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Plant Science Today (PST)

Review Articles

Vol. 11 No. sp4 (2024): Recent Advances in Agriculture by Young Minds - I

Advances and trends in weed management: A comprehensive review

DOI
https://doi.org/10.14719/pst.5141
Submitted
19 September 2024
Published
28-12-2024
Versions

Abstract

Weed management is a critical aspect of agricultural practices that can significantly impact crop yield and quality. As traditional methods face challenges such as herbicide resistance and environmental concerns, the agricultural sector is witnessing a shift towards innovative strategies for weed control. This review explores the emerging trends in weed management, focusing on sustainable and efficient approaches. Among them, one prominent trend is the adoption of agro ecological weed management strategies, which combine various control methods such as cultivation techniques, mechanical techniques, biological control and reasonable herbicide use. This approach minimizes reliance on herbicides while maximizing weed suppression and preserving natural ecosystems. Another significant trend is developing and utilizing precision agriculture technologies for targeted weed control techniques such as satellite imaging, unmanned aerial vehicles (UAVs) and sensor-based systems. These innovations enable farmers to accurately identify and manage weeds, reducing herbicide usage and minimizing environmental impact. Furthermore, the exploration of alternative weed control methods, including thermal, electrical and microwave-based technologies, is gaining momentum. These non-chemical approaches offer potential solutions to herbicide-resistant weeds and contribute to sustainable agricultural practices. Moreover, the integration of advanced breeding techniques and biotechnology for developing herbicide-resistant crops and enhancing allelopathic traits presents promising avenues for long-term weed management. In conclusion, this review highlights emerging technology for dealing with major problems, including increased understanding of weed biology linked with genomics; novel herbicide-resistant crops and redesigned weed-competing crops; multi-target herbicides; and enhanced biocontrol agents. When combined, these strategies could make up the elements of the next integrated packages designed to impede the emergence of new weed issues.

References

  1. FAO. https://www.fao.org/publications/home/fao-flagship-publications/the-state-of-food-and-agriculture/en
  2. Sosnoskie, Lynn M, Stephen O Duke. Implications of weakening of the united states geological survey pesticide national synthesis project for weed scientists. Weed Science. 2023;71(6):517-19. https://doi.org/10.1017/wsc.2023.59
  3. Liebman M, Baraibar B, Buckley Y, Childs D, Christensen S, Cousens R, et al. Ecologically sustainable weed management: How do we get from proof-of-concept to adoption? Ecol Appl. 2016;26(5):1352-69. https://doi.org/10.1002/15-0995
  4. HRAC. 2023. https://hracglobal.com/tools/2024-hrac-global-herbicide-moa-classification
  5. Chauhan BS, Matloob A, Mahajan G, Aslam F, Florentine SK, Jha P. Emerging challenges and opportunities for education and research in weed science. Front Plant Sci. 2017;8:1537. https://doi.org/10.3389/fpls.2017.01537
  6. Mortensen DA, Egan JF, Maxwell BD, Ryan MR, Smith RG. Navigating a critical juncture for sustainable weed management. Biosci. 2012;62(1):75-84. https://doi.org/10.1525/bio.2012.62.1.12
  7. Verma SK, Singh SB, Meena RN, Prasad SK, Meena RS, Gaurav A. A review of weed management in India: The need of new directions for sustainable agriculture. Bioscan. 2015;10:253-63. https://thebioscan.com/index.php/pub/article/download/1451/1398
  8. Mishra JS, Rao AN, Singh VP, Kumar R. Weed management in major field crops. Advances in Weed Management. Indian Society of Agronomy. 2016;1-23. Available from:https://www.researchgate.net/profile/Rakesh-Kumar-59/publication/309771518_Weed_management_in_major_field_crops/links/5a0fd32e458515cc5aa6a7d2/Weed-management-in-major-field-crops.pdf
  9. Travlos I, Gazoulis I, Kanatas P, Tsekoura A, Zannopoulos S, Papastylianou P. Key factors affecting weed seeds' germination, weed emergence and their possible role for the efficacy of false seedbed technique as weed management practice. Front Agron. 2020;2:1. https://doi.org/10.3389/fagro.2020.00001
  10. Anderson RL. A rotation design to reduce weed density in organic farming. Renew Agric Food Syst. 2010;25(3):189-95. https://doi.org/10.1017/S1742170510000256
  11. Narwal SS. Weed management in rice: Wheat rotation by allelopathy. Critical Reviews in Plant Sciences. 2000;19(3):249-66. https://doi.org/10.1080/07352680091139222
  12. Davis AS, Raghu S. Weighing abiotic and biotic influences on weed seed predation. Weed Res. 2010;50(5):402. https://doi.org/10.1111/j.1365-3180.2010.00790.x
  13. Fernando M, Shrestha A. The potential of cover crops for weed management: A sole tool or component of an integrated weed management system. Plant J. 2023;12(4):752. https://doi.org/10.3390/plants12040752
  14. Brooker RW, Pakeman RJ, Adam E, Banfield-Zanin JA, Bertelsen I, Bickler C, et al. Positive effects of intercrop yields in farms from across Europe depend on rainfall, crop composition and management. ASD. 2024;44(4):35. https://doi.org/10.1007/s13593-024-00968-2
  15. Wang Z, Wang C, Tan X, Lou H, Wang X, Shao D, et al. Developing diversified forage cropping systems for synergistically enhancing yield, economic benefits and soil quality in the Yangtze river Basin. Agric Ecosyst Environ. 2024;365:108929. https://doi.org/10.1016/j.agee.2024.108929
  16. Begam A, Pramanick M, Dutta S, Paramanik B, Dutta G, Patra PS, et al. Inter-cropping patterns and nutrient management effects on maize growth, yield and quality. Field Crops Res. 2024;310:109363. https://doi.org/10.1016/j.fcr.2024.109363
  17. Hashim S, Marwat KB, Saeed M, Haroon M, Waqas M, Shah F. Developing a sustainable and eco-friendly weed management system using organic and inorganic mulching techniques. Pak J Bot. 2013;45(2):483-86. https://doi/full/10.5555/20133151183
  18. Mahmood, Azhar, Muhammad Zahid Ihsan, Abdul Khaliq, Saddam Hussain, Zahid Ata Cheema, et al. Crop residues mulch as organic weed management strategy in maize. Clean–Soil, Air, Water. 2016;44(3):317-24. https://doi.org/10.1002/clen.201500155
  19. Testani E, Ciaccia C, Campanelli G, Leteo F, Salvati L, Canali S. Mulch-based no-tillage effects on weed community and management in an organic vegetable system. Agronomy. 2019;9(10):594. https://doi.org/10.3390/agronomy9100594
  20. Mas MT, Pardo G, Pueyo J, Verdú AM, Cirujeda A. Can hydro-mulch reduce the emergence of perennial weeds. Agronomy. 2021;11(2):393. https://doi.org/10.3390/agronomy11020393
  21. Nichols V, Verhulst N, Cox R, Govaerts B. Weed dynamics and conservation agriculture principles: A review. Field Crops Res. 2015;183:56-68. https://doi.org/10.1016/j.fcr.2015.07.012
  22. Smith RG, Warren ND, Cordeau S. Are cover crop mixtures better at suppressing weeds than cover crop monocultures? Weed Sci. 2020;68(2):86-94. https://doi.org/10.1017/wsc.2020.12
  23. Tripathi A, Singh AK, Singh S, Gupta S, Kaushik S, Gupta SP, et al. Effect of tillage, crop residue and weed management practices on yield attributes and yield of timely sown wheat (Triticum aestivum L.) in sub-tropical India. Afr J Bio Sc. 2024;6:8605-19. https://doi.org/10.33472/AFJBS.6.6.2024.8605-8619
  24. Walsh MJ, Squires CC, Coleman GR, Widderick MJ, McKiernan AB, Chauhan BS, et al. Tillage based, site-specific weed control for conservation cropping systems. Weed Technol. 2020;34(5):70410. https://doi.org/0.1017/wet.2020.34
  25. Lodha AK, Thakur R, Tabasshum S, Singh S. Effect of fertilizer and manure on weed incidence, depletion of nutrients by weeds and yield of soybean. IJWS. 2009;41(3):201-03. https://doi.org/ IJWS-2009-41-3&4
  26. Sweeney AE, Renner KA, Laboski C, Davis A. Effect of fertilizer nitrogen on weed emergence and growth. Weed Sci. 2008;56:714-21. https://doi.org/10.1614/WS-07-096.1
  27. Chandel NS, Chandel AK, Roul AK, Solanke KR, Mehta CR. An integrated inter-and intra-row weeding system for row crops. Crop Prot. 2021;145:105642. https://doi.org/10.1016/j.cropro.2021.105642
  28. Knezevic SZ. Ecological weed management in row crops. Ecologically-based weed management: Concepts, challenges and limitations. United States.Wiley. 2023;14:261-69. https://doi.org/10.1002/9781119709763.ch14
  29. Harding DP, Raizada MN. Controlling weeds with fungi, bacteria and viruses: A review. Front Plant Sci. 2015;6:659. https://doi.org/10.3389/fpls.2015.00659
  30. Mortensen K. Biological control of weeds using microorganisms. In: Boland GJ, Kuykendall LD, editors. Plant-microbe interactions and biological control. Marcel Dekker, Inc., New York, 1998; p. 223–47.
  31. Bailey KL. The bioherbicide approach to weed control using plant pathogens. Integrated Pest Management: Current concepts and ecological perspectives, Elsevier, San Diego. 2014;245-66. https://doi.org/10.1016/B978-0-12-398529-3.00014-2
  32. Ray P. Evaluation of augmentative release of Zygogramma bicolorata Pallister (Coleoptera: Chrysomelidae) for biological control of Parthenium hysterophorus L. Crop Prot. 2011;30(6):587-91. https://doi.org/10.1016/j.cropro.2011.02.005
  33. Markin GP, Littlefield JL. Biological control of tansy ragwort (Senecio jacobaeae L.) by the cinnabar moth, Tyria jacobaeae (CL) (Lepidoptera: Arctiidae), in the northern rocky mountains. In: Proceedings of the XII International Symposium on Biological Control of Weeds, La Grande Motte, France; 2007:583-88. https://doi/abs/10.1079/9781845935061.0583
  34. Webber III CL, Shrefler JW. Corn gluten meal and spring-transplanted onions (Allium cepa L.): Crop safety, weed control and yields. In: National Allium Research Conference. College Station TX: Texas A & M; 2006 Dec 29.p87. https://doi.10.1300/J512v13n03_03
  35. Travlos I, Kanatas P, Tsekoura A, Gazoulis I, Papastylianou P, Kakabouki I, Antonopoulos N. Efficacy of different herbicides on Echinochloa colona (L.) link control and the first case of its glyphosate resistance in Greece. Agronomy. 2020;10(7):1056. https://doi.org/10.3390/agronomy10071056
  36. Melander, B. Current achievements and future directions of physical weed control in Europe. AFPP—3rd International Conference on Non-chemical Crop Protection Methods, Lille, France. 2006; p. 49-58.
  37. Peruzzi A, Martelloni L, Frasconi C, Fontanelli M, Pirchio M, Raffaelli M. Machines for non-chemical intra-row weed control in narrow and wide-row crops: A review. J Agric Eng. 2017;48(2):5770. https://doi.org/10.4081/jae.2017.583
  38. Machleb J, Peteinatos GG, Sökefeld M, Gerhards R. Sensor-based intra-row mechanical weed control in sugar beets with motorized finger weeders. Agronomy. 2021;11(8):1517. https://doi.org/10.3390/agronomy11081517
  39. Simpson S, Stephen. Portable steam weed killing apparatus. United States patent US. 2000. https://patents.google.com/patent/US6029589A/en
  40. Melander B, McCollough MR. Advances in mechanical weed control technologies. Burleigh Dodds Series in Agricultural Science. Aaarhus University, Cambridge, UK. 2021. http://dx.doi.org/10.19103/AS.2021.0098.11
  41. Gürsoy S, Özaalan C. Effects of the share types of an inter-row cultivator at different working depths on weed control and plant growth in cotton production. Agric Sci Technol. 2023;154:1313-8820. http://doi.org/10.15547/ast.2023.04.038
  42. Dwivedi N, Kumar D, Suryavanshi P. Precision farming techniques for sustainable weed management. ELSR. 2022;8:142-49. https://doi.org/10.31783/elsr.2022.82142149
  43. Mishra AM, Kaur P, Singh MP, Singh SP. A self-supervised overlapped multiple weed and crop leaf segmentation approach under complex light condition. Multimed Tools Appl. 2024; p. 1-26. https://doi.org/10.1007/s11042-024-18272-2
  44. Monteiro A, Santos S. Sustainable approach to weed management: The role of precision weed management. Agronomy. 2022;12(1):118. https://doi.org/10.3390/agronomy12010118
  45. McAllister W, Whitman J, Varghese J, Davis A, Chowdhary G. Agbots 3.0: Adaptive weed growth prediction for mechanical weeding agbots. IEEE T-RO. 2021;38(1):556-68. https://doi.org/10.1109/TRO.2021.3083204
  46. Huang Y, Reddy KN, Fletcher RS, Pennington D. UAV low-altitude remote sensing for precision weed management. Weed Technol. 2018;32(1):2-6. https://doi.org/10.1017/wet.2017.89
  47. Singh V, Rana A, Bishop M, Filippi AM, Cope D, Rajan N, Bagavathiannan M. Unmanned aircraft systems for precision weed detection and management: Prospects and challenges. Adv Agron. 2020;159:93-134. https://doi.org/10.1016/bs.agron.2019.08.004
  48. Gonzalez-de-Soto M, Emmi L, Perez-Ruiz M, Aguera J, Gonzalez-de-Santos P. Autonomous systems for precise spraying–Evaluation of a robotised patch sprayer. Biosyst Eng. 2016;146:165-82. http://dx.doi.org/10.1016/j.biosystemseng.2015.12.018
  49. Chostner B. See and spray: The next generation of weed control. Resour Magazine. 2017;24(4):4-5. Available from: https://elibrary.asabe.org/abstract.asp?aid=47805
  50. Kanimozhi G, Sathayamoorthy NK, Babu R, Prabhakaran J. Effect of herbigation through micro sprinkler on weeds flora, weed dry weight and weed control efficiency. Int J Chem Stud. 2019;7(3):3528-31. Available from: https://www.chemijournal.com/archives/?year=2019&vol=7&issue=3&ArticleId=6061&si=false
  51. Manisankar G, Ghosh P, Malik GC, Banerjee M. Recent trends in chemical weed management: A review. The Pharma Innovation. 2022;11(4):745-53. https://www.thepharmajournal.com/archives/?year=2022&vol=11&issue=4&ArticleId=11906
  52. Barbieri GF, Young BG, Dayan FE, Streibig JC, Takano HK, Merotto Jr A, Avila LA. Herbicide mixtures: Interactions and modeling. Advances in Weed Science. 2022;40:e020220051. https://doi.org/10.51694/AdvWeedSci/2022;40:seventy-five011
  53. Scavo A, Mauromicale G. Integrated weed management in herbaceous field crops. Agronomy. 2020;10(4):466. https://doi.org/10.3390/agronomy1004046
  54. Walsh MJ, Broster JC, Schwartz-Lazaro LM, Norsworthy JK, Davis AS, Tidemann BD, et al. Opportunities and challenges for harvest weed seed control in global cropping systems. Pest Manag Sci. 2018;10:2235-45. https://doi.org/10.1002/ps.4802
  55. Walsh M, Newman P, Powles S. Targeting weed seeds in-crop: A new weed control paradigm for global agriculture. Weed Technol. 2013;27(3):431-36. https://doi.org/10.1614/WT-D-12-00181.1
  56. Patterson KM, Schwartz-Lazaro LM, LaBiche G, Stephenson IV DO. Effects of narrow-windrow burning on weed dynamics in soybean in Louisiana. Front Agron. 2021;3:730280. https://doi.org10.2135/cropsci2017.03.0210
  57. Walsh MJ, Powles SB. Management strategies for herbicide-resistant weed populations in Australian dryland crop production systems. Weed Technol. 2007;21(2):332-38. https://doi.org/10.1614/WT-06-086.1
  58. Schwartz-Lazaro LM, Norsworthy JK, Walsh MJ, Bagavathiannan MV. Efficacy of the integrated harrington seed destructor on weeds of soybean and rice production systems in the Southern United States. Crop Sci. 2017;57(5):2812-18. https://doi/abs/10.2135/cropsci2017.03.0210
  59. Ruttledge A, Widderick M, Walsh M, Broster J, Bell K, Rayner A, et al. The efficacy of chaff lining and chaff tramlining in controlling problem weeds. Grains Research Update. 2018;26. https://grdc.com.au/data/assets/pdf_file/0022/364711/GRDC-Grains-Research-Update-Narromine-2018.pdf#page=27
  60. DeSousa N, Griffiths JT, Swanton CJ. Predispersal seed predation of redroot pigweed (Amaranthus retroflexus). Weed Sci. 2003;51(1):60-68. https://doi.org/10.1614/0043-1745(2003)051[0060:PSPORP]2.0.CO;2
  61. Türke M. Complicating a complex ecosystem function: The controversial role of gastropods in a Myremcochorous seed dispersal mutualism. Doctoral Dissertation, Friedrich-Schiller-Universität Jena, Diss. 2011. https://core.ac.uk/download/pdf/224755728.pdf
  62. Ichihara M, Inagaki H, Matsuno K, Saiki C, Yamashita M, Sawada H. Postdispersal seed predation by Teleogryllus emma (Orthoptera: Gryllidae) reduces the seedling emergence of a non-native grass weed, Italian ryegrass (Lolium multiflorum). Weed Biol Manag. 2012;12(3):131-35. https://doi.org/10.1111/j.1445-6664.2012.00445.x
  63. Jha P, Kumar V, Godara RK, Chauhan BS. Weed management using crop competition in the United States: A review. Crop Prot. 2017;1(95):31-37. https://doi.org/10.1016/j.cropro.2016.06.021
  64. Andrew IK, Storkey J, Sparkes DL. A review of the potential for competitive cereal cultivars as a tool in integrated weed management. Weed Res. 2015;55(3):239-48. https://doi.org/10.1111/wre.12137b
  65. Gage KL, Krausz RF, Walters SA. Emerging challenges for weed management in herbicide-resistant crops. Agriculture (Basel). 2019;9(8):180. https://doi.org/10.3390/agriculture9080180
  66. Green JM. The benefits of herbicide-resistant crops. Pest Manag Sci. 2012;68(10):1323-31. https://doi.org/10.1002/ps.3374
  67. Peerzada AM, Chauhan BS. Thermal weed control: History, mechanisms and impacts. In: Non-chemical Weed Control. Academic Press. United Kingdom; 2018.9-31. https://doi.org/10.1016/B978-0-12-809881-3.00002-4
  68. Hoyle JA. Factors affecting thermal weed control. Auburn University. Final Dissertation. 2012. http://hdl.handle.net/10415/2980
  69. Spagnolo RT, Custódio TV, Morais CS, Reis ÂV, Machado AL. Heat-applicator machine for weed control. Engenharia Agrícola. 2020;40(5):595-600. http://doi.org/10.1590/1809-4430
  70. Martelloni L, Frasconi C, Sportelli M, Fontanelli M, Raffaelli M, Peruzzi A. Hot foam and hot water for weed control: A comparison. J Agric Eng. 2021;52(3):10. https://doi.org/10.4081/jae.2021.1167
  71. Cutulle MA, Armel GR, Brosnan JT, Kopsell DA, Hart WE, Vargas JJ, et al. Evaluation of a cryogenic sprayer using liquid nitrogen and a ballasted roller for weed control. JTE. 2013;41(6):869-74. https://doi.org/10.1520/JTE20120296
  72. Forcella F. Air-propelled abrasive grit for postemergence in-row weed control in field corn. Weed Technol. 2012;26(1):161-64. https://doi.org/10.1614/WT-D-11-00051.1
  73. Nawaz A, Farooq M, Cheema SA, Cheema ZA. Role of allelopathy in weed management. Recent Advances in Weed Management. Springer, NewYork. 2014;39-61. https://doi.org/10.1007/978-1-4939-1019-9_3
  74. Ahn JK, Chung IM. Allelopathic potential of rice hulls on germination and seedling growth of barnyard grass. J Agron. 2000;92(6):1162-67. https://doi.org/10.2134/agronj2000.9261162x
  75. Aslam F, Khaliq A, Matloob A, Tanveer A, Hussain S, Zahir ZA. Allelopathy in agro-ecosystems: A critical review of wheat allelopathy-concepts and implications. Chemoecology. 2017;27:1-24. https://doi.org/10.1007/s00049-016-0225
  76. Jabran K, Jabran K. Allelopathy: Introduction and concepts. Manipulation of allelopathic crops for weed control. Springer Brief in Plant Science. Springer Cham. 2017;p. 1-2. https://doi.org/10.1007/978-3-319-53186-1
  77. Chou CH. The role of allelopathy in agroecosystems: Studies from tropical Taiwan. In: Agroecology: Researching the Ecological Basis for Sustainable Agriculture. New York, NY: Springer New York; 1990; p. 78. https://doi.org/10.1007/978-1-4612-3252-0_7
  78. Singh HP, Batish DR, Pandher JK, Kohli RK. Assessment of allelopathic properties of Parthenium hysterophorus residues. Agric Ecosyst Environ. 2003;95(2-3):537-41. https://doi.org/10.1016/S0167-8809(02)00202-5
  79. Ghosh S, Sarkar B, Thongmee S. Nano herbicides for field applications. In: Agricultural Nanobiotechnology.Woodhead Publishing. 2022; p. 439-63. https://doi.org/10.1201/9781003364429
  80. Shan P, Zhang M, Lian X, Lu W, Yin X, Liu H, et al. Rational design of acid-degradable polymeric micelles in response to root-mediated pH changes for site-specific herbicide delivery. Ind Crop Prod. 2023;202:116991. https://doi.org/10.1016/j.indcrop.2023.116991
  81. Shweta, Sood S, Sharma A, Chadha S, Guleria V. Nanotechnology: A cutting-edge technology in vegetable production. JHSB. 2021;96(6):682-95. https://doi.org/10.1080/14620316.2021.1902864
  82. Susha VS, Chinnamuthu CR. Synthesis and characterization of Iron based nanoparticles for the degradation of atrazine herbicide. Res J Nanosci Nanotechnol. 2012;2:79-86. https://doi.org/10.3923/rjnn.2012.79.86
  83. Zotti M, Dos Santos EA, Cagliari D, Christiaens O, Taning CN, Smagghe G. RNA interference technology in crop protection against arthropod pests, pathogens and nematodes. Pest Manag. Sci. 2018;74(6):1239-50. https://doi.org/10.1002/ps.4813
  84. Huirong Dong, Yong Huang, Kejian Wang. The development of herbicide resistance crop plants using CRISPR/Cas9-mediated gene editing. Genes. 2021;12(6):912. https://doi.org/10.3390/genes12060912
  85. Patzoldt WL, Hager AG, McCormick JS, Tranel PJ. A codon deletion confers resistance to herbicides inhibiting protoporphyrinogen oxidase. Proceedings of the National Academy of Sciences. 2006;103(33):123. https://doi.org/10.1073/pnas.0603137103
  86. Han YJ, Kim JI. Application of CRISPR/Cas9-mediated gene editing for the development of herbicide-resistant plants. Plant Biotechnol Rep. 2019;13(5):447-57. https://doi.org/10.1007/s11816-019-00575-8
  87. Pannell DJ, Stewart V, Bennett A, Monjardino M, Schmidt C, Powles SB. RIM: a bioeconomic model for integrated weed management of Lolium rigidum in Western Australia. Agric Syst. 2004;79(3):305-25. https://doiorg/10.1016/S0308-521X(03)00089-1
  88. Kropff MJ, Weaver SE, Smits MA. Use of ecophysiological models for crop-weed interference: Relations amongst weed density, relative time of weed emergence, relative leaf area and yield loss. Weed Sci. 1992;40(2):296-301. https://doi.org/10.1017/S0043174500057374
  89. Bagavathiannan MV, Beckie HJ, Chantre GR, Gonzalez-Andujar JL, Leon RG, Neve P, et al. Simulation models on the ecology and management of arable weeds: structure, quantitative insights and applications. Agronomy. 2020;10(10):1611. https://doi.org/10.3390/agronomy10101611
  90. Wu W, Mesgaran MB. Exploring sterile pollen technique as a novel tool for management of Palmer amaranth (Amaranthus palmeri). Weed Sci. 2024;72(3):234-40. https://doi.org/10.1017/wsc.2024.7
  91. Ghersa CM, Holt JS. Using phenology prediction in weed management: A review. Weed Res. 1995;35(6):461-70. https://doi.org/10.1111/j.1365-3180.1995.tb01643.x
  92. Abubakar BS. Weed detection using machine learning: A systematic literature review. Syst Lit Rev Meta-Anal J. 2021;2:61–73.
  93. Abubakar BS. Weed detection using machine learning: A systematic literature review. Systematic Literature Review and Meta-Analysis Journal. 2021;2(2):61–73. https://doi.org/10.54480/slrm.v2i2.21
  94. Ghatrehsamani S, Jha G, Dutta W, Molaei F, Nazrul F, Fortin M, et al. Artificial intelligence tools and techniques to combat herbicide-resistant weeds—A review. Sustainability. 2023;15(3):1843. https://doi.org/10.3390/su15031843
  95. Osorio K, Puerto A, Pedraza C, Jamaica D, Rodríguez L. A deep learning approach for weed detection in lettuce crops using multispectral images. AgriEngineering. 2020;2(3):471-88. https://doi.org/10.3390/agriengineering2030032
  96. Göktogan AH, Sukkarieh S, Bryson M, Randle J, Lupton T, Hung C. A rotary-wing unmanned air vehicle for aquatic weed surveillance and management. J Intell Robot Syst. 2010;57:467-84. https://doi.org/10.1007/s10846-009-9371-5
  97. Peña JM, Torres-Sánchez J, de Castro AI, Kelly M, López-Granados F. Weed mapping in early-season maize fields using object-based. 2013;8(10):77151. https://doi.org/10.1371/journal.pone.0077151
  98. Bonadies S, Gadsden SA. An overview of autonomous crop row navigation strategies for unmanned vehicles. EAEF. 2019;12(1):24-31. https://doi.org/10.1016/j.eaef.2018.09.001
  99. Sulaiman N, Che’Ya NN, Mohd Roslim MH, Juraimi AS, Mohd Noor N, Fazlil Ilahi WF. The application of hyperspectral remote sensing imagery (HRSI) for weed detection analysis in rice fields: A Review Appl Sci. 2022;12(5):2570. https://doi.org/10.3390/app12052570
  100. Patterson EL, Saski C, Küpper A, Beffa R, Gaines TA. Omics potential in herbicide-resistant weed management. Plants. 2019;8(12):607. https://doi.org/10.3390%2Fplants8120607
  101. Maroli AS, Gaines TA, Foley ME, Duke SO, Dogramaci M, Anderson JV, et al. Omics in weed science: A perspective from genomics, transcriptomics and metabolomics approaches. Weed Sci. 2018;66(6):681-95. https://doi.org/10.1017/wsc.2018.33
  102. Larrinua IM, Belmar SB. Bioinformatics and its relevance to weed science. Weed Sci. 2008;56(2):297-305. http://dx.doi.org/10.1614/WS-07-079.1
  103. Westwood JH, Charudattan R, Duke SO, Fennimore SA, Marrone P, Slaughter DC, et al. Weed management in 2050: Perspectives on the future of weed science. Weed Sci. 2018;66(3):275-85. http://dx.doi.org/10.1017/wsc.2017.78
  104. Deng W, Yang M, Li Y, Xia Z, Chen Y, Yuan S, Yang Q. Enhanced metabolism confers a high level of cyhalofop-butyl resistance in a Chinese sprangle top (Leptochloa chinensis (L.) Nees) population. Pest Manag Sci. 2021;77(5):2576-83. https://doi.org/10.1002/ps.6297
  105. Genze N, Vahl WK, Groth J, Wirth M, Grieb M, Grimm DG. Manually annotated and curated dataset of diverse weed species in maize and sorghum for computer vision. Scientific Data. 2024;11(1):109. https://doi.org/10.1038/s41597-024-02945-6
  106. Chiou A, Yu X. Industrial decision support system (IDSS) in weed control and management strategies: Expert advice using descriptive schemata and explanatory electronics society capabilities. In: IECON 2007-33rd Annual Conference of the IEEE Industrial. 2007; p. 105-10. http://dx.doi.org/10.1109%2FIECON.2007.4460407
  107. Parsons DJ, Benjamin LR, Clarke J, Ginsburg D, Mayes A, Milne AE, Wilkinson DJ. Weed manager—A model-based decision support system for weed management in arable crops. Comput Electron Agr. 2009;65(2):155-67. https://doi.org/10.1016/j.compag.2008.08.007
  108. Boinot S, Alignier A, Storkey J. Landscape perspectives for agroecological weed management. A review. ASD. 2024;44(1):7. https://doi.org/10.1007/s13593-023-00941-5
  109. Kaur A, Singh G, Menon S, Kumari K. Integrated weed management: A comprehensive review of conventional, non-conventional and emerging strategies for sustainable agriculture. J Adv Biol Biotechnol. 2024;27(8):156-67. https://doi.org/10.9734/jabb/2024/v27i81130
  110. Varma N, Wadatkar H, Salve R, Kumar TV. Advancing sustainable agriculture: A comprehensive review of organic farming practices and environmental impact. J Exp Agric Int. 2024;46(7):695-703. https://doi.org/10.9734/jeai/2024/v46i72623

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