Enhancing genomic association studies in slash pine through close-range UAV-based morphological phenotyping.

In forestry genetics and industry, tree morphological traits such as height, crown size, and shape are critical for understanding growth dynamics and productivity. Traditional methods for measuring these traits are limited in efficiency, scalability, and accuracy, posing challenges for large-scale forest assessments. This study focuses on integrating unmanned aerial vehicle (UAV) technology with GWAS to improve genomic association studies in slash pine ().

Genetic selection for growth, wood quality and resin traits of potential Slash pine for multiple industrial uses.

This study aims to understand the genetic basis of key industrial traits in Slash pine ( Engelm. var. ) to enhance improvement efficiency.

CountShoots: Automatic Detection and Counting of Slash Pine New Shoots Using UAV Imagery.

The density of new shoots on pine trees is an important indicator of their growth and photosynthetic capacity. However, traditional methods to monitor new shoot density rely on manual and destructive measurements, which are labor-intensive and have led to fewer studies on new shoot density. Therefore, in this study, we present user-friendly software called CountShoots, which extracts new shoot density in an easy and convenient way using unmanned aerial vehicles based on the YOLOX and Slash Pine Shoot Counting Network (SPSC-net) models.

Phenomic selection in slash pine multi-temporally using UAV-multispectral imagery.

Genomic selection (GS) is an option for plant domestication that offers high efficiency in improving genetics. However, GS is often not feasible for long-lived tree species with large and complex genomes. In this paper, we investigated UAV multispectral imagery in time series to evaluate genetic variation in tree growth and developed a new predictive approach that is independent of sequencing or pedigrees based on multispectral imagery plus vegetation indices (VIs) for slash pine.

Prediction of Needle Physiological Traits Using UAV Imagery for Breeding Selection of Slash Pine.

Leaf nitrogen (N) content and nonstructural carbohydrate (NSC) content are 2 important physiological indicators that reflect the growth state of trees. Rapid and accurate measurement of these 2 traits multitemporally enables dynamic monitoring of tree growth and efficient tree breeding selection. Traditional methods to monitor N and NSC are time-consuming, are mostly used on a small scale, and are nonrepeatable.

Genetic analysis and elite tree selection of the main resin components of .

Pine resin, as a natural material, has been widely used in food, pharmaceutical, and chemical industries. Slash pine ( Engelm var. ) is the primary tree species for resin tapping due to its high resin yield, low resin crystallization rate, and high turpentine content.

Prediction and Comparisons of Turpentine Content in Slash Pine at Different Slope Positions Using Near-Infrared Spectroscopy.

Pine resin is one of the best known and most exploited non-wood products. Resin is a complex mixture of terpenes produced by specialized cells that are dedicated to tree defense. Chemical defenses are plastic properties, and concentrations of chemical defenses can be adjusted based on environmental factors, such as resource availability.

Spectrometric Prediction of Nitrogen Content in Different Tissues of Slash Pine Trees.

The internal cycling of nitrogen (N) storage and consumption in trees is an important physiological mechanism associated with tree growth. Here, we examined the capability of near-infrared spectroscopy (NIR) to quantify the concentration across tissue types (needle, trunk, branch, and root) without time and cost-consuming. The NIR spectral data of different tissues from slash pine trees were collected, and the concentration in each tissue was determined using standard analytical method in laboratory.

Prediction and Utilization of Malondialdehyde in Exotic Pine Under Drought Stress Using Near-Infrared Spectroscopy.

Drought is a major abiotic stress that adversely affects the growth and productivity of plants. Malondialdehyde (MDA), a substance produced by membrane lipids in response to reactive oxygen species (ROS), can be used as a drought indicator to evaluate the degree of plasma membrane damage and the ability of plants to drought stress tolerance. Still measuring MDA is usually a labor- and time-consuming task.