Effect of non-chemical weed management practices on weed dynamics and performance of sweet corn (Zea mays L.)

Introduction

Sweet corn, which is a variety of maize known for its greater sugar percentage is an important crop in global agriculture and food systems. Sweet corn kernels have tenderness and naturally high in sugar levels, thus making it suitable for both fresh and processed consumption. Sweet corn is a specialty maize grown for its immature cobs, valued for both fresh consumption and use in processed foods. It provides significant amounts of roughage, essential minerals, and vitamins, particularly A and C. Its palatability and nutritive quality have driven widespread consumer acceptance and increasing cultivation worldwide (Olabode and Sangodele, 2015) [1] . One of the major issues contributing to lower yields of sweet corn is competition from weeds for growth resources like nutrients, water, sunlight, and space (Sharma et al., 2010 [2] ; Mali et al., 2019) [3] . Early-establishing weed species and elevated weed pressure are often responsible for more pronounced yield reductions compared to weeds that emerge later in the crop cycle. In maize, yield losses attributable to weed interference may vary between 28% and 93%, influenced by the composition of weed flora, their competitive ability, and the duration of weedcrop competition (Choudary et al., 2021) [4] . Weed management encompasses a range of strategies including physical, chemical, cultural, biological and integrated methods. In recent years, there has been a notable shift away from herbicide-dependent practices toward non-chemical alternatives. This transition is largely driven by growing public concern over environmental sustainability and the adverse impacts associated with synthetic herbicides. Non-chemical weed control techniques focus on reducing pesticide reliance while promoting eco-friendly and sustainable agricultural practices (Duwadi et al., 2021) [5] . Mulch is a layer of material, either natural or artificial, placed on the soil surface to improve soil conditions and helps to regulate soil temperature, reduces fertilizer leaching, suppresses weeds and can increase crop yield (Nithisha et al., 2022) [6] . Cover crops, also known as living mulch, green manure, smother crops or catch crops are grown not for harvest but for their ecological benefits. They help in suppressing weeds, conserving soil moisture, improving soil fertility and structure, attracting useful insects and reducing erosion (Mennan et al., 2020) [7] . Keeping the above points into consideration, the present study was undertaken to evaluate the impact of nonchemical weed management practices on weed dynamics and the growth and yield of sweet corn.

Materials and Methods

The field experiment was conducted during Rabi 2024-25 at the College Farm, Agricultural College, Polasa, Jagtial, Telangana, India, to evaluate the effect of non-chemical weed management practices on weed dynamics and performance of sweet corn. The experiment comprised ten weed management treatments: T₁straw mulch (2-inch thickness), T₂live mulch with cowpea (one additive row between maize rows), T₃ -Gliricidia sepium leaf mulch (2-inch thickness), T₄ -Sesbania as intercrop used as mulch after 30 DAS, T₅ -coriander as intercrop, T₆synthetic weed mat (110 GSM), T₇intercultural operation at 20 and 40 DAS + hand weeding at 20 DAS, T₈tembotrione 34.4% SC at 100 g ha⁻¹ + atrazine 50% WP at 500 g ha⁻¹ applied at 20 DAS (for comparison), T₉weed-free check, and T₁₀weedy check. These treatments were evaluated under a randomized block design (RBD) with three replications. The experimental field was characterized by well-drained sandy clay loam soil with a textural composition of 66.1% sand, 6.2% silt, and 27.7% clay. The initial soil chemical properties included a neutral pH of 7.33, electrical conductivity of 0.24 dS m⁻¹, and a bulk density of 1.60 g cm⁻³. The organic carbon content was moderate (0.49%). Prior to sowing, the soil was low in available nitrogen (135 kg ha⁻¹), medium in phosphorus (21.9 kg ha⁻¹), and potassium (213.9 kg ha⁻¹). During the experimental period, the average maximum and minimum temperatures were 32°C and 13.7°C, respectively. The crop variety used was sweet corn hybrid 'SUGAR-75', which has a duration of 90-100 days. Sowing was done at a spacing of 60 × 20 cm using a seed rate of 6 kg ha⁻¹. The recommended dose of fertilizers (200:60:50 kg ha⁻¹ of N, P₂O₅, and K₂O) was applied using urea, DAP and MOP, respectively. Weed management practices were implemented according to the treatment schedule. All mulch materials were applied immediately after the sowing of sweet corn, except for the synthetic weed mat (T₆), which was laid out prior to sowing. Intercrop seeds were sown simultaneously along with sweet corn in designated rows as per the respective treatments. The crop was cultivated following the recommended package of practices for sweet corn. Weed density observations for grasses, sedges, and broad-leaved weeds were recorded at 20, 40, and 60 days after sowing (DAS) using a 0.5 × 0.5 m quadrat (0.25 m²) placed randomly at three locations within each plot. For statistical analysis, data on the total number of weeds and weed dry matter were collected, tabulated, and subjected to square root transformation (√x + 0.5) to normalize variance and improve data reliability (Gomez and Gomez, 1984). Weeds collected from each quadrat were ovendried at 65°C for 24 hours until constant weight and expressed in grams per square meter (g m⁻²). Weed control efficiency (WCE) was calculated based on weed dry weight using the following formula:

Where, WCE = Weed Control Efficiency (%) DMc = Dry matter of weeds in unweeded check (Control) DMt = Dry matter of weeds in treatment plot

The experimental design data were statistically analysed using Fisher's analysis of variance approach, and treatment means were compared using an F-test and the least significant difference test at a 5% probability level to determine CD values. On all of the gathered data, analysis of variance was carried out.

Results and Discussion

Weed flora

The common weeds observed in the experimental site were Cyperus esculentus among sedges and Echinochloa colona, Cynodon dactylon, Digitaria sanguinalis, Dactyloctenium aegyptium among grasses and Commelina benghalensis, Digera arvensis L., Amaranthus viridis, Phyllanthus madraspatensis, Trianthema portulacastrum and Boerhavia erecta L. etc. among broad-leaved weeds. Among the different groups of weeds, broad leaved weeds were predominant followed by sedges and grasses. Comparable results were reported by Chaudhari et al. (2023) [9] and Swetha et al. (2018) [10] .

Weed parameters

At 20 DAS, the lowest weed density and dry matter were recorded in T 6 (Weed mat mulch) and T 9 (Weed-free check), due to effective physical and manual suppression. Among mulches, T 3 (Gliricidia) and T 1 (Straw) recorded moderate densities (36.33 and 45.00 no. m -2 ) and dry matter (10.97 and 18.8 g m -2 ), while T 2 (Cowpea) and T 5 (Coriander) were least effective. T 7 and T 8 showed high pre-treatment weed loads (92.67-93.17 m -2 ; 29.21-29.80 g m -2 ) and T 10 (Weedy check) recorded the highest density and biomass (103.33 no. m -2 and 32 g m -2 ). At 40 DAS, T 9 again showed the lowest weed growth, followed by T 6 (21.67 no. m -2 and 24.67 g m -2 ) and T 8 (34.00 no. m -2 and 9.83 g m -2 ). T 3 and T 1 showed moderate suppression, while intercrops (T 2 , T 4 , T 5 ) remained less effective. T 10 registered the highest density (196.67 m -2 ) and dry matter (251.67 g m -2 ). At 60 DAS lowest weed density and dry matter was recorded in T 9 (Weed-free check), followed by T 6 (Weed mat mulch) (34.33 no. m -2 , 68.33 g m -2 ) and T 7 (IC at 20 and 40 DAS + HW at 20 DAS) was on par with T 6 with regarding to dry matter (73.33 g m -2 ). Weed control efficiency (WCE) reflected these trends, T 6 and T 9 reported 100% at 20 DAS. At 40 and 60 DAS, T 9 maintained full control, while T 6 showed high WCE values (90.19 -82.11%). T 7 and T 8 treatments recorded high weed control efficiency values next to T 6 and T 9 treated plots. T 3 treatment plot consistently outperformed other mulches and intercrops like T 2 and T 5 remained least effective across all stages. Similar results was noted by Uwah et al. (2011) [11] .

Crop parameters

Among the treatments, T 6 -mulching with weed mat (110 GSM) recorded significantly the highest plant height (83.0 cm at 30 DAS, 209.2 cm at 60 DAS and 229.0 cm at 90 DAS), which was followed by T 9 -weed-free check (79.1 cm at 30 DAS, 201.4 cm and 220.5 cm, respectively) at 30 and 90 DAS, T 7 -interculture and T 8 (tembotrione + atrazine), at all the stages of observation. The lowest plant height (61.5 cm at 30 DAS, 152.2 cm at 60 DAS and 194.2 cm at 90 DAS) was observed in T 10 -weedy check, indicating the suppressive effect of weed competition on vegetative growth. At 30 DAS, highest dry matter was recorded in T 6 (788 kg ha -1 ) which was on par with T 9 and T 7 (772 kg ha -1 , 766 kg ha -1 ) respectively, followed by T 8 (714 kg ha -1 ). Maximum crop dry matter production was recorded in T 6 (6736 kg ha -1 ), which was on par with T 9 (6600 kg ha -1 ) and followed by T 7 (6536 kg ha -1 ), T 3 -Gliricidia mulch (6433 kg ha -1 ) at 60 DAS. At 90 DAS, T 6 again recorded the highest dry matter (8927 kg ha -1 ), followed by T 7 (8755 kg ha -1 ) which in turn on par with T 9 (8652 kg ha -1 ). The lowest dry matter at all stages of observation was observed in T 10 (4565 and 6306 kg ha -1 ), due to greater competition. The superior performance of T 6 and T 9 can be attributed to uninterrupted growth by providing proper micro climate in case of T 6 . Similar results were provided by Ramakrishna et al. (2006) [12] and effective weed suppression during critical crop stages in both the treatments.

Yield Attributes

A significant variation was recorded among weed management practices for cob characters. The maximum cob length (22.53 cm), kernel rows cob -1 (18.00 no.), and kernel number row -1 (36.00 no.) were observed in T 6 (weed mat mulching), which is statistically on par with T 9 (weed-free check), followed by T 7 (IC + HW) and T 8 (tembotrione + atrazine). Treatments involving organic mulches like T 1 and T 3 showed improvement over weedy check but which was inferior to T 6 (weed mat). The lowest values cob length (18.97 cm), kernel rows cob -1 (14.33), and kernel number row -1 (26.00) were associated with T 10 (weedy check) followed by T₅ (coriander intercrop) due to intense weed competition restricting effective cob growth and kernel development. Similar findings were observed by Yaseen al. (2014) [13] .

Yield

T 6 (weed mat) treatment plot recorded the highest green cob (22,689 kg ha -1 ) and fodder yield (36,944 kg ha -1 ), which was significantly superior to all other treatments. It was followed by T 9 (19,933 and 31,389 kg ha -1 ) and T 7 (19,322 and 29,111 kg ha - 1 ). Among organic mulches, T 3 (Gliricidia) performed better (16,872 and 25,556 kg ha -1 ), while T 5 (Coriander) treatment reported poor green cob (12,957 kg ha -1 ) and fodder yield (19,166 kg ha -1 ). T 10 (Weedy check) recorded the lowest green cob (10,050 kg ha -1 ) and fodder yields (17,666 kg ha -1 ). Maximum harvest index was observed in T 4 (44.36%), which was on par with T 2 (43.53%) and T 1 (42.36%), whereas T 8 (35.35%) and T 10 (36.26%) showed the least, indicating poor assimilate partitioning under high weed pressure. These findings are similar to Asif et al. (2020) [14] .

Conclusion

Among all the weed management practices, T 6 (weed mat mulch) treatment recorded higher growth parameters, yield attributes and yield; lower weed density and dry weight. Among mulches and intercropping T 3 (Gliricidia leaves mulch) was found to be superior to other treatments.

Acknowledgement