Abstract: The pH and firmness index (FI) of red globe grapes determine the taste and post-harvest quality of the fruit. In this paper, a method for the detection of pH and firmness of red globe grapes based on transmission spectroscopy technology was proposed. Spectral datas were first collected from 360 full-growth-cycle red globe grape samples, which were pre-processed and modeled by different spectral pre-processing methods as a way to determine the best spectral pre-processing method. Then competitive adaptive reweighted sampling (CARS), successive projection algorithm (SPA), uniformative variable elimination (UVE) and CARS-SPA, UVE-SPA composite data dimensionality reduction methods were used respectively for extracting feature variables from spectra. Finally, partial least squares regression (PLSR) detection models for pH and firmness of red globe grapes were established, respectively. The optimal prediction models for pH and firmness of red globe grape samples were moving-average method (MA)-CARS-SPA-PLSR and MA-UVE-SPA-PLSR. The correlation coefficient of prediction (R_P) of the prediction sets of the two models were 0.9882 and 0.9588, and the residual predictive deviation (RPD) were 6.5857 and 3.5167, respectively. The results showed that transmission spectroscopy could be applied to the detection of pH and firmness of red globe grapes, which provided a new idea and a new method for the detection of pH and firmness of red globe grapes in the whole growth cycle.