Evaluation of agronomic performance of local and improved maize (Zea mays L.) varieties under weeds pressure

 Corresponding author: Guy Roland ANZARA Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0. Evaluation of agronomic performance of local and improved maize (Zea mays L.) varieties under weeds pressure Guy Roland ANZARA 1, *, Koffi Bertin YAO 2 and Adoni Hugues Sidoine TANO 2 1 Laboratory for the Improvement of Agricultural Production, UFR Agroforestry, Jean Lorougnon Guédé University, BP 150 Daloa, Côte d’Ivoire. 2 Laboratory of Biology and Improvement of Plant Production, UFR Natural Sciences, Nangui 2Abrogoua University, 02 BP 801 Abidjan 02, Côte d’Ivoire. World Journal of Advanced Research and Reviews, 2025, 27(02), 1822-1828 Publication history: Received on 13 July 2025; revised on 23 August 2025; accepted on 25 August 2025 Article DOI: https://doi.org/10.30574/wjarr.2025.27.2.3013 Abstract Maize (Zea mays L.) is the second most cultivated cereal after rice in Côte d’Ivoire. It is widely used in both human and animal diets across many communities. However, its production remains faced with recurrent yield declines, mainly related to weeding. Identifying maize variety with the highest performance against weeds could constitute the most appropriate solution in the agro-economic context of most farmers. Two weeding techniques, namely manual and chemical, and a control modality without weeding were applied to three maize varieties: yellow, purple and EV8728 SR. Their phenological, growth and agronomic parameters were evaluated. The results showed that manual weeding was more effective for weed control in maize. In addition, the comparison of all three varieties faced with severe weed pressure on non-weedy plots showed that purple variety recorded the lowest values, yellow variety showed intermediate values, while EV variety clearly stood out for its strong ability to grow and maintain high agronomic performance. Further studies may allow us to search for genes responsible for the tolerance of the EV variety involved in weed tolerance Keywords: Zea mays; Weed; Maize Varieties; Manual Weeding; Chemical Weeding 1. Introduction Maize (Zea mays L.) is one of the main cultivated species in the world. It plays an important role in both human and animal nutrition (poultry, pigs, cattle) in Sub-Saharan Africa. It is also widely used in the agri-food industry for oils, starches, and alcohols productions, making it a strategic crop from both nutritional and economic standpoint [1]. However, despite its socio-economic importance, maize cultivation faces many challenges that hinder its production. Mean yields of traditional varieties in farming communities are approximately 0.8 tons per hectare, compared to 6 to 8 tons per hectare in research stations [2]. The main causes of yield decline are believed to be linked to soil infertility, the emergence of diseases and pests, and especially the presence of weeds [3]. In fact, weeds remain the major constraint to maize production. Indeed, competition with weeds in tropical regions can result in yield losses of over 50 % [4]. Furthermore, weeds have detrimental effects on all phenological phases of the plants. They cause a slowdown or even complete cessation of growth and development in maize plants [5]. Considering weeds significant effect on crops, many studies have been undertaken, focusing mainly on chemical control strategies [6, 7]. Farmers due to its ease of application, reduced labor requirements, and time efficiency, making it a comparatively cost-effective option, generally favor this approach. Nevertheless, emergence of herbicide-resistant weed World Journal of Advanced Research and Reviews, 2025, 27(02), 1822-1828 1823 species remains a persistent challenge. Consequently, there is an urgent need to develop alternative solutions that are accessible to smallholder farmers. For most farmers, identifying maize genotypes tolerant to weed competition is one of the most appropriate solutions in their agro-economic context. Tolerant varieties have the advantage of increasing yields despite weeds presence [8]. Within this framework, the present study was undertaken to enhance maize productivity by identifying the variety demonstrating the greatest performance under weed-infested conditions. 2. Materials and methods 2.1. Study site The experiment was conducted in march 2025 on the experimental plot of Nangui Abrogoua University (5°23′19″ N latitude and 4°0′54″ W longitude) in the southern of Cote d’Ivoire (Figure 1). Figure 1 Location of the study site [9]. 2.2. Plant material Seeds of three maize varieties: purple maize (Figure 10 A) and yellow maize (Figure 10 B) both from seed bank of the Plant Physiology Laboratory, and the improved EV 8728 SR (Figure 10 C) were used in this study. The last variety, is a seed line developed by the National Center for Agronomic Research (CNRA) for enhanced growth, disease resistance, and high yield potential. A B C Figure 2 Maize of the purple (A), yellow (B), and EV 8728 SR (C) varieties 2.3. Experimental setup The experimental design followed a randomized complete block layout, covering a total area of 117 m² (13 m × 9 m). It consisted of three blocks, each subdivided into nine elementary plots separated by 0.5 m wide alleys, with a 1 m spacing between blocks to facilitate movement and field operations. Each block was arranged in ridges measuring 2 m in length, 1 m in width, and 0.30 m in height, giving an area of two m² per elementary plot. Within each elementary plot, the maize World Journal of Advanced Research and Reviews, 2025, 27(02), 1822-1828 1824 plants were arranged in two rows of five points spaced 0.3 m apart, and 0.5 m between rows. The experiment was based on three distinct treatments: two weeding methods (manual and chemical) and a control. Each treatment was three times replicated. A week after seedlings transplanting, a thinning operation was carried out to leave only one vigorous plant per hole. Weeds were removed using a hoe for manual weeding. Chemical weeding was carried out by targeted application of a selective herbicide based on nicosulfuron, at a dose of between 75 and 120 ml per 15 L of water, applied evenly to effectively eliminate weeds without affecting the crop. 2.4. Measured variables During this study, growth, phenology, and yield parameters were rigorously monitored throughout the maize development cycle from the early stages of vegetative growth to harvest. Three phenological parameters (the timing of male and female flowering and the duration of ear maturation), seven growth parameters (width, length and number of leaves, plant height, branch number, root length and number, and collar diameter), and four yield parameters (weight of grains, number of grains, weight of plants and ears) were evaluated according to [10]. 2.5. Statistical analysis of experimental data All data collected during this study were subjected to statistical analysis to assess the influence of both experimental factors (maize varieties and weeding methods) using STATISTICA software version 7.1 [10]. To this end, the Analysis of Variance (ANOVA) was performed to compare the means of different phenological, growth, and agronomic parameters across the three treatments (manual weeding, chemical weeding, and control) in order to determine the most suitable treatment. A separate ANOVA was also conducted to compare the means of all measured parameters among the three maize varieties. When a significant difference was detected between varieties for a given parameter, the ANOVA was followed by the least significant difference (LSD) test. This test enabled the identification of the variety exhibiting the best agronomic performance under weed-infested conditions. 3. Results 3.1. Effect of weeding methods on phenological and growth parameters Table 1 Effect of weeding method on maize phenological and growth parameters Parameters1 Weed control method Satistics2 Chemically Manually Control F P Phenoloical AnTi (DAT) 47.57 ± 3.284a 47.51 ± 4.206a 51.31 ± 5.310b 22.601 < 0.001 CoET (DAT) 55.64 ± 4.607a 56.10 ± 6.246a 62.22 ± 5.958b 38.054 < 0.001 CoMT(DAT) 77.99 ± 4.840a 77.68 ± 4.637a 90.52 ± 4.468b 223.417 < 0.001 Growth RoNb 28.37 ± 4.507b 25.63 ± 2.553a 29.20 ± 4.895b 6.169 0.003 RoLe (cm) 20.60 ± 2.660b 22.37 ± 3.479c 18.50 ± 2.801a 12.479 < 0.001 LeLe (cm) 4.9763 ± 1.981a 4.9373 ± 1.931a 5.0095 ± 2.013a 0.050 0.951 LeWi (mm) 51.046 ± 25.307a 51.426 ± 25.427a 47.2721 ± 22.975a 1.308 0.271 PlHg (cm) 105.795±587.320a 59.1917±37.471a 54.4101 ± 30.696a 1.044 0.353 NuLf 7.016 ± 2.098a 7.413 ± 2.314a 6.840 ± 2.183a 2.672 0.070 StCD (mm) 13.096 ± 6.115b 13.642 ± 6.285b 11.488 ± 55.133a 5.452 0.005 1AnTi : anthesis time, CoET : cob emergence time, CoMT : cob maturation time, RoNb: root number/ plant, RoLe: root lengh, PlHg: Plant heigh, NuLf: number of leaves, StCD: stem collar diameter, DAT: days after transplantation; 2 F-statistics and P: probability associated with the test. For each parameter, values with the same superscript letters are statistically equal (P ≥ 0.05) World Journal of Advanced Research and Reviews, 2025, 27(02), 1822-1828 1825 The weeding method had a significant effect on the three phenological parameters (P ˂ 0.05). Specifically, the timing of male and female flowering and the duration of ear maturation were higher on unweeded plots than in manually and chemically weeded plots (Table 1). Thus, weed infestation delayed the phenological parameters. In contrast, the weeding method did not affect growth parameters, except for root length and number. Compared to manual weeding, chemical weeding increased the number of roots while reducing their length. 3.2. Effect of weeding technique on agronomic parameters Table 2 presents values of agronomic parameters related to maize cobs and grains measurements following weed control method. Statistical analysis results revealed significant difference between all agronomic parameters following three treatments. Thus, plant, cobs, number and grain weights, were highest in manually weeded plots, followed by chemically weeded plots and then untreated plots. Table 2 Effect of weeding method on agronomic parameters Parameters Weed control method Statistics Chemically Manually Control F P Plant weight (g) 346.67 ± 103.130b 298.08 ± 118.67b 171.83 ± 54.005a 10.610 < 0.001 cob weight 132.92 ± 52.254b 152.92 ± 35.364c 67.67 ± 17.619a 16.673 < 0.001 Grains/ plant 253.33 ± 97.811b 366.08 ± 75.138c 132.92 ± 69.255a 24.463 < 0.001 Grain weight (g) 261.900 ± 50.578b 359.967 ± 71.384c 105.067±30.983a 17.272 0.003 3.3. Estimation of phenological parameters for the three varieties Values of the phenological parameters recorded during the development of maize three varieties studied (yellow, purple, and EV) are presented in Table 3. Statistical analysis of data from weeded plots revealed no significant variation in stamens appearance time of female flowering or cob maturation. In contrast, the date of male flowering was significantly influenced by the varieties (P < 0.001). Stamens earlier appeared in the EV variety than in the other two varieties. The male flowers of the EV variety appeared earlier than those of the other two varieties. On the unweeded control plots, a significant difference was observed for all parameters. The male and female flowers appeared earlier for the yellow variety. However, the EV variety matured earlier than the other varieties. The Yellow and Purple varieties had a later reproduction time, although the female flowers appeared earlier than the EV variety. The difference in ear maturity time between the two treatments for the three varieties was lower for the EV variety (-9.03%) than for the Yellow (-15.57%) and Purple (-18.09%) varieties. 3.4. Variation in growth parameters according to weeding in three maize varieties Statistical analysis of growth parameters revealed that plant height and leaf dimensions (length and width) varied significantly depending on whether the plants were weeded or not (Tables 4 and 5). The EV variety had broader leaves than both varieties. For leaf length and plant height, both the EV and yellow varieties exhibited the highest values in weeded and unweeded plots. Quantification of the relative reductions in these discriminating parameters showed that the EV variety expressed the lowest losses, with only a 3.04% reduction in leaf width, 6.47% in leaf length, and 2.1% in plant height. This was followed by the purple variety, with losses of 1.71%, 7.73%, and 3.66%, respectively, and finally the yellow variety, which was the most sensitive, exhibiting losses of 35.55%, 14.56%, and 8.68% respectively. 3.5. Impact of weed control on agronomic parameters of three maize varieties Statistical analysis of agronomic parameters showed a significant difference for all measured parameters across all treatments, except for the number of grains in the weeded plot (Table 4). In the unweeded control plots, the effects of competition from weeds resulted in a marked decrease in the mean values of the various parameters. The EV variety stood out with superior performance, exhibiting a seed weight loss of only 15%, compared to 27% for both the yellow and purple varieties. World Journal of Advanced Research and Reviews, 2025, 27(02), 1822-1828 1826 Table 3 Estimation of phenological parameters for the three varieties Maize varietie s Date of stamen appearance Date of cob appearance Date of cob maturation Weeded Control (unweeded) Loss (%) Weeded Control (unweeded) Loss (%) Weeded Control (unweeded) Loss (%) EV 47.60 ± 2.49b 50.27 ± 4.18a -5.60 56.10 ± 5.19a 63.80 ± 5.37b -13.72 75.45 ± 6.51a 82.27 ± 6.49a -9.03 Yellow 46.22 ± 3.46a 49.93 ±4.25a -8.02 54.98 ± 5.12a 59.60 ± 6.00a -8.40 77.93 ± 4.30a 90.07 ± 5.03b -15.57 Purple 48.80 ± 4.62b 53.73 ± 6.45b -10.10 56.53 ± 6.04a 63.27 ± 5.75b -11.92 76.55 ± 5.64a 90.40 ± 3.85b -18.09 F 7.60 5.15 1.28 4.79 3.005 23.16 P < 0.001 0.008 0.280 0.011 0.052 < 0.001 Table 4 Impact of weed control on growth parameters in three maize varieties Maize varities Leaf length (cm) Plant height (cm) Number of leaves Leaf width (cm) Weeded Control (unweeded) Loss (%) Weeded Control (unweeded) Loss (%) Weeded Control (unweeded) Loss (%) Weeded Control (unweeded) Loss (%) EV 60.93±21.56b 56.98±21.32b 6.47 67.25±32.159b 65.83±25.20b 2.10 7.83±5.58a 7.61±1.93a 2.896 5.59±2.11a 5.421±1.97c 3.04 Yellow 61.23±22.29b 52.30±21.398b 14.56 71.07±34.74b 64.90±30.72b 8.68 7.640±4.50a 6.89±4.40a 9.816 6.99±8.90b 4.507±1.52b 35.55 Purple 51.23±25.32a 47.27±22.97a 7.736 52.48±30.99a 54.41±30.69a 3.667 7.21±2.21a 6.84±2.18a 5.197 4.95±1.95a 3.889±1.463a 21.71 F 18.154 7.374 27.090 7.186 1.612 3.011 11.178 31.85 P < 0.001 < 0.001 < 0.001 < 0.001 0.200 0.050 < 0.001 < 0.001 In the same column, figures followed by the same letter are statistically identical at the 5% threshold., ; D: Not weeded Table 5 Impact of weed control on agronomic parameters of the three maize varieties Maize varieties Plant weight (g) Cob weight of the ear with Spath (g) weight of grains (g) Number of grains Weeded Control (unweeded) Loss (%) Weeded Control (unweeded) Loss (%) Weeded Control (unweeded) Loss (%) Weeded Control (unweeded) Loss (%) EV 387.17±56.36b 306.58±101.07b 20.81 133.08±35.03c 96.17±27.19b 27.735 40.20±10.07c 29.314±5.14b 27.089 230.00±82.57a 196.33±37.70b 14.63 Yellow 348.13±108.13b 217.58±73.56a 37.50 108.46±30.38b 73.25±21.29a 32.463 32.73±11.02b 23.673±4.24b 27.68 210.33±72.90a 138.33±41.88a 34.23 Purple 272.79±74.30a 171.83±171.83a 36.985 81.33±23.60a 67.67±17.61a 16.795 25.03±5.56a 21.116±3.20a 15.68 188.87±45.92a 107.92±46.13a 42.68 In the same column, figures followed by the same letter are statistically identical at the 5% threshold., ; D: Not weeded World Journal of Advanced Research and Reviews, 2025, 27(02), 1822-1828 1827 4. Discussion Weeding is one of the main factors limiting the production of cultivated plants. Its management increasingly represents a major challenge for achieving good crop yields. This study aimed at improving maize production with higherperforming varieties in the presence of weeds. Phonologically, based on different weeding methods, stamens and cob appearance, and maturity were identical on plots weeded manually and chemically. These parameters, however, were longer in unweeded plots. Weeds therefore had a negative impact on the stages of maize development. This finding was verified by [5] and [11], who showed that weed growth slows down the various phenological phases of maize. Regardless of the type of treatment, plant height, leaf width, leaf length, and the number of leaves did not vary between plots. However, the number of roots was higher in chemically weeded and unweeded plots. Indeed, during manual weeding, some maize roots were damaged, thereby reducing their number. The best agronomic performances were recorded in manually weeded plots, followed by chemically treated plots and control plots. Our results were consistent with those of [12], who showed that manual weeding was more effective for controlling weeds in maize. This technique allows for soil leveling, improves porosity, and reduces water loss and runoff. However, according to [13], the best way to manage weed infestation is to combine mechanical weeding with herbicides. Nevertheless, the issue of herbicide resistance in certain weeds, along with the long time required for manual weeding, has shown that identifying weed-tolerant varieties remains the most appropriate solution [14]. Screening of varieties against competition from weeds showed that weeds significantly delay flowering and ear maturation in all three varieties. These results confirm the observations of [15] on the phenological sensitivity of maize varieties under conditions of total weed cover. The shortest delay in ear maturity (9%) was obtained with the EV variety between weeded and unweeded plots. This reveals its high resilience in competition with weeds compared to the other two varieties, which showed delays of 15% and 18% respectively. The evaluation of agronomic parameters revealed that the EV variety once again stood out for its ability to maintain high agronomic performance, even under weedy conditions, reflecting better weed tolerance. These results could be explained by the fact that EV is an improved variety developed by the National Centre for Agricultural Research (NCAR) for optimal growth and disease resistance. Its ability to limit performance losses under stress conditions indicates high competitiveness with weeds. These findings are consistent with those of [16], who demonstrated that certain maize varieties exhibited greater resilience to competition from weeds. Thus, a judicious varietal selection can significantly reduce yield losses due to weed infestation by identifying those with the highest competitive ability ([17]. However, the purple variety is the most sensitive to weeds, exhibiting reduced growth and overall lower yield in unweeded plots. The yellow variety occupies an intermediate position. 5. Conclusion The present study aimed to identify the maize variety with the highest agronomic performance for improving maize productivity in Côte d’Ivoire. The results revealed that weed infestation delays the different phenological stages of maize, while weeding significantly enhanced both vegetative and reproductive development. The best agronomic performances were observed in manually weeded plots, followed by chemically treated plots, and finally the control plots. The EV variety clearly distinguished itself by maintaining high agronomic performance even under non-weeded conditions, indicating greater tolerance to weed competition. Compliance with ethical standards Disclosure of conflict of interest The authors have not declared any conflict of interests. Author Contributions Anzara and Tano implemented the field trial. Yao and Anzara performed the statistical analysis and drafted the manuscript. World Journal of Advanced Research and Reviews, 2025, 27(02), 1822-1828 1828 References [1] Shahid M, Arshad E, Kamran TA, Shehzadi I, Akram J, Arif Z, Rameesha A, Javaria M. Integrated nutrient management to maintain maize productivity while reducing environmental impacts. Cornous Biology. 2024; 2 (1): 29-35. [2] Nyembo KL, kisimba MM, Theodore MM, Jonas L, Kanyenga LA, Becker NK, Mpundu MM, Baboy LL. Effets de doses croissants des composts de fumiers de poules sur le rendement de chou de chine (Brassica chinensis L.). Journal of Applied Biosciences. 2014; 77: 6505-6522. [3] Mango MG, Mangara A, Kouadio YL, Koné M. Évaluation de la flore adventice dans les cultures de manioc, Manihot esculenta Crantz (Euphorbiaceae) de la zone péri-urbaine d’Abidjan au sud de la Côte d’Ivoire. Journal of Animal & Plant Sciences. 2022; 53(1) : 9580-9659. https://doi.org/10.35759/JAnmPlSci.v53-1.2. [4] Joshi PK, Singh NP, Singh NN, Gerpacio Roberta V, Pingali Prabhu L. Maize in India: Production Systems, Constraints, and Research Priorities. Maize Production Systems Papers 7646, CIMMYT: International Maize and Wheat Improvement Center. 2005. DOI: 10.22004/ag.econ.7646 [5] Colbach N, Fernier A, Le Corre V, Messean A, Darmency H. Simulating changes in cropping practices in conventional and glyphosate-resistant maize. I. Effect on weeds. Environmental Science and Pollution Research. 2017; 24: 13121-13135. doi:10.1007/s11356-017-8591-7 [6] Schmidt-Jeffris RA, Beers EH, Sater C. Meta-analysis and review of pesticide non-target effects on phytoseiids, key biological control agents. Pest Manag. Sci. 2021; 77: 4848–4862. [7] Brovini EM, Quadra GR, Paranaíba JR; Carvalho L, Pereira RO, de Aquino SF, Occurrence and environmental risk assessment of 22 pesticides in Brazilian freshwaters. Aquat. Toxicol. 2023; 260:106566. [8] Zamljen S, Leskovšek R. Critical Period of Weed Control in Maize as Influenced by Soil. Tillage Practices and Glyphosate Application. Agronomy. 2023; 14 (1): 93. [9] N’Goran K. Plan d’aménagement et de gestion du parc national du banco 2019-2028. Office ivoirien des parcs et réserves. Ministère de l’environnement et du développement durable. 145 pages [10] Kimou S.H., Coulibaly L.F., Soumahoro A.B., Koné T. & Koné M. Influence du mode de culture du maïs [Zea Mays (L.) (Poaceae)] et du niébé [Vigna Unguiculata (L.) Walp (Fabaceae)] sur la masse et la qualité nutritionnelle des graines des deux espèces. EuropeanScientific Journal. 2018; 14(36): 501-517. [11] StatSoft (2005). Statistica for windows; version 7.1, statsoft Inc.,Tulsa Soltani N, Dille JA, Burke IC. Potential Corn Yield Losses from Weeds in North America. Weed Technology. 2016; 30(4):979-984. doi:10.1614/WT-D-1600046.1 [12] Yao KB, Yao Beugré MM, Adjoumani K, Bakayoko Y, Kouakou TH. Effects of sowing practice and weed control method on growth and yield of two maize varieties (zea mays L.) cultivated in Côte d’Ivoire. Indian Journal of Plant Sciences. 2021; 10:103-113. [13] Kouamé KF, Sylla M, Touré A. Influences des pratiques culturales sur le développement et les cycles phénologiques des adventices majeures du riz irrigué au Centre de la Côte d’Ivoire. Int. J. Biol. Chem. Sci. 2020; 14 (9): 3253-3261. [14] Chunari A, Shrivastav R. A Cytogenetical Review on Genetic Mechanism of Herbicide Resistance in Corn. Plant Cell Biotechnology and Molecular Biology 2025; 26(3): 63-75. [15] Tardieu F, Simonneau T, Muller B. The physiological basis of drought tolerance in crop plants: a scenariodependent probabilistic approach. Annual Review of Plant Biology. 2018. 69:733–759. [16] Chikoye D, Manyong VM, Ekeleme F. Characteristics of the weed management domain for maize in the northern Guinea savanna of Nigeria. Weed Science. 2010; 58(1): 25-31. [17] Nasir M, Islam, AK. MM, Islam MS, Ahmed S, Salam MA, Anwar MP. Weed Competitiveness of Popular Maize Varieties of Bangladesh. Fundamental and Applied Agriculture. 2024; 9(4): 294–302. https://doi.org/10.5455/faa.243245.