College of Biosystems Engineering and Food science, Zhejiang University, Hangzhou 310058, China.
Key Laboratory of Spectroscopy Sensing, Ministry of Agriculture, Hangzhou 310058, China.
Sensors (Basel). 2018 Feb 18;18(2):621. doi: 10.3390/s18020621.
Fast detection of toxic metals in crops is important for monitoring pollution and ensuring food safety. In this study, laser-induced breakdown spectroscopy (LIBS) was used to detect the chromium content in rice leaves. We investigated the influence of laser wavelength (532 nm and 1064 nm excitation), along with the variations of delay time, pulse energy, and lens-to-sample distance (LTSD), on the signal (sensitivity and stability) and plasma features (temperature and electron density). With the optimized experimental parameters, univariate analysis was used for quantifying the chromium content, and several preprocessing methods (including background normalization, area normalization, multiplicative scatter correction (MSC) transformation and standardized normal variate (SNV) transformation were used to further improve the analytical performance. The results indicated that 532 nm excitation showed better sensitivity than 1064 nm excitation, with a detection limit around two times lower. However, the prediction accuracy for both excitation wavelengths was similar. The best result, with a correlation coefficient of 0.9849, root-mean-square error of 3.89 mg/kg and detection limit of 2.72 mg/kg, was obtained using the SNV transformed signal (Cr I 425.43 nm) induced by 532 nm excitation. The results indicate the inspiring capability of LIBS for toxic metals detection in plant materials.
快速检测作物中的有毒金属对于监测污染和确保食品安全非常重要。在这项研究中,激光诱导击穿光谱(LIBS)被用于检测水稻叶片中的铬含量。我们研究了激光波长(532nm 和 1064nm 激发)、延迟时间、脉冲能量和透镜-样品距离(LTSD)的变化对信号(灵敏度和稳定性)和等离子体特征(温度和电子密度)的影响。通过优化实验参数,我们使用单变量分析对铬含量进行定量,并采用几种预处理方法(包括背景归一化、面积归一化、乘法散射校正(MSC)变换和标准化正态变量(SNV)变换)进一步提高分析性能。结果表明,532nm 激发比 1064nm 激发具有更好的灵敏度,检测限约低两倍。然而,两种激发波长的预测精度相似。使用 532nm 激发产生的 SNV 变换信号(Cr I 425.43nm)获得了最佳结果,相关系数为 0.9849,相对标准偏差为 3.89mg/kg,检测限为 2.72mg/kg。结果表明,LIBS 对植物材料中有毒金属的检测具有激发能力。