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.

Anaerobic codigestion of olive mill wastewater for renewable energy production constitutes a promising process to overcome management and environmental issues due to their conventional disposal. The present study aims at assessing biogas and biomethane production from olive mill wastewater by performing biochemical methane potential tests. Hence, mixtures containing 0% (blank), 20% and 30% olive mill wastewater, in volume, were experimented on under mesophilic conditions. In addition, life cycle assessment and life cycle costing were performed for sustainability analysis. Particularly, life cycle assessment allowed assessing the potential environmental impact resulting from the tested process, while life cycle costing in conjunction with specific economic indicators allowed performing the economic feasibility analysis. The research highlighted reliable outcomes: higher amounts of biogas (80.22 ± 24.49 NL.kg_SV⁻¹) and methane (47.68 ± 17.55 NL.kg_SV⁻¹) were obtained when implementing a higher amount of olive mill wastewater (30%) (v/v) in the batch reactors. According to life cycle assessment, the biogas ecoprofile was better when using 20% (v/v) olive mill wastewater. Similarly, the economic results demonstrated the profitability of the process, with better performances when using 20% (v/v) olive mill wastewater. These findings confirm the advantages from using farm and food industry by-products for the production of renewable energy as well as organic fertilizers, which could be used in situ to enhance farm sustainability.

The characterization of poplar wood assumes a strategic position to increase the competitiveness of the entire forest wood supply chain. From this aspect, the identification of wood quality represents a primary objective for researchers and private landowners. The quality of wood can be defined via traditional visual methods based on the experience of technicians or using traditional tools, such as incremental drills and sound hammers. The traditional properties of these traits, based only on visual characteristics, can outline a classification based on the macroscopic properties of wood with the aim of defining the volume of recoverable wood. However, this approach does not provide a good indicator of the physical or mechanical properties of wood. Mechanical tests of wood require the felling of trees with the correlated preparation of the specimens. A different solution to determine wood quality is based on the application of non-destructive technology (NDT). In this context, the aim of the present study was to determine the predictive accuracy of non-destructive analysis of the MOEd in standing trees and logs of a 22-year-old poplar clone and to examine the relationship with MOEs in sawn specimens. This relationship was also studied at three different stem heights. We non-destructively measured poplar trees and green logs using TreeSonic and Resonance Log Grader and compared the results with those obtained via a destructive method using a universal testing machine. The results showed that for clone I-214 poplar trees, the dynamic elastic moduli of standing trees and logs were validly correlated with the static elastic modulus. These results suggest that it is possible to evaluate the mechanical properties of poplar wood directly from standing trees using non-destructive techniques (NDT) and that this tool can be easily used to presort material in the forest.