crop, leading to enhanced physiological processes and ultimately greater yield potential. Such integrated management practices not only mitigate the immediate impact of weed competition but also contribute to long-term agricultural sustainability by reducing reliance on single-tactic interventions and fostering healthier agroecosystems (Joshi et al., 2016).

The findings demonstrate that effective weed management is essential for sustaining transplanted aman rice productivity under field conditions. The treatment T₄ (pre-emergence herbicide + one hand weeding at 35 DAT) was the most effective, producing the highest grain yield (5.88 t ha⁻¹) with the lowest weed density (5.51 m^-2). In contrast, T₁ (no weeding) resulted in severe yield loss (4.88 t ha^-1) due to intense weed competition. Among varieties, BR11 performed better than BRRI dhan49, and the interaction V₁T₄ (BR11 × T4) achieved the maximum yield (6.19 t ha^-1). Therefore, adopting such integrated strategies can enhance yield stability, reduce labor constraints, and support sustainable rice production in Bangladesh and similar agro-ecological regions.

Acharya, M., Yadav, S. P. S., Mehata, D. K., Bhandari, N., Khatri, R. and Mainali, R. P. 2026. Multivariate analysis of cucumber (Cucumis sativus L.) landraces in central Nepal. Electron. J. Plant Breed. 17: 113-124 https://doi.org/10.37992/2026.1702.021

Afroz, R., Salam, Md. A. and Begum, M. 2019. Effect of weeding regime on the performance of boro rice cultivars. J. Bangladesh Agric. Univ. 17: 265-273. https://doi.org/10.3329/jbau.v17i3.43192

Ahmed, S., Kumar, V., Alam, M., Dewan, M. R., Bhuiyan, K. A., Miajy, A. A., Saha, A., Singh, S. S., Timsina, J. and Krupnik, T. J. 2021. Integrated weed management in transplanted rice: options for addressing labor constraints and improving farmers’ income in Bangladesh. Weed Technol. 35: 697-709. https://doi.org/10.1017/wet.2021.50

Akter, M., Rasul, S. and Salam, M. A. 2020. Effect of integration of herbicide with manual weeding on the performance of transplant aman rice cultivars. J. Bangladesh Agric. Univ. 18: https://doi.org/10.5455/jbau.81118

Ali, M. A. Islam, M. Kabiraj, M. Sarker, U. K. Zaman, F. and S. K. Paul. 2024. Effects of weed control treatments on Boro rice and associated weeds. Int. J. Life Sci. Agric. Res., 3: 1026-1036. https://doi.org/10.55677/ijlsar/V03I12Y2024-17

Ali, M. I., Monira, S., Rashed, M., Salim, M., Salam, M. A. and Das, R. C. 2022. Effects of herbicidal weed control practices on yield performance of T. aman rice varieties in Bangladesh. J. Agrofor. Environ. 15: 14-20. https://doi.org/10.55706/jae1513

Arthanari, P. M. 2023. Weed management with Triafamone herbicide in transplanted rice ecosystem. Emir. J. Food Agric. 35: 351-356. https://doi.org/10.9755/ejfa.2023.v35.i4.3027

Ashraf, U., Hussain, S., Sher, A., Abrar, M., Khan, İ. and Anjum, S. A. 2018. Planting geometry and herbicides for weed control in rice: implications and challenges. IntechOpen. https://doi.org/10.5772/intechopen.79579

Butts, T. R., Kouame, K. B., Norsworthy, J. K. and Barber, L. T. 2022. Arkansas Rice: Herbicide resistance concerns, production practices, and weed management Costs. Front. Agron. 4. 881667. https://doi.org/10.3389/fagro.2022.881667

Chandra, G. S. and Walia, U. S. 2025. Role of planting patterns and weed control treatments on growth and yield of unpuddled transplanted rice (Oryza sativa L.). Agric. Sci. Dig. 1-5. https://doi.org/10.18805/ag.d-6231

Chaudhary, R. S. and Dhakal, S. 2023. Weed management in pulses: overview and prospects. IntechOpen. https://doi.org/10.5772/intechopen.110208

Choudhary, V. K., Sahu, M. P., Dubey, R. P., Singh, R. and Mishra, J. S. 2025. Assessment of seed rate and weed management practice on weed control, crop productivity and profitability of dry direct-seeded rice. J. Agric. Food Res. 22: 102110. https://doi.org/10.1016/j.jafr.2025.102110

Dhakal, A. and S. Poudel. 2020. Integrated pest management (IPM) and its application in rice: A review. Rev. Food Agric., 1: 54-58. https://doi.org/10.26480/rfna.02.2020.54.58

Dolie, S., Nongmaithem, D., Jamir, M., Mohan, G., Tzudir, L. and Singh, A. P. 2023. Date of transplanting and integrated weed management effects on growth and yield of black rice (Oryza sativa L.) under SRI. Indian J. Agric. Res. 59: 571-575. https://doi.org/10.18805/ijare.a-6075

Ferdous, J., Islam, N., Salam, M. A. and Hossain, M. 2016. Effect of weed management practices on the performance of transplanted aman rice varieties. J. Bangladesh Agric. Univ. 14: 17. https://doi.org/10.3329/jbau.v14i1.30591

Fiza, F., Begum, M., Mia, M. L., Das, B., Ahmed, S., Shimo, F. J., Tanim, K. M. Y., Datta, P., Talukder, S. K. and M. S. Islam. 2024. Weed management and yield performance of T. aman rice as influenced by Artocarpus heterophyllus leaf residues. Asian J. Crop Soil Sci. Plant Nutr., 10: 387-394. https://doi.org/10.18801/ajcsp.100124.47

Hossen, K. 2020. Assessment of different weed control methods on growth and yield performance of T. aus rice. Agric. Res. Technol. Open Access J. 24: 556267 https://doi.org/10.19080/artoaj.2020.24.556267

Humaira, Z. Sarker, B. Hossen, M. Pinkya, S. Z. S. Onna, K. A. M. Zaman, F. and M. S. Islam. 2025. Weed growth observation in transplant aman rice field as influenced by the organic manures and fertilizers with rice straw allelopathy. Asian Plant Res. J., 13: 35-45. https://doi.org/10.9734/aprj/2025/v13i2299

Islam, M. S., Hossain, M. R., Shammy, U. S., Joly, M. S. A., Shikder, M. M. and Mia, M.L. 2024. Integrated effect of manures and fertilizers with the allelopathy of Fimbristylis dichotoma (L.) on the yield performance of rice. Int. J. Multidiscip. Res. Growth Eval., 5: 333-340. https://doi.org/10.54660/.IJMRGE.2024.5.2.333-340

Islam, M. J. Islam, M. S. Mia, M. L. Uddin, M. R., Rahman, M. R. and M. A. Salam. 2025. Influence of water management and weeding practices on the growth and yield of Boro rice (cv. BRRI dhan29). IKR J. Agric. Biosci., 1: 215-228. https://doi.org/10.5281/zenodo.17641047

Janghel, P., Sahu, S. K., Thakur, A. K., Chandrakar, T., Singh, D. P., Masali, H., Parvathi, S. and Shailesh. 2025. Efficacy of herbicides on weed dynamics and yield of direct seeded rice (Oryza sativa L.). Int. J. Res. Agron. 8: 106-109. https://doi.org/10.33545/2618060x.2025.v8.i8b.3501

Joshi, N., Singh, V. and Dhyani, V. C. 2016. Effect of different planting geometry and herbicides for controlling the weeds in direct seeded rice. J. Appl. Nat. Sci. 8: 2203-2205. https://doi.org/10.31018/jans.v8i4.1112

Kumar, V., Bana, R. S., Singh, T. and Louhar, G. 2021. Ecological weed management approaches for wheat under rice–wheat cropping system. Environ. Sustain. 4: 51-61. https://doi.org/10.1007/s42398-020-00157-3

Matloob, A., Khaliq, A. and Chauhan, B. S. 2014. Weeds of direct-seeded rice in Asia: problems and opportunities. In Advances in agronomy (p. 291). Adv. Agron. 127: 291. https://doi.org/10.1016/bs.agron.2014.10.003

Mia, M. L. Hossain, M. D. Islam, M. S. Hasan, A. K. and M. A. Salam. 2024. Assessment of crop establishment method and weed management practices on the growth performance of T. aman rice. Rev. Food Agric., 5: 47-53. https://doi.org/10.26480/rfna.01.2024.47.53

Negalur, R. B. and Halepyati, A. S. 2016. Weed control efficiency and weed index as influenced by weed management practices in machine transplanted rice (Oryza sativa L.). J. Appl. Nat. Sci. 8: 1947-1952. https://doi.org/10.31018/jans.v8i4.1068

Parthipan, T. and Ravi, V. 2014. Productivity of transplanted rice as influenced by weed control methods. Afr. J. Agric. Res. 11: 1445-1449. https://doi.org/10.5897/ajar2013.7217

Paul, S., Nath, B., Huda, Md. D., Bhuiyan, M. G. K. and Paul, H. 2025. Assessment of mechanical weeders in paddy fields: A study on operational effectiveness in Bangladesh. Heliyon 11: e42639. https://doi.org/10.1016/j.heliyon.2025.e42639

Popy, F. S., Islam, A. K. M. M., Hasan, A. K. and Anwar, Md. P. 2017. Integration of chemical and manual control methods for sustainable weed management in inbred and hybrid rice. Bangladesh Agric. Univ. 15: 158-166. https://doi.org/10.3329/jbau.v15i2.35057

Rathika, S., Ramesh, T. and Shanmugapriya, P. 2020. Weed management in direct seeded rice: A review. Int. J. Chem. Stud. 8: 925. https://doi.org/10.22271/chemi.2020.v8.i4f.9723

Roy, P. C., Sarkar, M. A. R. and Paul, S. K. 2017. Yield and Grain Protein Content of Aromatic Boro Rice (cv. BRRI dhan50) as Influenced by Integrated Fertilizer and Weed Management. Int. J. Appl. Sci. Biotechnol. 5: 51-58. https://doi.org/10.3126/ijasbt.v5i1.17008

Sahu, R., Kumar, D., Sahu, J., Sharda, K. and Sohane, R. 2020. Bio-efficacy of pre and post-emergence herbicides for control of complex weed flora in transplanted rice (Oryza sativa L.). Int. J. Chem. Stud. 8: 2348. https://doi.org/10.22271/chemi.2020.v8.i2aj.9100

Shahabuddin, M., Hossain, M., Salim, M. and Begum, M. 2016. Efficacy of pretilachlor and oxadiazon on weed control and yield performance of transplant aman rice. Prog. Agric. 27: 119-127. https://doi.org/10.3329/pa.v27i2.29320

Singh, M. K. 2018. Ecologically sustainable integrated weed management in dry and irrigated direct-seeded rice. Adv. Plants Agric. Res. 8: 319-331. https://doi.org/10.15406/apar.2018.08.00333

Sultana, N., Das, B., Akhter, M. S., Sultana, N. and Rahman, Md. A. 2025. Comparative performance of transplanted aman rice varieties under raised bed and conventional cultivation methods in Bangladesh. Asian J. Agric. Hortic. Res. 12:123-136. https://doi.org/10.9734/ajahr/2025/v12i3398

Suseendran, K., Ramesh, C. B., Stalin, P., Murugan, G. and Saravanaperumal, M. 2017. Effect of low dose herbicides on growth and yield of rice (Oryza sativa L). J. Emerg. Technol. Innov. Res. 3: 606-608. https://www.jetir.org/papers/JETIR1701137.pdf

Verma, B., Bhan, M., Jha, A. K. and Porwal, M. 2023. Influence of weed management practices on direct-seeded rice grown under rainfed and irrigated agroecosystems. Environ. Conserv. J. 24: 240-248. https://doi.org/10.36953/ecj.16622536

Verma, S., Shrivastava, S., Vaheed, M., Yadav, D., Bhushan, C., Srivastava, M., Rajpoot, S. K., Singh, S. B. and Singh, H. 2025. Three-way combination of post-emergence herbicides under DSR and TPR: deciphering weeds, energy budgeting, productivity and economic output in Northern Indo-Gangetic plains. Curr. Sci. 129: 634-640. https://doi.org/10.18520/cs/v129/i7/634-640