Estimation Of Genetic Parameters And Selection Of Superior Genotypes In A 12-Year-Old Clonal Norway Spruce Field Trial After Phenotypic Assessment Using A Uav

Height is a key trait in the indices applied when selecting genotypes for use in both tree breeding populations and production populations in seed orchards. Thus, measurement of tree height is an important activity in the Swedish Norway spruce breeding program. However, traditional measurement techniques are time-consuming, expensive, and often involve work in bad weather, so automatization of the data acquisition would be beneficial. Possibilities for such automatization have been opened by advances in unmanned aerial vehicle (UAV) technology. Therefore, to test its applicability in breeding programs, images acquired by a consumer-level UAV (DJI Phantom 4 Pro V2.0) system were used to predict the height and breast height diameter of Norway spruce trees in a 12-year-old genetic field trial established with 2.0 x 2.0 m initial spacing. The tree heights were also measured in the field using an ultrasonic system. Three additive regression models with different numbers of predictor variables were used to estimate heights of individual trees. On stand level, the average height estimate derived from UAV data was 2% higher than the field-measured average. The estimation of family means was very accurate, but the genotype-level accuracy, which is crucial for selection in the Norway spruce breeding program, was not high enough. There was just ca. 60% matching of genotypes in groups selected using actual and estimated heights. In addition, heritability values calculated from the predicted values were underestimated and overestimated for height and diameter, respectively, with deviations from measurement-based estimates ranging between -19% and +12%. However, the use of more sophisticated UAV and camera equipment could significantly improve the results and enable automatic individual tree detection.