Watermelon and muskmelon are sweet, juicy and rich in nutrients.There is great significance in manufacture and circulation for its internal quality detection. The traditional detection methods for internal quality of watermelon and muskmelon are inefficient, long time, high cost and destructive, which can not meet the needs of modern production. With the rapid development of spectral analysis techniques, near-infrared spectroscopy (NIRS) and hyperspectral imaging (HSI) for the internal quality non-destructive detectionof watermelon and muskmelon has become a research hotspot. In order to track national and international progress of research, this paper presents the technical characteristics and system composition of NIRS and HIS. The spectral information analysis methods are concluded, including spectral information preprocessing, variable selection, model establishment and evaluation. Afterwards, the recent progress of NIRS and HSI in the non-destructive detection for the internal quality (soluble solids content, firmness, total acid content, maturity and moisture, etc.) of watermelon and muskmelon is summarized. Finally, the future trends of spectral analysis techniques in the internal qualitynon-destructive detection of watermelon and muskmelon are discussed from the technical difficulties and practical applications.This review indicates thatthe following aspects are identified as the direction of future research, using deep learning methods to analyze spectral information, establishing comprehensive evaluation model of multi-feature information fusion, and developing the rapid non-destructive detection system based on the deep integration of artificial intelligence and mobile terminal.