Weed pressure management through tillage and weed control approaches in rice under resource conserving agriculture

doi:10.21203/rs.3.rs-3777840/v1

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Weed pressure management through tillage and weed control approaches in rice under resource conserving agriculture

https://doi.org/10.21203/rs.3.rs-3777840/v1

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The present investigation was conducted during three seasons i.e. Kharif seasons in 2019 and 2020 at research cum instruction farm, at Indira Gandhi Krishi Vishwavidyalaya, Raipur (C.G.), where adequate facilities for irrigation and drainage exist. The soil of the experimental field was silty clay in texture. The soil was neutral in reaction (6.86) with normal electrical conductivity (0.349). It had low nitrogen, medium phosphorus and high potassium contents.The experiment was laid out in split plot design with five tillage practices (main plot) i.e. two conventional transplanted rice CT (TPR), one conventional direct-seeded rice CT (DSR), one zero tillage (ZT) and one zero tillage with residues (ZT + R), and three weed management practices (sub-plot) treatments replicated thrice. The test varieties taken was “IGKV R1” sown as per the treatments with recommended dose of fertilizers. The outcomes explicated that among tillage practices, transplanted system of establishment i.e. CT (TPR)-CT-CT proved to be most beneficial in terms of significant economic produce, lowest weed pressure but ZT + R-ZT + R-ZT + R proved with about comparable yield i.e. only 8.39% lesser yield and about 19% lesser weed control efficiency (WCE) than transplanted system i.e. CT (TPR)-CT-CT. Moreover, the yield in zero tillage system increased in second year of trial unlike in CT (TPR)-CT-CT. Hence, long term trial of ZT + R-ZT + R-ZT + R is more eco-friendly and sustainable. Among weed management practices, IWM i.e. oxadiargyl 80 g ha^− 1 PE fb hand weeding at 25 DAS/T proved to be registered highest value of all the parameters taken for study. Moreover, it registered 47% higher grain yield than weedy check and 12% higher weed control efficiency (WCE) than recommended herbicides treatment i.e. pyrazosulfuron 20 g ha^− 1 fb penoxsulam 22.5 g ha^− 1 PoE.

Conservation

conventional tillage

integrated weed management

residue mulching weed flora

yield and zero tillage

Rice, as a fundamental staple food, holds significant dietary importance for over half of the global population, primarily in Asia. The global consumption of rice has shown a modest rise over recent years, with approximately 520 million metric tons consumed globally in the 2021–2022 crop year from 437.18 million metric tons in the 2008/2009 crop year. India ranks second in rice consumption, with 108.5 million metric tons, following China (Anon., 2023). This crop supports the livelihoods of millions of farmers and their families worldwide, offering employment not only in farming but also in various stages of production, including planting, harvesting, milling, and marketing. Furthermore, rice plays a pivotal role in global trade and economies.

The conventional practice of puddling in rice cultivation, while effective in reducing water percolation and suppressing weeds, demands substantial water, capital, and energy resources. Moreover, it leads to soil structure degradation (Bhatt et al. 2016). (Direct sown rice (DSR) emerges as a viable alternative, conserving water, time, labor, and consequently, reducing costs (Singh et al. 2017). However, weed infestation remains a major challenge in DSR, with uncontrolled weed pressure ranging from 10 to 100% (Rao et al. 2007). Traditional puddled transplanting systems effectively suppress live weeds and their viable seeds by submerging them in saturated soil, resulting in delayed weed emergence (Jat et al. 2019; Soni et al. 2020). In contrast, non-puddled methods witness earlier emergence of viable weed seeds, intensifying weed infestation (Eager et al. 2013; Baker et al. 2018).

To mitigate weed emergence in DSR and preserve soil moisture, temperature regulation, and enhance water productivity, the retention of crop residues on the soil surface plays a critical role (Y Singh and H S Sidhu 2014). Conservation agriculture presents itself as a cognitive solution, relying on three core principles: minimal soil disturbance during seeding, permanent soil cover using crops, residues, or mulches, and crop diversification (FAO, 2021). When complemented with complementary practices like appropriate nutrient management and enhanced groundcover, conservation agriculture aims to deliver multiple ecosystem services (Hobbs et al. 2007; Chabert and Sarthou 2020).

The simultaneous application of these principles intends to bolster soil health, fertility, and structure while curbing soil degradation, improving water infiltration, reducing pesticide dependence, and promoting climate change mitigation through carbon sequestration. Conservation agriculture is expanding globally at a rate of 10M ha/year, currently practiced on nearly 160 million ha globally. It is implemented on a wide array of pedoclimates and production systems primarily in field crops (but also vegetables, vineyard, fruit trees, etc.)(Cordeau et al. 2023). Although its adoption in India is limited, standing at 1.5 million ha under zero-till wheat in North-western India (FAO, 2014).

Despite the potential of herbicide application in weed control, challenges such as herbicide resistance, weed shift, and detrimental effects of persistent soil herbicides pose significant constraints. Therefore, the strategic management of herbicides and their rotational use is critical to curb herbicide resistance in weeds (Bhullar et al. 2016). The introduction of unique weed challenges in conservation agriculture necessitates innovative weed management strategies that align with its principles. Combining physical, biological, or chemical weed management tactics with existing cultural weed management in conservation agriculture can achieve integrated weed management objectives. With appropriate integration of weed management, conservation agriculture can potentially enhance the productivity of direct-seeded rice, traditionally lower than transplanted rice (Bhattacharyya et al. 2015).

The present investigation was conducted during three seasons i.e. Kharif seasons in 2019 and 2020 at research cum instruction farm, at Indira Gandhi Krishi Vishwavidyalaya, Raipur (C.G.), where adequate facilities for irrigation and drainage exist. The soil of the experimental field was silty clay in texture. The soil was neutral in reaction (6.86) with normal electrical conductivity (0.349). It had low nitrogen, medium phosphorus and high potassium contents.The experiment was laid out in split plot design with five tillage practices (main plot) and three weed management practices (sub-plot) treatments replicated thrice. Rice-wheat-cowpea (fodder) cropping system in respective three seasons of kharif, rabi and summer was adopted to validate conservation agriculture principles. The treatments applied in rice were, viz. CT (TPR)-CT-CT [Conventional tillage (Transplanted rice)], CT (TPR)-ZT-ZT, CT (DSR)-CT-ZT (Direct-seeded rice), ZT-ZT + R-ZT (Zero tillage), ZT + R-ZT + R-ZT + R (Zero tillage with residues) in main plots and Rec. herbicides (pyrazosulfuron 20 g ha^− 1 fb penoxsulam 22.5 g ha^− 1 PoE), IWM (oxadiargyl 80 g ha^− 1 PE fb hand weeding at 25 DAT/S)], weedy check in sub-plots. The test varieties taken was “IGKV R1” sown as per the treatments with recommended dose of fertilizers. The required amount of herbicides was sprayed using 375 l/ha of water with knapsack sprayer fitted with a flat fan nozzle. At sampling time (50 and 75 days after sowing/transplanting; DAS/T), a quadrate of 50 × 50 cm was placed at two places in each plot to determine the density and dry weight of different weeds. Weed dry weight was recorded after drying the weed samples at 70°C for 48 h. Weed control efficiency and weed index were calculated based on the data recorded at 50 and 75 DAS/T in rice as per standard formula. Grain and straw yield (t ha^− 1) were recorded just before harvesting. Rice grain yield was expressed at 14% moisture content. Data were analyzed using analysis of variance (SAS Software packages, SAS EG 4.3). Means of treatments were compared based on Critical Difference (CD) test at p < 0.05 probability level. Weed density and dry weight were square root transformed, before analysis. However, for better understanding, original values are given in parenthesis.

Weed index (WI) (%)

Weed index was calculated by the formula mentioned under; it is expressed in percentage.

$$\text{WI (%)}\text{ }\text{= }\frac{ \text{G}\text{r}\text{a}\text{i}\text{n} \text{y}\text{i}\text{e}\text{l}\text{d} \text{o}\text{f} \text{w}\text{e}\text{e}\text{d} \text{f}\text{r}\text{e}\text{e} \text{p}\text{l}\text{o}\text{t}-\text{G}\text{r}\text{a}\text{i}\text{n} \text{y}\text{i}\text{e}\text{l}\text{d} \text{i}\text{n} \text{a} \text{t}\text{r}\text{e}\text{a}\text{t}\text{m}\text{e}\text{n}\text{t}\text{ }}{ \text{G}\text{r}\text{a}\text{i}\text{n} \text{y}\text{i}\text{e}\text{l}\text{d} \text{o}\text{f} \text{w}\text{e}\text{e}\text{d} \text{f}\text{r}\text{e}\text{e} \text{p}\text{l}\text{o}\text{t}}\times 100$$

Weed control efficiency (WCE) (%)

Weed control efficiency was calculated taking into consideration the reduction in weed dry weight in treated plot over the weed dry weight in untreated weedy check and expressed in per cent.

$$\text{WCE (%)}\text{ }\text{= }\frac{ \text{D}\text{M}\text{C}-\text{D}\text{M}\text{T}\text{ }}{ \text{D}\text{M}\text{C}}\times 100$$

WCE = Weed control efficiency (%)

DMC = Dry weight of weeds in untreated plot (g)

DMT = Dry weight of weeds in treated plot (g)

Weed dynamics

Weed flora

(Shrestha et al. 2006) deduced that long-term shifts in weed species composition result from the interplay of multiple factors, including tillage practices, environmental influences, crop rotation, the presence of summer fallow periods, and the specific weed management approaches employed. (Mishra and Singh 2012) focused on studying the weed seed bank in a rice-wheat cropping system under various tillage and weed management practices, identifying four predominant weed species: Echinochloa colona, Cyperus iria, Avena ludoviciana, and Medicago hispida. The experimental plots exhibited a diverse weed flora primarily consisting of major broad-leaved weeds like Alternanthera triandra and Cyanotis axillaris, sedges such as Cyperus iria, and grasses like Echinochloa colona and Sporobolus diander. Additionally, other identified weeds included Monochoria vaginalis, Caesulia axillaris, Phyllanthus niruri, Spilanthes acmella, Ludwigia octavilis, and Brachiaria ramosa, among others. (Choudhary and Dixit 2018) discovered that in direct-seeded rice, the weed population displayed considerable diversity while maintaining a similar species composition.

Figure 1 described that at 50 days after sowing/transplanting (DAS/T), the highest percentage composition was recorded for Alternanthera triandra (32% in 2019 and 26% in 2020), followed by Echinochloa colona (20%) during both years. At a later stage, specifically at 75 DAS/T, Alternanthera triandra remained prominent, comprising 28% (2019) and 25% (2020) of the total, followed by Echinochloa colona at 16% and 15% in 2019 and 2020, respectively. Cyanotis axillaris consistently exhibited the lowest percentage composition during both observation periods. Over the four-year experimental periods, the relative dominance of weeds followed a sequence in the rainy season, with Echinochloa colona > Cyperus iria > Caesulia axillaris > Alternanthera philoxeroides > Ammannia baccifera (Nandan et al. 2018).

Relative weed density (RWD) (%) at 50 and 75 DAS/T

Throughout the observation periods of 50 and 75 days after sowing/transplanting (DAS/T), the periodic relative weed density (RWD) for various weed species was computed and visualized in Fig. 2.

Consistently, Alternanthera triandra exhibited the highest relative weed density across all tillage practices in both years. Notably, CT (TPR)-ZT-ZT displayed the highest relative weed density for Alternanthera triandra. Grassy weeds exhibited greater presence under ZT, while CT demonstrated a higher proportion of broad-leaved weeds in terms of density and biomass (Matloob et al. 2015).(Demjanová et al. 2009) revealed that among the weed groups, annual broadleaf weeds (17 species) predominantly outpaced perennial weeds (6 species) and annual grassy weeds (4 species) across all soil tillage treatments. A significant benefit of conventional tillage was observed in reducing perennial weed density. The total weed density showed significant variation, with mouldboard primary soil tillage significantly reducing the density to 16.3 plants m^− 2 compared to reduced tillage systems ranging from 36.7 to 39.2 plants m^− 2. In comparison to mouldboard ploughing, disk ploughing and shallow loosening treatments notably increased weed density by 240% and 225%, respectively. Additionally, conventional tillage notably decreased the density of perennial weeds from 7.5-9.0 plants m^− 2 in reduced treatments to 2.6 plants m^− 2.

(Nandan et. al., 2018) concluded that in first year of trial, the highest total weed density was recorded in ZTDSR-ZT, substantially exceeding those in CTTPR-CT, UPTPR(Unpuddled TPR)-ZT and ZTTPR-ZT by 43.8%, 56.8%, and 46.7%, respectively unlike in next year in which ZTTPR-ZT registered highest. The treatment with residue notably reduced the total density of narrow-leaved weeds by 7.3% compared to the without residue. Tillage systems exhibited variable influence on the density and biomass of weed species. CT favored broad-leaved weeds like Trianthema portulacastrum, while ZT plots had more growth of grasses, particularly Dactyloctenium aegyptium. These differences between tillage systems were more pronounced at the early stages of weed competition (Matloob et al. 2015). (Singh et al. 2005) noted that C. rotundus and Commelina diffusa Burm. f. were dominant weeds in drill-sown rice under ZT. Although perennial weeds that propagate through underground vegetative parts usually thrive in undisturbed soils, in this study, the density and biomass of sedges were either similar between the two tillage systems or higher in CT than ZT (Matloob et al. 2015). Adoption of ZT might prompt shifts in weed flora toward annual grasses (Tuong et al. 2005). Continuous ZT notably harbored a higher proportion of viable weed seeds in the upper 0–5 cm soil layer than CT (Mishra and Singh 2012). Under ZT, 77% of the seeds were found in the top soil surface (2 cm) or tend to reside within the 2–5 cm soil depth, leading to their early emergence (Chauhan and Johnson 2011), while CT buried 62% of seeds to a depth of 2–5 cm (Chauhan and Johnson 2009). This difference might be due to the prevention of germination of small-seeded weed species, usually occurring under CT systems, indicating an implication of light requirement for germination (Matloob et al. 2015). (Bàrberi and Lo Cascio 2001) highlighted that in the 0–15 cm soil layer, tillage had a greater influence on weed composition than crop rotation. In tilled soil under CT, weed seeds are believed to be uniformly distributed (Ball 1992). (Mishra and Singh 2012) reported that the densities of weeds like E. colona and C. iria were significantly increased in rice under ZT. (Matloob et al. 2015) added that despite a higher increase in density and biomass in CT plots in 2011 compared to 2010, it was similar to that observed for ZT. This increase might be attributed to the buildup of the soil seed bank in 2010. Grasses like D. aegyptium, E. colona, and E. crus-galli were more abundant in ZT plots than CT during 2010. However, in the second year of the study, the emergence of these weeds was similar between the two tillage systems. These inconsistent results, especially during the second year, contradict predictions made in previous studies [(Chauhan 2011); (Chauhan and Johnson 2011); (Chauhan 2012)], which assumed that weed species with smaller photoblastic seeds cannot emerge from deeper soil depths that usually occur following CT operations. The variations in results between these studies may be attributed to several factors. The impact of tillage systems on vertical seed distribution is influenced by the type and frequency of tillage implements used. Soil cultivation can alter the vertical distribution of weed seeds in the soil profile, subsequently impacting seedling establishment due to factors like seed dormancy, longevity, predation, and the potential for a seedling to emerge from a specific depth (Chauhan and Johnson 2010). Differences in the qualitative and quantitative aspects of weed seed banks might also contribute to variations among studies. Irrigation can also modify weed emergence and growth in rice (Bhager et al. 1999). Most studies assessed weed growth within a specific timeframe, such as up to 30 DAS and flowering (Mahajan et al. 2014).

Regarding weed management practices, a similar trend was observed in the weedy check, except for the highest relative density of Echinochloa colona observed in other treatments. Notably, in CT (TPR)-CT-CT, the highest relative weed density of other weeds occurred at 25 DAS/T in both years. Treatments involving ZT + R-ZT + R-ZT and ZT-ZT + R-ZT exhibited the highest relative weed density of Echinochloa colona at 25 DAS/T across both years. At harvest, Sporobolus diander dominated, followed by Alternanthera triandra, in both tillage and weed management practices during both years. Cyanotis axillaris consistently exhibited the lowest relative weed density across all observation periods and treatments throughout both years.

Total weed dry matter

At different time intervals data are presented in Fig. 3. Data revealed that total weed dry matter was significantly influenced by the tillage and weed management practices both years at all observation periods (i.e. 50 and 75 DAS/T). Among tillage practices, significantly lower total weed dry matter was recorded at CT (TPR)-CT-CT and the highest total weed dry matter was observed under ZT-ZT + R-ZT in 2019 and CT (DSR)-CT-ZT in 2020 at all observation periods. The higher weed biomass in CT might have occurred from continuous heavy soil crushing. Such soils are more aerated, warmer and experienced greater temperature fluctuations. These conditions offer better germination environments for most weed seeds, even dormant weed seeds, which may be brought up to the upper soil layers from the sub-soil layers in CT (Batlla et al. 2020). Considerable disparities in weed dry biomass were evident between the conventional treatment utilizing mouldboard ploughing and reduced tillage approaches. A substantial reduction in weed biomass (by 48%) of grassy weeds under the conventional method compared to zero tillage (ZT) in 2010. However, this discrepancy lost statistical significance in 2011 (Matloob et al. 2015). (Marasini et al. 2020) noticed that a negative linear correlation between weed dry weight at 30, 45, and 60 days after sowing (DAS) and grain yield was established, indicating a relationship where higher weed dry weights were associated with reduced yields (R² = 0.5353, 0.5188, 0.365, respectively). The choice of tillage method notably influenced weed dry weight at 30 DAS, with zero tillage demonstrating significantly higher values. While weed dry weights at 15, 45, and 60 DAS were not overtly affected by tillage methods, the values remained notably elevated in the zero tillage approach. Furthermore, weed management practices exhibited a significant impact on weed dry weight. (Govindan and Chinnusamy 2014) reported heightened weed density and dry weight within the zero tillage system. Additionally, (Feldman et al. 1997) suggested that the reduced soil disturbance characteristic of zero tillage might retain a substantial portion of the weed seed bank near the soil surface, consequently leading to increased emergence of weed seedlings.

Amid various weed management practices, notably lower dry matter accumulation of total weed biomass was consistently observed under Integrated Weed Management (IWM), employing oxadiargyl at 80 g ha^− 1 in a pre-emergence application, followed by hand weeding at 25 days after sowing/transplanting (DAS/T). Conversely, the highest dry matter accumulation was consistently recorded under the weedy check. A significant interaction between different tillage practices and weed management strategies was evident at 50 and 75 DAS/T (Table 1) across both years, as well as the mean values during all observation periods.

Due to interaction effect of tillage and weed management practices lowest total weed dry matter was found in the interaction of treatments CT (TPR)-CT-CT and IWM i.e. oxadiargyl 80 g ha^− 1 PE fb hand weeding at 25 DAS/T which was at par with interaction of CT (TPR)-ZT-ZT and IWM i.e. oxadiargyl 80 g ha^− 1 PE fb hand weeding at 25 DAS/T while highest total weed dry matter was registered in interaction treatments of CT (DSR)-CT-ZT and weedy check.

(Ahmed and Chauhan 2014) reported that the decreased density and weight of weeds were potentially due to the comprehensive and seasonal control of weeds through the sequential application of pre- and post-emergence herbicides. The pre-emergence application of oxadiargyl at 75 g ha^− 1 effectively managed weeds during the early stages of crop growth, followed by the post-emergence application of bispyribac-sodium at 30 g ha^− 1 to control late-emerging weeds. Pyrazosulfuron-ethyl, applied at rates of 20 and 25 g ha^− 1, significantly reduced the density and biomass of weeds like Cyperus iria and Echinochloa colona when administered 3 to 10 days after transplanting (Chopra and Chopra 2003). (Ramesha et al. 2017) revealed that pyrazosulfuron-ethyl at 10% WP and 20g ha^− 1, applied at 3 days after sowing, resulted in the lowest total weed dry weight (14.42, 9.46, and 7.48 gm^− 2 at 15, 30, and 60 days after application, respectively). This was closely followed by applications of pyrazosulfuron-ethyl at 10% WP and 15g ha^− 1 (17.79, 14.48, and 12.68 g m^− 2 at 15, 30, and 60 days after application, respectively) and Saathi at 15g ha^− 1 (17.56, 14.56, and 10.93 gm^− 2 at 15, 30, and 60 days after application, respectively). Overall, the study suggested that pyrazosulfuron-ethyl at 10% WP and 20 g ha^− 1 was notably effective against a broad range of weeds and recommended its safe use for controlling various weed categories in transplanted rice while improving rice grain yield. The weed control efficiency recorded for these herbicides was reported as 79.6% and 69.2%, respectively (Mathew et al. 2013).

The combination of compatible herbicides employing different modes of action offers a broad spectrum of weed control ((Mahajan and Chauhan 2013; Awan et al. 2015)). Similar outcomes were echoed by (Baraibar et al. 2017), (Jat et al. 2019), and (Hossain et al. 2021).

Weed control efficiency (WCE) (%)

Weed control efficiency computed at 50 and 75 DAS/T is presented in Table 1. WCE gradually increased up to 75 DAS/T in both years in all treatments. The data revealed that among tillage practices, highest weed control efficiency was observed under CT (TPR)-CT-CT followed by CT (TPR)-ZT-ZT. This may be effect of physical manipulation of soil which resulted into destruction of weed seed bank more efficiently. As hand weeding is a most effective approach of weed management which culminated in to potential control of the emerging weed pressure, weed control efficiency of integrated methods of weed management was registered highest i.e. among weed management practices, at all the observation periods, in both years, maximum weed control efficiency was recorded in IWM i.e. oxadiargyl 80 g ha^− 1 PE fb hand weeding at 25 DAS/T. Similar findings were reported by (Mathew et al. 2013) and (Ahmed and Chauhan 2014).

Grain yield (t ha^− 1)

Data with respect to grain yield is presented in Table 1. Grains yield ha^− 1 was significantly different among all treatments. Among tillage practices, being statistically at par with CT (TPR)-ZT-ZT, CT (TPR)-CT-CT produced significantly higher grain yield as compared to other tillage practices both years data, whereas the lowest recorded under CT (DSR)-CT-ZT at all observation periods. However, CT (TPR)-CT-CT also found at par with the treatments ZT + R-ZT + R-ZT + R and ZT-ZT + R-ZT in 2020.

As regards to influence of weed management practices, it was observed that significantly higher grain yield were noticed when crop was treated with IWM i.e. oxadiargyl 80 g ha^− 1 PE fb hand weeding at 25 DAS/T over other two treatments during both years. The lowest grain yield was observed in weedy check control. Interaction effect on grain yield due to tillage and weed management practices was significant in both years and in mean (Table 1). The interaction effect of CT (TPR)-CT-CT and IWM i.e. oxadiargyl 80 g ha^− 1 PE fb hand weeding at 25 DAS/T gave highest grain yield which was at par with interaction effect of CT (TPR)-ZT-ZT CT and IWM i.e. oxadiargyl 80 g ha^− 1 PE fb hand weeding at 25 DAS/T. While interaction effect of CT(DSR)-CT-ZT and weedy check on grain yield was lowest.

Higher rice yield and yield attributing characters with CT treatments in the initial years (Sapkota et al. 2015) might be due to favourable effect of tillage practices on hastening of organic matter decomposition and higher nutrient availability and enhanced root growth. The increased yield in these treatments might be due to cumulative effect of lower weed density, dry matter, higher weed control efficiency an increased number of panicle bearing tillers per unit area, filled grains per panicle (Sairamesh et al. 2015). These results are also in accordance with the findings of (Rahman et al. 2004), (Saharawat et al. 2010), Mishra and Singh (2012), (Ahmed and Chauhan 2014) and (Meher et al. 2018).

Straw yield (t ha^− 1)

The data on straw yield is presented in Table 1 which indicates that the treatments significantly influenced it. Among tillage practices, being statistically at par with CT (TPR)-ZT-ZT, CT (TPR)-CT-CT produced significantly higher straw yield as compared to other tillage practices both years data, whereas the lowest recorded under CT (DSR)-CT-ZT at all observation periods.

As regards to influence of weed management practices, it was observed that significantly higher straw yield were noticed at all the observation periods when crop was treated with IWM i.e. oxadiargyl 80 g ha^− 1 PE fb hand weeding at 25 DAS/T over other two treatments during both the years and in mean data also while the lowest number of straw yield was observed in weedy check. However, interaction effect on straw yield due to tillage and weed management practices was non-significant at all observation periods in both years and in mean. The result is in accordance with (Kiran et al. 2010), (Saharawat et al. 2010) and (Meher et al. 2018).

Weed index (WI) (%)

Data on weed index (WI) as influenced by different treatments are presented in Table 1, which revealed that the interaction effect of CT (TPR)-CT-CT and IWM i.e. oxadiargyl 80 g ha^− 1 PE fb hand weeding at 25 DAS/T gave lowest weed index while interaction effect of (DSR)-CT-ZT and weedy check was highest. These results are conformity with the findings of (C M et al. 2010) and (A et al. 2011).

Table 1

Weed control efficiency (WCE), Grain yield, Straw yield and Weed index (WI) of rice as influenced by tillage and weed management practices under conservation agriculture
Treatments	Weed control efficiency (WCE) (%)				Grain yield (t ha^− 1)		Straw yield (t ha^− 1)		Weed index (WI) (%)
	2019	2020	2019	2020	2019	2020	2019	2020	2019	2020
	50 DAS/T		75 DAS/T
Tillage practices
CT (TPR)-CT-CT	81.87	73.86	78.76	71.86	5.78	5.44	7.14	7.26	11.11	12.06
CT (TPR)-ZT-ZT	75.83	70.04	74.26	66.56	5.62	5.27	6.81	6.90	13.61	14.79
CT (DSR)-CT-ZT	45.62	54.33	48.96	44.94	4.95	4.19	5.97	5.43	23.88	32.31
ZT-ZT + R-ZT	45.53	61.15	48.68	56.73	5.09	5.11	6.12	6.66	21.84	17.32
ZT + R-ZT + R-ZT + R	48.75	64.00	51.85	60.69	5.17	5.18	6.68	7.25	20.50	16.23
SEm±					0.14	0.16	0.20	0.12
CD ( P = 0.05)					0.46	0.51	0.64	0.39
Weed management
Rec. herbicides	74.27	78.05	76.68	75.12	5.95	5.63	7.46	7.61	8.60	9.04
IWM	87.40	90.88	86.26	85.51	6.51	6.19	7.49	7.73	-	-
Weedy check	-	-	-	-	3.52	3.30	4.67	4.76	45.97	46.58
SEm±					0.18	0.19	0.14	0.18
CD ( P = 0.05)					0.54	0.55	0.43	0.54
Interaction (T x W)					S	S	NS	NS

The outcomes explicated that among tillage practices, transplanted system of establishment i.e. CT (TPR)-CT-CT proved to be most beneficial in terms of highest yield, lowest weed pressure but ZT + R-ZT + R-ZT + R having comparable yield i.e. only 8.39% lesser yield, about 20% lesser weed control efficiency and 9% more weed index than transplanted system i.e. CT (TPR)-CT-CT. Moreover, the yield increased in ZT + R-ZT + R-ZT + R in second year of trial unlike CT (TPR)-CT-CT and weed index bar reduced to 4% as well. Hence, long term trial of ZT + R-ZT + R-ZT + R is more eco-friendly and sustainable. Among weed management practices, IWM i.e. oxadiargyl 80 g ha^− 1 PE fb hand weeding at 25 DAS/T proved to be registered highest value of all the parameters taken for study. Combination of zero tillage mulched with crop residues and IWM proved to be edge in socio-economic and ecologically sound, hence can be recommended to the farmers.

Acknowledgement: The authors sincerely acknowledge Director, ICAR-DWR, Jabalpur, MP-482004 , for providing the funding through AICRP-WM during the course of experimentation.

Authors’ contribution: S.M carried out the experiment, analysed and interpreted the data; N.T conceptualized and designed the experiment, reviewed the data and interpretation, supervised the laboratory work, provided necessary tools and instruments and analysed data. S.S critically revised the article. A.M. Mahapatra reviewed the data and drafted the article. All authors approved the final version of the article to be published and agreed to be accountable for all aspects of work.

Compliance with Ethical Standards:

Conflict of interest: The authors declare no existence of any conflict of interest.

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Weed pressure management through tillage and weed control approaches in rice under resource conserving agriculture

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Version 1

Abstract

Figures

Introduction

Materials and Methods

Weed index (WI) (%)

Weed control efficiency (WCE) (%)

Result and Discussion

Weed dynamics

Weed flora

Total weed dry matter

Weed control efficiency (WCE) (%)

Grain yield (t ha^− 1)

Straw yield (t ha^− 1)

Weed index (WI) (%)

Conclusion

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1

Weed pressure management through tillage and weed control approaches in rice under resource conserving agriculture

Status:

Version 1

Abstract

Figures

Introduction

Materials and Methods

Weed index (WI) (%)

Weed control efficiency (WCE) (%)

Result and Discussion

Weed dynamics

Weed flora

Total weed dry matter

Weed control efficiency (WCE) (%)

Grain yield (t ha− 1)

Straw yield (t ha− 1)

Weed index (WI) (%)

Conclusion

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1

Grain yield (t ha^− 1)

Straw yield (t ha^− 1)