The objective of the present work was to identify russet on the peel of the pear cultivars ‘Abate Fetel’, ‘Conference’’, ‘Williams Christ’, ‘Sweet Sensation’, ‘Vereinsdechants Birne’ (Comice), and ‘Alexander Lucas’ using new non-invasive technology with real-time data processing including colourimetry, spectrometry, 3D profilometry and a luster sensor. Non-invasive true and false colour images at 40x magnification with a 3D-profilometer allowed identification of russet on ‘Conference’ pear with a larger roughness, expressed as Ra (arithmetic difference between peaks and troughs), of 3.3 μm compared with Ra 2.5 μm on fruit without russet. The non-invasive russet detection using the luster sensor CZ-H72 failed to detect differences (8 artificial units-a.u.) in glossiness between russet (54.5 a.u.) and non-russet (62.5 a.u.) ‘Conference’ (green) in contrast to ‘Sweet Sensation’ (red) with a 2.5-fold difference between russet (29.3 a.u) and non-russet (61.2 a.u.) surfaces. For the red pear cultivars’ Williams Christ’ and ‘Sweet Sensation’ (66.8°hue for russet and 62.4°hue russet-devoid peel), non-invasive detection of russet was hampered when using colourimetry. For green pear, however, a difference between russet (79.9°hue or 82.4°hue) and russet-devoid (94.8°hue or 99.7°hue for ‘Conference’ or ‘Alexander Lucas’) fruit could be detected. In contrast, russet was detected for all cultivars using portable non-invasive spectrometry (190–1100 nm). A new spectral russet index (SRI) was proposed relating the two peaks (550 nm–600 nm and 775 nm–785 nm of light reflection) to the trough (667 nm–685 nm). Russeted pear with SRI = 3.6 exhibited ca. 25% smaller SRI values than russet-devoid peel (SRI = 4.8) of both cultivars ‘Conference’ (green) and ‘Sweet Sensation’(red), irrespective of peel colour. Overall, both non-invasive techniques 3D-profilometer and spectral light reflection with the novel russet index, are suitable for russet detection in pears. In particular, the study has identified colourimetry as a suitable measure for russet detection for green and luster sensor for red pear cultivars. The study has also shown that russet can be identified non-invasively by a range of new affordable mostly portable technologies in real time, which offer new possibilities of russet detection in the field or on a grading line.