Spectral characterisation of 14 V-type candidate asteroids from the MOVIS catalogue

Most of the currently known basaltic (V-type) asteroids are believed to be past or present members of the Vesta dynamical family. The rising discoveries of V-type asteroids that are not linked to the Vesta family dynamically suggest that a number of major basaltic bodies may have been present during the early stages of the solar system. Using the near-infrared (NIR) colour data in the Moving Objects from VISTA Survey (MOVIS) catalogue, a list of 477 V-type candidates was compiled, with more than half of them outside the Vesta family. In this work, we aim to provide a spectral analysis of 14 V-type candidates of various dynamical types. The computed visible and NIR spectral parameters are used to investigate evidence of space-weathering or mineralogical differences from the expected basaltic composition. Based on the analysis of their visible spectra, we confirm 11 new V-type asteroids: six low-i asteroids - (3188) Jekabsons, (3331) Kvistaberg, (4693) Drummond, (7223) Dolgorukij, (9007) James Bond, and (29733) 1999 BA4; along with four inner-other asteroids - (5524) Lecacheux, (19983) 1990 DW, (51742) 2001 KE55, and (90023) 2003 BD13; as well as one fugitive - (2275) Cuitlahuac. Additionally, we analysed three peculiar outer main belt V-type candidates based on their visible + NIR spectra. We confirm the diogenite-like composition of (2452) Lyot. The spectrum of asteroid (7302) is not consistent with a basaltic composition and likely reflects an S-type body. The spectrum of (14390) 1990 QP10 is similar to a V-type but it shows unique spectral features that suggest a peculiar composition. Overall, our results demonstrate the efficiency of the MOVIS catalogue in identifying V-type objects, with a success rate of over 85%. The identification of V-types in the inner main-belt is more likely due to the presence of the Vesta family and other nearby asteroids that had escaped from the family. In the middle and outer main belt, where the amount of data is more limited, the proportion of false positives increases.