Abstract Malachite green is not used in aquaculture owing to its severe toxic effects on humans and other living organisms. The presence of this compound in fishery water should be quantified and reported in all water quality reports. In this paper, a method based on surface-enhanced Raman scattering combined with partial least squares regression for rapid, accurate, reliable, and sensitive detection of trace malachite green in fishery water is described. A prepared sol of 100-nm-size gold particles was used as an active substrate for Raman spectral data acquisition. Three parameters that affect detection, namely, the volume of gold nanoparticles (400 µL), the volume of sodium chloride (300 µL), and the adsorption time (8 min) were optimized in single-factor experiments. Under the optimal condition, the proposed method demonstrated a wide linear range of detectable concentrations (0.01–5.0 µmol/L) and the limit of detection was 2.7 × 10−9 M. The proposed method successfully detected spiked malachite green in fishery water samples, with satisfactory recoveries and relative standard deviations. Thus, this study suggests a rapid, simple, accurate, and sensitive approach for detecting malachite green residues in fishery water samples, which is promising for wide applications in environmental monitoring and food safety.

中文翻译：

---

使用偏最小二乘回归的表面增强拉曼光谱使用大尺寸金纳米粒子快速准确检测水产养殖水中的孔雀石绿

摘要 孔雀石绿对人类和其他生物体具有严重的毒性作用，因此不用于水产养殖。渔业用水中该化合物的存在应量化并在所有水质报告中报告。在本文中，描述了一种基于表面增强拉曼散射结合偏最小二乘回归的方法，用于快速、准确、可靠和灵敏地检测渔业水中的痕量孔雀石绿。制备的 100 nm 大小的金颗粒溶胶用作拉曼光谱数据采集的活性基质。在单因素实验中优化了影响检测的三个参数，即金纳米粒子的体积 (400 µL)、氯化钠的体积 (300 µL) 和吸附时间 (8 分钟)。在最优条件下，所提出的方法表明可检测浓度的线性范围很宽 (0.01–5.0 µmol/L)，检测限为 2.7 × 10−9 M。所提出的方法成功地检测了渔业水样中的加标孔雀石绿，具有令人满意的回收率和相对标准偏差。因此，本研究提出了一种快速、简单、准确、灵敏的检测渔业水样中孔雀石绿残留的方法，有望在环境监测和食品安全方面得到广泛应用。