Congressi Nazionali SISEF

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Presentazione orale

Ludovisi R, Fabbrini F, Harfouche A, Gaudet M, Scarascia Mugnozza G, Sabatti M

Estimation of aboveground biomass production in a full-sib family of black poplar (Populus nigra L.) using multiple regression linear model

Riassunto: The estimation of qualitative and quantitative above-ground biomass production is a primary aspect involved in the assessment of short rotation forestry plantations. Actually, the multiple regression linear model is one of the most utilized models for the quantification of the aboveground biomass A family of black poplar (Populus nigra) grown in four contrasting sites across Italy was examined for the estimation of biomass production. The purposes of this study were both methodological and biological: (i) to look at the phenotypic and genetic variation available in the different environments in terms of aboveground biomass production; (ii) to estimate the influence of the genetic background and of the environmental conditions on the relationships between biomass and its predictors; (iii) to determine whether one predictor is sufficient to accurately predict tree biomass and whether the use of predictive equations could be standardized among contrasting environments. The regression equations that link the aboveground biomass (stem, branch and total dry mass) with circumference, height and number of sylleptic branches were developed for each site. A statistical software was used to find the best equation, on the basis of the coefficient of determination R2, that allows to estimate the biomass production at genotypic level. The obtained results showed that the circumference is the best predictor of biomass estimation and, sometimes the height and number of sylleptic branches are useful measures to increase the precision of the linear model. The analysis of covariance (ANCOVA) was used to verify the hypothesis of the use of only one effective equation for the estimation of the biomass production of the four sites. The results showed that it is not possible to use a single equation for all the sites, as they significantly differed for their growth. They will also be used for the study of: genotype × environment interaction (G × E), phenotypic plasticity, and QTLs (Quantitative Trait Loci) mapping associated to biomass determinants, to better understand the genetic basis of biomass production in poplar species.

Parole Chiave: Populus Nigra, Biomass, Multiple Regression Linear Model, Ancova

Citazione: Ludovisi R, Fabbrini F, Harfouche A, Gaudet M, Scarascia Mugnozza G, Sabatti M (2011). Estimation of aboveground biomass production in a full-sib family of black poplar (Populus nigra L.) using multiple regression linear model. In: VIII Congresso Nazionale SISEF “Selvicoltura e conservazione del suolo: la sfida Europea per una gestione territoriale integrata“ (Rende (CS), 04-07 Ottobre 2011), Abstract-book, Contributo #c08.6.2. - [online] URL: https://congressi.sisef.org/?action=paper&id=1426


Dettagli

Congresso VIII Congresso Nazionale SISEF
“Selvicoltura e conservazione del suolo: la sfida Europea per una gestione territoriale integrata”
Rende (CS), 04-07 Ottobre 2011
Collocazione c08.6.2 (#)
Sessione Sessione 06
Moderatore/i Gianfranco Minotta, Maurizio Sabatti
Data Oct 07, 2011
Ora 12:53-12:53
Luogo -
Info Autori
(*): speaker

R Ludovisi
Department for innovation in biological, agro-food and forest systems (DIBAF), University of Tuscia, via S. Camillo de Lellis snc, 01100 Viterbo, Italy.
Italy

F Fabbrini
Department for innovation in biological, agro-food and forest systems (DIBAF), University of Tuscia, via S. Camillo de Lellis snc, 01100 Viterbo, Italy.
Italy

A Harfouche
Department for innovation in biological, agro-food and forest systems (DIBAF), University of Tuscia, via S. Camillo de Lellis snc, 01100 Viterbo, Italy.
Italy

M Gaudet
Department for innovation in biological, agro-food and forest systems (DIBAF), University of Tuscia, via S. Camillo de Lellis snc, 01100 Viterbo, Italy.
Italy

G Scarascia Mugnozza
Department of Agronomy, Forestry and Land use, Agricultural Research Council, Via del Caravita, 00186 Roma, Italy
Italy

M Sabatti
Department for innovation in biological, agro-food and forest systems (DIBAF), University of Tuscia, via S. Camillo de Lellis snc, 01100 Viterbo, Italy.
Italy