RESPONSE OF WEEDING REGIMES AND PLANTING LOCATION ON THE GROWTH AND YIELD OF SOYBEAN
Abstract
Soybean (Glycine max (L.) is an important staple and industrial crop grown in tropical, subtropical and temperate regions of the world. However, its production is constrained by incessant weed competition for nutrient, water and sunlight which reduces output. To minimize the impact of weed competition, this study assessed the effectiveness of different weed management regimes. Soybean seeds were sown in two (2) locations of Delta State (Asaba and Ozoro), and the weed management regimes were T1: No weeding, T2: weeding 3 weeks after planting, T3: weeding 3, 6 weeks after planting, T4: weeding, 3, 6, 9 weeks after planting, and T5: weeding all through. The experiment was a 2 (location) by 5 (weeding regimes) factorial arranged in a randomized complete block design (RCBD) and replicated three times. Data were collected on the agronomic and number of pods produced. Data collected were analysed using analysis of variance and means were separated using least significant differences. At 12 weeks after planting, the plant height, number of leaves and number of pods produced differed significantly and ranged from 24.33±1.02 (Asaba) to 41.46±1.02 (Ozoro), 21.47±1.69 (Asaba) to 48.10±1.69 (Ozoro), and 15.25±1.39 (Asaba) to 24.44±1.39 (Ozoro) between locations, and ranged from 31.90±1.90 (T2) to 37.97±1.90 (T5), 23.93±3.18 (T1) to 41.63±3.18 (T5), and 12.78±2.62 (T1) to 25.01±2.62 (T5) amongst the treatments. Keeping the soybean farm weed-free ensures higher productivity relative to less weeded plots.
Downloads
References
Bianchi F, Stewart C, Astbury NM, Cook B, Aveyard P, Jebb SA. Replacing meat with alternative plant-based products (RE-MAP): a randomized controlled trial of a multicomponent behavioral intervention to reduce meat consumption. Am J ClinNutr. (2021). 32:2416–2425.doi: 10.1093/ajcn/nqab414.
Briceno, R., Lopez, S.R., Lopez, S.O., Oliva-cruz, M., Fernandez, G.D., Murga, T.E., Trigoso, I.D., Gurbillion, B.M &Barboza, E. (2021). Site selection for a network of weather stations using AHP and near analysis in a GIS environment in Amazona, NW Peru. Climate 9 (12): 169
Chaudhary, Juhi& S M, Shivaraj& Khatri, Praveen & Ye, Heng& Zhou, Lijuan&Usovsky, Mariola&Dhakate, Priyanka&Kumawat, Giriraj&Patil, Gunvant&Sonah, Humira&Ratnaparkhe, Milind&Deshmukh, Rupesh& Nguyen, Henry. (2019). Approaches, Applicability, and Challenges for Development of Climate-Smart Soybean. 10.1007/978-3-319-93536-2_1.
Duan Z, Li Q, Wang H, He X, Zhang M (2023) Genetic regulatory networks of soybean seed size, oil and protein contents. Front Plant Sci 14:1160418
Ekeleme, F., Kumar, P.L., Ademulegun, T., Solomon, R.
Ekeleme, F., Kumar, P.L., Ademulegun, T., Solomon, R.
Fasusi, Samuel & Kim, Ji-Min & Kang, Sungtaeg. (2022). Current Status of Soybean Production in Nigeria: Constraint and Prospect. Journal of the Korean Society of International Agriculture. 34. 149-156. 10.12719/KSIA.2022.34.2.149.
Fussy, Andre &Papenbrock, Jutta. (2022). An Overview of Soil and Soilless Cultivation Techniques—Chances, Challenges and the Neglected Question of Sustainability. Plants. 11. 1153. 10.3390/plants11091153.
Gai, Yuhong& Liu, Shuhao& Zhang, Zhidan& Wei, Jian& Wang, Hongtao& Liu, Lu &Bai, Qianyue& Qin, Qiushi& Zhao, Chungang& Zhang, Shuheng& Xiang, Nan & Zhang, Xiao. (2025). Integrative Approaches to Soybean Resilience, Productivity, and Utility: A Review of Genomics, Computational Modeling, and Economic Viability. Plants. 14. 671. 10.3390/plants14050671.
Gaut BS, Seymour DK, Liu Q, Zhou Y (2018) Demography and its effects on genomic variation in crop domestication. Nat Plants 4:512–520
Goettel W, Zhang H, Li Y, Qiao Z, Jiang H, Hou D, Song Q, Pantalone VR, Song BH, Yu D et al (2022) POWR1 is a domestication gene pleiotropically regulating seed quality and yield in soybean. Nat Commun 13:3051
Horn, Lydia &Shimelis, Hussein. (2020). Production constraints and breeding approaches for cowpea improvement for drought prone agro-ecologies in Sub-Saharan Africa. Annals of Agricultural Sciences. 65. 10.1016/j.aoas.2020.03.002.
IFAD (2019). Soybean production manual. Enhanced small holders Agri-business promotion programme for field Extension Facilitators . Ministry of Agriculture, Republic of Zarrbia, P.1
Khamare, Yuvraj& Chen, Jianjun& Marble, Stephen. (2022). Allelopathy and its application as a weed management tool: A review. Frontiers in Plant Science. 13. 10.3389/fpls.2022.1034649.
Korav, Santosh & Dhaka, Anil & Singh, Ram & Reddy, G.. (2018). A study on crop weed competition in field crops. 7. 3235-3240.
Lu L, Wei W, Li QT, Bian XH, Lu X, Hu Y, Cheng T, Wang ZY, Jin M, Tao JJ et al (2021a) A transcriptional regulatory module controls lipid accumulation in soybean. New Phytol 231:661–678
national Institute of Tropical Agriculture, Ibadan, Nigeria. p.4
national Institute of Tropical Agriculture, Ibadan, Nigeria. p.4
Neve, Paul &Caicedo, Ana. (2022). Weed Adaptation as a Driving Force for Weed Persistence in Agroecosystems. 10.1002/9781119525622.ch15.
Obidiebube, Eucharia&Akparobi, Achebe. (2013). EVALUATION OF SOYBEAN VARIETIES (GLYCINE MAX L MERIL), FOR ADAPTATION TO TWO LOCATIONS OF RAINFOREST ZONE OF DELTA STATE. European Journal of Business and Innovation Research Vol.1, No.3, pp, 69 -73
Omoigui, L. O., Kamara, A. Y., Kamai, N., Dugje, I. Y., Ekeleme, E., Kumar, P. L., Ademulegun, T., Solomon, R. (2020). Guide to soybean production in Northern Nigeria. International Institute of Tropical Agriculture, Ibadan, Nigeria. P.4.
Omoigui, L.O., Kamara, A.Y., Kamai, N., Dugje, I.Y.,
Omoigui, L.O., Kamara, A.Y., Kamai, N., Dugje, I.Y.,
Omoigui, L.O., Kamara, A.Y., Kamai, N., Dugje, I.Y., Ekeleme, F., Kumar, P.L. and & Solomon, R. (2020). Guide to soybean production in northern Nigeria. Ibadan, Nigeria: IITA, (31 p.).
Schmutz, Jeremy & Cannon, Steven &Schlueter, Jessica & Ma, Jianxin&Mitros, Therese & Nelson, William &Hyten, David & Song, Qijian& Cheng, Jianlin&Xu, Dong &Hellsten, Uffe& May, Gregory & Yu, Yeisoo& Sakurai, Tetsuya &Umezawa, Taishi& Bhattacharyya, Madan& Sandhu, Devinder&Valliyodan, Babu& Jackson, Scott. (2010). Genome sequence of the paleopolyploid soybean. Nature. 463. 178-83. 10.1038/nature08670.
Song J, Im J, Kim J, Kim D , Lim Y, Yook M, Lim S and Kim D.
Song, J., Im, J., Kim, J., Kim, D., Lim, Y., Yook, M., Lim, S. and Kim, D. (2021). Modelling the effects of nitrogen fertilizer and multiple weed interference on soybean yield. Agronomy, 11:515.
Storkey, J., Addy, J., Mead, A., Macdonald, AJ.,(2021). Agricultural intensication and climate change have increased the threat from weeds. Global Change Biology 27,
Tehulie, Nuru&Misgan, Tenalem& Awoke, Tigist. (2021). Review on weeds and weed controlling methods in soybean (Glycine max L.). International Journal of Current Research. 1-06.
Toomer, Ondulla& Oviedo, Edgar & Ali, Muhammad &Patino, Danny & Joseph, Michael &Frinsko, Michael & Vu, Thien&Maharjan, Pramir& Fallen, Ben &Mian, Rouf. (2023). Current Agronomic Practices, Harvest & Post-Harvest Processing of Soybeans (Glycine max)—A Review. Agronomy. 13. 427. 10.3390/agronomy13020427.
weed interference on soybean yield. Agronomy11: 515.
Zhang YL, Li CH, Wang YW, Hu YM, Christie P, Zhang JL, (2016). Maize yield and soil fertility with combined use of compost and inorganic fertilizers on a calcareous soil on the North China Plain. Soil & Tillage Research. 155: 85–94.
Author(s) and co-author(s) jointly and severally represent and warrant that the Article is original with the author(s) and does not infringe any copyright or violate any other right of any third parties, and that the Article has not been published elsewhere. Author(s) agree to the terms that the GPH Journal will have the full right to remove the published article on any misconduct found in the published article.
