The fruit structure effect (passion fruit, tomato and apricot) was investigated on prediction performance of soluble solids content (SSC) using NIR spectroscopy. Relationships between spectral wavelengths and SSC data were evaluated through the application of chemometric techniques based on partial least squares (PLS). Good prediction performance was obtained for apricot with correlation coefficients of 0.93 and root mean square errors of prediction (RMSEP %) of 3.3%. For the passion fruit and tomato, the prediction models were not satisfactorily accurate due to the high RMSEP. Results showed that NIR technology can be used to evaluate apricot internal quality, however, it was not appropriate to evaluate internal quality in fruits with thick skin, (passion fruit), and/or heterogeneous internal structure (tomato).