为了提高激光诱导击穿光谱技术的检测能力和准确性，分别采用单变量分析和多变量分析方法[多元线性回归(MLR)]对样品中Cr 进行定量分析。分别利用CrI: 425.435 nm 和CrI: 427.48 nm 两条特征谱线进行单变量分析，并在5 种不同激光能量下获得了Cr 的检测限，结果表明谱线CrI: 425.435 nm 的分析结果要优于CrI: 427.48 nm，获得Cr 最佳的检测限为5.8 mg/g。利用多变量分析方法，研究了浓度预测值与浓度实际值之间的线性相关性，与单变量分析方法相比，线性相关性由0.98 提高到了0.99 以上；采用留一交叉验证方法，比较了两种方法的预测相对误差(REP)，单变量分析方法的REP 分别为6.73％和7.59％，而MLR 分析方法的REP 则为4.66％，结果表明激光诱导击穿光谱技术结合MLR 能够提高样品浓度预测的准确性。

In order to improve the detection capability and accuracy of laser-induced breakdown spectroscopy (LIBS), the univariate and multivariate method [multiple linear regression (MLR)] are adopted to make quantitative analysis on Cr contained in samples respectively. Univariate analysis has been made by use of two characteristic spectral lines CrI: 425.435 nm and CrI: 427.48 nm, the limits of detection are obtained under the condition of five laser energies. The results indicate that the analytical results of CrI: 425.435 nm are better than CrI: 427.48 nm, the best limit of detection of Cr is achieved 5.8 mg/g. The linear correlation between the prediction and actual values of concentration of samples is discussed using MLR, the correlation coefficient is increasing to above 0.99 from 0.98 compared with univariate method. Using the approach of leave-one-cross-validation, the relative errors of prediction (REP) of univariate analysis of CrI: 425.435 nm and CrI: 427.48 nm are 6.73％ and 7.59％ respectively, while the REP of MLR is reduced to 4.66％ . The results indicate that LIBS combined with MLR can improve the accuracy of prediction on concentration of samples.