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Browsing Scientific papers by Subject "agro-pellets"

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    Chemometric approach for assessing the quality of olive cake pellets
    (Elsevier, 2013-12) Brlek, Tea; Pezo, Lato; Voća, Neven; Krička, Tajana; Vukmirović, Đuro; Čolović, Radmilo; Bodroža Solarov, Marija
    This article investigates the influence of processing parameters (conditioning and binder content), on quality of fuel agro-pellets produced from four olive cultivars (Istarska Bjelica, Buža, Pendolino, Leccino) grown in experimental filed in Croatia (Istria). Physical and chemical properties of pellets have been determined to assess their quality. Low ash and sulphur levels were detected, with elevated nitrogen levels for all samples. Analysis of variance and post-hoc Tukey's HSD test at 95% confidence limit have been utilised to show significant differences between various samples. Low coefficients of variation have been obtained for each applied assay (0.09–2.98%), which confirmed the high accuracy of the measurements. Score analysis and principal component analysis have been used for assessing the effect of process variables and variety of cultivars on final quality of pellets. For PCA modelling, experimental data for physical and chemical properties have been used. Standard score analysis revealed that equally good physical and chemical characteristics of pellets can be obtained with conditioning at 50 °C, but also without conditioning. The use of binders didn't affect the quality of pellets as much.
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    The quality analyses of olive cake fuel pellets – mathematical approach
    (Savez Hemijskih Inženjera Srbije, 2016-01) Brlek, Tea; Pezo, Lato; Voća, Neven; Vukmirović, Đuro; Čolović, Radmilo; Kiš, Darko; Brkljača, Jovana
    This article investigates the effect of processing parameters (conditioning temperature and binder content), on final quality of produced agro-pellets for heat energy generation, obtained from four different olive cultivars using different technological parameters. Technological, physical and chemical properties of pellets (carbon, hydrogen, nitrogen and sulphur content, particle density, abrasion length, moisture, ash content, higher and lower heating values, fixed carbon and volatile matter content) have been determined to assess their quality. The performance of Artificial Neural Network (ANN) was compared with the performance of second order polynomial (SOP) model, as well as with the obtained experimental data in order to develop rapid and accurate mathematical model for prediction of final quality parameters of agro-pellets. SOP model showed high coefficients of determination (r 2 ), between 0.692 and 0.955, while ANN model showed high prediction accuracy with r 2 between 0.544 and 0.994.