Pruning Biomass Potential in Italy Related to Crop Characteristics, Agricultural Practices and Agro-Climatic Conditions

This work, developed under the EuroPruning Project, aims to look at relations between pruning biomass production and several factors related both to crop species and management. The aim is to find out mathematical relations that allow improvement of the biomass potential assessment. This is generall...

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Main Authors: Luigi Pari, Vincenzo Alfano, Daniel Garcia-Galindo, Alessandro Suardi, Enrico Santangelo
Format: Article
Language:English
Published: MDPI AG 2018-05-01
Series:Energies
Subjects:
Online Access:http://www.mdpi.com/1996-1073/11/6/1365
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spelling doaj-1d3ff971915849c796a58243def60feb2020-11-24T21:08:01ZengMDPI AGEnergies1996-10732018-05-01116136510.3390/en11061365en11061365Pruning Biomass Potential in Italy Related to Crop Characteristics, Agricultural Practices and Agro-Climatic ConditionsLuigi Pari0Vincenzo Alfano1Daniel Garcia-Galindo2Alessandro Suardi3Enrico Santangelo4Consiglio per la ricerca in agricoltura e l’analisi dell’economia agraria (CREA), Centro di ricerca Ingegneria e Trasformazioni agroalimentari, Monterotondo, 00016 Rome, ItalyConsiglio per la ricerca in agricoltura e l’analisi dell’economia agraria (CREA), Centro di ricerca Ingegneria e Trasformazioni agroalimentari, Monterotondo, 00016 Rome, ItalyResearch Centre for Energy Resources and Consumption (CIRCE), 50018 Zaragoza, SpainConsiglio per la ricerca in agricoltura e l’analisi dell’economia agraria (CREA), Centro di ricerca Ingegneria e Trasformazioni agroalimentari, Monterotondo, 00016 Rome, ItalyConsiglio per la ricerca in agricoltura e l’analisi dell’economia agraria (CREA), Centro di ricerca Ingegneria e Trasformazioni agroalimentari, Monterotondo, 00016 Rome, ItalyThis work, developed under the EuroPruning Project, aims to look at relations between pruning biomass production and several factors related both to crop species and management. The aim is to find out mathematical relations that allow improvement of the biomass potential assessment. This is generally calculated using biomass production ratios. These ratios are variable due to the influence of several aspects. On the one hand there are crop characteristics—such as species, cultivar, and age—and on the other, crop management, which is often associated to local habits and conditions such as the training system, planting pattern, density, pruning methods, irrigation and climate. This work has been produced by gathering data from literature reviews and surveying. The subset of Italian records in the EuroPruning database consists of 70 records. Each record contains the biomass production ratio and eight agronomic variables. Additionally, a set of six climatic and agro-climatic groups of variables (in total 28 variables) have been added to each record. Moderate to good correlations have been found, especially with few climatic factors. As a result, two regression models are proposed for the evaluation of the vineyard and olive tree pruning biomass ratios for Italy, and applied to assess pruning biomass potential.http://www.mdpi.com/1996-1073/11/6/1365pruning availabilitybiomass potential assessmentcorrelation analysisregression modelbioenergy
collection DOAJ
language English
format Article
sources DOAJ
author Luigi Pari
Vincenzo Alfano
Daniel Garcia-Galindo
Alessandro Suardi
Enrico Santangelo
spellingShingle Luigi Pari
Vincenzo Alfano
Daniel Garcia-Galindo
Alessandro Suardi
Enrico Santangelo
Pruning Biomass Potential in Italy Related to Crop Characteristics, Agricultural Practices and Agro-Climatic Conditions
Energies
pruning availability
biomass potential assessment
correlation analysis
regression model
bioenergy
author_facet Luigi Pari
Vincenzo Alfano
Daniel Garcia-Galindo
Alessandro Suardi
Enrico Santangelo
author_sort Luigi Pari
title Pruning Biomass Potential in Italy Related to Crop Characteristics, Agricultural Practices and Agro-Climatic Conditions
title_short Pruning Biomass Potential in Italy Related to Crop Characteristics, Agricultural Practices and Agro-Climatic Conditions
title_full Pruning Biomass Potential in Italy Related to Crop Characteristics, Agricultural Practices and Agro-Climatic Conditions
title_fullStr Pruning Biomass Potential in Italy Related to Crop Characteristics, Agricultural Practices and Agro-Climatic Conditions
title_full_unstemmed Pruning Biomass Potential in Italy Related to Crop Characteristics, Agricultural Practices and Agro-Climatic Conditions
title_sort pruning biomass potential in italy related to crop characteristics, agricultural practices and agro-climatic conditions
publisher MDPI AG
series Energies
issn 1996-1073
publishDate 2018-05-01
description This work, developed under the EuroPruning Project, aims to look at relations between pruning biomass production and several factors related both to crop species and management. The aim is to find out mathematical relations that allow improvement of the biomass potential assessment. This is generally calculated using biomass production ratios. These ratios are variable due to the influence of several aspects. On the one hand there are crop characteristics—such as species, cultivar, and age—and on the other, crop management, which is often associated to local habits and conditions such as the training system, planting pattern, density, pruning methods, irrigation and climate. This work has been produced by gathering data from literature reviews and surveying. The subset of Italian records in the EuroPruning database consists of 70 records. Each record contains the biomass production ratio and eight agronomic variables. Additionally, a set of six climatic and agro-climatic groups of variables (in total 28 variables) have been added to each record. Moderate to good correlations have been found, especially with few climatic factors. As a result, two regression models are proposed for the evaluation of the vineyard and olive tree pruning biomass ratios for Italy, and applied to assess pruning biomass potential.
topic pruning availability
biomass potential assessment
correlation analysis
regression model
bioenergy
url http://www.mdpi.com/1996-1073/11/6/1365
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