Abstract: At present, a large tract of farmland or soil may be contaminated by heavy metal, which could make agricultural products polluted, bringing a harmful effect on human health.Hence, it is necessary to determine the heavy metal concentration in farmland soil.Rapid detection of heavy metals in soil is a key point of information acquirement tools in precision agriculture, and it also provides a base on prevention soil heavy metal pollution and sustainable development of agriculture.The traditional techniques for determining heavy metals is high in cost, time-consuming, use of large amount of chemicals, complex in sample preparation, and expensive in experimental device, etc.Laser-induced breakdown spectroscopy (LIBS), a form of atomic emission spectroscopy (AES), is regarded as a useful tool for rapid, real-time and in situ measurements because of its unique characteristics, such as no or less sample preparation, multi-element analysis, direct measurement without contact with the materials, stand-off or remote analysis and high detecting speed.Relying on those unique capabilities, LIBS technique has a tremendous growth and been widely applied in variety of areas, such as environmental monitoring, geological applications, biomedical detection, industrial analysis, agriculture and food.In order to evaluate the feasibility of determining the heavy metals in soil, in this research, we employed LIBS technology combined with calibration curve and chemometrics methods to quantitatively analyze the content of Pb and Cd in soil samples.Soil samples with different Pb and Cd concentration were prepared.A laboratorial LIBS device working in air was employed to obtain the spectra of soil samples.Based on analysis of LIBS curves and the data from atomic spectra database in national institute of standards and technology (NIST), emission lines at Pb I 405.78 and Cd I 361.05 nm (I was atomic spectral line) were identified as characteristic lines.Then, models and calibration curves based on LIBS intensity, Lorentz fit intensity after normalized, peak areas and corresponding content were established and fitted.For Pb element, the linear relationships of coefficient of determination (R2) of three methods were: 0.98385, 0.97097 and 0.99321, respectively.And Cd element failed to provide an effective linear relationship.Meanwhile, PLSR (Partial Linear Square Regression) model for predicting Pb and Cd were built and results demonstrated that the calibration curve and PLSR model provided similar performance, resulting in correlation coefficient of 0.9485 and root mean square error of 2.044 mg/g in the prediction set.And PLSR model for Cd element prediction revealed the promising results, resulting in correlation coefficient of 0.9949 and root mean square error of 97.05 μg/g in the prediction set.The achievements of the research not only provides a guide for detecting heavy metals in soil, but also lays a theoretical foundation for development of the portable LIBS detector used in the field.