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  4. Silicon nanoparticles: Comprehensive review on biogenic synthesis and applications in agriculture
 
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Silicon nanoparticles: Comprehensive review on biogenic synthesis and applications in agriculture

Type
Journal article
Language
English
Date issued
2023
Author
Mahawar, Lovely
Ramasamy, Kesava Priyan
Suhel, Mohammad
Prasad, Sheo Mohan
Živčák, Marek
Brestic, Marian
Rastogi, Anshu 
Skalický, Milan
Faculty
Wydział Inżynierii Środowiska i Inżynierii Mechanicznej
Journal
Environmental Research
ISSN
0013-9351
DOI
10.1016/j.envres.2023.116292
Web address
https://www.sciencedirect.com/science/article/abs/pii/S0013935123010964
Volume
232
Number
1 September 2023
Pages from-to
art. 116292
Abstract (EN)
Recent advancements in nanotechnology have opened new advances in agriculture. Among other nanoparticles, silicon nanoparticles (SiNPs), due to their unique physiological characteristics and structural properties, offer a significant advantage as nanofertilizers, nanopesticides, nanozeolite and targeted delivery systems in agriculture. Silicon nanoparticles are well known to improve plant growth under normal and stressful environments. Nanosilicon has been reported to enhance plant stress tolerance against various environmental stress and is considered a non-toxic and proficient alternative to control plant diseases. However, a few studies depicted the phytotoxic effects of SiNPs on specific plants. Therefore, there is a need for comprehensive research, mainly on the interaction mechanism between NPs and host plants to unravel the hidden facts about silicon nanoparticles in agriculture. The present review illustrates the potential role of silicon nanoparticles in improving plant resistance to combat different environmental (abiotic and biotic) stresses and the underlying mechanisms involved.
Furthermore, our review focuses on providing the overview of various methods exploited in the biogenic synthesis of silicon nanoparticles. However, certain limitations exist in synthesizing the well-characterized SiNPs on a laboratory scale. To bridge this gap, in the last section of the review, we discussed the possible use of the machine learning approach in future as an effective, less labour-intensive and time-consuming method for silicon nanoparticle synthesis. The existing research gaps from our perspective and future research directions for utilizing SiNPs in sustainable agriculture development have also been highlighted.
Keywords (EN)
  • nanotechnology

  • silicon nanoparticles

  • environmental stress

  • biological synthesis

  • machine learning algorithm

License
closedaccessclosedaccess Closed Access
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