Supplementary Table 1. Environmental and phenotype data (full population) for the three Eucalyptus grandis sites surveyed for Leptocybe invasa infestation. [Excel file]
Supplementary Table 2. Predictor variable datasets and outlier detection prior to partial least squares modeling. (A) Predictor variable datasets used for outlier detection and partial least squares modeling. (B) The proportion of samples classified as outliers (and thus trimmed) for each set of models, prior to partial least squares modeling. [Excel file]
Supplementary Table 3. The 48 measured terpenes. (A) The name, major ions and retention time of the 48 measured terpenes. (B) The motivation for combining groups of terpenes. (C) The correlation of terpenes with the Leptocybe invasa screenings (LS1, LS2) and individual breeding values (IBV) for the Siya Qubeka (SQF) site. [Excel fie]
Supplementary Table 4. Leptocybe invasa heritability estimates for L. invasa screening 1 (LS1) and L. invasa screening 2 (LS2) for the Eucalyptus grandis population across sites. [Excel file]
Supplementary Table 5. Summary of the best partial least squares models, based on near-infrared reflectance (NIR) data, for Leptocybe invasa screenings (LS1, LS2) and individual breeding values (IBV) at the Mtunzini (MTZ) and Nyalazi (NYL) sites. [Excel file]
Supplementary Table 6. Bayesian model selection results to identify the most important terpenes for predicting Leptocybe invasa infestation. (A) Bayesian model selection results at the Siya Qubeka (SQF) site. (B) Bayesian model selection results at the Mtunzini (MTZ) site. (C) Bayesian model selection results at the Nyalazi (NYL) site. (D) Bayesian model selection results across all three sites. [Excel file]