Statistical approaches to the discrimination of mantle- and crust-derived low-Cr garnets using major and trace element data

Diamond exploration focuses on geochemical analysis of indicator minerals that are more abundant than diamond itself. Among such indicators, low-Cr (Cr₂O₃?<?1 wt%) garnets from mantle eclogites are problematic since they overlap compositionally with many lower-crust-derived garnets also transported by kimberlite. Misclassification of these garnets may create “false positive” mantle signatures and possible misdirection of exploration efforts. Statistical solutions using major elements in low-Cr garnet (Hardman et al. in J Geochem Explor 186:24–35, 2018) provide improved error rates for the discrimination of low-Cr crustal and mantle garnets recovered from kimberlite. In this study we analysed a large suite of garnets (n?=?571) from both crustal and mantle settings, already characterised for major elements, for a wide range of trace elements by laser ablation inductively-coupled plasma mass spectrometry and use these new data along with literature data (n?=?169) to evaluate the effectiveness of adding trace elements to garnet-based diamond exploration programs. A new garnet classification scheme, initially using a major-element based filter, uses garnet Sr contents and Eu anomalies to help identify low-Cr garnets that are misclassified using major element methods. Combined with existing methods, our new trace element classifiers offer improvement in classification error rates for low-Cr, crustal and mantle garnets to as low as 4.7% for calibration data.