In Uruguay, Pinus taeda is the dominant conifer in industrial plantations, generating large volumes of knot-containing offcuts during processing. These residues are highly enriched in extractives, offering opportunities for valorization within a circular bioeconomy. This study examined the recovery of bioactive compounds from P. taeda knotwood through ethanol extraction, process optimization, Gas Chromatography coupled with Mass Spectrometry and Flame Ionization Detection (GC-MS/FID) analysis, and antifungal evaluation. The effects of extraction temperature, ethanol concentration, and liquid-solid (L/S) ratio on extraction yield, total phenolic content, and FRAP antioxidant activity were assessed, and response models were developed to identify optimal conditions. Maximum extraction yield (20.8%) occurred at 47°C, 100% ethanol concentration, and L/S of 8.3. The highest phenolic content (5.7g gallic acid equivalents/100g) was predicted at 61°C, 100% ethanol, and L/S 15, while the greatest antioxidant capacity (15.8 mmol ascorbic acid equivalents/100g) was achieved at 75°C and L/S 15, independently of ethanol concentration. Two extraction conditions, representing the best compromise among yield, phenolics, and antioxidant performance, were selected for further characterization and antifungal tests. GC-MS/FID analysis showed that stilbenes and terpenoids dominated the extracts. Antifungal assays against Trametes versicolor and Gloeophyllum trabeum revealed strong inhibition, reaching up to 65% and 97% after seven days. Overall, the results demonstrate that P. taeda knotwood residues can be efficiently valorised via ethanolic extraction to obtain bioactive fractions with high antioxidant and antifungal activity, supporting sustainable and circular approaches for wood protection.

Pine wilt disease, caused by Bursaphelenchus xylophilus, poses a serious threat to global pine forest ecosystems and forestry production. Thaumatin-like proteins (TLPs), which belong to the PR-5 family, are known to participate in plant defense, but their roles in pine have not been well characterized. In this study, a comprehensive genome-wide analysis of the TLP gene family was conducted in Pinus taeda. A total of 116 TLP genes were identified and classified into four major clades based on phylogenetic analysis. Gene structure and conserved motif analyses revealed that members within the same clade generally exhibited similar exon-intron organization patterns and conserved motif compositions. Promoter analysis identified numerous cis-regulatory elements associated with stress responses and phytohormone signaling. Transcriptome data from different stages of pine wood nematode infection identified eight TLP genes that exhibited continuous differential expression, and their expression patterns were further confirmed by qRT-PCR. A multilayer regulatory network highlighted MYB and other transcription factors as key upstream regulators, and yeast one-hybrid assays confirmed MYB-mediated regulation. Together, these findings improve our understanding of the TLP gene family in P. taeda and offer valuable candidate genes and regulatory information for future studies on pine resistance to pine wilt disease.

A resource-driven stand-level survival model for loblolly pine plantations in the southern United States

The oleoresin defense system of loblolly pine (Pinus taeda) protects trees from insects and pathogens and is an important source of renewable biofuels and chemicals, but the genetic basis of oleoresin production is poorly understood. We characterized the genetic architecture of oleoresin flow, resin canal number, stem wood terpene content, and monoterpene composition in two clonal populations of P. taeda. We used quantitative genetic analyses, genome-wide association studies (GWASs), multiplex network learning, and gene expression profiling to elucidate shared gene networks underlying defense traits and to identify high-quality candidates for breeding and engineering loblolly pine. Genetic analyses revealed polygenic inheritance and trait-to-trait correlations provide strong evidence for shared genes regulating constitutive and induced oleoresin flow. We identified 236 single nucleotide polymorphisms associated with oleoresin flow, resin canal number, and terpene composition and highlight candidate genes likely involved in terpene biosynthesis, cambial meristem reprogramming, and pathogen perception and immune signaling. Fourteen GWAS candidates were methyl jasmonate-responsive in tissues where resin canals initiate and terpene production occurs. Integrating quantitative genetics, GWAS, gene expression, and multiplex network analyses enabled the prioritization of high-quality candidate genes. This work advances the development of more resilient loblolly pine optimized for ecological performance, renewable chemical, and biofuel production.

The biosynthesis and accumulation of plant secondary metabolites are tightly regulated by environmental fluctuations, serving as a crucial interface mediating plant–environment interactions. Nevertheless, the phenotypic instability of secondary metabolism-related traits induced by environmental variability has hampered the precise breeding of stress-resistant cultivars. Pinus taeda is an key timber tree species in southern China, and its foliar catechins exhibit substantial stress-resistant potential. However, phenotypic variation driven by seasonal changes has limited the germplasm innovation and genetic selection of this species. In this study, 54 half-sib families of P. taeda were used as experimental materials. Combined with near-infrared spectroscopy (NIRS) and the BLUP model, we systematically analyzed the seasonal variation characteristics, genetic parameters of catechin content (CC), and genetic gains under different breeding strategies across four seasons. Our results demonstrated that family and season had extremely significant effects on CC (p < 0.001), whereas the season × family interaction effect was not significant, indicating that the genetic expression of CC is stable across seasons. CC was higher in spring and winter but lower in summer and autumn; specifically, the mean CC in summer was 47% lower than the peak value in spring (26.95 ± 0.46 μg·g−1), reflecting a resource trade-off between growth and defense metabolism. Genetic parameter analysis revealed that family-mean heritability (0.373–0.714) was higher than individual heritability and within-family heritability, with August identified as the optimal selection season. The maximum genetic gain across the three breeding strategies (individual selection, family selection, and combined selection) reached 7.86%, among which individual selection exhibited the smallest fluctuation in genetic gain. Finally, three superior families and 14 superior individuals were screened out. This study elucidates the seasonal genetic pattern of foliar CC in P. taeda, clarifies the optimal selection stage and efficient breeding strategies, and provides theoretical guidance and material support for the genetic improvement, germplasm innovation, and resource utilization of secondary metabolic traits in this ecologically and economically important tree species.

This study evaluated the effectiveness of genomic selection (GS) in loblolly pine (Pinus taeda) using a two-generation closed breeding population and a genetically diverse and a large Mainline population. Single-step genomic best linear unbiased prediction (ssGBLUP) models were used to include all phenotypic, genotypic, and pedigree information. Prediction accuracies of genomic estimated breeding values reached up to 0.70 for stem volume and stem straightness. Prediction accuracy showed a strong linear relationship with mean relatedness between training and validation populations (r > 0.92). Scaling the genomic and pedigree relationship matrices improved model stability, increased prediction accuracy, and reduced bias in genomic estimated breeding values. Estimates of heritability and variance components from ssGBLUP were consistent with pedigree-based models, particularly when genomic relationships were properly scaled. Genomic selection had approximately 50% more genetic gain per year relative to conventional selection. Overall, these results demonstrate that GS can be effectively integrated into operational Pinus taeda breeding programs, given sustained investment in large, well-connected training populations with high-quality phenotypic data. We also outline the planned implementation of GS in the North Carolina State University Cooperative Tree Improvement Program to increase genetic gain.

Accurate quantification of fine-root turnover, a pathway representing a large and uncertain flux of carbon into soils, is critical for improving terrestrial ecosystem models. Efforts to model this carbon flux directly have relied on tracing stable carbon isotopes through root systems, and these studies reveal complex dynamics in sampled fine roots, best described to date by two-rate models. The rates derived from these models have been traditionally interpreted either as two distinct turnover rates (fast and slow), or as movement through two distinct biochemical pools (labile, recently fixed carbon and recalcitrant carbon consisting of complex polymers like lignin). However, a competing, mechanistic explanation exists: the observed two-rate dynamics may reflect the demography of the root system, where roots of different functional classes (e.g., defined by root order) inherently possess differential lifespans and turnover rates. Here we introduce a new model, the demographic carbon distribution model (DCDM) that models both the carbon flux into root systems and the demography of fine roots. We then fit each of these models to $\delta ^{13}$C values obtained from loblolly (Pinus taeda L.) fine roots. The DCDM model predicts that root turnover is substantially faster than has been previously reported. Pairing this model with data on fine roots assayed by root order, we were able to obtain estimates of fine-root turnover for different functional groups of roots. Furthermore, sampling individual roots highlights the importance of variation in root turnover estimates, indicating that mean behavior alone is insufficient to capture complex root dynamics. Because terrestrial carbon models depend on estimates of root turnover, we demonstrate how the estimates obtained here could impact predictions from ecosystem models.

growth in the market is the reconstituted wood panels. According to a report by Fortune Business Insights (2024), the global market for medium-density fiberboard (MDF) was US$ 42.26 billion in 2023 and is projected to grow to US$ 44.84 billion in 2024 and to US$ 70.98 billion by 2032. The East Asian region, with China at the forefront, accounts for a substantial share of panel production, so much so that in 2034, according to the FactMR report (2024), this region is expected to hold 32.6% of the global market. The Brazilian MDF market generated revenue of US$ 1446.6 million in 2022 and is expected to reach US$ 2066.3 million by 2030. Thus, Brazil is expected to continue leading this market in Latin America, with growth of 4.6% between 2023 and 2030 (Horizon Grand View Research, 2024). The demand for sustainability in the construction and interior design industries is driving the market. As MDF panels can be produced from lower quality wood compared to that used in the lamination and sawmill sectors, this product continues to gain prominence in the developing economies of Asia and Latin America due to the availability of the main raw materials, wood, and adhesives (Fortune Business Insights 2022). According to data from the Food and Agriculture Organization of the United Nations -FAO (2019), Asia produces around 70 million m³ of MDF annually,

Loblolly pine (Pinus taeda) trees experiencing dieback have altered resin canals, earlywood, and latewood relative to asymptomatic trees

Effect of field storage on the quality of residual biomass from the harvesting of Pinus taeda L

Rapid chemical characterization of loblolly pine forest residues with near-infrared hyperspectral imaging

Surface fire is the primary ecological filter maintaining eastern North American woodlands. However, fire is not the only filter affecting species demographics, and in the absence of fire, the influence of secondary filters, such as seed predators, increases. To explore how different seed predator guilds affect individual species, we established seed offerings examining the effects of predator type (invertebrates only and invertebrates + small mammals), forest type (upland and floodplain), season (fall and summer), and offering location (beneath conspecific and heterospecific focal trees) on seed removal of four fire-sensitive tree species at two sites in the southeastern United States. Additionally, we explored the effects of forest structure on seed removal. Excluding small mammals had no impact on seed removal for any species, indicating that invertebrates were the primary seed predator. Winged elm (32%) and sweetgum (31%) seed removal in the floodplains significantly exceeded red maple (15%) and loblolly pine (6%). In the uplands, sweetgum (68%), winged elm (64%), and red maple (55%) seed removal significantly exceeded that of loblolly pine (4%). Sweetgum seeds were removed more frequently than loblolly pine regardless of focal tree identity. However, seed removal of both species beneath conspecific focal trees did not significantly exceed that recorded beneath heterospecific trees. Competing vegetation height was highest in the uplands in the summer and was positively associated with sweetgum seed removal intensity. Collectively, these results suggest that loblolly pine seeds have the highest probability of avoiding seed predator removal, potentially increasing its odds of establishing on upland sites

Pinus thunbergii is an important ornamental species in Taiwan; however, its needles frequently develop yellowish spots that have long been attributed to Lophodermium needle cast. From 2023 to 2025, surveys conducted across 13 sites and 52 sampling events consistently associated these lesions with a slow-growing Basidiomyceteous fungus, identified as Atractidochium hillariae based on morphology and multilocus phylogenetic analyses (ITS, SSU, LSU). Previously reported only as an endophyte of Pinus taeda in the United States, A. hillariae was the dominant fungus isolated from yellowish-spot needles of P. thunbergii, whereas Lophodermium spp. predominated in fallen, dead needles. Detached twig and field inoculations with A. hillariae reproduced restricted bright yellow lesions with reddish-brown centers identical to field symptoms, and the pathogen was successfully reisolated, fulfilling Koch's postulates. The new disease is designated as "Atractidochium needle spot disease". Monthly monitoring revealed that disease severity increased from November, peaked in April-May, and declined in June-July. A newly developed A. hillariae-specific PCR assay targeting the ITS region enabled sensitive (limit of detection, 25 fg μl-1) and specific detection from field samples. In vitro mycelial growth inhibition assays demonstrated that pyraclostrobin and tebuconazole exhibited the strongest inhibition (EC50 < 0.1 mg kg-1), suggesting their potential for chemical control. Future research on the disease cycle, host range, and fungicide efficacy in planta will facilitate the development of effective management strategies. It is also worth exploring whether A. hillariae functions as an opportunistic endophyte capable of shifting from a latent to a pathogenic phase under certain conditions.

Abstract We demonstrate that the inputs and conceptual foundation needed for individual-tree-level precision thinning optimization algorithms are already available. As more resource managers adopt LiDAR-based inventories, precision thinning can become a value-added outcome of collecting these data. We use LiDAR to assess individual-tree stem volumes in Pinus taeda L. plantations in the southeast US. Rather than arbitrarily selecting starting rows in row thinning operations, we use field- and LiDAR-derived stem volume data to inform row selection. Among all three study sites, row-to-row tree volume variability was present, indicating that selecting rows to be removed deliberately could improve thinning outcomes. A machine learning model based on LiDAR-derived metrics was also accurate in estimating individual stem volume in the primary study site and LiDAR was accurate in measuring pre- and post-thinning stem counts, the data that would be needed to audit thins.

Pine trees, globally distributed and economically vital evergreen conifers, are threatened by pine wilt disease (PWD) attributed to the pine wood nematode (PWN). Many studies have been conducted on phenome and transcriptome profiling in select Pinus species upon PWN infection, but a high-throughput phenotyping of PWD progression and transcriptomic analysis across diverse Pinus species remains lacking. Here, we developed a deep learning-based phenotyping program to quantify PWD symptoms and conducted a pan-transcriptome analysis using PWD-susceptible (Pinus densiflora, Pinus koraiensis, Pinus thunbergii) and -resistant (Pinus parviflora, Pinus strobus, Pinus rigida × Pinus taeda) Pinus species and a hybrid. Our results showed severe wilting of leaves within 14 weeks after PWN infection in susceptible species but not in resistant ones. Pan-transcriptomic analysis revealed the upregulation of genes involved in leaf abscission and abscisic acid responses in PWD-resistant taxa, while PWD-susceptible taxa downregulated genes associated with desiccation response after PWN infection. These findings suggest that activating genes involved in water conservation plays a role in mitigating PWD infection in Pinus trees. Notably, all five Pinus species and one hybrid exhibited upregulation of the elongation factor Tu receptor (EFR) gene and pathogenesis-related (PR)-3 gene upon PWN infection, suggesting a potential role of the EF-Tu receptor in detecting PWN invasion and activating the PR-3 gene. Our study introduces a novel deep learning-based phenotyping program for precise PWD symptom quantification and enhances understanding of the molecular mechanisms underlying PWD resistance. These insights contribute to high-throughput monitoring of PWD progression in Pinus forests for disease prevention and facilitate the development of PWD-resistant pine trees.

APAR is a better predictor than LUE of the stem growth differences found between Loblolly pine grown in the United State and Brazil

Long-term stand growth and survival of loblolly pine open-pollinated families and clonal varieties in the West Gulf Coastal Plain

This study investigates the pyrolysis behavior of loblolly pine through thermogravimetric (TGA) and derivative thermogravimetric (DTG) analysis under varying nitrogen flow rates of 5–40 mL min−1 and heating rates of 5–20 °C min−1. The pyrolysis proceeded through three distinct phases: Phase I: initial moisture release, Phase II: active devolatilization, and Phase III: char formation. Kinetic modeling using both integral and differential forms of the Coats–Redfern method revealed distinct mechanistic interpretations. The integral approach primarily identified diffusion-controlled models (D1, D3) during moisture and char stages and reaction-order or contraction models (F2, R2) during devolatilization, with activation energies ranging from 8.89 to 70.48 kJ mol−1. In contrast, the differential method captured sharper transitions and favored complex nucleation and growth mechanisms (A3, A4) and power laws (P3, P4), yielding higher activation energies up to 111.29 kJ mol−1 in Phase II. These results underscore the influence of both inert gas flow and thermal ramp on pyrolysis reactivity and demonstrate that kinetic model selection significantly affects activation energy interpretation. The findings contribute to a more nuanced understanding of biomass pyrolysis and offer insights into reactor design and process optimization in thermochemical conversion systems.

Outcomes of European colonization encompass surface fire exclusion followed by the forestation of open ecosystems and tree densification within forests, with concomitant replacement of fire-tolerant tree species, specifically oaks, by fire-sensitive tree species. In Kentucky, a 10.5 million ha area of the eastern United States, I compared tree composition between a historical assessment (1907–1909) and modern surveys (2010–2014), utilizing a divergence metric of squared-chord distance, which revealed a similar progression. Following the time since Euro-American settlement and associated fire exclusion, historically dominant fire-tolerant oaks decreased from 52% of all trees to 21% of all trees in Kentucky, while maples increased from 5 to 19% of all trees, reflecting shared changes across three regions. The Loess Hills region in western Kentucky and the Central Interior, a flat region of historical grasslands, displayed greater tree composition divergence than the Appalachian Mountain region in eastern Kentucky. The least decrease in oaks, at 19 percentage points, and the greatest decrease in fire-tolerant shortleaf pine ( Pinus echinata ), at 5.5 percentage points, occurred in the Daniel Boone National Forest, within the Appalachian region. American chestnut ( Castanea dentata ) decreased by nine percentage points in the Appalachian region, where red maple ( Acer rubrum ), previously of trace abundance, became the most abundant tree species at 14% of all trees, with yellow-poplar ( Liriodendron tulipifera ) at 12% of all trees. American beech ( Fagus grandifolia ) decreased by nine percentage points in the Interior region, where eastern redcedar ( Juniperus virginiana ), also previously of trace abundance, became the most abundant tree species at 12% of all trees. Sweetgum ( Liquidambar styraciflua ) decreased in the Loess region, where green ash ( Fraxinus pennsylvanica ) became the most abundant species, along with a new addition of planted loblolly pine ( Pinus taeda ). Kentucky contains a range of ecosystems, reflecting trends common to the eastern U.S. of decreased fire-tolerant species relative to fire-sensitive species following fire exclusion, as well as trends specific to regions, depending on species distributions.

Abstract Background Open pine woodlands occur throughout the southeastern United States. Thinning and prescribed fire commonly are used to establish and manage pine woodlands for multiple objectives, often including timber production and wildlife habitat. Although fire effects in loblolly and shortleaf pine woodlands have been summarized widely, the effects of fire during all seasons of the year are not well understood. We implemented 72 burns at 9 sites throughout the southeastern US, 2020–2023, to evaluate how fire treatment during the dormant, early growing-, mid-growing-, and late growing-season on a 2-year fire-return interval may affect understory composition, structure, and species diversity indices. Results Fire intensity and burn coverage were greatest in the dormant-season treatment and least in the mid-growing-season treatment. Coverage of semi-woody and woody plants in the understory was less in all treatments compared to control. However, after two fire events, coverage of semi-woody and woody understory plants increased in the dormant-season treatment and woody understory plants increased in the mid-growing-season treatment, whereas neither increased in the early- and late growing-season treatments. These results indicate growing-season fire sets-back semi-woody and woody vegetation better than dormant-season fire if intensity is adequate to top-kill the plants. Forb coverage increased following all seasons of burning, but the increase was greatest in the late growing-season treatment. Coverage of graminoids decreased in control and in the mid- and late growing-season treatments, partially because of fire timing and because understory sunlight was reduced from an average of 54% to 39% over 4 years as overstory tree crowns expanded following thinning. Percent visual obstruction was least following early growing-season fire. Understory species richness increased in all treatments as well as control. Conclusion We documented changes in plant composition and structure as related to fire seasonality and intensity after 2 fire events on a 2-year fire-return interval. All fire treatments changed understory composition, and each produced different effects that could allow managers to better meet objectives in systems dominated by Southern yellow pines. Growing-season fire offers more flexibility throughout the year to accomplish objectives, including wildlife habitat management, beyond the traditional dormant-season burn window.