Abstract: Aiming at the problems of large size, high cost and destructive detection of the traditional method of heavy metal cadmium detection in vegetable leaves, a method for detecting heavy metal cadmium in vegetable leaves based on visible light-near-infrared spectroscopy was proposed, and a method was built without pretreatment. The heavy metal cadmium detection instrument with fast detection speed, small size and easy to carry can be suitable for mobile on-site detection. Nutrient solution of four heavy metal cadmium stress gradients（0 mg/L, 1 mg/L, 3 mg/L and 5 mg/L） was configured, lettuce samples were cultivated under each cadmium stress, and leaf reflectance data was collected through a hyperspectral imaging system. Three characteristic bands（550 nm, 680 nm and 800 nm） were selected by using principal component analysis（PCA）, and a heavy metal cadmium detection model was built by using partial least squares regression（PLSR）. The correlation coefficient R_P of test set was 0.914 9, and the root mean square error of test set was 0.527 1 mg/kg. The designed detection instrument for heavy metal cadmium in vegetable leaves included: light source part, signal processing part, display part, power supply part and control part. The size of the instrument was 50 mm×70 mm×60 mm. Using self-made instrument for calibration experiment, selecting A/D acquisition voltage as reference, calibration data were used for modeling, model training set correlation coefficient R_c was 0.858 1, training set root mean square error was 0.497 5 mg/kg, test set correlation coefficient R_p was 0.843 2, root mean square error of the test set was 0.552 6 mg/kg, and the model prediction performance was better. Finally, the detection accuracy of the portable heavy metal cadmium nondestructive testing instrument was verified. Totally 30 groups of cadmium-stressed lettuce leaves were selected for real-time detection, which were not related to the modeling. Compared with the standard physical and chemical values, the root mean square error was 0.32 mg/kg, and the absolute measurement error was-0.69～0.66 mg/kg, the average absolute error was 0.26 mg/kg. The results showed that the instrument can realize real-time non-destructive detection of cadmium content in lettuce leaves.