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Editorial

Integrated Weed Management: A Shift towards More Sustainable and Holistic Practices

by
Jose L. Gonzalez-Andujar
Department of Crop Protection, Institute for Sustainable Agriculture (CSIC), 14004 Cordoba, Spain
Agronomy 2023, 13(10), 2646; https://doi.org/10.3390/agronomy13102646
Submission received: 28 September 2023 / Revised: 18 October 2023 / Accepted: 19 October 2023 / Published: 20 October 2023
(This article belongs to the Section Weed Science and Weed Management)

1. Introduction

Feeding more people sustainably is among humanity’s biggest challenges in the next few decades [1]. It is estimated that agricultural production has to increase by 60% by 2050 in order to fulfill the food needs of the population [2]. There are many factors that limit crop production, including the presence of pests, diseases, and weeds.
Since the dawn of agriculture, farmers have come up against weeds. Weeds compete with crops for essential resources such as light, water, and nutrients [3]. Weeds outnumber pests and diseases in terms of their potential impact on crop production, with estimates indicating that they are responsible for the highest potential crop losses (34%) [4]. On a global scale, weeds cause economic losses exceeding US$ 100 billion [5], to which we have to add the cost of herbicides of US$ 25 billion [6]. These numbers underline the importance of keeping weeds under control and the need for a science that studies them. I consider this section to be a call to action to present news insights or perspectives that shape a new approach to sustainable weed management [7].

2. Integrated Weed Management

The discovery and commercialization of 2,4-D and other phenoxy herbicides in the 1940s provided the stimuli that started weed research on its way as a fully-fledged new science, and, since then, weed control has relied mainly on the use of chemical herbicides. Among the reasons for intensive herbicide use are: it is a cost-effective way to control weeds; the lack of threshold-based spraying decisions; and the absence of a sufficiently effective and cheap non-chemical method [8]. All the above has resulted in weed resistance, thus triggering environmental concerns [9]. To date, 269 weed species have evolved resistance to herbicides, and 21 out of 31 known modes of action for herbicides have been affected [10].
The speedy proliferation of herbicide-resistant weeds and the resulting environmental issues have forced farmers to adopt different approaches to weed management, i.e., reducing the employment of synthetic herbicides and their impact and spurring scientific research into seeking new control methods. In this regard, different approaches have been made that have recovered control methods used before the arrival of synthetic herbicides. For example, crop rotation, practiced by farmers since 6000 BC, is a tactic that allows the varying of selection pressure on weeds, preventing the dominance of any one weed species, and delaying the development of herbicide resistance. In southern Spain, the biennial sunflower-winter cereal rotation has been implemented for the last decade. It is aimed at controlling winter weeds and currently forms a consolidated and stable agricultural system [11].
The application of individual tactics may not be enough to achieve efficient weed control due to the high fecundity and dispersal capacity of some weed species [12]. In this context, Integrated Weed Management (IWM), rooted in the Integrated Pest Management concept, has emerged. IWM is an evolving approach that aims to effectively manage and reduce the impact of weeds in agricultural systems [13]. IWM combines different methods, such as chemical, biological, mechanical weeding, and/or specific crop management, to improve the efficiency of weed control. By using multiple strategies simultaneously, farmers can target weeds at different stages of their life cycle and disrupt their growth and reproduction. This approach reduces the reliance on herbicides alone, leading to more sustainable weed management. In recent years, new perspectives have emerged within IWM that reflect a shift towards more sustainable and holistic practices [14]. These tendencies emphasize the importance of integrated approaches, knowledge sharing, and the use of innovative technologies. In this regard, one important tendency is the recognition and integration of ecological principles in weed management [15]. Ecologically-based weed management focuses on understanding the dynamics of weed populations, their interactions with the surrounding environment, and the contribution of weeds to ecosystem services [16,17,18].
Collaboration and knowledge sharing are also becoming increasingly significant in weed management. Farmers, researchers, extension services, and other stakeholders are engaging in collaborative networks to exchange information, experiences, and best practices. This collective approach facilitates the implementation and adaptation of IWM techniques based on local conditions and needs. By working together, stakeholders can develop innovative solutions and share the benefits of successful weed management strategies using Decision Support Systems [19].
Advancements in technology are also shaping new trends in IWM. Precision agriculture tools, such as satellite imagery, drones, and sensors, enable farmers to accurately map and monitor weed infestations in real time [20,21,22]. These technologies provide valuable data for decision-making, allowing farmers to target specific areas with precise interventions. Additionally, advancements in biological control methods (such as the use of beneficial insects, RNAi technology, allelopathy, and microbial bioherbicides [23,24,25,26,27]) offer promising alternatives to conventional chemical herbicide-resistant crops and weeds.
However, it would be essential to explore new extensions of the IWM in order to enhance its effectiveness. One such future development could involve considering the dispersal of weed propagules between fields. In this context, the concept of Landscape Weed Management (LWM) [28] could offer valuable insights in this respect. LWM suggests integrating weed control strategies at various spatial scales, ranging from the field to the landscape. Another step forward is the integration between specific-site management and IWM [29]. Although precision weed control has the potential to reduce herbicide usage by targeting weeds or patches more effectively and minimizing its application to surrounding areas, it does not contribute significantly to the progress of integrated weed management.
Weed management is experiencing a paradigm shift, emphasizing the need to strike a balance between ecosystem services and the disservices offered by weeds. By combining diverse control methods, embracing ecological principles, promoting collaboration, and leveraging innovative technologies, farmers can effectively manage weeds while minimizing the negative environmental, yield, and economic impacts. Future research should focus on understanding the agroecology of weeds and how they can be integrated with digital farming, the social environment, and biotechnology. Ultimately, this shift towards a more sustainable and comprehensive approach to weed management will play a crucial role in ensuring the long-term viability and resilience of agricultural systems.

Funding

This research was funded by FEDER (European Regional Development Funds) and the Spanish Ministry of Science and Innovation funds (grant number PID2019-103929RB-I00) and partially supported by the Junta de Andalucia, Qualifica Project (grant number QUAL21_023 IAS).

Conflicts of Interest

The author declares no conflict of interest.

References

  1. Fróna, D.; Szenderák, J.; Harangi-Rákos, M. The Challenge of Feeding the World. Sustainability 2019, 11, 5816. [Google Scholar] [CrossRef]
  2. Alexandratos, N.; Bruinsma, J. World Agriculture towards 2030/2050: The 2012 Revision; ESA Working Paper No. 12-03; FAO: Rome, Italy, 2012. [Google Scholar]
  3. Bastiaans, L.; Kropff, M.J. Weed competition. In Encyclopedia of Applied Plant Sciences, 2nd ed.; Thomas, B., Murray, B.G., Murphy, D.J., Eds.; Elsevier: Amsterdam, The Netherlands, 2017; Volume 3, pp. 473–478. [Google Scholar]
  4. Oerke, E.C. Crop losses to pests. J. Agric. Sci. 2006, 144, 31–43. [Google Scholar] [CrossRef]
  5. Appleby, A.P.; Muller, F.; Carpy, S. Weed control. In Agrochemicals; Muller, F., Ed.; Wiley: New York, NY, USA, 2000; pp. 687–707. [Google Scholar]
  6. Agrow. Agrochemical Sales Flat in 2002. Agrow: World Crop Protection News. Available online: http://ipm.osu.edu/trans/043_141.htm (accessed on 15 September 2023).
  7. McCauley, C.; Legleiter, T.; Herman, R.; Rasoulpour, R.; Schroeder, J.; Pilcher, T.; Meinders, K.; Wright, T. Sustainable weed management—What is it and how are we doing? Weed Technol. 2022, 36, 768–776. [Google Scholar] [CrossRef]
  8. Munier-Jolain, N.; Chavvel, B.; Gasquez, J. Long-term modelling of weed control strategies: Analysis of threshold-based options for weed species with contrasted competitive abilities. Weed Res. 2002, 42, 107–122. [Google Scholar] [CrossRef]
  9. Duke, S.O.; Heap, I. Evolution of weed resistance to herbicides: What have we learned after seventy years. In Biology, Physiology and Molecular Biology of Weeds; Jugulam, M., Ed.; CRC Press: Boca Raton, FL, USA, 2017. [Google Scholar]
  10. Heap, I. The International Herbicide-Resistant Weeds Database. Available online: www.weedscience.org (accessed on 15 September 2023).
  11. Lopez-Bellido, R.J.; Lopez-Bellido, L.; Castillo, J.E.; Lopez-Bellido, F.J. Sunflower response to tillage and soil residual nitrogen in a wheat-sunflower rotation under rainfed Mediterranean conditions. Aust. J. Agric. Res. 2002, 53, 1027–1033. [Google Scholar] [CrossRef]
  12. Benvenuti, S. Weed seed movement and dispersal strategies in the agricultural environment. Weed Biol. Manag. 2007, 7, 141–157. [Google Scholar] [CrossRef]
  13. Kudsk, P. Advances in Integrated Weed Management, 1st ed.; Burley Dodds Science Publishing: Cambridge, UK, 2022. [Google Scholar]
  14. Korres, N.E.; Burgos, N.R.; Travlos, I.; Vurro, M.; Gitsopoulos, T.K.; Varanasi, V.; Duke, S.O.; Kudsk, P.; Brabham, C.; Rous, C.E.; et al. New directions for integrated weed management: Modern technologies, tools and knowledge discovery. Adv. Agron. 2019, 155, 243–319. [Google Scholar]
  15. Storkey, J.; Neve, P. What good is weed diversity? Weed Res. 2018, 58, 239–243. [Google Scholar] [CrossRef] [PubMed]
  16. Blaix, C.; Moonen, A.C.; Dostatny, D.F.; Izquierdo, J.; Le Corff, J.; Morrison, J. Quantification of regulating ecosystem services provided by weeds in annual cropping systems using a systematic map approach. Weed Res. 2018, 58, 151–164. [Google Scholar] [CrossRef]
  17. MacLaren, C.; Storkey, J.; Menegat, A.; Metcalfe, H.; Dehnen-Schmutz, K. An ecological future for weed science to sustain crop production and the environment. A review. Agron. Sustain. Dev. 2020, 40, 1–29. [Google Scholar] [CrossRef]
  18. Gonzalez-Andujar, J.L.; Aguilera, M.J.; Van Acker, R. Quantifying and Disentangling the Competition Effect of a Weed Community in a Long-Term Biennial Cereal-Legume Rotation. Agronomy 2023, 13, 1432. [Google Scholar] [CrossRef]
  19. Chantre, G.R.; Gonzalez-Andujar, J.L. Decision Support Systems for Weed Management; Springer International Publishing: Cham, Switzerland, 2020. [Google Scholar]
  20. Zhang, W.; Miao, Z.; Li, N.; He, C.; Sun, T. Review of Current Robotic Approaches for Precision Weed Management. Curr. Robot. Rep. 2022, 3, 139–151. [Google Scholar] [CrossRef] [PubMed]
  21. Cravero, A.; Pardo, S.; Sepúlveda, S.; Muñoz, L. Challenges to Use Machine Learning in Agricultural Big Data: A Systematic Literature Review. Agronomy 2022, 12, 748. [Google Scholar] [CrossRef]
  22. Andujar, D.; Martinez-Guanter, J. An Overview of Precision Weed Mapping and Management Based on Remote Sensing. Remote Sens. 2022, 14, 3621. [Google Scholar] [CrossRef]
  23. Uludag, A.; Uremis, I.; Arslan, M. Biological Weed Control. In Non-Chemical Weed Control, 1st ed.; Jabran, K., Chauhan, B.S., Eds.; Elsevier: Amsterdam, The Netherlands; Academic Press: London, UK, 2018; pp. 115–132. [Google Scholar]
  24. Zabala-Pardo, D.; Gaines, T.; Lamego, F.P.; Avila, L.A. RNAi as a tool for weed management: Challenges and opportunities. Adv. Weed Sci. 2022, 40 (Suppl. S1), e020220096. [Google Scholar] [CrossRef] [PubMed]
  25. Khamare, Y.; Chen, J.; Marble, S.C. Allelopathy and its application as a weed management tool: A review. Front. Plant Sci. 2022, 13, 1034649. [Google Scholar] [CrossRef] [PubMed]
  26. Aci, M.M.; Sidari, R.; Araniti, F.; Lupini, A. Emerging Trends in Allelopathy: A Genetic Perspective for Sustainable Agriculture. Agronomy 2022, 12, 2043. [Google Scholar] [CrossRef]
  27. Duke, S.O.; Pan, Z.; Bajsa-Hirschel, J.; Boyette, C.D. The potential future roles of natural compounds and microbial bioherbicides in weed management in crops. Adv. Weed Sci. 2022, 40 (Suppl. S1), e020210054. [Google Scholar] [CrossRef] [PubMed]
  28. Gonzalez-Andujar, J.L.; Plant, R.E.; Fernandez-Quintanilla, C. Modeling the effect of farmers’ control decisions on the population dynamics of winter wild oat (Avena sterilis ssp. ludoviciana) in an agricultural landscape. Weed Sci. 2001, 49, 414–422. [Google Scholar] [CrossRef]
  29. Young, S.L. Beyond precision weed control: A model for true integration. Weed Technol. 2018, 32, 7–10. [Google Scholar] [CrossRef]
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Gonzalez-Andujar, J.L. Integrated Weed Management: A Shift towards More Sustainable and Holistic Practices. Agronomy 2023, 13, 2646. https://doi.org/10.3390/agronomy13102646

AMA Style

Gonzalez-Andujar JL. Integrated Weed Management: A Shift towards More Sustainable and Holistic Practices. Agronomy. 2023; 13(10):2646. https://doi.org/10.3390/agronomy13102646

Chicago/Turabian Style

Gonzalez-Andujar, Jose L. 2023. "Integrated Weed Management: A Shift towards More Sustainable and Holistic Practices" Agronomy 13, no. 10: 2646. https://doi.org/10.3390/agronomy13102646

APA Style

Gonzalez-Andujar, J. L. (2023). Integrated Weed Management: A Shift towards More Sustainable and Holistic Practices. Agronomy, 13(10), 2646. https://doi.org/10.3390/agronomy13102646

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