The consumption on the freshcut fruit is growing significantly, in order to satisfy the requirement of the consumption with high quality and accuracy quantity, a freshness detection device for freshcut fruit was developed using visible/nearinfrared spectroscopy. The device was designed based on spectral analysis and sensor technology, which was integrated electronic components, including micro spectrometer, gravity sensor, illuminance meter and raspberry pie display. It was operated with hardware and software system, in which the hardware system included a data acquisition module, a light source module, a result output displays module, and a controller module. The software implements functions such as processing data, invoking a hierarchical model, and feedback grading results. Taking freshcut apples as an example, the spectral reflectance of 400~820nm bands was collected from 24 red Fuji apple samples, which were in the range of 0~2h, 2.5~8h and 8.5~30h, respectively. The samples were measured for four sets of spectral data, and a total of 288 raw sample data were obtained. The apples were divided into two grades in a cutoff time of 2h. After processing the reflected spectral data onto 15 points of S-G smooth convolution, the kernel function was used as the support vector machine of Gaussian kernel function (RBF) to establish the apple freshness visibility/near infrared spectrum detection hierarchical model. The accuracy of prediction set was 86.81%. The freshness detection device for freshcut fruit using visible/nearinfrared spectroscopy could provide a technical support for the freshness identification nondestructively and rapidly during the storage after cutting.