Rice exposure to silver nanoparticles in a life cycle study: effect of dose responses on grain metabolomic profile, yield, and soil bacteria

Abstract

Under an appropriate exposure dose, AgNPs provide positive impacts on rice tillering, yield, grain metabolite profile, and soil bacteria.

Antifungal mechanisms of silver nanoparticles on mycotoxin producing rice false smut fungus

“…However, Ag was primarily distributed in the rice hull and surface of the grains (bran), and is not delivered into the polished grains at the 1 mg/kg and 10 mg/kg doses. 6 Due to antimicrobial activities of AgNPs, it is necessary to evaluate the application potential of AgNPs on preventing the phytopathogenic fungi U . virens .…”

“… 5 Recent study showed that low doses of AgNPs increases the yield and tillering of rice, which provides a positive theoretical basis for the practical application of AgNPs. 6 …”

AgNPs-Triggered Seed Metabolic and Transcriptional Reprogramming Enhanced Rice Salt Tolerance and Blast Resistance

“…The hydrodynamic diameter and ζ potential of the AgNPs were 134.7 ± 1.38 nm and 9.95 ± 0.76 mV, respectively, as measured by dynamic light scattering (Zetasizer Nano ZS, Malvern), with well dispersed 40 mg/L AgNPs suspensions. The peroxidase-like (POD-like) catalytic activity of AgNPs (15 mg/L) was determined using a nanozyme-catalyzed colorimetric reaction, which has been described in our previous publication …”

“…After wiping the surface water with king wipes, rice seeds were snap-frozen in liquid nitrogen for complete metabolic inactivation, and then ground into fine powder using pestle and mortar in liquid nitrogen. Metabolite extraction was carried out by following our previous method . Specifically, 60 mg of tissue powder was added into a 1.5 mL Eppendorf tube, followed by adding 360 μL of prechilled methanol and 40 μL of the internal standard 2-chloro- l -phenylalanine (0.06 mg/mL methanol).…”

“…Metabolites were unambiguously assigned by the BinBase identifier numbers using retention index and mass spectrum as the two most important identification criteria. More details regarding sample derivatization and GC-MS analysis are referenced in previous study …”