Importance of variables in RandomForest in R
If the features scale of measurement and/or number of categories vary, permutation accuracy is more reliable than the GINI index (Strob et al. 2007). 

However, better yet is to use Boruta all relevant variable selection prior to running random forests to determine which variables are relevant to the target property, and which are not. This allows you to trim your dataset to only useful, or relevant variables.

Strobl, Carolin, Anne-Laure Boulesteix, Achim Zeileis, and Torsten Hothorn. “Bias in Random Forest Variable Importance Measures: Illustrations, Sources and a Solution.” BMC Bioinformatics 8 (2007): 25. doi:10.1186/1471-2105-8-25.