| Literature DB >> 32628442 |
Peiguang Hu1, Jing An1,2, Maquela M Faulkner1, Honghong Wu1, Zhaohu Li2, Xiaoli Tian2, Juan Pablo Giraldo1.
Abstract
Fundamental and quantitative understanding of the interactions between nanoparticles and plant leaves is crucial for advancing the field of nanoenabled agriculture. Herein, we systematically investigated and modeled how ζ potential (-52.3 mV to +36.6 mV) and hydrodynamic size (1.7-18 nm) of hydrophilic nanoparticles influence delivery efficiency and pathways to specific leaf cells and organelles. We studied interactions of nanoparticles of agricultural interest including carbon dots (CDs, 0.5 and 5 mg/mL), cerium oxide (CeO2, 0.5 mg/mL), and silica (SiO2, 0.5 mg/mL) nanoparticles with leaves of two major crop species having contrasting leaf anatomies: cotton (dicotyledon) and maize (monocotyledon). Biocompatible CDs allowed real-time tracking of nanoparticle translocation and distribution in planta by confocal fluorescence microscopy at high spatial (∼200 nm) and temporal (2-5 min) resolution. Nanoparticle formulations with surfactants (Silwet L-77) that reduced surface tension to 22 mN/m were found to be crucial for enabling rapid uptake (<10 min) of nanoparticles through the leaf stomata and cuticle pathways. Nanoparticle-leaf interaction (NLI) empirical models based on hydrodynamic size and ζ potential indicate that hydrophilic nanoparticles with <20 and 11 nm for cotton and maize, respectively, and positive charge (>15 mV), exhibit the highest foliar delivery efficiencies into guard cells (100%), extracellular space (90.3%), and chloroplasts (55.8%). Systematic assessments of nanoparticle-plant interactions would lead to the development of NLI models that predict the translocation and distribution of nanomaterials in plants based on their chemical and physical properties.Entities:
Keywords: agriculture; carbon dots; cerium oxide nanoparticles; crops; silica nanoparticles; surfactant
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Year: 2020 PMID: 32628442 DOI: 10.1021/acsnano.9b09178
Source DB: PubMed Journal: ACS Nano ISSN: 1936-0851 Impact factor: 15.881