Abstract: Abstract: Lingwu long jujube, as one of the special advantage fruits in Ningxia Hui Autonomous Region, is favored by consumer. The traditional methods used in fruit soluble solids content detection are destructive testing and can't satisfy the fruit commercialization testing requirements because the fruit has lost its commodity value after testing. With simple principle and strong adaptability, dielectric spectrum detection technology is easy to operate and nondestructive, and has become the development trend of fruit quality nondestructive testing in recent years. In order to explore the possibility of predicting LingWu long jujube soluble solids content and to establish optimal prediction model of long jujube soluble solids content based on the dielectric spectrum, dielectric loss factor ε″ spectra and dielectric constant ε′ spectra of 300 long jujube were measured with a network analyzer under 101 selected frequency points in the frequency range of 200 MHz-18 GHz. The prediction model of soluble solids content was researched using the long jujube dielectric loss factor ε″ spectra and dielectric constant ε′ spectra. The 300 jujubes are divided into calibration set and prediction set according to the proportion of 4:1 using K-S method. The influences of frequencies and storage time on long jujube dielectric parameters were discussed with variance analysis method. The effective information of the dielectric spectra was extracted by genetic algorithm (GA) and correlation coefficient method (CC). Prediction model of soluble solids content was established using partial least squares (PLS), principal components regression (PCR) and support vector machine (SVM). The best modeling method was acquired by comparative analysis of determination coefficient R2, the standard deviation RMSEC and the standard deviation RMSEP. The results indicated that, with the frequency increasing, dielectric loss factor ε″ of long jujube decreased first and then increased, while dielectric constant ε′ decreased gradually. The polarization characteristic frequency ?r of long jujube in the GHz frequency segments was 5.74 GHz gained from the spectrum curve. The analysis of variance indicated that frequency and storage time had a significant influence on dielectric properties. It is feasible to predict the soluble solids content based on the dielectric spectra. In order to improve the reliability of sugar prediction model, the effective information extraction methods of GA and CC were analyzed comparatively. 15 characteristic frequency points of the dielectric loss factor ε″ and 14 characteristic frequency points of the dielectric constant ε′ were optimized by GA. 14 effective frequency points of the dielectric loss factor ε″ and 19 effective frequency points of the dielectric constant ε′ were optimized by CC. Among them, the polarization characteristic frequency ?r (5.74 GHz) of ε″ and ε′ could be found by both GA and CC. The modeling effect with the extracted effective information using GA and CC is better than that with original spectrum modeling, the modeling effect with PCR is better than that with PLS and SVM. The optimal prediction models of soluble solids content based on dielectric loss factor ε″ and dielectric constant ε′ spectra were GA-PCR and CC-PCR respectively. The effect of GA-PCR modeling with dielectric loss factor ε″ is better than that of CC-PCR modeling with dielectric constant ε′, the correlation coefficients of calibration set and prediction set are 0.933 and 0.925 respectively, and the root mean square errors (RMSE) were 0.661 and 0.702.