A Smartphone-Based Silver Nanoparticle Assay for Detecting Enhanced Gamma-Aminobutyric Acid Content in Germinated Rice via Metabolic Modulation
- 1Srinakharinwirot University , , ,
Abstract
This study aimed to increase the γ-aminobutyric acid (GABA) content in rice grains and develop surface-modified silver nanoparticles (AgNPs) as a simple colorimetric chemosensor for its detection. To stimulate GABA production, rice grains from the Kor Kho 6 (RD6) and Khao Dawk Mali 105 (KDML105) cultivars were treated with various solutions targeting the GABA metabolic pathways. Results demonstrated that simultaneously supplementing the GABA substrate with 2% (w/v) monosodium glutamate and inhibiting GABA transaminase with a 2% (w/v) rosmarinic acid solution yielded the highest GABA content. For quantitative detection of GABA, surface-modified AgNPs with citrate (Cit-AgNPs) were synthesized and characterized using UV–visible spectrophotometry, transmission electron microscopy (TEM), and dynamic light scattering (DLS). The Cit-AgNPs successfully quantified GABA levels, as evidenced by a colorimetric shift from yellow to green. This transition corresponded to a decrease in absorbance at 393 nm and the emergence of a shoulder peak in the 450–550 nm region. This sensing mechanism was subsequently integrated with the PhotoMetrix smartphone application, offering a practical and accessible platform for GABA quantification. Analysis of RGB color intensity revealed a linear relationship between the green color intensity and GABA concentration in the range of 50–500 ppm (R2 = 0.9757). The assay demonstrated a limit of detection (LOD) of 44.20 ppm and a limit of quantification (LOQ) of 147.00 ppm. Furthermore, the GABA content measured in rice grains using this smartphone-based method closely aligned with the standard high-performance liquid chromatography (HPLC) results, exhibiting an error margin of approximately 5%. These findings indicate that this smartphone-based method holds significant potential for practical application in resource-limited testing facilities.
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BibTeX
@article{tongraung2026smartphonebased,
title = {{A Smartphone-Based Silver Nanoparticle Assay for Detecting Enhanced Gamma-Aminobutyric Acid Content in Germinated Rice via Metabolic Modulation}},
author = {Pan Tongraung and Ladnaphone Hadaoheuang and Piyathida Piyasakulwong and Pichamon Phonraksa and Supakan Rattanakon},
journal = {ACS Omega},
year = {2026},
month = oct,
doi = {10.1021/acsomega.6c03525},
url = {https://pubs.acs.org/acsodf/article/11/41/62606/5444919/A-Smartphone-Based-Silver-Nanoparticle-Assay-for},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - JOUR
TI - A Smartphone-Based Silver Nanoparticle Assay for Detecting Enhanced Gamma-Aminobutyric Acid Content in Germinated Rice via Metabolic Modulation
AU - Pan Tongraung
AU - Ladnaphone Hadaoheuang
AU - Piyathida Piyasakulwong
AU - Pichamon Phonraksa
AU - Supakan Rattanakon
PY - 2026
DA - 2026/10/05
JO - ACS Omega
DO - 10.1021/acsomega.6c03525
UR - https://pubs.acs.org/acsodf/article/11/41/62606/5444919/A-Smartphone-Based-Silver-Nanoparticle-Assay-for
AB - This study aimed to increase the γ-aminobutyric acid (GABA) content in rice grains and develop surface-modified silver nanoparticles (AgNPs) as a simple colorimetric chemosensor for its detection. To stimulate GABA production, rice grains from the Kor Kho 6 (RD6) and Khao Dawk Mali 105 (KDML105) cultivars were treated with various solutions targeting the GABA metabolic pathways. Results demonstrated that simultaneously supplementing the GABA substrate with 2% (w/v) monosodium glutamate and inhibiting GABA transaminase with a 2% (w/v) rosmarinic acid solution yielded the highest GABA content. For quantitative detection of GABA, surface-modified AgNPs with citrate (Cit-AgNPs) were synthesized and characterized using UV–visible spectrophotometry, transmission electron microscopy (TEM), and dynamic light scattering (DLS). The Cit-AgNPs successfully quantified GABA levels, as evidenced by a colorimetric shift from yellow to green. This transition corresponded to a decrease in absorbance at 393 nm and the emergence of a shoulder peak in the 450–550 nm region. This sensing mechanism was subsequently integrated with the PhotoMetrix smartphone application, offering a practical and accessible platform for GABA quantification. Analysis of RGB color intensity revealed a linear relationship between the green color intensity and GABA concentration in the range of 50–500 ppm (R2 = 0.9757). The assay demonstrated a limit of detection (LOD) of 44.20 ppm and a limit of quantification (LOQ) of 147.00 ppm. Furthermore, the GABA content measured in rice grains using this smartphone-based method closely aligned with the standard high-performance liquid chromatography (HPLC) results, exhibiting an error margin of approximately 5%. These findings indicate that this smartphone-based method holds significant potential for practical application in resource-limited testing facilities.
SN - 2470-1343
ER -