Papaya (Carica papaya L.) accounts for almost 4% of all tropical fruit production in Cuba. This project aims to assess the potential of a portable fish NIR spectrometer, in combination with multivariable statistical analyzes or machine learning tools, for the non-destructive and accurate prediction of ripeness indexes and control of papaya quality in both harvest and after harvest stages.