Crop growth, biomass accumulation and yield attributes of transplanted rice as influenced by sequential weed-management practices

Introduction

Rice (Oryza sativa L.) is one of the most important food crops globally and plays a central role in food and nutritional security, particularly in Asia. Weed interference is a major biological constraint to rice productivity because weeds compete with rice for nutrients, water, light and space, especially during early and active crop-growth stages. The magnitude of yield loss depends on weed density, species composition, duration of interference and crop competitiveness (Mahajan et al., 2014; Mamun, 2014; Dass et al., 2017) [2,3,1] . Crop establishment and early crop growth influence crop competitiveness, resource utilization and subsequent productivity. Although transplanted rice generally establishes a vigorous stand, weeds emerging after transplanting can compete throughout the season; maintaining adequate crop growth during the critical period of weed-crop competition is therefore important. Establishment practices also influence crop stand, canopy development and yield performance (Parameswari et al., 2014) [4] . Rice fields contain diverse weed communities comprising grasses, sedges and broad-leaved species with different emergence patterns, growth habits and responses to control measures. Consequently, a single intervention may not provide sustained suppression of all weed groups. Jannu et al. (2023) [5] emphasized the complexity of weed flora and the importance of timely and integrated approaches in rice. Although their review focused on direct-seeded rice, the underlying principles are relevant to rice production systems more broadly. Weed competition affects crop growth before its effects become evident in final yield. Competition during vegetative growth can reduce plant height, tillering, leaf area development and dry matter accumulation, thereby limiting canopy development, radiation interception and productive panicle formation (Mahajan et al., 2014; Dass et al., 2017; Mamun, 2014) [2,1,3] . Crop growth analysis using LAI, dry matter accumulation, CGR and RGR provides complementary information on canopy development and biomass production. Maintaining effective weed control during the critical period is particularly important for protecting crop growth and yield formation (Knezevic et al., 2015) [6] . Herbicide-based weed management is an important component of modern rice production because manual weeding is often constrained by labour availability, timeliness and cost. However, differences in weed emer gence and flora can reduce the effectiveness of a single herbicide application. Sequential pre-emergence (PE) followed by post-emergence (PoE) applications can extend weed suppression and target weeds emerging at different stages. Current weed-management approaches increasingly emphasize efficient and integrated strategies for sustainable crop production (Narendar et al., 2026) [7] . Accordingly, weedmanagement effectiveness should be assessed not only through weed density or mortality but also through crop establishment, canopy development, biomass accumulation and yield formation. Recent studies have reported improved crop growth and productivity under sequential herbicide programmes in transplanted rice. Choudhary et al. (2024) [8] reported improved weed management, crop productivity and profitability with herbicide-based approaches, while Shah et al. (2025) [9] observed improved crop growth and productivity under effective sequential herbicide applications. However, individual growth and yield attributes do not necessarily respond uniformly; weed suppression may strongly influence biomass and tiller formation while effects on RGR, panicle length or individual grain weight may be smaller or non-significant. Despite considerable research on weed-control efficacy, greater emphasis has often been placed on weed density, weed dry matter and final yield, with comparatively less attention to the crop-growth trajectory linking weed management with biomass accumulation and individual yield components. Therefore, the present study evaluated the influence of contrasting weed-management practices on plant height, tillering, LAI, dry matter accumulation, CGR, RGR and yield attributes of transplanted rice, with emphasis on the crop-growth responses underlying differences in productivity.

Materials and methods

A field experiment was conducted during the kharif season of 2024 at the Agronomy Main Research Farm, Odisha University of Agriculture and Technology (OUAT), Bhubaneswar, Odisha, India. The experimental soil was sandy loam with pH 5.41, organic carbon 0.62%, and available N, P and K of 275.23, 24.82 and 215.35 kg ha -1 , respectively. During the crop season, rainfall was 972.6 mm over 59 rainy days, with mean maximum and minimum temperatures of 32.6 and 24.6 °C, respectively. The experiment was laid out in a randomized block design (RBD) with eight weed-management treatments and three replications. Each plot measured 5.0 × 4.0 m. Rice cultivar 'Hasanta' was transplanted using 25-day-old seedlings at 20 × 10 cm spacing with two seedlings hill -1 . The recommended dose of fertilizer (RDF) was 80:40:40 kg N:P 2 O 5 :K 2 O ha -1 . PE herbicides were applied at 3 DAT and PoE herbicides at 20 DAT using a knapsack sprayer. The partially weedy check (T 8 ) received no herbicide and one hand weeding at 60 DAT. Treatment details are given in Table 1. Crop growth observations were recorded at specified stages. Plant height was measured from ground level to the tip of the tallest fully expanded leaf or panicle-bearing portion and expressed in cm. Tillers were counted from a representative area and expressed as tillers m -2 . LAI was determined from sampled leaf area relative to the corresponding ground area. Crop dry matter was determined from representative plant samples dried to constant weight and expressed as g m -2 . CGR and RGR were calculated from dry matter observations at the respective sampling stages. CGR was calculated as (W 2 -W 1 )/(T 2 -T 1 ), where W 1 and W 2 are crop dry matter (g m -2 ) at times T 1 and T 2 , respectively, and T 1 and T 2 are sampling dates in days. CGR was expressed as g m -2 day -1 . RGR was calculated as [ln(W 2 ) -ln(W 1 )]/(T 2 -T 1 ) and expressed as mg g -1 day -1 after multiplying g g -1

day -1 values by 1000. At physiological maturity, representative plants were selected for yield-attribute observations. Effective tillers were expressed as m -2

; panicle length was measured from base to tip in cm; filled and unfilled grains were counted per panicle; and test weight was recorded in g. At maturity, the net plot crop was harvested separately for each treatment, and grain and straw yields were recorded after threshing, cleaning and drying and expressed as t ha -1 . Data were subjected to analysis of variance appropriate for RBD. Treatment means were compared using critical difference (CD) at 5% probability when the F-test was significant, and SEm (±) was calculated. Differences among non-significant treatment means were not interpreted as significant. Relationships between selected crop-growth and yield variables were examined using regression analysis based on treatment means. Statistical significance was assessed at P ≤ 0.05.

Results and discussion

Plant height

Plant height was significantly influenced by weed-management treatments at 60 DAT and harvest. At 60 DAT, values ranged from 91.13 to 109.48 cm, with the highest under T 3 (109.48 cm), followed by T 1 (106.54 cm), and the lowest under T 8 (91.13 cm); the CD was 7.73 cm. At harvest, plant height ranged from 120.58 to 140.14 cm, with T 3 recording the maximum (140.14 cm), followed by T 1 (136.29 cm) and T 4 (135.61 cm), while T 8 recorded 120.58 cm (CD 8.43 cm) (Table .2).

The greater height under effective weed-management treatments indicates reduced competition for nutrients, water, light and space during active crop growth. T 3 also maintained comparatively low weed density and dry matter, which corresponded with better crop growth. Similar improvement in plant growth under sequential herbicide programmes was reported by Choudhary et al. (2024) [8] and Shah et al. (2025) [9] . The results are also consistent with the established effect of weed competition on rice growth and the importance of timely suppression during critical growth periods (Mahajan et al., 2014; Dass et al., 2017) [2,1] . The response appears to reflect improved growing conditions from weed suppression rather than a direct growth-promoting effect of the herbicides.

Number of tillers

Tiller number m -2 was significantly affected at 60 DAT and harvest. At 60 DAT, values ranged from 370.67 to 534.67 m -2 , with T 3 highest (534.67 m -2

), followed by T 1 (512.67) and T 4 (494.00), and T 8 lowest (370.67; CD 54.42). At harvest, T 3 again recorded the maximum (486.67 m -2

), followed by T 1 (466.00) and T 4 (443.33), whereas T 8 had the minimum (326.67; CD 46.95 m -2 ) (Table .2). Reduced weed interference during vegetative development favoured tiller initiation and retention by reducing competition for nutrients, moisture and radiation. The superiority of T 3 was associated with comparatively lower weed density and dry matter, while persistent competition in T 8 produced fewer tillers. This agrees with the reported sensitivity of rice tillering to early weed competition (Mahajan et al., 2014; Mamun, 2014; Dass et al., 2017) [2,3,1] and with improved productive tiller formation under effective weed management in transplanted rice (Choudhary et al., 2024) [8] . [8] and Shah et al. (2025) [9] .

Leaf area index

Crop dry matter accumulation

Dry matter accumulation was significantly influenced at both stages. At 60 DAT, values ranged from 643 to 1092 g m -2 , with T 3 highest (1092), followed by T 1 (998) and T 4 (931), and T 8 lowest (643; CD 166 g m -2 ). At harvest, values ranged from 1062 to 1874 g m -2 , with T 3 maximum (1874), followed by T 1 (1723) and T 4 (1681), and T 8 minimum (1062; CD 217 g m -2 ) (Table .2). Greater height, tiller production and LAI under T 3 provided a larger photosynthetically active canopy and greater biomass accumulation. Conversely, persistent weed pressure in T 8 restricted resource availability. Similar improvement in crop biomass under sequential herbicide treatments was reported by Shah et al. (2025) [9] and Choudhary et al. (2024) [8] .

Crop growth rate

CGR was significantly affected during both growth intervals. During 60-90 DAT, CGR ranged from 9.67 to 18.86 g m -2 day -1 ; T 3 recorded the highest (18.86), followed by T 4 (17.86) and T 1 (17.61), while T 8 recorded 9.67 (CD 3.14 g m -2 day -1 ). From 90 DAT to harvest, CGR ranged from 6.42 to 10.82 g m -2 day -1 , with T 3 highest (10.82), followed by T 4 (10.72) and T 1 (9.84), and T 8 lowest (6.42; CD 2.00) (Table .3). The consistently greater CGR under T 3 reflects greater absolute biomass accumulation and agrees with its higher height, tillering, LAI and dry matter. Effective weed suppression reduces competition for light, nutrients, water and space, supporting biomass production during critical crop-growth periods (Knezevic et al., 2015; Dass et al., 2017) [6,1] . Similar responses were reported by Choudhary et al. (2024) [8] and Shah et al. (2025) [9] .

Relative growth rate

RGR did not differ significantly among treatments in either interval.

During 60-90 DAT, RGR ranged from 12.59 to 15.09 mg g -1 day -1 , with T 4 numerically highest (15.09) and T 8 lowest (12.59). During 90 DAT to harvest, values ranged from 5.82 to 6.89 mg g -1 day -1 ; T 4 was numerically highest (6.89) and T 7 lowest (5.82) (Table .3). Because these differences were non-significant, they should not be interpreted as treatment effects. The contrast between significant CGR and non-significant RGR suggests that weed management influenced absolute biomass accumulation more strongly than the proportional rate of growth relative to existing biomass.

Effective tillers

Effective tillers m -2 were significantly influenced. T 3 recorded the highest number (392.00 m -2

), followed by T 1 (374.67) and T 4 (364.67), while T 8 recorded the lowest (255.33; CD 39.97 m -2 ). Greater effective tiller formation under T 3 was consistent with its higher tiller population during earlier growth (Table .3). Effective weed suppression during vegetative development can favour tiller initiation and survival, whereas prolonged competition can reduce productive tillers. Balaji et al. (2024) [10] similarly reported higher productive tiller numbers under effective sequential PE→PoE herbicide management.

Panicle length

Panicle length was not significantly influenced. T 3 recorded the longest panicles (25.53 cm), followed by T 4 (24.91) and T 1 (24.35), while T 8 recorded the shortest (22.08 cm). Although better crop growth may have contributed to the numerical advantage under T 3 (Table .3), the non-significant response indicates insufficient statistical evidence for a treatment effect. Weed-management effects were more clearly expressed through tiller production, biomass accumulation and grain number.

Filled grains

Filled grains panicle -1 were significantly influenced. T 3 recorded the highest number (163.00), followed by T 1 (152.67) and T 4 (146.00), whereas T 8 recorded the lowest (114.56; CD 20.00). Greater filledgrain number under T 3 can be related to its greater biomass, LAI and productive tiller development under reduced weed competition, providing more favourable conditions for reproductive development and grain filling (Table .3). Similar improvements in yield attributes under sequential weed management were reported by Choudhary et al. (2024) [8] and Balaji et al. (2024) [10] .

Unfilled grains

Unfilled grains panicle -1 were significantly influenced. T 3 recorded the lowest number (10.56), followed by T 4 (13.11) and T 5 (13.33), whereas T 8 recorded the highest (34.11; CD 3.98). The lower number under T 3 indicates better reproductive success under reduced weed competition, consistent with its greater crop biomass, LAI, effective tillers and filled grains (Table .3). Persistent weed interference in T 8 was associated with greater reproductive limitation, consistent with the reported effects of prolonged weed competition on crop resource acquisition and grain formation (Table .3) (Mahajan et al., 2014; Mamun, 2014; Dass et al., 2017) [2,3,1] .

Test weight

Test weight was not significantly affected. T 3 recorded the highest numerical value (24.52 g), followed by T 1 (24.26 g) and T 4 (24.18 g), while T 8 recorded the lowest (23.26 g). Thus, the treatments did not substantially modify individual grain weight under the experimental conditions. The numerical advantage under T 3 should not be interpreted as a statistically established response; differences in yield formation were more closely associated with crop stand, effective tillers and filled grains (Table .3).

Overall interpretation

The results show a consistent association between weed suppression and crop growth. T 3 , which maintained comparatively low weed density and dry matter, recorded the highest values for plant height, tiller number, LAI, dry matter, CGR, effective tillers and filled grains, together with the fewest unfilled grains. T 8 generally recorded the poorest crop-growth and yield-component values and the greatest number of unfilled grains. These responses support the importance of reducing the intensity and duration of weed-crop interference during critical growth periods (Dass et al., 2017; Knezevic et al., 2015) [1,6] . They are also consistent with recent evidence that sequential PE→PoE programmes can extend weed suppression and improve rice growth and productivity (Choudhary et al., 2024; Shah et al., 2025) [8, 9] . Importantly, RGR, panicle length and test weight were non-significant, showing that treatment effects were expressed mainly through vegetative growth, biomass accumulation, CGR, productive tiller formation and grain filling rather than uniformly across all traits.

Summary

Weed-management treatments produced clear differences in crop growth and several yield attributes of transplanted rice. Plant height, tiller production, LAI and crop dry matter accumulation were significantly influenced at 60 DAT and harvest, with T 3 consistently recording the highest values and T 8 the lowest. At harvest, T 3 produced 140.14 cm plant height, 486.67 tillers m -2 , LAI of 4.47 and 1874 g m -2 crop dry matter, compared with 120.58 cm, 326.67 tillers m -2 , 3.10 and 1062 g m -2 , respectively, under T 8 . CGR was also significantly higher under T 3 during 60-90 DAT and 90 DAT to harvest (18.86 and 10.82 g m⁻² day⁻¹, respectively), whereas RGR did not differ significantly. Effective tillers and filled grains were highest under T 3 (392.00 m⁻² and 163.00 panicle⁻¹), while T 8 recorded the lowest values (255.33 m⁻² and 114.56 panicle⁻¹). Unfilled grains were lowest under T 3 (10.56 panicle⁻¹) and highest under T 8 (34.11 panicle⁻¹). Panicle length and test weight were not significantly affected. Overall, better weed suppression was associated with improved vegetative growth, biomass accumulation, productive tiller formation and grain filling. The consistent performance of T 3 across the significantly influenced traits indicates that the sequential programme of pyrazosulfuron ethyl followed by florpyrauxifen-benzyl + cyhalofop-butyl provided favourable conditions for crop growth under the experimental conditions.

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