THERMAL SCIENCE

International Scientific Journal

Thermal Science - Online First

Ivan Brandić

,

Lato L. Pezo

,

Neven Voća

,

Josip Leto

,

Jona Šurić

,

Anamarija Peter

,

Nikola Bilandžija

online first only

Assessing the properties of Miscanthus x Giganteus under varying levels of ash fertilization treatment and regression neural network insight into calorific value

ABSTRACT
The aim of the study was to investigate the changes in ultimate, proximate analysis and calorific properties of Miscanthus x Giganteus with three types of planting materials (two rhizomes - R1 and R2 - and one seedling - S) and three ash fertiliser treatments (P0, P2, and P5) were included in the study. The research further examined their effects on crop yield, stem height and various chemical properties. The results showed that the maximum yield was obtained with the R1 x P2 plant type, while the minimum yield was recorded with the R2 x P2 plant type. In addition, the greatest average stem height (3.34 m) was recorded for the R2 x P5 plant type. Significant differences were also found in the chemical components between the plant types and treatments. For example, the highest ash content of 2.25% was found in plant type 'S' x P5, while the highest coke content of 14.48 % was found in plant type R1 x P5. The statistical analysis confirmed that planting material and ash fertilisation had significant influence on the physicochemical properties of Miscanthus x Giganteus. This consequently affects the calorific value, with the average higher and lower heating value being 18.32 and 17.04 MJ/kg, respectively. The neural regression network models showed robust predictive performance for the higher (HHV) and lower heating value LHV, with low chi-square values (Χ2) and high coefficients of determination (R2).
KEYWORDS
Miscanthus x Giganteus, fertilisation, energy properties, Artificial Neural Network, modelling
PAPER SUBMITTED: 2023-11-07
PAPER REVISED: 2024-01-02
PAPER ACCEPTED: 2024-01-15
PUBLISHED ONLINE: 2024-03-10
DOI REFERENCE: https://doi.org/10.2298/TSCI231107060B
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Assessing the properties of Miscanthus x Giganteus under varying levels of ash fertilization treatment and regression neural network insight into calorific value