水稻是我国主要的粮食作物之一,重金属含量的检测对其安全性及品质具有 重要意义。激光诱导击穿光谱(LIBS)有望克服传统方法检测耗时的缺点,实现水稻等作物植株中重金属含量的快速 原位定量检测。利用共线双脉冲激光诱导击穿光谱(DP-LIBS)技术对水稻叶片中的重金属镉(Cd)元素进行了分析。 由于不同的特征谱线对结果有不同影响,为获取更准确、稳定的分析结果,采用样品表面多点烧蚀的实验方法,讨论 了Cd I: 228.8 nm、Cd II: 214.4 nm和Cd II: 226.5 nm三条共振线对于定标曲线相关系数(R2)和预测结果的 影响。对比研究发现, 532 nm激光先于1064 nm激光进行激发,且两束脉冲时间间隔为0.5 μs时能够获取最好的 光谱强度;在三条分析谱线中, Cd I: 228.8 nm、Cd II: 214.4 nm和Cd II: 226.5 nm谱线的定标曲线R2值分 别为0.86、0.60和0.93, 原子谱线定量结果高于离子谱线; Cd I: 228.8 nm谱线预测相对误差 低于10%, 检测限是3.03 mg/kg。实验表明通过对LIBS检测条件的优化,可以实现对水稻叶片中的重金属含量的检 测。另外实验中所优化的光谱采集和特征谱线选择方法,也有望应用在不同农产品的重金属成分检测上。

Abstract: Rice is one of the main food crops in China, and the detection of heavy metal content is of great significance for its safety and quality. Laser-induced breakdown spectroscopy (LIBS) is expected to overcome the shortcomings of traditional methods for detecting time-consuming and achieve rapid insitu quantitative detection of heavy metals in crop plants such as rice. The collinear double-pulse laser-induced breakdown spectroscopy (DP-LIBS) technique was used to analyze the heavy metal Cd elements in rice leaves. Because different characteristic spectral lines have different effects on the results, in order to obtain more accurate and stable analysis results, the multi-point ablation test method of the sample surface was used to discuss the influence of the three resonance lines of Cd I: 228.8 nm, Cd II: 214.4 nm, and Cd II: 226.5 nm on the coefficient and prediction results of the calibration curve. The comparative study found that the best spectral intensity can be obtained when the 532 nm laser is excited before the 1064 nm laser, and the two pulses have a time interval of 0.5 μs. Among the three analytical lines, the calibration coefficients R2 of Cd I: 228.8 nm, Cd II: 214.4 nm and Cd II: 226.5 nm spectral lines are 0.86, 0.60, and 0.93 respectively, and it is found that the quantitative results of atomic spectral lines are higher than that of the ionic spectral lines. Further study shows that the relative prediction errors of Cd I: 228.8 nm spectral lines are less than 10%, and the detection limit is 3.03 mg/kg. Experiments show that by optimizing the detection conditions of LIBS, the detection of heavy metal contents in rice leaves can be achieved. In addition, the optimized spectral acquisition and characteristic spectral line selection methods in the experiment are also expected to be applied to the detection of heavy metal components in other different agricultural products.