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STRUCTURE ANALYSIS AND BIOMASS MODELS FOR PLUM TREE (PRUNUS DOMESTICA L.) IN ECUADOR

Published online by Cambridge University Press:  25 January 2017

B. VELÁZQUEZ-MARTÍ*
Affiliation:
Departamento de Ingeniería Rural y Agroalimentaria, Universitat Politècnica de Valencia, Camino de Vera s/n, 46022, Valencia, Spain
C. CAZCO-LOGROÑO
Affiliation:
Facultad de Ingeniería En Ciencias Agropecuarias y Ambientales, Universidad Técnica del Norte, Avenida 17 de Julio 5-21 y J. M, Córdova, Ibarra, Ecuador
*
§Corresponding author. Email: borvemar@dmta.upv.es

Summary

The development of dendrometric methodologies could allow accurate estimation of variables associated with the crown, such as primary production (fruit and timber) and tree vigor. The aim of this work was to develop a suitable method to estimate woody biomass in plum trees (Prunus domestica L.) in Imbabura, Ecuador by using an adapted dendrometry. Form factors and regression models were defined for branch volume calculation. From this, the distribution of woody biomass in the crown tree was characterized in every stratum. Occupation Factor and regression models were obtained in order to calculate the biomass in the crown tree, which can be used to estimate the CO2 captured in its structure during its development. Regression models for calculation of whole volume of the tree and pruned biomass were directly obtained from crown diameter and crown height with Rajustated2 of 0.74 and 0.81. The average moisture content of green material was 51%, and the average density of dry material was 0.66 ± 0.07 g cm−3. Proximate analysis of plum wood showed at 79.8 ± 9.2% volatiles and 2.1 ± 0.3% ash. Elemental analysis of the wood pointed to 46.5 ± 1.2% C, 6.1 ± 0.5% H, 46.3 ± 1.2% O, 0.6 ± 0.3% N, 0.06 ± 0.02% S and 0.02 ± 0.01% Cl. Cl, S and N contents are lower than the limits established by the standard EN 14691-part 4. With 46% of C, considering the relation 3.67 (44/12) between CO2 and C content, the CO2 sequestrated in the materials is 1.11 Mg m−3 wood material. Such method represents a tool to manage orchard resources and for assessing other parameters, such as raw materials for cultivation, fruit production, CO2 sink and waste materials (residual wood) used for energy or industry.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2017 

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References

REFERENCES

Andersen, H. E., Reutebuch, S. E. and McGaughey, R. J. (2006). A rigorous assessment of tree height messurement obtained using airborne LiDAR and conventional field methods. Canadian Journal of Remote Sensing 32:355366.CrossRefGoogle Scholar
Bessou, C., Basset-Mens, C., Tran, T. and Benoist, A. (2013). LCA applied to perennial cropping systems: A review focused on the farmstage. International Journal Life Cycle Assess 18:340361.CrossRefGoogle Scholar
Deckmyn, G., Evans, S. P. and Randle, T. J. (2006). Refined pipe theory for mechanistic modeling of wood development. Tree Physiology 26:703717.CrossRefGoogle ScholarPubMed
Doruska, D. and Burkhart, H. (1994). Modeling the diameter and locational distribution of branches within the crows of loblolly pine trees in unthinned plantations. Canadian Journal of Forest Research 24:23622376.CrossRefGoogle Scholar
EN 14691-part 4 (2009). Solid biofuels – Fuel Specifications and classes – Wood chips for non-industrial use. 10p.Google Scholar
Estornell, J., Velázquez-Martí, B., López-Cortés, I., Salazar, D. and Fernández-Sarría, A. (2014). Estimation of wood volume and height of olive tree plantations using airborne discrete-return LiDAR data. GIScience & Remote Sensing 51:1729.CrossRefGoogle Scholar
Francis, J. (2000). Estimating biomass and carbon content of saplings in Puerto Rican secondary forests. Caribbean Journal of Science 36:346350.Google Scholar
Garcia-Tejero, F., Durán-Zuazo, V. H., Arriaga, J. and Muriel-Fernández, J. L. (2012). Relationships between trunk and fruit diameter growths under deficit-irrigation programmes in orange trees. Scientia Horticulturae 133:6471.CrossRefGoogle Scholar
Gracia, C., Velázquez-Martí, B. and Estornell, J. (2014). An application of the vehicle routing problem to biomass transportation. Biosystems Engineering 124:4052.CrossRefGoogle Scholar
Maltamo, M., Eerikainen, K., Pitkanen, J., Hyyppa, J. and Vehmas, M. (2004). Estimation of timber volume and stem density based on scanning laser altimetry and expected tree size distribution functions. Remote Sensing of Environment 90:319330.CrossRefGoogle Scholar
Olson, M. E. and Rosell, J. A. (2013). Vessel diameter-stem diameter scaling across woody angiosperms and the ecological causes of xylem vessel diameter variation. New Phytologist 197:12041213.CrossRefGoogle ScholarPubMed
Pérez-Arévalo, J. J., Callejón-Ferre, A. J., Velázquez-Martí, B. and Suárez-Medina, M. D. (2015). Prediction models based on higher heating value from the elemental analysis of neem, mango, avocado, banana, and carob trees in Guayas (Ecuador). Journal of Renewable and Sustainable Energy 7:053122.CrossRefGoogle Scholar
Persson, A., Holmgren, J. and Soderman, U. (2002). Detecting and measuring individual trees using an airborne laser scanner. Photogrammetric Engineering and Remote Sensing 68:925932.Google Scholar
Sajdak, M. and Velázquez-Martí, B. (2012). Estimation of pruned biomass through the adaptation of classic dendrometry on urban forests: case study of Sophora japonica . Renewable Energy 47:188193.CrossRefGoogle Scholar
Sajdak, M., Velázquez-Martí, B., López-Cortés, I., Estornell, J. and Fernández-Sarría, A. (2014). Prediction models for estimating pruned biomass obtained from Platanus hispanica Münchh. used for material surveys in urban forests. Renewable Energy 66:178184.CrossRefGoogle Scholar
Velázquez-Martí, B. and Annevelink, E. (2009). GIS application to define biomass collection points as sources for linear programming of delivery networks. Transactions of ASABE 52:10691078.CrossRefGoogle Scholar
Velázquez-Martí, B., Fernández-González, E., López-Cortes, I. and Salazar-Hernández, D. M. (2011a). Quantification of the residual biomass obtained from pruning of trees in Mediterranean olive groves. Biomass and Bioenergy 35:32083217.CrossRefGoogle Scholar
Velázquez-Martí, B., Fernández-González, E., López-Cortes, I. and Salazar-Hernández, D. M. (2011b). Quantification of the residual biomass obtained from pruning of trees in Mediterranean almond groves. Renewable Energy 36:621626.CrossRefGoogle Scholar
Velázquez-Martí, B., Fernández-González, E., López-Cortes, I. and Salazar-Hernández, D. M. (2011c). Quantification of the residual biomass obtained from pruning of vineyards in Mediterranean area. Biomass and Bioenergy 35:34533464.CrossRefGoogle Scholar
Velázquez-Martí, B., Estornell, J., López-Cortés, I. and Martí-Gavila, J. (2012). Calculation of biomass volume of citrus trees from an adapted dendrometry. Biosystems Engineering 112:285292.CrossRefGoogle Scholar
Velázquez-Martí, B., Fernández-Gonzalez, E., López-Cortés, I. and Callejón-Ferre, A. J. (2013). Prediction and evaluation of biomass obtained from citrus trees pruning. Journal of Food, Agriculture & Environment 11:14851491.Google Scholar
Velázquez-Martí, B., López-Cortés, I. and Salazar, D. M. (2014). Dendrometric analysis of olive trees for wood biomass quantification in Mediterranean orchards. Agroforestry Systems 88:755765.CrossRefGoogle Scholar
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