This paper reports on the development and evaluation of methods and algorithms for detecting both external and internal quality of pickling cucumbers using the hyperspectral reflectance and transmittance images acquired by an online prototype described in a previous paper . Experiments were performed in 2 years on ‘Journey’ pickling cucumbers, some of which were subjected to mechanical stress to induce internal defect in seed cavity. Hyperspectral images of the ‘Journey’ pickling cucumbers were collected under reflectance, transmittance, and their combination modes. Partial least squares analysis was performed on spectra extracted from the hyperspectral images to predict firmness, color, and the presence of internal defect. The system performed well on predicting skin color (chroma and hue) with the coefficient of determination (R2) ranging between 0.75 and 0.77; however, it had poor prediction of fruit firmness. Transmittance data in the spectral region of 675–1,000 nm provided the best detection of internal defect for the test pickling cucumbers, with the detection accuracy up to 99%. Up to the best four wavelength combinations were identified using linear discriminant analysis for internal defect detection. The hyperspectral imaging technique can be used for simultaneous detection of color, size, and internal defect on pickling cucumbers.