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Article . 2013 . Peer-reviewed
License: Elsevier TDM
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Statistical evaluation of quality parameters of olive stone to predict its heating value

Authors: Mata, Jesús; Pérez, José A.; Díaz Villanueva, Manuel Jesús; Serrano, Antonio; Núñez, Nieves; López-Giménez, Francisco J.;

Statistical evaluation of quality parameters of olive stone to predict its heating value

Abstract

In Andalusia, residual biomass produced in the olive sector results from the large amount of olive groves and olive oil manufacturers that generate byproducts with a potentially high energy content, suitable for thermal and electrical energy production. The main residue, olive stone, is an important solid biofuel and is widely generated and consumed. Consequently, olive stone quality parameters must be studied in order to achieve an optimum energetic efficiency. Therefore, the main objective of this study is to describe olive stone energetic properties and to evaluate variability of these parameters before consumption. For this purpose, mean values, normal distributions, intervals and deviations of these parameters have been obtained and studied. Concerning to statistical results, climate and geographical variability of quality parameters has been described. Furthermore, variations between olive stone physicochemical parameters supplied by both olive oil factories and distribution companies have been calculated. Finally, a correlation between the ultimate analysis and higher heating values (HHV) of olive stone has been determined. Results obtained show that olive stone pretreatments developed by distribution companies have a significant effect on quality parameters such as moisture content and low heating value. Moreover, olive stone properties dependence on factors such as rainfall or soil type has not been confirmed. Lastly, the calculated correlation based on ultimate analysis (i.e. HHV(MJ/ kg) = 0.401C - 0.164H + 0.493N + 2.381S + 0.791) has been developed and validated with olive stone samples with HHV range from 20 to 21 MJ/kg (dry weight). Correlation has a mean absolute error (MAE) of 0.43% and a mean bias error (MBE) of -0.12% which indicate that it can be successfully used as a more economical and faster tool to accurately estimate olive stone HHV. The HHV prediction accuracies of 14 other correlations introduced by other researchers are also compared in this study.

Countries
Morocco, Spain
Keywords

Higher heating value (HHV), Solid biofuels, Ultimate analysis, Proximate analysis, Olive residues

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    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
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    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
40
Top 10%
Top 10%
Top 10%
Green