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    Item type:Publication,
    The energy potential evaluation of biomass fuel from weed pellets
    (2023-03-01)
    Saechua, W.
    ;
    Posom, J.
    ;
    Hongwiangjan, J.
    ;
    Nakawajana, N.
    The giant sensitive plant had the most appropriated qualifications for pellet production, as it contained a low content of moisture (3.07%) and ash (2.68%), and a high percentage of fixed carbon (14.13%) and volatile matter (80.12%) with the highest lower heating value of 18,334.08 J/g. It was found that a higher mixing ratio of water for pelletization led to increasing moisture and ash content but resulted in lower volatile matter and fixed carbon. The best mixing ratio for was 8% of water by weight, at which the evaluated properties of the giant sensitive plant pellets: LHV, FC, VM and ash content, were 18,747.46 J/g, 10.92%, 78.77% and 2.24%, respectively. The evaluation of the physical properties of the pellets revealed that a higher amount of water resulted in a larger diameter, greater length and higher fines content. Comparison of pellets from this work with the standard classes of biomass pellets found that the giant sensitive plant pellets could be classified in class I3. It was clearly seen that the weed can be utilized as a useful biomass fuel and formed in a pellet shape for combustion in industrial sectors.
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    Evaluation of the moisture content of Jatropha curcas kernels and the heating value of the oil-extracted residue using near-infrared spectroscopy
    (2015-02-01)
    Posom, Jetsada
    ;
    Sirisomboon, Panmanas
    The use of near-infrared spectroscopy for evaluation of moisture content of Jatropha curcas kernels and heating value of its residue after oil extraction were studied. In total, 100 samples of whole kernels from green, yellow and black fruits and oven-dried kernels scanned in diffuse reflection mode using a Fourier transform NIR spectrometer at wave numbers of 1,250,000-400,000m<sup>-1</sup> were used to develop moisture-predicting models. The corresponding residues after the oil extraction of the samples scanned in transflection mode using the same spectrometer and wave number range were used to develop the heating-value-predicting models. The models correlating the spectral data and the corresponding values measured using the reference method were developed by partial least squares regression and were validated using a test set. For the moisture content and heating value, coefficients of determination (R<sup>2</sup>) were 0.969 and 0.860, root mean square errors of prediction (RMSEP) were 4.0%wb and 360Jg<sup>-1</sup>, biases were -0.7%wb and -17Jg<sup>-1</sup> and ratios of prediction to deviation (RPD) were 5.7 and 2.6, respectively. In addition, vibration bands of fibre and cellulose had important effects on the prediction of the heating value.