Weed flora dynamics, weed control efficiency and nutrient uptake as influenced by integrated weed management in green gram (Vigna radiata L.)

Introduction

Weeds are among the most persistent biotic constraints in green gram (Vigna radiata L.) cultivation, competing with the crop for light, moisture, space and nutrients throughout its short growth cycle and disrupting the nutrient dynamics that underpin its growth and productivity [1] . A typical rainfed or irrigated green gram field supports a diverse weed flora spanning grasses, sedges and broad-leaved species, several of which, such as Parthenium hysterophorus, also carry allelopathic and human-health implications beyond their direct crop-competitive effect [2] . Because different weed species emerge and peak at different times through the crop's growth cycle, and pre-emergence herbicide efficacy itself varies spatially with soil moisture and organic matter, a single weed management intervention often leaves a significant fraction of the weed flora, and in particular later-emerging or escaping cohorts, uncontrolled [3] .

The residual weed seed bank further ensures that incomplete control in one season carries a legacy into subsequent seasons [4] . Weed control efficiency, weed index, weed persistence index and herbicide efficiency index are widely used composite measures for comparing the season-long performance of weed management treatments beyond simple weed counts, since they express weed suppression relative to the unweeded control and relative to yield loss, and so provide a more complete picture of a treatment's practical value than density or dry weight data alone. Nonchemical components, mechanical hoeing and hand weeding, remain an important complement to herbicide use in integrated programmes, both to control weeds that escape herbicide activity and to reduce the cumulative reliance on chemical inputs [5] , a consideration of growing importance given increasing attention to the environmental fate and non-target effects of repeated herbicide use [6] . Combining tactics with complementary modes of action and timing, the central principle of Integrated Weed Management, has therefore been proposed as the most reliable route to season-long, broad-spectrum weed suppression across a diverse weed flora [7] and [8] . Weeds do not merely occupy space and compete for light; they also directly remove nitrogen, phosphorus and potassium from the soil that would otherwise be available to the crop, so that the nutrient uptake and nutrient-use efficiency of a cropping system depend directly on how effectively its weed flora is suppressed [9] . Since the cost of nutrient loss to weeds is rarely quantified alongside herbicide and labour costs in on-farm decision-making [10] , a treatment's effect on crop and weed nutrient uptake, and on the associated soil available-nutrient status, is an important complement to weed density and yield data in evaluating a weed management package. Against this background, the present two-year field investigation was undertaken to characterise the weed flora at the experimental site and to evaluate the effect of nine integrated pre-emergence, post-emergence and mechanical/manual weed management combinations, together with an unweeded control, on weed density and dry weight dynamics, weed control efficiency and related indices, and nitrogen, phosphorus and potassium uptake by the crop, by weeds, and in the soil, in green gram cv. PDM 139.

Materials and Methods

A field experiment was conducted over two consecutive kharif seasons (2025 and 2026) at the Agriculture Research Farm, Faculty of Agriculture, Rabindranath Tagore University (RNTU), Raisen, Madhya Pradesh, India, on a medium-to-deep black (Vertisol) soil, near-neutral in reaction (pH 7.23) and low in organic carbon (0.38%) before sowing. The experiment was laid out in a Randomized Block Design with ten treatments (Table 1) and three replications, on plots of 5.00 m x 4.00 m. Green gram variety PDM 139 was sown at 30 cm x 10 cm spacing on 20 June in both years and fertilized uniformly at 20:40:20 kg N:P2O5:K2O per ha. Weed count (species-wise, No./m2) and weed dry weight (species-wise and total, g/m2) were recorded from randomly placed 1 m2 quadrats at 20, 40 and 60 days after sowing (DAS) and at harvest, excluding border rows, and weed species present at the experimental site were identified to family and, where possible, common name. Weed count and weed dry weight data were subjected to a square-root (√x+1) transformation before analysis of variance, in line with standard practice for count-type data, and back-transformed means are reported. Weed control efficiency (WCE, %) was calculated as WCE = [(DWC -DWT) / DWC] x 100, where DWC and DWT are the total weed dry weight in the unweeded control and the treated plot respectively [11] . Weed index (WI, %) was calculated relative to the highestyielding treatment as WI = [(Ymax -Yt) / Ymax] x 100 [12] . Herbicide efficiency index (HEI) was calculated as HEI = [(Yt -Yc)/Yt x 100] ÷ [(WDMt/WDMc) x 100] [13] , and weed persistence index (WPI) as WPI = (WPt/WPc) x (WDMt/WDMc) [14] , where Yt, Yc, WDMt, WDMc, WPt and WPc denote seed yield and weed dry matter/population in the treated and control plots respectively. Soil pH and electrical conductivity were determined by the glass electrode method [15] , organic carbon by the Walkley and Black rapid titration method [16] , available nitrogen by the alkaline potassium permanganate method [17] , available phosphorus by the Olsen sodium bicarbonate extraction method [18] , and available potassium by the neutral normal ammonium acetate extraction method [19] . Nitrogen, phosphorus and potassium uptake by the crop (grain and stover) and by weed biomass were computed as the product of nutrient concentration and dry matter yield, summed across plant parts. All data were subjected to analysis of variance appropriate to a Randomized Block Design, following Panse and Sukhatme [20] ; where the error variances of the two years were homogeneous, a pooled analysis across years was carried out, and pooled means, SEm±, CD (P=0.05) and CV% are reported. Weed flora composition: Ten weed species were recorded at the experimental site (Table 2), comprising two grasses (Echinochloa colona, Digitaria sanguinalis), one sedge (Cyperus rotundus) and seven broad-leaved species (Commelina benghalensis, Phyllanthus niruri, Parthenium hysterophorus, Amaranthus viridis, Euphorbia hirta, Chenopodium album and Trianthema portulacastrum), confirming a mixed, multi-family weed flora typical of green gram fields in central India. By contrast, single-application treatments T4, T6 and T7 showed WCE in the 73-85 per cent range at harvest, a gap of 4-16 percentage points that, compounded over the season, produced the substantially larger weed biomass documented in Table 3. 3 and4, where T8 and T9 were likewise the best-performing treatments and T4 and T6 among the weakest. Nutrient uptake by crop and weeds: Data on nitrogen, phosphorus and potassium uptake by the crop and by weed biomass, pooled over two years, are presented in Table 7. Nutrient uptake by the crop was highest under T8 (62.86 kg N, 18.13 kg P and 51.74 kg K/ha) and T9 (60.42 kg N, 17.39 kg P and 51.10 kg K/ha), and lowest under the unweeded control. Conversely, nutrient uptake by weed biomass was lowest under T8 and T9 and highest under the control, confirming that the higher crop nutrient uptake recorded under the better-performing treatments came at the direct expense of nutrient removal by weeds rather than any difference in soil nutrient supply.

Results

Table 1: Treatment details

Treatment

Discussion

The broad-spectrum, season-long weed suppression achieved under T8 and T9, evident in their consistently lowest weed count and dry weight across all four observation stages and all ten weed species, reflects the complementary mode-of-action structure of these treatments: an effective pre-emergence herbicide controlling the first flush of germinating weeds, a post-emergence herbicide with a distinct mode of action controlling weeds escaping the pre-emergence layer, and a physical (mechanical or manual) intervention removing any remaining flush ahead of the crop's critical growth stages. This is consistent with reports that a single weed management intervention typically leaves a fraction of a diverse weed flora uncontrolled, given differences in the timing of species-wise emergence and in pre-emergence herbicide efficacy across the field [3] , and that integrated, multi-tactic regimens are correspondingly more effective across a broad weed spectrum than any single tactic [7] and [8] . The sustained, rather than merely early-season, weed control efficiency recorded under T8 and T9 (remaining above 88% from 20 DAS through harvest) is a particularly important practical finding, since it demonstrates that these treatments do not simply delay weed emergence but suppress it through to crop maturity, addressing the residual weed seed bank concern raised for singlepass interventions [4] . The correspondingly highest weed index, weed persistence index and herbicide efficiency index recorded under T8 and T9 among the active treatments (Table 5) corroborate this pattern of consistently superior, season-long weed suppression relative to the other integrated treatments evaluated. The consistently higher nutrient uptake by the crop, and correspondingly lower nutrient uptake by weeds, recorded under T8 and T9 provides direct, quantitative confirmation that weeds compete with green gram for available soil nitrogen, phosphorus and potassium, and that effective weed suppression redirects this nutrient pool towards the crop rather than increasing overall nutrient supply [9] . This nutrient-competition dimension of weed management is often under-quantified relative to its yield and cost implications [10] , yet the present results show it to be a substantial and directly measurable component of the advantage integrated weed management confers, and one that plausibly also contributed to the higher seed protein content recorded under these treatments through improved nitrogen availability. The broadly stable soil pH, EC and organic carbon across treatments indicates that none of the herbicide or non-chemical interventions evaluated had a detectable adverse effect on these basic soil properties over the two-year study period, addressing, at least for this duration and this specific set of active ingredients, one of the general environmental-fate concerns raised for repeated herbicide use 6 . Mechanical hoeing and hand weeding, the non-chemical components of the two best-performing treatments, further reduced reliance on repeated herbicide application 5 , consistent with the wider case for integrating nonchemical tactics into herbicide-based weed management programmes. Treatments relying on a single herbicide application without a complementary post-emergence or mechanical/manual follow-up (T4, T6 and T7) consistently showed higher weed density and dry weight, and lower weed control efficiency and weed index, than the integrated treatments throughout the season, only modestly ahead of the unweeded control. This confirms that a single herbicide application, however well chosen, is generally insufficient to suppress the diverse, sequentially emerging weed flora characteristic of green gram fields in this region, and that combining it with a second, differently timed or differently acting intervention is necessary for effective, season-long weed and nutrient management.

Conclusion

Integrated weed management combining a pre-emergence herbicide with a post-emergence herbicide and a mechanical or manual follow-up operation achieved broad-spectrum, seasonlong suppression of a diverse ten-species weed flora and minimised nutrient diversion to weeds in green gram. Pendimethalin 1.0 kg/ha (PE) followed by imazamox 75 g/ha (30 DAS) followed by mechanical hoeing (45 DAS) (T8) recorded the lowest total weed count and dry weight, the highest weed control efficiency (89.16% at harvest), and the highest crop nutrient uptake among all treatments evaluated, and is recommended as the most effective weed management package for green gram in the central Narmada valley agro-climatic zone of Madhya Pradesh and comparable regions. Pyroxasulfone 0.75 kg/ha (PE) followed by halosulfuron-methyl 75 g/ha (25 DAS) followed by hand weeding (45 DAS) (T9) is recommended as an equally effective alternative, and single-tactic herbicide treatments without a complementary follow-up intervention are not recommended for season-long weed and nutrient management in this crop.

Acknowledgement

AcknowledgementThe authors gratefully acknowledge the Faculty of Agriculture, Rabindranath Tagore University, Raisen, Madhya Pradesh, for providing the experimental farm, laboratory facilities and technical support necessary to carry out this investigation, and the Department of Agronomy for its continued academic guidance throughout the study.

References

1. Hirani AK, Korav S, Rajanna GA, Elansary HO, Mahmoud EA. Determination of critical crop-weed competition period: impact on growth, nutrient dynamics and productivity of green gram (Vigna radiata). Heliyon. 2024;10(17).
2. Kaur A, Batish DR, Chauhan BS, Kaur S, Singh HP, Kohli RK. Parthenium hysterophorus. In: Biology and management of problematic crop weed species. Amsterdam: Elsevier; 2021. p. 311-333.
3. Metcalfe H, Milne AE, Hull R, Murdoch AJ, Storkey J. The implications of spatially variable pre-emergence herbicide efficacy for weed management. Pest Manag Sci. 2017;74(7):1665-1674.
4. Kumar S, Rana SS, Gaytri H, Rana N. Understanding and managing weed seed banks: a review. Agric Rev. 2024;45(3):508-513.
5. Kumar SP, Tewari VK, Mehta CR, Chethan CR, Chandel A, Pareek CM. Mechanical weed management technology to manage inter-and intra-row weeds in agroecosystems: a review. Indian J Weed Sci. 2022;54(3):220-232.
6. Parven A, Meftaul IM, Venkateswarlu K, Megharaj M. Herbicides in modern sustainable agriculture: environmental fate, ecological implications, and human health concerns. Int J Environ Sci Technol. 2025;22(2):1181-1202.
7. Riemens M, Sønderskov M, Moonen AC, Storkey J, Kudsk P. An integrated weed management framework: a panEuropean perspective. Eur J Agron. 2022;133:126443.
8. Cordeau S. Conservation agriculture and agroecological weed management. Agronomy. 2022;12(4):867.
9. Mishra JS, Kumar R, Mondal S, Poonia SP, Rao KK, Dubey R, et al. Tillage and crop establishment effects on weeds and productivity of a rice-wheat-mungbean rotation. Field Crops Res. 2022;284:108577.
10. Das TK, Behera B, Nath CP, Ghosh S, Sen S, Raj R, et al. Herbicides use in crop production: an analysis of costbenefit, non-target toxicities and environmental risks. Crop Prot. 2024;181:106691.
11. Mani VS, Malla ML, Gautam KC, Bhagwandas. Weed killing chemicals in potato cultivation. Indian Farming. 1973;23(2):17-18.
12. Gill GS, Kumar V. Weed index: a new method for reporting weed control trials. Indian J Agron. 1969;14(2):96-98.
13. Krishnamurthy K, Raju BG, Raghunath G, Jagnath MK, Prasad TVR. Herbicide efficiency index in sorghum. Indian J Weed Sci. 1975;7(2):75-79.
14. Mishra M, Mishra A. Estimation of integrated pest management index in jute: a new approach. Indian J Weed Sci. 1997;29(1-2):39-42.
15. Jackson ML. Soil chemical analysis. New Delhi: Prentice Hall of India Pvt. Ltd.; 1973.
16. Walkley A, Black IA. An examination of the Degtjareff method for determining soil organic matter, and a proposed modification of the chromic acid titration method. Soil Sci. 1934;37(1):29-38.
17. Subbiah BV, Asija GL. A rapid procedure for the estimation of available nitrogen in soils. Curr Sci. 1956;25(8):259-260.
18. Olsen SR, Cole CV, Watanabe FS, Dean LA. Estimation of available phosphorus in soils by extraction with sodium bicarbonate. Washington (DC): United States Department of Agriculture; 1954. USDA Circular No. 939.
19. Hanway JJ, Heidal H. Soil analysis methods as used in Iowa State College Soil Testing Laboratory. Iowa Agric. 1952;57:1-31.
20. Panse VG, Sukhatme PV. Statistical methods for agricultural workers. 2nd ed. New Delhi: Indian Council of Agricultural Research; 1967.