Torrefaction is one of the methods of thermal treatment of biomass, which allows obtaining a product of better quality in the form of biochar. The aim of the paper was to analyze the possibility of using goldenrod (Solidago canadensis, Solidago gigantea) for the production of biochar. The torrefaction process involved the vegetative and generative parts as well as the whole plant at temperatures of 250 °C and 275 °C, for 3 h. Next, the physicochemical properties of the raw material and biochar were determined, namely moisture content, ash content, volatile matter content, calorific value, and heat of combustion. The bulk density of raw biomass and biochar was also determined. It was found that after biomass torrefaction, the ash content, calorific value, and heat of combustion increased, while volatile matter content decreased. It has been observed that in both the case of raw biomass and biochar, the plant species and the sampled parts have a significant impact on the ash content, volatile matter content, calorific value, and heat of combustion.

So far, there are no results for research on the biomechanical parameters of giant miscanthus stalks taking into account both the influence of moisture content and the internode, from which the samples were taken. Therefore, the aim of the research was to comprehensively investigate the influence of the internode number (NrNod) and water content (MC) on the values of selected biomechanical parameters (modulus of elasticity and maximum stress) determined using various stress tests (three-point bending and compression along the fibers). The research was carried out for dry stalks of different humidities and for different internodes. The results obtained in this study proved that the independent variables of the water content and the internode number cause a statistically significant influence on the values of the examined biomechanical parameters of the miscanthus stem: the modulus of elasticity in compression, the maximum stress in compression, the modulus of elasticity in bending and the maximum stress in bending. The values of the modulus of elasticity (MOE) increase when increasing the NrNod. For individual internodes, MOE values are higher with a higher MC. The values of the maximum stress (σ) also increase when increasing the internode number. For individual internodes, the σ values are lower with a higher MC.

The aim of this paper is to develop neural models enabling the determination of biomechanical parameters for giant miscanthus stems. The static three-point bending test is used to determine the bending strength parameters of the miscanthus stem. In this study, we assume the modulus of elasticity bending and maximum stress in bending as the dependent variables. As independent variables (inputs of the neural network) we assume water content, internode number, maximum bending force value and dimensions characterizing the cross-section of miscanthus stem: maximum and minimum stem diameter and stem wall thickness. The four developed neural models, enabling the determination of the value of the modulus of elasticity in bending and the maximum stress in bending, demonstrate sufficient and even very high accuracy. The neural networks have an average relative error of 2.18%, 2.21%, 3.24% and 0.18% for all data subsets, respectively. The results of the sensitivity analysis confirmed that all input variables are important for the accuracy of the developed neural models—correct semantic models.