Content of citrus is one of the important factors affecting storage and processing of citrus. Realtime detection of water content of citrus can guarantee the quality of citrus. The visible/near infrared spectroscopy technology,as an increasingly mature nondestructive testing method,can effectively detect the water content of citrus. The Satsuma mandarin picked from the Institute of Forest and Fruit at Wuhan Academy of Agricultural Sciences were placed naturally at room temperature for reducing the water content of the Satsuma mandarin and increasing the water content gradient of the citrus. A spectrum collection device was built with Maya2000pro as a carrier. The score is obtained by dewatering in a super electric heating constant temperature blast drying oven and calculated according to GB 5009.3-2016. The fitting accuracy of partial least squares regression (PLS) model established was compared through the use of differential processing,multivariate scattering correction,standard normal variate,SG convolution smoothing,standardization and other pretreatment methods. Results showed that SNV was the most effective preprocessing method. At the same time,a competitive adaptive reweighted sampling algorithm is used to extract characteristic wavelengths to establish a partial least square regression model,a BP neural network model and a least square support vector machine model based on water content of citrus. The results showed that the LSSVM model established with 359 wavelengths obtained by CARS screening using the spectrum after SNV preprocessing had the best prediction effect. The correlation coefficient and root mean square error of the calibration set are 0.937 5 and 0.008 6,respectively. The correlation coefficient of the verification set and the root mean square error are 0.831 6 and 0.012 0. The natural placement method at room temperature improves the water content gradient of Satsuma mandarin,thereby ensuring the adaptability of the model. It is indicated that the visible/near infrared spectroscopy technology is feasible for detecting the water content of Satsuma mandarin.