In this paper, Lingwu Long Jujube VC content was regarded as the research object, and a combination of hyperspectral imaging technique with chemometrics method was used to explore a rapid and nondestructive detecting method for fruit internal components. Vitamin C content of Long jujube was measured by high performance liquid chromatography (HPLC). A total of 164 Lingwu long jujubes of hyperspectral images in region of 400~1 000 nm were acquired. Then spectral curves were obtained by ENVI 4.8 software from the region of interest (ROI). The models were built for chemical value and spectral data by UnsecramblerX 10.4 software. Outliers were to be eliminated by Monte Carlo cross validation method; Samples division was set partitioning based on joint X-Y distance(SPXY) method to improve the prediction performance of the model; The spectral's pretreatment was analyzed, such as Moving Average, Median Filter, Normalize, Baseline, multiple scatter correction (MSC), Detrending and standard normal variate (SNV) and so on; To reduce the amount and dimension of data, the feature wavelengths were extracted by competitive adaptive weighting algorithm (CARS), uninformative variable elimination ( UVE) and continuous feeding Shadow algorithm (SPA) ; Compared to the models of full spectrum (FS) and the feature wavelengths extracted by CARS and UVE of PLSR and SVM built, the optimal model was determined. A total of 7 abnormal samples were eliminated using Monte Carlo cross validation method. After eliminating abnormal sample data, the samples were divided into calibration set and prediction set by SPXY method, and calibration samples is 117, and prediction samples is 40. The spectral pretreatment were studied by the 7 methods. The results showed that the model effect without spectral pretreatment was the best, and its Rc was 0.8779, and RMSECV was 0.0481; Without a preprocessing method by CARS, UVE and SPA method to reduce the dimensions, a total of 16 feature wavelengths were selected by CARS, which were 415, 487, 406, 631 636, 655, 660, 665, 670, 684, 689, 694, 723, 732, 747 and 881 nm. A total of 32 feature wavelengths were selected by UVE, which were 415, 406, 627, 631, 636, 651, 655, 660, 665, 670, 675. 679, 684, 689, 694, 699, 703, 708, 742, 747, 751, 756, 761, 766, 771, 775, 780, 785, 790, 795, 919 and 924 nm. A total of 3 feature wavelengths were selected by SPA, which were 401, 665 and 684 nm. Comparing models of the full band spectrum with the models of extracted characteristic wavelengths of PLSR and SVM, the UVE-SVM model is the best, and its R2c is 0.847 1 and R2p is 0.714 9, which indicates that UVE effectively reduces the dimension of the spectrum and simplifies the data processing. This study explores the application of hyperspectral imaging technology in the field of fruit, explores a new method for nondestructive testing of Lingwu Long Jujube VC content, provides a theoretical basis for visible and near infrared hyperspectral model established for the rapid detection of other components of fruit.