Prediction of Freeze Damage and Minimum Winter Temperature of the Seed Source of Loblolly Pine Seedlings Using Hyperspectral Imaging

Abstract The most important climatic variable influencing growth and survival of loblolly pine is the yearly average minimum winter temperature (MWT) at seed source origin, it used to guide transfer improved lots throughout species’ distribution. This study presents a novel approach for assessment freeze-induced damage prediction MWT origin seedlings using hyperspectral imaging. A population comprising 98 representing wide range was subjected an artificial freeze event. visual were evaluated family level modeled with image data combined chemometric techniques. Hyperspectral scanning conducted prior event on four occasions periodically after freeze. significant relationship (R2 = 0.33; p < .001) between observed. Prediction accuracies based varied among seedling portions (full-length, top, middle, bottom portion aboveground material) dates. Models top predictive both MWT. highest accuracy [RPD (ratio deviation) 2.12, R2 0.78] achieved obtained Adoption this method would greatly facilitate characterization deployment well-adapted families across landscape.