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The promise of association genetics to identify genes or genomic regions controlling complex traits has generated a flurry of interest. Such phenotype-genotype associations could be useful to accelerate tree breeding cycles, increase precision and selection intensity for late expressing, low heritability traits. However, the prospects of association genetics in highly heterozygous undomesticated forest trees can be severely impacted by the presence of cryptic population and pedigree structure. To investigate how to better account for this, we compared the GLM and five combinations of the Unified Mixed Model ( UMM ) on data of a low-density genome-wide association study for growth and wood property traits carried out in a Eucalyptus globulus population (n = 303) with 7,680 Diversity Array Technology (DArT) markers. Model comparisons were based on the degree of deviation from the uniform distribution and estimates of the mean square differences between the observed and expected p-values of all significant marker-trait associations detected. Our analysis revealed the presence of population and family structure. There was not a single best model for all traits. Striking differences in detection power and accuracy were observed among the different models especially when population structure was not accounted for. The UMM method was the best and produced superior results when compared to GLM for all traits. Following stringent correction for false discoveries, 18 marker-trait associations were detected, 16 for tree diameter growth and two for lignin monomer composition (S:G ratio), a key wood property trait. The two DArT markers associated with S:G ratio on chromosome 10, physically map within 1 Mbp of the ferulate 5-hydroxylase (F5H) gene, providing a putative independent validation of this marker-trait association. This study details the merit of collectively integrate population structure and relatedness in association analyses in undomesticated, highly heterozygous forest trees, and provides additional insights into the nature of complex quantitative traits in Eucalyptus.

IntroductionAnkle malleolar fractures are one of the most common surgical fractures. The literature about ankle fracture sport related is reduced. Severe fractures, fractures–dislocations, syndesmosis lesions, associated osteochondral lesions, postoperative complications, as well as age are associated in several studies with worse functional results and may, therefore, also be associated with a lower rate of sports return. This study aims to retrospectively assess the return to physical activity at the level prior to injury in individuals undergoing surgical treatment of unstable malleolar ankle injuries and to identify risk factors associated with a non-return.Materials and methodsWe retrospectively evaluated between January 2008 and December 2017, patients with an unstable malleolar fracture of the ankle surgically treated, recreational or competitive sportsman with a minimum follow-up of one year. Demographic data, fracture classification according to AO classification, presence/absence of osteochondral lesion, presence/absence of unstable syndesmosis lesion, associated dislocation, type of surgery, postoperative complications, functional outcome evaluation with the AOFAS score and sports return.Results92 patients met the inclusion criteria. The mean AOFAS score observed was 90.93 (67–100). 69.7% of patients returned without limitations in performing physical activity. 21.75% returned with limitations and 8.7% did not return to physical activity. No association was observed between age, sex, syndesmosis lesion and greater risk of not returning to physical activity. Patients with bimalleolar or trimalleolar fractures, osteochondral injury, or associated dislocation presented an increased risk of inferior functional score and non-return sporting activity.ConclusionsBimalleolar and trimalleolar fractures, associated presence of dislocation and osteochondral lesions are associated with worse clinical outcome and lower return onset.

Genetic variation and co-variation among the key pulpwood selection traits for Eucalyptus globulus were estimated for a range of sites in Portugal, with the aim of improving genetic parameters used to predict breeding values and correlated response to selection. The trials comprised clonally replicated full-sib families (eight trials) and unrelated clones (17 trials), and exhibited varying levels of pedigree connectivity. The traits studied were stem diameter at breast height, Pilodyn penetration (an indirect measure of wood basic density) and near infrared reflectance predicted pulp yield. Univariate and multivariate linear mixed models were fitted within and across sites, and estimates of additive genetic, total genetic, environmental and phenotypic variances and covariances were obtained. All traits studied exhibited significant levels of additive genetic variation. The average estimated within-site narrowsense heritability was 0.19±0.03 for diameter and 0.29± 0.03 for Pilodyn penetration, and the pooled estimate for predicted pulp yield was 0.42±0.14. When they could be tested, dominance and epistatic effects were generally not statistically significant, although broad-sense heritability estimates were slightly higher than narrow-sense heritability estimates. Averaged across trials, positive additive (0.64±0.08), total genetic (0.58±0.04), environmental (0.38±0.03) and phenotypic (0.43±0.02) correlation estimates were consistently obtained between diameter and Pilodyn penetration. This data argues for at least some form of pleiotropic relationship between these two traits and that selection for fast growth will adversely affect wood density in this population. Estimates of the across-site genetic correlations for diameter and Pilodyn penetration were high, indicating that the genotype by environment interaction is low across the range of sites tested. This result supports the use of single aggregated selection criteria for growth and wood density across planting environments in Portugal, as opposed to having to select for performance in different environments

Traditional quantitative genetic models in forestry often overlook the influence of an individual’s genes on neighboring trees. However, genetic competition models help bridge this gap. Competition varies among populations, over time, and across environments, yet forest breeders rarely monitor these dynamics or their effects on selected genotypes. We investigated the effects of competition on genetic variances, breeding value accuracy, and selection response in 14 Pinus taeda L. progeny tests using spatial (Spa) and spatial-competition (Spa-Comp) individual-tree mixed models. Our analysis covered traits such as diameter at breast height (DBH), total height (TH), and stem straightness (STR) across ages (3–21 years) and sites (altitude, soil texture, drainage). DBH was more affected by genetic competition than TH and STR, with effects varying across ages and sites. Direct-competition genetic correlations were negative for DBH from age 5 onward but positive for TH, reducing total heritable variance for DBH (<43.1%) while increasing for TH (<95.7%). Genetic competition accounted for less than 26% of direct additive variance. For DBH, the Spa-Comp model slightly improved breeding value accuracy (<~4%), while Spa inflated selection response (<3.83 percentage points), yet rank changes were minimal (common selected trees > 89%). These findings indicate that while competition inflates genetic gains, its impact on selection efficiency is minimal.

Intra-specific hybrids within Eucalyptus nitens and E. globulus were compared directly with inter-specific E. nitens x globulus using common parents. Diameter (age 2, 4, 6, 10 years) and Pilodyn (age 6 years) were used as indirect measures of growth and wood density, respectively. Genetic parameters were estimated for all cross types and traits. A direct comparison of the general combining ability with the general hybridising ability was made. Heterosis was estimated for intra- and inter-specific hybrids. The intra-specific hybrids in both species exhibit intermediate heritabilities and levels of additive genetic variance. The inter-specific F1 E. nitens x globulus exhibited high incidence of abnormalities at young ages and high levels of later age mortality. The mean performance of surviving inter-specific F1 hybrids was generally intermediate for all traits, to varying degrees, between the parental intra-specific crosses, and there is little evidence for significant heterosis. Different provenances of E. globulus may exhibit different responses to hybridisation. In this case, the inter-specific F1 hybrids, using Taranna E. globulus, appear to perform worse on average than those using King Island provenance for growth traits. There is evidence that specific hybrid families are produced that outperform most of the pure species families for one or other of the traits examined; however, there is no reliable quantitative genetic method of predicting which parents should be used.

Eucalyptus Longhorned Borers (ELB) are some of the most destructive pests in regions with Mediterranean climate. Low rainfall and extended dry summers cause stress in eucalyptus trees and facilitate ELB infestation. Due to the difficulty of monitoring the stands by traditional methods, remote sensing arises as an invaluable tool. The main goal of this study was to demonstrate the accuracy of unmanned aerial vehicle (UAV) multispectral imagery for detection and quantification of ELB damages in eucalyptus stands. To detect spatial damage, Otsu thresholding analysis was conducted with five imagery-derived vegetation indices (VIs) and classification accuracy was assessed. Treetops were calculated using the local maxima filter of a sliding window algorithm. Subsequently, large-scale mean-shift segmentation was performed to extract the crowns, and these were classified with random forest (RF). Forest density maps were produced with data obtained from RF classification. The normalized difference vegetation index (NDVI) presented the highest overall accuracy at 98.2% and 0.96 Kappa value. Random forest classification resulted in 98.5% accuracy and 0.94 Kappa value. The Otsu thresholding and random forest classification can be used by forest managers to assess the infestation. The aggregation of data offered by forest density maps can be a simple tool for supporting pest management.

The paper investigates the importance of additive and non-additive genetic variances for growth in Eucalyptus globulus (Tasmanian Blue Gum), based on a large collection of diameter growth data covering 40 sites and more than 4,200 genotypes, most of them cloned, and spanning three generations of breeding. The variance estimates were based on a model accounting for additive, full-sib family and clone within full-sib family terms. The results indicated a small amount of additive genetic variance for diameter [Formula: see text] and although non-additive genetic variance was also small, it accounted for a significant proportion of the total genetic variance present, corresponding to 80% of the additive variance. The interpretation of these non-additive effects is difficult. The results suggest, however, a possible role of epistasis. The evidence for this came from a strong observed bias in additive variance when clone effects were removed from the model and a larger than expected variance due to full-sib families relative to the variance due to clones within family. The relatively large proportion of genetic variance for growth that seems to be due to non-additive genetic effects has obvious implications in the breeding and deployment options in eucalypts, and these are briefly discussed.

Non-spatial and spatial analyses were carried out to estimate genetic parameters for growth and stem straightness traits between ages 4 and 7 in two series of eight progeny trials of Pinus elliottii Engelm. var. elliottii (PEE) established in 2004 and 2008, comprising 429 open-pollinated families from Instituto Nacional de Tecnología Agropecuaria (INTA) tree breeding population in Argentina. A first-order autoregressive spatial mixed model was found to significantly improve the fit of the model, compared with the standard non-spatial mixed model approach, due to substantial spatial heterogeneity within sites. The average individual-tree narrow-sense heritability estimates based on this spatial analysis were 0.49 for diameter at breast height, 0.36 for total height, and 0.48 for volume, with stem straightness being low to moderate (average = 0.11). The additive genetic correlation estimates between growth traits were positive (0.51 ≤ \\[\\hat{r}_{a}\\] ≤ 0.99) and statistically significant from zero. In contrast, the genetic correlations between growth traits and stem straightness although in general also positive were not significantly different from zero (− 0.22 ≤ \\[\\hat{r}_{a}\\] ≤ 0.59). Age-to-age genetic correlations were consistently higher for growth traits (\\[\\hat{r}_{a}\\] ≥ 0.81) than for stem straightness (\\[\\hat{r}_{a}\\] ≥ 0.33). The average additive genetic correlation estimated between sites within test series was high for all traits evaluated (average > 0.72). In contrast, average additive genetic correlation estimated between sites across series was slightly lower (average < 0.63). Implications of all these parameter estimates for genetic improvement of PEE in Argentina are discussed.

The first estimates of the importance of epistatic effects within Eucalyptus globulus were obtained from analysis of clonally replicated full-sib progeny tests grown in Portugal. Parents comprised diverse selections from the Portuguese landrace. Variance components were estimated for 4-year-old diameter growth and pilodyn penetration, an indirect measure of wood density, both key traits in the pulpwood breeding objective. The experimental components of variance were used to estimate heritabilities and proportions of the phenotypic variance due to dominance and epistasis. The additive variance was the only significant genetic component affecting either diameter or pilodyn. Estimates of the additive, dominance and epistatic effects accounted for 8-10%, 0-4% and 0.4% of the phenotypic variance in diameter, and for 11-17%, 0% and 5% of the phenotypic variance in pilodyn, respectively. A comparison of residual coefficients of variation within seedling and cloned progenies indicated that C effects within clones were not a serious source of random variability. Despite the test sites encompassing a diverse range of locations, no important genotype by environment interaction was detected. The results suggested that an improvement strategy combining both recurrent selection for additive genetic merit and clonal testing may be adequate for optimizing genetic gains from this genetic base.

Unmanned aerial vehicles (UAVs) are platforms that have been increasingly used over the last decade to collect data for forest insect pest and disease (FIPD) monitoring. These machines provide flexibility, cost efficiency, and a high temporal and spatial resolution of remotely sensed data. The purpose of this review is to summarize recent contributions and to identify knowledge gaps in UAV remote sensing for FIPD monitoring. A systematic review was performed using the preferred reporting items for systematic reviews and meta-analysis (PRISMA) protocol. We reviewed the full text of 49 studies published between 2015 and 2021. The parameters examined were the taxonomic characteristics, the type of UAV and sensor, data collection and pre-processing, processing and analytical methods, and software used. We found that the number of papers on this topic has increased in recent years, with most being studies located in China and Europe. The main FIPDs studied were pine wilt disease (PWD) and bark beetles (BB) using UAV multirotor architectures. Among the sensor types, multispectral and red–green–blue (RGB) bands were preferred for the monitoring tasks. Regarding the analytical methods, random forest (RF) and deep learning (DL) classifiers were the most frequently applied in UAV imagery processing. This paper discusses the advantages and limitations associated with the use of UAVs and the processing methods for FIPDs, and research gaps and challenges are presented.