Comparative wood anatomy within Abietoideae (Pinaceae). Botanical Journal of the Linnean Society. 120(2): 184-196.



Abstract: This study, which includes 51 species and six genera of subfamily Abietoideae (Pinaceae), assesses the systematic significance of the wood structure within this group. In particular, the presence of normal and traumatic resin canals, the ray structure and the axial parenchyma constitute phylogenetically informative features. Comparative wood anatomy of Abietoideae clearly supports the monophyly of the genera Abies-Cedrus-Keteleeria-Nothotsuga-Pseudolarix-Tsuga, all of which have axial parenchyma with nodular transverse end walls in the regions of growth ring boundaries, crystals in the ray parenchyma and pitted horizontal and nodular end walls of ray parenchyma cells. Axial resin canals support a subdivision of the subfamily into two groups: Abies, Cedrus, Pseudolarix and Tsuga, without axial resin canals; and Keteleeria and Nothotsuga, with axial resin canals and a specific arrangement of traumatic axial resin canals.

 

Prediction of standard particleboard mechanical properties utilizing an artificial neural network and subsequent comparison with a multivariate regression model. Investigación Agraria: Sistemas y Recursos Forestales. 17(2): 178-187


Abstract: The physical properties (specific gravity, moisture content, thickness swelling and water absorption) and mechanical properties (internal bond strength, bending strength and modulus of elasticity) were determined on 93 Spanish-manufactured standard particleboards of different thicknesses selected randomly at the end of the production process. The testing methods of the corresponding European standards (EN) were used, except in the case of the thickness swelling and absorption tests, for which the Spanish UNE standard was used. The thickness and the values obtained for the physical properties were entered into an artificial neural network in order to predict the mechanical properties of the board. The fit was compared with the usual multivariate regression models. The use of a neural network made it possible to obtain the values of bending strength, modulus of elasticity and internal bond strength of the boards utilizing the known data, not only of thickness, moisture content and specific gravity, but also of thickness swelling and water absorption. The neural network proposed is much better adapted to the observed values than any of the multivariate regression models obtained.

 

Sorption and thermodynamic properties of juvenile Pinus sylvestris L. wood after 103 years of submersion. Holzforschung. 62(6): 745-751.



Abstract: The hygroscopicity and thermodynamic properties of juvenile Pinus sylvestris L. wood taken from the submerged piles of a bridge built in 1903 over the Jiloca River, in Spain, were compared with the corresponding values of juvenile wood of the same species from recently cut trees. The 35 degrees C and 50 degrees C isotherms were plotted and subsequently fitted using the Guggenheim-Anderson-Boer-Dent method, and the isosteric heat of sorption was obtained through the integration method of the Clausius-Clapeyron equation. The isotherms were compared by means of the hysteresis coefficients. Infrared spectra were recorded to study the chemical modifications, and the crystal structure of the cellulose was studied by X-ray diffractograms. The submersion in water resulted in hemicellulose degradation and a decrease in the crystallinity index and the crystallite length, accompanied by a corresponding increase in the proportion of amorphous zones. Owing to this, the equilibrium moisture contents of the water logged wood are higher than in the recent wood, both in adsorption and in desorption. In terms of the thermodynamic properties, the bond energy is higher in the recent wood than in the water logged wood.

 

Artificial neural networks in wood identification: the case of two Juniperus species from  the Canary Islands. IAWA Journal. 30(1): 87-94.


Abstract: Neural networks are complex mathematical structures inspired on biological neural networks, capable of learning from examples (training group) and extrapolating knowledge to an unknown sample (testing group). The similarity of wood structure in many species, particularly in the case of conifers, means that they cannot be differentiated using traditional methods. The use of neural networks can be an effective tool for identifying similar species with a high percentage of accuracy. This predictive method was used to differentiate Juniperus cedrus and J. phoenicea var. canariensis, both from the Canary Islands. The anatomical features of their wood are so similar that it is not possible to differentiate them using traditional methods. An artificial neural network was used to determine if this method could differentiate the two species with a high degree of probability through the biometry of their anatomy. To achieve the differentiation, a feedforward multilayer percepton network was designed, which attained 98.6% success in the training group and 92.0% success in the testing or unknown group. The proposed neural network is satisfactory for the desired purpose and enables J. cedrus and J. phoenicea var. canariensis to be differentiated with it 92% probability.

 

Bordered pit and ray morphology involvement in elm resistance to Ophiostoma novo-ulmi. Canadian Journal of Forest Research-Revue canadienne de recherche forestière. 39(2): 420-429.



Abstract: The main objective of this study was to identify differential anatomical features between Ulmus pumila L. and Ulmus minor Mill. clones resistant to Dutch elm disease and U. minor clones susceptible to Dutch elm disease, with a focus on the intervascular pits and medullary rays. Resistant elms showed lower mean values than susceptible elms for pit membrane diameter, pit aperture area, pit membrane abundance per vessel-wall area, ray width, and ray tangential area. A principal component analysis of the parameters measured revealed slight differentiation between species but clearly grouped U. minor clones according to their susceptibility group. In comparison with susceptible elms, the pit structure observed in resistant elms may limit passive fungal spread within the sapflow, lower the probability of fungal cells passively reaching pit membranes, and reduce the vulnerability of the xylem to cavitation. Similarly, the ray structure observed in the resistant elms is likely to reduce the amount of easily accessible nutrients available for fungal growth as well as the rate of radial colonization in comparison with susceptible elms. Examination of the principal component loadings suggested that susceptible U. minor clones were mainly characterized by enhanced values of pit membrane abundance per vessel-wall area relative to resistant U. minor trees.

 

Esteban, L.G.

de Palacios, P.


2009

20

Martín, J.A.

Solla, A.

Esteban L.G.

de Palacios, P.

Gil L.


2009

Esteban, L.G.

García Fernández, F.

de Palacios, P.,

Moreno Romero, R.

Navarro, N.


2009

Esteban, L.G.

de Palacios, P.

García Fernández, F.

Guindeo, A.

Conde, M.

Baonza V.


2008

García Fernández, F.

Esteban, L.G.

de Palacios, P.

Guindeo, A.

Navarro, A.

Conde M.


2008

19

18

17

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