Abstract: Forest measurements, including genetic trials, have relied on traditional measurement methods, an approach affected by different types of errors. To assess genetic trials, Terrestrial Laser Scanning (TLS) devices offer potential to improve accuracy. This study aimed to imple ment an approach for analyzing forest genetics trial measure ments using TLS data. A 15-year-old Pinus taeda L. progeny test in North Carolina USA was assessed using both TLS data and traditional field measurements. Accuracy was assessed using adjusted R², bias, percent bias, and RMSE. Genetic parameters were estimated via BLUP for diameter at breast height (DBH). The R²_adj values were 0.56 for DBH and 0.29 for total height (HT). Field-measured DBH had higher heritability (h² = 0.32) than raw TLS data (h² = 0.17). However, “cleaned” TLS estimates (DBH_R) improved herit ability (h² = 0.27) and showed stronger phenotypic correla tion with DBH_F (R = 0.84) than DBH_L (R = 0.75). GCA predictions using BLUP showed high correlation (R = 0.92) between field and TLS DBH estimates. Estimated gains using DBH_F were 11.3% and 12.1% for selecting the top 1st progeny (30 families) and the top 1st and 2nd progenies (15 families), respectively. Estimated gains using DBH_F were 11.3% and 12.1% for selecting the top 1st progeny (30 fami lies) and the top 1st and 2nd progenies (15 families), respec tively. Corresponding gains from DBH_L were 6.9% and 9.6%, and from DBH_R, 8.5% and 10.3%. The results demon strate that TLS, combined with the proposed methodology, is a reliable alternative for genetic analysis in forest trials.

Key words: Terrestrial laser scanning, Tree breeding, Genetic trials, Precision forestry, LiDAR