Weed parameters and weed indices as influenced by agronomical practices and weed management in direct-seeded rice

Introduction

Rice (Oryza sativa L.) is one of the world's most important staple food crops, sustaining nearly half of the global population, particularly in Asia, where it forms the cornerstone of food and nutritional security and rural livelihoods. In India, rice contributes about 43 per cent of total food grain production and 46 per cent of total cereal production, besides providing employment to millions of people through rice cultivation and rice-based industries. Thus, rice plays a pivotal role in ensuring food security, generating rural employment and contributing significantly to the Indian economy (Deivasigamani, 2016) [1] . Globally, rice is grown on 163 million hectares, producing 769 million tons with an average productivity of 4.71 t/ha. In India, rice is cultivated on 51.27 million hectares, with a production of 150.18 million tons and average productivity of 2.93 t/ha (Anon., 2024) [2] . In Gujarat, rice is cultivated on 0.89 million hectares, producing 2.22 million tons with an average productivity of 2.49 t/ha (Anon., 2025) [3] . Traditionally, rice is cultivated by transplanting seedlings into puddled soil; however, intensive puddling creates a hard pan below the plough layer, reduces soil permeability and results in substantial water losses through evaporation and percolation (Farooq et al., 2011) [4] . Moreover, puddling and transplanting are highly labour-and water-intensive operations. Under these circumstances, direct-seeded rice (DSR) has emerged as a viable alternative to TPR because it eliminates nursery raising and transplanting operations, facilitates earlier crop establishment and timely sowing and reduces labour, water and cultivation costs (Singh et al., 2008; Rahman et al., 2019) [6,5] . Direct seeding also avoids puddling, transplanting and prolonged maintenance of standing water, thereby improving water-use efficiency (Inagaki et al., 2021) [7] . However, the benefits of DSR are accompanied by a serious weed-management challenge. Unlike transplanted rice, where puddling and standing water suppress several weed species during crop establishment, rice and weeds emerge simultaneously under DSR, resulting in intense crop-weed competition (Raj et al., 2017) [8] . Weed infestation can cause severe yield losses, with losses of 50-60 per cent reported under un controlled conditions (Subbaiah et al., 2000) [9] and losses as high as 95 per cent reported in India (Naresh et al., 2011) [10] . Therefore, effective and timely weed management is a prerequisite for realizing the productivity and resource-use benefits of direct seeded rice. The main objective of weed management in direct-seeded rice is to suppress early weed emergence and reduce the weed seed bank while maintaining a competitive environment for rice throughout the critical period of crop-weed competition (Raj et al., 2017) [8] . Agronomical practices such as stale seedbed (SSB) and summer fallow with deep tillage offer considerable potential for proactive weed management by targeting weeds before crop establishment. The SSB technique stimulates weed seed germination before crop sowing, followed by destruction of emerged weed seedlings through shallow tillage or non-selective herbicides, thereby reducing subsequent weed emergence (Sindhu et al., 2011) [11] . Such approaches can reduce the initial weed pressure and dependence on post-emergence weed-control interventions, while providing an environmentally sustainable approach to weed management (Vemulapalli et al., 2016) [12] . Nevertheless, agronomical practices alone may not provide adequate control of the diverse and continuously emerging weed flora in directseeded rice. Consequently, herbicides have become an important component of weed management because they provide rapid, economical and effective control of weeds (Bhurer et al., 2013) [13] . Manual and mechanical weed-control methods are often constrained by labour scarcity, unfavourable weather conditions and increasing labour costs, particularly during the critical period of weed competition (Mahajan et al., 2013) [14] . Herbicides are therefore particularly useful for controlling weeds such as Echinochloa spp., which may be difficult to distinguish from rice during manual weeding (Ihsan et al., 2014) [15] . However, continuous reliance on herbicides with similar modes of action may result in shifts in weed flora, including shifts from grasses towards sedges and broad-leaved weeds and from annual to perennial species (Rajkhowa et al., 2006) [16] . Furthermore, the complex weed flora of DSR is difficult to manage effectively through a single pre-or post-emergence herbicide application (Mahajan et al., 2013) [14] . The development of low-dose, broad-spectrum herbicides and premix formulations has expanded the available options for managing diverse weed flora. Pre-emergence herbicides provide early suppression of weeds during crop establishment, whereas post-emergence herbicides can control subsequent weed flushes and reduce crop-weed competition (Pusdekar et al., 2020) [17] . Recent advances in broad-spectrum pre-and post-emergence pre-mix herbicides have further provided opportunities to improve weed management while addressing labour and water constraints in DSR (Jehangir et al., 2024) [18] . However, inadequate control, weed escapes and regeneration of certain weed species have been reported despite the use of existing herbicide recommendations. This indicates the need for sequential and integrated approaches involving different weed-management interventions rather than reliance on a single herbicide application (Raj et al., 2013) [19] . Therefore, systematic integration of agronomical practices and herbicide sequences may consequently improve weed-control efficiency, reduce crop-weed competition and enhance the sustainability of direct-seeded rice production. Keeping this in view, the present experiment was carried out with the objective to study the interaction effect of agronomical practices and weed management on the weed parameters and weed indices in direct-seeded rice.

Materials and Methods

The present field experiment was conducted during the kharif seasons of 2024 and 2025, at the College Farm, N. M. College of Agriculture, Navsari Agricultural University, Navsari, Gujarat, India. The soil of experimental unit was clayey in texture, low in organic carbon and available nitrogen, medium in available phosphorus and high in available potassium with slightly alkaline in reaction with normal electric conductivity. Rice variety GNR-8 (Aarti) was sown with seed rate 60 kg/ha. The seeds were sown manually with row spacing of 30 cm. The experiment was laid out in a Strip Plot Design with three replications, comprising 20 treatment combinations. The experimental treatments consisted of four agronomical practices assigned to the vertical strips, viz., Stale seedbed with glyphosate at 15 DBS (A 1 ), Stale seedbed with shallow tillage at 15 DBS (A 2 ), Summer fallow with deep tillage at 80 DBS (A 3 ) and Control (A 4 ) as well as five weed management practices assigned to the horizontal strips, viz., Weedy check (W 1: Control), Weed-free check (W 2: 3 HW at 20, 40 and 60 DAS), Pretilachlor 30% + Pyrazosulfuron-ethyl 0.75% WG 15 + 600 g a.i./ha as (PE) fb Triafamone 20% + Ethoxysulfuron 10% WG 44 + 22.5 g a.i./ha (PoE) (W 3 ), Pretilachlor 30% + Pyrazosulfuron-ethyl 0.75% WG 15 + 600 g a.i./ha (PE) fb Metsulfuron-methyl 10% + Chlorimuron-ethyl 10% WP 4 g a.i./ha (PoE) (W 4 ) and Pendimethalin 30% EC 1000 g a.i./ha (PE) fb Bispyribac-sodium 10% SC 25 g a.i./ha (PoE) fb one HW at 50 DAS (W 5 ). As per the treatment schedule, stale seedbed (SSB) was prepared by providing pre-sowing irrigation after levelling the plots and allowing them to remain undisturbed for 15 days for weed emergence. The emerged initial flush weeds were subsequently removed by shallow tillage using a spiketooth harrow in the SSB with shallow tillage treatment, whereas glyphosate was applied at 15 DBS in the SSB with glyphosate treatment. Under summer fallow with deep tillage treatment, the field was deep-ploughed to a depth of 25-30 cm after harvesting the winter crop and left unplanked during summer. The pre-emergence herbicides, viz., pendimethalin and pretilachlor + pyrazosulfuron-ethyl, were applied at 2-3 DAS, while the post-emergence herbicides, viz., bispyribac-sodium at 25 DAS, chlorimuron-ethyl + metsulfuronmethyl and triafamone + ethoxysulfuron at 30 DAS, were applied using a knapsack sprayer fitted with a flat-fan nozzle. Observations on total weed density were recorded at 60 DAS, while weed dry weight was recorded at harvest and subjected to statistical analysis after square-root transformation using the following formula:

Where, X = transformed value x = original value The weed indices, viz., Weed Control Efficiency (WCE), Treatment Efficiency Index (TEI), Weed Management Index (WMI), Agronomic Management Index (AMI) and Integrated Weed Management Index (IWMI) were calculated using following formulae: Weed Control Efficiency (WCE) was calculated by using formula proposed by Kondap et al. (1985) [20] . Weed Control efficiency (%) =

𝐷𝑊𝐶 -𝐷𝑊𝑇 𝐷𝑊𝐶

Where, WCE = Weed control efficiency DWC = Dry matter accumulation of weeds in weedy check control Treatment Efficiency Index (TEI) was calculated by using formula proposed by Krishnamurthy et al. (1975) [21] . TEI =

Where, Y T = Crop yield from treated plot, Y C = Crop yield from control plot WDMC = Weed dry matter in control, WDMT = Weed dry matter in treatment Weed Management Index (WMI) was calculated by using formula proposed by Sarma (2016) [22] . WMI = 𝑃𝑒𝑟𝑐𝑒𝑛𝑡 𝑐𝑟𝑜𝑝 𝑦𝑖𝑒𝑙𝑑 𝑜𝑣𝑒𝑟 𝑐𝑜𝑛𝑡𝑟𝑜𝑙 𝑃𝑒𝑟𝑐𝑒𝑛𝑡 𝑐𝑜𝑛𝑡𝑟𝑜𝑙 𝑜𝑓 𝑤𝑒𝑒𝑑𝑠 Agronomic management index (AMI) was calculated by using formula proposed by Sarma (2016) [22] . AMI = 𝑃𝑒𝑟𝑐𝑒𝑛𝑡 𝑐𝑟𝑜𝑝 𝑦𝑖𝑒𝑙𝑑 𝑜𝑣𝑒𝑟 𝑐𝑜𝑛𝑡𝑟𝑜𝑙 -𝑃𝑒𝑟𝑐𝑒𝑛𝑡 𝑐𝑜𝑛𝑡𝑟𝑜𝑙 𝑜𝑓 𝑤𝑒𝑒𝑑𝑠 𝑃𝑒𝑟𝑐𝑒𝑛𝑡 𝑐𝑜𝑛𝑡𝑟𝑜𝑙 𝑜𝑓 𝑤𝑒𝑒𝑑𝑠 Integrated Weed Management Index (IWMI) was calculated by using formula proposed by Sarma (2016) [22] . IWMI = 𝑊𝑀𝐼 + 𝐴𝑀𝐼 2

Results and Discussion

The mean values pertaining to total weed density at 60 DAS in response to agronomical practices and weed management and its interaction during pooled analysis was significantly influenced and are presented in the Table .1.

Agronomical practices

Among the tested practices, SSB with Glyphosate (A 1 ) noted significantly the lower total weed density (5.25 weeds/m 2 ) at 60 DAS, but it was par with SSB with shallow tillage (A 2 ). The reduction in weed density under stale seedbed treatments was attributed to the stimulation and subsequent destruction of early-emerging weeds before crop establishment. This depleted the readily germinable weed seed bank and reduced subsequent weed emergence. Similar reductions in weed density under stale seedbed practices were reported by Hazarika et al. (2025) [23] , Sinchana et al. (2022) [24] and Saikia et al. (2013) [25] .

Weed management

The total weed density was significantly influenced by different weed management at 60 DAS. Significantly the lowest total weed density (3.02 weeds/m 2 ) was noted under W 5 (Pendimethalin as PE fb Bispyribac-Na as PoE fb one HW) and was followed by W 2 (3 HW at 20, 40 and 60 DAS), W 3 (Pretilachlor + Pyrazosulfuron-ethyl as PE fb Triafamone + Ethoxysulfuron as PoE) and W 4 (Pretilachlor + Pyrazosulfuron as PE fb Metsulfuron + Chlorimuron as PoE). The superior performance of sequential herbicide treatments was attributed to their complementary action in controlling successive weed flushes throughout the crop growth period. Pendimethalin suppressed earlyemerging weeds, whereas Bispyribac-Na and hand weeding controlled subsequent and escaped weeds, ensuring sustained weed suppression. Similar effectiveness of sequential herbicide application, particularly Pendimethalin fb Bispyribac-Na with hand weeding, was reported by Sar et al. (2024) [26] , Baghel et al. (2018) [27] , Tej et al. (2017) [28] and Kumari et al. (2016) [29] .

Interaction

The interaction between agronomical practices and weed management on total weed density was significant and are depicted in the Table .2. Among the combinations, at 60 DAS, A 1 W 5 (SSB with glyphosate + Pendimethalin as PE fb Bispyribac-Na as PoE fb one HW) noted significantly the minimum total weed density (2.30 weeds/m 2 ) and it was comparable with A 2 W 5 . The lower weed density under integrated treatments was attributed to the combined effect of stale seedbed-induced depletion of the initial weed flush and sequential herbicide action against subsequent weed cohorts. In A 1 W 5 , Pendimethalin fb Bispyribac-Na with supplementary hand weeding provided sustained suppression by controlling early-and late-emerging and escaped weeds through complementary actions. Similar superiority of integrated stale seedbed and sequential herbicide-based approaches in reducing successive weed flushes has been reported by Yonas et al. (2023) [30] , Das et al. (2025) [31] and Barik et al. (2025) [32] . Conversely, the maximum total weed density was noted in A 4 W 1 (control + weedy check) with value of 14.64 weeds/m 2 at 60 DAS. by agronomical practices and weed management in DSR (pooled over 2 year)

The data regarding to the total weed dry weight was significantly influenced by agronomical practices, weed management and their interaction at harvest during pooled analysis are represented in the [33] , Chandrakar et al. (2015) [34] , Sinchana et al. (2022) [24] and Ravikiran et al. (2019) [35] .

Weed management

At harvest, W 2 (3 HW at 20, 40 and 60 DAS) noted significantly the minimum total weed dry weight (13.98 kg/ha), being at par with W 5 .

The treatments W 3 and W 4 showed intermediate performance, whereas the maximum weed dry weight was noted under weedy check (W 1: 33.69 kg/ha). The lower weed biomass under sequential herbicide treatments was attributed to sustained suppression of successive weed flushes, thereby restricting weed establishment and biomass accumulation throughout the crop growth period.

Pendimethalin fb Bispyribac-Na with supplementary HW further enhanced control by suppressing early-and late-emerging weeds, including herbicide escapes. Similar reductions in weed dry biomass with sequential Pendimethalin fb Bispyribac-Na, particularly when integrated with HW, were reported by Karki et al. (2022) [36] , Pooja et al. (2021) [37] and Rana et al. (2016) [38] .

Interaction

Agronomical practices and weed management interaction on total weed dry biomass was significant at harvest during the pooled analysis (Table -2). At harvest, the lowest weed dry biomass was noted un-der SSB with glyphosate combined with weed free check (A 1 W 2: 2.74 g/m 2 ), which remained statistically comparable with other effective combinations involving SSB with glyphosate or shallow tillage integrated with weed free check and Pendimethalin fb Bispyribacsodium with one HW (A 1 W 5 , A 2 W 2 and A 2 W 5 ), where these treatment combinations maintained lower weed dry biomass, whereas control with weedy check (A 4 W 1 ) recorded the maximum weed dry biomass (40.96 kg/ha) due to unrestricted weed growth throughout the crop season. As depicted in Fig. 1, A 1 W 2 recorded the maximum reduction (70.1%) followed by A 2 W 2 (69.3%), A 1 W 5 (67.0%) and A 2 W 5 (65.1%) as compared with the control + weedy check (A 4 W 1 ). The lower weed biomass under integrated treatments was attributed to depletion of the initial weed flush through stale seedbed preparation, followed by effective suppression of successive weed cohorts through sequential herbicide application and hand weeding. The combination of Pendimethalin as PE fb Bispyribac-Na as PoE with one hand weeding provided season-long weed suppression and achieved weed biomass comparable to the weed-free treatment. Similar effectiveness of integrating stale seedbed with sequential herbicide application in achieving weed control comparable to intensive hand weeding was reported by Das et al. (2025) [31] and Barik et al. (2025) [32] .

The data presented in the Fig. 2 revealed that weed control efficiency (WCE) was markedly influenced by agronomical practices and weed management treatments in mean values of two years.

Agronomical practices

At harvest, SSB with glyphosate (A 1 ) exhibited the highest WCE (51.10%), followed by SSB with shallow tillage (A 2: 44.46%), while summer fallow with deep tillage (A 3 ) recorded comparatively lower WCE (24.56%). The control treatment (A 4 ) served as the untreated reference and therefore no WCE value was assigned. Thus, the effectiveness of agronomical practices in improving weed control efficiency followed the order A 1 > A 2 > A 3 > A 4 .

Figure 1. Per cent reduction in total weed dry biomass under superior interactions over control + weedy check in DSR (pooled over 2 year)

Weed management

The highest WCE was observed with weed free check (W 2 ) attaining 82.79 per cent at harvest. The performance of W 2 was closely approached by Pendimethalin fb Bispyribac-Na fb one HW (W 5 ) that attained 81.59 per cent weed control efficiency. Thus, the effectiveness of agronomical practices in improving weed control efficiency followed the order W 2 > W 5 > W 3 > W 4 > W 1 .

Interaction

The interaction between agronomical practices and weed management exerted a marked influence on weed control efficiency (Fig. 3). Among all the treatment combinations, SSB with glyphosate + weed free check (A 1 W 2 ) recorded the highest WCE (91.10%), closely followed by SSB with shallow tillage + weed-free check (A 2 W 2 ) (90.57%). Among the herbicide-based treatments, SSB with glyphosate + Pendimethalin fb Bispyribac-Na fb one HW at 50 DAS (A 1 W 5 ) registered 89.17% WCE, followed by SSB with shallow tillage + the same herbicide sequence (A 2 W 5 ) (87.89%). In contrast, the weedy check under summer fallow with deep tillage (A 3 W 1 ) recorded the lowest weed control efficiency (27.88%).

Weed management efficiency indices

The treatment efficiency index (TEI), weed management index (WMI), agronomic management index (AMI) and integrated weed management index (IMI) displayed in the Table-3 showed variation in mean values of two years, indicating the relative effectiveness of treatments in weed suppression and crop performance.

Agronomical practices

The data presented in Table .3 indicated that SSB with glyphosate (A 1 ) exhibited superior TEI with a mean value of 0.49, followed by SSB with shallow tillage (A 2: 0.42), while summer fallow with deep tillage (A 3 ) recorded the lowest TEI (0.14). However, the weed management index (WMI) and integrated weed management index (IWMI) showed a different response pattern, with A 2 recording the highest values (WMI: 0.52 and IMI: -0.24), followed by A 1 (WMI: 0.47 and IWMI: -0.26) and A 3 (WMI: 0.43 and IWMI: -0.28). The higher efficiency indices under stale seedbed practices indicated their better con-tribution towards reducing weed interference and improving overall crop performance. Whereas, Agronomic Management Index (AMI) remained almost identical among all the agronomical practices.

Weed management

The efficiency indices exhibited marked variation among the weed management treatments. Among the treatments, Pendimethalin fb Bispyribac-Na fb HW (W 5: 4.97) recorded the highest treatment efficiency index (TEI), followed by Pretilachlor + Pyrazosulfuron fb Triafamone + Ethoxysulfuron (W 3: 2.34) or Metsulfuron + Chlorimuron (W 4: 2.13). The higher TEI under W 5 indicated greater

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