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Phenotypic Correlations among Growth and Selected Wood Properties in White Spruce (Picea glauca (Moench) Voss) †

Phenotypic Correlations among Growth and Selected Wood Properties in White Spruce (Picea glauca (Moench) Voss) †

Abstract: We examined phenotypic relationships among radial growth-related, physical (i.e., related to wood density), and anatomical (i.e., related to tracheid dimensions) wood properties in white spruce (Picea glauca (Moench) Voss), in order to determine the strength and significance of their correlations. Additionally, principal component analysis (PCA) was used to establish if all of the properties must be measured and to determine the key properties that can be used as proxies for the other variables. Radial growth-related and physical properties were measured with an X-ray densitometer, while anatomical properties were measured with a Fiber Quality Analyzer. Fifteen wood properties (tracheid length (TL) and diameter (TD), earlywood tracheid length (ETL) and diameter (ETD), latewood tracheid length (LTL) and diameter (LTD), ring width (RW), ring area (RA), earlywood width (EWW), latewood width (LWW), latewood proportion (LWP), ring density (RD), intra-ring density variation, earlywood density (EWD), and latewood density (LWD)) were assessed. Relationships were evaluated at intra-ring and inter-ring levels in the juvenile wood (JW) and mature wood (MW) zones. Except for a few cases when mature tracheid diameter (TD) was involved, all intra-ring anatomical properties were highly and significantly correlated. Radial growth properties were correlated, with stronger relationships in MW compared to JW. Physical properties were often positively and significantly correlated in both JW and MW. A higher earlywood density coupled with a lower latewood density favored wood uniformity, i.e., the homogeneity of ring density within a growth ring. Managing plantations to suppress trees growth during JW formation, and enhancing radial growth when MW formation starts will favor overall wood quality. In order, RW-EWW-RA, TL-ETL-LTL, and RD-EWD-LWP are the three clusters that appeared in the three wood zones, the whole pith-to-bark radial section, the juvenile wood zone, and the mature wood zone.
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Modélisation de la croissance et de la qualité du bois de l'épinette blanche (Picea glauca) à l'échelle individuelle en fonction de la compétition inter- et intra-spécifique

Modélisation de la croissance et de la qualité du bois de l'épinette blanche (Picea glauca) à l'échelle individuelle en fonction de la compétition inter- et intra-spécifique

ABSTRACT In the Bas-Saint-Laurent region, 36 000 ha of plantations are ready for a first commercial thinning. Commercial thinning can be used to sustain past plantation investment and reduce the gaps between current and pre-industrial forests. To identify silvicultural treatments that respect the ecosystem-based forest management objectives, an individual stem growth model and an individual stem acoustic velocity model were calibrated using data from white spruce plantations (Picea glauca). A stratified random sampling plan by ecological type, tree height and plantation density allowed the establishment of 96 permanent sample plots in the region. The white spruce relative growth was modeled with linear and non-linear models where distance-independent and distance- dependent competition indices were used. The same competition indices were tested for acoustic velocity models. However, only the linear forms were used. The type of competition (conifers vs broadleaves) was incorporated into the models. For relative growth models, the non-linear form gave better results than the linear form. The model with the lowest AIC (Akaike's index criterion) was the one using the basal area of larger trees where the effect of competition from conifers and broadleaves was discriminated. In the case of the acoustic velocity models, the model with the lowest AIC used the diameter at breast height to mean stand diameter ratio squared. In this case, the discrimination of the competition from conifers and broadleaves did not improve the model results. For both relative growth and acoustic velocity models, distant independent competition indices provided the best results, and can be explained by the even-aged structure of the sampled plantations. These relative growth and acoustic velocity models will then be integrated into a tactical growth simulator that will help forest managers to make informed decisions. Subsequently, commercial thinning methods will be identified based on stands characteristics.
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The effect of light availability and basal area on cone production in Abies balsamea and Picea glauca

The effect of light availability and basal area on cone production in Abies balsamea and Picea glauca

The degree to which the remaining unexplained variation (typical of canopy trees, e.g., Sork et al. (1993), as well as subcanopy trees) is due to genetic differences within a stand is not understood. The variation cannot be primarily due to asynchrony in masting, as this is a weather-cued regional phenomenon (e.g., Alexander et al. 1982; Sork et al. 1993; Koenig and Knops 1998), although this will bear some share of it. Furthermore, intra- and inter-specific competition prob- ably had different effects from tree to tree. There is a nega- tive relationship between radial growth increment and cone production in some species (Eis et al. 1965; Mart’yanov and Batalov 1990; El-Kassaby and Barclay 1992), and this is also expected to vary between individuals. There is also a possibility that there were light differences our proxy mea- sures could not include or that a measure at the terminal leader does not describe satisfactorily the overall light condi- tions reaching the crown of an understory tree. Crown form (the ratio of crown height to crown width) was not taken into account here, nor were the roles of sunflecks (see the good review by Chazdon (1988)) and seasonal light variability (Gendron et al. 2001). Subcanopy conifers can benefit from the higher light availability prevailing in late spring and early fall (while aspens do not bear leaves) to fix substantial amounts of carbon (Constabel and Lieffers 1996). This prob- ably lowers the part of the variability in cone production ex- plained by the light-availability gradient. While the goal of the present study was to determine the effect of both mid- growing season light availability and basal area on cone pro- duction in Abies balsamea and Picea glauca, further studies are needed that would quantify other variables to include them in the regression and increase the explained variation. Cone production, from bud differentiation to ripening (Owens and Blake 1985), is a 2-year process in both species, and it appears that no long period of acclimation is required
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Phenotypic correlations among growth and selected wood properties in white spruce (Picea glauca (Moench) Voss) †

Phenotypic correlations among growth and selected wood properties in white spruce (Picea glauca (Moench) Voss) †

† This manuscript is part of a Ph.D. thesis by the first author, available online at depositum.uqat.ca . ‡ Researcher emeritus. Received: 1 June 2019; Accepted: 15 July 2019; Published: 16 July 2019    Abstract: We examined phenotypic relationships among radial growth-related, physical (i.e., related to wood density), and anatomical (i.e., related to tracheid dimensions) wood properties in white spruce (Picea glauca (Moench) Voss), in order to determine the strength and significance of their correlations. Additionally, principal component analysis (PCA) was used to establish if all of the properties must be measured and to determine the key properties that can be used as proxies for the other variables. Radial growth-related and physical properties were measured with an X-ray densitometer, while anatomical properties were measured with a Fiber Quality Analyzer. Fifteen wood properties (tracheid length (TL) and diameter (TD), earlywood tracheid length (ETL) and diameter (ETD), latewood tracheid length (LTL) and diameter (LTD), ring width (RW), ring area (RA), earlywood width (EWW), latewood width (LWW), latewood proportion (LWP), ring density (RD), intra-ring density variation, earlywood density (EWD), and latewood density (LWD)) were assessed. Relationships were evaluated at intra-ring and inter-ring levels in the juvenile wood (JW) and mature wood (MW) zones. Except for a few cases when mature tracheid diameter (TD) was involved, all intra-ring anatomical properties were highly and significantly correlated. Radial growth properties were correlated, with stronger relationships in MW compared to JW. Physical properties were often positively and significantly correlated in both JW and MW. A higher earlywood density coupled with a lower latewood density favored wood uniformity, i.e., the homogeneity of ring density within a growth ring. Managing plantations to suppress trees growth during JW formation, and enhancing radial growth when MW formation starts will favor overall wood quality. In order, RW-EWW-RA, TL-ETL-LTL, and RD-EWD-LWP are the three clusters that appeared in the three wood zones, the whole pith-to-bark radial section, the juvenile wood zone, and the mature wood zone.
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Variation in Wood Quality in White Spruce (Picea Glauca (Moench) Voss). Part I. Defining the Juvenile–Mature Wood Transition Based on Tracheid Length

Variation in Wood Quality in White Spruce (Picea Glauca (Moench) Voss). Part I. Defining the Juvenile–Mature Wood Transition Based on Tracheid Length

Tel.: +1-819-762-0971 (ext. 2863); Fax: +1-819-797-4727. Academic Editors: Phillip G. Comeau and Bill Mason Received: 8 November 2014 / Accepted: 19 December 2014 / Published: 8 January 2015 Abstract: Estimations of transition age (TA) and juvenile wood proportion (JWP) are important for wood industries due to their impact on end-product quality. However, the relationships between analytical determination of TA based on tracheid length (TL) and recognized thresholds for adequate end products have not yet been established. In this study, we used three different statistical models to estimate TA in white spruce (Picea glauca (Moench) Voss) based on TL radial variation. We compared the results with technological maturity. A two-millimeter threshold, previously suggested for good paper tear strength, was used. Tracheid length increased from pith to bark and from breast height to upper height. Juvenile wood (JW) was conical with the three models. At breast height, TA ranged from 11 to 27 years and JWP ranged from 15.3% to 47.5% across the three models. The linear mixed
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Étude et modélisation de la variation de la qualité du bois basées sur les propriétés anatomiques, physiques et la croissance du bois chez l’épinette blanche (Picea Glauca (Moench) Voss) et le pin gris (Pinus Banksiana Lamb)

Étude et modélisation de la variation de la qualité du bois basées sur les propriétés anatomiques, physiques et la croissance du bois chez l’épinette blanche (Picea Glauca (Moench) Voss) et le pin gris (Pinus Banksiana Lamb)

3.1 Intra-ring and inter-ring radial variations of growth-related, physical, and anatomical wood properties in white spruce (Picea glauca): a- Ring width (RW), earlywood width (EW), [r]

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Spatially explicit modeling of PAR transmission and growth of Picea glauca and Abies balsamea in the boreal forests of Alberta and Quebec

Spatially explicit modeling of PAR transmission and growth of Picea glauca and Abies balsamea in the boreal forests of Alberta and Quebec

Abstract: To investigate the feasibility of a spatially explicit, radiation-based regeneration model for the boreal forest, we tested the predictions of a three-dimensional simulator of photosynthetically active radiation transmission (%PAR), MIXLIGHT, and the growth response of understory Abies balsamea (L.) Mill. (balsam fir) and Picea glauca (Moench) Voss (white spruce) to %PAR in two large (>1 ha) mixed-species forest sites, one in eastern Canada at Lac Duparquet, Quebec, and one in western Canada at Calling Lake, Alberta. Overstory tree locations and dimensions were obtained from aerial photographs or ground measurements and allometric relationships. Seasonal %PAR calculated by MIXLIGHT for the Calling Lake site was very similar to seasonal %PAR measured by quantum sensors (n = 5, %PAR range = 15%–33%, r = 0.93). Daily measurements of %PAR were also predicted well by simulations at both sites (n = 34–36, %PAR range = 1%–45%, r ≥ 0.76). Functional relationships, designed to saturate at the maximum height growth poten- tial of these sites, were developed to predict sapling height growth from simulated seasonal %PAR and initial height (R 2 ≥ 0.74). These results demonstrate the potential of the MIXLIGHT simulator for estimating PAR at microsites
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Identification des zones pour l'établissement de plantations d'épinette blanche (Picea glauca) améliorée dans la réserve faunique du Saint-Maurice, QC

Identification des zones pour l'établissement de plantations d'épinette blanche (Picea glauca) améliorée dans la réserve faunique du Saint-Maurice, QC

iii ABSTRACT White spruce (Picea glauca (Moench) Voss) is one of the most important species for reforestation in Canada. Given its importance for Canada’s forest industry, white spruce is therefore the object of important genetic improvement programs in most provinces. To optimize the use of genetically improved spruce trees, better identification of reforestation sites would be desirable. To identify those sites, data from plantation inventories carried out by the government of Quebec were used, along with climatic, topographic, edaphic, and hydrological variables, to determine which variables best predicted site index. Three models were tested, namely the “general” model, which used data derived from the current mapping at a scale of 1 / 20,000 for the entire forest territory of Quebec, a model “simplified” that use the ecoforestry map information and the location of inventory plots and the “LiDAR” model, which used information from digital elevation models generated with LiDAR data for the area in Quebec with available information. Even if the predictive accuracy of the general model is low, it is slightly better than previously published studies. A methodology was proposed to generate a productivity map of the Saint-Maurice wildlife reserve. This map, overlapped with the map of plantation constraints, determined that only 0,18% of the total area of the reserve showed areas of high productivity (Site index > 12 m) without plantation constraints. However, the majority of the areas of the reserve (59,85%) still offer areas with good productivity (Site index of 8 to 12 m) and no constraints for planting.
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Insect herbivory (Choristoneura fumiferana, Tortricidea) underlies tree population structure (Picea glauca, Pinaceae)

Insect herbivory (Choristoneura fumiferana, Tortricidea) underlies tree population structure (Picea glauca, Pinaceae)

Geneviève J. Parent 1,2,3 , Isabelle Giguère 1,2 , Gaby Germanos 1,2 , Mebarek Lamara 1,2 , Éric Bauce 1 & John J. MacKay 1,2,3 Variation in insect herbivory can lead to population structure in plant hosts as indicated by defence traits. In annual herbaceous, defence traits may vary between geographic areas but evidence of such patterns is lacking for long-lived species. This may result from the variety of selection pressures from herbivores, long distance gene flow, genome properties, and lack of research. We investigated the antagonistic interaction between white spruce (Picea glauca) and spruce budworm (SBW, Choristoneura fumiferana) the most devastating forest insect of eastern North America in common garden experiments. White spruces that are able to resist SBW attack were reported to accumulate the acetophenones piceol and pungenol constitutively in their foliage. We show that levels of these acetophenones and transcripts of the gene responsible for their release is highly heritable and that their accumulation is synchronized with the most devastating stage of SBW. Piceol and pungenol concentrations negatively correlate with rate of development in female SBW and follow a non- random geographic variation pattern that is partially explained by historical damage from SBW and temperature. Our results show that accumulation of acetophenones is an efficient resistance mechanism against SBW in white spruce and that insects can affect population structure of a long-lived plant.
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Molecular events of apical bud formation in white spruce, Picea glauca

Molecular events of apical bud formation in white spruce, Picea glauca

https://doi.org/10.1111/j.1365-3040.2010.02257.x Access and use of this website and the material on it are subject to the Terms and Conditions set forth at Molecular events of apical bud formation in white spruce, Picea glauca El Kayal, Walid; Allen, Carmen C. G.; Ju, Chelsea J.-T.; Adams, Eri; King- Jones, Susanne; Zaharia, L. Irina; Abrams, Suzanne R.; Cooke, Janice E. K.

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Copy number variations in the gene space of Picea glauca

Copy number variations in the gene space of Picea glauca

26 limitées pour plusieurs espèces. Pour les plantes, les caractéristiques clés des VNCs sont peu connues en particulier le taux auquel elles sont générées. Dans ce travail, on a développé une approche pour l’identification des VNCs géniques chez le conifère arborescent Picea glauca, une espèce qui possède un génome large et complexe et un temps de génération long. On a utilisé des données brutes de puces de génotypage obtenues pour 3663 individus appartenant à 55 familles bi-parentales pour détecter des VNCs dans l’espace génique et estimer leur taux de mutation à travers le génome. Nos résultats montrent que les VNCs affectent une petite proportion de l’espace génique et sont majoritairement des pertes de nombre de copies. Les VNCs identifiées chez les descendants ont été soit héritées des parents ou générées via des évènements de novo. Les estimés du taux de mutation du NC couvrent au moins trois ordres de grandeur, peuvent atteindre des niveaux élevés et varient pour différents gènes, allèles et classes de VNCs. L’analyse du spectre des taux de mutation a permis d’identifier des corrélations entre le taux de mutation et le niveau d’expression des gènes et la relation entre µ et l’expression des gènes est mieux expliquée dans le cadre de l’hypothèse de barrière par la dérive génétique. Cette étude montre que les mutations de novo non seulement génèrent fréquemment de nouveaux polymorphismes de nombre de copies chez les arbres, mais peuvent aussi contribuer comme force évolutive dirigeante déterminant la destinée des allèles.
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Relations allométriques de l'épinette noire (Picea mariana (Mill.) B.S.P.) et de l'épinette blanche (Picea glauca (Moench) Voss)

Relations allométriques de l'épinette noire (Picea mariana (Mill.) B.S.P.) et de l'épinette blanche (Picea glauca (Moench) Voss)

Article publié dans la Revue canadienne de recherche forestière.. Malgré l'importance de ces deux espèces au sein de la forêt boréale canadienne et malgré l' importance d[r]

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L'effet du couvert et du lit de germination sur la germination et la survie du sapin baumier (abies balsamea (L.) Mill.) de l'épinette blanche (picea glauca (moench) voss.) et du thuya (thuja occidentalis L.) au sud de la forêt boréale

L'effet du couvert et du lit de germination sur la germination et la survie du sapin baumier (abies balsamea (L.) Mill.) de l'épinette blanche (picea glauca (moench) voss.) et du thuya (thuja occidentalis L.) au sud de la forêt boréale

Pourcentage de germination moyen des graines viables semées par traitement dans le boisé des sites résineux (R), mixte (M) et feuillu (F).. Les moyennes surmontées de lettres ident[r]

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Caractéristiques morpho-physiologiques des familles biparentales d'épinette blanche (Picea glauca (MOENCH) Voss) en réponse aux changements climatiques : cas de l'augmentation de la température et de la concentration en CO₂ et de leur interaction

Caractéristiques morpho-physiologiques des familles biparentales d'épinette blanche (Picea glauca (MOENCH) Voss) en réponse aux changements climatiques : cas de l'augmentation de la température et de la concentration en CO₂ et de leur interaction

28 significativement par les traitements d’augmentation de la température. Suite à une augmentation de la température de 4,8 ºC au-dessus de la température ambiante, Tjoelker (1997) a observé une augmentation de 63 % en hauteur, 29 % en diamètre et 57 % de la biomasse totale pour des plants de Picea abies de 1 an. Les résultats d’une autre étude sur des plants de 1 an de Fagus sylvatica ont montré une augmentation de 10 % en hauteur et de 12 % de la biomasse totale suite à l’élévation de la température de 2,3 ºC, alors qu’une température de 4,8 ºC au-dessus de la température ambiante a résulté en une diminution de la biomasse totale de 23 %, sans aucun effet significatif sur le diamètre dans les deux cas (Bruhn 1998 cité par Saxe et al. 2001). D’autre part, certaines études ont montré que l’exposition à des températures élevées avait tendance à diminuer la production de cire cuticulaire (Cape et Percy 1993), mais à favoriser la production de cire en amas plutôt qu’une distribution uniforme à la surface des aiguilles des plants de Picea sitchensis (Bong.) Carr produits en conditions contrôlées (Jeffree et al. 1976). Finalement, les résultats d’une étude de Man et Lu (2010) ont mis en évidence que des températures plus élevées pendant le débourrement de plants d’épinette blanche, consistant en une augmentation entre 5 et 10 C par rapport au témoin, diminuaient significativement le temps nécessaire à l’ouverture des bourgeons. Ainsi, on observe que la réponse des plants soumis à une augmentation de la température est dépendante, notamment, de l’espèce, de la température optimale pour sa croissance, ainsi que du degré d’augmentation de la température (Saxe et al. 2001).
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Scaling MoE and MoR measurements for white spruce (Picea glauca) from mini-clear samples to full length lumber and relating the results to tree-level variables

Scaling MoE and MoR measurements for white spruce (Picea glauca) from mini-clear samples to full length lumber and relating the results to tree-level variables

Clear wood samples describe the mechanical properties at a smaller scale with fewer defects and more homogenous wood (Auty and Achim 2008, Schneider et al. So-called [r]

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Effet des coupes partielles sur la largeur des cernes, la masse volumique du bois et les propriétés anatomiques des trachéides de l’épinette blanche (picea glauca [moench] voss) dans un peuplement mixte

Effet des coupes partielles sur la largeur des cernes, la masse volumique du bois et les propriétés anatomiques des trachéides de l’épinette blanche (picea glauca [moench] voss) dans un peuplement mixte

Tableau 4.3 V ale urs moyennes ajustées plus ou moins 1 'écart type de 1' épaisseur des parois cellulaires (ÉPC), de largeur de bois final et de la masse volumique du cerne en fon[r]

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Sprucing up eastern Canadian mixedwoods : does white spruce (Picea glauca) respond to partial harvesting?

Sprucing up eastern Canadian mixedwoods : does white spruce (Picea glauca) respond to partial harvesting?

Moreover , the influ ence of ti m e since treatment, tree social status (dom inant, co-dominant or suppressed), pre-treatment growth rate and neighbourhood competition [r]

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Effet des coupes partielles sur la largeur des cernes, la masse volumique du bois et les propriétés anatomiques des trachéides de l'épinette blanche (Picea glauca [Moench] Voss) dans un peuplement mixte

Effet des coupes partielles sur la largeur des cernes, la masse volumique du bois et les propriétés anatomiques des trachéides de l'épinette blanche (Picea glauca [Moench] Voss) dans un peuplement mixte

4.3 Valeurs moyennes ajustées plus ou moins l'écat1 type de l'épaisseur des parois cellulaires (ÉPC), de largeur de bois final et de la masse volumique du cerne de l' épi[r]

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Caractérisation d’un gène de résistance contre la tordeuse des bourgeons de l’épinette (Choristoneura fumiferana) chez l’épinette blanche (Picea glauca (Voss) Moench)

Caractérisation d’un gène de résistance contre la tordeuse des bourgeons de l’épinette (Choristoneura fumiferana) chez l’épinette blanche (Picea glauca (Voss) Moench)

25 Materials and methods Plant material sampling and preparation Progeny of seven resistant (R) and six non-resistant trees (N-R) were obtained by growing plants from open-pollinated seeds that were collected in September 2011 (120 to 200 seeds per tree), cleaned and stored at -20° C. Seeds were germinated and plants (seedlings) grown in standard conditions for P. glauca: high density polyethylene 110 ml pots, a standard potting mix of peat, perlite and vermiculite (60%, 20%, 20%, respectively) and fertilized weekly with 20/20/20. The plants were grown in a plastic greenhouse from June 2012 to April 2013, which represents an extended growth period. Half of them were then placed in cooled growth rooms for hardening off and put through a rest period of 13 weeks while the others were kept in growing condition in 1,7L pots. The seedlings were taken out of the growth rooms then transferred to 1.7 L pots in July 2013 and placed in an open end plastic house for growth.
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Modular organization of the white spruce (Picea glauca) transcriptome reveals functional organization and evolutionary signatures

Modular organization of the white spruce (Picea glauca) transcriptome reveals functional organization and evolutionary signatures

Functional annotation analysis The cDNA sequences from which the oligonucleotide probes were designed (Raherison et al., 2012) were annotated against the A. thaliana protein data set (The Arabidopsis Information Resource 10) using BLASTX (E-value < 10 10 ). Functional classes presented in Table S2 were developed as follows: first, we identified and clustered enriched biological process gene ontology (GO) terms using the Database for Annotation, Visuali- zation and Integrated Discovery (DAVID; enrichment at P-value < 0.05; Huang et al., 2009); second, enriched GO terms were classified into functional categories of plant GO slim using CATE GO RIZER (Hu et al., 2008); and finally, based on the GO term itself, its cluster and its functional category, each GO term was manually assigned to a consensus functional class. Six sequences that we analysed represented P. glauca MYB proteins. These sequences were named in this report: BT112255, PgMYB29; BT117714, PgMYB30; BT119291, PgMYB31; DR571012, PgMYB32; BT108182, PgMYB33; and BT106711, PgMYB34.
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