Calculation of biomass volume of citrus trees from an adapted dendrometry

A methodology and computational algorithms, to calculate volumes and the total biomass contained in citrus trees from an adapted dendrometry were developed. The methodology could be used as a tool to manage resources from the orchards, establishing adequate predictive models for assessing parameters such as income from raw materials for the cultivation, fruit production, CO2 sink, and waste materials (i.e. residual wood) used for energy or industry. Dendrometry has been traditionally applied to forest trees. However, little research has been conducted on fruit trees due to their heterogeneous structure. To develop the process of biomass quantification it was necessary to perform systems of measurement, enabling to determine volumes of the analysed trees. Firstly, form factors and volume functions for the branches were calculated. These volume functions gave 0.97 coefficient of determination from base diameter and length. The relationships between apparent crown volume and actual volume in the crown (i.e. no hollows) of the trees were established, with 0.80 coefficient of determination. Occupation factor and the distribution of biomass in the crown strata were evaluated. These results could be correlated with production and quality of the fruit, with the amount of residual biomass coming from pruning, and with LIDAR data what may produce a simple, quick and accurate way to predict biomass.This research were developed by the project AGL2010-15334 funded by the Ministry of Science and Innovation of Spain funds.Velázquez Martí, B.; Estornell Cremades, J.; López Cortés, I.; Marti Gavila, J. (2012). Calculation of biomass volume of citrus trees from an adapted dendrometry. Biosystems Engineering. 112(4):285-292. https://doi.org/10.1016/j.biosystemseng.2012.04.011S285292112

Estimación de parámetros de estructura de nogales utilizando láser escáner terrestre

[EN] Juglans regia L. (walnut) is a tree of significant economic importance, usually cultivated for its seed used in the food market, and for its wood used in the furniture industry. The aim of this work was to develop regression models to predict crown parameters for walnut trees using a terrestrial laser scanner. A set of 30 trees was selected and the total height, crown height and crown diameter were measured in the field. The trees were also measured by a laser scanner and algorithms were applied to compute the crown volume, crown diameter, total and crown height. Linear regression models were calculated to estimate walnut tree parameters from TLS data. Good results were obtained with values of R2 between 0.90 and 0.98. In addition, to analyze whether coarser point cloud densities might affect the results, the point clouds for all trees were subsampled using different point densities: points every 0.005 m, 0.01 m, 0.05 m, 0.1 m, 0.25 m, 0.5 m, 1 m, and 2 m. New regression models were calculated to estimate field parameters. For total height and crown volume good estimations were obtained from TLS parameters derived for all subsampled point cloud (0.005 m – 2 m).[ES] Juglans regiaL. (nogal) es un árbol de importancia económica por el fruto que proporciona y por su madera utilizada en la industria del mueble. El objetivo de este trabajo fue calcular modelos de regresión para estimar los pa-rámetros altura total, altura, diámetro y volumen de copa de nogales utilizando datos registrados mediante un escáner láser terrestre. Un conjunto de 30 árboles fueron escaneados y se aplicaron algoritmos para calcular los parámetros anteriores, que también se midieron en campo utilizando técnicas tradicionales. Se obtuvieron buenos resultados, con valores de R2 entre 0,90 y 0,98 para todos los parámetros. Además, para analizar la relación entre la densidad de puntos registrada y la precisión en la estimación de los parámetros de los nogales, las nubes de puntos de todos los árboles fueron sub-muestreadas utilizando diferentes distancias de separación entre puntos: 0,005 m, 0,01 m, 0,05 m, 0,1 m, 0,25 m, 0,5 m, 1 m y 2 m. Se calcularon nuevos modelos de regresión con los datos muestreados obteniéndose buenas estimaciones de los parámetros para todos los conjuntos de datos.The authors appreciate the financial support provided by the regional government of Spain (Conselleria d'Educacio, Cultura i Esport Generalitat Valenciana) in the framework of the Project GV/2014/016.Estornell, J.; Velázquez-Martí, A.; Fernández-Sarría, A.; López-Cortés, I.; Martí-Gavilá, J.; Salazar, D. (2017). Estimation of structural attributes of walnut trees based on terrestrial laser scanning. Revista de Teledetección. (48):67-76. https://doi.org/10.4995/raet.2017.7429SWORD677648Belsley. D.A. 1991. Conditioning Diagnostics: Collinearity and Weak Data in Regression. John Wiley & Sons.Chianucci, F., Puletti, N., Giacomello, E., Cutini, A., & Corona, P. (2015). Estimation of leaf area index in isolated trees with digital photography and its application to urban forestry. Urban Forestry & Urban Greening, 14(2), 377-382. doi:10.1016/j.ufug.2015.04.001Corona, P., Agrimi, M., Baffetta, F., Barbati, A., Chiriacò, M. V., Fattorini, L., … Mattioli, W. (2011). Extending large-scale forest inventories to assess urban forests. Environmental Monitoring and Assessment, 184(3), 1409-1422. doi:10.1007/s10661-011-2050-6Fernández-Sarría, A., Martínez, L., Velázquez-Martí, B., Sajdak, M., Estornell, J., & Recio, J. A. (2013). Different methodologies for calculating crown volumes of Platanus hispanica trees using terrestrial laser scanner and a comparison with classical dendrometric measurements. Computers and Electronics in Agriculture, 90, 176-185. doi:10.1016/j.compag.2012.09.017Gil, E., Llorens, J., Llop, J., Fàbregas, X., & Gallart, M. (2013). Use of a Terrestrial LIDAR Sensor for Drift Detection in Vineyard Spraying. Sensors, 13(1), 516-534. doi:10.3390/s130100516Greaves, H. E., Vierling, L. A., Eitel, J. U. H., Boelman, N. T., Magney, T. S., Prager, C. M., & Griffin, K. L. (2015). Estimating aboveground biomass and leaf area of low-stature Arctic shrubs with terrestrial LiDAR. Remote Sensing of Environment, 164, 26-35. doi:10.1016/j.rse.2015.02.023Keightley, K. E., & Bawden, G. W. (2010). 3D volumetric modeling of grapevine biomass using Tripod LiDAR. Computers and Electronics in Agriculture, 74(2), 305-312. doi:10.1016/j.compag.2010.09.005Manes, F., Incerti, G., Salvatori, E., Vitale, M., Ricotta, C., & Costanza, R. (2012). Urban ecosystem services: tree diversity and stability of tropospheric ozone removal. Ecological Applications, 22(1), 349-360. doi:10.1890/11-0561.1MAAM. 2015. Encuesta sobre superficies y rendimientos cultivos (ASYRCE). Encuesta de marco de áreas de Espa-a. Ministerio de Agricultura, Alimentación y Medio Ambiente de Espa-a, 44 pp.Rosell, J. R., Llorens, J., Sanz, R., Arnó, J., Ribes-Dasi, M., Masip, J., … Palacín, J. (2009). Obtaining the three-dimensional structure of tree orchards from remote 2D terrestrial LIDAR scanning. Agricultural and Forest Meteorology, 149(9), 1505-1515. doi:10.1016/j.agrformet.2009.04.008Rosell Polo, J. R., Sanz, R., Llorens, J., Arnó, J., Escolà, A., Ribes-Dasi, M., … Palacín, J. (2009). A tractor-mounted scanning LIDAR for the non-destructive measurement of vegetative volume and surface area of tree-row plantations: A comparison with conventional destructive measurements. Biosystems Engineering, 102(2), 128-134. doi:10.1016/j.biosystemseng.2008.10.009Rosell, J. R., & Sanz, R. (2012). A review of methods and applications of the geometric characterization of tree crops in agricultural activities. Computers and Electronics in Agriculture, 81, 124-141. doi:10.1016/j.compag.2011.09.00

Challenges of the use of new generation massive sequencing (NGS) of the benthic macrofauna for the evaluation of the marine environment quality.

La Directiva Marco del Agua 2000/60/CE obliga al diagnóstico ambiental del ecosistema marino, incluyendo la evaluación de las especies de macroinvertebrados considerados bioindicadores presentes en el medio. Hasta la fecha, este tipo de determinaciones se realizan mediante la identificación taxonómica de visu de la macrofauna bentónica presente en las muestras y el cálculo de bioíndices asociados, un proceso costoso en términos de tiempo y financiación y, en algunos casos, subjetivo por precisar de un equipo humano altamente especializado y por la dificultad de identificar correctamente determinadas especies. En este sentido, las técnicas de DNA barcoding permiten identificar de forma fiable organismos empleando técnicas de secuenciación de DNA y evitando las desventajas de la identificación morfotaxonómica. Por otro lado, el reciente desarrollo de técnicas de secuenciación masiva de DNA de nueva generación (NGS) ha permitido el desarrollo del DNA metabarcoding, o caracterización de poblaciones de organismos presentes en una muestra empleando datos genómicos. Este trabajo plantea los retos fundamentales que presenta, a día de hoy, el análisis de organismos bioindicadores de calidad ambiental marina a través de las técnicas de secuenciación NGS.The Water Framework Directive 2000/60/EC regulates the environmental diagnosis of the marine ecosystem, including the evaluation of species of bioindicator macroinvertebrates present in the environment. To date, these types of determinations are carried out through the morphotaxonomic identification of the benthic macrofauna present in the samples and the calculation of associated biotic indexes, a process that is time-consuming and resource-intensive, being in some cases inaccurate due to the requirement of highly specialized human resources and the difficulty of correctly identifying certain species. In this respect, DNA barcoding techniques allow the reliable identification of organisms using DNA sequencing techniques and avoiding the disadvantages of morphotaxonomic identification. On the other hand, the recent development of New Generation DNA Sequencing techniques (NGS) has allowed the development of DNA metabarcoding, i.e. the characterization of populations of organisms present in a sample using genomic data. This paper shows the fundamental challenges to be overcome in order to establish a NGS sequencing-based assessment of the marine environmental quality.Ciencias Experimentale

Retos del empleo de la secuenciación masiva de nueva generación (NGS) de la macrofauna bentónica para la evaluación de la calidad ambiental marina

The Water Framework Directive 2000/60/EC regulates the environmental diagnosis of the marine ecosystem, including the evaluation of species of bioindicator macroinvertebrates present in the environment. To date, these types of determinations are carried out through the morphotaxonomic identification of the benthic macrofauna present in the samples and the calculation of associated biotic indexes, a process that is time-consuming and resource-intensive, being in some cases inaccurate due to the requirement of highly specialized human resources and the difficulty of correctly identifying certain species. In this respect, DNA barcoding techniques allow the reliable identification of organisms using DNA sequencing techniques and avoiding the disadvantages of morphotaxonomic identification. On the other hand, the recent development of New Generation DNA Sequencing techniques (NGS) has allowed the development of DNA metabarcoding, i.e. the characterization of populations of organisms present in a sample using genomic data. This paper shows the fundamental challenges to be overcome in order to establish a NGS sequencing-based assessment of the marine environmental quality.La Directiva Marco del Agua 2000/60/CE obliga al diagnóstico ambiental del ecosistema marino, incluyendo la evaluación de las especies de macroinvertebrados considerados bioindicadores presentes en el medio. Hasta la fecha, este tipo de determinaciones se realizan mediante la identificación taxonómica de visu de la macrofauna bentónica presente en las muestras y el cálculo de bioíndices asociados, un proceso costoso en términos de tiempo y financiación y, en algunos casos, subjetivo por precisar de un equipo humano altamente especializado y por la dificultad de identificar correctamente determinadas especies. En este sentido, las técnicas de DNA barcoding permiten identificar de forma fiable organismos empleando técnicas de secuenciación de DNA y evitando las desventajas de la identificación morfotaxonómica. Por otro lado, el reciente desarrollo de técnicas de secuenciación masiva de DNA de nueva generación (NGS) ha permitido el desarrollo del DNA metabarcoding, o caracterización de poblaciones de organismos presentes en una muestra empleando datos genómicos. Este trabajo plantea los retos fundamentales que presenta, a día de hoy, el análisis de organismos bioindicadores de calidad ambiental marina a través de las técnicas de secuenciación NGS