# A SERS/LSPR Dual-Signal Aptamer Sensor for Abscisic Acid Detection Based on Unmodified Gold Nanoparticles

## TL;DR

This paper introduces a new sensor for detecting abscisic acid in plants using gold nanoparticles and two signals, making detection faster and simpler.

## Contribution

A dual-signal aptamer sensor using unmodified gold nanoparticles for sensitive and rapid abscisic acid detection is developed.

## Key findings

- The SERS detection range was 0.04–40 µM with a LOD of 17.6 nM.
- The LSPR detection range was 0.4–80 µM with a LOD of 36 nM.
- The sensor successfully detected abscisic acid in cucumber and tomato samples.

## Abstract

The plant hormone abscisic acid (ABA) plays an important role in crop growth and development, so it is urgent to establish a simple and sensitive method for the detection of ABA. (1) As one of the most sensitive spectral detection methods, surface-enhanced Raman spectroscopy (SERS) has made some progress in the detection of ABA, but it involved a complicated modification process of noble metal nanoparticles and was time-consuming. (2) In this work, a SERS and (local surface plasmon resonance) LSPR dual-signal aptamer (Apt) sensor based on the aggregation of dispersed (gold nanoparticles) AuNPs and the improved plasmonic coupling with formed SERS was developed and applied to the detection of the plant hormone ABA. Through the specific recognition of Apt and ABA, the prepared crystal violet (CV) and Apt modified AuNPs tended to aggregate in a high concentration salt solution, resulting in changes in LSPR characteristics of the detection system and enhanced SERS intensity of CV signal molecules. Thus, the quantitative relationship between ABA concentration and SERS intensity of signal molecule CV and the degree of absorbance change of AuNPs were established. (3) The linear range detection of SERS was 0.04~40 µM, the detection limit lod (LOD) was 17.6 nM, the linear range detection of LSPR was 0.4~80 µM, and the LOD was 36 nM. (4) The sensor has a good ability to detect ABA in the samples of common plants such as cucumber and tomato and has the characteristics of no chemical bond modification, more reliable detection results, and a universal detection platform.