In a world facing increasing environmental and energy challenges, anaerobic digestion of agrifood by-products and food waste could contribute to the production of green energy while reducing greenhouse gas emissions into the atmosphere. Anaerobic digestion is a biological process capable of breaking down and stabilising organic matter in the absence of oxygen and converting it into a renewable source of energy, known as biogas. Biomethane production also enables the generation of electricity and produces digestate, a by-product of the digestion process that can be used as a soil conditioner or fertiliser. This review aims to highlight how substrate pretreatment, together with the optimisation of operating parameters, application of additives, recirculation of digestate and frequent feeding, can increase biogas production. An overview of the basics of the anaerobic digestion of agrifood by-products and food waste is provided, including feedstock characteristics (nutrient content, particle size and inhibitory compounds) and process parameters (process configuration, pH, temperature, total and volatile solids, total Kjeldahl nitrogen, ammonium, chemical oxygen demand, carbon/nitrogen ratio, retention time, organic loading rate, etc.). In addition, recent studies in the field of processes, equipment and pretreatments that can significantly improve the anaerobic digestion process of agricultural and food wastes were classified and discussed. Finally, the challenges and future perspectives of biogas production from the agrifood sector are addressed.

Forests in southern Italy are mainly located in mountainous areas, where ground-based extraction is still the most common harvesting technique. In particular, 60% of southern Italy’s forests are on slopes with an angle of inclination between 20–60%. The low level of mechanization in forest operations is due to the difficult site conditions, as well as the small-scale characteristics of both the forest owners and the harvesting contractors. The most common work method uses chainsaws to fell the trees, and animals or farm tractors equipped with winches for bunching and extraction. This study assesses the productivity and cost effectiveness of extraction with a purpose-built John Deere 548H skidder, including a comparison of winch and grapple configurations. The results show that the productivity of skidding depends on distance as well as the condition of the skid trail. The number of trees per cycle and volume of each load also had a clear effect. While large purpose-built skidders represent a significant investment, this study demonstrates that the productivity is very high compared to traditional extraction methods and the resulting extraction costs are very competitive. As such, this study indicates that, over time, southern Italian harvesting operations should invest in purpose-built harvesting systems.

In the middle of XIX century, Calabrian pine was planted in southern Italy to increase the forest cover in mountainous areas. Many of these forest stands were never managed, since they were considered non-profitable for wood production. Therefore, in order to promote timber value, it is fundamental to study, more deeply, the characteristics and management options for this species. The acoustic technologies applied to predict the mechanical and physical properties of timber are well-established practices in forest research. In this study, we hypothesized that the tree stand density could influence the dynamic modulus of elasticity (MOEd) and, therefore, the future wood quality. We specifically aimed to verify if different management options, when applied, could influence the timber quality of Calabrian pine growing in similar environmental conditions. The study was conducted in the Aspromonte National Park (Calabria, Southern Italy). We derived the MOEd values from data obtained by the acoustic velocity measured through the TreeSonic™ timer. Calabrian pine trees were selected in stands where different intensities of thinning were applied eleven years before this study began (no thinning, thinning 25%, thinning 50%, and thinning 75%). The percentage refers to the number of trees cut with respect to the total number of occurring trees. The analyses were conducted on a total of 804 trees (201 trees for each intensity of thinning). A strong positive correlation was observed between the acoustic velocity, the thinning treatments and diameter at breast height (DBH). The thinning realized at 25% induced better tree wood quality. We also analyzed the best predictors for MOEd estimation, using variables easily measurable in the field, such as tree diameter, tree height, or their transformations (number of trees per hectare, basal area per hectare). We provide, here, a useful tool for predicting the wood stiffness in relation to stand parameters easily measurable in forest inventories.

Mixed-species forests may deliver more forest functions and services than monocultures, as being considered more resistant to disturbances than pure stands. However, information on wood quality in mixed-species vs. corresponding pure forests is poor. In this study, nine plots grouped into three triplets of pure and mixed-species stands of European beech and Calabrian pine (three dominated by European beech, three dominated by Calabrian pine, and three mixed-species plots) were analysed. We evaluated tree growth and wood quality through dendrochronological approaches and non-destructive technologies (acoustic detection), respectively, hypothesizing that the mixture might improve the fitness of each species and its wood quality. A linear mixed model was applied to test the effects of exogenous influences on the basal area index (BAI) and the dynamic modulus of elasticity (MOEd). The recruitment period (Rp) was studied to verify whether wood quality was independent from stem radial growth patterns. Results showed that the mixture effect influenced both wood quality and BAI. In the mixed-species plots, for each species, MOEd values were significantly higher than in the corresponding pure stands. The mixture effect aligned MOEd values, making wood quality uniform across the different diameter classes. In the mixed-species plots, a significant positive relationship between MOEd and Rp, but also significantly higher BAI values than in the pure plots, were found for European beech, but not for Calabrian pine. The results suggest the promotion of mixing of European beech and Calabrian pine in this harsh environment to potentially improve both tree growth and wood quality.

The improvement of harvesting methodologies plays an important role in the optimization of wood production in a context of sustainable forest management. Different harvesting methods can be applied according to forest site-specific condition and the appropriate mechanization level depends on a number of factors. Therefore, efficiency and functionality of wood harvesting operations depend on several factors. The aim of this study is to analyze how the different harvesting processes affect operational costs and labor productivity in typical small-scale Italian harvesting companies. A multiple linear regression model (MLR) and artificial neural network (ANN) have been carried out to predict gross time, productivity and costs estimation in a series of qualitative and quantitative variables. The results have created a correct statistical model able to accurately estimate the technical parameters (work time and productivity) and economic parameters (costs per unit of product and per hectare) useful to the forestry entrepreneur to predict the results of the work in advance, considering only the values detectable of some characteristic elements of the worksite.